Quality of Life and Work in Europe: Theory, Practice and Policy

Theory, Practice and Policy Edited by Margareta Bäck-Wiklund Tanja van der Lippe Laura den Dulk Anneke van Doorne-Huisk...

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Theory, Practice and Policy Edited by

Margareta Bäck-Wiklund Tanja van der Lippe Laura den Dulk Anneke van Doorne-Huiskes

Copyright material from www.palgraveconnect.com - licensed to Universitetsbiblioteket i Tromso - PalgraveConnect - 2011-04-13

Quality of Life and Work in Europe

10.1057/9780230299443 - Quality of Life and Work in Europe, Edited by Margareta Back-Wiklund, Tanja van der Lippe, Laura den Dulk and Anneke Doorne-Huiskes





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Theory, Practice and Policy Edited by

Margareta Bäck-Wiklund University of Gothenburg, Sweden

Tanja van der Lippe Utrecht University, the Netherlands

Laura den Dulk Erasmus University Rotterdam, the Netherlands

Anneke van Doorne-Huiskes Utrecht University, the Netherlands




Selection and editorial matter © M. Bäck-Wiklund, T. van der Lippe, L. den Dulk, A. van Doorne-Huiskes 2011 Individual chapters © their respective authors 2011

No portion of this publication may be reproduced, copied or transmitted save with written permission or in accordance with the provisions of the Copyright, Designs and Patents Act 1988, or under the terms of any licence permitting limited copying issued by the Copyright Licensing Agency, Saffron House, 6-10 Kirby Street, London EC1N 8TS. Any person who does any unauthorized act in relation to this publication may be liable to criminal prosecution and civil claims for damages. The authors have asserted their rights to be identified as the authors of this work in accordance with the Copyright, Designs and Patents Act 1988. First published 2011 by PALGRAVE MACMILLAN Palgrave Macmillan in the UK is an imprint of Macmillan Publishers Limited, registered in England, company number 785998, of Houndmills, Basingstoke, Hampshire RG21 6XS. Palgrave Macmillan in the US is a division of St Martin’s Press LLC, 175 Fifth Avenue, New York, NY 10010. Palgrave Macmillan is the global academic imprint of the above companies and has companies and representatives throughout the world. Palgrave® and Macmillan® are registered trademarks in the United States, the United Kingdom, Europe and other countries. ISBN 978–0–230–23511–3 hardback This book is printed on paper suitable for recycling and made from fully managed and sustained forest sources. Logging, pulping and manufacturing processes are expected to conform to the environmental regulations of the country of origin. A catalogue record for this book is available from the British Library. A catalog record for this book is available from the Library of Congress. 10 9 8 7 6 5 4 3 2 1 20 19 18 17 16 15 14 13 12 11 Printed and bound in Great Britain by CPI Antony Rowe, Chippenham and Eastbourne


All rights reserved. No reproduction, copy or transmission of this publication may be made without written permission.


List of Tables and Figures

vii

Acknowledgements

x

Contributors

xi

1 Quality of Life and Work in a Changing Europe Tanja van der Lippe and Margareta Bäck-Wiklund

1

Part I Context, Theory and Methods 2 Quality of Life and Work in a Changing Europe: A Theoretical Framework Laura den Dulk, Margareta Bäck-Wiklund, Suzan Lewis and Dorottya Redai

17

3 The Institutional Context of the Quality of Life Siyka Kovacheva, Anneke van Doorne-Huiskes and Timo Anttila

32

4 Data and Methods Tanja van der Lippe, Stefan Szücs, Sonja Drobniˇc and Leila Billquist

55

Part II Empirical Results 5 Quality of Work and Quality of Life of Service Sector Workers: Cross-national Variations in Eight European Countries Patrick Präg, Maria das Dores Guerreiro, Jouko Nätti, Michael Brookes and Laura den Dulk 6 Quality of Life and Satisfaction with the Work–life Balance Stefan Szücs, Sonja Drobniˇc, Laura den Dulk and Roland Verwiebe 7 Variations in Work–life Balance Satisfaction among Service Sector Employees Barbara Beham, David Etherington and Eduardo Rodrigues

77

95


Contents

118

v


8 Competing Demands: Work and Child Well-being Linda Lane, Tanja van der Lippe, Stanimir Kabaivanov and Margareta Bäck-Wiklund

135

9 Gender Differences in Quality of Life Eva Fodor, Linda Lane, Joop Schippers and Tanja van der Lippe

149

Part III Policy Implications and the Future Research Agenda 10 Healthy Organizations Suzan Lewis, Anneke van Doorne-Huiskes, Dorottya Redai and Margarida Barroso 11 Scenarios for the Quality of Life in the Europe of the Future Maria das Dores Guerreiro, Annabelle Mark, Leila Billquist and Polina Manolova

165

186

12 The Social Quality Instrument: Measuring the Social Quality of Work in European Workplaces Sakari Taipale, Barbara Beham and Jouko Nätti

206

13 Quality of Life and Work in a Changing Europe: Future Challenges Anneke van Doorne-Huiskes and Laura den Dulk

217

Bibliography

233

Index

252


vi Contents


Tables 3.1 3.2 3.3 4.1 4.2 4.3 5.1 5.2 5.3 5.4 6.1

6.2

6.3

6.4 7.1 7.2 7.3 7.4

Country-specific features of employment policies Statutory leave arrangements for parents in January 2009 Institutional context for integrating work and family life Sample size and response rate Variables used in the analysis (Means) Case study organizations and number of interviews in each Public hospitals, workforce characteristics and organizational change at the time of the study Bank/insurance companies, workforce characteristics and organizational change at the time of the study IT and telecom companies, workforce characteristics and organizational change at the time of the study Retail companies, workforce characteristics and organizational change at the time of the study Satisfaction with work–life balance: Items and the SWLB scale (per cent ‘very satisfied’ or ‘satisfied’ and scale means) Satisfaction with life: Items and the SWLS scale (per cent ‘strongly agree’, ‘agree’ or ‘slightly agree’ and scale means) Least squares regression analysis of satisfaction with work–life balance for men and women (standardized OLS coefficients) Least squares regression analysis of life satisfaction for men and women (standardized OLS coefficients) Sample composition Occupational status Mean scores of study variables Linear regressions – satisfaction with work–life balance (pooled sample)

43 46 53 60 66 68 79 82 83 85

106

107

110 113 125 126 127



130

vii


viii List of Tables and Figures

7.5

131 145 146 152 152 155

157

159 190 195

Figures 2.1 Conceptual model and hypothesized relationships 3.1 Countries grouping according to macro-economic indicators 3.2 Women’s activity rates, part-time work and fertility in 2006 5.1 Subjective measures of quality of work (adjusted means) 5.2 Overall life satisfaction by country (adjusted means) 5.3 Overall life satisfaction by organization 6.1 Conceptual model for the empirical analysis 6.2 Correlation between satisfaction with work–life balance (SWLB) and life satisfaction (SWLS) across organizations and countries 7.1 Country variation in satisfaction with work–life balance (mean scores) for professionals and non-professionals 7.2 Country variation in satisfaction with work–life balance (mean scores) for part-time and full-time employees 7.3 Country variation in satisfaction with work–life balance (mean scores) for older and younger employees 7.4 Interaction between age and level of state support predicting satisfaction with work–life balance 8.1 Family meal frequency by country

19 36 39 87 91 92 100

108 127 128


Linear regressions – satisfaction with work–life balance, all employees 8.1 Correlation matrix 8.2 Regression results 9.1 Percentage of women in each country and in each company 9.2 Means and percentages to describe working hours 9.3 Quality of work and quality of life 9.4 Relationship between life course, work engagement and quality of life of men and women in eight European countries 9.5 Regression analysis to explain work engagement and quality of life, unstandardized coefficients (standard errors in brackets) 11.1 Factors making up the axes 11.2 Future scenarios, by country

128 132 137



192 198 211 213 Copyright material from www.palgraveconnect.com - licensed to Universitetsbiblioteket i Tromso - PalgraveConnect - 2011-04-13

11.1 The position of the various countries in the trend quadrants 11.2 Chains of events 12.1 The structure of the Social Quality Instrument 12.2 Screenshot

ix


The editors would like to acknowledge the support from the European Commission for funding the Framework Six project ‘Quality of Life in a Changing Europe’. We wish to thank the project officer of the European Commission, Ian Perry, for providing continuous support during the endeavour of the project. We are also most grateful to the organizations that took part in the study, and the employees who shared their experiences about life and work with us. Furthermore, we would like to acknowledge the support of Peter Hermus and Annejet Kerckhaert regarding the data collection, and the work of the project managers, Els van Kampen and Marijke Veldhoen-van Blitterswijk. Finally, we are greatly indebted to Cecilia Willems for the excellent job she made of correcting the English language of all contributions. This book is the result of a very pleasant and inspiring collaboration of researchers and we would like to thank all contributors for their work, input and inspiration. Margareta Bäck-Wiklund Tanja van der Lippe Laura den Dulk Anneke van Doorne-Huiskes


Acknowledgements

x


Timo Anttila (PhD) is a researcher in the Department of Social Sciences and Philosophy at the University of Jyväskylä, Finland. His research interests are new forms of employment, working time, knowledge work and time use. Margareta Bäck-Wiklund is Professor of Social Work and Family Policy at the University of Gothenburg, Sweden. Her research interests are modern family life and parenting. Her current research is focused on family–work balance. Margarida Barroso is a PhD student at ISCTE-IUL and researcher at the Research Centre for Studies in Sociology (CIES), Portugal. Her research interests are work, organizations and occupations, ways of life and public policies. Barbara Beham is Assistant Professor at the Institute of Management at Humboldt-Universität zu Berlin in Germany. Her research focuses on the work–family interface and family-supportive organizational policies. Leila Billquist is a Senior Lecturer at the Department of Social Work, University of Gothenburg, Sweden. Her research interests are social services agencies and clients, with a particular interest in organization and profession. Michael Brookes is a Senior Lecturer in economics at Middlesex University Business School. His current research interests are wage and employment discrimination as well as industrial relations. Anneke van Doorne-Huiskes is Emeritus Professor of Sociology at the Department of Sociology and ICS Research School of Utrecht University. Her research interests are welfare states, labour market and gender, gender and organization, organizational culture and work–life balance. Since 1987 she has been a senior partner of VanDoorneHuiskes


Contributors

xi


xii Contributors

Maria das Dores Guerreiro is a Professor at the Department of Sociology, ISCTE-IUL, Lisbon University Institute, Portugal. Her research interests are work–life balance, gender and work, equal opportunities, young generations, family, organizations and professions, social policies, new forms of work and employment. Sonja Drobniˇ c is Professor of Sociology, Chair of Social Science Research Methods at the University of Hamburg, Germany. Her main area of expertise is cross-national research and longitudinal methods. Her research focuses on employment and self-employment, careers of couples over the life course, division of household labour, quality of life and work, and gender differences in social capital. Laura den Dulk is Assistant Professor at Erasmus University Rotterdam, Department of Public Administration. Her main area of expertise is cross-national research regarding work–life policies in organizations in different welfare state regimes. Current research interests include the attitudes, opinions and behaviour of top managers towards work–life policies and the social quality in European workplaces. David Etherington is Principal Researcher at the Centre for Enterprise and Economic Development Research at Middlesex University Business School. His research interests are local government in the area of employment, labour markets, employment relations, skills and social exclusion. Eva Fodor is Associate Professor of Gender Studies at the Central European University in Budapest, Hungary. She is a scholar of comparative social inequalities: she studies the ways in which gender regimes are constructed, maintained and modified in different societies. Stanimir Kabaivanov is a PhD student at the University of Plovdiv in Bulgaria. His research interests are in the field of youth transitions to employment, parenthood and quality of work.


and Partners, a research and consultancy firm in Utrecht, the Netherlands.

Siyka Kovacheva is an Assistant Professor in sociology at the University of Plovdiv in Bulgaria. Her research has focused on the social transformation of Bulgarian society, changes in family life, including gender and intergenerational relations, and work–life balance.


Contributors

xiii

Suzan Lewis is Professor of Organizational Psychology at Middlesex University Business School (formerly at Manchester Metropolitan University). Her research focuses on work–personal life issues and workplace practice, culture and change, in diverse national contexts. Tanja van der Lippe is Professor of Sociology of Households and Employment Relations at the Department of Sociology and Research School ICS of Utrecht University. Her research interests are in the area of work–family linkages in Dutch and other societies. Polina Manolova is an MA student in social policy at the University of York, UK. She has a Bachelor degree of politology at the University of Plovdiv. Her areas of interest are youth participation, youth transitions and family policy. Annabelle Mark is Professor of Healthcare Organization, Director NHS General Management Training Scheme – Human resource specialism; founding academic OBHC (Organizational Behaviour in Healthcare); chair of SHOC (Learned Society for Studies in Organising Healthcare). Jouko Nätti is Professor of Social Policy at the University of Tampere, Finland. His research focuses on working life research, working time, forms of employment, labour market policy, unemployment, work and household, job insecurity, knowledge work, gender and age at work. Patrick Präg is a PhD student at ICS/University of Groningen, the Netherlands. For two years he worked as a research assistant at the University of Hamburg, Germany. His research interests include work and family conflict, social inequality, and crime and deviance. Dorottya Redai is a PhD student at the Gender Studies Department of Central European University, Hungary. Her research interests are quality of life, and gender in education and politics in Central Eastern Europe.


Linda Lane is a Senior Lecturer at the Department of Social Work, University of Gothenburg, Sweden. Her research interests are gender and work, work and family life, social policy and industrial relations.

Eduardo Rodrigues is a PhD student at Lisbon University Institute (ISCTE-IUL) and researcher at the Centre for Research and Studies in Sociology (CIES). His research interests are sociology of the family, gender and quality of life.


xiv

Contributors

Stefan Szücs is an Assistant Professor at the Centre for Public Sector Research (CEFOS), University of Gothenburg, Sweden. His research interests include the development of local governance and working life. Sakari Taipale is a Senior Lecturer at the Department of Social Science and Philosophy, University of Jyväskylä, Finland. His current research interests are related to ICT and mobility studies as well as to quality of life issues in the information age. Roland Verwiebe is Professor for Social Stratification Research and Quantitative Methods at the University of Vienna, Austria. His main research interests are social inequality, migration, quality of life, labour markets and Europeanization.


Joop Schippers is Professor of Labour and Gender Economics at Utrecht University. His research interests are male–female wage differences, human capital investments, labour market flexibility and organizational behaviour with respect to women and older workers.


Quality of Life and Work in a Changing Europe Tanja van der Lippe and Margareta Bäck-Wiklund

Intense globalization, rapidly changing workplaces and the increasing number of female employees and dual-earner families have revived the interest of researchers around the world in how people assess their lives overall (Moen and Chermack, 2005; Crompton et al., 2007; Valcour, 2007; Esping-Andersen, 2009). In the European Union, social quality has been set as a new standard for assessing both economic growth and social well-being. Economic growth and global competitiveness are drawing more attention, while policies regulating the labour market and conditions of work are being used to retrench welfare regimes in crisis. One of the most pressing challenges is to ensure that improvements in economic competitiveness are not achieved at the expense of quality of life or by increasing inequity between people. This book is about how, in an era of major change in both private and working lives, European men and women living in different national welfare state regimes evaluate the quality of their lives and well-being. The organization of work and the workplace is crucial for men and women attempting to establish everyday routines in order to achieve quality of life (Gallie and Russell, 2009). Work intensification appears to prevail across Europe, and everyday life is becoming more and more demanding (Green, 2006; Lewis et al., 2009a). Focusing in particular on the service sector, we seek to understand the driving forces behind the logistics of juggling working and private life, children and the increasingly demanding standards of good and involved parenting.


1

1 The innovativeness of the underlying study The book is based on the study Quality of Work and Life in a Changing Europe. The study’s multi-method approach addressed work and family 1


Quality of Life and Work in a Changing Europe

quality of life at three levels: national social policy, organizational, and family and individual. The countries covered in the book are Bulgaria, Finland, Germany, Hungary, the Netherlands, Portugal, Sweden and the UK. They belong to five main policy regimes (Esping-Andersen, 1990, 1998; Blossfeld and Drobniˇc, 2001), with Sweden and Finland as social-democratic (universalistic), Germany and the Netherlands as corporatist (conservative), the UK as liberal, Portugal as sub-protective (Mediterranean), and Hungary and Bulgaria as post-socialist. The countries differ in the way they address quality of work and life and the policies they have in place. The book contributes to the literature in its theoretical approach, data collection and cross-country comparative analysis. The theoretical approach makes use of sociological, economic and psychological insights to understand the interdependence between the quality of work and the quality of life. To understand the quality of life, we believe that we must unravel the interdependence of new organizational forms, quality of work and quality of life. At the micro level, individuals look for strategies to cope with changing work forms that impact on their quality of work. Solutions can vary in scope, depending on the employee’s own resources (education, skills, etc.) and the demands perceived in the work and home environment, with clear consequences for their quality of life. At the meso level, organizations have implemented new forms of work, often implying new governance structures. The macro level includes the institutional, cultural and economic context that impacts on quality of life as well. Using unique quantitative and qualitative data introduced below, we analyse under what conditions European workplaces could be transformed into healthy organizations in which social quality can be achieved and work can be organized in both a socially and economically sustainable way. Our cross-country analysis shows new and contrasting trends between welfare regimes, confirming that welfare models are moving targets and adding new knowledge to our empirical and theoretical understanding of welfare state regimes. The countries included in the study represent different welfare regimes as well as the east/west and north/south dimensions of regime models. The analysis shows a trend towards convergence between welfare regimes, with higher labour market activity rates, gender equity in paid work and a variety of different institutional support mechanisms for working parents. At the same time, there are growing differences within policy regimes. We look at how these differences will evolve in future for the countries in question.


2


Tanja van der Lippe and Margareta Bäck-Wiklund

3

2 The main aims of this book

1. to use an internationally comparative perspective to investigate the quality of work and life of European women and men and the way quality of life and work are interrelated, based on both workplace and family/household factors; 2. to analyse how and under what conditions European workplaces could be transformed into healthy organizations where work is organized in a socially as well as an economically sustainable manner; 3. to improve our knowledge of the impact of public and organizational policies on the well-being of European women and men, and to analyse future trends in this area for specific countries. The empirical material on which this book is based was collected before the world economic crisis at the end of the first decade of the twentyfirst century. Nevertheless, the results of the study show that individuals reflect on past, present and future conditions and that they tend to calculate risk when evaluating their quality of life. The idea of an upcoming crisis was already there before it happened.

3 Unique quantitative and qualitative data We have used a combination of quantitative and qualitative data to achieve these aims and enrich our analysis. The same data were collected in eight European countries in 2007. We describe the procedure, along with reflections on steps taken, pros and cons in co-ordinating eight countries, and handling a large-scale dataset and its impact on the validity and reliability of the data and results found. Against this background, we analyse the unique survey material of 7867 employees working in 32 service sector organizations (four in each country). The data provide new perspectives on the quality of life and work of European women and men and their overall life satisfaction, and they also highlight findings at the institutional, workplace and gendered individual and household/family level. In each country a retail company, a bank and/or insurance company, a telecom/IT company and a public hospital participated in the research. We supplement the survey data with a case study from one workplace in each country (five hospitals and three private sector companies). The case studies are based on


This book has three main aims:



individual interviews and innovation groups and give us a more profound picture of the discourses that evolve around the issues associated with the intensification of work and family life. In order to identify and to find practical solutions to these issues, we also present a Social Quality Instrument, adapted for cross-national use. Finally, we have looked at what worries loom ahead by asking politicians, researchers and journalists to explore obstacles to and opportunities for a sustainable quality of life in Europe from a global perspective. This comprehensive book and its multilayered analysis help us rethink the meaning of work and life and provide new empirical as well as theoretical underpinnings. It also contributes to a growing discussion in the literature of the very nature and meaning of ‘work–life balance’ as well as its relationship to life satisfaction and the differing consequences for women and men. We furthermore explore the limitations of achieving this balance, given a context where the service sector is embedded in a global capitalist economy and men have a privileged position within it. An additional important perspective is that of ‘healthy’ workplaces, that is those workplaces that are both effective in what they do and meet the quality of life needs of their employees.

4 Quality of work and quality of life Quality of life has been recognized as an important construct in a number of social and medical sciences. Each academic field has developed a somewhat different approach to investigating the construct of quality of life. For example, sociologists and political scientists are often interested in the quality of life at the societal or population level; psychologists and medical scientists are interested in quantifiable aspects of individual and subjective experiences of a good life (Rapley, 2003; Noll, 2004). The Scandinavian approach focuses entirely on resources and objective living conditions, such as standard of living and personal income (Erikson, 1993), and the American approach emphasizes subjective well-being via satisfaction and happiness as perceived and experienced by the individual (Campbell et al., 1976). The World Health Organization defined quality of life as ‘an individual’s perception of their position in life in the context of the culture and value system in which they live and in relation to their goals, expectations, standards, and concerns’ (WHOQOL Group, 1998, p. 551). Despite various definitions and inconsistencies, the majority of scholars at least seems to agree that the construct of quality of life is multidimensional and that it has subjective as well as objective components


4


5

(e.g. Sirgy, 2002; Rapley, 2003). Individuals may perceive and evaluate objectively similar living conditions quite differently. We adopt the same generally broad idea of quality of life in this book. People’s experiences are segmented into life spheres, facets or life domains (Sirgy, 2002). A person may have distinct experiences in relation to education, family, health, work, friends, etc. The hierarchy of life domains particular to an individual reflects the salience of the different domains to this person. Employment is a key factor in people’s quality of life. Being employed and receiving adequate pay are consistently ranked as an important requirement for individual quality of life (e.g. Clark, 2001a; European Foundation for the Improvement of Living and Working Conditions, 2005). In every European country for which there is adequate evidence, people in employment reported significantly higher levels of life satisfaction than the unemployed (Gallie and Russell, 1998). Work not only gives an individual an adequate income, it is also a source of psychological stability and personal development. It structures the day, offers a stable pattern of regular activity and gives people a sense of identity and participation in a collective purpose (Gallie, 2002). However, we should also point out here that the quality of work varies significantly among sectors and groups of employees. There are certain jobs that do not allow for personal development; they are insecure, dangerous and unhealthy, and provide little opportunity for participation. In addition, certain groups in the workforce are particularly affected by unfavourable working conditions, such as non-skilled workers, older workers, women, part-time workers, etc. Similar to quality of life research, there is little consensus on a definition of quality of work or on what constitutes a good job (Smith et al., 2008). Scholars from various academic fields, concerned with different levels of analyses, conceptualize quality of work in varying ways. Economists, for example, mainly define quality of work in terms of pay and working hours, while organizational psychologists are concerned with a comprehensive view of an employee’s well-being, which includes such factors as job satisfaction and job autonomy (Rosenthal, 1989). Indeed, empirical studies on what constitutes a good job provide evidence that quality of work is comprised of more than monetary awards (Clark, 2005). Neither income nor working hours were rated as the most important aspects of a job by employees in seven OECD countries; instead, both male and female participants considered job security and having an interesting job most important (Clark, 2005). Lane (2000), for example, defined quality of working life in terms of having a meaningful





job. The European Foundation (2005) sees quality of work as a broad and multifaceted construct that includes four key areas: job security, health and well-being, competence development and combining work and non-working life. One of the most recent definitions of quality of work, offered by Green (2006), is a set of work features that foster the well-being of the worker. Following the ideas of Sen (1993), Green argues that high-quality jobs generate capabilities that allow workers to achieve well-being and a range of personal goals. Capabilities are derived from wages and other reward conditions, including future prospects (such as pensions and security), as well as job control (the ability to choose). ‘A high-quality job is one which affords the worker a certain capability – the ability and the flexibility to perform a range of tasks (including the necessary sense of personal control), to draw on the comradeship of others working in cooperation, to choose from and pursue a range of agency goals and to command an income that delivers high capability for consumption’ (Green, 2006, pp. 14–15). Green does not refer, however, to the ability to successfully manage working and private life. Moreover, paid work is not only a source of capabilities; it is also a source of demands. This study considers the impact of both job resources and demands, above and beyond resources and demands at home, and the impact of the wider workplace and national context.

5 Trends and developments in working life Working life has undergone dramatic changes in the past few decades, mainly due to the introduction of information and communication technologies, shifts towards globalization, restructuring and downsizing. Other changes accompanying these major trends include new patterns at work (e.g. telecommuting, teamwork, self-regulated work and alternative working hours), resulting in a general move towards a more flexible workforce in terms of number of employees, skills and functions (Sparks et al., 2001). Countries differ considerably in the prevalence of part-time employment. Some countries, such as the Netherlands, have very high part-time rates, but the UK, Sweden and Germany also have a high proportion of part-time employees. In Eastern and Southern Europe, however, part-time work is still relatively uncommon, as it also is in Finland (European Commission, 2006). In relation to working hours, overall work pressure increased in Europe between 1991 and 2000; in 2000, 60 per cent of workers reported having to work at a fast pace and meet deadlines. In Western Europe, the percentage of workers


6


7

experiencing work pressure is the highest in Sweden, followed by Finland, the Netherlands and the UK. Lower levels of work pressure are found in Portugal, and German workers occupy a middle position (Houtman et al., 2006). The modern labour market is not only increasingly flexible in nature but is also seeing the disappearance of ‘jobs for life’ (Green, 2006). Consequently, it has been argued that modern working life is becoming more insecure, above and beyond unemployment rates (Green, 2006), although there do not seem to have been any sharp changes in job tenure or retention rates (see, for example, Clark, 2005). Countries do differ, however, in the average length of job tenure: tenures in the UK are relatively short and those in Southern Europe are relatively long (Paugam and Zhou, 2007). There has also not been a visibly sharp increase since the 1990s in the share of workers on nonstandard employment contracts (fixed-term contracts, temporary work and traineeships). In fact, the Scandinavian countries, the Netherlands and Germany have witnessed a decline in non-standard contracts. The highest proportion of workers on a non-standard contract can be found in Portugal (18 per cent) and Bulgaria (22 per cent) compared to 11 per cent of Swedish workers (European Foundation, 2009). Job autonomy trends vary from country to country. The UK witnessed an overall decline in workers’ freedom to decide how the work is done during the 1990s; Germany and Sweden, on the other hand, have seen an increase in job autonomy (Gallie, 2007). Dutch workers also report relatively high levels of job autonomy (Houtman et al., 2006). Like in Sweden and Finland, Dutch workers often have ‘challenging’ jobs combining high work pressure with a large degree of autonomy. Portuguese workers, on the other hand, report a low degree of job autonomy and also witnessed a larger decrease between 1995 and 2000 (Ibid.). The share of workers with little job autonomy increased between 2000 and 2005 to 40 per cent in Bulgaria and 33 per cent in Hungary. Another indicator of job autonomy is the degree of control over the pace of work. A relatively high proportion of workers (44 per cent in the UK to 36 per cent in Sweden) say that their work pace is outside their control and dependent on others, such as clients, supervisors and colleagues. In most countries, the share of workers who lack autonomy over their work pace increased between 1990 and 2005 (European Foundation, 2009).



6 Trends and developments in private life Life has become more demanding not only at work but also in the private domain. The rise of dual-earner families and the growing number



of women in the labour market have forced more people to try to combine paid work with childcare and other life activities. The decline of the single-breadwinner family model implies that people increasingly need to adapt their working life to their personal and family life and vice versa. Life gets more complicated when a couple tries to juggle two jobs, children’s school hours and leisure activities, and a social life. They also have less time to recover from work. The increased flexibility of working life (flexible working hours) and technological advances (e-mail and mobile phones) have also made the boundary between work and family more permeable. As a result, work can be interrupted by family demands and vice versa (Kossek et al., 2005). Moen and Chermack argue that ‘both paid work (as a result of downsizing and restructuring) and parenting (as a result of the push towards intensive mothering and insights in child development) are increasingly “greedy” institutions’ (2005, p. 103). Nevertheless, research shows that parents in every country protect family time from the demands of paid work (Bianchi et al., 2000, 2006). This is in line with theories of modern-day parenthood, which some researchers claim exert a strong normative pressure on parents – and especially mothers – to invest a large amount of time in their children (Hochschild, 1997; Bianchi et al., 2000). Gender inequality still prevails, since women bear the main responsibility for the home, including providing informal care for children, the disabled and older parents (Bianchi et al., 2000; Davis and Greenstein, 2004; Fuwa, 2004). Changing employment and policy constraints impact on care, as does the changing composition of society. Some countries (such as Portugal) rely on the broader family institution for informal care, but others (Sweden, for example) outsource this work. A new issue was introduced into the discussion of job quality in the 1990s, reflecting the growth of female labour market participation: how to reconcile a career and family life (Gallie, 2007). The emergence of a new post-industrial working time regime was another driving factor behind this lively discussion. Unlike industrial working time, the post-industrial working time regime is usually characterized by the deregulation of collective norms, diversification in the length and pattern of working time and blurring of the boundaries between work and private life (Perrons et al., 2005). Long working hours are a growing topic of discussion in the literature, in particular their impact on personal relationships and home life (Hochschild, 1997; Jacobs and Gerson, 2004). There is no evidence that people are generally working longer hours, although at the household level, the sum total of hours worked by both partners has increased. Some countries face new polarization trends in


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7 Structure of the book The book is divided into three sections. The first section, consisting of three chapters and entitled Context, Theory and Methods, provides the theoretical framework, outlines the institutional contexts and current trends in the eight countries and gives detailed descriptions of the methods used in the study. The second section consists of five chapters and is entitled Empirical Results. Each chapter applies a cross-national comparative perspective and highlights points from the overall findings of the study and the differing analytical levels and perspectives on quality of work and quality of life. A cross-national analysis spots differences that can be explained by the differing welfare state regimes, and a deeper multi-level gendered analysis tests theoretical assumptions about which factors in the work and family domain influence the quality of life for different occupational groups, working parents and genders. The third section, Policy Implications and the Future Research Agenda, consists of three chapters and draws on the qualitative material. It analyses issues that are blocking or easing the functioning of a ‘healthy organization’ from the employee’s perspective and presents and compares country scenarios. The picture that emerges highlights differing concerns about the future and adds an extra dimension to the academic discourse on the quality of life and work. The chapters in this section discuss and challenge these notions and offer practical solutions, including a research-based online instrument for assessing and improving quality at work. Although the book was written by many authors, it is actually a monograph. It begins by describing a research problem and associated theoretical insights, continues with a description of the data and empirical analyses, and concludes with future trends and policy implications. This approach will help deepen our understanding of the interface between working life and family/personal life and its impact on the overall life satisfaction of European women and men.


working hours, with working hours growing longer on the one hand and the share of part-time jobs increasing on the other (Scherer and Steiber, 2007). This book studies changes in both the family and the work domain in relation to quality of work and quality of life.

7.1 Context, theory and methods In Chapter 2, Laura den Dulk, Margareta Bäck-Wiklund, Suzan Lewis and Dorottya Redai develop a theoretical framework for understanding quality of life in a changing Europe. Using the current theoretical discourse



about quality of work and life, which indicates that demands and resources at work and in households have developed over time, they present a model that sets out to explain overall life satisfaction and satisfaction with managing work and family/personal life across countries and in the service sector. Unlike many previous quality of life studies, the authors look at multiple life domains and the way they impact on one another in understanding quality of life. In Chapter 3, Siyka Kovacheva, Anneke van Doorne-Huiskes and Timo Anttila analyse the institutional context within which companies, families, women and men in the partner countries develop strategies to achieve quality of work and quality of life. The chapter examines the economic, labour market and demographic trends in Europe of the past 15 years and focuses on similarities and differences in employment and family policies across countries. Similarities include policies pushing employees towards higher activity rates and greater flexibility in employment. At the same time, there is growing divergence within policy regimes. These trends may have consequences for the quality of work and life. In Chapter 4, Tanja van der Lippe, Stefan Szücs, Sonja Drobniˇc and Leila Billquist present the data and methods. The task of understanding the relationship between the quality of work and the quality of life in a changing Europe and testing the theoretical model described in Chapter 2 required a variety of data to be collected, from a variety of different sources. This chapter provides detailed information on our data and discusses the advantages and disadvantages of the various data sources. In sequence, it discusses secondary data, the large-scale survey performed among employees working in four service sector organizations in each country, the in-depth interviews and innovation groups at one organization in each country, the scenarios constructed on the future of work and, finally, the online quality of life instrument.

7.2 Empirical results In Chapter 5, Patrick Präg, Jouko Nätti, Maria das Dores Guerreiro, Michael Brookes and Laura den Dulk present the initial descriptive analyses of the international comparative quality of life survey dataset. The aim is to describe and compare subjective indicators of quality of work and life across countries and organizational contexts. This chapter presents a range of subjective indicators for the quality of work and life as reported by service sector employees in eight European countries, including work engagement, stress, work–home


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interference and enrichment, satisfaction with work–life balance, and overall life satisfaction. In addition, it provides background information on the organizational context, including workforce characteristics and organizational changes at the time of our research. In Chapter 6, Stefan Szücs, Sonja Drobniˇc, Laura den Dulk and Roland Verwiebe deepen the analysis of quality of work and life by evaluating how job demands and resources and the way employees manage their work and non-work roles are related, either negatively or positively, to quality of life. The main objective of this chapter is to understand variations in satisfaction with the work–life balance and overall well-being in differing organizational contexts and across European countries. Data from the Quality survey make it possible to control for the type and status of work organization to some extent, and to examine workplace effects within and between countries. The study design includes three levels of analysis: individual job and household demands and resources, workplace/organizational context and country context. In Chapter 7, Barbara Beham, David Etherington and Eduardo Rodrigues use the large-scale Quality of Life survey to study the variation in work–life satisfaction among different categories of employees. The existing work–family research and literature has tended to focus on homogeneous samples of managerial and professional workers, with very few studies covering the work–life experiences of other employee categories. In this chapter the authors specifically study work–life satisfaction and its relationship with work-related antecedents for professional vs. non-professional, full-time vs. part-time, and older vs. younger workers. It examines whether the level of state support in the eight countries influences employees’ ability to successfully combine work and private life. In Chapter 8, the focus shifts towards working parents and their children. Linda Lane, Tanja van der Lippe, Stanimir Kabaivanov and Margareta Bäck-Wiklund explore the implications of dual-earner parents’ work–family conflicts, focusing on the way the organization of working life affects who participates in family meals and how often. The family meal was chosen because it represents a consistent opportunity for family members to create and share experiences and, as such, stands as a symbol for ‘good parenting’, meaning presence and involvement. The chapter looks at what working conditions are most unfavourable to and undermine opportunities for shared family meals. In Chapter 9, Eva Fodor, Linda Lane, Joop Schippers and Tanja van der Lippe study gender inequalities in quality of life. Although women might lag behind men in terms of their objective labour market





situation, this may be less so for subjective feelings of quality of work and in the broader context of quality of life. The chapter looks in particular at the life course, as the role of work differs over the life course of men and women, with important implications for their quality of life. Whereas men have to put all their eggs in the basket of a labour market career for social approval, women can also opt for ‘dedicated motherhood’ as a road leading to fulfilment and recognition in society.

7.3 Policy implications and the future research agenda In Chapter 10, Suzan Lewis, Anneke van Doorne-Huiskes, Dorottya Redai and Margarida Barroso explore the notion of a healthy organization that meets a dual agenda by fulfilling individual needs and ensuring organizational efficiency. Healthy organizations are effective in what they do and also meet the needs of the workforce, recognizing that individual and organizational health are interdependent. This chapter discusses the findings of a qualitative study of healthy organizations based on case studies of one organization in each selected country. The case studies help deepen our understanding of the survey data and to focus on the ways in which specific organizational contexts and processes impact on quality of life and work. In Chapter 11, Maria das Dores Guerreiro, Annabelle Mark, Polina Manolova and Leila Billquist present the results of a scenario exercise focusing on the future of Europe and the related policy implications. The exercise was run in each of the eight countries involved in the Quality project and was intended to predict future social trends and how they might impact on quality of work and quality of life. The authors perform a comparative analysis of the themes raised during the group discussions in order to highlight similar and differing clusters of concerns and projections regarding uncertainties and the future of European society. Cultural and symbolic factors permeate the future scenarios related to quality of life and work. Although there are specific country and welfare regime factors, there are also similarities related to contemporary trends, with globalization affecting both workplaces and family patterns. In Chapter 12, Sakari Taipale, Barbara Beham and Jouko Nätti discuss the Social Quality Instrument: Measuring Social Quality of Work in European Workplaces. At times, scholars and work–life studies are criticized for not providing practical tools for assessing and improving social quality at work. In this chapter, the authors describe how they developed a research-based online instrument for measuring the social quality of work and piloted it in work organizations within the framework of


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the Quality project. They also account for the cross-national usefulness of the instrument and offer a critical analysis of its pros and cons. In the concluding chapter, Chapter 13, Anneke van Doorne-Huiskes and Laura den Dulk summarize the main findings of the book. They review the strengths and weaknesses of the study and discuss recommendations for future research and future challenges in the field of quality of work and life.







Part I


Context, Theory and Methods





Quality of Life and Work in a Changing Europe: A Theoretical Framework Laura den Dulk, Margareta Bäck-Wiklund, Suzan Lewis and Dorottya Redai

1 Introduction Chapter 2 discusses the theoretical framework of this study, which explores the quality of work and life in eight European countries. Unlike many previous quality of life studies, our study looks at multiple life domains and the way they impact on one another. The rise of dualearner families and the increase in the number of qualified women entering the labour market are forcing more people to combine paid work and care responsibilities or other life activities. Consequently, people increasingly need to adapt their working life to their private and family life and vice versa. Life becomes more complicated when trying to juggle two jobs, children’s school timetables and hobbies, and a social life. In addition, increased flexibility and advanced technology – for example, flexible working hours, e-mail and mobile phones – affect the permeability of work and family boundaries (Kossek et al., 2005). As a result, the work and household domains increasingly interact with and influence each other. Any analysis of the quality of life of workers must consider both domains as well as people’s ability to successfully manage their work and private life. Problems or conflicts between work and family life can have negative impacts on health and well-being (for example, OECD, 2001). In this book, we discuss how demands and resources at work and at home impact on the quality of work and private life. We extend this resources – demands approach by examining the impact of resources and demands on the quality of work and life in the wider workplace and national context. Countries in Europe differ in the way their public policies and regulations address quality of work and quality of life.


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A Theoretical Framework

Some countries offer additional resources such as social security, public health care or childcare facilities (see also Chapter 3). Across the board, however, they are all facing similar major social and economic changes likely to affect the quality of life and work, although the pace and timing may differ: an ageing and more diverse workforce, changing forms of work organization, increasing competition due to processes of globalization and rapid technological advances, welfare state retrenchment and reductions in social provisions. These changes also influence workplace policies and practices, since it is there that global trends and national policies and regulations are played out. Workplaces have witnessed trends such as downsizing and restructuring, the rise of flexibility and changing employment contracts. How are new working practices and emerging work–family policies impacting on the quality of work and life of service sector workers in Europe? Examining this question in a time of profound and continuous change involves analysing not only the negative impacts but also – following the example set in the current literature – taking a more positive approach by focusing on such aspects as work engagement, work–home enrichment and satisfaction with the work–life balance.

2 Demands and resources and the quality of life: conceptual model The central focus in our theoretical approach is the relationship between quality of work and quality of life and how they are affected by rising demands in both working life and private life; that is, the opportunities and barriers male and female workers face in different workplaces and European countries. Perceived quality of work and quality of life are related to job and household characteristics, the workplace context and the wider national context. Our basic assumption is that paid work contributes to people’s quality of life as long as their resources are adequate to meet the demands and needs they face (Moen and Chermack, 2005). Both the workplace and the family or household situation generate demands and resources. Demands at work are, for instance, long working hours, frequent travel and shift work. Demands at home include caring for children or an elderly relative. Resources at work include job autonomy over the way work is done, co-worker relationships and work– life support. Resources at home are, for instance, a supportive network of family and friends and a partner with whom to share domestic work. When resources lag behind the demands workers face in various life domains, tensions and feelings of stress may arise that in turn impact


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on their well-being. On the other hand, people feel in charge of their lives when resources are adequate to meet their needs and the demands made on them. According to Moen and Chermack (2005), it is precisely this sense of control that enhances quality of life. Figure 2.1 indicates how resources and demands in the work and household domains affect the quality of life of European service sector workers. The conceptual model proposes both a direct relationship between resources and demands and quality of life and an indirect relationship via outcomes such as stress, work–home interference, enrichment, work engagement and satisfaction with the work–life balance. Heavy work and household demands and inadequate resources can result in negative work–home interference and feelings of stress.

Institutional context: globalization, welfare state regime, labour market conditions Workplace context: organizational culture and structure Job demands Working hours Work pressure Commuting times Job insecurity Work-led flexibility Career demands

Job resources Autonomy Flexible work arrangements Social support Work−life support Training

Stress, work−life balance, work engagement, work− home interference and enrichment

Healthy organization Quality of life

Household demands Children Domestic work Care responsibilities

Household resources Partner Absence of conflict with partner Paid/informal domestic help Household income

Figure 2.1


Laura den Dulk et al.

Conceptual model and hypothesized relationships



On the other hand, a high-quality job and a supportive household situation that generates resources may result in work engagement, satisfaction with the work–life balance and work–home enrichment. The arrow between the resources and demands indicates the buffering effect of available resources: resources can help people cope with demands, thereby mitigating their negative impact. We discuss the hypothesized relationships in more detail below.

2.1 Job and household demands and the quality of life High work pressure, long working hours and commuting reduce the time and energy people have to engage in activities in other life domains and may result in feelings of stress, exhaustion and negative workto-home interference. Research indicates that the level of work–family conflict rises with the number of working hours: the more people work, the more negative work-to-home interference they perceive (Scherer and Steiber, 2007), and the more their overall quality of life is affected. In addition, many studies have shown that the fear of losing one’s job is detrimental to well-being (Green, 2006). Job loss not only implies a loss of income but also a loss of social contacts, opportunities for selfactualization and career opportunities, and it may eventually lead to social exclusion (Paugam and Zhou, 2007). Job insecurity is therefore very stressful and can have a negative impact on the quality of life of workers. Flexible working arrangements, such as flexible starting and finishing times, part-time work and teleworking, are often presented as a resource and a solution to work–family issues, but the relationship between such arrangements and satisfaction with work and private life is not straightforward (Peters et al., 2009). Of greatest relevance is whether employees are in control of the arrangements. The European Foundation for the Improvement of Living and Working Conditions (2002) makes a distinction between positive and negative flexibility. Positive flexibility means that workers can use flexible working arrangements to suit their own needs. Negative flexibility, on the other hand, is when flexible working arrangements are dictated by a worker’s tasks, clients or supervisor. Negative flexibility includes overtime or unforeseen changes in work schedules. Long working hours have a negative impact on employee well-being and stress as well as on perceived work–life balance. Last-minute schedule changes at work might be very difficult to accommodate when people have little flexibility or few resources in their private life (that is, for example, workers with children, single


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parents). Depending on the household situation, some employees might prefer predictability over flexible working hours. Flexibility is therefore a double-edged sword: it can allow workers to adjust paid work and responsibilities at home but it can also result in their spending more time working rather than less, for example when workloads are intensified (Lewis and Den Dulk, 2008). Whether flexible working practices are beneficial or not seems to depend on the workers’ degree of control as well as their workload. This study therefore distinguishes between work-led flexibility and flexible working arrangements, such as flexible starting and finishing times, that enable people to adapt their working hours to activities and demands in their private life. However, it should be noted that some flexible working arrangements, particularly a reduced hours week and telecommuting, are often associated with intensification of work (Lewis et al., 2009a; Kelliher and Anderson, in press). In addition to or beyond job demands, this study takes household demands into consideration. Depending on their stage of life, people may be responsible for caring for young children, parents, relatives and friends. The presence of children can be very enriching and as such increase overall life satisfaction, but it can also present new demands. Raising children is costly and involves major care responsibilities. Parents today are expected to provide far more parental care and more financial resources than their own parents were able to provide (Lewis and Den Dulk, 2008). Although women spend more time in paid work, time spent with children has not decreased (Gauthier et al., 2004; Sayer et al., 2004). Cultural norms and expectations of good parenting, child development and children’s needs have led to the idea that parents owe their children a ‘time debt’. The configuration of motherhood that places the mother–child relationship at the centre leans heavily on post-Freudian disciples such as Melanie Klein, John Bowlby and Donald W. Winnicott. Winnicott introduces the notion of ‘goodenough’ mothering, arguing that even though the mother is not perfect, she should recognize, be empathic to, and willing and able to meet the child’s needs (1971). This has left us with an idealized view of the good mother, but nowadays there is also strong competition from the new, involved father. Both ideals place demands on parental attention and involvement in order to meet children’s needs. In a study of reconstituted families, the researchers argue that children’s needs are one of the few remaining unquestionable moral assertions among parents in contemporary society (Ribbens et al., 2000, p. 800). In the case of the new fatherhood, however, research shows that the expectations often exceed the actual outcome (Hobson, 2002; Plantin et al., 2003).





In addition to childcare responsibilities at home, people may also have to care for relatives or friends outside the household. Caring for chronically or seriously ill parents, for instance, can be very demanding and time-consuming. More generally, a large amount of domestic work may result in feelings of stress and negative home-to-work interference. Overall, we expect that job and household demands are negatively related to overall life satisfaction.

2.2 Job and household resources and the quality of life Job and household demands are not necessarily problematic; they are only likely to have a negative impact on the quality of life when the resources needed to meet them are inadequate. The resources-demands approach allows us to see that resources have both a main effect and a buffering effect (Demerouti et al., 2001; Schaufeli and Bakker, 2004). House (1981) argues that support can enhance health and well-being directly, regardless of the demands people face. Schaufeli and Bakker (2004) support this idea by showing that job resources have a direct negative effect on burnout and a direct positive effect on work engagement. In addition, resources at work and at home can help people cope with demands and as such moderate the negative relationship between demands and overall life satisfaction. Hence, resources in the workplace and at home are assumed to have a positive impact on quality of life. Based on the demand-control-support model developed by Karasek and Theorell (1990), job autonomy and social relationships at work have been put forward as resources relevant to a person’s well-being. Traditionally, job autonomy refers to task autonomy, that is, the freedom to decide how the work is done (Schaufeli and Bakker, 2004). Recently the introduction of flexible working hours, variable work schedules and teleworking have added time and spatial autonomy to the list of important dimensions of job autonomy (Kossek et al., 2005). Job autonomy gives people latitude to deal with work pressure and a feeling that they are in charge of their lives (Houtman et al., 2006). Valcour (2007) found that job autonomy has both a direct and a buffering effect on satisfaction with the work–life balance. In addition, she also found that job autonomy moderates the impact of increased working hours on satisfaction with the work–life balance (Valcour, 2007). According to Saari and Judge (2004), job autonomy is the variable most relevant in predicting job satisfaction. In addition to job autonomy, worker well-being also depends on employees’ social relationships with their co-workers and supervisor


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(Schaufeli and Bakker, 2004; Bakker et al., 2006). When employees have to work hard but feel supported by their co-workers and supervisor, their satisfaction is likely to increase. Good social relationships at work offer employees additional energy that can contribute to overall life satisfaction. Furthermore, training on the job is an important form of support because it stimulates personal growth, learning and abilities, contributing to overall life satisfaction and helping people meet new and existing job and/or family demands. Income is an important resource when meeting the needs and demands of daily life. In particular, when basic needs are in danger of being unmet, income is an important determinant of overall life satisfaction. It allows people to maintain a certain standard of living and to fulfil basic needs such as housing and food, but it also gives them an opportunity to outsource care responsibilities or domestic work. When people earn enough money to meet their basic needs, their income becomes less important up to a certain optimal level, although research still shows a positive relationship with overall life satisfaction (Schyns, 2003). Real wages have increased in most countries, although many countries have also witnessed an increase in wage inequality (see Chapter 3). As described in the next chapter, wage levels in the eastern and southern European countries included in this study are lower than in the more affluent western or northern European countries. While the impact of income on life satisfaction has been widely studied, researchers have been less interested in other forms of support in the household, with the exception of spousal support. Having a partner can be viewed as an important source of support because it allows workers to share household and breadwinning tasks (instrumental support) as well as the worries and joys of everyday life (emotional support). Previous studies show, for example, that spousal support has both a direct and a buffering effect on work–family conflict (for example, Matsui et al., 1995; Van Daalen et al., 2006). The absence of conflict in the spousal relationship is important. Fighting about the division of domestic work with your partner conflicts with the ideal of a romantic relationship and as such negatively impacts on overall life satisfaction. It is probably more important to feel good about your relationship than to merely have a spouse or partner, with whom your relationship may also be negative (Abendroth and Den Dulk, 2008). Outsourcing domestic work reduces the amount of time spent on domestic chores and can relieve the double burden of paid and domestic work. Nowadays, household outsourcing has become a well-known strategy for dealing with household demands, at least for those with





sufficient income: people can outsource tasks to house cleaners, babysitters, home maintenance suppliers, by ordering take-away food or going to a restaurant (De Ruijter, 2005). Having good social relationships with relatives and friends can contribute to overall life satisfaction. Relatives and friends can offer domestic or financial support and can help meet job and family demands, for example when working overtime or caring for young children (Shaffer et al., 2005). When considering resources that help people find ways to combine work and family/private life, studies tend to focus on three types of resources: family-friendly organizational culture, supportive supervisory practice and available work–family benefits and policies (for example, Warren and Johnson, 1995; Thompson et al., 1999; Den Dulk, 2001). Benefits and arrangements such as telecommuting, flexitime, part-time work, job sharing, employer-supported childcare and elderly care, career breaks, enhanced leave arrangements and other familyfriendly organizational policies can be seen as instrumental support (Frone, 2003; Shaffer et al., 2005). Emotional support for the work–life balance in the workplace comprises support provided by the supervisor and co-workers. A family-friendly organizational culture is the result of both. Classifying an organization’s culture as family-friendly implies that its overarching philosophy or belief structure is sensitive to the family needs of its employees and is supportive of employees who are combining paid work and family roles (Warren and Johnson, 1995, p. 163). So far, research indicates that support provided by supervisors and co-workers explains more variance in work–family conflict and satisfaction with work–life balance than the presence and use of work–family benefits and policies (for example, Allen, 2001; Behson, 2005; Den Dulk and Peper, 2007). We therefore include perceived emotional work–life balance support provided by the direct supervisor and co-workers as a source of support in this study, in addition to the use of work–life policies.

2.3 Mediating outcomes: stress, work–life balance, work engagement, work–home interference and enrichment So far, we have focused on the direct effect of demands and resources on workers’ quality of life. The impact of resources and demands can also, however, be mediated by outcomes such as work–home interference, work engagement or stress. A lack of resources and heavy job and/or household demands can result in negative work-to-home or


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home-to-work interference or conflict. Problems or conflicts between job and household demands can have a negative impact on people’s motivation at work, their well-being, health and quality of life (for example, Van Doorne-Huiskes, 1992; Allen et al., 2000; OECD, 2001). Greenhaus and Beutell (1985), the founding fathers of work–family conflict theories, define work–home conflict or interference as a form of inter-role conflict in which the role pressures from the work and family domains are mutually incompatible in some respect (Greenhaus and Beutell, 1985, p. 77). Their basic assumption is that the time and energy needed to fulfil the roles in the work and private domains are scarce (Geurts et al., 2005). Greenhaus and Beutell (1985) distinguish between three major forms of role conflict: time-based conflict refers to a person’s physical or psychological inability to meet the demands of his/her role in one domain due to the demands of his/her role in the other; strain-based conflict refers to role-produced strain in one domain affecting a person’s performance in another; and behaviour-based conflict refers to the specific patterns of in-role behaviour being incompatible with expectations regarding another role. Time-based conflict can occur when people need to work late and cannot get home in time to collect their children. Strain-based conflict may occur when work is highly stressful, making it difficult to respond patiently to care demands at home. An example of behaviour-based conflict is combining a business attitude at work with a sensitive attitude at home. This latter form of work–home interference has been less widely researched because it is not easy to operationalize (Dikkers, 2008). Until recently, research mainly focused on the negative relationship between the work and household domains, that is, work–family conflict. Nowadays, concepts of work–home enrichment and work–life facilitation have been introduced, emphasizing the positive interdependencies between work and private life (Grzywacz and Marks, 2000; Greenhaus and Powell, 2006). Work–home enrichment refers to the extent to which experiences in one domain improve the quality of life in the other (Carlson et al., 2006; Greenhaus and Powell, 2006). As with negative work–home interference, a bi-directional relationship is conceptualized. For example, home-to-work enrichment occurs when skills required in raising children improve performance at work. On the other hand, skills developed at work can positively influence people’s personal life. Work– home enrichment may in turn have a positive impact on overall life satisfaction; moreover, it may mediate the impact of job and household demands and resources. Negative and positive experiences are not necessarily opposite ends of a continuum or mutually exclusive. People can





experience both highly negative and highly positive effects (Watson and Tellegen, 1985), and positive well-being is qualitatively different from and not just the absence of negative well-being (Hart and Haworth, 2007). Rather than focusing on cross-domain transfers of experiences, Valcour (2007) introduced the concept of overall satisfaction with the way one manages one’s work and private life. She defines satisfaction with the work–life balance as an overall level of contentment resulting from an assessment of one’s degree of success at meeting job and family role demands (Valcour, 2007, p. 1512). This more positive understanding takes into account that the significance of work and family or private life differs between individuals and that the private life encompasses more than the family role alone (Abendroth and Den Dulk, 2008). A more positive approach has also resulted in research focusing on work engagement, as opposed to outcomes like burnout or stress. Some researchers originally regarded work engagement as the opposite of burnout, but recently it is more frequently described as the positive antithesis of burnout and defined and operationalized as a separate concept (Schaufeli and Bakker, 2004; Bakker et al., 2006). Work engagement conveys full psychological presence in or focus on role activities (Kahn, 1990, 1992). According to Schaufeli et al., engaged employees have a sense of energetic and effective connection with their work activities and see themselves as able to deal with the demands of their jobs (Schaufeli et al., 2006, p. 702). Unlike stress or burnout, which are related to job demands (such as work intensity or long hours), engagement appears to be more closely related to job resources (Bakker et al., 2005a). Job resources that have been associated with work engagement include perceived level of control and autonomy, training, social support and supportive relationships (Maslach and Leiter, 1997; Bakker et al., 2005b; Koyuncu et al., 2006). These factors are more likely to be present in higher status jobs, and so job and organizational type may also be relevant predictors of work engagement. While almost all research on work engagement focuses on organizational factors, there is some evidence that family resources such as spousal support may also be relevant and influence work engagement (Bakker et al., 2005b), indicating a need to extend research to the study of non-work influences (Lewis et al., 2008a). Based on Greenhaus and Powell’s (2006) argument that the potential effects of job and family resources are stronger if roles are more salient, Lewis et al. (2008a) argue that work engagement is related to the work–home enrichment process. Highly work-engaged employees


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are likely to experience their work roles as highly salient and as such impact the enrichment process. Unlike the scarcity hypothesis, which predicts that high levels of work engagement will deplete energy and resources available for the family, the role-expansion hypothesis suggests that work engagement may generate self-esteem and other social or economic resources that enrich family as well as working life. There has been little research on work engagement and work–family enrichment, but Rothbard (2001) provided evidence that engagement in multiple roles (work engagement and family engagement) can be enriching. The extent to which job and household demands and resources impact feelings of stress, work engagement, work–life interference and enrichment depends largely on contextual factors; that is, how work is organized at the workplace, the workplace culture and the wider societal context.

3 Impact of workplace context The quality of an employee’s work and other life domains is naturally related to his or her workplace experiences. It is here that global trends and national public policies and regulations are played out. In particular, organizational culture – the prevailing but often unarticulated norms, values and assumptions that underpin working practices – can either support or challenge quality of life (Rapoport et al., 2002; Lewis and Cooper, 2005). These assumptions are often highly gendered (Acker, 1990; Swanberg, 2004; Bailyn, 2006); in other words, they are predicated on an image of the ideal worker as someone who can work full time and often excessive hours and will not allow family or other obligations to interfere with work (Rapoport et al., 2002; Bailyn, 2006; Van Echtelt et al., 2009). Such assumptions can lead to a failure to challenge inefficient ways of working, because ‘this is how things have always been done’ (Rapoport et al., 2002). This ideal worker myth may have been appropriate when men were either single or the primary breadwinners, but it is increasingly outdated and can create demands that conflict with other needs. In a gendered culture, those who work part time or flexibly are often marginalized, regarded as second-class workers. Thus, while flexible or work–life balance policies may be potential resources, cultural norms may limit those who are willing to make use of them, or stigmatize those who do, with implications for quality of work and private life. Managerial support is a well-established resource for achieving quality or managing work and private life (Lewis, 2001; Den Dulk and Peper,





2007). However, the extent of that support may also be influenced by the demands that managers face in intensified workplaces, as well as the degree to which they endorse the ideal worker myth. More recently, support by colleagues has also been identified as a crucial resource, but this too can be compromised by intensified workloads, particularly in teams where one worker’s absence has to be covered by his or her already overloaded colleagues (Bäck-Wiklund and Plantin, 2007; Lewis et al., 2009a). Focusing on the positive as well as the negative aspects of working allows us to develop hypotheses about the well-being or health of organizations that go beyond the absence of stress and illness, as discussed in Chapter 10. Taking a holistic view, healthy organizations are those that are effective in what they do and also meet the needs of their workforce, recognizing that individual and organizational health are interdependent (McHugh and Brotherton, 2000; Cernigoj Sadar, 2005). In our explorations of healthy organizations in this book, we focus on both employee and workplace needs and address a dual agenda of employee quality of life and workplace effectiveness (Rapoport et al., 2002; Lewis and Cooper, 2005. We also incorporate the notion of the social sustainability of organizations (Webster, 2004; Lewis et al., 2007) in our definition. This involves thinking about the potential health of organizations in the future as well as in the current context.

4 Impact of the institutional context So far we have discussed how individual and workplace-related factors affect the quality of work and life for service sector workers. Studies of inequality and differences in life courses across countries tend to show fairly consistent patterns, however, challenging researchers to look at inequality-generating processes and outcomes that in fact may vary more widely between societies (Mayer, 2005, p. 19). With a growing number of countries joining the EU, it is also interesting to explore how different institutional configurations impact on individual lives. The countries included in this study differ in the way they address quality of work and life and in the public policies and regulations they have in place. Finland and Sweden combine a high level of state-funded social protection and support for full-time employment among men and women. Both countries have generous public work–life policies supporting the combination of work and family life in all life stages. In the Netherlands and Germany, public work–life policies are more modest and the one-and-a-half breadwinner model – in which men work full time and women part time – is dominant. In the UK, public support


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for the work–life balance is also modest and more emphasis is placed on the market as a provider of services. Portugal has a low level of state support for the work–life balance, little labour market flexibility and a relatively low standard of living compared with the western countries in this study. The two eastern European countries in this study also have a lower standard of living and a moderate level of public work–life policies combined with more precarious labour market conditions and low expectations of employer support (Kovacheva et al., 2006; see also Chapter 3). Public work–life policies and social protection by the state can clearly serve as resources for quality of life. When more emphasis is placed on the market, inequalities are likely to occur. Chapter 3 will elaborate on the role of the institutional context and differences and similarities across countries.

5 Gender perspective in relation to quality of work and life Each element of the theoretical model discussed above is gendered; that is, women and men’s quality of work and quality of life are affected differently by job and household demands and resources. The workplace is not gender-neutral, despite the disembodied, genderless, abstract notion of the worker in organizational logic (Acker, 1990). The career track is masculine in nature; it is based on a male notion and experience of ‘job’. In the corporate world, the ideal worker is a man whose life centres on his job while a woman takes care of his personal needs and his children (Acker, 1990; Hochschild, 1994). Institutional hierarchies, power relationships and the gender-typing of jobs are all signs of male domination in the workplace. Despite women’s increasing labour market participation, and national and company-level policies to assist working women with their double burden, the basic gender patterns of labour division have not fundamentally changed (Hochschild, 1989; Burchell et al., 2007). This section outlines general trends related to the gendered nature of quality of work and life, based on the literature and data drawn from the 2003 European Quality of Life Survey (EQLS). Gender-related findings in our sample data are discussed in Chapter 9. Research shows that in all the countries participating in our survey, women spend less time doing paid work than men but spend disproportionately more time doing domestic work (see Kovacheva et al., 2006). Women need more resources to balance their work and domestic duties, and the 2003 European Quality of Life Survey shows that a good work– life balance has a higher impact on women’s overall life satisfaction than on men’s (see Beham et al., 2008). According to the EQLS data, job insecurity has a particularly negative effect on men’s quality of life





where differences in gender roles are more pronounced and men see themselves as (primary) breadwinners. For women, job insecurity has a statistically significant effect only in Hungary, Bulgaria and Finland, where female full-time employment prevails and is expected. Flexible working arrangements are aimed at helping employees manage their work–life balance. Women who are primary caretakers at home have little flexibility and few resources in their private life and may prefer predictable work schedules. Work–life balance is especially difficult for women to maintain in societies with traditional, rigid gender roles, for example in Hungary, where a woman does about 80 per cent of the housework, even if her job is more prestigious and better paid than her male partner’s – a situation that has not significantly changed in the past 25–30 years (Frey, 2006). According to EUROSTAT 2004 data, employed women in Hungary spend more time on both wage-earning work and domestic work than any other nationality in Europe (cited in Horváth et al., 2006). Not surprisingly, of the countries participating in our survey, it is only Hungary where having a partner clearly increases life satisfaction for men but not for women (Beham et al., 2008). The gender wage gap was 15 per cent in the EU27 countries in 2006. In Hungary and Bulgaria there has been a significant reduction in the wage gap in the past decade, whereas in the EU the gap has only declined by 1 per cent (Hungarian Central Statistical Office, 2008). Persistent horizontal and vertical segregation within and between professions means that a woman with the same qualification as a man may earn less, as women work in greater numbers in less well-paid professions and sectors (Reskin and Roos, 1990; Reskin, 1993; Burchell et al., 2007). A family-friendly organizational culture, supervisor support and family-friendly benefits and policies, both on the company and state level, very often mean women-friendly or mother-friendly measures, since balancing work, household and childcare duties is primarily seen as the task of employed women, not men. These policies are doubleedged swords: on the one hand, they may alleviate women’s double burden to some extent, but on the other they contribute to the persistence of traditional gender roles and women’s disadvantaged position in the labour market (Jacobs and Gerson, 2004; Mandel and Semyonov, 2005).


30

6 In summary This chapter discussed the theoretical framework of our study. Using the demands-resources approach, we argued that demands and resources at


31

work and in the household impact on the quality of life directly and indirectly via such outcomes as stress, work engagement, satisfaction with work–life balance, work–home interference and enrichment. The demands and resources available and their impact are also shaped by the workplace context and the relevant country’s social policies and regulations and labour market conditions. Our discussion of the theoretical framework has shown us what a complex concept quality of life is. To fully grasp its meaning, we must take not only household and workplace characteristics into account but also the institutional context. Comparisons of European countries reveal both similarities and differences. We have argued that the demands on parenting have increased across Europe. Research on trends in job demands suggests that working life too has become more demanding for many workers, due to work intensification and job insecurity (for example, Green, 2006; Lewis et al., 2009a). In some countries, however, these demands may be offset by the availability of part-time work and social protection against unemployment. We are also seeing more work–life policies being introduced in many countries. The necessary change in organizational culture that enables people to actually use these policies is lagging behind, however. Whether workers can compensate for this by drawing on resources at home, such as help from family and friends, remains to be seen. In addition, training opportunities have declined and, in some countries, so has job autonomy (European Foundation, 2009). Where this is the case, we expect to see a poorer quality of life among service sector workers. The advantage of our theoretical model is that it is broad and focused at the same time, giving us leeway to test several parts of the model empirically. Chapters 5–9 examine and test the relationships hypothesized in our theoretical framework. That framework is also a valuable starting point for exploring certain relationships in greater depth, as can be seen in Chapters 10 and 11. In all these chapters, the institutional context plays an important role in understanding quality of life. We therefore first discuss the institutional context of the countries included in this study in more detail and follow up this discussion by hypothesizing on the differences we expect to find between them. Chapter 4 discusses the research design.




The Institutional Context of the Quality of Life Siyka Kovacheva, Anneke van Doorne-Huiskes and Timo Anttila

1 Introduction In this chapter we analyse the institutional context in eight European countries by examining economic, labour market and demographic trends and changes in employment and family policies in each one. Institutional contexts matter. Male and female employees in Europe cannot escape the wider institutional environment and the cultural and structural conditions of their countries, either in their work or their private lives. Less supportive contexts may have a negative influence on the quality of life and work. Our analysis concentrates on the macro level: the country-specific institutional arrangements that impact on the quality of life without being part of it, strictly speaking. We provide the necessary background for subsequent chapters, which focus on the meso (organizational) and micro (individual and household) levels, making use of the quantitative and qualitative data collected in the Quality project. The purpose of this chapter is essentially to describe similarities and differences across the eight Quality countries. Our main question is whether and to what extent differences in institutional contexts indicate different attitudes towards life and work by the citizens of the various countries. In cross-national comparative research, the institutional context is a broad concept encompassing elements of both social structure and culture (Hantrais, 1999; Mills et al., 2006). The structural aspect is important; individuals base their strategies on the opportunity structures created by society at large, by the companies that employ them and by their family and community relationships. Information on individual and household values and strategies is taken from the Quality survey and the qualitative part of the study, discussed in the following chapters.


3

32


The countries analysed in this study are a very mixed group. They include countries where the national GDP per capita is well above the EU average, such as the Netherlands, and countries where the GDP is less than half the EU average, such as Bulgaria; countries with high activity rates for both genders, such as Sweden, and countries with an aboveaverage share of inactive women, such as Hungary. Also included are countries with expanding populations, such as the UK, and countries with declining populations, such as Germany; countries with high levels of expenditure on family policies, such as Finland, and countries with low levels of expenditure, such as Portugal. How can we make sense of the many institutional arrangements that affect the conditions for achieving quality of work and quality of life in the eight countries?

2 Citizens and states, lives and policies The countries included in the Quality project were chosen in accordance with the theory of welfare policy regimes and its categorization system. While the interplay of mechanisms providing social security and guaranteeing quality of work and life is country-specific, there are some common modes of combining the roles of the state, market and family, which Esping-Andersen (1990) defined as welfare state regimes. The regimes reflect the ‘institutional arrangements, rules and understandings that guide and shape concurrent social policy decisions, expenditure developments, problem definitions, and even the respond-and-demand structure of citizens and welfare consumers’ (1990, p. 80). The various regimes differ in two essential ways: in their de-commodification, or the degree to which individuals and their families maintain a ‘socially acceptable standard of living’ (1990, p. 37) independent of their participation in the labour market; and in their social stratification, or the degree and type of social inequality they produce. Esping-Andersen suggested a distinction between three clusters: ‘liberal’, ‘corporatist’ and ‘social-democratic’. This typology is neither the first to be proposed, nor has it been uncontested since its publication (see Abramson, 1999). Other classifications are gender regimes (Lewis, 1992; Pascall and Kwak, 2005), production and employment regimes (Gallie, 2007), family (Pfau-Effinger, 2005) and work-care (Haas, 2003) typologies, all involving differing sets of indicators. We find the welfare regime concept useful because it explains the contexts, the ‘frameworks of historical institutionalization that differ qualitatively between countries’ (Esping-Andersen, 1990, p. 80). For example, de-commodification


Siyka Kovacheva et al. 33


The Institutional Context

goes furthest in the social-democratic regime, and social stratification has moved far beyond the initial stage created by the market to universal social citizenship. The state is the leading social institution providing social protection, minimizing reliance on the family and maximizing capacities for individual independence. The corporatist regime, on the other hand, offers less support for the de-commodification of social rights and services and concentrates on preserving status differentials. The role of the state is smaller and individuals rely more on the resources of the family, fostered by the Church and its emphasis on tradition. The liberal regime has the lowest degree of de-commodification and the highest level of inequality, based on dual stratification: a market-based hierarchy of access to goods and services and equal, but minimal, social protection. Here, the market is the main care provider, followed by the family, while the state plays a marginal role in distributing resources. Various attempts have been made to modify this typology, the most significant proposing the inclusion of at least one new type – that of the sub-protective (Mediterranean) cluster (Ferrera, 1996; Gallie and Paugnam, 2000; Scheepers et al., 2002; Gallie, 2007). This regime, which Esping-Andersen sees as part of the corporatist cluster, has the lowest level of state-funded social security. Social capital is crucial to achieving an acceptable quality of life, and people’s social contacts and the care provided by family and friends play a major role in their coping strategies (Scheepers et al., 2002). The social upheaval in Central and Eastern Europe in the 1990s leads us to question whether the former Eastern Bloc countries now constitute a new type of welfare state or whether they are accepting the features of existing models in the West. While researchers agree that these countries have started from a similar institutional system (Deacon and Szalai, 1990; Ferge, 2001), after almost 20 years of reform there is still no accepted classification of their policy regimes. What we see at present are mixed regimes combining elements from the other models – liberal, corporatist or sub-protective (Kovacheva, 2000; Potucek, 2004). They are often seen to be moving in different directions (Fodor et al., 2002), prompting Wallace (2002) to distinguish between the ‘re-institutionalizing’ regime in Hungary and the ‘de-institutionalizing’ regime in Bulgaria. This distinction, however, is descriptive rather than based on analytical typologies and refers more to the current stage of welfare reform in each country than to concrete patterns in the welfare mix. The countries in the Quality study have been grouped into the five main welfare regimes: social-democratic/universalistic (Sweden and


34


Finland), corporatist/conservative (Germany and the Netherlands), liberal (the UK), sub-protective/Mediterranean (Portugal), and postsocialist (Hungary and Bulgaria). Below we look at how the different welfare states encourage or inhibit their citizens’ quality of work and life. We do this on the basis of two other aims: to analyse socio-economic trends in employment patterns, work, fertility and family structures; and to explore current trends in public policies on employment and family life, with an expected impact on the work–life balance. To meet these objectives, we make use of official statistics from Eurostat and European and national policy documents.

3 Changes in work and family life The decade preceding the current economic downturn which started in Europe in 2008 was characterized by years of economic stability in most European countries, with the new European Union member states significantly increasing their economic output. In 2007, Hungary’s GDP per capita had almost caught up with Portugal’s, and Bulgaria had managed to increase its GDP by more than a third compared with 1997. By 2008, however, most countries had been hit by the economic recession and were registering negative economic growth. There are still major differences in the standard of living across the eight countries, with GDP per capita in purchasing power standards (PPS) in the Netherlands being 3.6 times higher than in Bulgaria. Within-country differences in material well-being also have a significant impact on individual quality of life. Previous research has shown that social inequalities have a stronger effect on life satisfaction in poorer societies (Fahey and Smyth, 2004; Böhnke, 2008). Figure 3.1 shows the eight countries grouped according to these two economic indicators. The UK belongs to the group of wealthy countries, with a GDP per capita of 118.9 per cent (EU27 = 100%) and with high inequality in income distribution as measured by the Gini index. In contrast, Hungary and Bulgaria belong to the group of countries with low economic output and low income inequality. Portugal is among the poorest and most unequal European societies, with a Gini index of 37. The four Northern and Western European countries form the group with high living standards and low inequality, the Gini indices of the two social-democratic states (Sweden and Finland) being lower than those of the corporatist states (Germany and the Netherlands). Inequality in most countries has risen over time, although by only a few percentage points or fluctuating at the same level. The two




36


40 38 PT

36 34

GDP per capita in PPS (EU27 = 100) 50

70 HU

90

28 26 24

BG

22 20 Figure 3.1

EU27 110

DE 130

150 NL

Gini coefficient

30 30

FI SE

Countries grouping according to macro-economic indicators

Source: Eurostat (http://epp.eurostat.ec.europa.eu/portal/page/portal/structural_indicators/).

post-socialist countries experienced a steeper rise than the other countries in the first few years of market liberalization, followed by stabilization at a level below the EU average. Nevertheless, because social equality was greater when they began their reforms in 1989 (UNDP, 1999), there are widespread feelings of injustice in the two countries about the new income distribution and the widening welfare gap between East and West (Sirovatka and Bartakova, 2008). Children and the elderly are at greater risk of poverty than other groups. In all the countries surveyed, people in paid employment tend to have lower rates of relative poverty than those who do not work. Workers who have completed compulsory education or less or who are on part-time or temporary contracts are most often found among the working poor. In countries such as Bulgaria, poverty is becoming feminized, whereas in Hungary, for example, women and men run an equal risk of falling into poverty (Fodor, 2002). 3.1 Labour market changes Labour market trends in the eight countries surveyed followed common European trends in the past 10 years, but there were also significant differences between them. Until 2007, economic activity rates continued to rise in most countries, as did the degree of work flexibility. We


UK

32


define work flexibility as atypical employment terms (e.g. temporary or fixed-term employment), working time (most typically part-time work) and workplace (such as telecommuting or differing workplaces; see Atkinson and Meager, 1986; Wallace, 2003). Hungary was the only EU country in our survey to register a decline in employment in 2007, but by 2008, the others had also begun to feel the turmoil in the international financial markets and declining fuel supply in their employment figures. Women and men in Europe still have significantly different career and employment opportunities. In all the countries surveyed, employment conditions are more favourable to men than to women. European labour markets tend to be unfavourable to two other vulnerable groups: the young (aged 15–24) and older workers (aged 55–64). Young workers have been hit hardest by the economic recession. Their job prospects are greatest in the Netherlands, whereas older workers are better placed in the Swedish labour market. Both types of flexibility (part-time and fixed-term jobs) are more typical of younger and older workers (Kovacheva and Pohl, 2007).

3.2 Trends in family life The population of Europe continued to increase slowly in the past 10 years, mainly as a result of rising longevity and international migration (EOSS, 2008), accompanied by changes in family patterns and reproductive behaviour. One important trend shared by the countries surveyed is the postponement of parenthood. The mean age at which women have their first child has increased by about two years in most countries in the past 10 years. As an absolute value, first-time mothers are oldest in the Nordic countries and the Netherlands, peaking at 30.58 years in the latter (Eurostat, data for 2006). First-time mothers in Bulgaria are the youngest at 24.57 years. Women in Hungary experienced the steepest increase, from 26.31 years in 1995 to 28.7 years in 2006. During the communist era, people in Hungary and Bulgaria tended to marry early and have children quite young, stimulated by the pro-natalist policy of the state (Mozni, 1994). With the start of the transition to a pluralist society, both marriage and fertility rates dropped significantly. The same trend had appeared much earlier in the old member states, associated more with lifestyle changes than with economic and political upheavals as in Central and Eastern Europe. Childbirth outside of marriage has also





risen dramatically; in 2007, more than half of children in Sweden and Bulgaria had been born outside of marriage, and only in Germany did this group constitute less than a third of the child population. Another common development, evident since the 1970s is the decline in family size, although the trend for smaller families has been minimal or even reversed since 2000 in such countries as Sweden, Finland and the UK. In many countries, fertility declined by half when measured over a longer time period. In Portugal, for example, fertility dropped from 3.0 children in 1968 to 1.5 children in 1993, and in Germany from 2.5 children in 1963 to 1.2 children in 1995. The two post-socialist countries, Bulgaria and Hungary, recorded a drop of almost 0.5 children from 1992 to 1997 and 1999 respectively, but since then fertility has started to rise in these countries as well. We see a similar pattern in Germany – first a decline (although much smaller than the two CEE, Central and Eastern European, countries) in the first five years after the reunification of West and East Germany and then a slight increase. The UK, Finland and Sweden presently have the highest total fertility rates (around 1.8), followed by the Netherlands (1.7), while the four remaining survey countries have much lower rates (slightly more than 1.3). Countryspecific factors such as ethnicity, education and income, availability of support from the extended family or of community childcare facilities, family structure and individual preferences all result in significant differences in fertility patterns. Rising life expectancy and low fertility rates have had one major effect: the population in the Quality project countries is ageing, as it is in Europe as a whole. The European Observatory on the Social Situation (2008) has identified the ageing population as the overriding challenge facing Europe. The trend is strongest in Germany and Bulgaria and least evident in the Netherlands and the UK. In most countries, the number of young people (aged 0–14) is declining with some short-term fluctuations, while the number and relative share of the population accounted for by those aged 65 and, particularly, 80 and older is rising. Bulgaria and Germany have the fewest young people in Europe, with only one out of eight inhabitants in these countries being younger than 14 (IFP, 2008). In Germany, one out of five inhabitants is aged 65 or older, giving it the oldest population in Europe (together with Italy). The changing age structure of the population will have a significant effect on the social protection system and public policies, as well as on the need for lifelong learning (Figure 3.2). Looking at our eight countries’ employment and demographic trends, we see there are two broad groups: one with both low fertility and low


38


Siyka Kovacheva et al. 39 % 80.0

TFR 2

75 1.84

70.0

1.85

1.84 1.7

1.8 1.6

60.0 1.37

1.35

1.4

1.32 45.8

1.2

42.4

40

40.0 30.0

57.6

50.9

20.0

61.9

64.0

65.5

68.5

69.6

71.8

0.8 0.6

19.3

16.9

1

0.4 10.0

4.1

0.2

2.1

0.0

0 HU

BG

PT

women's activity rate

Figure 3.2

DE

UK

FI

women in part-time jobs

NL

SE

total fertility rate

Women’s activity rates, part-time work and fertility in 2006

Source: Eurostat, LFS and Population and Social Conditions (http://epp.eurostat.ec.europa.eu/ portal/page/portal/employment_unemployment_lfs/data/database and http://epp.eurostat. ec.europa.eu/portal/page/portal/population/data/database).

female employment rates (Hungary, Bulgaria, Portugal and Germany) and the other with high fertility and high female employment rates (Sweden, Finland, the Netherlands and the UK). The link between women’s fertility rates and employment rates suggests that women’s greater involvement in the labour market in the past 15–20 years has not necessarily lessened their desire to have children and start a family. Reducing women’s working hours also does not lead to them having more children. Portugal and Finland, for example, have similar percentages of women working part-time but significantly different fertility rates. More women in Germany hold part-time jobs than in Sweden, but they tend to have fewer children. Flexible work arrangements that reduce the number of working hours do not encourage parents to have more children. To better understand the institutional framework of the quality of work and life in the countries under study, we must examine their job security and family support policies.


1.34

50.0

4 Employment policies Gallie (2007) takes the extent of state intervention in the labour market and the corresponding power relations as a basis for distinguishing



three types of employment regimes: inclusive (with extensive labour market rules); dualist (insider–outsider divisions); and market regimes (rules are kept to a minimum). According to this system, the two Nordic countries represent the inclusive regime, Germany belongs to the dualist regime, and the UK to the market regime. The remaining four countries do not fit neatly into one or other of these three regimes, as they manage to combine contrasting elements of worker protection and market freedom. In terms of social protection expenditure, we have seen contradictory trends in the past 10 years – varying rates of decline in most of the countries and a significant rise in Portugal. Sweden spends the most on social protection as a percentage of GDP, followed by Germany, Finland and the Netherlands. Bulgaria, Hungary and Portugal spend the least (less than 25 per cent of GDP) and the UK takes a middle position. All eight countries have developed a variety of policy measures targeting specific groups with weak labour market attachment and vulnerable to social exclusion, such as older employees, women (and mothers in particular), the young, the disabled, low-skilled workers, ethnic minorities and immigrants. Policies promoting the participation of older workers have focused on protecting employees against age discrimination. All countries see gender equality in employment as a main policy objective and have implemented policies specifically promoting the labour market participation of women. Women have historically had a prominent place in the Swedish labour market, fostered by an expansion in maternity/parental leave and childcare facilities, reforms in the educational system promoting equal opportunities in education, the adoption of the Equal Opportunity Act in 1977, and the introduction of labour market policies that addressed the needs of working women. At the other end of the spectrum is the Netherlands, where female employment rates are lower than the European average, particularly in terms of the number of working hours. The Dutch government has introduced tax measures reducing the gap between gross and net wages, making it more rewarding to work additional hours. The main instruments used by the British government to encourage female participation in the labour market are the National Childcare Strategy and the Working Family Tax Credit, targeting lone mothers and mothers of young children by increasing the tax credit payable for younger children (Lewis and Purcell, 2006). Most of the Quality project countries have promoted flexible working both as an alternative to rising unemployment in times of economic recession and as a means of achieving a better work–life balance. They


40


have implemented a variety of policy measures leading to the growth of flexible working practices. Many of these encourage working time flexibility, but only a few are devoted to flexible workplaces, such as encouraging employees to work from home or to change workplaces. One measure with dubious consequences for the quality of work is flexibility in contractual terms and conditions. While the number of fixed-term contracts has fallen in Bulgaria since the end of the 1990s, in Finland temporary contracts for less than a year have been promoted even in the public sector. A major difference in the countries’ policies is whether flexibility is employer-led or employee-led (Wallace, 2004). Flexibility can have different effects on people’s quality of work and quality of life, depending on whether companies have reduced worker protection and increased job insecurity in response to global competition or whether employees have requested flexible working patterns in order to achieve a better work–life balance. One important aspect of the institutional context is the legal framework and the nature of the social dialogue. Trade unions have played a leading role in constructing the European Social Model throughout the twentieth century, first by developing social protection legislation on the national level and then by disseminating it on a wider basis. In the past 20 years, employers’ associations have intensified their activities at the European level, insisting on promoting flexible employment or preventing ‘social dumping’. Yet the impact of the social dialogue on the quality of life varies greatly from one country to the next, depending on the degree of unionization and the established traditions of the social dialogue. In the eight countries surveyed, union density in 2006 varied between 80 per cent in Sweden and 74 per cent in Finland to only 15 per cent in Portugal (Fulton, 2007). The Nordic countries have a history of strong ties between the state and the trade unions. Despite a recent minor decline in the traditionally high membership rate (Taipale and Hirvonen, 2006), collective bargaining is still the main method used to settle labour market issues. The Nordic countries have well-developed, clearly defined employer and employee organizations with high membership densities; in addition, both organizations evolved before the modern labour market and both were involved in defining and developing the framework for the model (Lane et al., 2006). In the UK, trade union density declined during most of the 1990s, but the trend has recently been reversed to some extent. The social partners are not regularly involved in policy-making – wage negotiations in particular tend to be decentralized. However, the topic of quality of life has been widely debated by the trade unions in the UK





(Lewis and Purcell, 2006). In Germany, union density has dropped from every third employee in 1991 to every fifth in 2004. As a result, collective wage agreements have been abandoned or ignored in many cases. The two post-socialist countries restored the freedom to organize in the early 1990s, leading to the founding of many independent trade unions and employers’ associations. The transition to a market economy, however, led to a decline in the influence of the trade unions: the closure of large state enterprises and mass unemployment meant a sharp fall in union membership. Trade unions do not exert a strong influence on newly established small and medium-sized enterprises, which constitute the bulk of the two countries’ economies. The Portuguese government has met serious opposition recently from the trade unions, which are against its efforts to raise the age of retirement and reduce retirement provisions (Guerreiro and Rodrigues, 2006). Although collective agreements also cover working hours, the organization of flexible working time and paternity and maternity leave, they still focus mainly on wages and financial matters (Table 3.1). Summing up our review of employment policies affecting the quality of work in the eight countries, we see that they generally resemble the designated welfare regime but also have some country-specific features within that overall context. The two countries that have a socialdemocratic regime provide high levels of social protection for their workers, guaranteed by high unionization levels and an active social dialogue. They have a moderate level of expenditure on labour market policy and offer the unemployed a wide range of options and personalized services. They also encourage flexible working, but not at the expense of the workers. The two corporatist countries, Germany and the Netherlands, also offer a high level of social protection, accompanied by policies encouraging the unemployed to find work. The social dialogue is influential in both countries, but unionization is declining in Germany. Work flexibility is particularly important in the Netherlands, which is a model of ‘flexicurity’ – that is, a high level of flexible employment matched by high standards of worker protection. The liberal regime in the UK is known for its relatively low level of social protection and highly flexible employment practices. Unemployment policy concentrates on getting the unemployed into work, while union density is moderate but declining somewhat in importance. Portugal, representing the sub-protective regime, offers a low level of social protection to employees and underdeveloped unionization. Labour market policies and measures intended to increase work flexibility are gaining momentum but are still minor compared with the other countries. Flexibility


42


Country-specific features of employment policies

Country

Welfare regime

Level of social protection expenditure

Level of labour market policy expenditure

Level of work flexibility

Level of unionization

Sweden Finland The Netherlands Germany The UK Portugal Hungary Bulgaria

Social-democratic Social-democratic Corporatist Corporatist Liberal Sub-protective Post-socialist Post-socialist

High High High High Medium Low Low Low

Medium Medium High High Low Low Low Low

Medium Medium High High High Low Low Low

High High Medium Medium Medium Low Low Low

43



Table 3.1


of employment is limited to temporary and fixed-term contracts, while part-time work is rare. The two post-socialist countries are similar in having moved from a high to a low level of social protection expenditure and from high union density to low. Policies encouraging flexibility exist but have not had much effect, and there is little public expenditure on labour market policies.

5 Family policies There has been growing concern at European level in recent years about the difficulties faced by families. It has been matched by a change in attitude: instead of considering the family a private domain in which the state interferes only when the family’s own resources are exhausted, more comprehensive forms of family support are now regarded as appropriate. Compared with employment policies, however, family policies at European level are few. It is up to each member state to define and implement such policies. Childcare benefits and services and parental leave are used by all eight countries, but to differing extents and with varying methods of funding. In terms of public expenditure on families, Germany, Sweden and Finland spend more than 3 per cent of GDP on family assistance, and Hungary is also above the European average. At the other end of the spectrum are Bulgaria and Portugal, which spend less than 1.2 per cent of GDP. The Netherlands and the UK occupy a middle position. In 2007, monthly benefits per dependent child (for the first child) varied from 154 euros in Germany to 11 euros in Bulgaria. Child benefits were universal in Germany, Sweden, Finland, the UK, the Netherlands and Hungary and means-tested in Bulgaria and Portugal. The eight Quality project countries differ in the provision and use of childcare facilities. In countries where public childcare provisions are a recent phenomenon, such as the UK and the Netherlands, the past 10 years have seen the expansion of such provisions and a rise in the number of children enrolled in both public and private care. In contrast, the formerly extensive state daycare system in Bulgaria and Hungary has declined, not so much because of the falling birth rate as the privatization of state assets. The Nordic countries are moving towards a more flexible range of childcare services, giving parents more choice between state, municipal, private and subsidized care at home. The more positive attitude towards formally organized childcare in the UK has not yet resulted in a wide network of affordable services, which still tend to be privately owned and expensive for parents earning low


44


to mid-range salaries. In addition, informal childcare provided by family members is becoming more popular (Lewis and Purcell, 2006). In contrast, employers in the Netherlands are expected to contribute to the cost of childcare; since 2008, childcare has been funded on a tripartite basis, with the state, the employer and the parents all paying a share. Dutch employers are also encouraged to buy or hire places for their employees in childcare centres and parents are entitled to choose their childcare provider (Veldhoen et al., 2006). Giving parents more choice in respect of childcare (i.e. allowing them to choose between subsidized, home, municipal and private daycare) is one of the main trends in current Finnish family policy. In south-western and south-eastern Europe, the tradition of informal help from the extended family is still very alive. Few children below the age of three go to pre-school, although the numbers have increased in the past 10 years in most of the countries, with the exception of the UK. In 2006, the number of three year olds in preschool varied between 34 per cent of children in Finland and 82 per cent in Sweden. The difference between the two Nordic countries is also very significant. In Finland, home care is still seen as more appropriate for children up to the age of three, while public care is more acceptable for three to six year olds. Almost all Finnish children aged six are in childcare. A similar pattern can be seen among six year olds in Sweden. The dominant trend in family leave policies has been their expansion in coverage, length (the UK and Portugal) and/or payments (Bulgaria). There are still enormous differences between countries in the types of care leave available, however. Many experts argue that the right to care and be cared for should be recognized as a civil right (Knijn and Kremer, 1997; Leira and Saraceno, 2002). It is the welfare policies, the institutional frameworks and the underlying values that have the most significant impact on the provision of care for dependents and the way in which this unpaid work in the home is combined with paid work outside the household. One of the key target groups of these policies consists of families with young children. In all eight countries, families with young children have several childcare options: maternity, paternity and parental leave; child sick leave; family emergency leave; informal help from the extended family and friends; formal childcare provided by state, municipal or private facilities; and various flexible working arrangements allowing employees to integrate paid work and unpaid care at home. Table 3.2 summarizes the most common statutory leave arrangements for parents of young children in each country. It shows that leave policies are generous and flexible in the social-democratic regime; they




Statutory leave arrangements for parents in January 2009∗ Maternity leave

Paternity leave Parental leave

Non-transferable leave for fathers

Leave for caring for a sick child

Flexibility of parental leave

60 days per child per year up to child’s twelfth birthday (80% of earnings)

Can be taken up to child’s eighth birthday. Very flexible, from full benefit to 1/8th of a normal working day. Allows parents to work full time or part time

Social-democratic/universalistic regime Sweden

–

10 days upon birth of child

60 days ‘Daddy 480 days shared Quota’ (80% of jointly by both earnings) parents. Of these, 390 days at 80% of earnings and 90 days at flat rate

Finland

105 weekdays, including Saturdays (earnings related with a minimum flat rate)

18 weekdays + option of 12 bonus days (earningsrelated with a minimum flat rate)

158 weekdays (a combination of earnings-related and flat rate)

12 (bonus) days when father uses last 12 days of parental leave (‘Daddy month’)

Maximum 4 days in a row (unpaid), compensation practices vary according to collective labour agreements

Both parents can take parental leave in up to two separate periods of at least 12 working days each. Parents can both work part time. They are entitled to Partial Parental Allowance

91 days unpaid after 1 year of employment

–

Right to ‘reasonable unpaid time off’ but for how long is at employer’s discretion

Right to request a flexible working schedule and reduced hours

Liberal regime The UK

14 days (flat Up to 365 days’ leave of which 273 rate) days are paid at a flat rate



46

Table 3.2

Germany

14 weeks: 6 weeks before the birth and 8 weeks (compulsory) following the birth (100% of earnings)

–

Paid leave: 12 months, or 14 if the other parent takes two more months (67% of earnings, minimum 300 euros, maximum 1800 euros) – Unpaid leave: 3 years maximum

–

10 days per year and child, paid/unpaid, 25 days maximum (20 days for lone parents, 50 days maximum)

Unpaid leave may be taken until child’s third birthday; with employer’s consent, 12 months can be taken between child’s third and eighth birthday. During unpaid leave, parent may work up to 30 hours per week

The Netherlands

112 days fully paid

2 days fully paid

182 days unpaid (26 weeks) up to the child’s eighth birthday (75% of earnings for civil servants)

26 weeks per parent per child. Not transferable between parents

10 days per year, paid at 70% of earnings

Entitlement to unpaid leave on a 50% part-time basis up to 12 months when child is under 8. Leave can be spread over a shorter or longer period or taken up in three separate periods, maximum

105 statutory days fully paid (to mothers or fathers) or 135 statutory days at 83% pay to mothers or fathers, if at least one month is taken exclusively by each parent.

10 optional days fully paid (in addition to the compulsory 10 days’ paternity leave)

Up to 30 days per year, paid at 60% of earnings

The 120 days’ leave can be taken as 150 days paid at 80% of earnings

Sub-protective/Mediterranean regime Portugal

6 statutory weeks fully paid

10 compulsory days fully paid

47



Corporatist/conservative regime

(Continuted) Maternity leave

Paternity leave

Parental leave

Non-transferable leave for fathers

Leave for caring for a sick child

Flexibility of parental leave

+ 3 optional months at 25% pay to father + 3 optional months at 25% pay to mother Post-socialist regime 410 days at 90% pay

15 days at 90% pay

365 days (paid, flat rate) + 365 days (unpaid)

–

60 days per year, fully paid

Can be taken by father, mother or one of their parents. The no unpaid leave can be taken up to child’s eighth birthday, provision for part-time leave, no specified right to request reduced working time

Hungary 180 days (6 months) at 70% pay

5 days fully paid

18 months at 70% pay with a maximum (70% of 2 × minimum wage) + 12 months paid at flat rate (minimum pension amount). Or as a universal right, 3 years, flat rate for those uninsured

5 fully paid days which must be taken before the child is 2 months old

2 days per child per year, fully paid. Additional leave depending on age of child and marital status, paid as sick leave (60–70% of average wages)

Full-time work is allowed after the child’s first birthday

Bulgaria

∗ Available to employees living as a couple and offering the greatest level of coverage while subject to various eligibility criteria in each country. Maternity leave: leave upon the birth of the child, reserved for the mother. Paternity leave: leave upon the birth of the child, reserved for the father. Parental leave (called also child-raising leave): may be taken by both parents and/or split into quotas reserved for the two genders. Non-transferable part: the number of days of parental leave reserved for fathers only. Child sick leave: leave to which parents are entitled to care for sick children; other arrangements cover care for adult family members. Flexibility of leave: whether leave can be taken up in several instalments and/or by working part time, and whether parents may reduce their working hours.



48

Table 3.2

offer parental choice, but also take gender equality in parental childcare responsibilities very seriously by providing longer parental leaves that both partners are eligible to take up, long fathers’ quotas, and no or short maternity leaves. The cultural norms underpinning this policy reflect the belief that support for childcare is as much the state’s responsibility as it is a family responsibility and that both partners have both the right to care and the right to work and a career. The liberal and conservative regimes are similar in offering short maternity and parental leaves and giving fathers little encouragement to care for their children. This reflects their understanding that childcare is primarily a private responsibility. One significant difference is that maternity leave in the corporatist regime of the Netherlands is fully paid, while in the liberal regime of the UK the mother’s right to paid care leave is contingent on eligibility criteria and not fully paid. The post-socialist regime offers long paid maternity leave and long paid parental leave (although at a low pay rate) with no serious concern for gender equality. While officially attesting to gender equality in employment, this policy is based on the assumption that caring for small children is a mother’s responsibility and that the father will join in caring for the children much later, if at all. Drawing upon a comparative study in 19 European countries, Wall (2007) presents a more detailed typology of parents’ leave policy models. She suggests six such models, based on duration, level of compensation and gender equality. According to this typology, Sweden represents the ‘one-year leave gender-equality-oriented pattern’, Finland the ‘parental choice oriented policy model’, Germany and Hungary the ‘long-leave mother home-centred policy model’, the UK and the Netherlands the ‘short-leave part-time mother policy model’, and Portugal the ‘early return to full-time work leave policy model’. There is no country in the Quality study that represents the ‘short-leave male breadwinner model’, typical of the Mediterranean countries in Southern Europe. Bulgaria, which is not included in Wall’s study, is close to ‘the long-leave mother home-centred policy model’ typical of the other post-socialist country, Hungary. However, it deviates from the model in that childcare services are widely available and the unpaid parental leave has a six-month father’s quota. The small amount of compensation paid during parental leave encourages many mothers in the middle and higher income groups to take only a short period of maternity leave at 90 per cent of earnings – a trend that may indicate the encroachment of another model based on short-term maternity leave. Wall also attests to ongoing changes within these models; Portugal, for example, has moved





from the ‘short-leave male breadwinner model’ to the ‘early return to full-time work leave policy model’. One recent trend in our eight countries is the adoption of policy measures encouraging fathers to play a larger role in family life and to get them more involved in caring for very young children. Sweden, for example, introduced the ‘daddy month’ in 1989 and extended it to two months in 2001. Sweden is, moreover, the only country that does not have maternity leave, which it abolished in 1994 (Ferrarini and Forssén, 2005), and fathers have access to all parental insurance schemes. Leave bonuses offered to working fathers in Finland have been quite effective, and an increasing number of fathers are now taking up parental leave. A recent law on parental leave in Germany extended the new incomebased payment to a maximum of 14 months if the other partner takes up leave for the final two months; the aim is to promote fathers’ involvement in childcare activities and to encourage a rise in fertility and an earlier return of mothers to paid employment. Paternity leave was introduced in the UK in 2006 under the Work and Families Act, which allows fathers to take up part of maternity leave as paid parental leave. The idea is to make it easier for mothers to re-enter the labour market, to increase fathers’ involvement in childcare and to achieve a more equal division of labour in the household. In Portugal, the law considers both parents equal when it comes to taking up parental leave; in addition, a father on parental leave enjoys the same protection against dismissal as a female worker who is pregnant, has recently given birth or is nursing a child. Bulgaria divided the third year of parental leave (unpaid) – available to parents with children under the age of eight – in two so that fathers and mothers can each take up six months; the father’s quota, however, can be transferred to the mother. Bulgarian law also permits one of the grandparents to take up the parental leave (provided he or she is employed), thus formalizing the informal practice of intergenerational support for childcare. When paid maternity leave was prolonged to 315 days in 2007 and then to 410 days in 2009, fathers were not allowed to take up any part of it initially. Under outside pressure, the law was amended so that fathers are currently allowed to take ‘maternity leave’ once the child is six months old. Attempts to increase the role of fathers are frustrated, however, by the reduction in income and consequent negative effect on family budgets and careers. Even in Sweden, where maternity leave was abolished more than 10 years ago, mothers still bear the primary responsibility for home and children, with persisting traditional gender roles and inequality. This brief review of family policies reveals different patterns of family support in the various policy regimes. In the countries with a liberal


50


regime, such as the UK, the main responsibility for individual well-being is borne by the individual and the family, while the state plays a minimal role and only when individuals and families have failed to protect themselves against risk. Child benefits are moderate and the market is the major provider of childcare, but employers are increasingly expected to offer parental leave and other family-friendly policies. Germany and the Netherlands belong to the cluster of countries that favour the traditional family model in their policies, with only one of the spouses being in paid work and the other caring for family members (Esping-Andersen, 1990; Fagnani, 2007). Child benefits are generous and universal. Instead of extended statutory parental leave, flexible working arrangements are used to integrate work and family. The Dutch tax system offers greater incentives to employers who provide childcare facilities. In the socialdemocratic countries, childcare is viewed as a responsibility shared between the state (and local government) and the family. There is an extensive set of public and private childcare options, as well as wellpaid, lengthy and flexible parental leave arrangements. In Finland, the market has recently begun to play a larger role in providing more flexible services. Tax reductions are either absent or insignificant compared with the role of child benefits and services. The post-socialist countries of Hungary and Bulgaria show a mix of contradictory changes in their family policies (Kovacheva, 2000; Fodor et al., 2002), moving from the generous state support of the one-party regime, with universalistic elements resembling that of the Scandinavian countries, to various new patterns adapting to the growing role of the market. Policies are more centralized than in the Scandinavian countries, and the state is expected to do more, although the family actually plays a much bigger role. Both countries have recently introduced tax-alleviation mechanisms, which are playing an increasingly important role. The sub-protective regime is often described as familialistic and Portugal is no exception. The family is the main institution providing childcare, and despite recent changes in state policy (increase in parental leave options and greater working time flexibility), financial pressure on households has prevented many parents from making use of the facilities. Child support is based mainly on family tax credits.



6 Conclusions What institutional trends have we found in the Quality project countries? They can be summed up as follows: growing similarity between and rising diversity within welfare regimes in supporting a higher



quality of life. Official statistical data on employment and demographic trends show that countries are converging in some significant ways; for example, they are all moving towards greater work flexibility, part-time work in particular. This trend is most prominent in the Netherlands and the UK and least evident in Hungary and Bulgaria. Family patterns are becoming more diverse in all countries, with marriage being postponed and the mean age of first-time mothers increasing. The decline in fertility seen in the 1990s slowed and was even reversed in most countries by the first decade of the twenty-first century. Prompted by the renewed European Policy Agenda and the open method of co-ordination, national policies are growing more similar in encouraging higher employment rates and gender equity in paid work, as well as more generous parental leave provisions and childcare services. At the same time, we have observed growing divergence within policy regimes. Within the corporatist regime, for example, the Netherlands is focusing on ‘flexicurity’ and high employment activity rates, especially for younger workers (15–24 year olds), whereas Germany is somewhat less flexible about work and offers more generous social benefits and higher spending on the aged and families. Within the social-democratic regime, Finland gives the market a greater role in providing more flexible childcare services, while Sweden places more emphasis on gender equality in parental leave and childcare. Portugal seems to be moving from the sub-protective regime typical of the Mediterranean to a weak corporatist regime, increasing its social protection expenditure and providing more support for childcare. Although starting from a similar model of centralized and universalistic provision of social services, the two post-socialist countries have moved to different blends of social-democratic, liberal, corporatist and sub-protective features. In this chapter, we examined the interplay between demographic and employment trends on the one hand and changes in the corresponding policies on the other. This allowed us to evaluate the role that the welfare regimes play in promoting quality of life. Table 3.3 shows the main features of the various institutional contexts as they relate to quality of life across the Quality project countries. We expect that the features typical of the social-democratic welfare states – greater employment security, more gender equality in both paid and unpaid work, and extensive state support for family care – will provide a better institutional context for quality of life than the material prosperity but lower levels of protection and equality of the corporatist and the liberal regimes. The countries in the sub-protective and post-socialist regimes tend to combine low living standards with


52


Institutional context for integrating work and family life

Welfare regime

Countries

Employment

Childcare

Rank in material well-being

Expected rank in quality of life

Socialdemocratic

Sweden

Generous state support for equal full-time participation of both partners

Generous state support for involvement of both partners

3

1

Finland

Generous social support for equal full-time participation of both partners

Variety of public and private support options for childcare

4

2

The Netherlands

‘Flexicurity’ (support for both full-time and part-time jobs) with women in part-time work

Moderate public support, major role for the family

1

3

Germany

Generous social support for full-time jobs, encouragement for flexibility

Moderate public support, major role for the family

5

4

Liberal

The UK

Moderate support for full-time jobs, high employer-led flexibility

Minimum public support, moderate support from the employer

2

5

Subprotective

Portugal

Minimal state support, low level of work flexibility

Minimum state support, generous family support

6

6

Postsocialist

Hungary


Moderate state support, generous family support

7

7

Bulgaria


Moderate state support, generous family support

8

8

Corporatist

53



Table 3.3


low levels of work flexibility and minimal or declining state support. Strong support from the extended family cushions the institutional deficiencies of the state and businesses in providing a decent quality of life. Policy models are not static; they are a moving target for social research. Path dependence has a significant impact but so have globalization, people’s rising aspirations and shifting views about the necessary reforms. Opinions are divided as to how globalization will impact on the European welfare states. Some claim that they must be trimmed in search of greater efficiency, others assume that they must expand in an effort to compensate (for a discussion and empirical testing, see Garrett and Mitchell, 2001). As policy institutions go through this process of modification and change, they face the challenge of the ‘individualization of the social’ (Ferge, 1997; Pascall and Lewis, 2004). While allowing greater freedom for diversification in employment and family patterns, they should at the same time resist the precarization of work and family life by investing more in citizenship rights. That is the only way to ensure a good balance between work and care and between flexibility and security, and to achieve a good quality of life.


54


4 Tanja van der Lippe, Stefan Szücs, Sonja Drobniˇc and Leila Billquist

1 Introduction The task of understanding the relationship between the quality of work and the quality of life in a changing Europe and testing the theoretical model described in Chapter 2 required a variety of data to be collected, from a variety of different sources (e.g. survey data, secondary data, interviews, innovation groups and scenarios). All these data were analysed in order to acquire a full and comprehensive understanding of the quality of work and life. We believe that the multi-method approach used here greatly increases the reliability of our findings. This chapter provides detailed information on our data and discusses the advantages and disadvantages of the various data sources. We begin by discussing the data available on quality of work and quality of life. Many large-scale surveys have been conducted in Europe in recent years relating to the quality of work or the quality of life. These studies gave us a basis for measuring the concepts derived from the theoretical model described in Chapter 2. We also collected our own quantitative data from organizations in all eight countries under study: the UK, Finland, Sweden, Germany, the Netherlands, Portugal, Hungary and Bulgaria. The chapter discusses the data-collection procedure, the content of the questionnaire, the advantages and disadvantages of collecting quantitative data in eight countries, measurement of the concepts in the theoretical model, the reliability and validity of the data, and methods for analysing such a large dataset. It then focuses on qualitative data. To obtain a better understanding of the healthy organization – defined as an organization that meets both its own and its employees’ needs – we interviewed employees in order to examine workplace changes and their impact on the current quality of work and life. Building on these interviews, we set up innovation groups in each


Data and Methods

55


Data and Methods

country to address the challenges involved in enhancing the quality of work and life. In the final part of the study, we performed a scenario analysis in all eight countries. This involved inviting high-level experts to develop scenarios that would help us understand the future quality of work and life in Europe. Scenario thinking is a construct of the intellect – a tool for ordering one’s perceptions about alternative future environments in which one’s decisions might be played out. This chapter discusses the value of performing a scenario analysis. Finally, combining all the data, we developed a social quality instrument that enables any interested employee to calculate the quality of his or her own work.

2 Secondary data Just as there is no standard or generally agreed definition of ‘quality of life’ and ‘quality of work’ (see Chapter 1), there is also no general agreement on how these concepts should be measured. Given the lack of a single composite measure, most studies adopt or suggest various key dimensions and rely on a set of objective or subjective indicators. Concerns about job quality – and consequently the measurement of job quality – have also become an important socio-economic policy issue, both at the international level, owing to the International Labour Organization’s definition of ‘decent work’ (1999), and at the European level, owing to the inclusion of ‘quality in work’ indicators in the European Employment Strategy in 2001 (European Commission, 2001). The European Union’s quality in work indicators are multi-dimensional in nature. There are 10 groups of indicators: intrinsic job quality; skills, life-long learning and career development; gender equality; health and safety at work; flexibility and security; inclusion and access to the labour market; work organization and work–life balance; social dialogue and worker involvement; diversity and non-discrimination; and overall economic performance and productivity. These indicators are both objective and subjective, but they have significant weaknesses. As discussed by Davoine et al. (2008), the concept of quality in work in the European Employment Strategy is weakly defined, and was established on the basis of political consensus rather than theoretical considerations. The growing relevance of quality of life and quality of work to policy has been accompanied by an increasing number of national and cross-national datasets that include indicators which may be relevant for the quality of life and work on the micro (individual) level. In


56


57

order to select the datasets most suitable to our research objectives, we specified a number of selection criteria and examined available data sources according to these criteria: (1) Secondary data must contain some measure of quality of life, such as overall life condition, satisfaction, or happiness; (2) Data sources must provide objective and subjective indicators in selected life domains, in particular measures on working conditions, household and family situation, satisfaction with work and family/private life, health and well-being; (3) all eight countries must be included in the dataset. We reviewed the following comparative datasets, focusing on the type and relevance of the information provided, the countries involved and the points in time for which information was available, looking briefly at issues of data quality such as comparability and survey response rates: European Quality of Life Survey, European Working Conditions Survey, World Value Survey, European Value Survey, European Social Survey, International Social Survey Program (‘Family and Changing Gender Roles’ and ‘Work Orientations’ modules), Eurobarometer, European Community Household Panel and European Community Statistics on Income and Living Conditions. In terms of content and country coverage, three datasets emerged as suitable sources of data on quality of life and work in Bulgaria, Finland, Germany, Hungary, the Netherlands, Portugal, Sweden and the UK: the European Quality of Life Survey (EQLS), the European Working Conditions Survey (EWCS) and the World Value and European Value Survey Series (WVS/EVS). The EQLS explores both subjective and objective aspects of quality of life in significant domains that shape the living conditions and opportunities of individuals. The questionnaire covers eight key issues of quality of life, for example economic situation, work–life balance and subjective well-being. The aim of the EWCS is to provide a comprehensive picture of how workers perceive and assess their working conditions and working lives in Europe. The domains and areas of work covered by the survey include the organization, social support, and health and wellbeing at work. Finally, WVS and EVS include a number of indicators for studying quality of life and work, such as perceptions of life and perceptions of work. Each of these surveys has specific advantages and disadvantages, and it is impossible to identify a single ideal dataset covering every aspect of quality of life and work. Nevertheless, analyses of secondary data sources revealed cross-country differences in quality of life and working conditions that served as a basis for conceptualizing and designing our own study on service sector employees.


Tanja van der Lippe et al.


58

Data and Methods

3 Survey of the service sector in eight European countries

To help us understand the quality of work and life of employees in eight European countries, we conducted a detailed employee survey covering major aspects of the respondents’ working lives as well as their individual and home situations. We decided to focus on service sector workers because the service sector is a growing sector of the economy but less widely researched (e.g. Ackroyd et al., 2005). Moreover, the service sector employs both lower skilled workers and professionals as well as a large number of female workers. Because we wanted to understand the specific organizational context, we selected the same four types of sector organizations in each country and had a national team of researchers survey employees in each of those four different organizations: a bank/insurance company, a retail company, an IT/telecom company and a public hospital. We selected these organizations because each one is subject to conditions that are likely to impact on employees’ quality of work and life. The extent to which these conditions prevail differs from one country to the next, of course. We selected a bank/insurance company because both traditional and modern ways of working can be expected there; a retail company because such companies tend to employ many women in lower skilled jobs; an IT/telecom company because they typically encourage career competition and employ many professionals; and a public hospital because they are significant workplaces for female professionals. Moreover, we expect hospitals to feel the brunt of economic and government policies, and this too might impact on quality of life. The data were collected in 2007. It was often time-consuming and difficult to get organizations to agree to participate in the survey. Many organizations were hesitant and requests took a long time to work their way through the organization. In some cases, the works council needed to be consulted before the research could start. We asked these organizations to co-operate both on the quantitative survey and on the interviews and innovation groups. In general, it is our impression that organizations were more interested in the interviews and the innovation groups than in the employee survey. Nowadays, many large companies conduct their own employee surveys, for example with respect to satisfaction with working conditions, and they therefore tend to view surveys from outside the company as superfluous. Moreover, organizations expect their employees to be busy and do not want to bother them by giving them extra work in the form of a questionnaire.


3.1 Getting access to organizations



59

The questionnaire covered the concepts as described in the theoretical model in Chapter 2. We asked about demands and resources in both the workplace and the employee’s private situation. Job demands include working hours, insecurity and work pressure, while job resources include support and social relationships at work, the use of flexible working arrangements and job autonomy. Household demands include care and domestic workload and the presence of children, while household resources include the presence of a partner and domestic and informal help in the household. We must note here that country-specific cultural differences were taken into account as much as possible in the questionnaire. A few examples illustrate how we went about this. Flexible working conditions are an important aspect of life in the Western European countries under study, and employees believe they make it possible to combine work and family life. Although flexible working conditions are almost non-existent in the two Eastern European countries under study, we nevertheless included questions about flexible working conditions. Another example is that employee representatives, such as a works council members, play an important role in the Nordic countries but not at all in the other European countries, but we still included this measure in our questionnaire. A final example is that in Portugal, as in other Southern European countries, informal care – that is, informal arrangements whereby family members outside the household, neighbours and friends provide childcare – is very important and more common than in other European countries. We therefore included informal care in the questionnaire. We furthermore operationalized concepts as much as possible according to internationally accepted standard scales so that the data would be comparable with other studies. This was the case for demands, resources and quality of life. Standard background variables were also measured using customary survey questions. It was not an easy task to apply the same questionnaire in all countries. For one thing, it had to be written in the language of the country concerned. Our approach was to develop the questionnaire in English and translate it into the various languages of the other participating countries. We then had the texts back-translated by English native speakers in order to check the translation and comparability between the questionnaires. Both a paper version and a web-based survey were available in the different languages. The researchers in the various countries often used a combination of paper and web-based surveys to collect the data, depending on the degree of computer access of employees across the different organizations. Bulgaria was the only country that


3.2 Developing the questionnaire


60

Data and Methods

3.3 Organizational information In addition to employee information, we also collected organizational data. This information was provided by the manager of Human Resources Management and included structural, cultural and policy factors in the respective organizations. Structural characteristics included the percentage of women in the workforce, the percentage of workers on temporary contracts and on sick leave, and turnover rate. We also asked the managers to compare the organization’s economic position to its competitors’. For organizational culture, we asked whether the organization was open or closed; performance-driven or characterized by social relationships; team-based or individual; informal or formal. Policies included flexible working practices, teleworking policy, compressed working week, enhanced leave policies such as maternity and paternity leave, childcare policy and equal opportunity policy. We also asked whether any major event (such as a takeover) had taken place in the research period, as that might have influenced the results. 3.4 Response rate We have calculated the response rate for each organization in every country. As shown in Table 4.1, the response rates vary from high in Sweden, Portugal and Bulgaria to low in Hungary and Germany. As a result, the database contains data from 32 different organizations across Table 4.1

Sample size and response rate

Bulgaria Finland Germany Hungary The Netherlands Portugal Sweden The UK Total a

Bank/ insurance

Retail

IT/Telecom

Hospital

Total

193 (60%) 218 (76%) 199 (32%) 204 (2%) 189 (38%) 527 (66%) 195 (79%) 193 (20%) 1918

200 (89%) 113 (35%) 167 (24%) 192 (17%) 305 (51%) 384a 107 (65%) 204 (20%) 1672

195 (57%) 472 (59%) 518 (35%) 401 (40%) 221 (44%) 299 (50%) 212 (71%) 308 (20%) 2626

201 (87%) 164 (47%) 317 (37%) 150 (2%) 313 (63%) 163a 162 (65%) 181 (20%) 1651

789 967 1201 947 1028 1373 676 886 7867


did not make use of the web survey. In all the other countries, the web survey was widely used as a tool for data collection. Employees received a letter in which they were asked to complete the questionnaire by filling in either the paper or the web-based version.

Response rates are not reported.



61

3.5 Measurement of concepts in line with the theoretical model Overall life satisfaction: Our measure of overall life satisfaction was based on a scale designed by Pavot and Diener (1993). Respondents were asked to rate a series of statements on a scale from 1 (strongly agree) to 7 (strongly disagree) (items reversed). The statements were: ‘In most ways my life is close to my ideal’; ‘The conditions of my life are excellent’; ‘I am satisfied with my life’; ‘So far I have got the important things I want in life’; and ‘If I could live my life over, I would change almost nothing’. The Alpha reliability coefficient for the scale was 0.88 (countries ranged from 0.84 to 0.90). Satisfaction with work–life balance: Satisfaction with work–life balance was measured on a three-item scale based on Valcour (2007). Respondents were asked to rate a series of statements on a scale from 1 (very satisfied) to 5 (very dissatisfied) (items reversed). The respondents had to indicate how satisfied or dissatisfied they were with ‘ . . . the way you divide your time between work and personal life’; ‘ . . . your ability to meet the needs of your job with those of your personal or family life’; and ‘ . . . the opportunity you have to perform your job well and yet be able to perform home-related duties adequately’. The latter item was originally developed by Rothausen (1994). The Alpha reliability coefficient for the scale was 0.89 (countries ranged from 0.85 to 0.93). Work engagement: Our measure of work engagement is a short version of the flow scale developed by Schaufeli et al. (2006). Respondents were asked to rate a series of statements on a scale from 1 (never) to 7 (always/every day). The statements were: ‘At my work, I feel bursting with energy’; ‘When I get up in the morning, I feel like going to work’; ‘I am enthusiastic about my job’; ‘My job inspires me’; ‘I am proud of the work that I do’; and ‘I feel happy when I am working intensely’. The Alpha reliability coefficient for the scale was 0.92.


eight countries and responses from 7867 employees. Of these, 68 per cent have a partner with whom they live. Of these couples, 86 per cent both have a paid job. Forty-six per cent have children living at home. The number of respondents do differ somewhat between the empirical chapters due to missings on specific variables.

Health status: Health status was measured by the question: ‘All in all, how would you describe your state of health these days?’ Respondents were asked to indicate their health status on a scale from 1 (excellent) to 4 (poor) (items reversed).


62

Data and Methods

Working hours: Working hours were measured by the following singleitem question: ‘How many hours do you actually work per week? Include overtime, whether paid or unpaid, but not your commuting time. Calculate hours for an average working week.’ Because of a large number of missing data for the variable working hours in the Finnish data, in order to consider Finland in the analysis, missing data for each respondent was replaced with the corresponding variable contracted hours. Work pressure: Our measure was taken from the job demand scale developed by Karasek and Theorell (1990). Respondents were asked to answer a series of questions on a scale from 1 (never) to 4 (always). The questions were: ‘Does your job require you to work fast?’; ‘Does your job require you to work very hard?’; ‘Do you feel that your job requires too much input from you?’; ‘Do you have enough time to complete your job?’ (item reversed); and ‘Does your job often make conflicting demands on you?’ The Alpha reliability coefficient for the scale was 0.73. Job insecurity: Our measure was based on the original 10-item 7-point scale developed by Kraimer et al. (2005). Respondents were asked to rate a series of statements on a scale from 1 (I strongly agree) to 5 (I strongly disagree). The statements were: ‘I am afraid I will lose my job’; ‘I worry about keeping my job’; ‘I am sure I can keep my job’ (item reversed); and ‘I think I might lose my job in the near future’. The Alpha reliability coefficient for the scale was 0.83. Commuting time: Commuting time was measured by the following single-item question: ‘How long does the journey between your home and your work take? Calculate the number of minutes for a one-way journey; if you have different workplaces or modes of transport, take the average.’ Career (work–life balance) demands: The career demand measure was based on the work-home culture scale developed by Dikkers et al. (2007) and Den Dulk and Peper (2007). The original scale has 18 items (including supervisor–colleague WLB support), of which we use items on career demands. Respondents were asked to rate a series of statements on a scale from 1 (I strongly agree) to 5 (I strongly disagree) (items reversed). The statements were: ‘To get ahead in this organization, employees are expected to work overtime on a regular basis’; ‘In order to be taken seriously in this organization, employees should work long days and be


3.6 Work-related indicators



63

Control over work, time and place: Our measure was based on the jobcontrol scale developed by Karasek and Theorell (1990). Respondents were asked to answer a series of questions on a scale from 1 (never) to 4 (always). They were asked the following questions: ‘Do you get to learn new things in your job?’; ‘Does your job involve repetitive tasks?’ (item reversed); ‘Are you free to decide how your job is to be done?’; ‘Are you free to decide what your job involves?’; and ‘Are you free to decide when you do your work?’ The Alpha reliability coefficient for the scale was 0.70. Social support: Social support was measured according to a scale developed by Karasek and Theorell (1990). Respondents were asked to rate a series of statements on a scale from 1 (I strongly agree) to 5 (I strongly disagree) (items reversed). The statements were: ‘There is a good spirit of unity in my workplace’; ‘My colleagues are there for me’; ‘People understand that I can have a bad day’; ‘I get on well with my superiors’; and ‘I get on well with my colleagues’. The Alpha reliability coefficient for the scale was 0.83. Supervisor–colleague (work–life balance) support: Our measure of supervisor–colleague WLB support was based on a scale developed by Dikkers et al. (2007) and Den Dulk and Peper (2007). It was based on an original 18-item scale (including career WLB demand), of which we use items on supervisor-colleague support. Respondents were asked to rate a series of statements from a scale of 1 (I strongly agree) to 5 (I strongly disagree) (items reversed). The statements were: ‘My direct superior supports employees who want to switch to less demanding jobs for private reasons’; ‘My direct superior supports employees who (temporarily) want to reduce their working hours for private reasons’; and ‘I am comfortable discussing my private life with my direct superior’. The Alpha reliability coefficient for the scale was 0.80. Training: We measured this variable by asking the respondents ‘Over the past 12 months, did you receive any education or training paid for by your employer?’ (Yes = 1, No = 0).


available all the time’; and ‘In this organization employees are expected to put their job before their private life when necessary’. The Alpha reliability coefficient for the scale was 0.85.

Supervisory position: We measured this variable by asking the respondents ‘Do you have a supervisory position?’ (Yes = 1, No = 0).


64

Data and Methods

3.7 Family indicators

Hours spent on care: Our measure was based on the question ‘Do you have care responsibilities for elderly parents or other relatives or friends? If yes, how many hours do you spend on this on average per week?’ Housework disagreements: Our measure was based on a single-item question (intended for couples) ‘How often do you and your partner disagree about sharing housework?’ Responses were (1) several times a week, (2) several times a month, (3) several times a year, (4) less often/rarely, (5) never (items reversed). In order to consider singles in the analyses, we included them in the mean of this variable and added a dummy for ‘married/living together’ or not. The respondents living in single households were assigned the mean score (2.37), as prescribed by Poortman and Kalmijn (2002, p. 184). Number of children at home: This variable was measured by asking the respondents ‘Do you have children living at home?’, with 0 indicating no children at home. Partner (married/living together): The presence of a partner in the household was measured by the following single-item question: ‘Are you currently married/living together?’. Household income: Our measure was based on the question ‘If you add up the income from all sources and all household members, which alternative below describes your total net income per month (wages, pensions, benefits, grants, allowances, etc.)? Net is after deduction of national and local taxes and after deduction of compulsory contributions to national social security. If you don’t know the exact figure, please estimate’. The alternatives ranged from (1) less than 150 euros, to (12) 10,000 euros or more. Number of persons with income in household: Our measure was based on the question ‘How many household members contribute to the household’s total income (including yourself)?’


Hours spent on housework: Our measure was based on the question ‘How much time do you spend on domestic work (laundry, cleaning, preparing meals, grocery shopping, etc.) on average per week?’

Paid domestic help: Our measure was developed within the Time Competition research project at Utrecht University (Van der Lippe and Peters, 2007). Respondents were asked to answer a question on a scale from 1



65

Childcare flexibility: Childcare flexibility was measured on a threeitem scale based on the Sloan foundation flexibility survey. Respondents (with children living at home) were asked to respond to a series of questions on a scale from 1 (very easy) to 5 (very difficult) or not applicable (items reversed). They were asked how easy it was for them ‘ . . . to find day care for your child/children?’; ‘ . . . to get adult supervision for your child/children before or after school?’; and ‘ . . . to make unanticipated child care arrangements? (e.g. unexpected delays, sick teacher)’. The Alpha reliability coefficient for the scale was 0.85. In order to consider respondents without children in the analysis, we included them in the mean of this variable and added a dummy for ‘having children living at home’ or not. The respondents with no children living at home were assigned the mean score (3.04), as prescribed by Poortman and Kalmijn (2002, p. 184). Social networks: Our measure was based on one of the items of the scale (quality time) developed by Galinsky (1999). Respondents were asked how often they spend leisure time with friends outside their home during a typical week. Responses were (1) less than once a week, (2) sometimes (once or twice a week), (3) often (three to four times a week), (4) always (every day), (missing data) not applicable. 3.8 Personal characteristics Gender: Gender was a dummy variable coded 0 = men and 1 = women. Education: The respondent’s level of education was measured by the International Standard Classification of Education’s (ISCED’s) classification, coded (1) not completed primary (compulsory) education, (2) primary education or first stage of basic education, (3) lower-level secondary education or second stage of basic education, (4) upper secondary education, (5) post-secondary, non-tertiary education, (6) first stage of tertiary education (not leading directly to an advanced research qualification), (7) second stage of tertiary education (leading directly to an advanced research qualification), and (8) other, please specify (missing data).


(never) to 4 (always). The question was ‘During a typical week, how often do you use paid domestic help?’

Age: Age was measured using the respondent’s year of birth. Table 4.2 shows the means of all variables per country.


Variables

Overall life satisfaction Satisfaction with work–life balance Work engagement (flow) Health status

Bulgaria

Finland

Germany

Hungary

4.19 3.35

4.86 3.43

4.70 3.38

4.22 3.25

4.78 2.91

4.62 2.93

4.67 2.80

44 2.91 2.43 33

NA 2.69 2.35 27

3.01 2.26

The Netherlands

Portugal

Sweden

UK

Eta

4.98 3.63

4.44 3.17

5.04 3.49

4.14 3.19

0.27∗∗∗ 0.17∗∗∗

4.97 2.84

5.29 3.06

5.11 2.97

5.02 3.14

4.20 2.82

0.26∗∗∗ 0.15∗∗∗

37 2.33 2.07 33

45 2.88 2.77 45

33 2.27 2.19 37

45 2.97 2.81 37

38 2.60 2.10 32

37 2.65 2.60 33

0.42∗∗∗ 0.32∗∗∗ 0.27∗∗∗ 0.20∗∗∗

2.53 2.06

2.94 2.31

3.31 2.40

2.43 2.28

3.58 2.52

2.74 2.56

3.28 2.02

0.35∗∗∗ 0.34∗∗∗

3.98 2.97

3.85 3.52

3.98 3.16

3.85 3.04

3.87 3.63

3.93 3.09

4.34 3.60

3.73 3.21

0.23∗∗∗ 0.32∗∗∗

0.37 0.12

0.72 0.12

0.63 0.27

0.68 0.30

0.55 0.17

0.62 0.32

0.56 0.12

0.40 0.25

0.23∗∗∗ 0.20∗∗∗

13.24

7.57

11.10

10.67

10.60

10.33

10.62

12.61

0.18∗∗∗

3.46

0.70

0.97

2.20

0.67

1.57

0.32

1.97

0.15∗∗∗

Work-related indicators Working hours Work pressure Job insecurity Commuting time (in minutes) Career demands Control over work, time, place Social support Supervisor–colleague work–life support Training Supervisory position Family indicators Hours spent on housework Hours spent on care



Variables used in the analysis (Means)

66

Table 4.2

2.48

2.49

2.33

2.07

2.07

2.50

2.35

2.45

0.15∗∗∗

0.82 63

0.66 68

0.68 71

0.83 65

0.87 74

0.81 68

0.90 68

0.66 66

0.09∗∗∗ 0.07∗∗∗

3.03 2.24

7.48 1.75

7.51 1.78

4.97 2.01

7.53 1.79

6.85 1.88

7.47 1.76

8.17 1.88

0.68∗∗∗ 0.23∗∗∗

1.13 3.12 2.01

1.03 3.21 1.60

1.08 3.11 1.80

1.11 2.94 1.68

1.24 3.38 1.94

1.71 2.90 1.60

1.10 3.05 1.62

1.13 2.59 1.76

0.36∗∗∗ 0.19∗∗∗ 0.19∗∗∗

75 5.34 38

78 5.18 38

60 4.37 41

49 4.47 38

68 4.16 39

54 5.18 37

63 5.00 43

59 3.77 41

0.20∗∗∗ 0.41∗∗∗ 0.20∗∗∗

Personal characteristics Gender (per cent female) Education Age

Comment: Weighted analysis (all countries are given equal weight in terms of proportion of respondents). Note: ∗ p ≤ 0.05; ∗∗ p ≤ 0.01; ∗∗∗ p ≤ 0.001.

67



Housework disagreements No. of children at home Partner (married/living together) Household income No. of persons with income in household Paid domestic help Childcare flexibility Social networks

68

Data and Methods

4 Interviews and innovation groups

We extended our quantitative data collection by adding qualitative data focusing on change, its impact on current quality of life and issues that are likely to affect the quality of work and life (positively or negatively) in the future. This part of the study explored in depth the notion of a healthy and socially sustainable workplace and the factors that are perceived to contribute to or challenge quality of life and workplace effectiveness in one specific organization in each country. This part of the study was carried out in two stages: 1) interviews and 2) innovation groups. Each country team approached one of the four organizations that had completed the survey to invite them to participate in the qualitative phase of the research. For comparability purposes, we decided to focus on hospitals in so far as possible, as this seemed particularly appropriate when studying the ‘healthiness’ of workplaces. This was not feasible in all the countries, however, and in other cases negotiations were carried out with the other organizations. Ultimately, we collected qualitative data at five hospitals (in Sweden, Finland, the UK, Bulgaria and Germany) and three private sector organizations (a bank in Portugal, a telecom company in the Netherlands and a household retail chain in Hungary; see Table 4.3). It was easier to negotiate access to organizations in some countries than in others. The most difficult was Germany, where the approval of the hospital works council was required. Eventually the works council reluctantly granted its approval, but under strict conditions. The researchers were only permitted to carry out eight interviews and were not allowed to tape them. In Hungary, some interviewees were uneasy about their interviews being recorded; their distrust and concern Table 4.3

Case study organizations and number of interviews in each Sector

The Netherlands The UK Bulgaria Finland Portugal Sweden Hungary Germany

Telecom Hospital Hospital Hospital Finance Hospital Retail Hospital

Number of interviews 13 20 14 12 14 10 20 8


4.1 Interviews


69

about anonymity may have been a legacy of the socialist regime. They seemed less willing than interviewees elsewhere to talk openly and critically about their organization. The case studies were carried out in the summer of 2007. Researchers interviewed between eight and 20 participants in each organization, including medical and nursing staff at various levels of seniority and administrative staff and managers in hospitals, as well as a range of staff and managers in the private sector organizations. Key contacts, usually human resource management staff, helped recruit convenience samples that were gender balanced and included participants differing in occupation, status and, where appropriate, ethnicity. Union representatives were also interviewed. The original intention was that participants should come from a single department so that the second phase of the study (innovation groups) could focus in depth on specific issues, but again, this was not always feasible. The cross-national team developed a semi-structured interview schedule to ensure common approaches as well as attention to national and organizational contexts. The schedule first introduced the notion of the dual agenda. In order to understand the ways in which the organizations were changing and the impact change was having on effectiveness and employee quality of life, the team used a time-based approach (uniting a past, present and future time perspective). Participants were first asked what it was like to work for their organization now; what were the main challenges and how did this affect their work effectiveness and quality of life (and might this differ by gender?). The interviewer then asked the interviewees to reflect on the past and how things had changed since they had started working there, or in the past 5–10 years. The final question was what the interviewee perceived to be the main opportunities and threats with respect to the effectiveness of the organization and the quality of working life in the next 5–10 years. The idea was that future thinking would be embedded in reflections on the past and present trends. The interview schedule was tested in each country. The interviews were more or less open conversations, with the interview guide being used as a checklist to determine what the conversations should include. Following the checklist was not the primary goal, however; instead, the aim was to create suitable conditions for a reflexive dialogue allowing interview group members to discuss their own associations and interpretations throughout the interview process. The interviewer had an open, non-judgemental attitude and gave the interviewees assurances regarding their anonymity and confidentiality,




Data and Methods

contributing to a constructive and permissive climate (Skårner and Månsson, 2008). Interviews were taped (except in the German hospital, where this was not permitted) and as many as possible were transcribed. Some initial content analysis was undertaken to identify major themes relating to aspects of ‘healthy organizations’ and barriers reported across countries. This allowed us to construct a framework for the thematic analysis of the transcripts. The transcripts were not translated, but the reports, including the interview quotes, were written in English. Emerging themes were fed back to a mixed group of managers and other employees in innovation groups in the second phase of the project.

4.2 Innovation groups The purpose of the innovation groups was to address the challenges identified in terms of their potential impact on the dual agenda (quality of life and workplace effectiveness), as well as to engage participants in the collaborative development of small innovations that could help to meet these dual objectives. Eight innovation groups were set up, one in each country. Five were set up in hospitals (Finland, Bulgaria, the UK, Germany and Sweden) and three in private sector organizations (a retail chain in Hungary, a telecom company in the Netherlands and a bank in Portugal). Participants were drawn from the case study interviewees and in most cases the groups were characterized by gender and occupational diversity. Line managers were included, and crucial to the process. The innovation group meetings were limited to between one-and-a-half and two-and-a-half hours owing to availability problems with respect to resources and accommodation, and the difficulty involved in releasing staff for longer periods. In each country, we began the session by negotiating a set of ground rules such as anonymity, interpersonal respect and non-judgemental brainstorming. We told each group about the dual agenda, this being their guiding principle, and defined healthy organizations for them as those meeting the dual agenda of both quality of life and workplace effectiveness. We then presented slides and handouts listing major challenges to the health of each organization as they had emerged from the thematic analysis. Participants discussed these and brainstormed possible dual-agenda solutions in terms of changes to working practices. There are various factors that influence groups and group processes/dynamics at different levels; much depends on the research focus


70


71

and the questions asked. As this was a comparative study of eight countries, factors we had to take into account at the macro level included the country in which the interview was conducted, its history, welfare policy, etc. All of these will have influenced the manner in which individual participants interpreted and understood the group process and discussions. At the meso or organizational level, individual participants would have been influenced by the organization (public or private), its culture and his or her position within that organization. At the individual level, factors such as age and gender may have had an important impact on group dynamics. As researchers, we had to bear these factors in mind when we analysed the results. It became clear in the interviews that participants in some countries were ‘more ready to think creatively’ than those in others. In still other groups, the participants focused more on the negative than the positive aspects of their work. The moderator played an important role in the group process/dynamics, as his/her conduct could affect the group and influence the manner in which participants interacted with one another and the moderator. Occasionally the moderator played the role of interventionist, for example by helping the participants to stay focused on thinking constructively about the dual agenda. For more detailed information on group processes and differences between groups, see The Comparative Report on Innovation Groups (Lewis et al., 2008b). In general, we can say that discussion in the groups was intense, informative and elicited positive feelings of openness and co-operation. The innovation groups are discussed in Chapter 10.

5 Constructing scenarios One of the aims of our study into the relationship between quality of work and quality of life was to make policy recommendations and sketch likely scenarios for the future. In general terms, scenarios may be regarded as a more useful, theoretically oriented and methodologically sustainable alternative to making simple predictions. Constructing scenarios is a particularly appropriate method when considering complex problems that develop over a long period of time and are characterized by uncertainty. Scenarios can clarify initially vague uncertainties and help ascertain various possible outcomes arising from today’s recognizable societal trends (Van der Heijden, 2005). We can examine the effects of certain economic, political, social or cultural trends, their degrees of certainty or uncertainty and their impact




Data and Methods

by sketching hypothetical scenarios that help us analyse the probability of their happening on the one hand and their desirability with regard to quality of life on the other. In our study, a scenario describes not only the current status of a society (or its components) and its possible and desirable future statuses, but also the series of events than can lead to these possible statuses (resulting from its present condition). Scenarios are particularly useful methodological tools for guiding decision-making, as they allow reflection on the present and sustainable plans for the future. We organized a scenario-building session in each country with groups of top-level experts from the fields of economics, politics, science and culture. Each group of participants had different characteristics, thereby offering access to different and sometimes contrasting but always wellinformed perspectives on quality of life. The age and occupational diversity of each group guaranteed some interesting, productive sessions, which lasted three or four hours. We asked the experts to consider future uncertainties, create a story, develop two scenarios, and finally identify a chain of events that could lead to these scenarios. In each country, between six and 16 high-level experts were present during the scenario session. Each group concentrated on the following themes: what are the main challenges facing each country in particular and the European Union in general when it comes to quality of life and work? What can or should be done in the different national contexts to meet these challenges? How can each individual person’s quality of life be protected and improved? How can social quality goals be reconciled with economic development targets and inter-generational solidarity in each country and in Europe as a whole? Chapter 11 explains the scenario method in full and describes the scenarios.

6 Social Quality Instrument We used both the quantitative and qualitative data to develop a Social Quality Instrument. This is a practical tool that will allow European workplaces to measure various aspects of the social quality of work. Developing the instrument involved analysing the quantitative and qualitative data. The most important indicators of quality of life were included, ultimately leading to an instrument consisting of 15 questions. The instrument is available to everyone on the Web (http:// socialquality.jyu.fi/social-quality-instrument), but it is mainly intended for service sector workers.


72


73

The purpose of the instrument is basically two-fold. First, we aim to offer a research-based tool that European workplaces can use to evaluate the social quality of work. We hope that organizations will use the instrument to consider whether they have organized their work in a socially sustainable manner and how they might improve current working conditions. Secondly, we intend using the Social Quality Instrument to gather new data from European workplaces. As people from across Europe respond to the questions, their answers are saved in data files for further analysis. This new data will then be used in the Quality project to study the social quality of work in Europe. Chapter 12 offers a detailed description of the Social Quality Instrument.

7 Discussion In this study, we collected data from many different sources in order to gain a complete and comprehensive picture of the quality of work and life and the way healthy organizations can function in a socially sustainable manner. The real advantage of our methodological approach is that we have collected multi-actor and multi-method data at many different levels – the employee level, the employer level, the organizational level and the policy level – in eight European countries. The quantitative data make it possible to test our hypotheses and study the relevance and importance of each of the explanatory factors for quality of life. The qualitative data give us more profound insights into quality of life and how it relates to healthy organizations. By starting at the organizational level, we acknowledge that employees are embedded in their organization and that researchers make use of that fact by having surveying many different employees in the same organization. This would not have been possible if we had collected data at the individual level, as is the case in large-scale datasets like the European Quality of Life Survey or European Social Survey. One important reason for collecting information in so many different ways is that we want to learn from different countries. Restricting ourselves to quantitative data makes it difficult to explore in depth the influence of cultural, economic and policy differences on quality of life, given the small number of countries surveyed. In this sense, it is more productive to approach the problem from different angles and be open to expected and unexpected differences between countries. Moreover, although there has been a relatively large number of studies on the quality of life, often using a quantitative approach, the multifaceted




Data and Methods

nature of the material is clear. Such material is more conducive to a combination of different methods that can unravel complex causes and meanings. Since our research also focused on policy implications, we were very happy that we were able to include so many policy-relevant aspects in our design, such as the scenario set-up. Like all other data designs, our approach had some disadvantages as well. By choosing four specific organizations, we are not able to generalize our findings to the country level. Moreover, since we have only a few organizations per country, we had to exercise some caution in our interpretations and conclusions. It would be difficult to stress the impact of the country or organization on quality of life. Furthermore, our design has made it difficult to collect information from other family members, which would have been very interesting given the research problem at hand. Finally, using the same survey in each organization and country implies that we were unable to ask specific questions aimed at only one organization, for example. All in all, however, we hope it is clear that our approach has many benefits and is very useful in unravelling the complex causes and meanings of the quality of life. Subsequent chapters present the outcomes of our data collection and analysis.


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Part II


Empirical Results





Quality of Work and Quality of Life of Service Sector Workers: Cross-national Variations in Eight European Countries Patrick Präg, Maria das Dores Guerreiro, Jouko Nätti, Michael Brookes and Laura den Dulk

1 Introduction How do European service sector workers evaluate their quality of work and life nowadays? Europeanization and globalization are bringing about major shifts in the economy, but we know little about how this is affecting the well-being of Europe’s citizens. This chapter presents a range of subjective indicators for the quality of work and life as reported by service sector employees in eight European countries. In addition, it provides background information on the organizational context. The countries involved are at different stages of economic development and have differing welfare systems, as explained in Chapter 3. Four organizations were surveyed in each country: one bank or insurance company, one public hospital, one retail organization and one IT or telecom company. This chapter serves as a context for the other chapters in this book. Its aim is to describe and compare subjective indicators of quality of work and life across countries and organizational contexts. Those indicators are: work engagement, stress, work–home interference and enrichment, satisfaction with work–life balance and overall life satisfaction. The key question addressed by this chapter is: how do these subjective indicators of quality of work and life differ between countries and service sector organizations, and how are they similar? We begin by describing the organizations included in the study, including workforce characteristics and organizational changes at the time of our research. We have grouped them by sector; in other words, we first discuss the hospitals in the eight


5

77


78

Service Sector Workers

2 Portraits of the service organizations in eight European countries 2.1 Public hospitals The hospitals participating in this study represent the public sector. Some of the hospitals selected are university hospitals, while others are public hospitals in major cities. In general, the healthcare sector is dominated by female employees, and this is reflected in the high proportion of female workers in our hospital samples, ranging from 89 per cent in the Finnish hospital to 71 per cent in the UK and Portuguese hospitals. Regarding age, the hospitals in our study have more mature or older workforces than the other service organizations studied, with the average age varying from 39.1 years in the Portuguese hospital to 44.5 years in the Swedish hospital (see Table 5.1). Compared to other sectors, healthcare has a relatively highly educated workforce (European Foundation for the Improvement of Living and Working Conditions, 2008). The hospital workers in our study are also often highly educated, the two exceptions being the Dutch and German samples, where the shares of higher educated workers are relatively small. In the Dutch sample, this is because doctors are not included in the sample, as they are not employed by the hospital but are selfemployed. The healthcare sector is considered a relatively favourable one in terms of working conditions, especially with respect to working hours. Compared to other sectors, however, healthcare workers and social workers are more likely to experience violence at work (Jettinghoff and Houtman, 2009). Organizational change was common among the hospitals in the study. All European countries face growing healthcare expenses owing to the ageing of the population, and at the time of the study many hospitals reported that they were facing financial cuts and reforms. Not all of the hospitals in our study had a recent reduction in their workforce, however; the Finnish and Dutch hospitals, for example, reported a staff increase, and the workforce in the Swedish and German hospitals had remained stable in recent years.


countries, followed by the banks/insurance companies, the IT/telecom companies and finally the retail companies. Next, we look at how service sector workers in these organizations and countries evaluate their quality of work and life. Finally, we conclude the chapter with a discussion of our exploration.


Public hospitals, workforce characteristics and organizational change at the time of the study Sweden

UK

The Netherlands

Workforce characteristics




1000–5000 employees 89% female 93% higher educated∗ Older workforce (43.5 years mean age)

100–500 employees 83% female 87% higher educated Older workforce (44.5 years mean age)


1000–5000 employees 83% female 46% higher educated Older workforce (42 years mean age)

Organizational change




Change in staffing: increase Major event: new work procedure for emergency work introduced, financial cuts, closing of departments and relocation of employees

Change in staffing: stable Major event: merging of departments and start of a new department

Change in staffing: decrease Major event: serious financial problems, possible closure or merger feared (although nothing concrete)

Change in staffing: increase Major event: announcement of financial cuts and closing down of departments

Germany

Portugal

Hungary

Bulgaria





1000–5000 employees 80% female 31% higher educated Mature workforce (40.3 years mean age)





79

Finland


Table 5.1

(Continued)

Germany

Portugal

Organizational change Change in staffing: stable Major event: no major events at the time of the survey

∗

Hungary

Bulgaria




Change in staffing: decrease Major event: National Health Service undergoing major reform due to the reduction of public expenses, new permanent employment contracts prohibited

Change in staffing: decrease

Change in staffing: stable

Major event: general crisis of Hungarian healthcare, reduction of state funding

Major event: major changes in 1997 when a new national classification of occupations was introduced, resulting in new contracts at the hospital. Also in 1997, reforms in the healthcare system (new Law on Health Insurance, Law on Healthcare Institutions, Law on Professional Associations). After the survey doctors and nurses at a hospital in Sofia went on strike, backed by staff at other healthcare institutions but not involving staff at the hospital we studied

ISCED 4–6.



80

Table 5.1

Patrick Präg et al.

81

Based on the European Working Conditions Survey (EWCS), Jettinghoff and Houtman (2009) show that in general, financial sector workers reported relatively favourable physical working conditions, few nonstandard hours, high-skilled work and high levels of social support, at least until 2005. Trends in working conditions and job satisfaction show that ambient conditions (such as exposure to noise, fumes, powder or dust), weekend work and violence and discrimination decreased in the financial sector and satisfaction with working conditions increased between 1995 and 2005. As the economic crisis has shown, however, conditions can change rapidly and it is important to note the organizational changes that were taking place at the time of the study. Mergers, takeovers and changes of ownership were very common within the banking and insurance industry, perhaps increasing feelings of job insecurity, in this case meaning uncertainty not about redundancy but about one’s future job content or work location. Nevertheless, at the time of the study, our companies still had relatively favourable working conditions. Both banks and insurance companies are included in our study. These are all relatively large organizations, except for the two Scandinavian cases. They have relatively highly educated workforces and a large proportion of female employees. The average age varies between 30.7 years (Germany) and 44.2 years in Finland (see Table 5.2). 2.3 IT and telecom companies Workers in the telecommunication industry are required to meet heavy demands, that is they often need to work hard and at a breakneck pace (Jettinghoff and Houtman, 2009). Four of the eight companies in our study had faced cuts in staff in the past few years, while the other four reported an increase. IT and telecom companies have a relatively young workforce, with the lowest mean age being found in Bulgaria (32.8 years). The Swedish and German IT companies were exceptions with older workforces (43.8 and 43.9 years, respectively) (see Table 5.3). 2.4 Retail companies The retail companies were included in the study because they employ a relatively large share of lower educated workers. At first, the aim was to include supermarket chains in every country. Obtaining access to the chains proved difficult, however, and so we extended our focus to other types of retail chains, such as electronics and travel/outdoor shops. Many of the companies included in the study employ a young, largely


2.2 Banks and insurance companies


Bank/insurance companies, workforce characteristics and organizational change at the time of the study Sweden

The UK

The Netherlands





100–500 employees 83% female 71% higher educated∗ Older workforce (44.2 years mean age)


5000–10,000 employees 46% female 62% higher educated Mature workforce (38.3 years mean age)

5000–10,000 employees 42% female 51% higher educated Older workforce (43.0 years mean age)





Change in staffing: decrease Major event: some branch offices were closed down, and operational responsibilities were redistributed in the top management

Change in staffing: decrease Major event: reorganization from one into two separate insurance departments, based on function

Change in staffing: stable Major event: no major events at the time of the survey

Change in staffing: increase Major event: take-over of a major bank

Germany

Portugal

Hungary

Bulgaria








10,000+ employees 68% female 82% higher educated Older workforce (40.3 years mean age)





Change in staffing: n.a. Major event: integrating previous take-over

Change in staffing: increase Major event: mergers, major reorganization and evaluation of all departments and services

Change in staffing: increase Major event: reorganization

Change in staffing: stable Major event: expected take-over and change of ownership (huge international banking group). New technologies and products, pay rise

∗

ISCED 4–6.


82

Finland


Table 5.2

IT and telecom companies, workforce characteristics and organizational change at the time of the study

Finland

Sweden

The UK

The Netherlands





500–1000 employees 69% female 63% higher educated∗ Younger workforce (34.1 years mean age)


5000–10,000 employees 61% female 23% higher educated Younger workforce (35.2 years mean age)

1000–5000 employees 36% female 30% higher educated Younger workforce (37.4 years mean age)





Change in staffing: decrease Major event: no major events at the time of the survey, but still feeling the impact of previous outsourcing strategies

Change in staffing: decrease Major event: no major events at the time of the survey

Change in staffing: stable Major event: no major events at the time of the survey

Change in staffing: increase Major event: take-over of a smaller company; higher performance targets

Germany

Portugal

Hungary

Bulgaria












Change in staffing: increase Major event: new subsidiary

Change in staffing: decrease Major event: outsourcing

Change in staffing: decrease Major event: change in ownership

Change in staffing: increase Major event: tough competitive environment and expected competition from alternative communication channels and new providers; new technologies, pay rise

∗

ISCED 4–6.


83



Table 5.3


female workforce, although the British and German shops had older workforces with an average age of 48.7 years. Some of the companies were expanding at the time of the study, whereas others had more or less stable workforces. The Dutch case represented a relatively secure work environment because the chain is part of a semi-profit organization (see Table 5.4). 2.5 Summary The hospitals in our study are fairly similar across the eight countries; they all have a mature or older, female, professional workforce and they are all facing financial cuts and reforms, although some of these are more drastic than others. The banks and insurance companies also have an older and highly educated workforce. The banking and insurance industry offers relatively good working conditions in most countries, but employees are also experiencing considerable turbulence and change. Many telecom companies in this study have a young workforce, and they differ considerably from one another when it comes to staffing: some are increasing staff and some are downsizing their workforce. They operate in a highly competitive market, and outsourcing, mergers and takeovers are common. The retail companies have a lower educated, largely female workforce than the other service organizations and are also subject to much turbulence and change; some are doing better than others. Hence, despite our including comparable cases, there are some striking organizational differences between countries within the four sectors.

3 Subjective indicators of quality of work and life We have seen that the 32 organizations vary considerably in their demographic composition both within countries and industries. In order to obtain comparable estimates of cross-national variation in the quality of life, we present adjusted means derived from analyses of covariance (ANCOVA) (Keppel and Wickens, 2004). The adjusted means show country and organizational averages in the quality of life and work net of differences in age, percentage of female workers, educational attainment and sample size. In other words, these are the means that we would expect to find if the demographic make-up (in terms of age, gender and education) of all the organizations was equal to the empirical average found across countries and industries. In addition, all indicators presented below have been converted from the original scale to a range of


84


Retail companies, workforce characteristics and organizational change at the time of the study

Finland

Sweden

The UK

The Netherlands





100–500 employees 91% female 34% higher educated∗ Younger workforce (36 years mean age)

100–500 employees 77% female 25% higher educated Mixed workforce (40.5 years mean age)










Major event: more competition and slight decline in sales owing to opening of new mall nearby

Change in staffing: decrease but increase in part-time work Major event: ongoing reorganization within the company, increasing share of part-time workers

Major event: taken over by US company in 1999 and since then gradually introducing new contracts with less favourable working conditions

Major event: new shop concept (more active approach to the customers, rather than waiting behind the counter)

Germany

Portugal

Hungary

Bulgaria





10,000+ employees 55% female 44% higher educated Younger workforce (34.3 years mean age)







Change in staffing: increase



Major event: expansion due to growth in sales and a merger

Major event: mergers and acquisitions and the opening of new supermarkets

Major event: expansion in a number of stores and growth in profits

Change in staffing: stable (no recruitment problems) Major event: rising competition coming from big international chains that started investing in Bulgaria after 2000

∗

ISCED 4–6.


85



Table 5.4


0 to 100. Reported values thus represent the percentage of the maximum value that could have been measured. This conversion makes it easier to interpret the indicators (Cohen et al., 1999) and is frequently used in some areas of quality of life research (e.g. Cummins, 2003). In this section, we first compare perceived quality of life and work across countries. We then consider the variation between sectors within countries and possible patterns according to type of sector. 3.1 Quality of work and life across countries 3.1.1 Work engagement How happy are employees at work? Work engagement expresses how good people feel at work. Work engagement is typified by vigour, dedication and absorption (Schaufeli et al., 2002). It is based on the concept of ‘flow’, which has its origins in positive psychology (Seligman and Csikszentmihalyi, 2000). In order to measure work engagement, we used seven items taken from the Utrecht Work Engagement Scale (Schaufeli et al., 2006; see Chapter 4). Research has shown that work engagement is related to job resources such as working time and work intensity, job autonomy, training and relationships with colleagues (Lewis et al., 2009b). Results obtained in this survey rank the Netherlands (71 per cent) as having the highest levels of work engagement and the UK as having the lowest (53 per cent). Portugal (69 per cent), Sweden (66 per cent), Hungary (66 per cent), Bulgaria (63 per cent) and Germany and Finland (61 per cent both) are ranked between these two extremes (Figure 5.1 (a)). 3.1.2 Stress Stress is a common phenomenon in contemporary life and represents an individual’s response to the demands of his or her environment (Weinberg and Cooper, 2007). Much of the research on the quality of working life focuses on occupational stress, burnout, work–family conflict and other negative outcomes. Stress may be caused by heavy job demands and a lack of job resources, as well as demands associated with other life domains such as the family (see Chapter 2). In this sample, average job-related stress across the eight countries is greater than private or family-related stress. Figure 5.1 (b) shows that workplace stress affects about half of the respondents, with the largest percentages being in the UK (50 per cent), Portugal (47 per cent) and Hungary (46 per cent). These are all countries where employees work long hours. The lowest percentages were found


86



87

Figure 5.1

Subjective measures of quality of work (adjusted means)



in the Netherlands (33 per cent) and Bulgaria (36 per cent), despite differences in the average number of hours worked in the two countries. Finland, Sweden and Germany are in the middle bracket. Family-related stress is less common among our service sector workers. In the UK 37 per cent and in Portugal 35 per cent of workers report family-related stress. The Nordic countries are ranked in the middle, together with Germany and Hungary. Bulgaria and the Netherlands have the lowest levels of family-related stress at 25 and 27 per cent respectively. 3.1.3 Work–home interference and enrichment Increasingly, employees combine paid work with other life activities. The work–life balance has hence become an important dimension of the quality of work and life. The literature shows that combining paid work with other life domains may have a positive as well as a negative impact on quality of life (see Chapter 2). Chapter 2 argues that a lack of resources and heavy work and/or household demands can result in negative work-to-home or home-to-work interference or conflict. From a positive perspective, work–home enrichment refers to the extent to which experiences in one domain improve the quality of life in the other (Carlson et al., 2006; Greenhaus and Powell, 2006). Figure 5.1 (c) shows the average work-to-home interference experienced by European service sector workers, as measured by three items on a scale developed by Geurts and colleagues (Geurts et al., 2005). It turns out that around 40 per cent of Bulgarian and Hungarian service sector employees report work-to-home interference. In the UK and Germany this is 35 per cent, and in Portugal 34 per cent. Workers reporting the least amount of work–home interference were found in Sweden (30 per cent), Finland (28 per cent) and the Netherlands (26 per cent). A growing number of researchers have been exploring the positive aspects of combining work and family life in recent years. As some authors have argued, professional activity can have a positive effect on the private domain. Moen et al. (1992), for instance, were able to show that women’s multiple-role involvement had long-term positive effects on their health and social integration. Work can benefit the family regardless of the amount of perceived difficulty balancing home and work. The beneficial aspects of multiple-role engagement have gained in relevance (Grzywacz and Butler, 2005; Voydanoff, 2005; Greenhaus and Powell, 2006). Work is beneficial not only because it gives families resources and satisfies their material needs in the form of pay, but also because the social and interpersonal relationships established in the


88


89

workplace produce social capital. It is at work that people make friends and acquaintances, build networks and get the information and support they need to resolve problems in the domestic domain. This is especially true when people curtail their social lives outside of work because they have so little time left after working long hours. In order to assess to what extent European service sector workers believe their jobs enrich their private lives, we used a measure consisting of three items taken from the work–family enrichment scale developed by Carlson et al. (2006). Figure 5.1 (d) reveals some variation across countries. Basically, we can distinguish two groups of countries with relatively high and relatively low levels of work-to-home enrichment. On average, service sector workers in Portugal (60), Bulgaria (58), Finland (58), Sweden (57) and the Netherlands (55) find their jobs enriching for their private lives. Employees in Germany (46) and Hungary (45) generally perceive less work-to-home enrichment, while British service sector workers award a mean score of 50. 3.1.4 Satisfaction with work–life balance Another way of conceptualizing the way work and home impact on quality of life is the notion of work–life balance satisfaction (Eby et al., 2005; Poelmans et al., 2005). This concept, developed by Valcour (2007), is defined as ‘an overall level of contentment resulting from an assessment of one’s degree of success at meeting work and family role demands’ (Valcour, 2007, p. 1512, see also Chapter 2). A perceived conflict between work and family is negatively related to life satisfaction, job satisfaction and organizational commitment (Kossek and Ozeki, 1998; Allen et al., 2000), and positively related to health problems (Grzywacz and Tucker, 2008). A number of authors stipulate that workers in the Nordic countries should be experiencing the highest levels of work–life balance satisfaction owing to the family support policies of the socialdemocratic welfare regimes (Crompton and Lyonette, 2006; Leitner and Wroblewski, 2006). However, other researchers show that women in the Nordic countries are actually less satisfied with their ability to combine work and family (Scherer and Steiber, 2007). This is related to the large proportion of women who work full time in Sweden and Finland, a pattern that is in fact stimulated by generous work–family policies. After returning to work from what are indeed long and generous parental leaves, women tend to combine childcare responsibilities with fulltime jobs, potentially leading to work–home interference. In addition, Drobniˇc et al. (2010) show that although work–life interference is more





serious in the less affluent European countries than in the richer Nordic and Western European countries, it is only workers in the latter countries who perceive their life satisfaction as being negatively affected by work–life interference. In order to assess European workers’ satisfaction with their ability to combine work and private life, we used a three-item measure developed by Valcour (2007). Figure 5.1 (e) shows service sector workers’ average satisfaction with their work–life balance. Country differences are fairly small but significant. Dutch employees, a large percentage of whom work part time, express the largest degree of satisfaction with their work–life balance, reaching a score of 65. On average, Swedish and Finnish service sector workers have slightly lower scores (62). Bulgarians assign a mean score of 60, followed by Germans (59), Hungarians (56), Portuguese (55), and British (54) workers. Respondents in these countries also report the least amount of support from their superiors, notably when they want to reduce their working hours for personal reasons. Bulgarians, Hungarians and the Portuguese also report a higher average number of working hours; in these countries, the long-hours culture tends to prevail (Burke and Cooper, 2008).

3.1.5 Overall life satisfaction The final subjective measure of quality of life is overall life satisfaction, which we measured using the well-established scale developed by Pavot and Diener (1993). Life satisfaction is defined as an individual’s subjective judgement of their overall quality of life, based on their own set of criteria: ‘The quality of life must be in the eye of the beholder’ (Campbell, 1972, p. 442). As a measure of subjective well-being, this judgement is considered the cognitive component, as opposed to the affective component, which in turn comprises pleasant and unpleasant affects. There is consensus among quality of life researchers that subjective and objective measures should be considered together (Präg et al., 2010). In empirical terms, Figure 5.2 shows us that there is a marked divide in overall life satisfaction between the countries under study. The highest level of overall life satisfaction has been observed among Swedish and Dutch service sector workers. Both have average scores of roughly 67 on the satisfaction with life scale. Finland and Germany are close behind, with scores of 64 and 62, respectively. Life satisfaction for service sector workers in the other countries is considerably lower. On average, Portuguese workers score 57, Hungarians have a mean of 54 and both


90


Figure 5.2

91

Overall life satisfaction by country (adjusted means)

British and Bulgarian workers score approximately 53 on the satisfaction with life scale. These results are roughly in line with findings from representative cross-national studies (e.g. Drobniˇc et al., 2010). Crossnational differences in life satisfaction are often attributed to economic development and national wealth (Diener and Suh, 1999; Fahey and Smyth, 2004). However, the fact that British workers score at the same level as Bulgarian workers strongly suggests that there are also other mechanisms at play. Findings from other studies generally confirm that life and job satisfaction levels are lower and work–home interference levels higher in the UK than in Sweden, Finland, the Netherlands and Germany (Fahey and Smyth, 2004; Pichler and Wallace, 2009). In general, however, the difference between UK scores and those in other Western European countries tends to be smaller than observed in our study of service sector workers (see also Chapter 6). Research on the quality of life contends that overall life satisfaction is located at the very top of a domain hierarchy that organizes individuals’ memories and perceptions within these domains (Sirgy, 2002). Material well-being and social relationships are two very important life domains relating to overall life satisfaction. There is a considerable amount of research literature on the effects of material conditions (Diener et al., 1993; Easterlin, 2001; Diener and Biswas-Diener, 2002; Clark et al., 2008) suggesting that the correlation between income and life satisfaction is





moderate, and that increases in income generate little if any additional satisfaction once a certain level of income has been reached. There is evidence, however, that differences in life satisfaction are considerable between the rich and the poor (Lucas and Schimmack, 2009) and that income plays a more important role in less affluent countries (Drobniˇc et al., 2010). This sample of service sector workers combines better paying and more prestigious occupations, for instance in healthcare (e.g. doctors), and more precarious and poorly paid occupations (e.g. the majority of retail jobs). Socio-economic well-being, measured here as a worker’s level of satisfaction with his or her household income, is a salient predictor for overall well-being (Van Praag et al., 2003).

4 Comparing organizations across countries Besides differences between countries with respect to quality of life, the data have also revealed variations between organizations. Figure 5.3 illustrates this for the indicator overall life satisfaction. Earlier in this chapter, we saw notable differences between countries in overall life satisfaction. If we take the employing organization into account, we also see variation across organizations within countries.

Figure 5.3


92

Overall life satisfaction by organization


93

The highest level of overall life satisfaction can be found among Finnish bank workers, but it is not the case that bank/insurance employees report the highest levels of life satisfaction in every country in our survey. For example, in the Netherlands and Bulgaria it is hospital workers who score highest (although at a far lower level in the latter country), while in Hungary, hospital workers and bank employees in fact have the lowest scores. In many countries (although not in all), telecom workers are generally the least satisfied with their lives. In other words, we see no clear pattern by organization within our data set, unlike the country differences. This is also true for the other subjective quality of work and life indicators.

5 Discussion At a time of enormous change in the world economy, socially sustainable working conditions that preserve and improve the quality of life are a crucial issue in Europe. Drawing on a survey conducted in 32 service sector organizations in eight European countries, this chapter presented the cross-national distribution of subjective quality of life indicators of service sector workers, including work engagement, stress, work–home interference and enrichment, satisfaction with work–life balance and overall life satisfaction. Although we cannot assume that our samples are representative, we can report a number of interesting outcomes. For most indicators, Swedish, Finnish and Dutch employees reported similarly high levels of contentment, namely overall life satisfaction, work–life balance satisfaction and work engagement. A gloomier image of quality of life and work emerges for the less affluent countries, Portugal, Hungary and Bulgaria. Service sector workers from these countries score among the lowest on most indicators. Only for work-to-home enrichment do Portuguese and Bulgarian employees rank highest. Remarkably, British service sector workers have scores similar to those of employees from less affluent countries when it comes to quality of work and life. On both work and non-work indicators, their scores are comparable and often lower. German service sector workers range in between these two groups. The aim of this chapter was to explore the data with a view to the subjective indicators of quality of life. The key question was: what are the differences and similarities in quality of life between countries and across service sector organizations? We found a consistent pattern of country-specific differences, as discussed above, but organizational differences were less clear. The description of the various organizational





contexts revealed major variations in workforce characteristics, but even sharper differences in terms of organizational change and economic position (increase or decrease in staff numbers). The differences between organizations in similar sectors show that there is no clear pattern across organizations when it comes to the subjective indicators of quality of work and life. Subsequent chapters, which focus more on explanatory analysis, may shed more light on the role of the organizational context.


94


Quality of Life and Satisfaction with the Work–life Balance Stefan Szücs, Sonja Drobniˇc, Laura den Dulk and Roland Verwiebe

1 Introduction In spite of an abundance of literature on the quality of work and the quality of life, we still know little about the relationship between the individual’s ability to balance working with other areas of life and overall life satisfaction. In particular, we have only limited knowledge of how work organizations, the working environment and the broader societal context affect this relationship. Paid employment is an important determinant of a high quality of life in Europe (Clark, 2001a, 2005). Working not only gives people an adequate amount of money to make ends meet, but it also offers them a clear time structure, a sense of identity, social status and integration, and opportunities for personal development (Gallie, 2002, 2007). However, with demands rising both at work and in the home (see Chapter 2), managing the interface between work and other life domains is becoming increasingly complex and difficult. As a result, people may feel less satisfied with their work–life balance and this, in turn, may affect their quality of life (Parasuraman et al., 1992; Rice et al., 1992; et al., 1999). There are signs that the ability to balance working with other life domains is becoming an important issue for individuals’ quality of life in Europe, and that its relevance to overall life satisfaction grows along with a country’s economic prosperity and welfare provisions (Szücs et al., 2008; Drobniˇc et al., 2010). The EU Social Agenda and the Lisbon Strategy have identified the compatibility of work and family life as a core value, one that is believed to have major influence on quality of life (European Foundation for Living and Working Conditions, 2005). It is therefore important to study both the relationship between working life and private life and the sources of work–life balance and well-being from a comparative European perspective.


6

95


Satisfaction with the Work–life Balance

In this chapter, we evaluate how job-related and household-related demands and resources influence employees’ overall satisfaction with how they manage their work and non-work roles – in other words, their work–life balance satisfaction – and whether satisfaction with work–life balance is associated with overall life satisfaction. The main objective of this chapter is to understand variations in satisfaction with the work– life balance and overall well-being in differing organizational contexts and across European countries. The vast bulk of research on quality of life has involved random samples of employees/respondents in a single country, with little concern for the status or function of their work organizations. Data from the Quality survey allow us to control for the type and status of work organization to some extent (see, e.g. Szücs et al., 2008) and to examine workplace effects within and between countries. The study design includes three levels of analysis: individual job and household demands and resources, workplace/organizational context, and country context. Male and female employees are analysed separately to capture gender differences in how they balance working life and private life and in their perceived quality of life. The broader theoretical framework in which our study is embedded is outlined in Chapter 2, and the data used for the analysis are described in detail in Chapter 4.

2 Measuring quality of life Quality of life research stems from two distinct approaches that are sometimes labelled ‘the Scandinavian approach’ (with an emphasis on the objective ‘level of living’) (Erikson, 1974, 1993) and the American ‘quality of life’ approach (Campbell et al., 1976). The ‘level of living’ approach draws on the tradition of Swedish welfare research and thus focuses heavily on objective living conditions. According to this approach, quality of life depends crucially on the individual’s command over resources that he or she can mobilize and use to control and consciously direct his/her living conditions (Erikson, 1974). This tradition is uninterested in any subjective evaluation of living conditions and indeed even suspects such evaluations of bias. Contrary to the ‘level of living’ approach, the American ‘quality of life’ approach draws on individuals’ subjective assessment of their quality of life (Campbell et al., 1976; Diener et al., 1985, 1999; Pavot and Diener, 1993). Individual resources are not considered relevant for individuals’ welfare;


96


instead, the focus is on individual needs. The basic idea is that living conditions as the individual perceives and evaluates them subjectively make up the core of quality of life, regardless of how others would evaluate those conditions. Scales drawing on subjective well-being, positive affect or satisfaction with important life domains (such as work, family and health) have been used by the proponents of the subjective approach (Veenhoven, 1996). Researchers increasingly recognize that both objective conditions of life and subjective aspects are important in analysing quality of life. Consequently, we do not adhere to a single theoretical tradition but consider both objective indicators and subjective evaluations to gain a better understanding of quality of life in European societies. In this chapter, we take the satisfaction with life scale (SWLS) as an indicator of people’s subjective well-being and their quality of life (Diener et al., 1985). Life satisfaction is an overall cognitive assessment of feelings and attitudes about one’s life at a particular point in time and is considered a desirable goal in and of itself. Among the various components of subjective well-being, the SWLS focuses on assessing global life satisfaction. Life satisfaction differs a great deal among individuals and between European countries (Fahey and Smyth, 2004). It not only depends on personal characteristics and private life circumstances, but also on individuals’ social status in the workplace (Marmot, 2004), their position within large social networks (Fowler and Christakis, 2008) and broad societal contexts that include the relevant country’s economic performance, social security level and political culture (Böhnke, 2008). On average, people in Denmark, Sweden, the Netherlands and Finland are among the happiest in Europe (Eurobarometer 68, 2007; see also Inglehart et al., 2001). National levels of subjective well-being are closely and positively related to the level of economic development. The populations of rich countries are happier and more satisfied with life than the populations of poor countries (Inglehart and Klingemann, 2000; Fahey and Smyth, 2004). This pattern is further explained by an advantageous economic situation at the individual level, and by the ideology, functioning and outcomes of government and its welfare state at the macro level. Quality of work, however – and work–life conflict in particular – seems to depend on gendered cultural attitudes rather than welfare regime support (Strandh and Nordenmark, 2006, p. 606; Van der Lippe et al., 2006), a contradiction that has been labelled the ‘timepressure-happiness paradox’ (Garhammer, 2002, p. 240; Van der Lippe et al., 2006, p. 316).


Stefan Szücs et al. 97


98


The concept of work–life balance is closely related to the concept of work–family balance, a term frequently used in popular as well as academic writing, although explicit definitions are rare (Frone, 2003). Work–family balance is associated with an equilibrium or overall sense of harmony in life (Clarke et al., 2004), indicating a satisfactory resolution of the multiple demands of work and family domains. Frone (2003) provided a four-fold taxonomy of work–family balance that includes the separate components of work-to-family conflict, family-to-work conflict, work-to-family facilitation and family-to-work facilitation. It remains unclear how these components relate to an individual’s level of satisfaction with his/her integration of work and family responsibilities or whether all four components need to reach optimal levels in order to satisfy a person (Valcour, 2007). In this study, we use the term work–life balance in order to indicate that we have included single households in the analysis and consider not only family roles, but also broader aspects of private life. Work–life balance has been defined as the individual’s perception of his or her ability to combine time and commitments at work with his or her private life. However, the work–life balance approach also has significant constraints (see a review in Lewis et al., 2007; Pichler, 2009). The focus of this chapter is therefore on satisfaction with work–life balance, which is clearly distinct from work–life balance. The concept captures perceptual or affective reactions to an unspecified level of balance, rather than the level of balance itself (Greenhaus et al., 2003). Some research has equated work–family balance with the experience of low levels of work– family conflict. This definition rests upon the untested assumption that employees who experience high levels of work–family conflict are automatically less satisfied with their ability to balance their work and family responsibilities (Valcour, 2007). In a recent study, Valcour (2007) elaborated on the concept of satisfaction with work–family balance and provided arguments favouring this concept over competing ones. Satisfaction with work–family balance is defined as an individual’s assessment that he or she has an adequate number of resources to respond effectively to job and family demands, as well as an individual’s affective response to this assessment (see also Chapter 2). This definition perceives satisfaction with work– family balance as a unitary, holistic construct that includes a cognitive and an affective component. The cognitive component is comprised of an appraisal of a person’s ability to meet multiple work and family


3 Satisfaction with the work–life balance


responsibilities. The affective component includes a positive feeling or emotional state as a result of this positive appraisal. Satisfaction with work–family balance is distinct from constructs describing crossdomain transfer processes such as work–family conflict, enrichment or facilitation. Whereas cross-domain constructs refer to experiences in one role that affect the quality of or the performance in the other, satisfaction with work–family balance refers to the overall level of contentment with how one handles one’s job and family demands (Valcour, 2007). Our measurement of satisfaction with work–life balance is based on three items from Valcour’s (2007) satisfaction with work–family balance scale (see Chapter 4), and refers to time as a critical personal resource for meeting job and private life demands, and to respondents’ assessment of their degree of success at integrating job demands and private/family roles. The words ‘satisfaction with work–life balance’ are used here rather than ‘satisfaction with work–family balance’ to make the concept equally relevant to respondents with and without children and to those living in or outside of traditional family structures.

4 Overall life satisfaction and satisfaction with the work–life balance: analytical model The analysis is based on the theoretical framework of the Quality project (Van der Lippe and Van Kampen, 2007; Den Dulk and Van der Lippe, 2009) and the conceptual model developed in Chapter 2. We proceed in two steps, as indicated in Figure 6.1. In the first step, we examine how resources and demands in the work and household domains affect service sector employees’ satisfaction with work–life balance. As argued in Chapter 2, the general assumption is that satisfaction with work–life balance will be higher when people have enough resources to meet the demands they are facing in both the work and private spheres. Gaps between demands and resources are likely to result in tensions and feelings of dissatisfaction with the work–life balance. However, we go beyond the resources–demands framework (cf. Voydanoff, 2005) by incorporating the workplace and country-level context in the analysis. In the next step, our dependent variable is satisfaction with life as the indicator of quality of life. Again, the analysis takes into account individual factors, such as job demands and resources, as well as household demands and resources, organizational or workplace context and national context. In addition, satisfaction with life is assumed




100


Institutional context: countries (welfare regime, economic development)

Job demands - Work demands (pressure) - Career demands - Job insecurity - Working hours - Commuting time Job resources - Control over work, time, place - Social support - Work−life support - Job training

Satisfaction with work− life balance SWLB

Satisfaction with life SWLS

Household demands - Housework (hours) - Disagreements about housework - Care time -Number of children Household resources - Partner - Household income - Paid/informal domestic help - Childcare flexibility - Social networks

Figure 6.1

Conceptual model for the empirical analysis

to be positively and significantly related to satisfaction with work– life balance, above and beyond individual demands and resources and workplace and societal context. 4.1 Individual-level determinants and hypotheses In line with the resources–demands theoretical framework, job demands refer to ‘physical, social, or organizational aspects of a job that require sustained physical or mental effort, and are therefore associated with certain physiological and psychological costs’ (Demerouti et al., 2001, p. 501). Voydanoff (2004, 2005) distinguishes two types of job demands: time-based and strain-based demands. Whereas time-based job demands


Workplace context: service sector organizations (high/low status)


are related to negative work–family outcomes through a process of resource drain or scarcity, strain-based job demands work through processes of psychological spillover between domains. Time-based job demands included in this chapter are working hours and commuting time. Recent studies have shown that commuting time is negatively related to overall life satisfaction (Szücs et al., 2008; Drobniˇc et al., 2010) and is particularly salient for female workers in low- to mediumstatus jobs (Isacsson, 2008). Examples of strain-based job demands are work pressure, career demands and job insecurity. Several strain-based job demands were found to be linked to higher levels of work–family conflict and lower levels of work–family balance. Research shows a close relationship between work pressure, job control and well-being in the workplace (Karasek and Theorell, 1990). Career demands are another factor that might affect satisfaction with work–life balance and life in general, in particular when they conflict with responsibilities in other life domains (Den Dulk and Peper, 2007). Job insecurity can have a negative effect on work–life balance and overall life satisfaction (Klandermans et al., 1991; Kraimer et al., 2005) and on satisfaction with work–life balance (Beham and Drobniˇc, 2010). Hence, we hypothesize that job demands (work pressure, career demands, job insecurity, working hours and commuting time) are negatively associated with satisfaction with work–life balance and satisfaction with life. Job resources are assumed to have a positive effect on satisfaction with work–life balance and life satisfaction by providing various sources of support and flexibility in the workplace. Chapter 2 described job autonomy, social relationships, job training and support from co-workers and supervisors when tackling work–life balance issues as resources important to the well-being of workers. Accordingly, in our analytical model we hypothesize that control over work, good social relationships, supervisor-colleague support for work–life balance issues and job training positively affect satisfaction with work–life balance and satisfaction with life. Various household demands can be assumed to reduce satisfaction with the work–life balance and thereby satisfaction with the quality of life in general. These include time spent on housework, disagreements over household chores between couples, number of children in the household and responsibilities for caring for older family members or friends. Household resources that are assumed to increase satisfaction with work–life balance and satisfaction with life include having a partner, childcare flexibility (Galinsky, 1999), paid/informal domestic help, total household income and supportive social networks (Bäck-Wiklund





and Plantin, 2007). Finally, we include the following individual-level variables as controls in our statistical analysis: education, age, health status and supervisory position in the workplace. Since we assume that gender is not a variable that simply raises or lowers the level of satisfaction with work–life balance or overall life satisfaction, we do not include it as one of the covariates in the model. Rather, we estimate the models for men and women separately in order to capture potential differences in the effects of independent variables on satisfaction with work–life balance and satisfaction with life, and differences in mechanisms that may – even in similar life circumstances for men and women – lead to differing outcomes.1

4.2 Organizational-level hypothesis The effects of demands and resources at the individual level can be significantly modified by the organizational and broader societal context. Recent studies show that determinants of happiness can also be sought at the meso level, such as workplace organizational status or position in large social networks (Marmot, 2004; Fowler and Christakis, 2008). Previous research suggests that the ability to balance home-related and work-related tasks is greater in organizations characterized by high status and high-involvement work practices (Batt, 1999; Berg et al., 2003; cf. Valcour, 2007, p. 1521). For example, Berg et al. (2003) argue that there are two mechanisms behind this positive relationship between satisfaction with work–life balance and high-performance work systems. First, high-performance work systems improve people’s sense of control and efficacy by increasing employee involvement in decision-making and opportunities for self-development through training and mentoring. Secondly, high-performance work systems are associated positively with the introduction of work–life policies (Osterman, 1995). The former is also likely to affect the quality of life. This implies that the status of the work organization in service work can have beneficial effects on an employee’s satisfaction with work–life balance and satisfaction with life. Our study covers work organizations perceived as low to mediumstatus as well as high-status ones. The university or general hospital represents a high-status publicly financed work organization. The banking/insurance industry represents the medium- to high-status privately financed type of work organization. Depending on its main functions, the IT/telecom industry – including consultant/systems development and/or client support – represents the low- to high-status work


102


organization. In our study, the retail/supermarket industry most clearly represents the low- to medium-status work organization. Accordingly, we expect that respondents working in retail will be less satisfied with their work–life balance and overall life satisfaction compared with those employed by the other organizations. It is important, however, to note that the impact of the organizational status may vary significantly even within firms, for example between a call centre agent and an accountant within an insurance company or a bank (see Chapter 7).

4.3 Macro level: the welfare regime and affluence hypotheses Cross-national studies show that macro-level social, economic, political and cultural systems play an important role in cross-country variations in quality of life (Fahey and Smyth, 2004; Szücs and Strömberg, 2006; Böhnke, 2008; Drobniˇc et al., 2010). The economic, institutional and cultural settings in which employees and their organizations are embedded create important opportunities and constraints for achieving a good work–life balance and a high quality of life. For analytical purposes, it has proven useful to cluster countries into a smaller number of welfare state categories, characterized by different modes and actors that balance social welfare against pure market forces. Within the framework of Esping-Andersen’s (1990, 1998) typology of welfare state regimes (social-democratic, corporatist and liberal), countries included in the Quality study cover the whole range of welfare regime types. Sweden and Finland belong to the social-democratic welfare regime with considerable state intervention, where the welfare provision is allocated on the basis of citizenship rights. In other words, the social-democratic model aims to secure a high level of social welfare for all citizens. The UK is considered a liberal welfare state. The liberal model is characterized by minimal state involvement in the provision of social welfare; here, social security is considered a matter of individual responsibility. The main regulatory institution is the market, not the state. Germany is often cited as a prototype for the corporatist model, which focuses on the idea of subsidiarity. The principle of welfare provision is insurance systems and the basic unit of intervention is the family. Other countries are not so clearly associated with these ideal-type regimes. The Netherlands has been categorized as both corporatist and social-democratic, depending on the focus of respective analysis. Southern European countries are usually clustered separately in the Mediterranean or sub-protective regime cluster,





although Portugal differs considerably in some respects from the typical representatives, such as Spain and Italy. Finally, Bulgaria and Hungary resemble the post-socialist type to some extent, which still has elements of the old paternalistic system; each, however, has introduced important elements from other, particularly liberal welfare regimes (Mau and Verwiebe, 2010). Based on a detailed discussion of the policy regimes in the countries under study, Chapter 3 hypothesized the impact on the quality of life (see Table 3.3). Countries that place more emphasis on providing a high level of social security for their citizens, such as those embracing the social-democratic model, are expected to provide better settings for a high quality of life. In addition, the level of economic prosperity in a country has been shown to be an important factor in explaining variation in life satisfaction (Fahey and Smyth, 2004; Böhnke, 2008; Drobniˇc et al., 2010). Grouping countries by GDP (see Figure 3.1) indicates that Bulgaria, Hungary and Portugal have lower standards of living compared to the more affluent countries in Western and Northern Europe. Accordingly, we hypothesize that respondents in Nordic and Western countries will be more satisfied with their quality of life than respondents in Southern and Eastern European countries, regardless of their individual and organizational characteristics.

5 Analysis and results We first analyse in detail the satisfaction with work–life balance and satisfaction with life scales to examine differences between the countries and between the sexes. We then estimate the model as outlined in Figure 6.1, using ordinary least squared (OLS) regression. In the first stage of analysis, satisfaction with work–life balance is regressed on country dummies, work organizations, individuals’ job demands and resources, household demands and resources, and control variables. In the second stage, satisfaction with life is regressed on country dummies, work organizations, individuals’ job and household demands and resources, control variables and satisfaction with work–life balance in order to assess the mediating role of satisfaction with work–life balance in life satisfaction. Hierarchical regression analysis is performed separately for men and women, allowing us to examine whether the determinants of satisfaction with quality of life differ between the sexes. Since the number of respondents varies between the sampled


104



5.1 Descriptive analysis Table 6.1 shows responses to the satisfaction with work–life balance scale items and the mean value of the satisfaction with work–life balance scale for men and women in the participating countries. The highest satisfaction with work–life balance is found in the Netherlands (score of 3.63 on a scale of 1–5), followed by Sweden and Finland. The lowest satisfaction with work–life balance is found in Portugal and the UK. With the exception of Hungary, where women are significantly less satisfied with their work–life balance than men, there are no statistically significant differences in the average satisfaction with work–life balance between men and women. Country differences in the average score on the satisfaction with life scale render some support to the welfare regime hypothesis, showing the highest satisfaction with quality of life in Sweden, the Netherlands and Finland (Table 6.2), followed by the corporatist and sub-protective welfare regimes of Germany and Portugal. The lowest satisfaction with life is found in the UK, Bulgaria and Hungary. Gender differences are statistically significant in the UK, Hungary, Germany and the Netherlands. With the exception of Hungary, where women have lower life satisfaction, female employees evaluate their quality of life significantly higher than their male counterparts. Further analyses show that – as expected – satisfaction with work–life balance and satisfaction with life are positively correlated (r = 0.48). The strongest correlation between satisfaction with work–life balance and satisfaction with quality of life is found in Germany (0.57), followed by the UK, Sweden, the Netherlands, Finland, Portugal, Bulgaria and Hungary (0.41). Thus, regardless of country differences in satisfaction with work–life balance and satisfaction with life levels, the correlation between the two measures is quite close. Hence, satisfaction with the compatibility of work and family life appears to have a major influence on quality of life. Figure 6.2 displays this correlation for all 32 organizations surveyed. The average satisfaction with work–life balance score for each work organization is plotted against the average life satisfaction score for the respective organization. The


organizations, all findings are based on weighted analysis; all countries and organizations weight the same in the analysis. Because experimental research designs are not applied and longitudinal data are not available, however, we are not able to determine the directionality of the proposed relationships empirically (Stone-Romero and Rosopa, 2008).


Satisfaction with work–life balance: Items and the SWLB scale (per cent ‘very satisfied’ or ‘satisfied’ and scale means)

The following question concerns your satisfaction with your work and your personal life. Please indicate how satisfied or dissatisfied you are with:

Bulgaria Finland Germany

Hungary

Netherlands

Portugal

Sweden

UK

The way you divide your time between your work and personal life

Men Women All

44.0 39.1 40.3

58.1 55.8 56.2

50.5 52.7 51.8

38.0 27.4 32.8

64.4 68.5 67.2

42.7 41.2 42.0

54.2 52.3 53.0

42.2 43.3 42.9

Your ability to meet the needs of your job with those of your personal or family life

Men Women All

48.0 48.9 48.5

53.0 55.6 54.9

52.8 55.5 54.4

55.9 52.6 54.3

60.9 64.1 63.2

45.2 46.2 45.7

52.0 53.1 52.6

42.4 42.7 42.8

The opportunity you have to perform your job well and yet be able to perform home-related duties adequately

Men Women All

54.9 55.0 54.9

55.5 57.2 56.7

52.8 50.6 51.4

45.8 42.4 44.1

64.4 62.0 62.7

45.9 44.9 45.3

57.5 60.3 59.1

43.2 42.9 43.1

The satisfaction with work–life balance scale (SWLB) 1 = Very dissatisfied, 5 = Very satisfied (scale construction defined in Chapter 4)

Men Women All

N

3.44 3.33 3.35

753

Gender difference in SWLB (Eta)

0.054

3.45 3.42 3.43

908 0.016

3.35 3.39 3.38

1198 0.024

3.31 3.18 3.25

860 0.083 ∗∗

3.61 3.64 3.63

860 0.019

3.19 3.15 3.17

1372 0.023

3.49 3.50 3.49

648

3.16 3.21 3.19

788

0.005

Comment: Weighted analysis in scale differences of the Eta measure (all countries are given equal weight in terms of proportion of respondents). Note: ∗ p ≤ 0.05; ∗∗ p ≤ 0.01; ∗∗∗ p ≤ 0.001. The country differences in the SWLB scale are statistically significant at p ≤ 0.001 level (Eta = 0.17).


0.025


106

Table 6.1

Satisfaction with life: Items and the SWLS scale (per cent ‘strongly agree’, ‘agree’ or ‘slightly agree’ and scale means)

Below are five statements with which you may agree or disagree:

Bulgaria

Finland

Germany

Hungary

Netherlands

Portugal

Sweden

UK

In most ways my life is close to my ideal

Men Women All

44.1 39.1 40.3

58.1 64.7 63.3

58.1 58.6 58.3

59.6 54.3 57.1

61.9 72.5 69.2

52.4 53.5 53.0

60.8 61.3 61.2

37.8 43.3 41.0

The conditions of my life are excellent

Men Women All

39.1 37.7 38.2

66.6 72.5 71.2

59.7 64.5 62.4

46.9 38.9 43.0

76.5 76.8 76.6

50.0 50.4 50.1

72.9 71.0 71.5

42.2 48.0 45.7

I am satisfied with my life

Men Women All

53.6 50.0 50.7

78.4 80.9 80.4

74.7 77.6 76.5

62.8 54.4 58.7

80.2 85.0 83.5

67.9 68.0 67.9

82.3 83.1 82.9

51.0 54.9 53.2

So far I have got the important things I want in life

Men Women All

58.9 60.4 59.8

66.8 76.6 74.6

75.7 77.5 76.6

60.4 57.6 59.1

67.0 73.7 71.5

72.3 75.1 73.6

83.2 87.2 85.9

58.8 66.8 63.5

If I could live my life over, I would change almost nothing

Men Women All

48.1 44.7 45.5

54.5 60.7 59.4

45.1 50.4 48.3

35.1 35.1 35.1

41.9 59.4 53.9

51.4 55.9 53.8

54.5 64.1 60.5

32.8 40.3 37.0

The satisfaction with life scale (SWLS) Men 1=Strongly disagree, 7=Strongly agree Women (scale construction defined in All Chapter 4) N

4.29 4.16 4.19

749

Gender difference in SWLS (Eta)

0.047

4.72 4.89 4.86

906 0.060

4.58 4.78 4.70

1199 0.083∗∗

4.30 4.13 4.22

856 0.069∗

4.82 5.05 4.98

1011 0.099∗∗

4.43 4.44 4.44

1372 0.004

5.02 5.05 5.04

648 0.013

3.99 4.25 4.14

788 0.088∗∗


107

Comment: Weighted analysis of scale differences in the Eta measure (all countries are given equal weight in terms of proportion of respondents). Note: ∗ p ≤ 0.05; ∗∗ p ≤ 0.01; ∗∗∗ p ≤ 0.001. The country differences in the SWLS scale are statistically significant at p ≤ 0.001 level (Eta = 0.27).


Table 6.2

108


5,4 BI UH

5,2 UH

Overall life satisfaction (Means)

5,0 RS RS UH

4,8

BI

IT

RS IT

ITUH

4,6

BI

IT BI

4,4

RS

RS UH

UH

IT

IT

4,2 RS BI BI

4,0

IT RS UH

3,8 2,8

3,0

3,2

3,4

3,6

3,8

Satisfaction with work−life balance (Means) Country Bulgaria Hungary Netherlands UK

Portugal Sweden

Germany Finland

Total population Rsq = 0 6316 Figure 6.2 Correlation between satisfaction with work–life balance (SWLB) and life satisfaction (SWLS) across organizations and countries Note: BI = bank or insurance company, IT = information technology or telecom company, RS = retail company or supermarket, UH = hospital or university hospital.


UH IT

RS BI BI

correlation between the scales is higher on the aggregate organizational data (r = 0. 63) than on the individual-level country data. We see that organizations in the Netherlands, Sweden and Finland are situated in the upper right-hand corner of the graph as a rule, indicating


high satisfaction with work–life balance and high satisfaction with life. Organizations in Bulgaria, Hungary and the UK exhibit low satisfaction with work–life balance and low satisfaction with life.2 The highest average scores within a particular country are found in the higher status banking/insurance (Finland and UK) and hospital/healthcare organizations (Sweden, the Netherlands, Portugal and Bulgaria). However, the retail sector gets the highest score for satisfaction with quality of life in Germany and Hungary. Overall, Figure 6.2 shows a country pattern, but the pattern across organizational contexts is less clear. Hence, these initial findings do not tend to support the organizational hypothesis.

5.2 Multivariate analysis: satisfaction with life The results of the multivariate regression analysis – in which satisfaction with work–life balance is regressed on individual job and household demands and resources as well as organizational and country variables – are presented in Table 6.3. In Model 1, country dummies, work organizations and individual control variables explain about 12 per cent of the variance in satisfaction with the work–life balance. There are some gender differences in satisfaction with work–life balance determinants. Women in Portugal and Hungary do not differ from women in the UK in their satisfaction with work–life balance. In all other countries, however, women are significantly more satisfied with work–life balance than in the UK, which is the reference country in the analysis. The hospital provides a significantly more favourable working environment in terms of work–life balance than the banking/insurance or retail organizations. The least satisfied are women in IT/telecom organizations. Living in a particular country makes a large difference for men’s satisfaction with work–life balance. Men in Finland, Sweden, the Netherlands, Germany, Hungary and Bulgaria are significantly more satisfied than men in the UK and Portugal when we control for work organizations, education, age, health status and supervisory work position. When individual job demands and resources are added into the analysis (Model 2), the macro level country effects disappear to some extent. For women, the banking/insurance and hospital sectors provide better work environments for satisfaction with work–life balance than the retail and IT/telecom sectors. The organizational effects are also stronger – and indeed, highly statistically significant – for men working in the banking/insurance, hospital and IT/telecom sectors. Men working in higher status organizations feel greater satisfaction with their




110 Table 6.3 Least squares regression analysis of satisfaction with work–life balance for men and women (standardized OLS coefficients) Model 1 Women

Men

Model 2 Women

Men

Model 3 Women

Men

Country Finland Sweden The Netherlands Germany Portugal Hungary Bulgaria The UK (reference)

0.12∗∗∗ 0.07∗∗∗ 0.14∗∗∗ 0.09∗∗∗ 0.03 0.01 0.07∗∗∗

0.09∗∗∗ 0.05∗∗∗ 0.02 0.08∗∗∗ −0.01 −0.04∗ 0.12∗∗∗ 0.02 0.02 0.08∗∗∗ 0.02 −0.05∗∗ 0.00 0.05∗∗∗ 0.00 0.06∗∗ 0.03∗∗ 0.04∗∗ 0.07∗∗∗ 0.10∗∗∗ 0.07∗∗∗

0.06∗∗∗ 0.01 0.00 −0.04∗∗ 0.00 0.00 0.01 −0.06∗∗∗ 0.06∗∗∗ −0.01 0.02 0.02 0.07∗∗∗ 0.06∗∗

0.04∗ 0.04∗∗ 0.09∗∗∗ 0.04∗∗ 0.05∗ −0.02

0.06∗∗∗ 0.05∗∗∗ 0.00

Work organization Banking/insurance Hospital IT/telecom Retail/supermarket (reference)

0.01 0.04∗∗ −0.04∗∗∗

0.06∗∗∗ 0.08∗∗∗ 0.07∗∗∗

0.08∗∗∗ 0.08∗∗∗ 0.09∗∗∗

Controls Education Age Health status Supervisory position

−0.10∗∗∗ −0.08∗∗∗ −0.07∗∗∗ −0.03 −0.06∗∗∗ −0.03 0.12∗∗∗ 0.06∗∗∗ 0.14∗∗∗ 0.08∗∗∗ 0.14∗∗∗ 0.09∗∗∗ 0.30∗∗∗ 0.30∗∗∗ 0.20∗∗∗ 0.19∗∗∗ 0.18∗∗∗ 0.18∗∗∗ 0.04∗∗∗ 0.08∗∗∗ 0.01 0.06∗∗∗ 0.02 0.06∗∗∗

Job demands and resources Work demands (pressure) Career demands Job insecurity Working hours Commuting time Control over work, time, place Social support Work–life support Training (yes/no)

−0.20∗∗∗ −0.23∗∗∗ −0.19∗∗∗ −0.24∗∗∗ −0.14∗∗∗ −0.03∗∗ −0.14∗∗∗ −0.06∗∗∗ 0.09∗∗∗

−0.19∗∗∗ −0.07∗∗∗ −0.09∗∗∗ −0.10∗∗∗ 0.10∗∗∗

−0.13∗∗∗ −0.02 −0.14∗∗∗ −0.06∗∗∗ 0.08∗∗∗

−0.17∗∗∗ −0.06∗∗∗ −0.08∗∗∗ −0.09∗∗∗ 0.09∗∗∗

0.13∗∗∗ 0.08∗∗∗ 0.12∗∗∗ 0.07∗∗∗ 0.03∗∗ 0.10∗∗∗ 0.03∗∗ 0.10∗∗∗ −0.02 −0.02 −0.01 −0.01

Household demands and resources Housework (no. of hours) Care time (no. of hours) Disagreements about housework

0.00

0.01

0.01

−0.02


Variables

−0.10∗∗∗ −0.07∗∗∗



Variance explained (Adj. R2 ) Model significance (ANOVA)

0.07∗∗∗

0.05∗∗∗

−0.02 −0.01 0.07∗∗∗ 0.11∗∗∗

0.01 0.01 0.10∗∗∗ 0.11∗∗∗

0.13

0.12

0.27

0.34

0.30

0.36

0.000

0.070

0.000

0.000

0.000

0.000

Comment: N = 3912 (women), N = 2442 (men), weighted analysis (all organizations are given equal weight). Note: ∗ p ≤ 0.05; ∗∗ p ≤ 0.01; ∗∗∗ p ≤ 0.001.

work–life balance than those working in retail, for example. The results therefore imply that among men, country-level differences in satisfaction with work–life balance can to a large extent be attributed to differences in both organizational status and individual job demands and job resources. This finding further suggests that for men, country-level policies do not matter in the same way as they do for women. As hypothesized, heavy job demands significantly undermine satisfaction with the work–life balance. Work pressure, career demands and long working hours are particularly detrimental to the work–life balance. However, job-related resources improve employees’ ability to cope with the conflicting demands of work and non-work roles and increase individuals’ satisfaction with work–life balance. Important job-related resources are control over work and social support, and – for men particularly – support for work–life balance issues. Job training is a less salient resource in this respect. It is also worth noting that the inclusion of job demands and resources increases the proportion of explained variance in the model significantly. When household demands and resources are added in Model 3 (Table 6.3), the least satisfied with their work–life balance are male employees in Sweden and Germany, and the most satisfied are women in Finland, Portugal and Bulgaria, as well as Bulgarian men. Male workers in the banking/insurance, hospital and IT/telecom sectors continue to exhibit a higher level of satisfaction with their work–life balance than those employed in retail. The effects of job and household demands and resources show a very similar pattern for men and women. Job demands have a negative effect, while job autonomy, social support and work–life


−0.06∗∗∗ −0.02

Number of children (at home) Partner (married/ living together) Household income Paid domestic help Childcare flexibility Social networks



balance support contribute positively to satisfaction with work–life balance. Having a partner, flexibility in childcare and supportive social networks increase satisfaction with work–life balance, while satisfaction with work–life balance is negatively associated with disagreements over housework in couple households. For female workers, satisfaction with work–life balance is further reduced by each additional child in the home. Household income and paid domestic help have no significant effect on satisfaction with work–life balance. In conclusion, individuals’ job and household demands and resources to a large extent determine their satisfaction with their work–life balance. Good health and older age also contribute to higher satisfaction with work–life balance. Interestingly, higher occupational status seems to be a valuable resource for men but not for women. When controlling for work and household characteristics, supervisory positions are associated with higher satisfaction with work–life balance in men but not in women. Moreover, highly educated women experience less satisfaction with work–life balance than women with lower levels of education. At the meso level, higher status organizations provide more favourable conditions for the work–life balance, particularly for men. Macro-level determinants, however, are not particularly relevant in explaining satisfaction with work–life balance when individual job and household demands and resources are included in the analysis. This pattern differs considerably from the analysis of satisfaction with quality of life, to which we turn next.

5.3 Multivariate analysis: satisfaction with life When satisfaction with quality of life is regressed on our set of independent macro, meso and micro variables and satisfaction with work–life balance, a different picture emerges. Country dummies that capture country-level differences in economic development, welfare security and other societal characteristics distinguish between countries in which service sector employees exhibit higher levels of life satisfaction – Finland, Sweden, the Netherlands, Germany and Portugal – and those with lower levels of life satisfaction, such as Bulgaria, Hungary and the UK (Table 6.4). In terms of work organization status, few differences can be found in the full model. There are some indications that female workers in the hospital and banking/insurance sectors are more satisfied with their quality of life than women in other service sectors included in the study, but these differences are minor and of only borderline significance.


112


Least squares regression analysis of life satisfaction for men and women (standardized OLS coefficients)

Variable and statistics

Model 1

Model 2

Model 3 Women

Men

Model 4

Women

Men

Women

Men

Women

Men

0.18∗∗∗ 0.18∗∗∗ 0.18∗∗∗ 0.15∗∗∗ 0.05∗∗∗ −0.04∗∗ −0.02

0.13∗∗∗ 0.22∗∗∗ 0.19∗∗∗ 0.15∗∗∗ 0.08∗∗∗ 0.06∗∗ 0.02

0.13∗∗∗ 0.10∗∗∗ 0.11∗∗∗ 0.11∗∗∗ 0.07∗∗∗ −0.02 −0.01

0.09∗∗∗ 0.06∗∗∗ 0.11∗∗∗ 0.06∗∗∗ 0.02 0.00 −0.01

0.17∗∗∗ 0.16∗∗∗ 0.11∗∗∗ 0.14∗∗∗ 0.12∗∗∗ 0.04∗∗ 0.08∗∗∗

0.10∗∗∗ 0.09∗∗∗ 0.11∗∗∗ 0.08∗∗∗ 0.05∗ 0.07∗∗∗ 0.06∗∗

0.15∗∗∗ 0.15∗∗∗ 0.11∗∗∗ 0.14∗∗∗ 0.10∗∗∗ 0.04∗ 0.06∗∗∗

0.04∗∗ 0.03∗ −0.02

0.04 0.04∗ 0.02

0.06∗∗∗ 0.03∗∗ 0.00

0.05∗∗ 0.06∗∗∗ 0.03

0.05∗∗∗ 0.04∗∗∗ 0.00

0.03 0.04∗ 0.01

0.03∗∗ 0.02∗ 0.00

0.04∗∗∗ 0.05∗∗∗ 0.32∗∗∗ −0.07∗∗∗

0.04∗∗ 0.04∗∗ 0.32∗∗∗ −0.10∗∗∗

0.04∗∗ 0.05∗∗∗ 0.25∗∗∗ −0.06∗∗∗

0.01 0.02 0.23∗∗∗ −0.04∗

0.01 0.01 0.23∗∗∗ −0.03∗∗

0.00 −0.04∗∗ 0.21∗∗∗ 0.00

0.03∗∗ −0.04∗∗∗ 0.17∗∗∗ −0.04∗∗∗

0.00 −0.07∗∗∗ 0.15∗∗∗ −0.02∗

−0.04∗∗∗ −0.05∗∗ −0.12∗∗∗

−0.05∗∗∗ −0.05∗∗∗ −0.08∗∗∗

−0.03∗∗ −0.05∗∗∗ −0.08∗∗∗

−0.06∗∗∗ −0.04∗∗ −0.06∗∗∗

0.03∗∗ 0.00 −0.08∗∗∗

0.02 0.02 −0.04∗∗∗

Country Finland Sweden The Netherlands Germany Portugal Hungary Bulgaria The UK (reference)

0.10∗∗∗ 0.11∗∗∗ 0.11∗∗∗ 0.10∗∗∗ 0.05∗∗ 0.06∗∗ 0.04∗

Work organization Banking/insurance Hospital IT/telecom Retail/supermarket (reference)

0.00 0.01 −0.02

Controls Education Age Health status Supervisory position Job demands and resources


113

Work demands (pressure) Career demands Job insecurity


Table 6.4

Variable and statistics

Model 1 Women

Men

Model 2 Women ∗∗∗

−0.07 −0.04∗∗∗ 0.09∗∗∗ 0.11∗∗∗ 0.07∗∗∗ −0.01

Working hours Commuting time Control over work, time, place Social support Work–life support Training (yes/no)

Model 3

Men ∗

−0.03 −0.07∗∗∗ 0.26∗∗∗ 0.11∗∗∗ 0.07∗∗∗ 0.01

Household demands and resources Housework (no. of hours) Care time (no. of hours) Disagreements about housework Number of children (at home) Partner (married/living together) Household income Paid domestic help Child care flexibility Social networks Satisfaction with work–life balance Variance explained (Adj. R2 ) Model significance (ANOVA)

0.20 0.000

0.18 0.000

0.27 0.000

0.31 0.070

Women ∗∗∗

−0.06 −0.03∗∗∗ 0.07∗∗∗ 0.11∗∗∗ 0.06∗∗∗ 0.00

0.00 0.00 −0.12∗∗∗ −0.01 0.17∗∗∗ 0.13∗∗∗ 0.02∗ 0.03∗∗∗ 0.11∗∗∗

0.34 0.000

Model 4

Men

Women

Men

−0.04 −0.07∗∗∗ 0.23∗∗∗ 0.11∗∗∗ 0.07∗∗∗ 0.01

−0.01 −0.02 0.04∗∗∗ 0.08∗∗∗ 0.05∗∗∗ 0.00

−0.01 −0.04∗∗ 0.20∗∗∗ 0.08∗∗∗ 0.03∗ 0.02

0.01 −0.03∗∗ −0.10∗∗∗ 0.03 0.11∗∗∗ 0.13∗∗∗ 0.06∗∗∗ 0.02 0.10∗∗∗

0.00 −0.01 −0.09∗∗∗ 0.01 0.15∗∗∗ 0.14∗∗∗ 0.02∗ 0.01 0.07∗∗∗

0.01 −0.03∗ −0.08∗∗∗ 0.03∗∗ 0.10∗∗∗ 0.13∗∗∗ 0.06∗∗∗ −0.02 0.06∗∗∗

0.33∗∗∗

0.34∗∗∗

0.41 0.000

0.43 0.000

∗∗

0.36 0.000

Comment: N = 3912 (women), N = 2440 (men), weighted analysis (all organizations are given equal weight). Note: ∗ p ≤ 0. 05; ∗∗ p ≤ 0. 01; ∗∗∗ p ≤ 0. 001.



(Continued)

114

Table 6.4

Job demands and resources and household demands and resources contribute significantly to employees’ satisfaction with life; some, however, are mediated by satisfaction with work–life balance, which has an extraordinarily strong effect (β = 0. 33, p ≤ 0. 001 and β = 0. 34, p ≤ 0. 001 for women and men, respectively) on satisfaction with life in general. The full model explains 43 per cent of variance in life satisfaction for men, and 41 per cent for women. Job and household demands that remain significant in terms of their impact on satisfaction with life are job insecurity and domestic disagreements over housework, which lower life satisfaction regardless of satisfaction with work–life balance. Employees’ satisfaction with life increases significantly, however, if they feel they have control over their work, perceive that they have social support in the workplace and satisfaction with work–life balance support, live with a partner, and have a high household income, paid domestic help and supportive social networks. Control variables show that good health has a strong positive and age a negative effect on overall life satisfaction. Highly educated women are somewhat more satisfied with their lives, but a supervisory position appears to lower life satisfaction, despite the higher occupational status. These findings have three major implications. First, job demands and resources related to the workplace have a major influence on satisfaction with work–life balance. Moreover, organizational context seems to be relevant as well. For women, the number of children constitutes an additional obstacle to work–life balance. It appears that national policies targeting equality between the genders with respect to work–life balance have been ineffective so far. Secondly, the affluence and welfare policies of the relevant nation nevertheless continue to have a major influence on overall satisfaction with life and on the household situation to some extent. Thirdly, because of the close relationship between satisfaction with work–life balance and quality of life, the findings suggest that a work–life balance that contributes to a higher quality of life depends to a large extent on personal and organizational or workplace initiatives as well as national policies. Thus, although the European Union has identified the compatibility of work and family life as a core value for quality of life in Europe, the phenomenon continues to rest on individual and organizational workplace initiatives in combination with the national institutional context.



6 Conclusion In this chapter we linked research on subjective quality of life, measured with the global life satisfaction scale (Pavot and Diener, 1993),



to research on work–life balance, specifically satisfaction with work–life balance. The objective was to assess the relationship between satisfaction with work–life balance and quality of life, taking into account job and household demands and resources on the individual level, the status of work organizations on the meso level, and countries on the macro level. Satisfaction with work–life balance is to a large extent determined by job demands and resources. Household demands, such as the number of hours spent on household chores and childcare, do not significantly lower satisfaction with the work–life balance, unless a couple disagrees about housework. The number of children is negatively related to satisfaction with work–life balance for women only, which underlines gendered responsibilities for childbearing and childcare. Support (social support as well as specific support for the work–life balance at work and supportive social networks in private life) and control over how, where and when work is done, as well as childcare flexibility are valuable resources that increase individuals’ ability to balance their work and private life. Gender differences in work–life balance satisfaction are most obvious in relation to the status and involvement of the work organization. Organizations with a higher status and workplace work–life balance support offer better conditions for fostering men’s satisfaction with their work–life balance. This is largely independent of country of residence. Life satisfaction, however, varies between countries when we control for individual- and organizational-level characteristics. Our results on service sector employees in selected organizations corroborate the results found in large-scale cross-national surveys. There are large differences in life satisfaction among European countries; in general, satisfaction is higher in more affluent societies and those that provide greater support for the social welfare of their citizens. The organizational status hypothesis receives little support in our analyses. Individuals’ job and household demands and resources do affect life satisfaction; however, satisfaction with work–life balance mediates many of these relationships. For example, the negative effects of working hours and career demands on life satisfaction disappear when satisfaction with work– life balance is taken into account. Our results confirm that satisfaction with work–life balance and overall life satisfaction are closely related. The greater the satisfaction with the work–life balance, the greater the overall life satisfaction. Hence, organizational and personal initiatives intended to improve individuals’ ability to balance work and non-work roles may increase not only satisfaction with their work–life balance,


116


but also their general life satisfaction, contributing to a higher quality of life. One major implication of this is that work organizations should pay closer attention to work–life balance support policies, as well as ensure that their employees have enough job resources to meet their job demands. This could be particularly important for women regardless of the work organization and for employees in lower status organizations more generally. The results of our study are consistent with the assumed causal model presented in Chapter 2, although we found the impact of the workplace context to be less substantial than expected. We used a rather crude measure for the impact of the organization: workplace status. Future research should elaborate on this by considering several workplace factors, such as the impact of organizational culture alongside formal work–life policies and high-performance work systems. Furthermore, we cannot rule out alternative explanations for the relationships we detected. Experimental research designs and longitudinal studies would be required to determine the directionality of the proposed relationships. Although our model explained more than 40 per cent of variance in life satisfaction, additional efforts to improve our understanding of the determinants of quality of life could include more indicators of other aspects of life that may affect satisfaction with work–life balance and life satisfaction. This would render the analysis more open to examining interactions between various determinants and levels of analysis, and lead to a better understanding of the complex concept of quality of life.

Notes 1. Chapter 9 discusses and analyses the gender perspective in relation to quality of life. 2. Findings from other studies generally confirm that the UK has lower life and job satisfaction, and higher work–home interference than Sweden, Finland, the Netherlands and Germany (Fahey and Smyth, 2004; Pichler and Wallace, 2009). However, when drawing conclusions from representative survey data – rather than from service sector organizations – the difference is less striking and the UK is less of an outlier than in our study.




Variations in Work–life Balance Satisfaction among Service Sector Employees Barbara Beham, David Etherington and Eduardo Rodrigues

1 Introduction The work–life balance has become a key area of concern for today’s workers (Valcour, 2007). The existing work–family research and literature has tended to focus on homogeneous samples of managerial and professional workers, with very few studies covering the work– life experiences of other employee categories (Casper et al., 2007). We therefore know relatively little about the work–life experiences of non-professional workers, older workers, part-time employees or ethnic minorities, for example. By investigating satisfaction with work–life balance for various employee categories working in a range of different service sector organizations, the present chapter fills this gap in the work–family literature. More specifically, we look at satisfaction with work–life balance and its relationship with work-related antecedents for professional versus non-professional, full-time versus part-time and older versus younger workers. We selected these categories to compensate for the shortcomings of previous research, which failed to examine the work–life experiences of lower-level non-professional workers (Lambert, 1999), the rise in part-time work due to the increasing flexibility of European workplaces and the ageing of our workforce. The broader theoretical framework of the study is presented in Chapter 2. A detailed discussion of the concept of satisfaction with work–life balance is provided in Chapter 6. Data from the Quality survey allow us to look at differences between the aforementioned employee categories and improve our understanding of the impact of European welfare state policies on service sector


7

118


119

employees’ satisfaction with work–life balance. The majority of studies on satisfaction with work–life balance have been conducted in the US (e.g. Saltzstein et al., 2001; Clark, 2001b; Greenhaus et al., 2003; Clarke et al., 2004; Valcour, 2007), meaning that little is known about the work–life experiences of employees in the European context. The eight countries under investigation represent various welfare state regimes, each characterized by a different level of state support for work and family (see Chapter 3 for more details). By including the level of state support for work–life integration in our statistical analysis, we examine whether the country context influences employees’ ability to successfully combine work and private life.

2 Employee categories 2.1 Professional versus non-professional workers Empirical evidence suggests that the work–life experiences of professional workers may differ from those of non-professional workers (e.g. Frone et al., 1992; Lambert, 1999; Casper et al., 2007; McGinnity and Calvert, 2009). The increasing speed at which business is transacted and such trends as globalization, restructuring and downsizing have placed more job demands on professional and managerial workers over the past 10 to 15 years. Professionals are under pressure to work faster and put in longer hours (Milliken and Dunn-Jensen, 2005). Higgins et al. (2000) found individuals working in professional and managerial occupations to be more closely involved in their work than employees in ‘earner’ occupations such as clerical, administrative or production work. Frone et al. (1992) saw a significant positive relationship between job involvement and work-to-family conflict for white-collar but not bluecollar workers. They concluded that the two groups differed in terms of the time input and level of temporal flexibility required by their jobs. Blue-collar workers are less likely than white-collar workers to spend leisure time in the workplace or to bring work home with them. A study by Grzywacz et al. (2007) of Latino poultry workers in the US revealed a low frequency of work–family conflict. Similar findings were reported by Grant-Vallone and Donaldson (2001) in a study among US non-professionals. One study conducted in eight Western European countries reported work–life conflict to be higher among professional than nonprofessional workers. After controlling for a range of job and family demands, the researchers found that differences in work–family conflict


Barbara Beham et al.


Variations in Work–life Balance Satisfaction

between professional and non-professional workers scarcely varied from one country to the next, with Sweden being the sole exception. Higher levels of work–family conflict among professionals can be partially explained by their longer hours and greater job pressure compared with non-professionals (McGinnity and Calvert, 2009). These results contradict the views of work–family researchers who argue that nonprofessional and marginalized workers, such as immigrants, have an especially difficult time balancing job and family demands because their jobs offer little autonomy and temporal flexibility. In addition, work–family policies such as flexitime or teleworking are often not available to non-professionals (e.g. Glass and Estes, 1997; Lambert, 1999; Golden, 2001). Tausig and Fenwick (2001), for example, found no difference in the work–life balance of professional and blue-collar workers in the US after controlling for individual and family characteristics and differing work schedules. Regardless of occupational status, perceived scheduling control increased satisfaction with the work–life balance.

2.2 Part-time versus full-time workers There has been an increase in part-time and atypical work in the past 10 years (Gasparini et al., 2000), and working part time has become a customary strategy for combining paid employment and family responsibilities, especially for women with children or elderly relatives. Working a part-time schedule is thought to provide employees with more convenient working hours, produce less stress and exhaustion, and enable them to better meet their personal and family responsibilities (Hakim, 1996; Barnett and Gareis, 2002). Some studies reported part-time work to be related to lower levels of role overload and work-to-family conflict and to higher levels of work–family balance (Fast and Frederick, 1996; Higgins et al., 2000; Van Rijswijk et al., 2004). However, these findings are contradicted by other research showing that part-time employees report more physical and mental health problems, less career satisfaction and job security, lower marital quality and a poorer work–life balance (Tausig and Fenwick, 2001; Barnett, 2003). In addition, merely cutting down on working hours proved to be unrelated to outcome variables such as burnout, job-role quality, intentions to leave the organization, life satisfaction and well-being (Barnett, 2003; Van Rijswijk et al., 2004). These inconsistent findings may be due to a number of methodological and conceptual problems, for example differing definitions of


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part-time and full-time work, the different reasons for working part time (voluntary vs. involuntary part-time work) and the varying nature of part-time jobs (Barnett and Gareis, 2000). Part-time employment is often concentrated in low-skill and low-quality work that tends to offer little job autonomy, inflexible working environments, limited career opportunities and fewer financial resources compared with full-time employment (Walsh, 2007). These disadvantages of ‘bad’ part-time jobs clearly hamper part-time workers’ ability to better manage their work and non-work responsibilities. On the other hand, employees in ‘good’ part-time jobs with appropriate salaries and opportunities for promotion, high levels of job autonomy and scheduling flexibility are in fact able to enhance their work–life balance (Van Rijswijk et al., 2004). Good part-time jobs are still quite scarce, however, and found in only a few professions (Barnett and Gareis, 2002).

2.3 Younger versus older workers The increasing number of older workers requires governments and organizations to rethink their work–life integration initiatives. Older workers differ significantly from their younger counterparts when it comes to their work–life needs. Younger workers place more emphasis on their careers and on the problems and challenges related to childcare, whereas older employees focus more on their private lives and social relationships. Balancing work and private/family life seems to be more important for older workers. Care responsibilities are furthermore no longer limited to younger employees; with life expectancy increasing and parenthood being postponed, more and more older employees have to combine child and elderly care duties with paid employment (Baltes and Young, 2007). Although there is much discussion of the ageing workforce in the business community and among the general public, very few studies have investigated the differences between older and younger workers in terms of work–family issues. A study by Higgins et al. (1994) revealed that older employees experience lower levels of work–family conflict because they have fewer childcare responsibilities later in life. Gordon et al. (2007) examined a US sample of working women over the age of 50. They found older women to experience greater amounts of work-to-family conflict than family-to-work conflict and greater amounts of family-to-work enhancement than work-to-family enhancement. However, these findings do not differ from prior research on other populations (Greenhaus and Powell, 2006). Tausig and Fenwick (2001)




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3 Hypotheses Our first set of hypotheses examines differences in satisfaction with work–life balance between the various employee categories. In line with previous findings in work–family research (see above), we expect satisfaction with work–life balance to be higher among non-professional workers (Hypothesis 1a), part-time employees (Hypothesis 1b) and workers older than 50 (Hypothesis 1c). We also investigate whether occupational class differences persist when job demands and resources are added into the equation. Professional workers frequently have more challenging jobs than non-professionals, with more job demands but also more job autonomy. However, the heavier work pressure and organizational demands may outweigh the greater job control, reduce their ability to balance work and private responsibilities and lead to lower overall levels of satisfaction with work–life balance. Part-time workers are thought to feel less career and work pressure because they are more frequently found in non-supervisory, routine jobs, but to also exercise more control over their working time, which may result in higher levels of satisfaction with work–life balance. Older workers in later career stages may experience less career and work pressure because they have more experience, and more job autonomy because they more frequently occupy managerial positions than younger workers. Accordingly, we expect non-professionals (Hypothesis 2a), part-time employees (Hypothesis 2b) and older workers (Hypothesis 2c) to report higher levels of satisfaction with work–life balance (after controlling for individual job demands and resources). Given the cross-national composition of our sample, we also examine whether employees living in countries with high or low levels of state support for work and family evaluate their work–life balance differently. We may assume that in those countries that offer employees and their families less support, it is a greater challenge for employees to balance work and private life than in those countries with more developed welfare and employment regulations. Accordingly, we hypothesize that employees in ‘high state support’ countries are more satisfied with


reported higher levels of perceived work–life imbalance among younger and better educated employees. A study using data taken from the 2005 European Working Conditions Survey showed that older workers felt more satisfaction with the way they balanced work and family/social commitments (Villosio et al., 2008).


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their work–life balance, above and beyond individual job demands and resources (Hypothesis 3). One could argue that higher levels of state support for work–life integration narrow the gap in satisfaction with work–life balance between employee categories because employees are less dependent on the discretion of their company. McGinnity and Calvert (2009), for example, found only minor differences in work– family conflict between female professionals and non-professionals in the Netherlands and Sweden, countries with high levels of support for reconciling work and family life. Part-time employees, for example, may be more satisfied with their work–life balance because they have more control over their working hours and feel less work and career pressure. However, in ‘high state support’ contexts fostering equal job opportunities and work–life integration, a less precarious labour market and a wide range of public work–family policies may compensate for the heavier job demands of full-time employees and thus minimize the gap in satisfaction with work–life balance between part-time and full-time workers. A similar case can be made for older versus younger workers. Younger workers may experience lower levels of satisfaction with work– life balance because they feel more work and career pressure and have less job autonomy than older workers. However, in countries with high levels of state support for work–life integration, younger workers may be better able to combine work and private responsibilities, and may thus be as satisfied with their work–life balance as older workers. Accordingly, we hypothesize that the gap in satisfaction with work–life balance between professionals and non-professionals (Hypothesis 4a), part-time and full-time employees (Hypothesis 4b) and younger and older workers (Hypothesis 4c) will be smaller in high state support countries (after controlling for individual job demands and resources).

4 Method The analysis in this chapter draws on survey data collected in four different service organizations (IT/telecom, banking/insurance, hospital and retail) in the respective countries (for details on how job demands and resources and satisfaction with work–life balance were measured, see Chapter 4). Survey participants were asked to describe their jobs and indicate their contractual working hours, supervisor status and the number of employees that they supervise. Job descriptions were coded using the International Standard Classification of Occupations (ISCO 88). The Erikson and Goldthorpe (1992) class schema, generally referred to as the EGP scheme, proposes 10 occupational groups allowing for





comparative analysis between different employee categories. We used ISCO-88 codes, supervisor status, number of employees under supervision and employment status (self-employed vs. employed; in our case we did not have any self-employed in our sample) to assign the participants to the various EGP classes. Given that our interest was in comparing professional and non-professional workers, we collapsed the EGP classes ‘high and low controllers’ into a new category of ‘professionals’ and the EGP classes ‘routine non-manual’, ‘routine manual’, ‘semi-unskilled manual’, ‘skilled manual’ and ‘manual supervisor’ into the category ‘non-professionals’. Professional status was then dummy-coded, with 1 = professional and 0 = non-professional. Participants also indicated the number of hours they were contracted to work for their organizations. The ILO Part-time Work Convention defines a part-time worker as an ‘employed person whose normal hours of work are less than those of comparable full-time workers’ (ILO, 1994). This definition does not tell us how many hours per week comprise a part-time job because the number of hours per week considered full time differs significantly per country, profession or even activity. Following the approach of Bielenski et al. (2002), who distinguished between marginal (up to 19 hours per week) and substantial (20–34 hours per week) part-time work, we defined part-time work as having fewer than 35 contracted hours per week in this study. Part-time status was dummy-coded, with 1 = working part time and 0 = working full time. The definition of an ‘older worker’ is debatable, as illustrated by research in the US. There, anyone over 40 is protected by the Age Discrimination in Employment Act (ADEA), and for hiring purposes, an employee older than 40 is considered an older worker (James, 2007). A study conducted by Reynolds et al. (2005) reported that nearly 40 per cent of employees think that employers begin to view employees as old by the age of 50. In line with these results, we collapsed the participants into two groups: employees over 50 (dummy code = 1) and employees aged 50 and younger (dummy code = 0). Based on the levels of statutory support for work and family life (see Table 3.3 in Chapter 3), we can group our eight countries into high and low state support countries. Whereas Finland, Sweden, the Netherlands and Germany can be described as high state support countries, the UK, Portugal, Hungary and Bulgaria are characterized by low levels of state support for work and family life. Country clusters are dummy-coded, with 1 = high state support and 0 = low state support for the work–life balance.


124


125

The following variables were included for job demands and resources: career demands, work pressure, job insecurity, job control and social support at work (see Chapter 4 for details). Respondent control variables were sex (0 = male; 1 = female), married or living with a partner (0 = no partner; 1 = partner) and children (0 = children; 1 = no children), added in all statistical analyses.

5 Results 5.1 Descriptive statistics Table 7.1 summarizes the distribution of the various employee categories in the sample. The percentage of non-professionals ranged from 17.3 per cent in Hungary to 52.2 per cent in Finland. Part-time work is especially common in the Netherlands, with more than half of the Dutch participants indicating that they worked fewer than 35 hours per week. Working part time has become the preferred flexible work arrangement for women in the Netherlands, allowing them to combine work and family responsibilities. Working reduced hours is less common in the Nordic countries, where institutional policies support equal and full-time employment for both sexes. It is almost non-existent in the former communist countries and in Portugal, where working part time is still not thought of as a viable strategy for combining work and family life (see Chapter 3 for more detailed information on the institutional context of the participating countries). Overall, 87.1 per cent of all part-time workers in the sample were female and 57.4 per cent were Table 7.1

Sample composition Part-time∗

Non-professional

FI SE UK NL GER PT HU BG TOTAL ∗ Working

Age 50+

Total

N

Per cent

N

Per cent

N

Per cent

n

486 245 365 485 367 436 143 329

52.2% 37.8% 47.7% 48.5% 30.8% 32.0% 17.3% 47.3%

152 146 187 547 325 50 24 35

18.8% 24.1% 24.0% 54.4% 27.3% 4.2% 3.2% 5.1%

191 213 218 245 306 142 147 150

21.2% 33.1% 28.0% 24.3% 25.8% 10.5% 17.4% 20.9%

908 648 789 1012 1198 1372 860 760

2856

38.4%

1466

20.9%

1612

21.4%

7547



fewer than 35 hours per week.



non-professionals. Retail companies and hospitals had the highest proportions of females and consequently of part-time workers. The share of employees older than 50 ranged from 10.5 per cent in Portugal to 33.1 per cent in Sweden. Sixty-one per cent of all employees over 50 were professionals. Employees over 50 were almost evenly distributed across the four sectors. The distribution of EGP classes in the sample is shown in Table 7.2. The majority of participants fall into either the high or low controller categories. Examples of high controllers are team leaders and hospital doctors; low controllers include nurses and IT technicians. Among the non-professional workers, the largest group is the routine non-manual workers (e.g. secretary). Given that the study was conducted in the service sector, it is not surprising that the number of manual workers in the sample is rather small. Professional workers are mainly employed in the IT/telecom sector, followed by hospitals and the banking/insurance sector. The proportion of non-professional employees is highest in the retail sector. Table 7.3 presents the mean scores of the study variables for the different employee categories. Independent sample T-tests were performed (analysis not presented in this chapter) to determine whether the various categories differ in the reported mean scores. Non-professionals reported higher levels of satisfaction with work–life balance and job insecurity and lower levels of career demands, work pressure and job resources than professionals. Part-time and older workers experienced higher levels of satisfaction with work–life balance than full-time and younger employees. Full-time employees reported higher work pressure but also higher levels of job control than part-time employees. Older Table 7.2

Occupational status n

Per cent

1744 2802

23.6% 37.9%

Manual supervisor Routine non-manual Semi-unskilled manual Skilled manual

19 2611 176 32

0.3% 35.4% 2.4% 0.4%

TOTAL

7384

Professional High controllers Low controllers Non-professional


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Barbara Beham et al. Mean scores of study variables Professional

Nonprofessional

3.32

3.40

3.57

3.30

3.45

3.32

3.05 2.56 2.34 2.29 3.95

2.93 2.49 2.50 1.79 3.90

2.68 2.43 2.21 1.86 3.94

3.09 2.56 2.45 2.06 3.92

2.94 2.58 2.33 2.08 3.92

3.02 2.52 2.42 2.02 3.94

Satisfaction with work–life balance Career demands Work pressure Job insecurity Job control Social support at work

Part- Full- Age time time 50+

Younger

workers experienced lower levels of career demands and job insecurity, but higher levels of work pressure and job control than their younger colleagues. No significant differences were found between part-time and full-time and younger and older workers for social support at work. Figures 7.1–7.3 show country variations in the mean satisfaction with work–life balance scores for the various employee categories. In all countries, except the UK and Bulgaria, non-professional workers reported higher levels of satisfaction with work–life balance than professional workers (Figure 7.1). The difference is greatest in Portugal and smallest in Hungary and the two Nordic countries. A possible Mean satisfaction with-life balance 3.80 3.70 3.60 3.50 3.40 3.30 3.20 3.10 3.00 2.90 2.80 FI

SE

UK

NL Prof

GER

PT

HU


Table 7.3

127

BG

Non-prof

Figure 7.1 Country variation in satisfaction with work–life balance (mean scores) for professionals and non-professionals


128


FI

SE

UK

NL

Part-time

GER

PT

HU

BG

Full-time

Figure 7.2 Country variation in satisfaction with work–life balance (mean scores) for part-time and full-time employees

Mean satisfaction with-life balance 3.80 3.70 3.60 3.50 3.40 3.30 3.20 3.10 3.00 2.90 2.80

FI

SE

UK

NL

50+

GER

PT

HU

BG

Under 50

Figure 7.3 Country variation in satisfaction with work–life balance (mean scores) for older and younger employees

explanation for the inverse results in the UK may be that professional workers there reported much higher levels of job control than nonprofessional workers. Bulgarian professionals also reported higher levels of job control and significantly fewer working hours per week than non-professionals (42.26 hours compared with 46.27 hours). In all other


Mean satisfaction with-life balance 3.90 3.80 3.70 3.60 3.50 3.40 3.30 3.20 3.10 3.00 2.90 2.80


129

countries (except for Finland, where data on actual working hours per week were missing), professionals reported longer actual working hours than non-professionals. In all countries, part-time workers reported higher levels of satisfaction with work–life balance than full-time workers (Figure 7.2). These results may be explained in part by our sample, which consists of employees in IT/telecom, banking/insurance, hospitals and retail. Except for retail, all these sectors have large numbers of professionals. Accordingly, the proportion of good part-time jobs in this sample may be higher than in a representative sample of all sectors in a country. The difference between part-time and full-time employees is greatest in the UK, where there are few statutory family support and childcare provisions, and smallest in the Nordic countries, where employees enjoy a high level of state support for work–life integration. With respect to age differences, employees over 50 reported higher levels of satisfaction with work–life balance than their younger counterparts in all countries (Figure 7.3). The difference between older and younger employees is especially marked in Bulgaria. Actual working hours per week may partially explain these differences. Whereas older workers reported working longer hours than younger employees in the majority of countries, in Bulgaria and the UK (where the satisfaction with work–life balance gap is also quite large), older employees worked significantly fewer hours per week than their younger counterparts. No significant differences were found between older and younger Bulgarian workers in terms of negative work–family interference (analysis not shown).

5.2 Multivariate statistics Table 7.4 presents a number of linear regression models of satisfaction with work–life balance for the pooled data. Unstandardized regression coefficients are reported in all models. Models 1–3 examine employee class differences in satisfaction with work–life balance with professionals, full-time employees, and younger workers as the reference categories. Model 1 shows that non-professional workers experienced higher levels of satisfaction with work–life balance than professional workers. However, the effect size is very small and only significant at the 10 per cent level. Consistent with predictions, part-time workers (Hypothesis 1b) and older workers (Hypothesis 1c) were more satisfied with their work–life balance than full-time and younger employees.




130

Variations in Work–life Balance Satisfaction Table 7.4 Linear regressions – satisfaction with work–life balance (pooled sample)

Constant Non-professional Part-time Age 50+ Female Partner Children Career demands Work pressure Job insecurity Job control Social support Adjusted R2 N

3.26∗∗ 0.04∼ 0.26∗∗ 0.14∗∗

0.02 7547

Model 2 5.00∗∗ 0.03∼ 0.14∗∗ 0.13∗∗ –0.04∗ 0.09∗∗ –0.09∗∗ –0.18∗∗ –0.39∗∗ –0.08∗∗

0.19 7547

Model 3 3.75∗∗ 0.09∗∗ 0.16∗∗ 0.13∗∗ –0.03 0.08∗∗ –0.10∗∗ –0.16∗∗ –0.35∗∗ –0.05∗∗ 0.14∗∗ 0.19∗∗ 0.23 7547

Note: ∼ p < 0.10; ∗ p < 0.05; ∗∗ p < 0.01.

When demographic variables and job demands are added into the equation, employee category differences remain significant but the difference between part time and full time decreases markedly in Model 2 (B = 0. 26, p < 0. 01 to B = 0. 14, p > 0. 01). In Model 3, differences between part-time and full-time and older and younger employees remain significant and almost unchanged in size, while the difference between professionals and non-professionals increases in size and significance. Accordingly, Hypotheses 2a–c are supported by our data. Model 3 explains 23 per cent of the variance. Next, we explore whether employee category differences in satisfaction with work–life balance vary between countries with high versus low state support for work–life balance (Table 7.5). Model 4 is a variant of Model 1 (Table 7.4) and presented here for comparison with other models. In Model 5, we use interaction terms to introduce the effect of employee category by level of state support on satisfaction with work–life balance. Models 6 and 7 add control variables, job demands and resources into the regression equation. Higher levels of state support for the work–life balance are significantly related to higher levels of satisfaction with work–life balance, providing initial support for Hypothesis 3. However, when individual job demands are taken into account, the relationship becomes insignificant. Adding job


Model 1



Linear regressions – satisfaction with work–life balance, all employees

Constant Non-professional Part-time Age 50+ High state support Non-prof∗ High state support Part-time∗ High state support Age 50+∗ High state support Female Partner Children Career demands Work pressure Job insecurity Job control Social support Adjusted R2 N

Model 4

Model 5

Model 6

Model 7

3.25∗∗ 0.04∼ 0.26∗∗ 0.14∗∗

3.17∗∗ 0.00 0.19∗∗ 0.16∗∗ 0.24∗∗ 0.06 −0.01 −0.06∗

5.02∗∗ 0.02 0.18∗∗ 0.12∗∗ −0.04 0.03 −0.05 0.01 −0.04∗ 0.09 −0.09 −0.18∗∗ −0.39∗∗ −0.08∗∗

3.76∗∗ 0.09∗∗ 0.20∗∗ 0.13∗∗ −0.01 0.00 −0.04 0.00 −0.03 0.09 −0.10 −0.16∗∗ −0.35∗∗ −0.05∗∗ 0.14∗∗ 0.19∗∗ 0.23 7547

0.02 7547

0.04 7547

0.19 7547

Note: ∼ p < 0.10; ∗ p < 0.05; ∗∗ p < 0.01.

resources into the equation does not change this result. Accordingly, Hypothesis 3 is not supported. The non-significant interaction terms in Model 5 indicate that the differences in satisfaction with work–life balance between professionals and non-professionals and full-time and part-time employees do not vary by level of state support for work–life integration. Independent of the level of state support, non-professional and part-time workers experience significantly higher levels of satisfaction with work–life balance, even when we control for job demands and resources. Figure 7.4 plots the interaction between age and high state support. The small but significant interaction coefficient for age in Model 5 indicates that the gap in satisfaction with work–life balance between younger and older employees is larger in countries with low state support. However, the interaction term becomes insignificant once individual job demands are added into the regression equation. Accordingly, Hypotheses 4a–c – which assumed that level of state support for work–life integration would affect the gap in satisfaction with work–life balance between employee categories above and beyond individual job demands and resources – are not supported by our data.


Table 7.5

131


132


5

4 3.5 3 2.5 2 1.5 1 Low state support Under 50

High state support Over 50

Figure 7.4 Interaction between age and level of state support predicting satisfaction with work–life balance

6 Discussion The present chapter examined differences in satisfaction with work– life balance between various employee categories in eight European countries. The results of the pooled model indicate that satisfaction with work–life balance is higher among non-professionals than professionals. This finding is in line with previous research in Western European countries. Using data collected in the 2004 European Social Survey, McGinnity and Calvert (2009) found that professional workers in Western European countries experience higher levels of work-tofamily conflict than non-professionals. In this study, however, the difference between them in terms of satisfaction with work–life balance was found to be quite small, even when controlling for differences in job demands and resources. Previous research has tended to focus on the work–life balance needs of higher skilled professional workers (McGinnity and Calvert, 2009). Our findings suggest that statutory and organizational work–life initiatives are equally required to support the work–life balance of non-professional workers, who are often


Satisfaction with work–life balance

4.5


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not eligible for work–family benefits offered by organizations (Lambert, 1999). Part-time workers were found to be more satisfied with their work– life balance than full-time workers. Working a reduced schedule seems to offer employees a viable way of effectively managing work and family responsibilities. However, our results also show that the gap between part-time and full-time employees is greatly reduced (B = 0.26, p < 0. 01 vs. B = 0. 14, p > 0. 01) when job demands are taken into account. A more detailed post-hoc analysis (not reported) revealed that the reduction in the unstandardized regression coefficient can be attributed mainly to heavy organizational career demands and work pressure. These findings suggest that reducing working hours will not, by itself, necessarily increase satisfaction with work–life balance. In order to improve employees’ satisfaction with their work–life balance, career demands and work pressure also need to be reduced. Such arrangements are referred to as ‘reduced-load work arrangements’ by work–family researchers (Lee et al., 2006). Above and beyond job demands and resources, older workers were consistently more satisfied with their work–life balance than younger ones. This is in line with previous studies of older workers (Villosio et al., 2008). A more detailed post-hoc analysis (not reported) revealed that the less stringent career demands experienced by older workers mainly account for these differences. The study further investigated the relationship between level of state support for work–life integration and satisfaction with work–life balance, and whether differences in satisfaction with work–life balance between employee categories are influenced by the level of state support for work–life integration. The positive, significant relationship between level of state support and satisfaction with work–life balance indicates that in countries with a wide range of statutory work–life integration policies, employees are more satisfied with their work–life balance. When individual job demands and resources are taken into account, however, the relationship becomes insignificant. The results of the study also do not support the hypothesis that there will be smaller gaps in satisfaction with work–life balance between employee categories in high support countries. The gap between younger and older workers was the only one initially found to be smaller in highly supportive countries, but again, once individual job demands and resources were taken into account, the relationship became insignificant. Our findings therefore concur with results of Chapter 6, which suggest that satisfaction with work–life balance is determined mainly by individual job demands and





resources, independent of country of residence. Unlike overall life satisfaction, which was found to vary significantly across countries, how employees assess their satisfaction with the work–life balance is influenced more by their individual work environments than by the larger country context. That means that organizational work–life balance initiatives and innovative job designs are required to improve employees’ satisfaction with work–life balance and minimize differences between employee categories. Future research might examine the impact of organizational work–life policies and job designs on satisfaction with work–life balance in different employee categories. In addition, experimental designs and longitudinal studies would allow for more precise, causal conclusions. Although the present results are in line with the assumed causal relations outlined in the hypothesis section of this chapter, rival explanations for significant relationships cannot be ruled out due to the cross-sectional design of the study.


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Competing Demands: Work and Child Well-being Linda Lane, Tanja van der Lippe, Stanimir Kabaivanov and Margareta Bäck-Wiklund

1 Introduction Changes in the world of work over the past 50 years have had important implications for family life. The single-breadwinner model has slowly given way to various forms of dual-earner models. Indeed, the majority of European children in two-parent households now live in families that practise some form of dual-earning (European Commission, 2008). Technological changes, access to global markets, the growth in services and labour market deregulation have reshaped both when people work and the way work is organized (Richter, 1994; Presser, 2003; Fagnani, 2003; Strazdins et al., 2004). These changes have had profound consequences for families and for the interaction between parents and between parents and their children. A major source of concern is the impact of dualearning on children’s well-being and quality of life. It has been argued that when both parents work, having to juggle two work schedules makes it harder for them to co-ordinate time spent with their children – an outcome that may jeopardize children’s well-being. The view that family time has declined because both parents work has persisted despite research evidence to the contrary. Trends show that parents’ time with children is relatively stable and has even increased in some countries (Gershuny, 2000; Gauthier et al., 2004; Sayer et al., 2004). One outcome of the parental time discourse is the debate about quantity time versus quality time, which emerged partially as a critique of the parental time discourse, but also in dialogue with it. By focusing on how to reconcile work and childcare in modern society, the quantity/quality time debate sought to capture the everyday reality of working parents and their concerns about child well-being. On the one hand, parents need to work to provide the material well-being that will


8

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sustain both themselves and their children. On the other hand, they need to spend time with their children to provide psychological and emotional well-being. The debate was fuelled by two highly politicized viewpoints. The quantity time viewpoint argued that the pressures of modern society are incompatible with family life. To cope with these pressures, parents need to spend more time with their children and less time working. The quality time viewpoint argued that to cope with the pressures of modern family life, parents must pay attention to how they spend time with their children. ‘In a climate, where everyday time is “going too fast” . . . it is “quality time” that represents the “islands” of time . . . that families need’ (Christensen, 2002, p. 78). The quantity/quality time debate focused on the views of parents, who were assumed to know what their children wanted or needed, and who had the authority to take decisions in their children’s best interest without asking them. Researchers interested in a child perspective argued that the debate should include children’s views on parental time and the way it ought to be used. In modern society, they argued, children are social actors with their own agendas, which need not correspond to those of their parents (James and Prout, 1997). It was suggested that the most efficient way to use family time to enhance child well-being would be to engage in activities that pay attention to quality/quantity arguments but also respect children’s views of the kind of time that is important to them (Lewis et al., 2008c). One family activity that has attracted a great deal of attention is the family meal. The ritual of family meals provides regular, consistent opportunities for family members to create and share experiences. Eating family meals together regularly contributes to and sustains a sense of family closeness, cohesion, connection, bonding and feelings of belonging (Wolin and Bennett, 1984; Jacob et al., 2008). In particular, by creating stability and predictability for family members, regular family meals seem to ease the stress of daily living and help families juggle the demands of work and home (Beutell and Greenhaus, 1983; Andersen and Leslie, 1991). Evidence for the status attributed to family meals is the fact that international studies include the number of meals children eat with their families as an indicator of child well-being (see, e.g. UNICEF, 2007). Furthermore, research has shown that eating together is an important and consistent family activity and one in which families continue to invest time and energy. Results from the Quality of Life in a Changing Europe project confirm this for the countries studied: we found that 96.5 per cent of parents reported eating a family meal at


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Per cent of family meal frequency by country 70 60

40 30 20 10 0 Sweden

UK

Netherlands Germany Portugal

1–2 times per week Figure 8.1

3–4 times per week

Hungary

Bulgaria

Always (everyday)

Family meal frequency by country

least once a week and more than 75 per cent at least three times a week. Family meal frequency by country for the Quality project is shown in Figure 8.1. Since Finland has important missings on essential variables of this chapter, it has been left out of the analyses. The benefits of the family meal for child well-being are well documented and both parents and children seem to agree on its merits (Eisenberg et al., 2004; McIntosh et al., 2005; Jacob et al., 2008). For example, Allen et al. (2008) reported that parents who eat fewer than three meals a week with their family said that they would prefer to have more frequent family meals, and Eisenberg et al. (2004) reported that in general, parents – and especially parents of adolescents – feel it is important for families to eat at least one meal together each day. These findings suggest that family meals are important and that parents want to participate in them, but that there are obstacles preventing them from doing so. Parents today are spending more time at work, and working conditions and workplace factors are likely to constitute some of the obstacles that limit working parents’ participation in family meals. When work–family scholars study the effects of work–home conflict, they tend to focus on the outcomes for organizations or employees. They are less concerned about the impact on children. The aim of this study is to include the child’s perspective by evaluating the implications


50



of workplace factors for dual-earner parents’ ability to fulfil children’s well-being requirements. Specifically, we consider whether time-based workplace factors such as working hours, commuting time and so forth compete with child well-being. What role do flexible working arrangements and supervisor/colleague support play in helping dualearner parents cope with the competing demands of work and child well-being? We define well-being as a multidimensional concept incorporating the psychological, physical and social dimensions that influence the quality of life. As a measure of child well-being, we use the family meal, a ritual that captures the multidimensionality of the well-being concept. We assess parents’ ability to enhance child well-being by examining the association between workplace factors and family meal frequency. In our study, we focus on workplace factors associated with worker ability to manage work and home responsibilities. This chapter is divided into two parts. In the first, we outline the concept of childhood and the development of a child perspective, followed by a brief review of research that has sought to include a child perspective in the parental time debate. Next, we link workplace factors to child well-being, followed by a discussion of family meals and how they might contribute to child well-being, given the constraints of parents’ work. In part two of the chapter, we examine our arguments empirically by describing a model that tests the association between workplace factors and child well-being. We examine direct relationships between these variables and child well-being as well as indirect relationships through work–home interference. The chapter concludes with the presentation and discussion of our results.

2 The concept of childhood: the development of a child perspective Researchers first became interested in studying the child perspective – that is, children’s perceptions of how parents’ work affects their quality of life – and in what children think would improve their well-being more than three decades ago, when social scientists began to study children as individuals with specific interests and experiences. Children came to be viewed as innovative and creative social actors who contribute to cultural production and change and actively participate in shaping the societies in which they live (Solberg, 1994; James and Prout, 1997). This new focus represented a paradigm shift: children were no longer regarded as mere passive objects of parental care and


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authority, but instead were acknowledged as active members of families and contributing towards change in family life. The UN Convention on the Rights of the Child (UN, 1989) recognized children’s individual human right to be heard and express themselves freely in matters concerning themselves. This document made it the responsibility of both families and government to safeguard children’s rights. As Qvortrup et al. (1994) have argued, however, children’s lack of power and status means that their views and knowledge are seldom considered, and decisions concerning them are therefore most likely to be made in their absence and without their consent. The most extensive study of the child’s perspective on parents’ work is Galinsky’s (1999) national survey of 1023 American children. The study revealed that spending more time with parents was not at the top of children’s wish list; indeed, only 10 per cent wanted to spend more time with their mother and 15.5 per cent with their father. In Europe, Klammer’s studies of German children found that, in general, children did not question the fact that their parents worked or the work and childcare arrangements affecting them. Children were, however, critical of parents working weekends and evenings. The results also showed that German children were often satisfied with quantity time, defined as ‘a carer’s background presence’ (Klammer, 2006). On the other hand, evidence suggests that simple parental presence or absence is not the main issue for adolescents (Crouter et al., 2004; Lewis et al., 2008c). In a smaller study, Polatnick (2002) questioned whether surveys could adequately capture the complex and contradictory feelings that children have about parent time. In line with Christoffersen (1998), she argued that even young children were able to internalize complex notions of work and comprehend, from an early age, the complexity of the tradeoffs that their parents made between them and their employers. As a result, children try to find strategies to cope with situations that they have no power to change. In the relationship between working parents and children, the parents’ working life structures the everyday lives of children. Although parents may take the impact of their work on children’s well-being into account, children must ultimately cope with parents’ decisions (Qvortrup et al., 1994; Näsman, 1995; Bäck-Wiklund, 2001). The ability of parents to increase their presence in children’s lives is conditional not only on their being able to find time from work but, also on children being available to participate in well-being activities. In modern societies, children are agents with their own set of time


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constraints. Children’s education and leisure activities impose limits on the amount of time they are available for their parents. Research shows that children’s views may differ considerably from those of their parents and that parents may make incorrect assumptions about what their children think or feel (Galinsky, 1999; Boutelle et al., 2001; Lewis et al., 2008c). For example, a number of American surveys show that although about 60 per cent of working parents say they want to spend more time with their children (Polatnick, 2002), spending more time with parents was not a priority for children (Galinsky, 1999). These findings suggest that neither the quality nor the quantity approach adequately explains the meaning of family time for children. Christensen (2002) has proposed a new approach that recognizes that quality and quantity have a much broader meaning for children than for adults. Attempts by parents to spend more time or quality time with them will not solve their everyday problems; instead, the quality/ quantity time approach should be replaced by one that pays more attention to the various ways children identify time that matters to them (Galinsky, 1999; Christensen, 2002).

2.1 Linking parents’ work demands to children’s well-being The relationship between parent and child is of fundamental importance in modern society. The underlying premise is that parents must provide for the material and psychological well-being of their children. Time spent in employment gives most parents the economic means to provide for their children’s material needs. Time spent with parents is a central feature of children’s lives, and physical presence is a prerequisite for capturing some of the dimensions associated with children’s well-being. Spending more time at work means spending less time with children. Parents must solve the problem of how to maximize their children’s well-being while also satisfying their children’s material needs. The length of the working day, work schedules and commuting distances all influence the amount of time parents have to spend with their children. For example, the strain of working long hours may have both a direct and an indirect effect. It may affect the mental health of parents and the way they interact with each other and with their children. In turn, these factors may affect children’s well-being indirectly (Jacob et al., 2008). By focusing only on the number of hours worked, however, we may miss some of the complexities that parents face in our post-modern, 24/7 economy. Job demands represent another type of


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constraint. Non-standard employment contracts are gradually replacing the standard 40-hour working week. These new arrangements include part-time work, fixed-term contracts and agency work (see Chapter 3). Contracts are often combined with irregular and unpredictable work schedules that require employees to be flexible and to work shifts, including weekends and holidays, a factor that may contribute to work interfering with family life (Strazdins et al., 2006). In addition, parents who have long commutes leave home early and return late, reducing the amount of time available for their children. Thus, the time parents spend at work – working on standard or non-standard contracts, overtime and commuting – limits child/parent time, reduces the time parents can engage in well-being activities and may reduce the frequency of family meals. Some organizations offer a number of flexible working arrangements to help employees balance working and home life. Two of these are flexitime, meaning variable starting and finishing times within agreed limits, and flexi-place, meaning practices that allow employees to work from home. Flexible working arrangements have been associated with less work–home interference. Dual-earner parents who can take advantage of flexible working arrangements are able to co-ordinate their time with children’s schedules, giving them more opportunity to engage in child well-being activities. We therefore expect flexible working arrangements to be associated with greater family meal frequency. In addition, organizations can help employees cope with work–home interference by supporting them in both their work and family roles. Results suggest that employee perceptions of co-worker and supervisor support can reduce the stress of multiple roles and have a positive impact on employee well-being. When employees perceive that they have the support of their colleagues and supervisors, they are less likely to fear sanctions or career setbacks if they occasionally leave the workplace to participate in family activities (Allen et al., 2008). Supervisors and colleagues can also set a good example by actively backing efforts encouraging parents to adopt strategies that support the work–family balance. When work interferes so much with non-work activities that employees feel they cannot properly fulfil the roles expected of them, they experience work–family conflict. Work–family conflict is bidirectional: on the one hand, there is work–home interference (WHI) and on the other, home–work interference (HWI). Work–home interference (WHI) occurs when the demands of work interfere with the demands of home


Linda Lane et al.



life (Parasuraman and Greenhaus, 2002). The present study focuses on WHI because research suggests that although the variables that give rise to interference originate at work, the outcomes of interference are located in the home. WHI is a mediating variable that links factors associated with one role with outcomes associated with the other role (Voydanoff, 2004). Work–home interference has been found to be associated with workplace factors included in this study, and we therefore expect that WHI will mediate relationships between workplace factors and family meal frequency. Although the workplace factors cited above may influence the amount of time parents have available for their children, the influence of parental employment on child well-being may vary due to a number of other work-related factors, such as physically demanding work, stress and poor work environment. Consequently, for most parents workplace factors represent a combination of conditions that influence both the quantity and quality of parental time. Other factors such as childcare duties and housework also add to the demands on dual-earner parents. The gender division of labour may mean that some of these demands affect women and men differently. For example, all family members may enjoy eating a meal, but meal planning, preparation, cooking and washing-up are traditionally female tasks (Harnack et al., 1998).

3 Data and methods The object of this study is to examine the associations between child well-being, workplace factors and WHI. We investigate the behaviour of a sample of dual-earner parents from seven European countries who participated in the Quality of Life in a Changing Europe survey in 2007 (see Chapter 4). Child well-being is measured by family meal frequency. We measured family meal frequency using a single item taken from the Quality survey: ‘During a typical week, how often do you eat a meal with all your household members?’ The responses ranged from one (‘less than once a week’) to four (‘always (every day)’). We focused on workplace factors that have been shown to influence how employees manage the competing demands of work and non-work activities. The variables studied include working hours, commuting time, overtime and shift work. We used two measures of organizational commitment to helping employees manage work and family, namely the provision of flexible working arrangements and supervisor/colleague support. Access to


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flexitime and flexi-place were each measured by a single item (‘Are you free to decide when you do your work?’ and ‘Are you free to decide to work wherever is best for you – either at home or at work?’). The responses were assessed on a four-point scale ranging from ‘never’ to ‘always’. Higher scores indicated more flexibility. Supervisor/colleague support was measured using a six-item scale that included the questions ‘My direct superior supports employees who want to switch to less demanding jobs for private reasons’ and ‘My colleagues support employees who want to switch to less demanding jobs for private reasons’. Responses ranged from strongly agree to strongly disagree. Coefficient α = 0.80. To assess WHI, we used a three-item scale developed by Geurts et al. (2005) that included the question ‘How often do you . . . not have the energy to engage in leisure activities with your spouse/family/friends because of your job?’ Responses were based on a four-point scale ranging from ‘never’ to ‘always’. Coefficient α = 0.75. Age, gender, education and number of children in the household were included as control variables because they have been shown to influence work–family outcomes. Research suggests that culture and tradition play significant roles in determining the importance of family meals, how they are organized and the amount of energy and time parents in each country are prepared to spend on them (see, e.g. Lupton 1994; Fiese, 2002; Mestdag and Vandeweyer, 2005). We therefore include country of origin as a list of dummy variables, with Hungary as the reference category. The study included all married/cohabiting employees with an employed partner and with children living in their households in Sweden, the UK, Germany, the Netherlands, Portugal, Hungary and Bulgaria. The respondents were employed in four service sectors (hospital, retail, IT/telecom, and banking and insurance). The sample was N = 2432 with 90 missing values, leaving a valid sample of 2342 respondents (see Chapter 4 for more details). We used OLS regression analysis to explore the relationship between the dependent variable and workplace factors. In the first step, family meal frequency was regressed on country dummies. In step 2, we entered the control variables. All independent variables (with the exception of WHI) were entered as a single block in step 3. To evaluate the mediating affects of WHI, we entered that variable in the final step. We also performed multinomial regression analysis using family meal frequency categories as the dependent variables; as the results remained the same, however, we present only the OLS results.


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The means, standard deviations and correlations among the study variables are presented in Table 8.1. Family meal frequency was negatively and significantly related to WHI (r = 100, ρ < 0. 01) and had a positive significant correspondence with shift work (r = 0. 082, ρ < 0. 01), flexitime (r = 0. 048, ρ < 0. 05), flexiplace (r = 0. 53, ρ < 0. 05) and supervisor/colleague support (r = 0. 64, ρ < 0. 01). Frequency of family meals was not significantly related to working hours, overtime or commuting time. We also found that WHI was significantly related to all other variables, with the exception of flexi-place. Although not reported in the table, more than 50 per cent of men and women report eating a family meal every day, and 75 per cent eat a family meal regularly. Regarding our first research question, we were interested in understanding the influence of work-related factors on child well-being, measured as frequency of family meals (see Table 8.2). After controlling for gender, age, education, number of children and country, we found that overtime (β = −0. 052, ρ < 0. 01), shift work (β = −0. 045, ρ < 0. 01) and commuting time (β = −0. 043, ρ < 0. 05) had significant effects on the frequency of family meals. All these work-related factors have a negative effect on family meal frequency. The regression results indicated no relationship between working hours and family meal frequency. In evaluating the effect of the two flexibility arrangements, we found a significant relationship between frequency of family meals and flexitime (r = 0. 048, ρ < 0. 05) and flexi-place (r = 0. 053, ρ < 0. 05), but the regression results indicate that neither flexitime nor flexi-place was significantly related to family meal frequency (β = 0. 003 ns and β = −0. 045 ns respectively). The regression results also indicated that supervisor/colleague support was associated with more frequent family meals (β = 0. 084, ρ < 0. 01). Our results show that more WHI is related to fewer family meals (r = −0. 100, ρ < 0. 01). However, we were also interested in exploring whether WHI mediates workplace factors. The regression equations indicated significant relationships between WHI and family meal frequency for women (β = −0. 176, ρ < 0. 01). There is evidence of at least partial mediation. When we entered WHI into the equation, overtime and commuting time were no longer significant. However, the strength of the significant negative relationship between meal frequency and shift work and the significant positive relationship between meal frequency and supervisor/colleague support remained constant.


3.1 Results


1. 2. 3. 4. 5. 6. 7. 8. 9. ∗ρ

Correlation matrix

Family meal WHI Working hours Shift work Overtime Commuting time Flexitime Flexi-place Support

M

SD

1

2

3

4

5

6

7

8

3.30 2.03 39.46 1.71 2.03 1.21 2.23 1.42 3.25

0.84 0.61 10.89 1.27 0.85 0.85 0.87 0.72 0.77

– −0.100∗∗ 0.001 0.082∗∗ −0.032 −0.035 .048∗ 0.053∗ 0.064∗∗

– −0.309∗∗ 0.046∗ −0.327∗∗ −0.049∗ −0.043∗ 0.028 −0.203∗∗

– −0.089∗∗ −0.361∗∗ 0.073∗∗ 0.208∗∗ 0.189∗∗ −0.168∗∗

– −0.021 −0.088∗∗ −0.230∗∗ −0.172∗∗ −0.052∗

– −0.001 0.045∗ 0.084∗∗ −0.129∗∗

– 0.017 −0.036 −0.053∗∗

– 0.391∗∗ 0.103∗∗

– 0.123∗∗

< 0.05; ∗∗ ρ < 0.01.

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Table 8.1

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Table 8.2

Regression results Family meal frequency SE B

β

0.075 0.077 0.067 0.068 0.062 0.074

−0.024 −0.174∗∗ −0.091∗∗ −0.106∗∗ −0.071∗ 0.043

0.018 0.041 −0.003 0.005 (0.004)

0.037 0.014 0.002 0.018

0.018 0.069∗∗ −0.024 0.009

Working hours Overtime Shift work Commuting time Flexitime Flexi-place Supervisor/colleague support Step 3 R2

−0.004 −0.055 −0.045 −0.042 0.002 0.035 0.070 (0.02)

0.002 0.022 0.015 0.021 0.023 0.027 0.024

−0.030 −0.026 −0.064∗∗ −0.038 −0.005 0.033 0.050∗

WHI Step 4 R2 Total R2

−0.167 (0.01) (0.06)

0.031

−0.121∗∗

B

Sweden The UK The Netherlands Germany Portugal Bulgaria Hungary (reference category) Step 1 R2

0.066 −0.492 −0.096 −0.200 −0.090 0.093 (0.03)

Control variables Gender Education Age Number of children Step 2 R2 Work-related factors

βs are standardized regression weights for the final equation. ∗ ρ < 0.05; ∗∗ ρ < 0.01.

4 Discussion and conclusions The purpose of this study was to evaluate the relationship between child well-being, measured as the frequency of family meals, and workplace factors. We were also interested in whether WHI mediated the relationship between workplace factors and the dependent variable. We found that although men and women differed by country, employment sector and working conditions, more than 75 per cent of the dual-earner


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parents in this study eat a family meal regularly and 50 per cent manage to eat a family meal every day. We did not specify whether the family meal was breakfast, lunch or dinner; nevertheless, our result compares favourably with other research on family meals. Mestdag and Vandeweyer (2005) found that about 60 per cent of Belgian parents managed one family meal on working days, and about 80 per cent on weekends. Studies of American children and adolescents found that about 30 per cent eat dinner with their family every day (Jacob et al., 2008). Although we did not discuss how family members interact with regard to meal planning, preparation and eating, food choice or mealtime traditions and practices, our results suggest that dual-earner parents identify family meals as important for child well-being. Our result is consistent with previous studies showing cross-country consensus with respect to parents’ attaching great value to family meals (Mestdag and Vandeweyer, 2005; Jacob et al., 2008). If this conclusion is correct, then it is important to understand why some employees are unable to achieve this goal. The results of our study provide evidence that workplace factors are associated with family meal frequency. First, we found that working overtime, shift work and long commutes all lower the frequency of family meals. Only overtime and commuting were related to family meal frequency through WHI, however, suggesting that, although shift work affects family meal frequency, it may do so in ways not directly related to WHI. Some parents perform shift work or other forms of non-standard work by choice (Riley and Glass, 2002). They see working outside the nine-to-five workday norm as potentially family-friendly because it allows them to spend more time with their children. They may therefore not perceive their work as contributing to WHI. Children, however, may not see this solution as being in their best interest or as corresponding with their desires (Galinsky, 1999; Christensen, 2002). As our results show, shift work is associated with fewer family meals and by extension contributes to lower child well-being. The way work schedules are organized and under what conditions will therefore influence outcomes for parents and children. The availability of flexitime and flexi-place working arrangements was not significantly related to family meal frequency. Although not elaborated on in this chapter, we suggest that the lack of association may be related to our sample. Women were overrepresented in the sample, and since they worked fewer hours than men, they were also less likely to use flexitime and flexi-place arrangements (Chapter 9, Table 9.2). Furthermore, although many organizations offer flexible


Linda Lane et al.



working arrangements, they may not be available to all categories of workers (Gottlieb et al., 1998). The results of our analysis indicate that supervisor/colleague support is strongly associated with frequency of family meals even when mediated by WHI. The suggestion is that support by supervisors and colleagues may be instrumental in reducing some of the negative effects of workplace factors on work and family outcomes. By helping employees avoid WHI, supervisor/colleague support facilitates child well-being. Before children were acknowledged as individual actors in families, the assumption was that parents knew what was best for their children and had legitimate authority to act on their behalf. Their hegemony over children was used to underpin arguments favouring either the quantity or quality time approach. One of the key elements in this debate was parents’ frustration at the competing demands of work and child well-being. Studies that include a child perspective advocate moving away from the quantity versus quality time debate. They claim that it is important to recognize the kinds or ‘qualities’ of time that children find important (Galinsky, 1999; Christensen, 2002; Lewis et al., 2008c). From a child perspective, our findings suggest that both the way we work and the amount of time we spend at work affect child well-being, but in different ways. Although both parents and children value family meals, workplace factors in fact make it difficult for dual-earner parents to organize as many as they would like. Parents find it very difficult to balance work, family and children’s activities. Our findings suggest that employers can help employees eat more meals with their families by providing an assortment of flexible working arrangements and by encouraging supervisor/colleague support. The more employers enable employees to participate in child well-being activities such as family meals, the less WHI employees will experience and the more satisfaction they will feel with their work.


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Gender Differences in Quality of Life Eva Fodor, Linda Lane, Joop Schippers and Tanja van der Lippe

1 Introduction Despite decades of policy promoting emancipation, gender differences still constitute a major social problem in Europe. In terms of social inequality and quality of life, women run a higher risk than men of being among the disadvantaged groups (Padavic and Reskin, 2002; EC, 2008). Comparable data from the UNECE’s Gender Statistics Database show that women in each of the eight countries in this research project have a smaller chance of being economically active and economically independent than men; they are also at a higher risk of unemployment, make less money when they do have jobs, are more often among the ‘working poor’ and have less institutional power than men in the workplace. Single mothers run a particularly high risk of poverty (Ypei, 2009). Moreover, due in part to persistent financial hardship, they also run a higher risk of depression (Brown and Moran, 1997), a dramatic expression of a lack of quality of life. Nowadays, it is quite common to analyse both objective and subjective indicators of the quality of work and to do so within the larger context of the quality of life (e.g. Gambles et al., 2006). Although women might lag behind men in terms of their objective labour market situation, that may not be the case when considering their subjective feelings about the quality of work and the broader context of the quality of life. With respect to quality of work, work engagement appears to be closest to what men and women perceive as a good quality of work (Bryce and Haworth, 2001). Chapter 2 addressed the importance of work engagement. The theoretical framework presented there, which represents a guideline for the empirical chapters, will form the basis of this chapter as well. Here, however, we also add the life course perspective,


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arguing that the role of work is different over the life course of men and women, with important implications for their quality of life. For instance, research based on the concept of social production functions has shown that during the stage of life when men start building their careers, women take a different route towards social approval: raising a family and being a good mother (Sanders et al., 1991). Whereas men seeking social approval are forced to put all their eggs into one basket (their career), women can – if they want to or if they are less successful in the labour market – also opt for ‘dedicated motherhood’ for fulfilment and social recognition. The same is true during the later stages of the life course, when it is considered quite natural for women to participate in voluntary work and care for the elderly, while men primarily have to provide the household’s income and future pension savings. As in the empirical chapters, we make use of data collected on employees working in 32 service sector organizations in eight European countries. We start by describing the objective labour market situation of these employees and how they, both men and women, feel about the quality of work and life in the eight countries under study. We then consider the role of the life course in describing and explaining men’s and women’s quality of work and life. Because their differing labour market situations and roles in unpaid, voluntary and care work evidently affect the quality of life of women and men differently during the various stages of the life course, we also present data on unpaid working hours.

2 Working hours and work arrangements Various researchers have attempted to explain why women have a less profitable labour market position than men. Their explanations include: the force of patriarchy (Reskin, 1988); differences in human capital (Becker, 1991); household responsibilities and domestic decisionmaking (Hochschild, 1989); and institutional and individual discrimination built into the conceptualization of the ideal worker in a global capitalist environment (Acker, 1990). They have devoted considerable attention to policies designed to strengthen women’s labour market and income position, both at the national (Sainsbury, 1994) and the supranational level (Mósesdóttir et al., 2006), for example anti-discrimination legislation intended to improve women’s education and offering facilities to help parents (mostly women) reconcile work and family life (Den Dulk, 2001). While companies have started to offer employees options that make raising a family more compatible with making a living, researchers have argued that this may push women into marginal


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positions in the labour market. Employers may consider that women – who in their perception represent additional costs because they require so many special facilities and arrangements – are more expensive than men, who ‘just do their job’. Consequently, employers may decide not to hire women at all, or to hire women at lower wages only. Economists label this phenomenon ‘risk selection’ or ‘statistical discrimination’ (Phelps, 1972). In addition, women’s growing participation in the labour market may exacerbate global inequalities among women: middle-class women working in core countries are now able to hire domestic workers from peripheral countries and produce a female army of underpaid, vulnerable, and occasionally, even illegal labourers (Lan, 2006). In the same vein, Hochschild (1997) calls attention to the problem of the ‘Time Bind’: an increase in the amount of time spent at work and a decrease in the amount of time devoted to family and communityrelated activities. However, even though we have seen a spectacular rise in women’s labour market participation rates in recent decades, we have not witnessed a similar increase in men’s participation in unpaid labour. In other words, women are copying men’s behaviour in paid labour or – more broadly – in the public domain, but they are also facing the less agreeable consequences of this behaviour, such as work-related and stress-related diseases and time wasted in traffic jams. On top of that, they still take or are forced to take primary responsibility for childcare and household chores. As a consequence, many women carry a double burden nowadays. What they have gained by accessing the world of paid labour has not been matched by a reduction in unpaid work and care. Table 9.1 shows the basic distribution of men and women across the economic sectors covered in this project. We see the highest proportion of women in retail and the lowest in IT/telecommunications. The percentages, however, vary depending on what segment of the working population actually participated in the different countries and sectors (e.g. whether doctors or nurses were more likely to fill out the survey in the hospitals we visited). As our surveys were not strictly representative in statistical terms, we must be circumspect in interpreting their outcomes. A number of factors influence how work impacts on the overall quality of life, but for most people, working hours and how they are distributed are certainly a key issue (Crompton, 2006; Scott et al., 2008). The ability to regulate one’s working hours may be one way of achieving a comfortable balance between work and non-work responsibilities. In this section, we therefore explore gender differences in the length of time people work, both in the paid labour market and at home, as well


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Table 9.1

Percentage of women in each country and in each company

Bulgaria Finland Germany Hungary The Netherlands Portugal Sweden The UK

69% 91% 98% 54% 93% 51% 77% 57%

68% 69% 38% 32% 36% 49% 27% 62%

83% 89% 79% 83% 83% 55% 82% 46%

82% 83% 54% 51% 42% 71% 77% 71%

579 710 721 418 691 735 410 460

767 906 1201 860 1012 1363 650 780

as other time-related conditions of work. The exact wording of the questions used to construct the variables in the tables is given in Chapter 4. Table 9.2 shows cross-country differences in the amount of time employees in the 32 organizations devote to paid work. Men and women who live in less developed economies such as Bulgaria and Hungary (as well as Portugal, as the third least developed) work longer hours, and the gender gap is much smaller here than in most of the other countries. While women work one to two hours less than men in Bulgaria, Hungary and

Table 9.2

Means and percentages to describe working hours Hours Commuting Unpaid % working worked time (mins) work overtime (hrs)

Bulgaria

Women Men Finland Women Men Germany Women Men Hungary Women Men The Women Netherlands Men Portugal Women Men Sweden Women Men The UK Women Men

44 45 n/a n/a 34 42 45 46 29 40 44 46 36 41 35 41

34 31 26 24 28 38 47 40 34 43 37 35 32 28 32 35

15.1 7.3 8.1 5.7 13.6 7.5 14.2 7.4 12.4 6.9 13.4 6.8 11.9 8.4 15.3 8.6

32 27 8 12 16 13 32 33 6 19 32 40 11 30 19 25

% using % using flexitime flexiplace 33 35 29 39 33 67 30 39 26 49 35 49 59 71 42 36

5 10 6 10 5 17 9 18 9 28 8 17 10 41 15 18


Retail IT/telecom Hospital Bank/ Total Total N insurance women


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Portugal, the gender gap ranges from five to 11 hours in the other countries. This is due to the almost complete absence of part-time work for women in Hungary and Bulgaria. Women are less likely to work part time in Portugal as well, compared with the EU 25 average (EC, 2007). Not surprisingly, women and men in the three least developed countries are more likely to work overtime at short notice. In addition, women in these three countries have a longer commute than in most other more developed countries (although so do men). All these factors add up not only to longer working hours, but also to a work environment that is more burdensome for women (and for men, to almost the same degree) in the less developed regions of the European Union. Our initial finding, then, is that women in the new European Union member states spend significantly more time in paid work than their counterparts in the older European Union member states, and that the gender gap in paid working hours is smaller. On the one hand, this may mean that women in Bulgaria, Hungary and Portugal have a higher level of economic independence than women in the other five countries. On the other hand, of course, the longer hours that women in the less developed economies work may mean that they need to contribute (substantially) to the household income. Some would consider women’s lack of freedom to work part time or to stay at home and care for their children as a serious form of deprivation. These different interpretations key into a long-running policy debate concerning the trade-off between economic independence and the freedom to choose not to participate in the labour market. No matter how we interpret the data, women in peripheral economies, therefore, have a different work–life balance than their counterparts in the other countries. Table 9.2 shows that women in all eight countries do significantly more household work than men. Cross-country differences are also notable: women in the countries where paid working hours are longer tend to do more, rather than fewer, hours of domestic work. As a consequence, women in less developed countries spend more hours in total on paid and unpaid work than women in the more developed countries of north-west Europe. In line with economic theory, the latter women have transformed part of their greater wealth into additional leisure time. For example, women in Bulgaria spend 59 hours on average doing paid and unpaid work (men: 52 hours), while women in the Netherlands spend 41 hours (men: 47 hours). There is considerable cross-country variation in the use of flexible working arrangements (flexible hours and teleworking). In each country, however (with the exception of the UK), men are more likely than


Eva Fodor et al.



women to report having had access to flexible working arrangements in the weeks prior to our survey; they are more likely to work in positions that allow them to work flexible hours and to work from home, typically upper-level professional jobs. In other cases, flexible hours are not necessarily beneficial to workers. If working-time flexibility takes the form of stand-by or on-call work, it may be detrimental to anyone who wants to combine work and family life, especially since caring for young children requires parents (or any other carer) to be available at fixed times.

3 Subjective feelings about working conditions Although their working conditions are clearly inferior, women are just as likely as or – occasionally – even more likely than men to enjoy their work. Schaufeli et al. (2002) introduced the concept of engagement, a positive emotional and motivational state of mind characterized by vigour, dedication and absorption. For them, vigour refers to working energetically and being willing to work hard even in difficult situations. Dedication, in turn, is linked to the experience of meaningful work. Being dedicated to one’s work means being proud of the work one is doing and feeling inspired by the content of that work. Absorption, on the other hand, means being immersed in one’s work and deriving pleasure from it (Hakanen, 2004, p. 229). In addition to work engagement, Table 9.3 describes three other indicators of subjective feelings towards work and life: perceived pressure at work, work–family balance and satisfaction with life. These variables are explained in Chapter 4. Workers in Bulgaria feel the most pressure at work, followed by those in Finland, Sweden and the UK. The difference between genders is small in this regard, with the exception of Germany, where women claim to feel more pressure in paid work than men do. Dutch workers, men and women alike, take the most pleasure in their work, ‘engagement’ as we called it, followed by Portuguese workers. In many countries there is a gender difference here: women are more likely to experience ‘work engagement’ than men. For example, in the UK the value of this indicator for women is 4.33 while it is 4.15 for men (on a scale from 1 to 7, with an overall mean of 4.8 and standard deviation of 1.2). The gender differences are small, which is remarkable since women appear to be at a disadvantage in a number of other areas (e.g. they lack autonomy and authority and are less likely to be able to use flexible schedules). Yet they appear to derive more pleasure from work than men. There is little gender difference in the support


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Eva Fodor et al. Quality of work and quality of life

Bulgaria Finland Germany Hungary The Netherlands Portugal Sweden The UK All

Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men Women Men

Work pressure

Work engagement

Work– family balance

Life satisfaction

2.8 2.75 2.65 2.59 2.42 2.22 2.48 2.48 2.25 2.34 2.59 2.57 2.6 2.62 2.67 2.61 2.56 2.51

4.82 4.64 4.83 4.53 4.73 4.77 4.99 4.99 5.33 5.21 5.13 5.15 5.07 4.92 4.33 4.15 4.91 4.83

3.3 3.4 3.4 3.4 3.4 3.3 3.2 3.3 3.6 3.6 3.1 3.2 3.5 3.5 3.2 3.2 3.3 3.3

4.3 4.2 4.8 4.7 4.8 4.6 4.1 4.2 5.0 4.8 4.4 4.4 5.0 5.0 4.2 3.9 4.5 4.4

men and women receive from their supervisors and their peers. Men, however, perceive their career as more demanding than women (these variables are not presented here in detail). They are more likely to say that they are required to work overtime and work hard, to be available at all times and to prioritize work over their home lives in order to get ahead. This could be interpreted as a lack of support. Women and men may receive different types of support, or be supported on different issues, and still experience the same or a similar level of overall support, however. Women are just as likely as men to believe that they have found the right balance between work and family obligations. This is surprising, since women are obviously doing more household work and have less leisure time overall than men. Yet this does not seem unacceptable or objectionable to the women in our sample. Similarly, women in each of the countries surveyed seem, on the whole, to be slightly happier with their lives than men (although not by much), with little variation between countries. In summary, we see some systematic cross-country patterns in the subjective evaluation of the quality of work: men and women in peripheral


Table 9.3

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countries are more likely to feel pressured and experience their work as a burden and a negative influence on their family lives. This is in line with our previous argument concerning patterns of labour force attachment in these countries: those who work must do so for longer hours and under more stressful conditions. In terms of gender differences, our main finding is that they are small overall. We should note, however, that our surveys were conducted well before the financial and economic crisis that hit most European countries in 2008–09. It is quite possible that many of the respondents are now out of work, although it appears that women have been hit less hard than men so far, as men are more concentrated in sectors and industries – such construction, automotive and banking – where jobs have disappeared at a much faster rate than in ‘female’ sectors such as care or education.

4 The role of the life course in understanding gender differences In attempting to understand the role gender plays in the quality of life, we argue that it is important to consider men’s and women’s life stage and family status. It could well be that small differences between men and women in perceived quality of work and life will change if we control for their life stage. There are major differences between male and female life courses. While the male life course has been dominated by paid work and the need to provide his family with a proper income, care-giving has been the theme of the female life course. Female life courses have become more diverse in recent decades (while male life course patterns have scarcely changed) as more women entered the labour market. Yet the role of paid work in the life course of many women in Europe is still quite different from that of men. While men usually arrange their lives around their work, many women still arrange their work around their unpaid care tasks – and indeed are obliged to do so. While leaving aside whether this is women’s ‘own choice’, that is, a choice they would have made even if they had not been bound by any restrictions, or the result of a lack of opportunity to make a paid career their priority, we cannot ignore the possibility that some of our results might relate to life course issues. One hypothesis concerns the differing impact a partner has for men and women. A young single woman is expected to want a career, and we presume this must have a big impact on her quality of work. A partnered woman has more household duties, is likely to spend less time on her career (Van der Lippe et al., forthcoming), and


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therefore depends less on the quality of her work. We expect to see less of a difference between single or partnered males in this respect. Another hypothesis is that the quality of a man’s work, in terms of work engagement, increases when he starts a family (more responsibility and the desire to show he is a proper breadwinner). A young mother, however, may show less work engagement during the same life stage because she will make her ‘new career’ of dedicated motherhood her priority. At the same time, men and women may also report differences in the quality of life, especially since they ‘produce’ that quality via different channels in this stage of the life course. Women may depend less on work engagement than men to achieve a good quality of life, but also find themselves more dependent on having a family life. For the purpose of analysis, we distinguish the following stages of the life course (also noting that individuals do not necessarily pass through all these stages, or pass through them in the same sequence; see Liefbroer and Dykstra, 2000): 1) young, single people without children; 2) young couples without children; 3) couples (

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