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EDITORIAL 331 Editorial ‘C ontinuous and Discontinuous Innovation: overcoming the innovators dilemma’ is the theme o...

Author: Petra de Weerd-Nederhof and Olaf Fisscher (Editors)

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EDITORIAL

331

Editorial

‘C

ontinuous and Discontinuous Innovation: overcoming the innovators dilemma’ is the theme of this issues’ special guest-edited section of, in total, six contributions. This includes an editorial introduction on the theme authored by the guest editors Mariano Corso (Politecnico di Milano) and Luisa Pellegrini (University of Pisa). The guest editors brought together five relevant papers working on research and discussion from the 7th CINet Conference held in Lucca (Italy) in 2006. The special aims at contributing to theory and practice on the two complex balancing acts of continuous and discontinuous innovation, that today represent a hot topic in innovation management. Please turn to their article which commences this issue, for a more detailed introduction of the five articles. Creativity and Innovation Management is affiliated with CINet and will continue to publish selected papers from their conferences in the future. The next CINet conference will be held in Valencia, Spain, focusing on radical challenges in innovation management (7–9 September 2008, see http:// www.continuous-innovation.net). This fourth and final issue of 2007 is quite a well filled one, with another (mini)special on Innovation Roles. These three articles are based on original presentations at the 2006 TIM Tagung in Vienna (Gemünden et al.), and the International Product Development Management Conference organized by EIASM, in 2006 in Milan (Sim et al. and Anderson & Berggren). All three articles address innovation roles issues from their own specific viewpoint. To start with Hans Georg Gemünden, Sören Salomo and Katharina Hölzle address role models for radical innovations in times of open innovation, reporting on their study of the influence of innovator roles in highly innovative ventures. Edward Sim, Abbie Griffin, Raymond Price and Bruce Vojak explore differences between inventors, champions, implementers and innovators in developing new products in large, mature firms. The summary conclusion is that different management strategies need to be developed to allow each of these specialist types to function in top form and subsequently be appropriately rewarded. It is unlikely that someone who is adept at managing inventors will be adept at managing champions, or that a good manager of implementers could also © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

manage innovators. And yet, as Sim et al. stress in their contribution, inventors, champions, innovators and implementers need to interact effectively in order for a technology to proceed from capability to successful product in the marketplace. Knowing how to get all these specialist types to work together is important to the firm! Closing the minispecial, Hans Andersen and Christian Berggren focus on individual inventors who, as they say in their introduction, often figure prominently as examples, role models or myths in the histories of technologybased companies. Whether individual inventors are still important in the rationalized R&D operations of modern, internationally competing firms is one of the questions they address in their article. This question is answered affirmatively and, moreover, the authors also shed light on how managers can leverage these inventors, as well as how to maintain and nourish the fragile inventive space in increasingly lean R&D organizations. Last but not least, Diana Grosse’s paper on project leadership in R&D was already announced in the September issue editorial as being complementary to the Leadership special we published in that issue. It has already been available on Online Early since September, and we indeed encourage you to check this feature on our Blackwell webpages regularly for the latest articles in digital form. The issue of Creative Leadership will be a topic for our 2nd Creativity and Innovation Management Community meeting to be held in Buffalo, 28–30 May 2008, combining among others the European perspective of our own founding editors Tudor Rickards and Susan Moger, with Gerard Puccio’s (the host in Buffalo) own views. A preliminary programme for that event will also be published on our website (in December 2007) and we hope to meet many of you there! The issue concludes with two book reviews which we hope will lead you to read the books discussed in full. Antoni Brack reviews Intellectual Property Law and Innovation by W. van Caenegem, and Bram Snitslaar highlights the main issues from Utterback et al.’s Design Inspired Innovation. We hope you enjoy your last CIM issue for this year, which has been a fruitful year for the Journal. We look forward to our 17th volume

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in 2008, which will start in March with a small selection of papers based on presentations from the 2006 R&D Management on Creativity and R&D held in Taiwan, brought together by our guest editors and members of editorial board Ming Huei Chen and Geir Kaufmann. Also, 2008 will bring new PDMA (Boston), CINet and EIASM (Hamburg) conferences, and perhaps already some publication of papers from the tenth European Conference on Creativity and Innovation (ECCI X, held in Copenhagen in October 2008). Also, there is the possibility to submit for a new special on TRIZ: Theory of Inventive Problem SolvingImpact for Creativity and Innovation Management. Please see the call for papers initiated by Carsten Gundlach and Martin Moehrle on our website and remember to submit via Manuscript Central mentioning TRIZ, as well as e-mailing your paper to gundlach@ kassel.ihk.de. The deadline is 15 March! Next year will also be the year of the second Tudor Rickards Best Paper Award, to be handed out if all goes well in Buffalo. Please send your nominations from among the four issues of our 16th volume to the editors at [email protected].

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Last but not least your editorial team will be strengthened by a third editor-in-chief, our former special issues advisor and colleague at the University of Twente, Klaasjan Visscher. In the March issue he will introduce himself a bit further. We will end this editorial by acknowledging the invaluable help of our ‘behind the scenes’ CIM team at Wiley-Blackwells in Oxford. A special thank you goes to our Journal Content editor David Thresher, accurate and always flexible! Thank you all for another year of stimulating cooperation. In Twente, our own editorial assistant Jeannette Visser-Groeneveld has been invaluable in many ways, and in particular in her skill to manage Manuscript Central. We wish all members of the CIM community a very merry Christmas and a happy New Year, and look forward to being in touch with you again in 2008! October 2007 Petra de Weerd-Nederhof Olaf Fisscher

© 2007 The Authors Journal compilation © 2007 Blackwell Publishing

CONTINUOUS AND DISCONTINUOUS INNOVATION

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Continuous and Discontinuous Innovation: Overcoming the Innovator Dilemma Mariano Corso and Luisa Pellegrini Challenged by competition pressures and unprecedented pace of change, firms can no longer choose whether to concentrate on the needs of today’s customers or on the anticipation of those of tomorrow: they must be excellent in both. This requires managing two related balancing acts: on the one side, being excellent in both exploitation and exploration of their capabilities and, on the other side, being excellent in managing both incremental and radical innovation. These balances are critical since exploitation and exploration, on the one side, and incremental and radical innovation, on the other, require different approaches that have traditionally been considered difficult to combine within the same organization. Working on evidence and discussion from the 7th CINet Conference held in Lucca (Italy) in 2006, this Special Section is aimed at contributing to theory and practice on these two complex balancing acts that today represent a hot issue in innovation management.

1. Introduction

T

oday excellent firms are challenged by very strong and unprecedented pressures. This is essentially due to the performance that their products have to possess to address customer needs, i.e., the needs of today’s and tomorrow’s customers (Boer & Gertsen, 2003; Boer, Kuhn & Gertsen, 2006). Indeed, if we focus our attention on the former, it is evident that today’s customers ask to be satisfied in terms of function, price, time, quantity, service and place of the existing product. This requires firms to be excellent in exploitation capabilities (‘Exploitation includes such things as refinement, choice, production, efficiency, selection, implementation, execution’, March, 1991, p. 71; ‘The essence of exploitation is the refinement and extension of existing competences, technologies, and paradigms. Its returns are positive, proximate, and predictable’, March, 1991, p. 85). Then, if we turn our attention to the latter, taking care of tomorrow’s customers means looking for new configurations of products; to satisfy such requirements firms have to be excellent in exploration capabilities (‘Exploration includes things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery, innovation’, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

March, 1991, p. 71; ‘The essence of exploration is experimentation with new alternatives. Its returns are uncertain, distant, and often negative’, March, 1991, p. 85) (Boer, Kuhn & Gertsen, 2006). Focusing on exploitation or exploration capabilities, therefore, entails different skills, attitudes, and management styles that have traditionally been considered difficult to combine. From these considerations, we can determine a first type of balancing need that organizations face: • In order to combine excellence in both satisfying today’s customer needs and anticipating the demand of tomorrow’s customers, firms are required to combine excellence in exploitation of old certainties and in exploration of new possibilities. (March, 1991; Boer & Gertsen, 2003; Boer, Kuhn & Gertsen, 2006) In addition, if we extend the argument connected with the requirements of tomorrow’s customer one step further, we can see that tomorrow’s customers ask for products with higher and higher levels of performance, or attribute sets, that are possible because of the technology embedded in the product (Danneels, 2004). This requires firms to

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manage the steady state innovation process, i.e., innovating incrementally, building upon their existing knowledge and capabilities. What has emerged recently is that customers not only ask for new configurations of products with higher performance, but also for new products with different attribute sets from the existing products (Danneels, 2004). It is the case, for example, with new products that address people who previously lacked the money or skill to buy/use a product (new market disruption), or new products based on a disruptive technology, that have, at first, lower performance on dimensions relevant to the mainstream market segment, but are valued by a different market group which leads the disruption (Christensen & Raynor, 2003; Burgelman et al., 2004; Danneels, 2004; Bessant, 2006a; Bessant, de Weerd-Nederhof & Fisscher, 2006), or products based on innovations which come ‘out of left field’, from the periphery. This requires firms to be excellent in incremental innovation, while at the same time innovating radically beyond the organizational normal operating envelope. This poses another challenge, in that incremental and radical innovation requires different processes, and organizations are often in conflict in terms of use of resources and management attention. The above-mentioned customer needs highlight the existence of another balance which does not substitute, but is concurrent with the previous one: • In order to sustain competition, firms are required to be excellent in both incremental and radical innovation. (Boer, 2001; Bessant, de Weerd-Nederhof & Fisscher, 2006) Firm sustainable competitiveness – i.e., the possibility for organizations to improve their performance continuously in order to cope with market demands and turbulence, customer sophistication and changing technology (Porter, 1990; Hamel & Prahalad, 1994; Douma, 1997) – requires the management of these two balancing needs that make innova-

Exploitation

tion in all of its 4Ps (the introduction and/or improvement of (i) products/services and (ii) process, (iii) the (re-)definition of the positioning of the firm or its products, and (iv) the (re-)definition of the dominant paradigm of the firm (Francis & Bessant, 2005)) play a key strategic role. During the last few years, innovation theory has produced a large but fragmented mass of literature that, more or less explicitly, has emphasized the importance of knowledge creation and learning. The objective of our work is to construct a coherent framework of the literature in order to highlight the theoretical and managerial implications in terms of knowledge generation and learning, following a historical-evolutive perspective. The abovementioned balancing acts – exploration/ exploitation and incremental/radical innovation – will serve as the key dimensions for this objective. The rest of this article is divided into three sections. In the next two sections the interpretative framework and the detailed analysis of the literature will be analysed; the final section will present the contributions selected for this Special, while collocating them in the interpretative model.

2. The Interpretative Framework of Innovation: The Role of KM The two balancing acts suggest, respectively, two key dimensions through which it is possible to review the state-of-the-art management literature on innovation: (i) the balancing act connected with exploration/exploitation focuses attention on the dimension connected with the ‘learning focus’, and (ii) the balancing act connected with incremental/radical innovation focuses attention on the dimension connected with the ‘innovation focus’. If we focus on the first dimension – the learning focus – the analysis of the management literature emphasizes an evolution like that shown in Figure 1.

Binary/orthogonal balance Balancing need Synergistic balance

Exploration t

Figure 1. Evolution of the ‘Learning Focus’ in Management Literature

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As shown in Figure 1, the state-of-theart management literature has traditionally considered and analysed exploitation and exploration separately (Andreassen & Gertsen, 2006; Boer, Kuhn & Gertsen, 2006), in the conviction that organizations can be good in one of the two capabilities, but are likely to fail to maintain an effective balance between the two (Burns & Stalker, 1961; Skinner, 1974; Porter, 1980; March, 1991, 1995). In the words of March (1991, p. 72): In studies of organizational learning, the problem of balancing exploitation and exploration is exhibited in distinctions made between refinement of an existing technology and invention of a new one [. . .]. It is clear that exploration of new alternatives reduces the speed with which skills at existing ones are improved. It is also clear that improvements in competence at existing procedures make experimentation with others less attractive [. . .]. Finding an appropriate balance is made particularly difficult by the fact that the same issues occur at levels of a nested system – at the individual level, the organizational level, and the social system level. It has only been in the last ten years that an increasing number of scholars – e.g., Spina et al. (1996) with the multi-focused manufacturing system – have begun to suggest that in the ‘continuously innovative organization’ (Boer, Kuhn & Gertsen, 2006) the ongoing interaction between exploitation and exploration processes is not only possible, but even necessary for sustainable excellence (Schonberger & Knod, Jr., 1997; Hamel, 2006; Soosay & Hyland, 2006). The question is (Boer, Kuhn & Gertsen, 2006): how is it possible? Recent management literature seems to suggest two different possibilities: binary and dual organizations that balance demands for exploitation and exploration in an orthogonal and a synergistic way, respectively. Binary and dual organizations, however, and the latter in particular, need much more investigation.

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The analysis of the first dimension highlights the three values in which the ‘learning focus’ can be articulated: (i) exploration, (ii) exploitation, and (iii) equilibrium between exploration and exploitation, both orthogonal (where a time/space separation takes place), and synergistic. If we focus our attention on the second balancing act, i.e., on the second dimension – the innovation focus –analysis of the management literature regarding innovation emphasizes an evolution like that shown in Figure 2. As shown in Figure 2, the management literature has analysed separately incremental and radical innovation, with radical innovation in conditions of discontinuity being investigated only recently (Bessant, 2006a), because of the ever increasing non-linear shifts in the ‘rules of the game’ of technologies and markets, i.e., highly uncertain and rapidly evolving conditions which result from discontinuities (Bessant et al., 2005). In the last few years some scholars have begun to discuss the interaction between incremental and radical innovation (Gilbert, 2003; Bessant et al., 2005), but this interaction really needs much more investigation as the management literature is still in its infancy. When considering the above-mentioned discontinuities, the management literature seems to be rather contrasting, particularly when incumbents’ serendipity is considered. In fact, many scholars report examples of the inertia/failure of established organizations when discontinuities occur (Tushman & Anderson, 1986; Henderson & Clark, 1990; Leonard-Barton, 1992a; Utterback, 1994; Tripsas & Gavetti, 2000). In particular, Christensen and Raynor (2003) state that when the market becomes disrupted from below, the existing incumbents, notwithstanding their dominant position in the mature phase of an existing technological trajectory, have little room to manoeuvre in the new one, being able at best to imitate or to move upmarket toward more complex, higher margin products (Gilbert, 2003), and at worst withdraw (Bessant, 2006a), because of their psychological

Incremental innovation

Binary/orthogonal balance Equilibrium

Radical innovation

Synergistic balance

t

Figure 2. Evolution of the ‘Innovation Focus’ in Management Literature © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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(not invented here syndrome) and institutional rigidities, sunk costs, commitments to existing technologies/markets, and the cognitive representations of top management that influence such commitments (LeonardBarton, 1992a ; Tripsas & Gavetti, 2000; Bessant et al., 2005). Others (Danneels, 2004) propose investigating more deeply, since different contributions (Tushman & Anderson, 1986; Markides, 1997; Evans & Wurster, 2000; Foster & Kaplan, 2002) show how incumbents have built on the new trajectory and kept their dominant position over the new players, while deploying/leveraging their knowledge. When discontinuities arise, the challenge is to manage innovation beyond the good practices and routines of the ‘steady state’ (i.e., the routines for ‘do better’ innovation), that are helpful in the mature phase, but can act as barriers against the entry and success in the fluid phase of a new technology/market, when both the old and the new technologies co-exist and evolve (Bessant et al., 2005). In other words, when discontinuities arise, the routines for ‘do different’ innovation assume a fundamental role for dealing with the challenges of ‘do different’, within the entire spread of the 4Ps (Francis & Bessant, 2005). This second dimension connected with the innovation focus can assume three values: (i) incremental innovation, which builds upon existing knowledge and capabilities, (ii) radical innovation, which goes beyond the normal operating envelope of the organization, and (iii) equilibrium between incremental and radical innovation. The combination of these two dimensions – ‘learning focus’ and ‘innovation focus’ – allows the construction of a bi-dimensional matrix, where the main streams of the literature can be mapped (Figure 3). Each stream will be analysed, highlighting the implications

in terms of knowledge creation and learning. However, readers should be warned that there exist overlapping and fuzzy borders between different streams. The analysis of the content of the main streams is presented in the next section. In our analysis we consider articles published in major English-language North American and European journals.

3. Knowledge Management in Innovation: Main Streams in the Literature 3.1 Incremental Exploitation Incremental exploitation refers to the ‘exploitation’ capabilities that lead to incremental product and process improvement. It deals with continuous improvement (CI), or kaizen (Imai, 1986), defined as ‘the planned, organised and systematic process of ongoing, incremental and companywide change of existing practices aimed at improving company performance’ (Boer et al., 2000, p. 1). According to Bessant’s CI maturity model (1998), CI is a long-term learning process that involves a suite of behaviours that cluster around several core themes, namely routines (for example behaviours associated with the systematic finding and solving of problems or with the monitoring and measuring processes, etc.), that evolve and are reinforced over time. The development of routines involves two kinds of learning: improving/reinforcing behaviours within a particular routine cluster or adding new routines to the repertoire. Organizations can progress towards higher CI maturity levels by acquiring, practising and repeating CI behaviours until they become ingrained as ‘the way we do things around here’.

Learning focus Exploitation

Innovation focus

Incremental innovation

Incremental exploitation

Equilibrium between radical and incremental innovation

Radical innovation

Equilibrium between exploration and exploitation

Exploration

Binary and dual forms

Incremental exploration

Full dexterous organization

Equilibrium between radical and incremental exploration

Radical exploitation

Radical exploration

Figure 3. The Matrix of Knowledge Creation and Learning

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There are a number of distinctive characteristics that differentiate CI from the more ‘traditional’ breakthrough innovation: 1. The type of change (Bessant, 1998): CI concerns incremental changes, i.e., the pattern of small modifications and improvements which have their impact on performance in a cumulative fashion, while traditional innovation concerns major discontinuous changes (developing new products, introducing new processes and radically transforming organizational structures). 2. The frequency of change (Bessant & Caffyn, 1997): in contrast to breakthrough innovation, CI is not limited to specific projects and situations, but is part of the everyday working life. 3. The type of knowledge (Bessant, 1998; Bessant, Caffyn & Gallagher, 2001): everyone in the organization has the capacity to solve problems in a creative fashion, while major, hi-tech discontinuous innovation remains the province of specialists, in that it implies skills and formal knowledge constraints. 4. The degree of workforce participation and scope of the innovative base in the organization (Bessant & Caffyn, 1997; Imai, 1997; Mitki, Shani & Meiri, 1997; Bessant, 1998; De Jager et al., 2004): while in the traditional perspective a neat split takes place between those employees concerned with exercising judgement – the specialists who often work apart from the mainstream of the organization’s operations (typically R&D and IT functions) – and those who have to repeat standardized tasks, in CI all the employees are reckoned to have the capacity to solve problems creatively, so amplifying the organizational innovative base. Today many streams of the literature, coming from different perspectives, theorize the necessity to involve people in the innovation activities (Bessant & Caffyn, 1997; Bessant, 1998): lean manufacturing (with its emphasis on team working and participation in innovation; Bessant, 2006c), total quality management (whose underlying recipe is based on the contribution of the participants in the process of finding and solving quality problems; Bessant, 2006c), ‘productivity through people’ programmes, Japanese manufacturing techniques, the learning organization, and advanced technology implementation. From a knowledge management (KM) and learning perspective, the importance of such continuous and widespread participation in problem-solving activities lies in three major effects: the mobilization of the organizational core knowledge base (Bessant, 1998) in that a 100-headed brain is unleashed (Boer et al., © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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2000), the systematic capture and conversion of tacit knowledge into explicit knowledge, which can be articulated in standard operating procedures (Bessant & Francis, 1999), and the possibility to activate learning processes (Bessant, 1998).1

3.2 Incremental Exploration Incremental exploration refers to exploration capabilities that lead to incremental innovation – i.e., innovation which builds on existing knowledge – in both processes and products. As far as processes are concerned, it is important to mention business process re-design or re-engineering (BPR) that attempts to contribute to performance improvement, but, in contrast to CI, through non-linear changes and without the widespread involvement of employees (Boer et al., 2000). As far as products are concerned, since 1980 three main streams have emerged in the management literature regarding new product development (NPD): concurrent engineering, multi-project management and organizational learning. From a KM and learning perspective, such streams move the focus from the quick and intense socialization of knowledge in cross-functional, often co-located teams, to knowledge sharing through commonality and reuse of design solutions, up to the overall dynamic of knowledge creation and transfer also in tacit form or embedded into processes and organizational routines (Corso et al., 2001). Since the early 1980s, concurrent engineering has been considered the new paradigm for NPD as it replaces phased programme planning (the stage-gate process) with the joint participation of different functional groups in the PI process (Joice, 1986; Nonaka, 1990). From the KM viewpoint, the focus is on quick and intense socialization of knowledge in crossfunctional, often co-located teams. In order to improve time-to-market of the specific development project, knowledge is socialized in tacit and contextual forms, with limited emphasis on its codification, abstraction and generalization to foster future innovation. Furthermore, concurrent engineering keeps a rigid separation between product concept generation and product development (Dougherty, 1990, 1992; Iansiti, 1995). Also within the development project, milestones and ‘gates’ are defined to set constraints on possible information loops (Cooper, 1992, 1994), thus implicitly limiting the scope for knowledge 1

In particular, the approach of the level 3 of Bessant’s (1998) model provides a framework for establishing a ‘learning organization’ (Bessant & Francis, 1999).

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sharing and learning (Iansiti, 1995; MacCormack & Iansiti 1997; Verganti, MacCormack & Iansiti, 1998). From a knowledge management perspective this means fostering rapid learning loops within the overall product development process. Since the late 1980s, multi-project management has highlighted the risk, implicit in a concurrent engineering approach, of isolating each innovation process from the rest of the organization. In a medium- to long-term perspective, success depends on the ability to foster the sharing of knowledge through commonality and reuse of design solutions (Wheelwright & Sasser, 1989; Wheelwright & Clark, 1992; Sanderson & Uzumeri, 1995). From a KM perspective, this means enlarging the scope of learning and knowledge sharing, shifting attention from single products to product families, and emphasizing the importance of components and product platforms as vehicles embodying knowledge (Henderson & Clark, 1990; Cusumano & Nobeoka, 1992). Multiproject management has become a key issue in product development; conceptual models and tools have been developed to support the management of the interdependencies connected with knowledge transfer between projects over time (Czajkowski & Jones, 1986; Clark & Fujimoto, 1991; De Maio, Verganti & Corso, 1994). Analysing such interdependencies, some authors focus on the actual object of the interaction (Itami, 1987; Nonaka, 1991) distinguishing between interactions related to the exchange of tangible technological solutions (e.g., parts, components), of codified knowledge (patents, processes and formulas) and of non-codified know-how, generally personembodied. Others focus on the scope of the interaction, distinguishing between the component level and the architectural level (Henderson & Clark, 1990). A third and final group of contributions focuses on the approach in the transfer process, that can either be reactive, when solutions and knowledge from past projects are ex post retrieved and reused, or proactive, when solutions are deliberately developed for future use, often for not previously planned projects (De Maio, Verganti & Corso, 1994). Many authors have shown how traditional reactive policies, based on the carry over of parts and subsystems, are intrinsically limited and may also be detrimental to innovation (Clark & Fujimoto, 1991; Witter et al., 1994). Excellent companies prefer to use proactive policies where ex ante efforts are made to predict characteristics and features of new parts and subsystems to suit future applications. Depending on the architectural or component knowledge embodied in the solutions, these proactive policies are named ‘product

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platforms’ or ‘shelf innovation’ (Hayes, Wheelwright & Clark, 1988; Wheelwright & Sasser, 1989; Wheelwright & Clark, 1992; Meyer & Utterback, 1993; Sanderson & Uzumeri, 1995). In 1990, product innovation became a key area of interest for scholars of organizational learning. While multi-project management focused mainly on transfer of knowledge embodied in design solutions, organizational learning analyses the overall dynamic of learning and knowledge creation and transfer also in tacit form or embedded into processes and organizational routines (Nonaka, 1991; Nonaka & Takeuchi, 1995). Also, while multiproject management considers learning and knowledge reapplication as an automatic process, organizational learning emphasizes how learning and knowledge reuse may face barriers at organizational and individual levels, asking for an aware management support (Imai, Nonaka & Takeuchi, 1985; Senge, 1990; Nonaka, 1991; Arora & Gambardella, 1994; Hedlund, 1994; von Hippel & Tyre, 1995; Bartezzaghi, Corso & Verganti, 1997). However, most contributions share the assumption that product innovation is the outcome of NPD projects over time, hence, implicitly considering downstream phases only as sources of information for feeding next generation product development, or even constraints to be anticipated during development (Clark & Fujimoto, 1991). Some contributions, in contrast, highlight the necessity to extend the innovative efforts to the overall product life-cycle (Itami, 1987; Bessant et al., 1994; Caffyn, 1997; Bartezzaghi, Corso & Verganti, 1999; Corso, 2002).

3.3 The Equilibrium between Incremental Exploration and Exploitation: Binary and Dual Forms The equilibrium between incremental exploration and exploitation (Tushman & O’Reilly, 1996) entails two forms: binary and dual organizations, where ‘binary organisations balance demands for exploitation and exploration in an orthogonal way, [while] dual organisations do so synergistically’ (Boer, Kuhn & Gertsen, 2006, p. 4). In binary organizations there is a separation between exploration and exploitation, which can be either space or time. Examples of the first case – space – are: (i) the structural ambidexterity,2 i.e., the structural separation of 2

According to Birkinshaw and Gibson (2004), the concept of ambidexterity – the right balance between adaptability and alignment – ‘has typically been associated only with structural separation of activities’ (p. 48), i.e., with structural ambidexterity. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


activities (Birkinshaw & Gibson, 2004) implied in the functional structures, where co-existing functions of exploration and exploitation operate at the same time, but in different places, with obvious shortcomings in terms of response time to environmental changes, innovativeness and horizontal co-ordination between departments (Boer, Kuhn & Gertsen, 2006), which drives toward the frequent failure of research ideas to be accepted (Birkinshaw & Gibson, 2004); (ii) the nonrevolutionary, or gradual, incremental transformation theory (Romanelli & Tushman, 1994) that interprets the organizational transformation as the lengthy and gradual result of the accumulation of short-run, incremental and disjointed reactions that the singular subunits put in place when one change (a problem or a goal) occurs in the local – internal and external – environment. Examples of the second case – time – are: (i) the punctuated equilibrium model in which the ‘equilibrium periods’ (long periods of small and incremental change in their basic pattern of activity, reinforced by the organizational inertia and institutionalization) are punctuated by revolutionary periods (brief periods of discontinuous, fundamental change) that, while disrupting established activity patterns, install the basis for new equilibrium periods (Tushman & Romanelli, 1985; Romanelli & Tushman, 1994; Tushman & O’Reilly, 1996); (ii) the innovation process model, in which radical systemic changes are followed by long periods of maintenance and incremental improvement (Imai, 1986); (iii) the combination of extensive ‘do what we do better’ improvements with periodic and radical ‘do what we do different’ changes, which create a different framework within which future ‘do better’ improvements can be made (De Jager et al., 2004); (iv) the theories of innovation dynamics, which suggest that when a new product concept or process emerges, there is an initial period of uncertainty during which there is experiment around different configurations, but, when a ‘dominant design’ or ‘technological trajectory’ is established, the emphasis shifts to incremental improvements and refinements: in the case of products, the effort is on the introduction of variations on the basic theme, while, in the case of processes, the effort is on the stretching/ developing of the performance, driving out waste, eliminating bugs, etc. (Bessant, 2006c). Dual forms synergistically balance exploitation and exploration (Boer, Kuhn & Gertsen, 2006). Examples include: (i) the continuously innovative organization, analysed from the perspective of co-ordination theory – co-ordination through strategic alignment, process integration, technological integration, © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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and organizational mechanisms (Paashuis & Boer, 1997; Boer, Kuhn & Gertsen, 2006) or (ii) the contextual ambidextrous firm, in which, in contrast to a top-down approach, the employee acts outside the border of his/her job and encourages action that involves adaptation to new opportunities, while being aligned with the business strategy (Birkinshaw & Gibson, 2004). Birkinshaw & Gibson (2004) also propose a sort of equilibrium between the dual and the binary organization, in that they conceive the contextual ambidexterity as complementary to the structural ambidexterity: structural ambidexterity, essential at times, should be temporary in order to give a new initiative the space/ resources to get started. ‘The eventual goal should be reintegration with the mainstream organization as quickly as possible. Contextual ambidexterity can enhance both the separation and reintegration processes’ (p. 55). Chapman and Corso (2005) draw attention to the necessity to extend the unit of analysis from the context of single companies to an inter-organizational setting, that of extended manufacturing enterprises (Busby & Fan 1993; Harland, Lamming & Cosins, 1999; Stock, Greis & Kasarda, 2000), that can scarcely rely on established organizational and managerial mechanisms to support the equilibrium between exploration and exploitation at company level: new information and communication technologies and particularly Internet applications can play a fundamental role in bridging these gaps. Examples include eprocurement, e-sourcing and e-collaboration applications which allow customers and suppliers to increase co-ordination and collaboration through the Internet in terms of inventory management, demand management, production planning and control and new product development (Porter, 1998; Lee & Whang, 2001; Cagliano et al., 2003). When considering this stream of the literature, knowledge represents a valuable tool for managing dualities: in particular, when considering co-ordination through technological integration, technology has to be interpreted as knowledge embedded in (i) people (the knowledge, skills, experience, people use to perform activities), (ii) methods and techniques, and (iii) plant, equipment, tools and infrastructure (Boer, Kuhn & Gertsen, 2006).

3.4 Radical Exploration Radical exploration refers to exploration capabilities that lead to radical innovation in new and uncharted territories (Bessant, 2006c).

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This stream of the literature deals with discontinuities,3 characterized by high instability (unpredictable and unstable conditions) and high uncertainty (the extent to which knowledge can be acquired to help deal with the environment). Such discontinuities reframe the space and the boundary conditions and open up new opportunities, while challenging incumbents (Bessant et al., 2005). As stated earlier, the literature is not all in agreement when analysing the destiny of the incumbents faced with discontinuous shifts. Those who claim to be attentive to the impact that discontinuities can have on established firms highlight the existence of a sort of trade-off between new (often SMEs) and experienced players. The former – only those who are successful, and hence analysable (Danneels, 2004) – are not encumbered with their past experience and are endowed with agility, flexibility, the ability to learn fast, the lack of preconceptions about the ways in which things might evolve (Bessant et al., 2005; Bessant, 2006b), but lack the knowledge base, assets and competencies. The latter have the competencies, the financial assets and the capacity to mix the technologies they master, but in many cases show a sort of inertia in responding effectively and, as a consequence, can falter. The main reasons for this possible inertia are numerous: (i) their core capabilities – both technological (Nelson & Winter, 1982; Teece, Pisano & 3

Bessant et al. (2005) lists the typical sources of discontinuity, namely: emergence of (i) a new market, (ii) a new technology, (iii) new political rules, (iv) running out of road, (v) sea change in market sentiment or behaviour, (vi) deregulation/ shifts in regulatory regime, (vii) fractures along ‘fault lines’, (viii) unthinkable events, (ix) business model innovation, (x) architectural innovation, and (xi) shifts in ‘techno-economic paradigm’ – systemic changes which impact whole sectors or even whole societies. In particular, in this last case, the ‘convergence of a number of trends’ is considered: according to Bröring and Leker (2007), convergence can either be induced by the fusion of demand structures and the combination of previously distinct product features into a hybrid product – such as personal computers and televisions starting to become substitutes (Prahalad & Ramaswamy, 2003) – or technology-driven since a new technological development is applied across conventional industry boundaries, such as genomics applied to both nutrition and pharmaceuticals (Rao, Angelov & Nov, 2006 highlight that the technological convergence of both incremental innovations and disruptive innovations can be sources of discontinuity). In both case, however, the convergence can be of the 1 + 1 = 1 type (total phasing out of the two formerly separate industries) or of the 1 + 1 = 3 type (emergence of an additional industry segment), where innovation seems to be an imperative or an opportunity, respectively.

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Shuen, 1997) and marketing capabilities (Christensen, 1997) – that in some cases prove to be ‘core rigidities’ (Leonard-Barton, 1992b), (ii) the cognitive representations of their top management, which, by restricting and directing search activities connected with technology development, can constrain the development of new capabilities (Tripsas & Gavetti, 2000), (iii) the impact that disruption can have on their competencies, that can be enhanced or destroyed (Tushman & Anderson, 1986), and (iv) the blinkers of dominant logic (i.e., successful recipes in terms of business models, processes, approaches to competition), that limit the ability of people in the organization to drive innovation or see new opportunities and threats (Prahalad, 2004). The incumbents who survived showed the ability to take on new knowledge, while unlearning knowledge that was no longer needed (Utterback, 1994), which indeed is seen to be redundant (Bessant, 2006b). Hence, the challenge for incumbents seems to be that of creating new routines in order to cope with discontinuous innovation (‘do different’ routines), i.e., managing discontinuity – the ‘ripples in the pond’ (Brown, 2004). This entails new approaches for sensing the periphery (Baden-Fuller, 2004; Day & Schoemaker, 2004; Huston, 2004), discovering weak signals regarding potential discontinuities in areas not usually investigated, understanding the needs of a market that does not yet exist which will shape the eventual dominant design, discovering and finding new users, making strategic choices in the face of high uncertainty, carrying out projects which lie at the fringes of the organizational experience, exploiting network relationships with actors other than ‘strong ties’ partners (Bessant et al., 2005), and learning to unlearn and see differently (Brown, 2004). Between these, the exploitation of network relationships, which root in the stream of inter-organizational design (Corso et al., 2001), seems to be the most investigated area4 with particular attention to the role played by customers as innovation sources. More exactly, while in the past, research-intensive companies believed that research in the organization’s core area of expertise had to stay in-house, with outsiders providing only less 4

Inter-organizational design expands the scope of the product innovation process outside the traditional R&D boundaries, in that external complexity hinders the single firm from the chance of managing the knowledge system supporting the whole NPD process. In particular, a first sub-stream stresses the importance of designing new roles within R&D – such as gatekeepers – to bridge to the external environment (Katz & Tushman, 1981; Ancona & Caldwell, 1990; Allen, 1997). A second © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


important support activities, today – as the pharmaceutical and chemical companies illustrate – businesses are using external sources for all phases of innovation, from discovery and development to commercialization and even product maintenance. This evolution, which gives organizations the possibility to access disruptive new ideas, implies the necessity to deploy a sourcing strategy in order to manage innovation holistically, as opposed to managing innovation transactionally, whose major shortcomings are failure to leverage organizational learning (no method for applying the lessons learned from one external relationship to the others) and, most importantly, unintentionally losing knowledge (Linder, Jarvenpaa & Davenport, 2003). To give shape to the external sources as part of a complete sourcing strategy, several innovation channels are available – buying innovation on the market, investing in innovators, co-sourcing, re-sourcing (Linder, Jarvenpaa & Davenport, 2003), inward technology licensing (Leone, Boccardelli & Magnusson, 2007) – and, with particular attention to channels specifically conceived for interacting with customers: community sourcing (Linder, Jarvenpaa & Davenport, 2003), democratizing innovation (von Hippel, 2005), co-creating value with customers (Prahalad & Ramaswamy, 2003; Prahalad, 2004), opening innovation (Chesbrough, 2003). When customers are considered, however, not all the authors agree on their role: Christensen (1997), for example, thinks that firms, while ‘[held] captive by their customers’, can miss the boat on disruptive technologies. From a learning perspective there are two major aspects to be highlighted: on the one side the fact that ‘the management task [is] not simply one of building and sustaining routines for innovation but also – and most importantly – one of creating the underlying learning routines which enable the organisation to do so’ (Bessant, 2006c, p. 19); on the other side, the

sub-stream focuses on the direct and early involvement of external actors in inter-organizational groups (Katz, 1982; Imai, Nonaka & Takeuchi, 1985; Clark & Fujimoto, 1991). Finally, other authors investigate the specific relationships the firm builds with actors belonging to the supply chain (vertical agreements) (von Hippel, 1976, 1977, 1978, 1988; Imai, Nonaka & Takeuchi, 1985; Takeuchi & Nonaka, 1986; Nonaka, 1990; Clark & Fujimoto, 1991; Cusumano & Takeishi, 1991; Dyer, 1996; Edwards & Samimi, 1997), with competitors (horizontal agreements) (Clark & Fujimoto, 1991) and with complementary firms and institutions (cross agreements) (Teece, 1986; von Hippel, 1988; Lundvall, 1988; Lee, 1996). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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creation of organizational routines and processes, by which firms acquire, assimilate, transform, and exploit knowledge to produce a dynamic organizational capability (Cohen & Levinthal, 1990; Andersen & Boer, 2007).

3.5 Equilibrium between Radical and Incremental Exploration This type of equilibrium deals with the challenge of coupling steady state innovation with discontinuous innovation, allowing routines for discontinuous innovation to sit alongside those for steady state innovation. A question of great interest is whether this balance can be reached in a synergistic way or in an orthogonal way, by organizational separation such as the creation of a spin-off unit to pursue disruptive technology (Bessant, 2006c; Danneels, 2006). In other words, when a mismatch between firms’ dominant steady state archetype (the ‘interpretative schema’ of the world, their strategy and resulting resource allocation; their routines and consequent structures and procedures) and the very different requirements for discontinuous innovation occurs, the question is: ‘is it possible to operate both archetypes under the same organizational roof and develop the ability to switch between them [. . .]? Or does successful management under different sets of conditions require setting up completely new organisations – for example, spinning off a completely new company to exploit new opportunities under discontinuous conditions?’ (Bessant et al., 2005, p. 9). The answers in the literature do not all point in the same direction (Danneels, 2004). Christensen (1997) proposes – although in wellspecified conditions5 – an orthogonal balance, in which incumbents should set up a separate organization endowed with their own resources for venturing into disruptive technology, in order to prevent problems connected, on the one side, with the missing fit between the disruptive technology and the mainstream organization’s resources, processes and values and, on the other side, with resources transferred from disruptive technology efforts to serve current customers. Also, other authors support this opinion, highlighting the advantages that creating a separate organization may have (Cohan, 2000), and in particular the possibility of avoiding possible misfits between the needs of the discontinuous 5

That is, when a disruptive technology requires a different cost structure for reasons of profitability and competitiveness, or when the size of the opportunity is insignificant relative to the growth needs of the mainstream organization.

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innovation and the business unit’s existing capabilities (Rice, Leifer & Colarelli O’Connor, 2002), and the opportunity, when the disruptive new business starts small, to figure out the requirements of the new customers, adjusting business models and product architectures early before huge resources are poured into the new business (Gilbert, 2003). Other authors highlight the disadvantages connected with the formation of an independent organization, in terms of lost synergies in purchasing, information sharing, branding, cross-promotion, and customer service (Gulati & Garino, 2000). From a knowledge management perspective, this trade off between arguments for and against a spinoff organization consists of the fact that ‘isolation may protect the project from the counterproductive forces within the mainstream, but it also cuts the project off from its most important sources of learning, competences and resources’ (McDermott & Colarelli O’Connor, 2002, pp. 431–32).

3.6 Radical Exploitation Radical exploitation refers to exploitation capabilities that lead to radical innovation in new and uncharted territories. Within this stream of the literature, many contributions highlight that in different industries many incumbents, while leveraging on their existing knowledge, could be credited with many radical innovations. This is the case with the telecommunications and medical device industries (Methe et al., 1997), manufacturers of television sets (Klepper & Simons, 2000), office products and consumer durables (Chandy & Tellis, 1998).

3.7 Fully Dexterous Organizations Full dexterity implies that organizations have the capabilities to innovate both radically and incrementally, while at the same time focusing on operational effectiveness. With respect to the other streams, full dexterity is the least investigated in the management literature. At the moment, authors simply highlight the necessity to further explore these aspects (Boer, 2001). The first tentative results are those of Martini and Pellegrini (2007), who describe a retrospective case study in which a knowledge management and an innovation management system were created not only for co-ordinating R&D and production – so combining excellence in exploitation and in exploration – but also for searching at the periphery, while picking up and amplifying weak signals – so combining excellence in incremental and radical innovation.

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4. The Special Section The analysis of the state-of-the-art literature shows that there remain research gaps to be covered and research questions to be answered in each stream of the literature of the ‘matrix of knowledge creation and learning’ depicted in Figure 3. This special section of Creativity and Innovation Management, which collects together five papers selected at the 7th CINet conference6 held in Lucca (Italy) in 2006, answers the following research questions. In particular: • In the incremental exploitation stream: 䊊 Are the premises of the CI maturity model culturally bound to national borders or rather do they transcend such borders? That is, to what extent do the constituent behaviour patterns of the CI maturity model converge across national borders, or are there country-specific differences? Mandar Dabhilkar, Lars Bengtsson and John Bessant, who draw upon the 2nd CINet survey, find that the premises of the CI maturity model transcend cultural and national borders and, hence, that the CI behaviour patterns converge across nations. 䊊 For implementing CI, human resource management (HRM) assumes a key role: it should secure a workforce capable of implementing CI and participate in the planning of employee training and development. Hence: which are the HRM practices that yield the greatest benefit in terms of CI development and, consequently, performance? The article by Frances Jørgensen, Bjørge Timenes Laugen and Harry Boer takes as its theme the impact of HRM on CI practices. Basing its results on the 2nd CINet Survey, these authors suggest that HRM can play an important role in supporting CI implementation that positively affects business performance. • In the stream connected with the equilibrium between incremental exploration and exploitation: 䊊 Can the concepts/practices of continuous innovation (that are usually applied to individual companies) be applied to manage improvement and innovation actions designed and implemented jointly among companies in a cluster? 6

CINet – the Continuous Innovation Network (http://www.continuousinnovation.net) – is an international group of researchers and practitioners who share common concerns about the effective management of innovation. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


The article by Luiz Cesar Ribeiro Carpinetti, Mateus Cecilio Gerolamo and Edwin Vladimir Cardoza Galdámez presents a conceptual model for managing actions for improving collective efficiency and measuring performance of an SME cluster. The article concludes that despite some difficulties in developing and using performance indicators in SMEs, the concepts presented by the proposed model can help to foster in clusters of SMEs co-operation and maturity in continuous innovation. 䊊 Is there a methodology for implementing information and communication technologies (ICT) in logistics? In the article by Jesús García-Arca and Carlos PradoPrado, the authors offer a methodology for implementing ICTs in the logistics field, with a participatory approach. • In the stream of radical exploration: 䊊 It is evident that faced with discontinuities, incumbents fail to cope with major changes in the environment and, thus, it is important to develop and search for best practices, whose implementation process is critical for success. Hence the question is: how do best performing companies implement new practices? Bjørge Timenes Laugen and Harry Boer investigate this research question through case studies in two highperforming manufacturing firms. The analysis of the implementation showed that a broad and incremental implementation approach initially leads to reduced performance followed by a gradual improvement as larger parts of the programmes are institutionalized. A ‘big bang’ implementation approach does not seem to lead to deterioration in performance.

Acknowledgements This special section of Creativity and Innovation Management is the closing act of the 7th CINet Conference, held in Lucca, Italy, in September 2006. It is the result of the precious work of many people whose contribution is gratefully acknowledged. In particular we would like to thank all the authors of the selected papers and the reviewers who spent some of their valuable time in reviewing them, namely: Prof. Pär Åhlström, Chalmers University of Technology, Sweden Prof. Vito Albino, Politecnico di Bari, Italy Prof. Ross L. Chapman, University of Western Sydney, Australia © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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Dr. Carmen Kobe, ETH Zürich, Switzerland Dr. Frances Jørgensen, Aalborg University, Denmark Prof. Paul Hyland, Central Queensland University, Australia Dr. Anna Nosella, University of Padova, Italy Dr. Anders Richtnér, Stockholm School of Economics, Sweden Dr. Stefano Ronchi, Politecnico di Milano, Italy Dr. Claudine A. Soosay, University of South Australia, Australia Prof. Stefano Tonchia, University of Udine, Italy Our appreciation also goes to the team at Blackwells.

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Prahalad, C.K. (2004) The Blinders of Dominant Logic. Long Range Planning, 37, 171–79. Prahalad, C.K. and Ramaswamy, V. (2003) The New Frontier of Experience Innovation. MIT Sloan Manacement Review, Summer, 12–18. Rao, B., Angelov, B., Nov, O. (2006) Fusion of Disruptive Technologies: Lessons from the Skype Case. European Management Journal, 24, pp. 174– 88. Rice, M.P., Leifer, R. and Colarelli O’Connor, G. (2002) Commercializing Discontinuous Innovations: Bridging the Gap from Discontinuous Innovation Project to Operations. IEEE Transactions on Engineering Management, 49, 330– 40. Romanelli, E. and Tushman, M.L. (1994) Organizational Transformation as Punctuated Equilibrium: An Empirical Test. Academy of Management Journal, 37, 1141–66. Sanderson, S. and Uzumeri, M. (1995) Managing Product Families: The Case of the Sony Walkman. Research Policy, 24, 761–82. Schonberger, R.J. and Knod, E.M., Jr. (1997) Operations Management. Customer-Focused Principles. McGraw-Hill, New York. Senge, P.M. (1990) The Fifth Discipline. The Art and Practice of the Learning Organization. Doubleday, New York. Skinner, W. (1974) The Focused Factory. Harvard Business Review, 52, 113–21. Soosay, C.A. and Hyland, P.W. (2006) Knowledge Exploration and Exploitation: The Absorptive Capacity for Continuous Innovation. 7th International CINet Conference ‘CI and Sustainability – Designing the Road Ahead’, Lucca, Italy, 8–12 September, pp. 734–45. Spina, G., Bartezzaghi, E., Bert, A., Cagliano, R., Draaijer, D.J. and Boer, H. (1996) Strategically Flexible Production: The Multi-Focused Manufacturing Paradigm. International Journal of Operations & Production Management, 16, 20– 41. Stock, G.N., Greis, N.P. and Kasarda, J.D. (2000) Enterprise Logistics and Supply Chain Structure: The Role of Fit. Journal of Operation Managent, 18, 531–47. Takeuchi, H. and Nonaka, I. (1986) The New Product Development Game. Harvard Business Review, 86, 137–46. Teece, D.J. (1986) Profiting from Technological Innovations: Implications for Integrations. Research Policy, 15, 285–305. Teece, D.J., Pisano, G. and Shuen, A. (1997) Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18, 509–53. Tripsas, M. and Gavetti, G. (2000) Capabilities, Cognition and Inertia: Evidence from Digital Imaging. Strategic Management Journal, 21, 1147– 61. Tushman, M. and Anderson, P. (1986) Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, 31, 439– 65. Tushman, M. and O’Reilly, C.A. (1996) Ambidextrous Organizations: Managing Evolutionary and Revolutionary Change. California Management Review, 38, pp. 8–30. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


Tushman, M.L. and Romanelli, E. (1985) Organizational Evolution: A Metamorphosis Model of Convergence and Reorentation. In Cummings, L.L. and Staw, B.M. (eds.), Research in Organizational Behavior, Vol. 7. LAI Press, Greenwich, CT, pp. 171–222. Utterback, J. (1994) Mastering the Dynamics of Innovation. Harvard Business School Press, Boston, MA. Verganti, R., MacCormack, A. and Iansiti, M. (1998) Rapid Learning and Adaptation in Product Development: An Empirical Study on the Internet Software Industry. EIASM 5th International Product Development Management Conference, Como, Italy, 25–26 May. Wheelwright, S.C. and Clark, K.B. (1992) Creating Project Plans to Focus Product Development. Harvard Business Review, 70, 71–82. Wheelwright, S.C. and Sasser, W.E. (1989) The New Product Development Map. Harvard Business Review, 67, 112–25. Witter, J., Clausing, D., Laufenberg, L. and Soares de Andrade, R. (1994) Reusability – The Key to Corporate Agility. 2nd International Product Development Management Conference on New Approaches to Development and Engineering, EIASM, Göteborg, 30–31 May.


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Mariano Corso ([email protected]) is Full Professor of Organization and Human Resources at Politecnico di Milano where he chairs the course in Management Engineering at the Cremona site. At the MIP, the Business School of Politecnico di Milano, he is director of the Masters in Management and Organization Development and of the Observatories on Enterprise2.0, ICT Strategic Sourcing and ICT Strategy and Governance. He has promoted and co-ordinated national and international research on Knowledge Management. He is author of more than 100 publications at the international level. Luisa Pellegrini (luisa.pellegrini@dsea. unipi.it) is Associate Professor of Management Engineering at the faculty of Engineering, University of Pisa where she teaches Innovation Management and Business Economics and Organisation. She is actively involved in national and international research projects on Knowledge Management and Continuous Innovation. She is member of the Continuous Innovation Network (CINet) and author of more than 40 international publications.

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Convergence or National Specificity? Testing the CI Maturity Model across Multiple Countries Mandar Dabhilkar, Lars Bengtsson and John Bessant This study empirically tests the Continuous Improvement (CI) maturity model across multiple countries. The analysis is based on data from the 2nd International CINet Survey, limited to the situation in Australia, Italy, the Netherlands, Spain, Sweden and the United Kingdom. Despite some differences in Continuous Improvement maturity level between countries, findings lend support to the convergence argument. Regardless of national specificity, Continuous Improvement behaviour patterns emerge in a similar fashion, and furthermore, correspond to improved operational performance if adopted. In addition, findings show that other contextual variables such as company size and type of production system are of limited importance. This implies that Continuous Improvement is something that can be implemented and developed successfully if managed properly, irrespective of contextual influences such as those stemming from cultural and industrial factors.

Introduction

C

ontinuous Improvement (CI), a core principle of the Total Quality Management (TQM) approach, is today commonly recognized and practised in industrial firms all over the world (Sila & Ebrahimpour, 2002). However, both the popular press and academic journals have published numerous accounts describing examples of CI implementation, subsumed under the heading of TQM, which have experienced varying degrees of success (e.g., Keating et al., 1999; Beer, 2003; Yeung, Cheng & Lai, 2006). A major reason why TQM implementations often run out of steam is the heavy focus on CI tools and techniques, neglecting how CI behaviour patterns emerge in the workplace. In order to overcome shortcomings of the tools- and techniquecentred TQM approaches, Bessant and Caffyn (1997) have proposed the CI maturity model. The model illustrates how organizations can progress towards higher CI maturity levels by acquiring, practising and repeating CI behaviours until they become ingrained as ‘the way we do things around here’ and form an integral part of the culture of the organization (Bessant & Caffyn, 1997). The advantage of this emphasis is that it brings insight

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into how CI maturity can be developed in an organization. The general idea is to provide a framework for assessing the maturity level but also, and more importantly, to specify the kind of behaviours that need to be further developed. Until now, few studies have empirically tested the premises of the CI maturity model. In an implementation case study, De Jager et al. (2004) found the model valid, and the study reported significant performance benefits for the case company. The 1st International CI Survey was launched in the mid 1990s. It identified broad differences between groups of companies classified by their CI maturity. However, a far less developed version of the CI maturity model was used at this time and this is one of the reasons for the second round of the survey. The 2nd International CI survey was more directly based on the constructs of Bessant and Caffyn’s (1997) CI maturity model. Several studies have used the dataset to analyse CI activities in the participating countries (e.g., Albors & Hervás, 2007; Corso et al., 2007; Dabhilkar & Bengtsson, 2007; Hyland, Mellor & Sloan, 2007; Middel, op de Weegh & Gieskes, 2007; Readman & Bessant, 2007). An overview of selected results is given in the work by Sloan and Boer (2007). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

CONVERGENCE OR NATIONAL SPECIFICITY?

However, so far only two studies have taken the opportunity to test the CI maturity model quantitatively. Using Swedish data, Dabhilkar and Bengtsson (2007) showed by multiple regression analysis that enhancement of CI maturity level significantly explained improvements in operational performance, working conditions and customer satisfaction. Recently, Jørgensen, Boer and Timenes Laugen (2006) have also used the aggregated survey data from the 2nd CI survey and confirmed that each prescribed group of CI behaviours was positively related to operational performance. However, this study did not analyse in detail the different CI maturity levels described by the model. Furthermore, as the study used aggregated data, it may cover important differences in CI practices reported earlier in the nation-specific studies. While there is still need for additional tests of the CI maturity model, a remaining question on the reliability and validity of the model also concerns the robustness of national differences. That is, to what extent do the constituent behaviour patterns of the CI maturity model converge across national borders, or are there country-specific differences? The overall purpose of this study is twofold. First, the study sets out to empirically test the CI maturity model by means of a large scale survey, i.e., the 2nd International CI Survey. The second purpose is to analyse whether the premises of the CI maturity model are culturally bound or transcend national borders. The analysis is restricted to countries represented in the 2nd International CI Survey by more than 50 observations, i.e., Australia, Italy, the Netherlands, Spain, Sweden and the United Kingdom. While the first purpose is interesting from a model development point of view, the second purpose relates to the debate on convergence versus national specificity in management practice. In particular, it concerns whether TQM is a universal approach applicable across nations and cultures, or if national specificity considerably affects its effectiveness (Rungtusanatham et al., 2005). As an example, Dahlgaard et al. (1998) found clear differences in TQM implementation between organizations in Western and Eastern countries. The Western companies lagged their counterparts in the East in issues like formulation of a quality policy, communicating its content to all employees in the organization, resources used for quality training per employee, participation of top managers in quality audits, quality motivation and quality suggestions, and the use and variety of quality tools and methods. In contrast to many other studies, Rungtusanatham et al. (2005), however, found preliminary evi© 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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dence that TQM practices possibly can follow indistinguishable patterns, i.e., support for the universality of TQM. In their study they compared Deming-based TQM constructs across German, Italian, Japanese and US plants. Our study is limited to six countries: five European countries and Australia. This limitation to a comparison between rather few countries is common to most TQM-related survey studies (Sila & Ebrahimpour, 2002). We would, of course, expect larger differences in CI practices if we had been able to include firms from Asia or the United States. This is open for further research. However, according to results from project GLOBE (House et al., 2002) on culture and leadership in 61 countries, even the countries represented in our dataset display important differences. According to Dickson, Den Hartog & Mitchelson (2003), the six countries in our study belong to four different kinds of culture and leadership clusters: Nordic Europe (Sweden), Germanic Europe (the Netherlands), Latin Europe (Italy, Spain) and Anglo (the UK and Australia). It is therefore highly relevant to analyse whether the behaviours of the CI maturity model show similar and convergent patterns across the countries in our sample, or if we can detect important national specifics.

The CI Maturity Model The CI maturity model was developed at the University of Brighton during a ten-year, industry-based research programme. Over 100 organizations participated in experiencesharing research aimed at improving the understanding and practice of CI. A detailed description of the model, as well as how it was developed, can be found in Bessant & Caffyn (1997) and Caffyn (1998). The term ‘continuous improvement’ means a continuous stream of high-involvement, incremental changes in products and processes for enhanced business performance. However, in order to fully exploit the potential of the maturity model, it is important to switch from regarding CI as a binary state to considering how CI emerges in the workplace. In particular, CI must be regarded as a bundle of routines which can help the organization improve what it currently does. Thus, CI can be practised with various levels of impact on business performance. The CI maturity model asserts five different capability levels (Bessant & Caffyn, 1997). 1. Pre-CI. There is no formal CI structure, problem solving is random, and the dominant mode of problem solving is by specialists.

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2. Structured CI. There are formal attempts to create and sustain CI, and a formal problem-solving process is used, supported by basic CI tools. CI is often parallel to operations. 3. Goal-oriented CI. All of stage 2, plus formal deployment of strategic goals and monitoring and measurement of CI against these goals. 4. Proactive/empowered CI. All of stage 3, plus the responsibility for CI is devolved to the problem-solving units. 5. Full CI (The Learning Organization). CI has become a dominant way of life, involving everyone in the organization. Learning is automatically captured and shared. Another important term to define is ‘ability’. The maturity model is made up of six CI abilities (Bessant & Caffyn, 1997). Companies enhance their CI capability by developing these abilities. Each ability is made up of a specific cluster of behaviours which reinforce each other. Developing an ability implies changes in its constituent behaviours. The model is made up of 32 behaviours. Details on each ability and its behaviours are given later in Table 5. In summary, enhanced CI capability results from developed abilities, which are all about changing organizational behaviours.

Convergence or National Specificity? An important source of inspiration in testing the CI maturity model across multiple countries comes from the seminal work of Rungtusanatham et al. (2005). In their effort to test the universality of TQM, they also developed the notion of convergence versus national specificity arguments in operations management, which is briefly summarized here. According to Rungtusanatham et al. (2005) the convergence argument posits that the complexity of modern technology leaves little managerial discretion in terms of structuring work and practices. Consequently, as technology evolves and spreads, organizations would need to structure their operations in similar ways if they are to be efficient and effective. The national specificity argument, in contrast, views technology and its implementation as embedded in the social context of the nation. As such, any organizational practice must, therefore, be adapted to the social context to maximize its effectiveness resulting, in turn, in the observed divergence of practices across nations. Therefore, whereas the convergence argument could explain

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how and why organizations adopting TQM should converge across different cultures, the national specificity argument explains how and why cross-national differences would impede the applicability of TQM within organizations. In contrast to Hofstede (1980), who asserts that management theory and practice are culturally bound, Rungtusanatham et al. (2005) argue that this statement is too strong and too general, particularly in the case of TQM. Their empirical investigation demonstrates that TQM is a comprehensive management paradigm with many definitional elements and relationships that appear to transcend cultural and national boundaries. Results of the 1st International CI Survey also favour the convergence argument. This article has so far only discussed results from the second round of the survey, but important contributions with regard to convergence versus national specificity were also made in the first round. While a less developed and different classification of CI maturity was used in the first round, i.e., Laggards, Late adopters, Early adopters and CI innovators, it was concluded that national specificity had only limited influence on CI practices and performance, whilst CI maturity had a much stronger impact (Gieskes et al., 2000). However, when comparing clusters of countries with similar cultural characteristics, some differences emerged in the way CI was organized. For example, starting with the assumption that the Nordic countries have low power distance between managers and employees led to the finding that these countries actually embarked on a more empowering and participatory style of CI (Martinsuo & Smeds, 2000). On the whole, though, little evidence was found supporting the theory that national culture or infrastructure has a dominant effect on the implementation of CI within industrial firms. The broad differences identified between groups of firms classified by their CI maturity were, however, of great significance (Boer et al., 2000).

Hypotheses With this article we try to add to current research on convergence versus national specificity issues in operations management by testing the validity of the CI maturity model across multiple countries. In line with the study on TQM by Rungtusanatham et al. (2005), as well as the findings of the 1st International CI survey (Boer et al., 2000), we expect that the premises, i.e., definitional elements and theoretical relationships, of the CI © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


maturity model transcend cultural and national boundaries. For example, the CI maturity model consists of six reliable and uni-dimensional CI abilities, as in Table 5 or Bessant and Caffyn (1997, pp. 19–20). CI is practised on five different capability levels, and increases in CI maturity correspond to improved operating performance (Bessant & Caffyn, 1997). We test these assumptions according to the following three sets of hypotheses: H1a The CI maturity model consists of six reliable and valid CI abilities. H1b CI abilities form a similar pattern regardless of national specificity. H2a CI is practised on five different maturity levels. H2b The classification into different CI maturity levels is not dependent on national specificity. H3a Increases in CI maturity, in terms of adoption of CI behaviours, will correspond to improvements in operating performance. H3b Increases in CI maturity will correspond to improvements in operating performance regardless of national specificity.

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Table 1. Participating Countries Country Australia (AU) Italy (IT) Netherlands (NTH) Spain (SP) Sweden (SWE) United Kingdom (UK) Total

N 89 60 51 105 77 70 452

Operationalizing Improved Operating Performance In line with Slack et al. (2006), five different aspects of operating performance were measured: flexibility, quality, dependability, speed and cost. The question in the survey instrument was posed as follows: To what extent has continuous improvement contributed to the following areas of business performance over the last three years? An index/composite measure was created, as shown in Table 2, where details on scale reliability are also given.

Data Collection In order to test the hypotheses we used data from the 2nd International CINet Survey. Data collection was conducted in 2004 and included data from 2003 relating to a whole range of CI-related issues. The survey was developed by an international research consortium, and comprises data from 543 manufacturing companies in 10 countries in Asia, Australia and Europe. However, Norway (N = 14), Ireland (N = 21), Hong Kong (N = 29) and Switzerland (N = 27) provided insufficient sample sizes and have therefore been removed from the analysis. Only countries with more than 50 observations were selected (Table 1).

Operationalizing the CI Maturity Model To measure the level and use of CI behaviours, the respondents were asked to indicate to what extent they agreed or disagreed with 32 formulated statements related to CI activities. The statements are based on the constituent behaviours of Bessant and Caffyn (1997, pp. 19–20) and can be found in Table 5 in this article. All statements were measured on a five-point Likert scale to indicate the degree to which the described behaviours were present in the organization. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

Control Variables Jørgensen, Boer and Timenes Laugen (2006), who previously analysed the same dataset as we do in this study, showed the importance of including contextual control variables: CI importance, company size and production process type. Following their example we assessed: • CI importance according to the responses to the CINet Survey item ‘How would you rate the overall importance of continuous improvement in your business unit? 1 = Not important, 2 = Of minor importance, 3 = Of operational importance, 4 = Of strategic importance, 5 = Vital’. • Company size according to the responses to the item ‘How many employees are there in the company?’ • Production process type according to the item ‘How would you describe the production system for your business unit’s most important product line? 1 = Project, 2 = Job shop, 3 = Batch, 4 = Line, 5 = Continuous’. Since our analysis focused on comparisons across multiple countries, we also had to add a set of control variables that assessed differences between countries. We used dummy

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Table 2. Dependent Variable – Improved Operational Performance Variable Flexibility – improved production volumes Quality – improved quality conformance Dependability – improved delivery reliability Speed – reduced lead times Cost – reduced cost X Eigenvalue = 2.7 (55) (Variance explained) Cronbach’s a = 0.79

Mean

Standard deviation

Factor loading

3.26 3.91 3.47 3.17 3.40 3.44

1.12 0.93 1.08 1.07 1.01 0.77

0.67 0.67 0.79 0.79 0.76

Table 3. Scale Reliability – Cronbach’s a Cronbach’s a

N

A – Getting the CI habit B – Focusing CI C – Spreading the word D – CI on the CI system E – Leading the way F – Building the learning organization

6 5 6 3 5 7

variables following the example in Field (2005, p. 208). Dummy coding is a way of representing groups of observations using only zeros and ones. To do this, we had to create several variables. The number of variables needed is one less than the number of groups we are recoding. In our case we had six countries and therefore five dummy variables were created.

Empirical Results Factor Analysis Results – Testing H1 Exploratory factor analysis with Varimax rotation was used to test Hypothesis 1. Results are given in Tables 3, 4 and 5. Behaviours that constituted a prior ability according to the work of Bessant and Caffyn (1997) were subjected to analysis, first by analysing the whole dataset, and then by analysing each country individually. Overall, this analytical procedure found six reliable and valid CI abilities as hypothesized.

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Total

AU

IT

NTH

SP

SWE

UK

0.83 0.85 0.85 0.78 0.85 0.87

0.79 0.83 0.82 0.77 0.79 0.83

0.83 0.86 0.86 0.80 0.88 0.91

0.83 0.82 0.86 0.71 0.86 0.87

0.89 0.86 0.89 0.85 0.89 0.87

0.77 0.85 0.84 0.75 0.77 0.80

0.80 0.83 0.81 0.72 0.85 0.87

However, this procedure also revealed two interesting findings from a model development point of view. A close comparison between Bessant and Caffyn (1997, pp. 19–20) and Table 5 reveal two major differences and some minor differences. First, all items that concerned the role of managers in CI ability A (Bessant & Caffyn, 1997, p. 19) loaded together on a separate factor when the factor analysis was broken down on a country level. A new CI ability (Leading the way) was therefore created (CI ability E in Table 5) following the example in Bessant, Caffyn and Gallagher (2001). Second, when Cronbach’s a was computed for CI ability E (Walking the talk) in Bessant and Caffyn (1997, p. 20) on a country level, this construct was not found reliable. Two countries scored at the 0.4 level and the remaining four countries around the 0.6 level. As a consequence the original CI ability Walking the talk (Bessant & Caffyn, 1997, p. 20) was replaced with the new CI ability Leading the way as shown in Table 5. The minor differences concerned six items that were phrased differently to Bessant and Caffyn (1997) or not © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


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Table 4. Scale Validity – First Eigenvalues and Percent of Variance Explained First eigenvalue (% variance)

A – Getting the CI habit B – Focusing CI C – Spreading the word D – CI on the CI system E – Leading the way F – Building the learning organization

Total

AU

IT

NTH

SP

SWE

UK

3.3 (55) 3.1 (62) 3.5 (58) 2.1 (70) 3.2 (65) 3.9 (56)

3.1 (51) 3.0 (59) 3.2 (53) 2.1 (69) 2.9 (57) 3.5 (49)

3.3 (55) 3.2 (64) 3.5 (59) 2.2 (72) 3.6 (72) 4.5 (64)

3.2 (53) 2.9 (59) 3.6 (59) 1.9 (64) 3.2 (65) 3.9 (56)

3.8 (64) 3.2 (63) 3.9 (64) 2.3 (77) 3.5 (70) 4.0 (57)

3.0 (50)* 3.1 (61) 3.3 (56) 2.0 (67) 2.8 (57) 3.4 (49)

3.2 (53) 3.0 (60) 3.0 (51) 2.0 (67) 3.3 (66) 4.0 (57)

Note: * Second eigenvalue = 1.16 (19).

present in the survey instrument and as a consequence omitted from data analysis.1 1

The term ‘organization’ was used rather than ‘managers’ as in Bessant & Caffyn (1997, p. 19) for the item The organization recognizes in formal but not necessarily financial ways the contribution of employees to continuous improvement in CI ability E (Leading the way) in Table 5. Four items from CI ability D in Bessant & Caffyn (1997, p. 20) were omitted: 1. The CI system is continually monitored and developed. A designated individual or group monitors the CI system and measures the incidence (i.e., frequency and location) of CI activity and the results of CI activity. 2. There is a cyclical planning process whereby the CI system is regularly reviewed and, if necessary, amended (single-loop learning). 3. The individual/group responsible for designing the CI system designs it to fit within the current structure and infrastructure. 4. Individuals with responsibility for particular company processes/systems hold regular reviews to assess whether these processes/systems and the CI system remain compatible. The item The ‘management style’ reflects commitment to CI values in CI ability E in Bessant and Caffyn (1997, p. 20) was phrased Managers at all levels display leadership and active commitment to ongoing improvement in the instrument and can now be found as the last behaviour of CI ability E (Leading the way) in Table 5. The item When something goes wrong the natural reaction of people at all levels is to look for reasons why rather than to blame the individual(s) involved in CI ability E in Bessant and Caffyn (1997, p. 20) has been redirected as the last item of CI ability A (Getting the CI habit) in Table 5. The item People at all levels demonstrate a shared belief in the value of small steps and that everyone can contribute, by themselves being actively involved in making and recognizing incremental improvements from CI ability E in Bessant and Caffyn (1997, p. 20) was omitted.


Reliability assessment was performed by computing Cronbach’s a for each CI ability, for the total dataset as well as by each country. Cronbach’s a is a reliability estimate for measurement scales, with 0.60 being the suggested lower bound value (Nunnally, 1967). A multiple-item measurement scale, whose Cronbach’s a is less than 0.60, would therefore not be regarded as reliable. Table 3 shows the result of the performed analysis. The six CI abilities appear to be reliable (0.71 ⱕ Cronbach’s a ⱕ 0.91). Validity assessment was performed by examining the dimensionality of each CI ability, for the total dataset as well as by each country. According to Rungtusanatham et al. (2005), demonstrating that a multiple-item measurement scale is uni-dimensional is one type of evidence indicative of construct validity. In the context of factor analysis, a measurement scale is uni-dimensional when the second eigenvalue is less than 1.00 and when factor loadings for constituent measurement items are greater than 0.30. Table 4 shows first eigenvalues as well as the percent of variance explained by the derived factors. The six CI abilities appear to be valid (only one factor was derived when constituent behaviours were subjected to analysis). There is one exception regarding CI ability A (Getting the CI habit) for the Swedish dataset. The item Ideas and suggestions for improvement are responded to in a clearly defined and timely fashion – either implemented or otherwise dealt with loaded on a second factor. A mistake seems to be the reason for this deviation. When the instrument was translated into Swedish, the word ‘suggestion system’ was mistakenly used. A retrospective back translation would read Ideas and suggestions are responded to by a well structured and time effective suggestion system. Using the term ‘suggestion

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Focusing CI

B

Generating and sustaining the ability to link CI activities to the strategic goals of the company

Getting the CI habit Developing the ability to generate sustained involvement in CI

A

Organizational ability

Individuals and groups use the organization’s strategy and objectives to focus and prioritize their improvement activities Everyone understands what the company’s or their department’s strategy, goals and objectives are Before embarking on initial investigation and before implementing a solution, individuals and groups assess the improvements they proposed against strategic objectives to ensure consistency Individuals and groups monitor/measure the results of their improvement activity and their impact on strategic or departmental objectives Improvement is an integral part of the individuals’ or groups’ work, not a parallel activity

People make use of some formal problem finding and solving cycle People use appropriate tools and techniques to support their improvement activities People use measurement to shape the improvement process People (individuals/groups) initiate, and carry through to completion, improvement activities – they participate in the process Ideas and suggestions for improvement are responded to in a clearly defined and timely fashion – either implemented or otherwise dealt with When something goes wrong the natural reaction of people at all levels is to look for reasons why rather than to blame the individual(s) involved

Constituent behaviours

Table 5. Factor Scores for CI Abilities and Constituent Behaviours (Based on Bessant & Caffyn, 1997)

0.772 0.728

0.440

0.673

0.762 0.784

0.650

0.644

0.776 0.770

0.808

0.724

0.750 0.773

0.835

0.756

0.764

0.852

0.846

0.804

0.743

AU

0.761

Total

0.772

0.853

0.824

0.693

0.854

0.563

0.747

0.610 0.869

0.874

0.750

IT

0.680

0.862

0.806

0.744

0.723

0.652

0.721

0.734 0.702

0.780

0.783

NTH

SWE

UK

0.796 0.747 0.771

0.834 0.788 0.840

0.714 0.761 0.789

0.782 0.782 0.685

0.845 0.833 0.780

0.761 0.713 0.440

0.805 0.110* 0.719

0.780 0.805 0.791 0.825 0.755 0.774

0.842 0.769 0.919

0.784 0.828 0.653

SP

354 CREATIVITY AND INNOVATION MANAGEMENT



E

D

C

Generating the ability to lead, direct and support the creation of and sustaining of CI behaviours

Leading the way

Generating the ability to manage strategically the development of CI

CI on the CI system

Generating the ability to move CI activity across organizational boundaries

Spreading the word

Individuals and groups are effectively working across internal (vertical and lateral) and external divisions at all levels People understand and feel ownership of the company’s processes People are oriented towards internal and external customers in their improvement activity Specific improvement projects are taking place with customers and/or suppliers Relevant improvement activities involve representatives from different operational levels The organization uses supplier and customer feedback as a means to improve company performance Ongoing assessment ensures that the organization’s processes, structure and systems consistently support and reinforce improvement activities Senior management make available sufficient resources (time, money, personnel) to support the continuing development of the company’s improvement system When a major organizational change is planned, its potential impact on the organization’s improvement system is assessed and adjustments are made as necessary Managers support improvement processes by allocating sufficient time, money, space and other resources The organization recognizes in formal but not necessarily financial ways the contribution of employees to continuous improvement Managers lead by example, becoming actively involved in the design and implementation of systematic ongoing improvement Managers support experimentation by not punishing mistakes, but by encouraging learning from them Managers at all levels display leadership and active commitment to ongoing improvement 0.761

0.809

0.844

0.877

0.881

0.882

0.485

0.752 0.596

0.822

0.828

0.834

0.748

0.747

0.807

0.752

0.797

0.820

0.775

0.753

0.864

0.779

0.809

0.854

0.714

0.599

0.744

0.714

0.928

0.821

0.921

0.655

0.882

0.850

0.879

0.809

0.764

0.811

0.794

0.766

0.787

0.677

0.856

0.733

0.857

0.805

0.766

0.767

0.776

0.847

0.761

0.877

0.689

0.827

0.798

0.651

0.924 0.837 0.874

0.826 0.835 0.863

0.877 0.870 0.897

0.668 0.334 0.477

0.858 0.760 0.868

0.905 0.841 0.736

0.855 0.755 0.832

0.864 0.855 0.877

0.781 0.704 0.688

0.829 0.727 0.737

0.770 0.759 0.672

0.834 0.839 0.739

0.782 0.690 0.696

0.809 0.743 0.733

CONVERGENCE OR NATIONAL SPECIFICITY? 355

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Generating the ability to learn through CI activity

Building the learning organization

Everyone learns from their experiences, both good and bad Individuals seek out opportunities for learning/personal development (e.g., active experimentation, setting own learning objectives) Individuals and groups at all levels share (make available) their learning from all work and improvement experiences The organization articulates and consolidates (captures and shares) the learning of individuals and groups Managers accept and, where necessary, act on all the learning that takes place People and teams ensure that their learning is incorporated into the organization by making use of the mechanisms provided for that Appropriate organizational mechanisms are used to deploy what has been learned across the organization

Constituent behaviours

Note: * Loading on this item on the second factor 0.940.

F

Organizational ability

Table 5. continued

0.756

0.704

0.744

0.777

0.738

0.746

0.788

0.819

0.621

0.669 0.629

AU

0.775

0.659 0.697

Total

0.812

0.896

0.851

0.804

0.837

0.572 0.778

IT

0.789

0.789

0.696

0.786

0.824

0.669 0.651

NTH

SWE

UK

0.620 0.562 0.716

0.833 0.826 0.806

0.813 0.692 0.807

0.800 0.773 0.813

0.783 0.739 0.782

0.665 0.691 0.625 0.749 0.560 0.693

SP

356 CREATIVITY AND INNOVATION MANAGEMENT



357

divide the sample of the 1st International CI Survey into four different groups of CI maturity: Laggards, Late adopters, Early adopters and CI innovators. Furthermore, the groups in Gieskes et al. (2000) are similar to the clusters of CI maturity identified in our analysis, in the sense that they also show evidence of a linear progression in maturity across the six CI abilities. In summary, we find partial support for Hypothesis 1a. There are a certain number of distinct maturity levels. The exact number, though, is still an open question. In order to test whether CI maturity is dependent on national specificity, clusters and countries were cross-tabulated as shown in Table 7. Results are in favour of the convergence hypothesis, even though some minor differences between countries exist. All countries are represented across all clusters in a relatively similar fashion, except for Cluster 4. While Spain is overrepresented, Australia, the Netherlands and Sweden have fewer observations in this cluster than expected. Rather than suggesting that Spanish business culture facilitates higher CI maturity levels, we speculate that the identified differences for Cluster 4 are caused by differences in sampling techniques. The Spanish sample was drawn from various public and private databases, which collected a population of firms already interested in the practice of quality procedures (Albors & Hervás, 2007, p. 335), while the Swedish survey, for example, targeted a representative sample of the Swedish manufacturing sector (Dabhilkar & Bengtsson, 2007, p. 278).

system’ may have led Swedish respondents to think about the old-fashioned suggestion box. We speculate that if this item was properly translated in the first place, all constituent behaviours of this CI ability for the Swedish dataset would load on the same factor. Table 5 shows factor loadings for the behaviours constituting each CI ability. The six CI abilities also appear to be valid from a factorloading point of view (factor loadings > 0.30). As outlined above, Sweden naturally deviates regarding CI ability A (Getting the CI habit). Based on the same line of reasoning, this is not considered problematic.

Cluster Analysis Results – Testing H2 The TwoStep cluster analysis function of SPSS was used to test Hypothesis 2. It is an exploratory tool designed to reveal natural groupings (or clusters) within a dataset. By comparing the values of a model-choice criterion across different clustering solutions, the procedure automatically determines the optimal number of clusters. Overall, results partly support Hypothesis 2 and are shown in Table 6. While five clusters was the number hypothesized, in line with Bessant and Caffyn (1997, p. 18), Table 6 shows that there are four unique clusters of observations with respect to CI maturity in the dataset. Mean values are shown in Table 6. Post hoc analyses (ANOVA, Tamahane’s T2) also show that the differences in mean values across all four clusters are significantly different for every CI ability A–F (p < 0.001). It is interesting to note that, working manually rather than using statistical software, Gieskes et al. (2000) also found it useful to

Regression Results – Testing H3 Hypothesis 3 was tested using hierarchical regression analysis, with blocks of variables

Table 6. Results of Cluster Analysis Mean value (standard deviation)

A – Getting the CI habit** B – Focusing CI** C – Spreading the word** D – CI on the CI system** E – Leading the way** F – Building the learning organization** N

Cluster 1

Cluster 2

Cluster 3

Cluster 4

2.1 (0.5) 2.2 (0.5) 2.4 (0.5) 1.8 (0.6) 2.1 (0.5) 2.2 (0.5)

2.9 (0.3) 3.1 (0.5) 3.3 (0.4) 2.9 (0.5) 3.0 (0.5) 3.0 (0.3)

3.7 (0.3) 3.8 (0.4) 3.9 (0.4) 3.6 (0.4) 3.7 (0.4) 3.6 (0.3)

4.3 (0.4) 4.4 (0.4) 4.5 (0.3) 4.3 (0.4) 4.4 (0.4) 4.3 (0.4)

55

113

91

123

Total 3.4 (0.8) 3.5 (0.8) 3.7 (0.8) 3.3 (0.9) 3.4 (0.9) 3.4 (0.7) 382

Note: ** Differences in mean values across all four clusters are significantly different (p < 0.001). © 2007 The Authors Journal compilation © 2007 Blackwell Publishing

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Table 7. Cross-Tabulations for Clusters of CI Maturity by Country

Cluster 1 Cluster 2 Cluster 3 Cluster 4 Total

Count Expected Count Expected Count Expected Count Expected Count Expected

count count count count count

AU

IT

NTH

SP

SWE

UK

Total

7 12 25 24 34 26 15 19 81 81

10 8 14 16 15 17 14 13 53 53

8 6 17 13 14 14 4 10 43 43

13 15 20 31 32 34 40 25 105 105

14 9 27 19 16 21 7 15 64 64

3 5 10 11 12 12 11 9 36 36

55 55 113 113 123 123 91 91 382 382

entered sequentially. This approach facilitates the opportunity to control for the influence of contextual variables. As mentioned earlier, previous research has shown it important to control for CI importance, company size and production process type (Jørgensen, Boer & Timenes Laugen, 2006), and due to the nature of this study, we also have to control for the possible influence of national differences. Furthermore, outliers were detected. Five percent of the sample, that is 27 of 452 observations, had standardized residuals greater than 2 and were consequently removed from the analysis as suggested in Hair et al. (1998). Influential observations were also searched for but not found. According to Field (2005), Cook’s distance values > 1 and Mahalanobis distances > 25 are causes for concern. Finally, we checked for multicollinearity as suggested in Hair et al. (1998). This led us to create the CI maturity index used in the regression analysis shown in Table 8. The original plan was to enter the six CI abilities shown in Tables 3, 4 and 5 in a set. However, the six CI ability variables were found to be highly correlated. Therefore, a CI maturity index variable was created instead, where all 32 CI behaviours that constitute the six CI abilities were averaged. Overall, results of the regression analysis support Hypothesis 3 and are shown in Table 8. That is, organizations can expect improved operating performance in response to adoption of CI behaviours, regardless of national specificity. Standardized b-coefficients are reported along with summary statistics. Two-tailed t-tests were applied to the b-coefficients of the predictor variables. Models 1, 2 and 3 present the hierarchical addition of sets of items addressing contextual variables and CI maturity. Model 1 indicates

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that the first set of contextual variables explains 12% of the observed variance in improved operating performance. The model is statistically significant (p < 0.001). Analysing the standardized b-coefficients shows that, while ‘CI importance’ and ‘Production process type’ have a statistically significant impact, ‘Company size’ does not. This means that the contribution of CI to improved operational importance is dependent on how the overall importance of CI is rated in the organization. It also suggests that CI undertaken in production systems towards the ‘continuous’ type of the continuum, contrary to the ‘project’ type, contributes to a higher extent to improved operating performance. ‘Company size’ does not matter for the contribution of CI to improved operating performance. The addition of dummy variables, representing differences between countries, in Model 2 does not bring the amount of explained variance towards higher levels (Adj R2 = 12%; p-value of F statistic = 0.70). Addition of the CI maturity index in Model 3 brings the explained variance up to 33%. The increase in explained variance is highly significant (p < 0.001), as is the overall regression model (p < 0.001). While the first set of contextual variables follows the same pattern as in Model 1 and Model 2, the second set of contextual variables comes to life in Model 3. With regard to differences between countries, a similar pattern emerges in Model 3 as in Table 7, where clusters of CI maturity are cross-tabulated by country. The regression results indicate significant differences in operating performance, when Spain is compared to Australia, the Netherlands and Sweden, and as CI maturity is taken into consideration. This was expected since Spain has a greater number of observations with high CI maturity (Table 7). More important, however, is to © 2007 The Authors Journal compilation © 2007 Blackwell Publishing


359

Table 8. Results of Multiple Regression Analysis Standardized b-coefficients

Step 1 CI importance Company size Production process type Step 2 SP vs AU SP vs IT SP vs NTH SP vs SWE SP vs UK Step 3 CI maturity index (CI behaviours/abilities A-F) R2 Adjusted R2 p-value of F statistic p-value of overall model

Model 1

Model 2

Model 3

0.33** 0.03 0.10*

0.33** 0.02 0.10*

0.16** -0.01 0.10*

0.13 0.12

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