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Editorial
T
his issue again contains a good variety of contributions in the field of creativity and innovation management. The breadth of this field is illustrated not only in the contents of the various issues of this Journal, but can also be seen in the International Handbook on Innovation, edited by Larisa V. Shavinina (2003, Pergamon, 1171 pages). At the end of this issue you will find a review of this handbook, of which several authors belong to the ‘Creativity and Innovation Management Community’, in that some are members of the board of associate editors and/or have contributed to the Journal in the past years. The concluding chapter is written by the founding editor Tudor Rickards. The author of the book review, Dries Faems, indicates amongst other things that selecting ‘creative environments’ instead of ‘creative persons’ as a unit of analysis seems to be a promising research strategy to study the nature of individual innovations. This emphasis on the relevance and influence of a creative environment or context can be seen as the central idea or leitmotiv of this issue. The psychological context in terms of trust, as well as the physical context of creativity, enhancement of group creativity, the enablers for learning behavior in innovation processes, and the importance of strategy and network stakeholders are addressed in the five contributions. Marko Kohtamäki, Tauno Kekäle and Riitta Viitala open this issue with a study on the role and nature of trust in the process of new business creation. Based on an extensive literature overview they develop a framework as was used in their exploration of a concrete business creation process. This framework comprises a lifecycle model of the business creation process as well as a characterization of trust in terms of its dimensions and components. For the empirical section the authors choose a single case study design. The high-tech case company has developed within a period of ten years into a multinational with about 400 employees. As one of their conclusions the authors find that, according to their theoretical proposition, the objects of trust change systematically across the different stages of the new business creation process. In the second article Tore Kristensen focusses our attention on the physical content © Blackwell Publishing Ltd, 2004. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
of creativity. What is the relation between creative processes and spatial dimensions? With respect to the creative processes, four sub-processes are distinguished (value creation, scaffolding, imagination and materialisation) along with four stages (preparation, incubation, insight and elaboration and evaluation). Just like the first contribution, the empirical part of this article is limited to a single case study. There is some evidence, conceptually as well as empirically, that there are differences in the spatial requirements between the stages. One of the author’s conclusions is that the preparation and the elaboration stages typically require a combination of communal and private space. Next, Hans Björkman describes the socalled Design Dialogue Groups as a source of innovation. This methodology aims for enhancement of creativity and organizational learning. Björkman developed and applied Design Dialogue Groups at Sif, the Swedish national trade union for white collar workers, where he himself holds the position of service developer. The Design Dialogue Groups have been used in a wide variety of purposes such as the development of national negotiation rounds and the development of a virtual community platform for members. In order to carefully design the dialogue groups and the group creativity processes, several design principles in the areas of domain-relevant skills, creativity related processes and task motivation are proposed. José Gieskes and Beatrice van der Heijden in their contribution report an interesting exploratory study where the authors use some quantitative techniques creatively (a discussion on allowed use might be appropriate) to provide new insights in the learning behaviour in new product development processes. The data and findings are based on an extensive research project referred to by the acronym CIMA (Continuous Improvement in global product innovation MAnagement), which involved 140 product innovation projects in 70 companies from 6 different countries. Although the core of the research is aimed at the psychometric qualities of the instrument, the conclusions of this study seem to be relevant for theory as well as for
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management practices. An example of this is the conclusion that enablers like the process definition, HRM policies and project planning and control appear to be effective in stimulating learning behaviour. Creativity and innovation performance measures seem to have become an area of ongoing interest and importance. Just like this year’s first issue, we end this issue with a contribution in this particular field. Rodney McAdam and William Keogh address the transition towards creativity and innovation measurement in small and medium sized enterprises, reporting from eight case studies. The specific research question dealt with was: ‘How can small and medium sized enterprises longitudinally transition from traditional performance measures to include measures of creativity and innovation, as a stimulant for increased competitiveness, based on a programme of critical action learning interventions?’ Findings were structured cross-mapping key-measurement principles with the process elements of creativity and innovation. The conclusions highlight the need to link measures to strategy, where the largest issue was senior management’s acceptance of employees’ ability to generate new knowledge in communities of practice and networks, to involve stakeholders in selecting measures, and to review measures dynamically. The need is apparent to adopt a wide or eclectic range of measures, reflecting the diversity within creativity and innovation.
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The book review of the International Handbook of Innovation concludes this issue. This will be the first, we hope, of a new series of book reviews and discussions. Looking forward to the next issue, we can already tell you that this will contain a selection of contributions by amongst others Geir Kaufmann and Robert Sternberg, two of our associate editors, from a Summer University Workshop on Creativity in the workplace coordinated by Todd Lubart. This second issue of 2004 will be with you in June, the second of two months featuring many interesting conferences for all of us. Some of these conferences are mentioned on the Journal’s website. The Creative Problem Solving Institute celebrates its 50th anniversary with a conference in June (www.cpsiconference.com), and we would also like to draw your specific attention again to the R&D Management Conference in Sesimbra (near Lisbon), Portugal, themed Managing People and Managing R&D. We cooperate regularly with the R&D Management conferences and Journal, and this year’s conference theme is in our opinion specifically relevant for our readers. More cooperation is foreseen in one of the next conferences on Creativity and Innovation in R&D in Taiwan, (organised by Jon Chao Hong, who published in this Journal recently on the concept of Chi) which we will inform you about through our website and these pages. Olaf Fisscher and Petra de Weerd-Nederhof March 2004
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Trust and Innovation: from Spin-Off Idea to Stock Exchange Marko Kohtamäki, Tauno Kekäle and Riitta Viitala Trust among entrepreneurs, their co-workers and between the entrepreneurs and their business partners plays a key role in the early stages of formation of a new company. In this piece of research, trust is defined as a belief consisting of eight trusting beliefs, emphasising the rational consideration between these beliefs and other situational factors. The concept of trust is developed through objects, mechanisms and antecedents. The present paper is an empirical exploration of these phenomena in the context of innovativeness in a high-tech company. The goal is to describe the role, content and impact of trust at the different stages of a business evolution process.
Introduction
T
he important processes of creating and benefiting from new innovations invariably take place in small and medium-sized firms. In Schumpeter’s (1934) terms, competition in capitalist economies consists of entrepreneurs using innovation to enter established markets. Entrepreneurial effort always includes a risk of failure. As many empirical studies have revealed, the risk of failure often materialises during the first years of a firm’s life cycle (e.g. Massel, 1978; Olofsson, Petterson & Wahlbin, 1986; Preisendörfer & Voss, 1990). On the other hand, what Schumpeter calls a process of creative destruction may occur. The main force behind that process is the entrepreneurial innovations of the actors (Vesalainen, 1995). In this paper our aim is to find a deeper understanding of the role and nature of trust in the process of new business creation. The very early stages of new business creation in particular demand learning and new knowledge creation processes from the actors. We chose to investigate a new-business creation process as a manifestation of an innovation process for two good reasons. First, new business creation has not yet been investigated from the point of view of trust. Since it is widely accepted that new business creation is a distinctive, complicated and risky process, there is considerable scope for investigating associated issues of trust. Second, a group of © Blackwell Publishing Ltd, 2004. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
people will, in most cases, establish a business without any assistance from other organizations, contributing to the fact that in its early stages a new firm is especially vulnerable (Chowdhurry, 2002). Trust, it is argued, should therefore play a perceivable role throughout this period. In literature, one often utilized approach is to separate the firm (or the organization) from individuals (Ylinenpää, 1999). We contend that the role of individuals in developing new innovations and creating new businesses is crucial and should more often be investigated in conjunction with processes and systems.
Innovativeness and New Business Creation In many ways, innovativeness is an essential precondition for new business creation. The connection between innovativeness and new business creation has been categorised into four different groups, in which the type of innovativeness as the basis of new business creation varies (Pihkala & Vesalainen, 1999). The first group includes new business creation where new innovations form the basis. These innovations are usually technology-based and are often created as a result of basic research. In this group, the creation of new innovations at the domestic or global level represents the core of the new business. The second group comprises new business creation that benefits
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from the innovations created in the first group. Innovativeness in this group refers to the ability to use market information in a new way and assumes prior experience in the relevant technology, field and markets. The third group consists of new business creation where innovations are associated with rationalising business created before. In this group a new business may, for example, be based only partially on a new business concept. Its innovativeness is therefore often local. The fourth group consists of new business creation where innovativeness is connected to the discovery of new ways to benefit from resources that have been left unused or under-utilized in other businesses. For example, this might include a firm’s resources left over in a bankruptcy which can subsequently be capitalized on in a new way. One of a number of approaches to new venture creation is the stage approach. Ardichvili, Cardozo, Harmon, Reynolds and Williams (1998) divide stage approaches into two categories. The first includes organization development models, which concentrate on phases leading to organization development (Bird, 1992; Hansen & Allen, 1992; Mitchell, Smith, Seawright, and Morse, 2000). The second category includes life-cycle models, which usually concentrate on the phases from the organisation’s initiation to its decline (Churchill & Lewis, 1983; Greiner, 1967, 1972; Kazanjian, 1988; Miller & Friesen, 1984; Scott & Bruce, 1987; Swayne and Tucker, 1973; Timmons, 1981; Webster, 1976). The life-cycle model provides a framework for studying the sequential patterns of emergence, growth, maturity, decline and death in organizations. It is argued that all organizations go through this kind of relatively predictable pattern of stages during their life cycles (Greiner, 1972), and where the subsequent stage is prefigured in the present stage (Van de Ven, 1995). Each stage has its specific features, which are expressed by labelling the stages with descriptive names in evolutionary models. As a pioneer, Greiner (1972) named the phases in an organisation’s growth such as (1) Creativity; (2) Direction; (3) Delegation; (4) Evolution; and (5) Revolution. Quinn and Cameron introduced a model of four stages: an entrepreneurial stage (early innovation, niche formation, creativity), a collectivity stage (high cohesion, commitment), a formalization and control stage (stability and institutionalization) and an elaboration of structure stage (domain expansion and decentralization). Swayne and Tucker (1973) have viewed the entrepreneurial process as consisting of conceptualizing, planning and action. Scott and Bruce (1987) have indicated that the new
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venture creation process involves the following phases: initiation, survival, growth, expanding and maturity. Researchers have focused on the relationship between stages and a host of organizational variables such as the criteria used in evaluating effectiveness (Quinn & Cameron, 1983), the priorities of top management (Smith, Mitchell & Summer, 1985), dominant problems (Kazanjian, 1988), human resource practices (Milliman, Von Glinow & Nathan, 1991), the role of stakeholders at each stage (Jawahar & McLaughlin, 2001) and board composition (Lynall, Golden & Hillman, 2003). One of the most supported findings is that resource needs, sophistication and managerial capabilities vary throughout the different stages of the life cycle (Jawahar & McLaughlin, 2001). A discussion about each of the stages often leaves the impression that the model is composed of separate stages. In fact, the stages are not disparate. Rather, they are sequentially linked and mutually reinforcing. Klofsten (1992) defined eight firm-level cornerstones that determine a firm’s early development process: business idea, the product, the market, the organization, core group expertise, core group drive/motivation, customer relations and other relations. The magnitude of these elements varies at different stages. Another critique is centred on the lack of consideration for social processes in the approach (Puhakka, 2002), which based on the latest literature is wrong to ignore (Sigrist, 1999). Until now, trust has unjustifiably received insufficient attention in the literature on new business creation (Larson, 1991).
Greiner’s Stage Model In this paper, Greiner’s (1967, 1972, 1998) lifecycle model is adopted to provide a framework for studying the nature and role of trust in the early stages of new business creation. We first sum up the main features of the model. At the stage of creativity, the first tasks to be carried out are those of creating a service or a product and surviving in the domain of the operations chosen. At this stage, entrepreneurs seek to achieve a survival threshold (see also Quinn & Cameron, 1983). They work long days, carry out most of the jobs in the organization and set its climate and culture. The dominant concern here is entering the marketplace (see also Jawahar and McLaughlin, 2001). There is little evidence of co-ordination and planning (see also Lynall, Golden and Hillman, 2003) and communication among
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employees is informal and frequent. The pressing need at this stage comes from the increased number of employees in the organization, since they require managerial direction and the organization needs someone to handle the general issues of management (Greiner, 1972). At the direction stage, the organization begins to ‘take shape’. Departments and functions begin to be defined and the division of labour is the dominant theme. The culture may still largely be one of the collective and individuals are likely to feel committed to the organization and to the goals of its managers (also Quinn and Cameron, 1983). At this stage, long hours of work are still only rewarded with modest salaries and the promise of ownership benefits. As the organization continues to grow and to carve out its strategic niche with more precision, the need for management control and delegation arises. Communication also becomes more formal and impersonal. Strong leaders still want to lead (Greiner, 1972). The delegation stage refers to when the implementation of both control and information/communication systems takes place. Communication and control become more formal. An explicit division is made between the tasks of top management – making strategic decisions and implementing policy – and those of the lower-level managers, charged with carrying out and overseeing operational decisions (see also Jawahar and McLaughlin, 2001). Stabilization of production, product reliability and maintaining cash flow are the other central concerns at this stage. The organization continues to grow, but more slowly. Structurally, it begins to resemble a bureaucracy with pronounced functional specialization and differentiation. The retention of key staff is important here. They are likely to leave the organization if they feel hemmed in or not able to influence or to participate in wider organizational goals (Greiner, 1972). At the co-ordination stage, the problems of overformalization are addressed and solutions sought. The organization may have begun to ‘plateau’ in terms of growth and performance and may even show the first stages of decline. Managers used to handling bureaucratic structures and processes usually have to learn new skills. New co-ordination systems prove useful for achieving growth through a more efficient allocation of a company’s limited resources. According to Jawahar and McLaughlin (2001) this stage is accompanied by strong cash flows and fewer attractive investment opportunities, which in turn leads to decisions focused on expansion within the chosen domain and new strategies emphasizing productivity enhancement. A lack of confidence may gradually build between line and
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staff, and between headquarters and the staff. The collaboration stage emphasizes action through teams and the skilful confrontation of interpersonal differences. Teams are combined across functions to handle specific tasks. Emergence of a matrix-type structure, team action, educational programs and real-time information systems are typical at this stage. Formal control systems are simplified and combined into single multi-purpose systems. This stage of renewal can occur as early as after 10 years of operation, but usually takes around 15 to 20 years, during which time a number of other ‘cures’ may also have taken place, such as the rapid turnover and replacement of senior managers. We study the role, nature and the components of trust at the early stages of a new company. According to Greiner (1972), there is a connection between the stage of evolution and the type of crisis. We are therefore eager to see if there are any signs of different types of trust crises present at the different evolutionary stages.
Trust in New Business Development Trust is a phenomenon that has attracted interest in very different research settings and has been applied when exploring various research themes such as individual dyadic relations (Butler & Cantrell, 1984); group relations (Järvenpää, Knoll & Leidner, 1998); organizations, dyadic relationships between organizations (Blomqvist, 2002); and network relations between individuals and organizations, as well as in societies (Fukuyama, 1995). In psychology, especially in the earlier research, the object has typically been the individual and his/her propensity to trust, often by using different game settings (Loomis, 1959; Solomon, 1960). Conceptualizations and typologies of trust have also varied significantly in the literature (Fukuyama, 1995; Kohtamäki, 2003a; Luhmann, 1988). According to the implicit ontological basis of the phenomenon, the various definitions of trust can be divided into three broad categories (Gustafsson, 2003). In the first category, trust is defined as an irrational feeling, belief or attitude. The researchers that adopt this view emphasize the affective element of trust as opposed to the elements that are cognitive or rational (Kramer, Brewer & Hanna, 1996). In this view, trust is a hunch or a feeling. In the second category, trust is considered as a rational expectation. Rotter (1967; see also Coleman, 1990) defined trust as ‘an expectancy held by an individual or a group that the word, promise, verbal or written
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statement of another individual or group can be relied upon’. Luhmann (1988, p. 102) drew further distinctions between the two concepts of confidence and trust. He defined that when the individual trusts, he evaluates the risk and when the individual is confident, he neither considers alternatives, nor sees the risk (Luhmann, 1988, p. 102). The third category is defined, according to Baier (1986; see also Gustafsson, 2003 about the interpretation), as a rational belief, somewhere in between the previous two views of trust. It combines the different elements of cognition, which refers to rational consideration, feeling and propensity (Fishbein & Middlestadt, 1995). In this work, trust is defined as ‘the trustor’s trusting belief to the trustee, in a situation that entails a rational consideration of the opportunities, risks and vulnerability’ (Kohtamäki, 2003b). Trust is the belief of an individual, even if manifested through interaction with one’s organization. The trustor’s trusting belief combines the feeling and cognitive rationalizing. The consideration of situational factors is also included in the definition. The discussions about trust in the literature are very diverse and vague in nature. Researchers discuss different dimensions of trust, often neglecting to address their imbalances. Nevertheless, the earlier research provides a sound basis from which to categorize the dimensions of trust. This is developed according to the work of Adler (2001), who divided the dimensions into four: sources, mechanisms, objects and bases. Here, however, the division of trust has been further developed into more simplified form and adopts only three dimensions: (1) objects; (2) mechanisms and (3) antecedents. First, trust can be directed towards an individual, community, institution or systems. This means that the trustor, whether it is an individual or an organization, can have trust in an individual, in a community (meaning a group or an organization), in an institution or in structures and systems. All the objects are to some degree studied in different scientific fields. Second, the mechanisms of trust can be divided into propensity, reputation, calculation, knowledge and identification. The trustors have different propensities to trust, meaning that some trust more blindly than others. Trust can also be created through a third-party opinion about the trustee. For example, Lewicki and Bunker (1996) have suggested that trust can be developed through calculating one’s own self–interest. Additionally, trust is suggested to develop through positive knowledge about the trustee. As the
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Table 1. The Different Dimensions and Components of Trust Dimensions Objects
Mechanisms
Antecedents
Components • • • • • • • • • • • • • • • • •
Individual Community Institution System Propensity Reputation Calculation Knowledge Identification Predictability Capability Integrity Benevolence Honesty Deterrence Community Reciprocity
Source: Developed after Adler, 2001.
trustor learns about the trustee’s attitudes, beliefs and behaviour, it is likely that this positive knowledge enhances trust. Lewicki and Bunker (1996), among others, have argued that identification towards the same mission and values also results in a strong trusting belief. Third, the antecedents of trust – or trusting beliefs – are argued to be an important dimension of trust. In this dimension, eight components are identified as derived from the earlier literature (Kohtamäki, 2003b). The main assumption here is that the trusting belief is developed through eight trusting subbeliefs: predictability, capability, integrity, honesty, benevolence, deterrence, community and reciprocity (Sako, 1992; Selnes, 1998; Shapiro, Sheppard & Cheraskin, 1992; Swan & Trawick, 1987). This implies that the trustee should behave predictably, be able to deliver what is expected, keep his word, speak what is true and act helpfully if needed (Cummings & Bromiley, 1996). The deterrence belief refers to the situation where the trustee’s clear threat of reputation loss can increase the trustor’s trust. It is also suggested that the feeling of community develops trust (Fukuyama, 1995; Lewicki & Bunker, 1996). Shared mission, vision, goals, values and rules are further considered instrumental in developing a strong trusting belief. The last trusting sub-belief is that of the reciprocity belief, which implies that a favour to the trustee
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develops an expectation of reciprocity. (Coleman, 1990; Kramer, 1991; Mayer, Davis & Schoorman, 1995; McKnight, Cummings & Chervany, 1998; Mitronen, 2002; Ouchi, 1980; Swan, Trawick & Silva 1985; Zaheer, McEvily & Perrone, 1998). In this study, where the research object is trust and the unit of analysis is the company, we focus our research on the meaning of trust in new business creation. In this way, the trustor is represented by each individual entrepreneur, whereas the trustees are represented by the individual fellow entrepreneurs, the community of entrepreneurs, systems and the institution. Within these constructs we analyse the mechanisms and antecedents of trust. The dimensions of trust outlined above provided the basis of analysis. Our theoretical propositions are: 1. There is variance in objects of trust at different stages of new business creation. 2. There is variance in mechanisms of trust at different stages of new business creation. 3. There is variance in antecedents of trust at different stages of new business creation. 4. The variance specified above is distinctive enough to be sensed in similar ways by different people in the same community.
Methodology There is no wholly satisfactory research protocol for identifying what trust is. We chose a single case study (Yin, 1991, pp. 46–51) as our research strategy in order to explore and describe the nature of trust in a process of new business creation. The case company here represents a critical case meeting all the conditions for testing the propositions in the frame of stage model (Yin, 1991, p. 47). Since we wanted to understand the interpretations of the actors in a natural setting, we chose to use interviews as a research method. On the basis of the interviewing data, we attempt to describe, analyse and understand how people retrospectively describe their experience of trust in the early stages of a firm’s life cycle. An interesting facet of the interviews was the extent to which interviewees described the business development process and how trust, as a phenomenon, was demonstrated in both explicit and implicit forms through the use of storytelling. Therefore, the methodological approach employed in this study has been influenced, albeit unintentionally, by ideas of phenomenographic research (Uljens, 1989, 1992), which can be characterized as a qualitative, interpretative, research approach often used in social sciences. In addition, we also adopted the second-order perspective, which
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involves the researcher describing how something is conceived or experienced by individuals without directly referring to some aspect of reality or any objective truth (Marton, 1978). In this study, we compare the constructions found in the data with our own propositions listed above (see Yin, 1991, p. 33). The data were collected among a group of the founders of the case company. Seven key people at the founding stages of X were interviewed. Asking a group of founders about the role of trust through the use of simple questions could easily be leading, suggestive or simplistic. That is why we chose to focus on critical incidents where the phenomenon of ‘trust’ had played a special role, or where its role had somehow transformed. We asked each of the interviewees to tell us ‘the whole story’ from the beginning and from the point of view of trust. The types of research questions used in conjunction with effective listening were ‘who’, ‘what’, ‘where’, ‘how’ and ‘why’, as suggested by Yin (1991, p. 17). The focused interviews remained open-ended and assumed a conversational manner (Yin, 1991, p. 89). Each of the researchers interviewed two or three informants, which prevented any individual interpretation of the first interview to influence those that followed. Substantive questions reflecting the actual inquiry were discussed in a research group (Schein, 1992, pp. 177–180) in order to remind each of them the information needed to be collected. They were posed to the investigator and not to an informant (see Yin, 1991, p. 76). That helped to ensure the homogeneity of interviews. The interviews, lasting from 45 minutes to 1.5 hours, were tape-recorded and transcribed. After coding the interview data and applying pattern coding (Miles & Huberman, 1994), constructs and themes for comparison and analysis were developed. The resulting stories about the phases, crises and events of the history of X were then ‘plotted’ alongside each other on an Excel worksheet and their similarities were analysed through the stages suggested by Greiner (1967, 1972, 1998). The comparison and interpretation of data were performed in collective discussions amongst the research group members. The following section includes a description of the stages, together with illustrative excerpts from the interviews.
Case Study Case Company The case company is a high-tech operation that in a time period of only ten years has
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developed from a key team of six engineering innovators into a multinational company of about 400 employees. The company was founded in 1993, when a group of six felt their future was threatened as a result of their employer deciding to move production to another unit. The team was faced with a decision either to move along with the production or to start up an enterprise. The first generation of products, innovated in reply to a perceived growing need on the market, was launched after about a year. The company continues to grow very rapidly – by the end of the millennium its revenues had increased 15-fold – and it has reached a position among the ten biggest companies in its field in the world. The company is very specialized and can benefit from flexible industry standards much better than their competitors, thus gaining a competitive edge. The dynamic culture and entrepreneurial spirit, which are still very visible in the activities of the company and confirmed by the respondents, are strengthened by shared ownership. Indeed, most of the workers own a share in the company. It appears, based on the case study and the eight interviews, that Company X has been
Large
Size of the organization
Individual members and the leader
Individual members and the leader
Identification
Identification
Trust to competence
Trust to competence
Trust to Integrity
Trust to integrity
Community belief
Trust to benevolence (motives)
developing very effectively along the general developed stages as proposed by Greiner (1967, 1972, 1998). Furthermore, it seems that the company has faced the typical crises stated in the Greiner model (1972). In this sense, our case company supports the internal validity of the study (see Yin, 1991, p. 109). What we find noteworthy is the development of trust over these stages and through the perceived crises. It also seems that at every stage there are separate dimensions that either increase or decrease trust among the founding team. Indeed, there is variance in objectives, mechanisms and antecedents of trust across the various stages. The different components, which arise from the data, are described in Figure 1.
Trust at the Creativity Stage The founders of X used to work for a big international company, but because of the turmoil of the early 1990s, the multinational decided to quit the business that would later become the core business of X. Gradually, the product development group started to give some thought on continuing in a company of their
Trust in the structures
Trust in the structures
Calculative mechanism
KnowledgePredictability based Collaboration mechanism
Vulnerability and the need to trust increased -everything to loose
Reciprocity belief Had nothing to lose – no other possibilities Creativity
Lack of structures
Small
Direction
Lack of structures
Trust in the company Knowledge
Predictability Decrease of informal interaction
Coordination
Delegation
Trust between individuals decreased Unreasonable division of power created distrust
Decrease of informal interaction
Lack of community
Trust between individuals decreased Lack of community
Trust to benevolence decreased Loss of community
Young
Mature Age of the organization
Figure 1. Components Effecting Trust and Distrust between Group Members at the Different Stages of the Greiner Model
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own. Many of these young engineers had rather narrow fields of expertise and so the prospects for finding a new well-paid job in the same region did not seem too good. One manager of the unit started to work on establishing a new company in the same field. Together with another knowledgeable person from the management of another unit, the duo started in secret to plan their own business, based on their respective areas of technical specialty. In this case description, we will call these people R and T, R being the manager of the unit in the multinational company where most of the staff of X originally came from. During six months, R conducted personal discussions with a core team of about 15 people, most – but not all – of which decided to jump on the bandwagon. By the end of May 1993, the core group had been established and were permitted to move to the premises of another international company, an investor partner, who we shall refer to as M. Most of the people in the core team were ready to make the jump. They created a common mission of saving themselves from unemployment, striving for high technology and serving the customers, even if it meant monetary sacrifices (all of the personnel were asked to contribute towards the basic capital in return for receipt of shares in the company). This, together with the participation of M, convinced the public financers, and so the necessary capital was raised. The readiness to start a new business was also largely derived from the trust they had in R. Most had been working with R and knew him as a capable, honest, straight-talking man with good contacts. They had also heard of M before (M also had a history in the same multinational concern but had later become successful on his own). They trusted in R and in themselves because they had worked as a team earlier, and they trusted in their personal competencies and in their knowledge of business and technology. According to Greiner (1998, p. 60), the main issue for such organizations is the person of the manager. Logically, the team of entrepreneurs must trust in this person, and the trust in the person chosen in X was indeed as solid as a rock. This is best illustrated by the fact that even though nobody really had to leave their former company and had unanimously turned down the idea when suggested by the senior person, they unanimously joined X when it was R who invited them to quit and form a company together: I’m confident that this will work, because R had solid professional skills in the field of technology. Moreover, he had also
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made the previous organisation succeed. (Informant 4) Yes, we trusted R, each other and ourselves. Inform ant 2 In this case, trust in the manager’s competence made it sensible to join the business development project from the member point of departure. On the other hand, the trust in the members’ abilities and competencies made the tight division of work possible, which many of the interviewees emphasized as one of the success factors of the process in their view. In this case the competence belief meant that the trustee, in order to act in a trustworthy manner, needs to respond to the expectations developed through the belief of the trustors (Kee & Knox, 1970; Kohtamäki, 2003b; Selnes 1998; Swan, Trawick and Silva, 1985). In the eyes of the trustor (any member or the manager), neither the leader nor the members seemed unreasonably opportunistic, and therefore the members felt safe. The members trusted the manager and each other to keep what was promised and to act altruistically (Butler, 1991; Butler & Cantrell, 1984; Hart, Marshall, Capps, Cangemi & Caillouet, 1986; Järvenpää, Knoll and Leidner, 1998; Kohtamäki 2003b; Mayer, Davis & Schoorman, 1995). Trust in the member’s integrity was also a determinant affecting the decision as to whether or not an individual joined the project. Furthermore, our case shows clear reciprocal trust between the three founders – they trusted and found each other on the basis of their special skills and knowledge and a common vision of what X would accomplish. In this way, they were able to make a multimillion dollar decision based on a handshake, facilitated by the common history in the multinational company and the decisiveness created as a result of the jointly perceived disappointment. Common history facilitates the identification-based mechanism of trust, meaning that the feeling of community is developed through a shared history (Lewicki & Bunker, 1996). It has been said that sharing develops trust, which in this case can be witnessed through the difficult situation that the group shared, in which the company where they were employed was about to move to another location (Coleman, 1990; Cook & Wall, 1980; Fukuyama, 1995; Hart, Marshall, Capps, Cangemi & Caillouet, 1986; Lewicki & Bunker, 1996; Shapiro, Sheppard and Cheraskin, 1992). The handshake is typically used as a metaphor to describe trust between individuals instead of a hierarchical contract (Jarillo, 1993). First, you were faced with the hard values: you had to have sufficient expertise in every
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field. And the starting point was product development oriented. The group was mainly composed of experts in product development. And then, you had to have expertise in production management and testing . . . we were skilled people, sure, but with a certain set of values. Industrious people, who were able to work hard and independently. And humble people. Informant 7 (Managing Director) At this stage of the process, the lack of structures caused some distrust, which was to some degree compensated by the high personal trust towards the leader and other members of the group. Feelings of insecurity were evident amongst some members while leaving the big company and the relative financial and job security that the company had earlier provided.
Trust at the Direction Stage The first years of the work at X concentrated on product development, partly because in their previous jobs the staff had found that the big players were not very focused on quality so there was a niche, and partly because finances were still so critical that X could not really afford a mistake on the market. At the end of the second working year production took off and products were launched through the channels R had managed to secure together with V, another old colleague from yet another of the units of the multinational. The products were received well and sales increased rapidly, leading to tremendous growth and, as is typical in this kind of startup, to the first cash crisis. While the rest of a growing team concentrated on new products and manufacturing, R and V managed to sell a licence to a big company, a move that saved X from cash bankruptcy. One of the respondents told us that: we trusted in the management’s ability to find funding because that was their task, and concentrated fully on our own tasks. Another one said: we were like running all alongside each other, and we knew that if some area lagged, it would soon catch up, we couldn’t stop and help it. Even though they were no longer a small team, the staff at X still remained very specialized and the knowledge about each detail typically rested with one individual. At this stage, T (the other member of the duo behind the idea of starting the business) had already
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left to establish another spin-off company, but generally most of the staff of X still comprised of either the first pioneer team or of their former colleagues from the multinational company. According to Greiner, a crisis of autonomy arises at this stage, and is resolved by the founders delegating responsibility to the workers of the organization. Again, logically, the basis of this must be the trust in the individuals’ abilities and skills to take on the responsibility. In our case company, all the respondents confirmed this view very clearly. All the members of the entrepreneurial team trusted not only in their own knowledge of the business but also in the will, ability and motives of others to solve the problems that arose in their areas of responsibility (integrity) and to survive as a team. Trusting that a member would keep to what he had promised also meant a lot. This could be defined as trust in integrity (Butler 1991; Butler & Cantrell 1984; Hart, Marshall, Capps, Cangemi & Caillouet, 1986; Järvenpää, Knoll and Leidner, 1998; Kohtamäki, 2003b; Mayer, Davis and Schoorman, 1995). In addition, trust in the trustee’s benevolent intentions was important (Cummings & Bromily, 1996; Mayer, Davis and Schoorman, 1995; Solomon, 1960). In this case the benevolence, as a trusting sub-belief means that the partner does not want to harm the trustor intentionally, but also that the trustee helps the trustor if needed (Luhmann, 1988, p. 45). Benevolence relates to altruism and is essentially an antonym of opportunism. The cash crisis in X did not influence people’s efforts and activity in product development or sales activities because everybody believed the financial managers would solve the problem in their area. For them, being able to see the practical products and perceive the markets made the mission of X explicit to all and strengthened the trust in the team. Many of the informants remembered fondly the first small-team ‘on a mission’ years, the long nights working with a technical problem and the sauna evenings together that set the culture of X. These long nights and problem solving had together created a base from which the community could develop through identification with each other’s values and goals. In other words, the participants shared purpose (Lewicki & Bunker, 1996). At this stage of the process, identification with the same goals was interpreted as a key mechanism of trust. We were like running all alongside each other, and we were confident that if some area lagged, it would soon catch up. (Informant 1)
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To be honest, I wondered many times how everything would end up but I never doubted anyone would break the confidence and not do his job. Everybody did his job, indeed. We never had major crises in the group. (Informant 5) What was that kind of trust based on? Isn’t it a bit like the Finnish Winter War – when you have a common problem . . . a common goal . . . and all had their stakes in it. (Informant 6) As in the previous stage, the lack of structures was evident, although the financial position of the company was improving after the 1995 cash crises. The company now struggled to improve its market position through competitive structures.
Trust at the Delegation Stage After the cash crisis was resolved and a licence income secured for several years to come, the interviewees felt that X was finally established in the market. As is typical at this stage, some re-organization took place. It seems from the interviews that some of the original owners wanted to cash out, so the organizational form – including the ownership of the shares – was changed. Some of the original team felt very badly about this, while some others gave the impression that they felt everything was alright. Nevertheless, with this move a great many of the founders had been reduced to minor shareholders and workers in the company, while some others gained larger amounts of shares. Even between the key owners there seems to have been some feeling of injustice as to the outcome of the division of the shares. This experience of injustice led further to distrust and a decrease in the feeling of community (see also Gustafsson, 2002, with regard to the reasonable as a basis for trust). During this process, the spirit of the entrepreneurial group was lost. The emphasis moved from the identification-based trust mechanism towards a more calculative mechanism within the whole group. This managerial act, however, facilitated the company going public a couple of years later. The crisis of control faced the case company after about five years of activity. Top management had taken decisions that were not based on mutual understanding among all in the team, and this split into ‘managers’ and ‘workers’ created some distrust in the benevolence of other group members’ intentions and motives. This doubt towards the trustee’s benevolent intentions and motives may cause distrust to occur and, as it has been defined by
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earlier researchers, trust often decreases catastrophically (Lewicki & Bunker, 1996). Indeed, many of the people interviewed commented on the unreasonable division of power and wealth in the newly organized company. There were no major crises when the business was growing rapidly . . . at that time, all used to pull together. Crises did not occur until we started to have something to divide. (Informant 3) When I’m thinking about it retrospectively, it (pursuit of profit) was their only motive to join in; they didn’t have any other motive. (Informant 4) Work at the new organization was no longer transparent to all, which marked an altogether new development in the company culture. Earlier, everybody had particularly commented on the positive openness of discussion. Trust in the company and in its procedures still prevailed, but the trust in individuals started to fray and caused further suspicion as well as a feeling of unpredictability and insecurity within the team. Positive predictability is argued to increase trust. The fear of the trustee taking advantage of the vulnerability of the trustee acting opportunistically may cause a feeling of insecurity (Korsgaard, Schweiger & Sapienza, 1995; Shapiro, Sheppard and Cheraskin, 1992).
Trust at the Co-ordination Stage At about the same time as the public listing of the company, it had become obvious that the initial ten-year strong burst of growth had ended. X was still growing, but much slower than before. Many of the informants sounded almost confused about the fact that they are now surrounded by colleagues that are not of the founding team, and in some cases are not even old acquaintances. In the minds of many, this leads to the realization that X has in fact become a ‘big’ company. As an engineer, and one of the founders, put it: even if the problem solving procedure is precisely the same as before, I cannot really know if the problem will be solved because the people aren’t the same I had learned to know. Furthermore, he said a new thing that has taken some learning has been to accept that I cannot know what is going on everywhere in the company. X had grown big enough in the market to have numerous people responsible for different customers, markets and technologies, and none of the founders even knew all the
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members of the management team personally. The interviewees’ trust in the company structures was at a high level. This stage, in our opinion, culminated in the first management generation’s departure from X. First, R announced he would be leaving to pursue other business ventures. He himself confessed that he had already decided he would leave ‘as soon as the number of staff grows to over 100’ – this had taken about ten years. Some months later, M also announced he would concentrate on developing new ventures, and finally, at the time of this interview, even V had left to establish a new company. Many of the founding members – although seemingly none of the founders that had gained larger numbers of shares during the listing of the company – still worked in their positions as engineers, concentrating on the technical details of the products. These founding members reported trust towards each other, deeper than its calculative form, but not reflecting the feeling of community. Trust between them was knowledge-based, meaning that the members knew each other in a positive sense, but did not experience the community as it was before the crises. According to Greiner (1972), the company will eventually come into a red-tape crisis, caused by growing bureaucracy. In our case company, there was not an overwhelming amount of administrative work or red tape, but the hierarchy was growing along with the number of staff to a point where personal relations and mutual trust started to lose their footing. A possible explanation is that perhaps the co-ordinative mechanism shifted from trust and social control towards a hierarchical control as the organization grew bigger (Durkheim, 1990; Granovetter, 1985, 1975; Ouchi, 1980; Powell, 1990; Rousseau, 1988). The original team was now clearly dispersed. Since the management and worker teams comprised of so many people who were not involved in the original team, it could be said that the organization had effectively adopted a new identity. The communication flow worsened beyond a mere question about openness. The procedures started to show a clear lack of overlap and even some factual information was lost. The hierarchical structures reduced the importance of interpersonal trust in the organization, but the lack of informal interaction caused distrust to some degree (Ouchi, 1980; Shapiro, Sheppard and Cheraskin, 1992). Nowadays I do wonder how the things are because you don’t know those people. (Informant 1)
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Among the fellows, we are US, but from the other departments only the old chaps are US. (Informant 5) If I mention the human side, that is, a worse side, it was about greed. When the business went public, we had outside people. And others got a bigger share many people waiting for the business to grow and earn a profit that way. (Informant 3)
Trust at the Collaboration Stage A new generation of management has since taken over responsibility of running the business. It seems the ‘fun time’ was over. Some of the founders got very emotional at our interviews when thinking back about the first five years of X. Nowadays, they practically do not visit X anymore although they still live nearby. This development has led to the de-motivation, disillusionment and the exhaustion of the staff. This has been particularly true about the founders, including R in particular, in whom everybody had placed their trust at the beginning. The core team of four have, in only about ten years, all come to the decision to leave the company for other business opportunities and were already before that perceived to be ‘distant’ by some of the respondents. At the same time, it also seems that the whole concept of trust between people has lost its importance and the prevailing people of the original team do their jobs without spending too much time thinking about the old days, the culture or the mission they originally based the company on. The need for trust in the employees culminates in trust in the organization. It is a predictability belief towards the continuation of the organization, even though the team that created the firm is not in charge anymore (Korsgaard, Schweiger & Sapienza 1995; Shapiro, Sheppard & Cheraskin, 1992). This belief is based on the knowledge about the company, its customer base, products and processes. I have already quit the business. We are no longer in contact with one another (among the core team). It became obvious that the founders had no longer importance as the number of people increases. (Informant 6) In the beginning, when we were a small group, we always held a monthly meeting, where we discussed the current situation. But after we went public, this was no longer possible because you had to inform the whole world of all the issues. Nowadays, the information comes from the Managing Director or in an information bulletin and reaches everybody simultaneously. It’s a
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change you just have to understand. (Informant 5) Now the second generation is in charge. You have to build trust again, gradually. I suppose you have this kind of breaks every ten years. (Informant 2)
Discussion and Conclusions One of our theoretical propositions was that objects of trust change systematically across the different stages of the new business creation process. In our case study, the object of trust changed over time. At the first stage it was the founders, then the teams’ skills and mission, and after that the procedures and roles, and finally, the company where individuals’ trust no longer matters and the reasons to do things and believe in things have been institutionalized. Therefore, this meant that the object of trust had developed from one individual to the group and then further to the company and its structures. Our second theoretical proposition was that there is variance in mechanisms of trust at different stages of new business creation. Interestingly, in this case the beginning of the story in this company’s history began from the last development phase of trust (identification). This means that the early development phases of trust mechanisms (calculative and knowledge-based) had already been passed whilst the group had worked in the company, which they subsequently left in order to develop new business ventures. In this case, trust was lost at the third stage of the process, during which some of the group members opportunistically sought to gain ownership, leading to the disintegration of group members. The crises also affected the relationships of those that were acting as trustworthy members. Some could relate to a shared ‘war’ against the opportunistic members at the beginning of the struggle, whereas afterwards the relationships turned colder because the community spirit was lost. It was difficult for some members to accept the unreasonable greediness of others. After this event, some of the members left the company, while those who were to stay experienced a rise in the level of bureaucracy. Whilst opportunism may be a reason for lack of trust, it is also a driver for innovation in some cases. Gradually, after the first two stages this trust has, for different reasons, been replaced by feelings of distrust. From the development of X we propose an interesting hypothesis: there can be matters and events that increase trust and also matters that can decrease trust, and both these developments can exist simultane-
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ously. This suggestion has been made earlier by Lewicki, McAllister and Bies (1998), but to our knowledge it has not been studied further. Our third theoretical proposition was that there is variance in antecedents of trust at different stages of new business creation. In the beginning (first two stages) trust was built on the strong feeling of community. Interviewees emphasized the meaning of personal competence, reciprocity and integrity, as well as good (benevolent) intentions. Later on, as the company developed its structures the strong feeling of community was lost and the members focused their trust towards the predictability of company structures. The predictability of the company had a meaning to some members in the development of a feeling of security. Simultaneously, the innovativeness of the organisation has changed in nature. From entrepreneurial ideas of leapfrogging the world, the mission became to develop by smaller steps and in a more organized way. We argue that a company that has reached the stage at which trust is institutionalized by procedures and structures, they will experience difficulties in creating the initial innovative climate where everybody relies on their own competence to ‘save the world’. Lastly, we proposed that the perception of change in trust mechanisms, objects and mechanisms would be distinctive enough to be sensed in similar ways by different people in the same community. The study also supports this proposition. In light of our data, trust is not just an individual phenomenon, but it is also collective. The interpretations of seven interviewed persons were distinctively similar concerning the nature and change process of trust at different stages in the founding team. There were common understandings and feelings about trust in the interviewed founding team, even though they had not discussed the matter openly together. Differences appeared, however, in the explanations for the changes in trust amongst the team. Personal reactions also differed. For example, some interviewees had stronger feelings of hurt than others. This case study also suggests that trust is a force that changes the culture of a company. Indeed in X, the culture changes seemed to coincide with the changes in trust objects and mechanisms. Furthermore, the determinants of trust seem to differ at different stages. Ultimately, in our case, levels of trust mainly rose and fell on the common perception of values and on the development and diversification of them within the team. By connection to cultures, we believe trust also connects to the level and type of innovation in a company. In the early stages when people trust their competence
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and are driven by vision, innovation is oriented towards new solutions and breakthrough products. At the latter stages, when trust is based on structures and continuity, the lack of interpersonal trust discourages people to talk about their big ideas, and people are just expected to solve the problems allocated to them (Fecikova & Kekäle, 2003, report the same finding in another much bigger company). Therefore, the connection of trust to the concept of cultures and subcultures should also be studied further from an innovation viewpoint. As a general conclusion, we argue – supported by our single case study – that the general development of trust follows the established general stages of development of a company. This dependence appears so logical and fits the theoretical propositions derived from earlier studies that it could be a general model and not purely dependant on the people and the nature of business in our case study. The feasibility of this kind of systematic contingency dependency would, however, require further study.
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Wasaensia, 104. University of Vaasa, Vaasa, Finland. Preisendörfer, P. and Voss, T. (1990) Organizational Mortality of Small Firms: The Effects of Entrerpreneurial Age and Human Capital. Organization Studies, 11, 1. Quinn, R.E. and Cameron, K. (1983) Organizational life cycles and shifting criteria of effectiveness: Some preliminary evidence. Management Science, 29, 33–51. Rousseau, D.M., Sitkin, S.B., Burt, R.S. and Camerer, C. (1998). Not so different after all: A cross – discipline view of trust. Academy of Management Review, 23(3), 393–404. Rousseau, J–J. (1988). Yhteiskuntasopimuksesta: Eli valtio–oikeuden johtavat aatteet. Karisto Oy, Hämeenlinna, Finland. Rosenfeld, R.H. and Wilson, D.C. (1999) Managing organizations. McGraw–Hill, Berkshire, NJ. Rotter, J.B. (1967) A new scale for the measurement of interpersonal trust. Journal of Personality, 35, 651–65. Sako, M. (1992) Prices, Quality and trust. Cambridge University Press, Cambridge. Schein, E. (1992) Organizational Culture and Leadership. Jossey-Bass, San Francisco, CA. Schumpeter, J.A. (1934) The Theory of Economic Development. Harvard University Press, Cambridge MA. Scott, M. and Bruce, R. (1987) Five stages of growth in small businesses. Long Range Planning, 20(3), 45–52. Selnes, F. (1998) Antecedents and consequences of trust and satisfaction in buyer–seller relationships. European Journal of Marketing, 32(3), 305–22. Shapiro, D., Sheppard, B.H. and Cheraskin, L. (1992). Business on handshake. Negotiation Journal, 8, 365–77. Sigrist, B. (1999). How Do You Recognize an Entrepreneurial Opportunity? Entrepreneurial Opportunity Recognition in a Swiss Context. PhD Thesis. University of Zurich, Zurich. Smith, K.G., Mitchell, T.R. and Summer, C.E. (1985) Top management priorities in different stages of the organizational life cycle. Academy of Management Journal, 28, 799–820. Solomon, L. (1960) The influence of some types of power relationships and game strategies upon the interpersonal trust. Journal of Abnormal Social Psychology, 61, 223–30. Swan, J.E. and Trawick, I.F. (1987) Building customer trust in the industrial salesperson: Processes and outcomes. Advances in Business Marketing, 2, 81–113. Swan, J.E., Trawick, I.F. and Silva, D.W. (1985) How Industrial Salespeople Gain Customer Trust. Industrial Marketing Management, 14, 203–211. Swayne, C. and Tucker, W. (1973) The Effective Entrepreneur. General Learning Press. Morristown, NJ. Timmons, J. (1981) Survey of the most active venture capital firms. In Vesper, K. (ed.), Frontiers of Entrepreneurship Research. Babson College, Wellesley, MA.
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Uljens, M. (1989) Fenomenografi – forskning om uppfattningar. Studentlitteratur, Lund, Sweden. Uljens, M. (1992) Phenomenological features of phenomenography. Report no 1992:03. Department of Education and Educational Research. University of Göteborg, Gothenburg, Sweden. Van de Ven, A.H. (1995) Longitudinal research for studying the process of entrepreneurship. In Sexton, D.L. and Kasarda, J.D. (eds.), The state art of entrepreneurship. Kent Publishing, Boston, MA, pp. 214–42. Vesalainen, J. (1995) The small firm as an adaptive organization: Organizational adaptation vs. environmental selection within environmental change. Vaasa, Finland: University of Vaasa. Webster, F. (1976) Entrepreneurs and venture – an attempt at classification and clarification. Academy of Management Review, 2(1), 54. Yin, R.K. (1991) Case Study Research. Design and Methods. Sage Publications, Newbury Park CA. Ylinenpää, H. (1999) Managing Competence Development and Acquisition in Small Manufacturing Firms. Department of Business Administration and Social Sciences Division of Industrial Organization. Luleå University of Technology, Luleå. Zaheer, A., McEvily, B. and Perrone, V. (1998) Does trust matter? Exploring the effects of interorganizational and interpersonal trust on performance. Organization Science, 9, 2. Zucker, L. (1986) Production of trust: institutional sources of economic structure. Research in Organizational Behavior, 8, 53–111.
Marko Kohtamäki is a researcher on the project ‘Entrepreneurship in network economy’ at the Department of Management in Vaasa. He takes special interest in network governance, trust and entrepreneurship. His main research activities concern research on governance of strategic networks, trust and new business creation. E-mail:
[email protected] Tauno Kekäle has a PhD in the field of quality management from the University of Vaasa (1998). He is currently holding a professorship in Industrial Management in the Faculty of Technology of the University of Vaasa, and his current research orientation is in new product development management, especially from an organizationalculture viewpoint. E-mail:
[email protected] Riitta Viitala’s PhD thesis is also from the University of Vaasa (2003). She holds a post-doctoral research fellowship at the Department of Management. She also regularly gives lectures and consults on the management of major Finnish companies. Her research interests include leadership and management of knowledge, among others. E-mail:
[email protected]
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The Physical Context of Creativity Tore Kristensen1 Creative processes are complex and consist of sub-processes, e.g. value creation, scaffolding, imagination and materialization. Creativity takes place in a physical context, i.e. in a confined space. Such space restricts and enables the free flow of sensory experiences and proximity of other people. The confinements may make certain sensory experiences available, e.g. vision of source material, sight and sound (including noise). This framing allows certain cognitive processes and restricts others. This may induce emotions that, in turn, facilitate or reduce the enhancement of creativity. Physical space affects the well-being of people, the channels of information, the availability of knowledge tools and sets the stage for coherence and continuity, which may contribute to competitive advantages.
Introduction
Creativity
C
A creative individual is somebody who actively seeks new knowledge, who is motivated by curiosity and who wants to achieve something. Creative individuals are also able to sustain ambiguity and stay in a state of ‘indecision’ for longer than others, and may show a risk-taking attitude. While these characteristics may be true, they should not be exaggerated. Csikzentmihaly’s (1996) interviews with over 100 people, especially selected for achievements at Nobel Prize level, indicate that lifestyle and being in the right place at the right time play a major role in creativity. To know when and where the right time and place indicates that factors outside the creative individual are at play. This means the creative person must match with the field of experts and the domain of knowledge. Wallas (1926) introduced a phase model, which has been used and referred to as an anchor point of creativity ever since (Csikszentmihaly & Sawyer, 1995). The model serves as a good guideline for how a creative process may consist of different phases. In the phase model, the first phase is preparation, the second is incubation followed by insight and lastly, elaboration and evaluation. We will inspect these, before describing relations between the creative processes and the spatial dimensions.
ompanies can generate more good ideas by using the physical space more diligently. By using the choice of place and space, creative processes may be facilitated. The creativity literature (e.g. Csikszentmihaly, 1996; Sternberg & Davidson, 1996) presents many good examples of individual people’s creative habits and launches the general argument that space means a lot for people’s emotional well-being, which in turn is fundamental for creative work. In the business literature, creativity is highlighted, whereas space is hardly ever mentioned. In the cognitive literature (e.g. Kirsh, 2001), some ideas on workspace in general are presented. In architectural literature, Alexander, Ishikawa and Silverstein (1977, p. 847) shows how a good workspace might be designed, but presents little theoretical explanation. Yet there is inspiration to find in this literature. So far, there is limited knowledge on how the physical space actually enhances creativity. The article is organized as follows: the next section addresses creativity including the conventional phase models. The third section explores spatial concepts. The fourth section defines embodied cognition and reframes the concept of creativity. This leads to further elaborations and ways of juxtaposing the nature of creativity into four different processes in the fifth section, where we also discuss spatial requirements. The final section contains a discussion and conclusion. © Blackwell Publishing Ltd, 2004. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
1
The author wishes to express warm thanks to Kjell Grønhaug for his generous support.
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The Preparation Stage The general issue of this stage is to facilitate data and information for the process. Such situations differ, as both a single individual as well as a team may conduct the preparation. Space for organizing the information and easy retrieval is essential. It is vital for team members to exchange frameworks, to set the common goals and stage the remaining process. The spatial arrangement must support as much information flow and absorption as possible to each member. The tools, like personal computers, bulletin boards and general access to information are important both for individuals and for teams. Communal space seems important for teams. Sometimes a private space is essential for analysis, both by individuals and team members. The length of this phase can vary – depending on when the team reaches a barrier, fatigue or leaves the assignment.
The Incubation Stage In the incubation stage, the cognitive processes seem to be essentially a personal or private affair. Incubation can happen when people change to other assignments or simply relax from a previous one, but the cognitive process of problem solving goes on implicitly. The literature on incubation only refers to individual cognitive processes, (Dorfman, Shames & Kihlstrom, 1997). Despite this, it seems likely that ‘distributed cognition’ happens because perceptual clues are shared among team members (Hutchins, 1995). In such cases, the team members need a medium of communication e.g. a bulletin board (Reddy, 2002) or any other cognitive artefact (Gedenryd, 1998). Some creative people are best left to themselves in the incubation stage, while others seek company. Incubation is an implicit cognitive process, but perceptual clues may facilitate the process. Staying in the room where all the information from the preparation stage is kept may facilitate such implicit perception as a process of ‘priming’.
The Insight Stage Insight (or illumination) is a ‘flash’ that occurs when the winning concept cuts across the barriers of consciousness. Accounts of insights are often reported as idiosyncratic, and it may not matter much where it takes place (Hadamard, 1945).
Elaboration and Evaluation We shall compare the results with the goals of the preparation stage where the value creation
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is at the centre. In this context, thorough analysis and evaluation are necessary in order to see if the desired goals and values are met. Contextually, this stage must resemble the preparation stage, as the operations are similar. While the preparation stage starts with a briefing, the elaboration and evaluation stages end with a debriefing and implementation. While we can assume how space may increase creativity, there are no aspects of this in the theories.
Spatial Concepts Concepts of space are often thought of in ‘vernacular’ terms, because of the difficulty of their articulation (Hillier, 1996). Even architects have only recently developed a scientific language for space (Hillier, 1996). The most basic concept when dealing with space must be that of place. The position and extent of the place must be established before the particulars of space matter (Nordberg-Schulz, 1970). ‘Place’ refers to the physical extent or territoriality, whether in the home or at work. The ‘dwelling’, signifying the locus one returns to, is important, as this is the foundation for an identity within the whole organization. Space is the ‘built environment’ and includes shelter, confinement and protection (Lawrence & Low, 1990, p. 454). ‘Built form’ also refers to specific elements (e.g. doors, windows, roofs, floors and chimneys) as well as sub-divisions of buildings (e.g. rooms, arrangements and connections) referred as ‘configurations’ (Hillier, 1996, p. 33). There are several concepts of space (Nordberg-Schulz, 1970). Although the concepts of physical, perceptual and phenomenological space differ analytically, in most situations these concepts must be seen in relation. Architects and builders create the physical space, but the space we use is founded on what we perceive. Physical space is the foundation of the perceived space that affords opportunities for our activities. Physical space is the objective and the perceived space is the subjective aspects of the same space. Other variables are paths, connecting spaces or spaces naturally leading to movement or in a certain direction. Paths guide much automatic behaviour (Bargh & Barndollar, 1996), since we usually follow them without effort or conscious decisions, which is an important aspect of how space directs behaviour. The density of the place can be important as it means that people move closer to or further away from each other, the so-called ‘proxemics’ dimension (Hall, 1968). Density is usually not a homogenous phenomenon. High
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density may result in more intense interaction, e.g. when people brainstorm. On the other hand, when people get too close, the space becomes crowded (Baldassare, 1978). Norberg-Schulz (1970, p. 17) defines space as ‘a relatively stable system of schemata’, where these schemata can be logical, pragmatic, perceptual, cognitive, emotional or existential. A number of spatial dimensions are important. One is configuration, which has a quantitative aspect and can be defined formally: If we define spatial relations as existing when there is any type of link-say adjacency or permeability-between two spaces, then configuration exists when relations between two spaces are changed according to how we relate one or other or both to at least one other space. (Hillier, 1996, p. 33, 96ff). When we consider two adjacent rooms and a situation where a person comes from the outside and enters one of the adjacent rooms, it becomes clear why configuration matters. If you have to pass through one to get to the other, the configuration is asymmetrical. This means that it is possible to grade rooms according to access. Some rooms are accessible from outside and allow strangers to enter. Others require more doors and are restricted to privacy. The issue is both practical and cultural. Few cultures allow a stranger coming from outside to enter the intimate rooms of a home or a shop. Buildings in most of the world have graded accessibility to rooms, marking the level of intimacy from the outside. Typically, there will be a communal space that strangers are invited into first, which is also the room that provides access to most of the other rooms in the house. This quantitative aspect is measured by the simple means of a jgraph and shown as simple branch or network models (Hillier, 1996, pp. 35, 99). The configurations can be characterized as form, e.g. centralized, linear, radial, clustered and grid (Ching, 1996, p. 57), which all offer a variety of usages. The other important characteristic is qualitative. This is more complex, and this is where the real challenge is. Many experiences and emotions are attributed to space (Baldassare, 1978). Particularly relevant for our purpose is the connection made between space and imagination. Aristotle made use of the spatial term topos (Nordberg-Schulz, 1970), which is similar in meaning to Newell and Simons’ (1972) term ‘problem space’, meaning a discourse. Physical space is correlated with cognitive space. This is a metaphorical relation, where the physical space gives form to cogni-
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tion. Our objective is to identify what qualities in the outer space feed into an effective inner creative process.
Embodied Cognition and Creativity Creative processes are mental, and have been the object of research among the early cognitive scientists, e.g. Newell and Simon (1973). The aim of that research was to develop a metaphor resembling a computer image of the brain. Although this research was successful for many years, criticism has recently emerged claiming that the research programme ignored context (Clark, 1997; Haugeland, 1995; Hurley, 1998). In contrast, their view assumes that cognition and emotion integrate body and mind, and that it cannot be regarded as an activity apart from the physical reality and body of the thinking and feeling subject. Much cognitive activity is ‘situated’, that is, it happens ‘online’ when challenges are met and action is required. This does not mean that planning and reflection are not happening or that they are not very important. It means that even when the best planning has been conducted, the reality of the situation is a direct force that must be accommodated in real time and with complex feedback. Hurley (1998) uses the following metaphor: the circus performer who puts the handle of a dagger in her mouth, tips her head back, balances a sword by its point on the point of the dagger, and with the whole kit balanced above her head magisterially climbs a ladder, swings her legs over the top rung, and climbs back down the other side of the ladder. Each move she makes is both the source of and exquisitely dependent on multiple internal and external channels of sensory and motor-signal feedback, the complex calibrations of which have been honed by years of practice. An only slightly less intricate structure of dynamic feedback relations knits the nervous system of a normally active organism into its environment. (Hurley, 1998, p. 2) Much cognitive work is ‘situated’, once we are there, we must act out the plan and make all kinds of situational adaptations as problems occur. Often, things happen so fast that only automatic responses (Bargh & Barndollar, 1996) and emotions (LeDoux, 1998) are fast enough. Creativity is a process that brings new knowledge, that is, previously unrelated elements of knowledge that are synthesized bring new insight through a mental process. There seem to be four sub-processes, ‘layered’ into each other, which connect with each other
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in a variety of ways. Each of these processes goes through the four phases of the Wallas model, but not equally strong. They run partly simultaneously and partly one of the processes dominates, according to which phase of the Wallas model we are in. The processes are: • • • •
value creation processes; scaffolding; imagination processes; materialization processes.
Value Creation Processes Value creation penetrates the whole process as the goal of creative endeavour. A critical element of innovation in business companies (Christensen, 1997) is that the process takes place in close co-operation with the value chains of the company. An innovation is a reconfiguration of value chains and if innovations are detached, i.e. done independently of implementation, implementation may jeopardize the innovation and no new value or exploitation will be realized.
Scaffolding ‘Scaffolding’ means that a creative process is designed within a context of space, tools, people and information. This usually takes place at the beginning of the creative processes in order to support the subsequent processes. Any cognitive process goes on within a mediating cultural and physical context. Cognitive processes are ‘embodied, environmentally embedded’ (Clark, 2001 p. 140). Humans move around in the ‘creative space’ much like we move around in a landscape. When this happens, a ‘perceptual rehearsal’ is performed (Ippolitto & Tweeney, 1995). This supports the process of imagination, which accommodates changes in concepts and adopts new ones. In this process, people perceive sensory impressions. Furthermore, the scaffolded environment becomes a part of the creative brain, and an implicit factor that we only question where we detect problems. Problems of sub-optimal environments may be experienced only as symptoms and as emotions can that impair the creative output. Haugeland (1995, p. 236) specifically asks whether the context embodies the information and knowledge created in cognitive tools and processes of a laboratory. Any studio or laboratory scaffolds its specific activities to match their ways of creative working (Kelley, 2001). The first spatial issue is that of shape or configuration. The basic configurations are; centralized, linear, radial, clustered and grid
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(Ching, 1996). At a very general level, the activity that takes place must be facilitated by the floor plan. Long corridors facilitate a hierarchical organization with people in separated rooms, whereas a flat structure is afforded by open space where people interact at many levels. For instance, people meet when their paths cross. A forum or meeting place enables many people to interact simultaneously. Narrow paths that only allow sequential passages reduce interaction (Sundstrom, Herbert & Brown, 1982). The linear space may appear tidy and well-ordered, but it is difficult for a group of people to assemble to discuss preparations or feed new information into the system. This is best done when a circular structure can be realized. Often, meeting rooms or lecture theatres are used in sharing information. But these are usually intended to communicate the ideas from one person to an audience, not the audience sharing information. Thus a centralized or radial shape seems more appropriate, in the sense that communal space can be realized at the centre of the creative space. Often there will be a centre, where communal tools may be placed, e.g. storage of vital information, earlier successes, etc. In situations where multiple disciplines work together, the need for a central location and information system may be vital. IDEO Product Development (Kelley, 2001) has such facilities. More advanced forms, such as clusters or grids, may improve the space, allowing special attention to be given to the specific requirements of tools, e.g. visual or prototyping. A creative space should allow the peculiarities of the present disciplines to deal with the particulars, while enabling communal space for intensive exchanges and collaboration. The design studio is a good model, as many designers like to design their workspace. Symmetries are often preferred for aesthetical reasons, but often functionality and variation is facilitated by asymmetry. An asymmetric space may also be more challenging and present an exciting atmosphere. When two planes are vertically in parallel, they can provide different configurations and allow paths to include both horizontal and vertical movements (Ching, 1996, p. 143). A grid structure can thus be obtained and allow both effectiveness and flexibility. A good creative space seems to contain challenges to the inhabitants and a part of its use. At first sight, the studio of the Finnish architect Alvar Aalto seems to be quite simple, but in reality it is not (Ching, 1996, p. 138). The space is basically Lshaped, which promotes functionality. The Finnish architect Aalto brings the outdoor area into the picture with an amphitheatre for lec-
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tures and social occasions in the surrounding garden. This is visible from the windows and brings a dynamic into the space that asserts its potential circular form and sense of community. Often, space developed for other purposes, e.g. sacral space, seems to afford creativity. In such space, the religious activities are usually centred where the community can surround the rituals and share them. Similar activities seem to be a part of the process of creativity and should therefore be similar.
Imagination In the creative processes the imaginative is sought, that which did not exist before. Real imagination is concerned with new insights. In a creative process, imagination may be intense, but with short duration. The concept imagination (Brann, 1991; Johnson, 1987) stands for the integration of knowledge into coherent and unified representations over time. These should be in the form of ‘schemata’ that mediate between abstract concepts, contents of sensory experiences and the creative, free, open-ended activities by which we achieve new ways of experiencing and accommodating the exiting structure of knowledge to integrate new knowledge. This is obvious if the outcome is a physical object, but even a service or system must be documented e.g. using visual and verbal descriptions (Horn, 1998). Imagination is the representation of what does not yet exist. To imagine is to envision or create. Imagination is a dramatic human capability and a way for changes (Brann, 1991, p. 23ff). Imagination, as the word’s etymological origin suggests, is having a picture in the ‘mind’s eye’. Some of the definitions include ‘to abstract or extract from multiple ideas and compound them into one’ or ‘the human capability to find analogies’. Lakoff and Johnson (1999) bring metaphors – cross-domain mappings – to the foreground of imagination. According to them, creativity is the recombination of existing elements of knowledge or symbolic representations. Herbert Simon’s (1996, p. 111) definition of design raises the issue of imagination. He distinguished between the logics of ‘what ought to be’ in contrast to ‘what there is’. Filling this gap is the role of design and, according to Simon, the solution is heuristic research, which is equal to imagining. The history of creative processes has explained how their creative thinking was visual (Feynmann, 1985; Hadamard, 1945). Crick and Watson (Gick & Lockhart, 1995, p. 214) similarly ‘saw’ the double helix of DNA after their own and others’ constant remodel-
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ling of the moleculcular structure. The workspace is found in design studios, and laboratories are filled with images, artifacts and models. Sometimes ‘odd artefacts’ such as a DC 3 wing finds its way into existence because it ‘must be there’ (Kelley, 2001). Such space is usually personalized and people design it themselves. The idea of sharing workspace and leaving a clean desk with no personal belongings seems to create a sterile environment that inhibits imagination. What seems to facilitate creativity is personal and idiosyncratic. Only flexibility can make this happen.
Materialization Finally, the materialization process transforms concepts into material objects. Concepts must be made to sensory experiences. A doctrine held high in the IDEO Product Development company is ‘rush to prototypes’ (Kelley, 2001). It means whenever possible an idea or concept should be materialized. This is in accordance with the embodied cognitive theory (Clark, 1997). The idea of ‘wideware’ is that the environment facilitates a cognitive process, where space, surfaces, objects (artefacts) are part of the apparatus and interact with the biological brain in a concerted way. Some cognitive processes are sometimes only possible when externalized. The lack of visual clues reduces the memory, although memory techniques may facilitate it. Brann (1991, p. 282ff) claims that memory is facilitated by using space – and by internalizing experiences in a spatialtemporal setting. Memory is sometimes facilitated by the impressions of a particular place. This could be due to different sensory impressions. Many people, when they forget something head back to the last place they could remember what it was about. We can generalize from this and use the environment systematically to stimulate memory creativity. A simple way of materializing is sketching and using diagrammatic methods, visual models and tangible objects. Therefore, availability of tools for prototyping and models is important. Some companies rent design studios for the purpose of immediate availability of workshop facilities. While it was not Newell and Simon’s (1973) intention to connect workspace and problem space, we make the connection because the two are natural extensions of each other when we consider embodied and embedded cognition. In particular, when we consider space for design work and research laboratories, this makes sense. Creative people externalize the mental constructs in order to work better with them. Other studies (Kirsh, 1995, 2001) also account for the importance of physical space
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Table 1. Embodied Creative Processes Preparation
Incubation
Elaboration and evaluation
Value creation
Guiding principle
Guiding principle
Guiding principle
Guiding principle and benchmark
Scaffolding
Physical organization of process
Subject to altering and manipulation
No particular role
No particular role
Imagination
Perceptual rehearsal accumulates information
Perceptual rehearsal accumulates information
The moment of novelty
No particular role
Materialization
Preparation includes tools for materialization
No particular role
A new concept, solution or artefact is material or sensory
The material object or artefact is subject of elaboration and evaluation
in work processes. In the end, value creation must be material to be implemented in production, whether products or services. Table 1 shows how the concepts of spatial embodiment and creativity processes work together.
A Case A big pharmaceutical company was in a process of developing new devices for their hormones. Having been one of the leaders in the field, the company decided that in order to improve their competitiveness, they had to integrate syringes for delivery of this particular hormone, aimed at the growth of children. The process they were aiming for was to follow a ‘Wallas-type’ creative process (Wallas, 1926). Early explorations led to the idea that since the new product was not strongly connected to the existing (pharmaceutical) product lines, there was no particular reason to expect that the development would benefit from proximity to the pharmaceutical research, and it was decided that the development team find their own space. Available space in the company is ordinary linear office space. Small rectangular offices were located in a sequential fashion like a typical office or hospital building. It was evident that walls could be put down and offices combined to form larger rectangular shapes. This was not found to be very attractive since the develop-
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ment team, consisting of engineers, product designers, a marketing and brand expert and a user research expert wanted a centre of gravity where the project was physically anchored. Instead, a design studio was commissioned on a part time (one to two days a week) basis to serve the space. The vicinity of the city centre, with easy access to city life and nice panoramic views may influence the process as well as the variation of changing spaces for one or two days a week. It is difficult to isolate the affect of place versus space, but we assume space is the most important factor. The studio consists of one big room and several workshops located in a ‘clustered’ fashion. The big room is at the centre of the design studio and paths go in radial manners out from this central location. Since the studio could only be used one to two days per week on a regular basis it was not possible to make fixed installations. Everything had to be flexible to allow other applications. The centre consists of two large tables with drawing facilities and computers. The space is large compared to the limited number of people and crowding is not an issue. The colours are light and the walls and floor filled with objects and models. In the preparation phase, the space was furnished with a bulletin boards, flat tabletops, drawers and filing cabinets for localization of specification, progress reports and sketches. Computers with CAD were present in the studio, as were metal and wood workshops,
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very close to the main location. Competing products and other relevant props were displayed on shelves surrounding the room. The work in this phase consisted of a lot of brainstorming. The individual participants prepared themselves, mainly at their own workspace home in the company. Asked why, the answer was that this was routine work, and for that purpose the existing structure served well. The incubation phase was not experienced as a real transition. The studio space provided tranquility and this was supported by sufficient space and light colours, availability of many objects, both familiar and strange. The view to outside where people would pass, sit for drinks in the sun provided a continual variation of view, very different from the one at the company site. Incubation just happened between weeks of intensive collaboration. It must be stated that this innovation is above all incremental. Novelty is needed and patentability is an important issue, still the process was incremental. Insights were explained to happen in communal sessions, where well-prepared experts presented their revised studies for the others. The close vicinity of the wood and metal workshops enabled the innovators to jump to simple models to explain the principles. The recordings of previous sessions were always present, easy to access and the bulletin board and tables displayed previous attempts. According to the company and the designers who manage the studio the process is very successful and the collaboration has lasted for several years. This gives an accumulation of recorded material and experience which itself is useful. It seems that the changing place may be a factor, since isolation from disturbances may be a factor. The inconvenience of bringing information from the company to the studio goes in a contrary direction. Most of the effects should be due to the spatial issues. Only seating arrangements have been changed during sessions. Private space for contemplation and concentration is available and frequently used.
Conclusions A limitation in this study is the lack of comparative situations. Csikzentmihalyi (1996) raised this as a general issue in creative studies. An experiment could be set up where two teams are given similar assignments but different spatial conditions. This means that the case is only an example of how some companies deliberately use physical space as a toll in their creative pursuits. In this paper, we
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have discussed the spatial requirements during different stages of creative processes. The article suggests that there are differences in the requirements between the stages. The preparation and elaboration stages typically require a combination of communal and private space. The incubation and insights stages probably require more private space. For example, useful information presented in the nature of objects, artifacts, tables, images, tabletops etc. can facilitate the process at an implicit level.
References Alexander, C., Ishikawa, S. and Silverstein, M. (1977) A Pattern Language Towns Buildings Construction. New York, Oxford University Press. Baldassare, M. (1978) Human Spatial Behavior. Annual Review of Sociology, 4, 29–56. Bargh, J. and Barndollar, K. (1996) Automacity in Action: the Unconscious as Repository of Chronic Goals and Motives. In Gollwitzer P.M. and Bargh J.A. (eds), The Psychology of Action. The Guilford Press, New York, pp. 3–51. Brann, E.T.H. (1991) The World of Imagination Sum and Substance Landham. Rowman & Littlefield Publishers Inc, Maryland. Ching, F.D.K. (1996) Architecture Form, Space, and Order, 2nd edition. John Wiley & Sons Inc., New York. Christensen, C.M. (1997) The Innovators Dilemma When New technologies Cause Great Firms to Fail. Harvard Business School Press, Boston MA. Clark, A. (1997) Being There: Bringing Brain, Body and the World Together Again. MIT Press, Cambridge MA. Clark, A. (2001) Mindware An Introduction to the Philosophy of Cognitive Science. Oxford University Press, New York. Csikszentmihalyi, M. (1996) Creativity Flow and the Psychology of Discovery and Invention. Harper Collins, New York. Csikszentmihaly, M. and Sawyer, K. (1995) Creative Insight: The Social Dimension of a Solitary Moment. In Sternberg, R.J. and Davidson, J.E. (eds), The Nature of Insight. MIT Press, Cambridge MA, pp. 329–63. Dorfman, J., Shames, V.A. and Kihlstrom, J.F. (1997) Intuition, incubation, and insight: Implicit Cognition in Problem Solving. In Underwood, G. (ed.), Implicit Cognition. Oxford Science Publications, Oxford. Feynman, R. (1985) Surely You are Joking Mr. Feynman! Adventures of a Curious Character. New York, Bantam Books. Gedenryd, H. (1998) How Designers Work. PhD dissertation, Lunds University, Lund, Sweden. Gick, M. and Lockhart, R.S. (1995) Cognitive and Affective Components of Insight. In Sternberg, R.J. and Davidson, J.E. (eds), The Nature of Insight. MIT Press, Cambridge MA. Hadamard, J. (1945) The Psychology of Invention in the Mathematical Field. Dover, New York.
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Hall, E.T. (1968) Proxemics. Current Anthropology, 9(2–3), 83–108. Haugeland, J. (1995) Having Thought. MIT Press, Cambridge MA. Hillier, B. (1996) Space is the Machine, Cambridge University Press, Cambridge. Horn, R.E. (1998) Visual Language Global Communication for The 21st Century MacroVU, Inc., Bainbridge Island, Washington. Hurley, S. (1998) Cognition in Action Cambridge. Harvard University Press, Boston MA. Hutchins, E. (1995) Cognition in the Wild. MIT Press, Cambridge MA. Ippolitto, M.F. and Tweeney, R.D. (1995) The Inception of Insight. In Sternberg, R.J. and Davidson, J.E. (eds) The Nature of Insight. MIT Press, Cambridge MA. Johnson, M. (1987) The Body in The Mind The Bodily Basis of Meaning, Imagination and Reason. The University of Chicago Press, Chicago. Kelley, T. with J. Littman (2001) The Art of Innovation Lessons in Creativity from IDEO, America’s Leading Design Firm New York, A Currency Book. Doubleday, New York. Kirsh, D. (1995) The Intelligent Use of Space. Artificial Intelligence, 73, 31–68. Kirsh, D. (2001) The Context of Work. Human Computer Interaction, 16, 305–22. Lakoff, G. and Johnson, M. (1999) Philosophy in the Flesh the Embodied Mind and Its Challenge to Western Thought. Basic Books, New York. Lawrence, D.L. and Low, S.M. (1990) The Built Environment and Spatial Form. Annual Review of Anthropology, 19, 453–505.
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LeDoux, J. (1998) The Emotional Brain. MacMillan, New York. Newell, A. and Simon, H. (1972) Human Problem Solving. Prentice–Hall, Englewood Cliffs NJ. Nordberg-Schulz, C. (1970) Space, Existence and Architecture. MIT Press, Cambridge MA. Reddy, M.C., Dourish, P. and Pratt, W. (2003) Coordinating Heterogenous Work: Information and Representation in Medical Care. In Proceedings of the European Conference on Computer Supported Cooperative Work (ECSW’01). Kluwer Academic Publishers, Dordrecht. Simon, H.A. (1996) Sciences of The Artificial, 3rd edition. MIT Press, Cambridge MA. Sternberg, R.J. and Davidson, J.E. (eds), The Nature of Insight. MIT Press, Cambridge MA, pp. 329– 63. Sundstrom, E., Herbert, R.K. and Brown, D.W. (1982) Privacy and Communication in An Openplan Office: A Case Study. Environment and Behavior, 14(3), May, 379–92. Wallas, George (1926) The Art of Thought. Harcourt Brace Jovanovich, New York.
Tore Kristensen is at Copenhagen Business School, Solbjerg Plads 3, DK-2000 Frederiksberg C., Denmark. E-mail:
[email protected]
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Design Dialogue Groups as a Source of Innovation: Factors behind Group Creativity Hans Björkman Sif – a Swedish national trade union for white-collar workers in Industry – has recognized the importance of enhancing its service innovation processes through careful listening to its members. This article will discuss the Design Dialogue Group (DDG) methodology that has been developed through collaborative research between Sif and the Fenix Research Program, in order to enhance group creativity and organizational learning. The emphasis of this paper is restricted to the issue of enhancing group creativity, and literature and empirical data will be used in order to discuss the factors enabling and restraining creativity. The major assumption behind this study is that many factors behind group creativity can be controlled. Thus, a careful design of the group creativity process would increase the likelihood for success since measures to enhance creative behaviours and to avoid pitfalls can be planned and/or taken by a group moderator. In short, the aims of this study are twofold: (1) to relate prior research contributions to DDG experiences in order to augment our understanding concerning factors enhancing and threatening creativity in DDG settings and (2) to systematize these findings into a set of proposed design principles related to domain-relevant skills, creativity-related processes, and task motivation. These propositions concern the recruitment of participants, group characteristics, and group processes.
Introduction
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any organizations face problems related to their innovation processes. Gathering customers, consumers or users in order to develop innovative ideas, to further develop existing concepts or to refine products or services in different kinds of user groups has been an important and growing practice for some time. Sif – a Swedish national trade union for white-collar workers in industry, has recognized the importance of enhancing its service innovation processes through careful listening to its members. This article will discuss a methodology that has been developed through collaborative research between Sif and the Fenix Research Program in order to enhance group creativity and organizational learning. The emphasis of this paper is restricted to the issue of enhancing group creativity, thus the literature and empirical data will focus on factors enabling and restraining creativity. © Blackwell Publishing Ltd, 2004. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
Researchers have found that creativity is one critical factor among others behind innovation. On a more general level, creativity is a topic of wide scope that is important at several levels. Creativity is relevant at the individual level, for example in problem solving, and at a societal level, creativity can lead to new scientific findings and new inventions. To remain competitive, individuals and organizations must adapt existing resources to changing task demands (Sternberg & Lubbart, 1999). While several definitions of creativity have been offered (e.g. divergent thinking as fluency (the ability to produce a large number of ideas), flexibility (the ability to produce a wide variety of ideas), originality (the production of unusual ideas) and elaboration (developing or building on other ideas) (Guilford 1967), we have chosen the definition put forth by Amabile (1996) as the development of novel ideas that are useful. This study focuses on issues related to group creativity and is based on the
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researcher’s prior experiences and research related to the development and evaluation of the Design Dialogue Group (DDG) method. Experiences from numerous DDG settings indicate that group results were to some extent evaluated as being creative, group participants evaluated their contributions as being creative and the design dialogue platform has been subsequently been extensively used in the organization. Thus, it makes sense to delve into the issue of group creativity to investigate behaviour in group settings and to develop road maps in order to enhance group performance regarding creativity. The aims of this study are twofold: (1) to relate prior research contributions to DDG experiences in order to augment our understanding concerning factors enhancing and threatening creativity in DDG settings and (2) to systematize these findings in a set of proposed design principles. After a brief presentation of the DDG method, a model for group creativity is presented, followed by a section where design principles for group creativity are proposed. Lastly, conclusions and managerial implications are presented.
The Design Dialogue Group The development of the DDG methodology is part of a long-term project aiming at strategic renewal of Sif as a trade union and has been organized in collaboration with the Fenix Research Program. The author has been employed by Sif for many years and is currently concluding his PhD studies in the Fenix Program. Additionally, the author has been involved in preparations and evaluations of all sets of sessions and has also moderated many DDGs. A more thorough description of evaluation results from one particular set of sessions aiming at developing activities for managers has been published elsewhere (Björkman, 2003). In short, the DDG methodology is similar to focus group methodology. The focus group methodology has become popular in market research because of its ability to produce rapid results with high face validity and involve many participants at a comparably low cost. The method is friendly and respectful (Frey & Fontana, 1993; Kreuger, 1994). The focus group methodology originates from sociological and mass media research during the 1940s. Merton used the notion ‘focused interview’ for this qualitative method for studies of attitudes, values and complex phenomena that occurred in social interactions in the 1950s (Merton, Fiske and Kendall, 1990). Some properties are common to most definitions of focus groups
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(Bormann, 1972): the purpose is to collect qualitative data, the participants have something in common and the discussions are held from a specific focus, e.g. a film, a specific event, a scenario, a specific notion or an imaginative theme. A typical focus group consists of four to twelve participants and a moderator. The group interview duration may vary with one and a half to four hours as being normal (Edmunds, 1999). Frey and Fontana (1993) define focus groups as structured and formal, while brainstorming groups are unstructured with the leaders non-directing. Others claim that the role of the moderator in a focus group may vary from non-directing to strongly directing. Millward (1995) claims that the moderator may control what is discussed and the process. What is discussed should not be strongly controlled in a focus group. The control over the process normally varies during the focus group meeting. While the majority of focus groups are organized by market research consultants as assignments from the organizations that will use the results, DDGs are focus groups that are organized by the organization to use the collected data in its own developmental processes Furthermore, the specific properties that distinguish DDGs from traditional focus groups are the following: • participants are invited to a session by the organization in which they are members (or potential members); • the sessions are moderated by an organizational member (a Sif employee); • the sessions are generally held on the organization’s premises; • the sessions not only have the purpose of bringing experiences and ideas to the organization, but also create relations between the participants and between the participants and the organization; • the sessions are video recorded and followed on a TV-screen by a group of organizational employees in order to enhance the learning in the organization; and • all sessions are evaluated by the participants. The methodology has been used in Sif with a wide array of purposes: • the development of activities for managers; • the mapping of competencies and skills required for members in the construction consultancy industry; • preparations of two national negotiating rounds; • the development of a virtual community platform for members; and
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• the development of tools for web-based learning related to individual and trade union rights and obligations in the labour market. There are three distinctive phases in the DDG process: (1) recruitment of participants, (2) execution of the group session and (3) evaluation of the process results during which research findings and results are assessed and analysed by the engaged group participants and internal service developers. In most cases, the recruitment has been conducted by an external market research firm, from directives concerning the participants’ professional occupation and other factors. An example of a typical group session (in this case targeting managers) is given to illustrate its work procedures. The dialogue group meeting was held as a two-hour session, mediated by the author. The discussions focused on three aspects: • ‘Being a manager’ – situation, role, opportunities, threats; • ‘How can the managers’ role and situation be improved’ – what kind of knowledge and skills needed to be developed?; • ‘What could “external parties” (such as trade unions) do to enhance the managers’ situation?’. Each of these aspects were described by each participant after a short time for individual reflection and discussed in the group. Documentation by the dialogue groups and analysis of the video recordings were used to produce a list of service ideas that had been discussed. This service idea list was then used in the evaluation process. For this study, all sessions were evaluated, with participants assessing the DDG method very positively. Their assessments related to group creativity and individual creative contributions have also been very positive. The
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assessments made by internal service developers have resulted in the following: • some ideas are assessed as creative; • many ideas are expressed at a systems level rather than at a detailed level; • many ideas are reproducible; • ideas assessed as creative are evaluated as less reproducible than other ideas; and • the capacity in the organization to use newly obtained ideas is a problem. Two specific examples will be used here in order to exhibit evaluated issues and results. The first is from the pilot study, during which the DDG methodology was initially developed. The participants individually assessed the method by considering various proposals. The results were measured on a 1 to 10 scale where 1 = disagree and 10 = agree completely (Table 1). In the second example, the participants’ evaluation of 12 DDG sessions related to the development of a virtual community platform for members show similar results. An overall performance index was created from items related to assessed opportunities to make oneself heard in the group, group involvement in the task, group creativity, individual involvement in the task, individual creativity, the quality of the exchange of ideas and experiences, whether it was worth the time to participate and whether the group contributed important ideas to Sif. The individual assessments of the sessions have been strongly positive. Group means on the performance index were from 7.35 to 9.21, with a group average of 8.59. The group means of the assessments concerning group creativity ranged from 7.57 to 9.75, with a group average of 8.70, while the group means of the assessments of individual creativity ranged from 5.60 to 9.17, with a group average of 8.02. The results indicate that participants assess the methodology and their contributions very positively.
Table 1. Evaluation made by participants (managers in industry, pilot study) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
It is not easy to find the time to participate in this kind of meeting It has been easy to understand how to work in the group The work in the group has not been too strongly moderated It has been easy to make oneself heard in the group The group has been engaged in its task The group has been creative I have been engaged in the group I have been creative in the group I have participated in an interesting exchange of ideas and experiences It was worth the time to participate The group has contributed important ideas to Sif
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7.7 7.1 7.6 9.4 9.2 9.0 8.7 8.4 8.7 8.7 7.7
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A Model for Group Creativity
Creativity-related Processes
Individual traits, behaviour and backgrounds have been in focus in the majority of creativity studies (Williams & Yang, 1999). In this study, a basic creativity model (Figure 1) has been developed from Amabile’s (1996) components of creative performance. Her basic model has been modified in order to include contributions from focus group theory, the group creativity literature and the creative climate model, developed by Ekvall (1996). The notions derived from the literature have then been adapted to the DDG setting, whereupon the model has been developed. The purpose of the model is to exhibit and operationalize factors that need to be considered in the design dialogue context. The creativity components in the model will be discussed, developed and refined below.
Domain-relevant Skills The role of domain-relevant skills in the production of creative work has received scant attention from researchers, but there is some evidence that exposure to a wide array of information in a domain can enhance creativity (Amabile, 1996). Special domain-relevant talent, which has been discussed by Amabile as an outstanding level of skills, shows resemblance to domain-relevant expertise. In the DDG setting, the moderator may be an expert on the issues to discuss, an expertise perhaps also shared by some participants. However, it can be debated whether expertise enhances creativity. Recent research has shown that experts may contribute fewer original ideas than average users (Magnusson, 2003).
1. Domain-relevant skills Includes: ∑ knowledge about the domain ∑ requisite technical skills ∑ special domainrelevant ‘talent’ or expertise Depends on: ∑ the participants ∑ the moderator
The focus group literature and research related to brainstorming methodologies discuss the matter of group size. Research has shown that groups consisting of eight people produced more ideas than groups consisting of four people, but that smaller groups generated more ideas per participant (Fern, 1982). Comparisons on brainstorming methodology used by individuals and by groups have shown that individual performances may be more productive than group performances (Rickards, 1999). Other factors related to group composition refer to the familiarity between the participants – with one suggestion being that in the ideal situation, none of the participants know each other – and the homogeneity of ages and sex (Greenbaum, 1998, 2000). Group creativity is related to the design of the group sessions, and in the DDG case, to the skills and actions taken by the moderator. In the DDG setting, work procedures are developed before each set of group sessions. Creativity is enhanced by a cognitive style characterized by a facility in understanding complexities and an ability to break sets during problem solving (Amabile, 1996). A DDG typically consists of people with different individual cognitive styles. The challenge is to create a form of interaction between the participants, thereby enhancing creativity through the mixture of cognitive styles (Paulus, 2000). Focus group theory suggests that the interaction in focus groups is less artificial than in more elaborate experimental situations. Group interviews are often considered to be enjoyable and interesting – the participants share experiences (Hylander, 2001). The group enables the individuals to open up (Kreuger, 1994). Attitudes are created in inter-
2. Creativity-relevant processes Includes: ∑ appropriate cognitive style ∑ implicit or explicit knowledge of heuristics for generating novel ideas ∑ conducive work style Depends on: ∑ group composition ∑ work procedures ∑ the moderator
3. Task motivation Includes: ∑ attitudes towards the task ∑ perceptions of one’s own motivation for undertaking the task Depends on: ∑ intrinsic motivation toward the task ∑ abilities to control extrinsic motivation factors ∑ the creative climate
Figure 1. Creative Components in a Design Dialogue Group Context: a Basic Model
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action with others, thus the focus group method becomes isomorphic with natural attitude creation processes. Moreover, thoughts and feelings may be easier to describe and express after listening to others (Morgan, 1997). Theories of group creativity express similar experiences. Utterances of members may contain task-related stimuli that elicit new ideas from other members (Pinsonneault et al., 1999). Members can learn from and imitate best performers, hence increasing group productivity (Pinsonneault et al., 1999). Working in groups stimulates individuals to perform better (Pinsonneault et al., 1999). Novel associations may be created through the mutual stimulation of associations, increasing the chances that one will come across ideas or categories one would not have thought of in a solitary session (Paulus, 2000). Knowledge and the use of heuristics is another important creativity-relevant component (Amabile, 1996, p. 89). A heuristic can be defined as ‘any principle or device that contributes to a reduction in the average search to solution’ (Newell, Shaw and Simon, 1962, p. 78). The use of heuristics/methods enabling creative performance may be explicit (the overt application of a specific method) or implicit (embedded in the moderating activities). Brainstorming techniques (Osborn, 1963) and other specific techniques aiming at enhancing creativity (see de Bono, 1992) may be examples of usable heuristics as well as more general problem-solving methodologies, such as SWOT-analyses. A work style conducive to creative production has several features, such as an ability to concentrate effort and attention (Amabile, 1996; Campbell, 1960; Hogarth, 1980; Prentky, 1980), an ability to abandon unproductive search strategies and temporarily put aside stubborn problems (Simon, 1966), a persistence in the face of difficulty (Roe, 1953; Walberg, 1971), and a high energy level, a willingness to work hard and an overall high level of productivity (Amabile, 1996; Bergman, 1979; Bloom, 1956; Davis & Rimm, 1977; Simonton 1980; Wallach & Kogan, 1965). So far, we have not discussed difficulties related to group creativity. However, there are several factors related to group interaction and work style that may be detrimental to creativity, such as evaluation apprehension, free riding/social loafing, production blocking, compliance and pressure for cognitive uniformity/conformity. Evaluation apprehension relates to the risk that productivity is impaired when members fear expressing ideas because of potential retaliation (Amabile, 1996; Paulus, 2000; Pinsonneault et al., 1999). Free-riding refers to the motivated, intentional with-
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drawal of efforts. Members might limit their efforts and contributions by relying on others to accomplish the task because of: (1) perceived dispensability of one’s effort; (2) diffused responsibility or (3) social and cognitive loafing, i.e. to be less motivated when individual contributions are combined as a group product (Paulus, 2000; Pinsonneault et al., 1999). Production blocking occurs in groups as only one can talk at a time, and ideas may be forgotten while waiting for the moment to express them (Paulus, 2000). Being unable to express ideas as they occur impairs productivity because ideas become irrelevant, people forget their ideas and people rehearse ideas to avoid forgetting ideas, which may prevent them from generating new ideas (Pinsonneault et al., 1999). Compliance occurs when participants give the answers the moderator is assumed to want (Albrect, Johnsson and Walther, 1993; Kelman, 1961). Lastly, pressure for cognitive uniformity/conformity indicates that members may feel pressure to remain within group or social norms (Pinsonneault et al., 1999).
Task Motivation Motivational variables in creativity have been given some attention by theorists. Intrinsic motivation arises from the individual’s positive reaction to qualities of the task itself: interest, involvement, curiosity, satisfaction, and positive challenge (Amabile, 1996). A person is said to be intrinsically motivated to engage in an activity if that person views such engagement as an end in itself and not as a means to some extrinsic goals (deCharms, 1968; Deci, 1975; Lepper & Greene, 1978). Extrinsic motivation arises from sources outside the task itself: evaluation, contractedfor rewards, external directives etc. (Amabile, 1996). The importance of intrinsic motivation and a freedom from extrinsic constraints has been expressed by theorists working within philosophy, humanistic psychology and social psychology (Amabile, 1996; Crutchfield, 1962; Koestler, 1964; Rogers, 1954). Amabile (1996, p. 119) has formulated ‘The Intrinsic Motivation Principle of Creativity’: Intrinsic motivation is conducive to creativity; controlling extrinsic motivation is detrimental to creativity, but informational or enabling extrinsic motivation can be conducive, particularly if initial levels of intrinsic motivation are high. The mechanisms of positive extrinsic factors have thus been described as extrinsics in service of intrinsics and the motivation-work cycle match (Amabile, 1996, p. 118). Extrinsics in service of intrinsics are defined as extrinsic factors that
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support one’s sense of competence or enable deeper involvement with the task, without undermining one’s sense of self-determination. The motivation-work cycle match notion suggests that extrinsic motivation may work in synergy with intrinsic motivation during those specific phases in the creative process, where the novelty of the outcome is of less importance. Thus, successful problem identification and response generation phases may require intrinsic motivation that is unencumbered by significant extrinsic motivation. Amabile has also identified general socialenvironmental influences on creativity. Positive influences that are likely to have a direct impact on intrinsic motivation are autonomy/sense of control, importance/ urgency in one’s work, optimal challenge and task matched to interest. The other positive influences that are likely to serve as synergistic extrinsic motivators are sufficient resources, recognition/reward that confirms competence, reward that enables intrinsically interesting work and sufficient task structure to support competent performance. Negative influences emanate from threatening critical evaluation connoting incompetence, expectation of critical evaluation, surveillance, contracted-for reward-connoting, restricted choice/constraint control, arbitrary/unrealistic deadlines and competition with co-workers. Dimensions related to organizational climate for creativity and innovation, as developed by Ekvall (1996), imply further factors to be explored. He has found ten dimensions, which will be used and discussed in the next section: challenge, freedom, idea support, trust/openness, dynamism/liveliness, playfulness/humour, debates, conflicts, risktaking and idea time.
The Developed Creativity Model In the section above, the concepts of the earlier exposed basic model for group creativity in the DDG context were further developed. The discussion is summarized in Figure 2.
Designing for Group Creativity – a Matter of Balance and Control Empirical data and theory indicate that creative actions and results are to a high extent dependent on process design and control. Experiences from DDG sessions have indicated the importance of design features such as careful recruitment of participants, preparation of the moderator and design of work procedures while shortcomings related to
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recruitment errors, insufficiently prepared moderators or poorly designed work procedures have resulted in less successful group performances. In this section, the creativityrelated factors in the model will be discussed in the DDG context. DDG experiences will hence be used in order to propose specific design principles.
Organizing Domain-related Skills During the recruitment process, the selection of participants with domain-related skills is facilitated by the potential participants since they must confirm that they belong to the targeted group (e.g. managers). Nevertheless, in a typical dialogue design group, the participants differ strongly along several dimensions, such as experience and industry/sector background. Thus, it is important that there is a balance between the diversity among the participants and the task to be executed. Task design and group design can thus not be executed separately. There is strong evidence that domainrelevant skills are essential while highly specific expertise may not always be required. The recruitment model used for the DDGs has resulted in groups where few highly specified experts at the group task have been identified, which may be due to the relatively wideranging group tasks. Opportunities for selecting moderators with domain-relevant skills are more evident. Internally recruited moderators have the advantage of familiarity with the domain. Another advantage is embedded in his or her relationship with the participants since it is more likely that an internal moderator will be seen as genuinely knowledgeable and interested in the issues discussed. Two kinds of moderators have been used: those who have been familiar with the task and those who are experts. Even though no specific assessment has been made, it seems that moderators who are experts at the task may have a small advantage. This advantage may be explained as being related to a better ability to explain the task to the participants and to delve into the most interesting issues during the group sessions. Arising from theoretical considerations and our experience, the following design principles are proposed: A1 If potential participants are given sufficient target group and task information, their pre-assessment of their own domainrelevant skills will contribute to the selection of individuals with such skills.
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1. Domain-relevant skills Includes: ∑ knowledge about the domain ∑ requisite technical skills ∑ special domainrelevant ‘talent’ or expertise Depends on: ∑ the participants and their level of expertise ∑ the moderator and his or her level of expertise
2. Creativity-relevant processes Includes: ∑ appropriate cognitive style ∑ implicit or explicit knowledge of heuristics for generating novel ideas ∑ conducive work style Depends on: ∑ group composition ∑ size ∑ sex and age ∑ work procedures ∑ conduciveness to appropriate cognitive and work styles ∑ use of heuristics ∑ the moderator ∑ conduciveness to appropriate cognitive and work styles ∑ knowledge of heuristics
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3. Task motivation Includes: ∑ attitudes towards the task ∑ perceptions of one’s own motivation for undertaking the task Depends on: ∑ intrinsic motivation toward the task ∑ interest, involvement, curiosity, satisfaction and positive nature of challenge ∑ abilities to control extrinsic motivation factors ∑ possible enabling factors: sufficient resources, recognition/reward that confirms competence, reward that enables intrinsically interesting work and sufficient task structure to support competent performance ∑ negative factors: threatening critical evaluation connoting incompetence, expectation of critical evaluation, surveillance, contracted-for reward-connoting, restricted choice/constraint control, arbitrary/unrealistic deadlines and competition with co-workers ∑ the creative climate ∑ the degree of challenge, freedom, idea support, trust/openness, dynamism/liveliness, playfulness/humour, debates, conflict, risk-taking and idea time
Figure 2. Creative Components in a Design Dialogue Group Context: an Extended Model A2 Participants with high levels of domainrelevant skills (experts) may be detrimental to creativity since they tend to produce ideas of less originality. Rather, their ideas may be easier to use in the development of new activities, services and products. A3 Internally recruited moderators have an advantage in comparison with external consultants as they are more familiar with the domain and are perceived by the participants to be familiar with and engaged in the task. A4 Internal moderators, who are experts at the task, may have an advantage in the interaction with participants and in terms of focusing discussions on important issues.
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Organizing Creativity-related Processes The creativity-related skills of the participants cannot be controlled in advance of the DDG setting. Thus, the usage of these skills is a matter of how the creativity-related processes are designed and controlled. In the model, this depends on three factors: (1) group composition, (2) the design of the work procedures for the group session, and (3) the skills obtained by the moderator. The first specific design factor is related to group size and composition. In the Sif case, the DDG size has varied from three to nine people. No specific differences in the participants’ assessment of the group sessions could be related to group size. The nature of the group tasks has not called for homogenous groups related to age or sex. On the contrary, the recruitment has aimed at
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securing an equal participation of women and men in the groups. Another design factor is related to the relations between group members. In general the participants have either not known each other in advance or have they were not colleagues, but in a few cases some of the participants were colleagues – in one case all of them were colleagues. We have not observed inferior results from these groups consisting of colleagues, but the data are not sufficient for drawing any conclusions. However, we feel that the very open-minded reflections on personal issues in groups consisting of managers are unlikely to have taken place if the managers had been colleagues. In brief, the design of work procedures is always carried out by a group consisting of the project manager for the project in which the results will be used (or the project group), at least one experienced moderator, other moderators who are going to participate and a DDG administrator. New moderators are carefully selected by the project manager and the experienced moderator. Although the selection criteria have never been clearly stated, open-mindedness and a conduciveness towards inquiry rather than advocacy (Argyris, Putnam and McLain Smith, 1995) are important individual traits. New moderators are given information about the method and they are obliged to follow at least one DDG session before they act as moderators. In general, a set of groups (4–12) is conducted within a project. The first group is moderated by an experienced moderator. If necessary, the work procedures are redesigned after the first session and thereafter continuously between the group sessions. In DDG settings, an appropriate cognitive style (Amabile, 1996) has an impact on task motivation and results. The specific challenge lies in the creation of cognitive stimulation (Paulus, 2000) and synergy through group interaction. Thus, the positive properties of this form of group interactions, which are related to the sharing of experiences in an interesting and enjoyable manner, are used (Hylander, 2001). The group enables people to open up (Kreuger, 1994) as attitudes and ideas are created in interaction with others. Experiences and ideas are contributed by individual participants or by smaller groups and then discussed in the group as a whole. In the work procedures developed in advance, different kinds of creativity-related heuristics are important elements. As discussed later, typical work procedures include a mixture of individual assignments and group exercises. Methodologies such as SWOT-analyses (Strengths, Weaknesses, Opportunities and Threats) and the grouping
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of experiences and ideas into families/groups are regularly used. The work procedures are designed in order to induce a work style conducive to creative production in the DDGs. This means that problems related to ideas created are not discussed, because idea evaluation is not conducted during the sessions. Each individual assignment or group exercise is strictly limited in time: generally five to fifteen minutes are consumed per assignment/exercise. This, in combination with the division of tasks into sub-tasks and clearly formulated rules for presentation of results, enhances the opportunities for the creation and maintenance of a high energy level and a high level of productivity. Another important moderator role is to enhance productivity through appreciative behaviour towards the participants, expressing an interest in the experiences and ideas they bring into the discussion. However, creativity may be hampered by factors related to group interaction and work style, and these factors need to be controlled. Threatening factors mentioned in the model discussion included evaluation apprehension, free riding/social loafing, production blocking and groupthink. It should be made clear to the participants that their ideas will not be evaluated during the session and that they are participating anonymously – the experiences expressed and ideas created will not be related to them as individuals or to a specific DDG during the evaluation and idea-refinement processes following the group sessions. Therefore, evaluation apprehension does not seem to be a major obstacle. Free-riding or social loafing may occur during the sessions. The moderator has an important role in listening to all participants and in asking questions to the quieter participants in order to make them active. It should be clearly stated at the beginning that the group effort as well as the individual experiences and ideas is important. The individual responsibility is evident during the individual assignments. Taken together, freeriding is handled, but may still be a problem. Production blocking could be a major problem in group processes. However, the mix between individual assignments and group exercises makes the problem less evident than if the whole sessions were organized on a group basis. Groupthink may be addressed through challenging questions from the moderator, but it may still occur as a problem. Generally, several DDGs are organized around a specific theme. Thus, the risk of overall results being blurred by groupthink is reduced. Thus, arising from theoretical considerations and our experience, the following design principles are proposed:
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B1 The mixture of individual assignments and group exercises enhances participants’ involvement and results in a broader description of experiences as well as in more ideas than if individual assignments are not used. B2 Evaluation apprehension may be controlled when guarantees are given that the results will not be traced to individuals or to specific groups. B3 Group productivity tends to be high when tasks are divided into specific sub-tasks which are dealt with under strict time limits and result-presentation rules are clearly stated. B4 The moderator’s ability to engage all participants is a critical factor in the DDG setting.
Organizing for Task Motivation Three notions related to task motivation have been used in the theory section: intrinsic motivation, extrinsic motivation and climate. Intrinsic motivation relates to the individuals’ reaction to qualities of the task itself: interest, involvement, curiosity, satisfaction and positive challenge (Amabile, 1996). Extrinsic motivation originates from sources outside the task itself, while climate factors may affect both intrinsic and extrinsic motivation. The propensity for high intrinsic motivation among the participants in DDG is relatively high. In most cases, the participants are members of the organization, paying a monthly fee and at least occasionally using services offered. People who are not initially interested in the task do not participate. The method aims at involving participants on the basis of their own experiences and wishes. As the task is not precisely specified during the recruitment process, participants tend to be curious in relation both to the task and the group process itself. The moderator initially expresses the task in order to present positive challenges to the participants. In most cases, the task and the division into sub-tasks, which needs to be conducted in only a few minutes, keep the levels of energy and interest high. However, the time limits may put too great a pressure on participants, thus reducing their intrinsic motivation. This and other threatening factors will be dealt with later in this section. The enabling climate factors found by Ekvall (1996) are related to both intrinsic and extrinsic motivation. A motivating culture provides challenge. Participants in DDGs are committed and the goals for the session are known and accepted. In most cases, everyone feels
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that his or her contributions are important. Freedom is in many ways limited for the participants in DDGs. However, no one is forced to participate, and there is a freedom to express attitudes and ideas. The moderator has an important role related to idea support. Novel ideas and thoughts are openly accepted since the creation of these is the major purpose of the sessions. It can at first be perceived as difficult to establish trust and security in a group where the participants do not know each other. The experience from DDG sessions is the opposite, which may be explained by the fact that the participants are not dependent on other participants or on the group results. This enables the creation of a common sense of trust and security. Obviously, the moderator is important, because his or her presence is a critical factor in this respect. Dynamism and liveliness indicate that new issues and methods are continuously introduced. This is definitely the case during the DDG sessions. The atmosphere during the sessions is, in spite of time pressures, designed to be relaxed, which opens up possibilities for playfulness and humour. There are, however, big differences between different groups in this respect and between moderators. Debates are not equally lively in all groups. A specific problem has been identified in large groups (seven people or more). On the one hand, individual assignments are very important in these groups in order to let everyone have his or her say. On the other hand, the exposition of results from many participants tends to reduce the available time for debate and dialogue. Risk taking may in this setting refer to one’s ability to step outside the limits set by the work procedures decided upon. It may be the case that the moderators have been too rigid in not letting interesting discussions continue. Lastly, the DDG method is problematic considering idea time. The time format is limited, often to two hours and attempts to collect participants’ reflections after the sessions have not been successful so far. From this brief discussion concerning enabling climate factors in the DDG setting, an important experience is related to the methodology’s ability to create trust and security among people who do not know each other. Other useful positive influences that are not covered by Ekvall have been derived from Amabile’s (1996) general socio-environmental influences on creativity. One factor is sufficient resources in cases where the DDG participants may meet problems due to lack of time, the absence of tools and insufficient background information. Recognition that confirms competence is continuously given by the moderator,
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while rewards confirming competence and enabling intrinsically interesting work are lacking – a small gift is given to everyone after the session, but this has not been known by the participants in advance. As discussed above the sessions are organized in order to provide a sufficient task structure to support competent performance. Among factors having a negative impact on creativity, Ekvall (1996) refers to conflict. So far, this has seldom shown to be a problem in DDGs. Amabile (1996) discusses threats related to expectations of critical evaluation. As shown above, this is not problematic in the DDG setting either. Surveillance could be threatening creativity, and the presence of a moderator – and people following the session on a TV monitor – could be a problem. When the moderator leaves the room during group exercises, discussions often tend to be more engaged. Participants are not contracted for a reward, which could have been problematic. Certainly, there are problems related to restricted choice/constraint control and unrealistic deadlines. Competition with co-workers may also be a problem because the time for expressing ideas and opinions is limited. Thus, arising from theoretical considerations and our experience, the following design principles are proposed: C1 Voluntary participation enhances task motivation. C2 Participants who are members of the organization and thus having a relationship with the session organizer are more task-motivated than non-members. C3 A DDG climate characterized by trust and security is more likely to be established if participants have no former relations with each other.
Conclusions and Practical Implications Based on theoretical studies and experiences from DDGs, a number of design principles have been proposed in three areas: domainrelevant skills, creativity-related processes and task motivation. These design principles include propositions concerning recruitment of participants, group characteristics and group processes. The aim of this paper has not been to propose a comprehensive list of design principles. Many more principles could be formulated and the proposed design principles may be developed and refined. Through additional research and testing of the principles, their scope and limitations could be explored and
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expressed further. Findings up to this point indicate that the issue of organizational learning and action-taking based on learning from group participants may be even more important than the issue of enhancing group creativity, at least in the organizational context studied. Hence, a study of organizational learning is in progress. A careful design of the group creativity process increases the propensity for success since measures in order to enhance creative behaviours and to avoid pitfalls can be planned and/or be taken by a group moderator. The main practical implication is that organizations involved in a high level of market interaction could successfully organize customer/user/member involvement in developmental processes on their own. This may be an opportunity for organizations with long-term relationships with their target groups, because it is likely that existing relations enhance performance in the processes where involvement takes place. Moreover, the process itself enhances the relationships between the organization and the participants. Below is some brief advice to those who would like to experiment with this: • Tell the potential participant what you want, and he/she will then know if he/she can contribute. • Try to assemble groups in which the participants do not know each other in advance. • Do not only use participants who are experts. • Try to involve volunteers and members/ users/clients who have close relationships with you since these individuals are generally more task-motivated. • Use your own moderators. • Mix individual assignments with group exercises and divide tasks into sub-tasks. • Promise that results will not be traced to individuals or specific groups. • Enable all participants to talk. The scope of this study has been on involving users in DDGs. However, the proposed design principles may have potential in other configurations, such as on the employeeorganization level. When carefully applied, the proposed design principles may well result in group creativity in many different settings. The other major strength of the methodology – that it tends to create involved and satisfied participants – is also of interest.
References Albrect, T.L., Johnsson, M.G. and Walther, J.B. (1993) Understanding communication processes
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in focus groups. In Morgan, D.L. (ed.), Successful focus groups. Advancing the state of the art. Sage Publications, Newbury Park, pp. 51–64. Amabile, T.M. (1996) Creativity in Context. Westview Press, Boulder. Argyris, C., Putnam, R. and McLain Smith, D. (1995) Action Science. Jossey-Bass, San Fransisco. Bergman, J. (1979) Energy levels: An important factor in identifying and facilitating the development of giftedness in young children. Creative Child & Adult Quarterly, 4, 181–8. Björkman, H. (2003) Service Innovation – A Collaborative Approach. In Adler, N., Shani, A. and Styhre, A. (eds.), Collaborative research in organizations. Sage, Thousand Oaks CA. Bloom, B.S. (1956) Report on creativity research at the University of Chicago. In Taylor, C. (ed.), The 1955 University of Utah research conference on the identification of creative scientific talent. University of Utah Press, Salt Lake City. Bormann, E.G. (1972) Fantasy and rhetorical vision: The rhetorical criticism of Social reality. Quarterly Journal of Speech, 68, 396–407. Campbell, D. (1960) Blind variation and selective retention in creative thought as in other knowledge processes. Psychological Review, 67, 380–400. Crutchfield, R. (1962) Conformity and creative thinking. In H. Gruber, G. Terrell and M. Wertheimer (eds.), Contemporary approaches to creative thinking. Atherton Press, New York. Davis, G.A. and Rimm, S. (1977) Characteristics of creativity gifted children. Gifted Child Quarterly, 21, 546–51. de Bono, E. (1992) Serious Creativity. Harper Business, New York/London. deCharms, R. (1968) Personal causation. Academic Press, New York. Deci, E. (1975) Intrinsic motivation. Plenum Press, New York. Edmunds, H. (1999) The Focus Group Research Handbook. American Marketing Association/ NTC Business Books, Lincolnwood IL. Ekvall, G. (1996) Organizational Climate for Creativity and Innovation. European Journal of Work and Organizational Psychology, 5(1), 105–23. Fern, E.F. (1982) The use of focus groups for idea generation: The effects of group size, acquaintanceship, and moderator on response quantity and quality. Journal of Marketing Research, 10, 1– 13. Frey, J.H. and Fontana, A. (1993) The group interview in social research. In Morgan, D.L. (ed.) (1993). Successful focus groups. Advancing the state of the art. Sage, Newbury Park CA, pp. 20– 34. Greenbaum, T.L. (1998) The handbook for focus group research, 2nd edition. Sage, Thousand Oaks CA. Greenbaum, T.L. (2000) Moderating focus groups. A practical guide for group facilitation. Sage, Thousand Oaks CA. Guilford, J.P. (1967) The nature of human intelligence. McGraw-Hill, New York. Hogarth, R. (1980) Judgement and choice. Wiley, Chichester. Hylander, I. (2001) Focus groups – A research method for qualitative data collection, 2nd edition,
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FOG-report no 42. Department of Education and Psychology, Linköping University, Linköping. Kelman, H. (1961) Processes of opinion change. Public Opinion Quarterly, 25, 57–78. Koestler, A. (1964) The act of creation. Dell, New York. Kreuger, R.A. (1994) Focus groups: A practical guide for applied research, 2nd edition. Sage, Thousand Oaks CA. Lepper, M. and Greene, D. (1978) Overjustification research and beyond: Toward a means-end analysis of intrinsic and extrinsic motivation. In Lepper M. and Greene D. (eds.), The hidden costs of reward. Lawrence Erlbaum Associates, Hillsdale NJ. Magnusson, P.M. (2003) Customer-Oriented Product Development. Experiments Involving Users in Service Innovation. Dissertation for the Degree of Ph.D. in Business Administration, Stockholm School of Economics, Stockholm. Merton, R.K., Fiske, M. and Kendall, P. (1990) The Focused Interview. A manual of Problems and Procedures, 2nd edition. The Free Press, New York. Millward, L. (1995) Focus Groups. In Breakwell, G.M., Hammond, S. and Fife-Shaw, C. (eds.), Research methods in psychology. Sage, London, pp. 274–92. Morgan, D.L. (1997) Focus groups as qualitative research. Qualitative Research Methods Series, 16, 2nd edition. Sage, Thousand Oaks CA. Newell, A., Shaw, J. and Simon, H. (1962) The processes of creative thinking. In Gruber, H., Terell, G. and Wertheimer, M. (eds.), Contemporary approaches to creative thinking. Atherton Press, New York. Osborn, A.F. (1963) Applied imagination, 2nd edition. Scribner, New York. Paulus, P.B. (2000) Groups, Teams, and Creativity: The Creative Potential of Idea-generating Groups. Applied Psychology: An International Review, 49(2), 237–62. Pinsonneault, A., Barki, H., Gallupe, R.B. and Hoppen, N. (1999) Electronic Brainstorming: The Illusion of Productivity. Information Systems Research, 10(2), 110–33. Prentky, R.A. (1980) Creativity and psychopatology. Praeger, New York. Rickards, T. (1999). Brainstorming. In Runco, M.A. and Pritzker, S.R. (eds.), Encyclopedia of Creativity, Vol 1. Academic Press, London, pp. 219–27. Roe, A.A. (1953) A psychological study of eminent psychologists and anthropologists and a comparison with biological and physical scientists. Psychological Monographs, 76 (2, Whole No. 352). Rogers, C. (1954) Towards a theory of creativity. ETC: A Review of General Semantics, 11, 249–60. Simon, H. (1966) Scientific discovery and the psychology of problem solving. In Mind and cosmos: Essays in contemporary science and philosophy. University of Pittsburgh Press, Pittsburgh. Simonton, D.K. (1980). Thematic fame, melodic originality, and musical Zeitgeist: A biographical and transhistorical content analysis. Journal of Personality, 48, 206–19. Sternberg, R.J. and Lubbart, T.I. (1999) The Concept of Creativity: Prospects and Paradigms. In
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Sternberg, R.J. (ed.) Handbook of Creativity. Cambridge University Press, Cambridge. Walberg, H.J. (1971) Varieties in adolescent creativity and the high school environment. Exceptional Children, 38, 111–16. Wallach, M. and Kogan, N. (1965) Models of thinking in young children. Holt, Rinehart & Winston, New York. Williams, W.W. and Yang, L.T. (1999) Organizational Creativity. In Sternberg R.J. (ed.), Handbook of Creativity. Cambridge University Press, Cambridge.
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Hans Björkman is an Executive PhD Candidate at the Fenix Program at Stockholm School of Economics and a service developer at Sif, Sweden. His main research activities concern user involvement in new service development. E-mail:
[email protected]
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Measuring and Enabling Learning Behaviour in Product Innovation Processes José Gieskes and Beatrice van der Heijden It is generally acknowledged that innovation is one of the most important predictors of firm success or failure. Successful innovation processes require creating new organizational capabilities to handle the external pressure for new products and processes (fast, good and at low costs), and the internal pressure for increased efficiency and effectiveness. Under these circumstances ‘learning’ is an important issue and the increased interest for topics such as knowledge management, organizational learning and continuous improvement illustrates its relevance. Within the CIMA (Continuous Improvement in Global Product Innovation Management) research project (CIMA-ESPRIT 26056) a methodology has been developed to help companies to stimulate learning behaviour of individuals and teams in product innovation processes. By studying learning behaviour in 140 product innovation projects in 70 companies in six countries, a seemingly valid and reliable scale for measuring learning behaviour has been developed. In addition, managerial activities and decisions that are predictive for improving learning behaviour have been identified.
Introduction
A
ccording to management practitioners and scholars, organizations are faced with an increasing globalization of markets, rapid developments in technology, changing norms and values in society and increasing demands for networking within and between industries. An organization’s success (both in terms of survival and growth) ‘more and more depends on its ability to orchestrate a range of organizational, technological and human practices and change efforts of varying scope and time-horizons’ (Boer et al., 2001). Both technical and market uncertainties are high. Customer needs, the number and types of competitors, and the range of technological possibilities is all characterized by frequent and substantial change. In many industries, product innovation is the most import factor driving firm success or failure. Most solutions to handle the increased pressure focus upon creating new organizational capabilities and innovative ways to use resources. In these surroundings the attention for ‘learning’ almost emerges naturally. Cur© Blackwell Publishing Ltd, 2004. 9600 Garsington Road, Oxford OX4 2DQ and 350 Main St, Malden, MA 02148, USA.
rently, there appears to be an increased interest in knowledge, learning and (continuous improvement) in new product and innovation processes (Bartezzaghi, Corso & Verganti, 1997; Bateson, 1972; Caffyn, 1998; Cangelosi & Dill, 1965; Imai, Nonaka & Takeuchi, 1985). This article builds on research (CIMAESPRIT 26056) that was aimed to help firms to stimulate learning in their product innovation processes. Two research questions will be dealt with: (1) How can we measure learning behaviour? (2) What managerial activities and decisions stimulate the development of learning behaviour? The next section provides some theoretical background to the study of learning behaviours within product innovation processes. The third section goes into the research methodology and describes, among others, the operationalization of learning behaviours and their influencing (stimulating) managerial activities and decisions, that is, the enablers. The following section goes into the outcomes of the study followed by a final
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section dealing with the practical and theoretical implications of the outcomes.
Theoretical Background Cangelosi and Dill (1965) already addressed learning in and by organizations in 1965, followed by Bateson (1972), and Argyris (1977), to mention but a few key researchers. Interest in learning in organizations has increased a lot since the seventies (Argyris & Schön, 1978; Fiol & Lyles, 1985; Hedberg, 1981; Jelenik, 1979; Levitt & March, 1988; Pedler, Boydell & Burgoyne, 1989; Shristastava, 1993), not only by academics but also by practitioners (see Senge, 1990). Later on, researchers focused more and more on product innovation within the larger domain of learning by and learning in organizations (Nonaka, 1991). Literature on learning by organizations, i.e. organizational learning,1 in general, has a normative character. One has been engaged in developing models and methodologies for creating change by improving learning processes. Studies dealing with learning in organizations focus more on understanding the nature and processes of learning in an organizational context. It is argued (De Geus, 1988; Senge, 1990; Stata, 1989) that learning is the key to increase the firm’s competitiveness and to develop structures and systems that allow the company to adapt to changing circumstances quickly and effectively (Kanter, 1989; Peters & Waterman, 1982). Learning in and by organizations is denoted in literature as organizational learning, leading to the concept of the so-called ‘learning organization’. The concept of the learning organization as an entity in itself is often dealt with in an anecdotal way by identifying characteristics or conditions for becoming a learning organization (Garvin, 1993; Jones & Hendry, 1992; Pedler, Boydell & Burgoyne, 1989). The concept is also approached by means of normative models based upon empirical research (Goh & Richards, 1997). Several authors have started studying the issue in a normative way, but over the years they have discovered that the topic was too complex to be dealt with normatively, also realizing that the assumptions they were building on were presented as facts, without being tested or falsified (Argyris, 1996; Pedler, Burgoyne & Boydell, 1991). Despite all this interest we know relatively little about learning (processes) in organizations. Already in 1986, Fiol and Lyles had written (1985, p. 803): ‘Although there exists widespread acceptance of the notion of organizational learning . . . No theory or model of
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organization learning is widely accepted’. Since their publication the situation has not changed much. There is still a huge lack of reports on systematic empirical research (Easterby-Smith, 1997; Gieskes, 2000; Miner & Mezias, 1996).
Perspectives on Organizational Learning ‘Learning is seen as a purposive quest to retain and improve competitiveness, productivity and innovativeness in uncertain, technological and market circumstances. The greater the uncertainties, the greater the need for learning’ (Dodgson, 1993). This quote includes several difficulties in studying the learning process. First, learning is a means to an end and not an end in itself. Consequently, the output of learning should contribute to goal realization. Second, there seem to be circumstances, that is, uncertainties, that trigger the need for learning while at the same time influencing (the direction of) the learning process. A process view on organizations acknowledges that learning can be viewed as a process of information processing which can have an outcome mirroring an impact on either changes in knowledge (cognition), changes in behaviours (either individual or organizational) or both. The learning process takes place within a context (both in the meaning of the environment in which the process takes place, as well as in the form of managerial activities) that affects the process (Hedberg, 1981; Lei, Slocum & Pitts, 1997; Nevis, DiBella & Gould, 1995; Stata, 1989). Learning can be viewed from different perspectives depending on the criteria used for differentiation (Easterby-Smith, 1997; Shristastava, 1993). The most important perspectives are characterized in Table 1 by means of a single phrase. The information-processing perspective sees organizations mainly as entities processing information by acquisition, distribution, interpretation and storage of information, that is to say, knowledge (Duncan & Weiss, 1979; Huber, 1991; Nonaka & Takeuchi, 1995). Learning is a continuous process resulting in an increase and improvement of knowledge.2 The contingency perspective sees organizations as open systems constantly adapting their structures to changes in the environment. Basically, the learning process in this view is a process of adaptation (Cangelosi & Dill, 1965; Cyert & March, 1963; Hutchins, 1991). Within the psychology perspective it is presumed that organizations interpret their internal and external environments in terms of
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Table 1. Perspectives on Organizational Learning Perspective
Characterization: learning is . . .
Information-processing perspective
Increasing and improving knowledge through processing processing information
Contingency perspective
Adapting to changes in the environment
Psychology perspective
Continuous and concerted sharing of assumptions in the context of collective action
Systems-dynamics perspective
Developing understanding of the complex causalities of osocial reality
Strategic perspective
Building unique competencies for competitive advantage
Production management perspective
Improving efficiency through experience
shared mental models (Argyris & Schön, 1978; Weick, 1996). In this view, learning is based upon two processes: reflection (analysing the situation and developing new ideas) and experimentation (testing these ideas). The systems-dynamics perspective uses principles and concepts from systems theory for understanding organizational learning processes (Morgan, 1986; Senge, 1990). Senge (1990) states that organizations are characterized by dynamic complexity, for which simple models on cause-effect relationships are not appropriate. Principles from systems theory such as processes and feedback loops are used to demonstrate the reality of organizations. Literature on organizational learning in the strategic perspective focuses on competition. Learning is seen as crucial in building competitive advantage, and as such, the organization should be concerned with building learning competencies. The production management perspective focuses on the relationship between learning on the one hand, and efficiency and productivity on the other hand. Research on the socalled ‘learning curve’ and on the ‘experience curve’ (Argote, Beckman & Epple, 1990; Boston Consulting Group, 1968) falls into this category. The discussion on the comparison of the NUMMI and Uddevalla production plants (Adler & Cole, 1993), and the discussion around lean organizations in general are exponents of this perspective. From literature it seems as if the above-mentioned perspectives serve as paradigms. Each perspective leads to specific conclusions on how learning in reality takes place, and on how it can be influenced. However, the perspectives are not necessarily mutually exclu-
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sive, but they can be applied complementing each other in studying organizational learning (see for example Huber, 1991; Nonaka & Takeuchi, 1995; Senge, 1990; Walsh & Ungson, 1991). Application of multiple disciplinary perspectives can lead to an increased understanding into the nature and problems of organizational learning. The assumption that organizations are able to learn, as well as the assumption that they all learn, whether consciously or not (Kim, 1993) has not been taken for granted in literature. Walsh and Ungson (1991) have pointed to anthropomorphism in the discussion on organizational memory, and it seems to apply to the discussion on organizational learning in general: There is something paradoxical here. Organizations are not merely collections of individuals, yet there are no organizations without such collections. Similarly, organizational learning is not merely individual learning, yet organizations learn only through the experience and actions of individuals. (Argyris & Schön, 1978, p. 9) At the same time, knowledge generated by the individual is not independent of organizational learning. Models of individual learning (Kolb, 1984) can be linked to theory on organizations as behavioural systems (Cyert & March, 1963), and to organizations as interpretation systems (Daft & Weick, 1984). The result is a model of organizational learning that addresses the issue of transfer of information through the exchange of individual and shared mental models (see also Argyris, 1996), that is, a model within the knowledge
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development perspective (Glynn, Lant & Milliken, 1994). Within the information-processing perspective (Duncan & Weiss, 1979; Huber, 1991; Nonaka & Takeuchi, 1995; Pentland, 1995; Sligo, 1996; Walsh & Ungson, 1991; Wijnhoven, 1995), knowledge is characterized as organizational knowledge when it is accepted and exchanged by the organizations’ members. Knowledge improvement is to be reached by the continuous process of learning. In the CIMA research project that is reported on, we apply a so-called combined perspective. In this perspective knowledge processing in and through the organization is seen as an important factor in the change of mental constructs, both on an individual and on a group level.
Learning in Product Innovation Processes In literature, the relationship between learning and product innovation processes is described in different ways. First, literature can be categorized according to the different perspectives on organizational learning. One group of theories can be classified under the information-processing perspective. The common denominator for these theories is the notion that Research and Development (R&D) is a rational problem-solving process. Information is processed as a result of going through the different phases of this problem-solving process. According to Brown and Eisenhardt (1995), in the rationalistic approach, organizational learning is seen as a predictable and controllable process where most of the learning takes place before the execution phase of the new product development process. A second stream of literature can be characterized by the focus of research upon learning in product innovation – in general limited to R&D or (even more limited to) new product development – and has linkages with the adaptation perspective of organizational learning. Within this perspective, two ways of looking at the relationship between learning and R&D or new product development can be distinguished. Product Innovation Processes (especially New Product Development) can, by nature, be viewed as learning processes since they have a primary role in generating new knowledge and distributing that knowledge throughout the organization. As such the process of knowledge development and accumulation is equated with learning (Carlsson, Keane & Martin, 1976; Nelson & Winter, 1982). Product innovation processes can also be viewed as one of the focal processes in an organization, where learning is essential in
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order to stay competitive (Bartezzaghi, Corso & Verganti, 1997; Caffyn, 1998; Hughes & Chafin, 1996; McKee, 1992). Within this view learning can be addressed by facilitating and stimulating a number of learning behaviours exhibited by individuals and groups related to the acquisition, generation, diffusion, storage and retrieval of knowledge. Changes in behaviour (at an individual, group and organizational level) can be seen as indicators for learning, and are often mentioned in literature, though hardly operationalized nor systematically empirically studied. The following citation summarizes this view: ‘. . . widely recognized belief that the acquisition, retention and retrieval of knowledge and experience from retention repositories (i.e. memory) influence subsequent individual behavior . . . ’(Walsh & Ungson, 1991, p. 58). As changes in behaviours have hardly been operationalized nor systematically studied, the development of a psychometrically sound instrument to measure (changes in) learning behaviour is one of the main goals of our study. In the following section we will go into the research methodology of our project.
Research Methodology The Research Model The CIMA research project adopted the approach of learning behaviours as indicators for learning processes. Starting with a state-ofthe-art literature review covering product innovation, organizational learning, continuous improvement (CI), knowledge management, and performance measurement in product innovation processes, an investigation framework has been developed and used to carry out ten in-depth case studies in six countries (Australia, Ireland, Italy, The Netherlands, Sweden and the UK). The findings of some fieldwork, together with a thorough analysis of the literature review resulted in a model for learning (and continuous improvement) in product innovation processes. This model underpinning the CIMA methodology is depicted in Figure 1. It has been tested and applied in a variety of companies. The development and application of the model and the methodology are elaborately explained and described in Boer et al. (2000), and in Boer et al. (2001). Learning behaviours exhibited by individuals and by teams are the core elements that lead to a certain performance. These behaviours can be addressed through so-called enablers, man-
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Capabilities
Learning Behaviours Enablers
Performances
Contingencies
Figure 1. Elements in the CIMA Model for Learning in Product Innovation Processes
agerial decisions and activities that do have an impact (but that not necessarily need to be aimed directly at improving learning behaviour). The identification of contingencies is required to take into account the uniqueness of product innovation processes and organizational differences. Capabilities (integrated stocks of resources that are accumulated over time through learning) are built through exercising the behaviours and, in turn, help building the learning behaviours. Based on the previously mentioned state-ofthe-art literature review, together with the case studies, and the testing of the CIMA methodology eight categories of learning behaviours, and eight categories of enablers have been distinguished. Examples of enablers are HRM policies, project planning and control, performance management, design tools and methods. Examples of learning behaviours are, for instance, using strategic goals and objectives to focus and prioritize learning activities, using product innovation processes as opportunities to develop knowledge, using parts of the available time and resources to experiment with new solutions, integrating and transferring new knowledge within and between innovation processes and embedding knowledge into vehicles such as reports, guidelines and databases. Learning behaviours were investigated by means of an e-questionnaire (to be answered by the responsible person for product innovation) that was filled out in workshops facilitated by the research team. Next to the mapping of exhibited learning behaviours, we have also investigated the enablers used for stimulating and facilitating these learning behaviours. The CIMA methodology has been used in 70 companies in the six participating
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countries, and the data have been centrally stored in the so-called CIMA database. This database has been analysed for different purposes: contingencies that influence firm level approaches to learning in product innovation processes have been studied (Ronchi, Chapman & Corso, 2000), as well as aspects of occupational culture and problems associated with learning (Hyland, Gieskes & Sloan, 2001), and barriers to learning in product innovation processes (Gieskes, 2003).
Sampling and Procedure Providing answers to the questions: (1) whether the measurement of learning behaviours in the CIMA model is reliable, and (2) which enablers (see Figure 1) are effective in stimulating learning behaviour in product innovation (PI) processes has been approached in a quantitative way. Before turning to the statistical analyses that have been carried out to answer the research questions, some background information on the research model and the sample will be given. The research model (including the operationalization of the variables and following the information-processing perspective) is depicted in Figure 2. In this model, learning behaviours are considered to be the dependents, while enablers are assumed to be the predictors. The information-processing perspective provides a valuable means for categorizing different learning behaviours with regard to learning process: • Knowledge acquisition and generation: individuals and groups use innovation
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Predictors
Enablers: 1. Product family strategy 2. Process definition 3. Organizational integration mechanisms 4. HRM policies 5. Project planning and control 6. Performance management 7. Design tools and methods 8. Computer-based technologies
Dependents
Frequency and diffusion of learning behaviors: 1. Focusing learning and improvement 2. Developing knowledge 3. Experimenting 4. Integrating knowledge within PI phases 5. Transferring knowledge between PI phases 6. Abstracting and generalizing 7. Embedding knowledge 8. Assimilating knowledge from external sources
Learning performance
Figure 2. The Research Model Including the Operationalization of the Variables
processes as opportunities to develop knowledge, use part of the available time and resources to experiment, and try to assimilate and to use knowledge from external sources (Cohen & Levinthal, 1990; Leonard-Barton, 1992; McGill, Slocum & Lei, 1992; McKee, 1992; Miner & Mezias, 1996; Pedler, Boydell & Burgoyne, 1989). • Information distribution: individuals and groups integrate and transfer knowledge within and between all the different phases of product innovation processes, and throughout the organization. People analyse their experiences in order to identify knowledge and information that is really important and may be applied in other situations (Dibella, Nevis & Gould, 1996; Pedler, Burgoyne & Boydell, 1991; Shaw & Perkins, 1991). • Information interpretation: people are aware of the value of sharing knowledge acquired in different product innovation processes (Daft & Weick, 1984; McKee, 1992). As such, individuals and groups use the strategic goals and objectives of a product innovation process to focus and prioritise their learning activities, that is to say, their behaviour (Bowen et al., 1994; Dibella, Nevis & Gould, 1996; McKee, 1992; Morgan, Katsikeas & Appiaha-Adu, 1998). • Information storage and retrieval: people embed knowledge and make it available to other people in the organization by incorporating it in vehicles such as reports, databases, and product and process standards that can be more widely disseminated and
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retained over time (Cooper et al., 1999; Dibella, Nevis & Gould, 1996). The companies in the CIMA database are all manufacturing companies. Although the majority of the companies are medium-sized, there is a considerable percentage that can be labelled as large, that is employing at least 250 employees. Approximately 50 per cent of the companies confine their manufacturing and New Product Developmental (NPD) activities to their home countries, and their markets are either regional or national. Only 5 per cent of the companies are globally oriented in their manufacturing activities, whereas hardly any company is globally oriented in its NPD activities. About 40 per cent of the companies operate alone and are privately owned, while another 35 per cent are subsidiaries of a multinational. The typical product development time in these companies’ specific industry is somewhere between six months and two years, whereas the typical product life-cycle in general is longer (> five years). The respondents were asked to identify a product innovation process or project that was recently completed and that was exemplary for the company. Four output characteristics of the projects were distinguished. ‘Newness’ refers to the degree of innovation involved in the products, ‘functionality’ to the functionality that is offered by the new products. The ‘product complexity’ is a measure for the complexity of the structure of the new products, that is, the number of distinct components that are needed. ‘Markets served’
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refers to whether both products are produced for different types of markets, customers, regions and so on. This study relies on retrospective reports about the variables of interest. There is reason to believe that individuals are in a good position to make a valid assessment of their own learning behaviours. The person who is doing the job possesses the greatest familiarity with the job, and because of that, is appropriate for filling in the questionnaire. Studies examining job-related variables have shown that those who possess greater familiarity with the job, in this case an innovation project, and the ratee (Kozlowski & Kirsch, 1987) provide ratings that are more reliable and have fewer errors (Miller, 1996). Who else has a better understanding of the project and one’s functioning in it than the employee him or herself? Notwithstanding the advantages of selfassessments, it was assumed that attention should be paid to prevent so-called ‘data inaccuracy’, implying that the data are incomplete, biased or imprecise. Approaches for minimizing the occurrence or magnitude of these inaccuracies were examined and several guidelines for improving the accuracy of retrospective reports have been followed in the CIMA research project (Huber & Power, 1985). More specifically, the person that was most knowledgeable about the issue of interest was identified, informants have co-operated with the researchers (by means of the workshops) and the questionnaires have been pre-tested and structured. The assumption that retrospective accounts of past strategies are accurate has been tested empirically, and the outcomes have indicated that substantial retrospective errors occur
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less in case the matter on which to report is more recent (Golden, 1992). Moreover, retrospective accounts of past behaviours are likely to be more accurate compared with the accounts of past beliefs and intentions (Golden, 1992). Altogether, the resulting research design is quite useful and easy to administer in providing a picture of the degree of learning behaviours.
Measurements Learning Behaviours The CIMA model distinguishes two dimensions of learning behaviours that apply to each of its eight categories (see Figure 2): frequency as a measure of how often the learning behaviour is exhibited by individuals and groups, and diffusion as a measure of how widespread the learning behaviour is throughout the product innovation process. The CIMA model assumes that enablers are either directed at improving the frequency or at improving the diffusion of the learning behaviour, which implies that the two dimensions are independent. This independency indicates that a change in frequency does not imply a change in the diffusion (and vice versa) of learning behaviours. Both dimensions have been measured using a five-point Likert scale. Table 2 depicts that scale anchors that have been used.
Outcomes of the Study An investigation into the correlations structure using Pearson’s r shows that the fre-
Table 2. Scale Anchors for Frequency and Diffusion Frequency
Diffusion
1 The behaviour was never shown.
The behaviour was not seen anywhere within the innovation process.
2 The behaviour was shown only rarely.
The behaviour was confined to one part of the innovation process.
3 The behaviour was shown rather frequently.
The behaviour was confined to some parts of the innovation process.
4 The behaviour was shown very frequently.
The behaviour was diffused in most parts of the innovation process.
5 The behaviour was always shown as part of day-to-day work.
The behaviour was spread throughout the innovation process.
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quency and the diffusion of learning behaviours are strongly related. The issue arising is whether there is a direction in the relationship between frequency and diffusion. In other words, in reality when stimulating learning behaviours through enablers, should the organization focus on frequency or on diffusion? This question cannot be answered confidently within the context of this study since the data do not allow for causal modelling (see also Jöreskog & Sörbom, 1993). In order to answer our research questions we have limited ourselves to reliability analysis, exploratory factor analysis and regression analysis.
Exploratory Factor Analysis (EFA) Factor analysis (FA) includes a variety of correlational analyses designed to examine the interrelationships among variables (Gorsuch, 1983). As such, FA is a generic term used to describe a number of methods to analyse interrelationships within a set of variables or objects, resulting in the construction of fewer objects, called factors. These factors are supposed to contain the essential information in a larger set of observed objects. Two major dichotomies regarding FA do exist: exploratory and confirmatory FA. Exploratory FA (EFA) is used to explore data in order to determine the number or nature of factors that account for the co-variation between variables when the researcher does not have, a priori, sufficient evidence to form a hypothesis about the number of factors underlying the data. Therefore, EFA is generally more thought of as a theory-generating procedure as opposed to a theory-testing procedure (Cronbach, 1990; Stevens, 1996). Confirmatory FA is a theory-testing model where the researcher begins with a hypothesis, prior to the analysis. The model specifies which variables will be correlated with which factors and which factors are correlated. In the CIMA research project it is assumed that ‘learning behaviour’ as a generic variable can be measured in a reliable way by means of eight different learning behaviours. As no hypotheses were formulated with regard to the number or nature of factors to be identified, EFA is the appropriate method to examine whether one or more factors can be identified within the eight behaviours, including their frequency and diffusion. Before an exploratory factor analysis was carried out, a reliability analysis using Cronbach’s alpha has been performed. Cronbach’s alpha is an empirical measure of the internal consistency of a scale and an estimate of the scale reliability. The results of the
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reliability analysis indicate that a seemingly reliable scale has been developed. Cronbach’s alpha for the total scale is 0.90, while the reliabilities for the frequency items, and for the diffusion items separately, are 0.79 and 0.81 respectively. The 16 items for learning behaviour all relate to the same construct of ‘learning behaviour’ and are a useful measure for it. As a newly developed scale has been constructed, Table 3 provides some details of the reliability analysis’ outcomes. The eight distinguished learning behaviours with the two dimensions, that is, frequency and diffusion, were identified by means of a thorough literature study and some case studies. Principal Component Analysis was used to explore the underlying structure of the variable ‘learning behaviour’. Orthogonal VARIMAX rotation (Norusˇis, 1993) was carried out and its results show that all sixteen items (eight for frequency and eight for distribution) load on one factor explaining 41 per cent of the variance (see Table 4). A second factor explains an additional 13 per cent of the variance, whereby only Learning Behaviour item number eight (people try to assimilate and use knowledge from external sources) loads well on this factor. The third and fourth components explain respectively 9 per cent and 8 per cent. The results of the EFA lead to the conclusion that the psychometric qualities of the newly developed scale are sufficient enough to justify its use in a subsequent analysis aimed at testing the effectiveness of enablers for stimulating learning behaviour.
Enablers Stimulating Learning Behaviour The majority of authors in literature on learning believe that management is the most influential factor in affecting learning behaviour, and in allowing learning to take place (Bowen et al., 1994; Cooper et al., 1999; Dixon, 1992; Huber, 1996; McGill, Slocum & Lei, 1992; Senge, 1990). In our study, we have used a more comprehensive list of different types of enablers (see Table 5). For each learning behaviour, the respondents were asked to indicate which enablers were used to stimulate the particular learning behaviour by ticking the appropriate enabler(s) and by, if applicable, adding enablers that were not mentioned in the list. It is hypothesized that the relationship between the enablers on the one hand, and learning behaviour on the other hand, is positive. Table 6 summarizes the different hypotheses that have been tested. The hypotheses in Table 6 can be tested empirically by means of regression analyses
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Table 3. Reliability Analysis (n = 66) Scale
Behaviour 1 (Freq.) Behaviour 2 (Freq.) Behaviour 3 (Freq.) Behaviour 4 (Freq.) Behaviour 5 (Freq.) Behaviour 6 (Freq.) Behaviour 7 (Freq.) Behaviour 8 (Freq.)
Scale if item Deleted
Corrected variance if item deleted
Item-total correlation
Squared multiple correlation
Alpha if item deleted
48.64 48.44 48.95 48.35 48.41 48.18 48.55 48.50 48.58 48.43 49.03 48.32 48.30 48.20 48.42 48.83
116.24 115.57 116.72 116.51 113.69 117.54 110.96 117.76 114.71 114.37 115.29 112.74 111.23 115.51 114.03 118.88
0.58 0.56 0.48 0.59 0.68 0.48 0.68 0.44 0.60 0.61 0.55 0.67 0.73 0.57 0.55 0.37
0.62 0.65 0.60 0.57 0.77 0.79 0.82 0.68 0.61 0.66 0.65 0.64 0.84 0.83 0.80 0.69
0.89 0.89 0.90 0.89 0.89 0.90 0.89 0.90 0.89 0.89 0.89 0.89 0.89 0.89 0.89 0.90
Behaviour 1 (Diff.) Behaviour 2 (Diff.) Behaviour 3 (Diff.) Behaviour 4 (Diff.) Behaviour 5 (Diff.) Behaviour 6 (Diff.) Behaviour 7 (Diff.) Behaviour 8 (Diff.)
with enablers as the predictor variable for learning behaviour in innovation projects. One might think of studying all possible relationships between enablers and behaviours, implying eight enablers by eight learning behaviours by two dimensions. The problem however with this analysis structure is that for some analyses the number of data will be very low, limiting the possibility to draw reliable conclusions. A second issue that would come up is the so-called phenomenon of ‘chance capitalization’ (see also Stevens, 1996). In order to avoid these pitfalls, we have decided to build on the previous section from which we inherit the aggregated scale for learning behaviour that enables us to test and measure in a seemingly reliable way the relationship between different types of enablers and learning behaviour. In Table 7, one can see which hypotheses have been confirmed in our study. Concerning the analyses of the effects of categories of managerial activities and
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decisions upon learning behaviour, our hypotheses have for the greater part been confirmed. For two enablers that were assumed to be effective in stimulating and facilitating learning behaviour, our hypothesis has been rejected. Product family strategy and computer-based technologies are not significantly related to learning behaviour. Six of the eight enablers indeed appear to be effective whereby two enablers, i.e. human-resource management policies, and project planning and control appear to have the strongest impact. In the last section we will go into the conclusions and a discussion of the outcomes of this study.
Conclusions and Discussion The finding that product family strategy is not significantly related to learning behaviour is interesting, since literature on learning and on Continuous Improvement (CI) emphasizes the formulation and deployment of goals as being
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Table 4. Principal Component Matrix Components
Behaviour 1 Frequency Behaviour 1 Diffusion Behaviour 2 Frequency Behaviour 2 Diffusion Behaviour 3 Frequency Behaviour 3 Diffusion Behaviour 4 Frequency Behaviour 4 Diffusion Behaviour 5 Frequency Behaviour 5 Diffusion Behaviour 6 Frequency Behaviour 6 Diffusion Behaviour 7 Frequency Behaviour 7 Diffusion Behaviour 8 Frequency Behaviour 8 Diffusion
1
2
3
4
0.65 0.68 0.63 0.69 0.53 0.59 0.65 0.72 0.76 0.81 0.57 0.65 0.73 0.61 0.46 0.40
0.16 0.06 0.12 0.03 0.05 0.22 0.25 0.18 -0.44 -0.45 -0.64 -0.59 0.12 0.27 0.60 0.56
-0.47 -0.34 -0.53 -0.49 -0.07 0.07 0.03 0.10 0.13 0.06 0.30 0.32 0.11 0.19 0.36 0.58
0.12 -0.007 -0.03 -0.07 0.60 0.60 -0.23 -0.16 -0.05 -0.007 0.14 0.03 -0.41 -0.50 0.25 0.062
Table 5. Examples of Enablers Enablers
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Specific examples
1. Product family strategies
Product family plans, carry-over policies, standardization policies
2. Process definition
Stage-gate processes, company innovation procedures
3. Organizational integration mechanisms 4. HRM policies
Teamwork, matrix organization, and committees Personnel rotation, departmental assessment and development plans, reward systems, empowerment programs
5. Project planning and control
Project termination reports, design reviews
6. Performance measurement
Comparison of measurements against previous results or with other subsidiaries or leading organizations
7. Design tools and methods
Standardized design methodologies and procedures, libraries of standard design solutions, integration procedures (e.g. Quality Function Deployment, Design for Manufacturability)
8. Computer-based technologies
IT systems, computer-aided technologies, prototyping technologies
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Table 6. Hypotheses Underlying the CIMA Model Hypothesis 1
Formulation and existence of a product family strategy are positively related to learning behaviour
Hypothesis 2
Definition and standardization of the innovation process are positively related to learning behaviour
Hypothesis 3
Organizational integration mechanisms are positively related to learning behaviour
Hypothesis 4
Development and execution of human-resource management policies is positively related to learning behaviour
Hypothesis 5
Planning and control of product innovation processes are positively related to learning behaviour
Hypothesis 6
Performance measurement is positively related to learning behaviour
Hypothesis 7
Standardization of design tools and methods is positively related to learning behaviour
Hypothesis 8
The implementation of computer-based technologies is positively related to learning behaviour
Table 7. Results of Regression Analyses with Enablers as Predictors and Learning Behaviour as Dependent (n = 66) Hypothesis 1
Formulation and existence of a product family strategy are positively related to learning behaviour
Rejected
Hypothesis 2
Definition and standardization of the innovation process are positively related to learning behaviour
Confirmed Multiple R = 0.31, R2 = 0.10, F(1, 66) = 7.04, p < 0.05*
Hypothesis 3
Organizational integration mechanisms are positively related to learning behaviour
Confirmed Multiple R = 0.30, R2 = 0.09, F(1, 66) = 6.74, p < 0.05*
Hypothesis 4
Development and execution of human resource management policies is positively related to learning behaviour
Confirmed Multiple R = 0.44, R2 = 0.19, F(1, 66) = 15.48, p < 0.001***
Hypothesis 5
Planning and control of product innovation processes are positively related to learning behaviour
Confirmed Multiple R = 0.48, R2 = 0.23, F(1, 66) = 19.82, p < 0.001***
Hypothesis 6
Performance measurement is positively related to learning behaviour
Confirmed Multiple R = 0.30, R2 = 0.09, F(1, 66) = 6.28, p < 0.05*
Hypothesis 7
Standardization of design tools and methods is positively related to learning behaviour
Confirmed Multiple R = 0.34, R2 = 0.12, F(1, 66) = 8.75, p < 0.01**
Hypothesis 8
The implementation of computer-based technologies is positively related to learning behaviour.
Rejected
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one of the key features for success (Bowen et al., 1994; Galer & Van der Heijden, 1992). An explanation for this finding can be found in the phrasing in the questionnaire of the enabler itself. The term ‘product family strategy’ implies the existence of a product innovation strategy on a product level, which is not formulated in all companies. A second explanation could be that since strategy is important for directing the activities of employees towards goal realization, product family strategy does have an effect upon focusing and framing behaviour, but not necessarily upon learning. A product strategy is a management decision, as such, that is a fact and does not serve as a trigger for learning (although the strategy decision-making process might) (De Geus, 1988). It is also argued that dynamic learning is not compatible with a very strong goal alignment (Galer & Van der Heijden, 1992). The stronger the goal orientation, the more difficult it is for organizations to be open to for alternatives. Computer–based technologies (such as ITsystems, computer-aided technologies (CAD, CAM, CAE) and Prototyping technologies) also appear not to be contributing to learning behaviour. However, some caution is called for interpreting this result, since the respondents indicated that to them the difference between computer-based technologies and design tools and methods3 was not always clear, and that it was not always possible to clearly distinguish between the two. Hypothesis 7, referring to the contribution of design tools and methods is confirmed with the enabler explaining 12 per cent of the variance in learning behaviour. Few scientists have studied the impact of computer tools and systems upon innovation processes (and as such their continuous impact upon learning) (Hanseth & Monteiro, 1997; Henfridsson & Soderholm, 2000; Tyre & Orlikowski, 1994). The authors demonstrate that computer tools and systems do not always result in learning. On the contrary, they more than once observed negative learning implications. Project management and control is an enabler that explains 23 per cent of the variance in learning behaviour. From research in the fields of Project Management and R&D Management, it is known that project planning and control are very effective in performance improvement. However, it is also known that the major benefit of project planning and control is realized during the start of its implementation and the more disseminated the implementation is, the better the effect. In fact, planning and control help to manage the
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product innovation process and when it is not effective, management is involved in operational activities in the project. Once the process becomes more under control, time (and often budget too) becomes available that can be used for additional, new activities. Particularly in freeing up energy for learning activities, project planning and control appear to be effective. It would be interesting to find out in future research if this enabler still has a strong impact on learning behaviour in product innovation processes that for a long time already have been subjected to effective planning and control. The last result to discuss concerns the impact of HRM policies, such as job rotation, reward systems, empowerment programmes, development plans. In general, HRM policies are aimed at helping people to develop, grow and empower themselves in such a way that they can contribute effectively to realizing both the organizations’ and their own goals. HRM policies can help people to learn and learn how to learn, and as such have a double effect. Work on learning styles (Honey & Mumford, 1986; Kolb, Fubin & McIntyre, 1973) has shown that individuals have a natural preference for the way they learn. Distinct ways of learning should be recognized and acknowledged as a prelude to broadening individual repertoires. This is necessary since different settings and different situations favour different learning styles (Brown & Duguid, 1991). HRM policies are important means in helping people to broaden their repertoire and help them perform well under different circumstances. At the same time HRM can address different learning styles in such a way that learning as a whole is improved. An interesting outcome is the fact that it is precisely these HRM policies that have been used least frequently in the CIMA research project to stimulate learning behaviour (Caffyn et al., 2000). In discussions on the outcomes of our study with practitioners, one indicated that HRM policies were perceived to be the expertise area of the HRM or personnel department, and that product innovation managers disqualified themselves from using enablers in this HRM category. Analyses on country-related differences by Hyland, Gieskes and Sloan (2001) indicated that there were no outstanding differences in the use of enablers that could be attributed to cultural differences among countries. Although the type of enablers that are applied may differ, this does not seem to be the case in terms of ‘how’ the enablers are applied. While the data
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do not provide information on this ‘how’, we cannot go into a further analysis of it. Analysis of the company and productrelated characteristics by Chapman et al. (2000) with the aim to identify and analyse the main contingent variables influencing firmlevel approaches to learning in product innovation, reveals that four cluster of companies can be identified: • The first cluster (12 companies) consists of entrepreneurial firms with less than 30 employees and with a low labour turnover. Their customers are located in a domestic market and provided with highly customized products. The operations and R&D activities are confined. The product life cycle is very long, although their development time is very short, and their complexity rather high. In these companies, management is very much involved in technological and customer issues. • The second cluster (24 companies) mainly concerns companies with less than 250 employees and an average labour turnover. Their market is national or restricted to a few countries in the same geographical area, while manufacturing and R&D sites are confined to the home country. The products’ level of complexity in general is not high, and the life cycle is medium, with a rather long development time. • The third cluster (20 companies) in general consists of large industrial groups with more than 250 employees and a high labour turnover. Their market is a geographical area (Europe, Asia) while their operations and R&D activities, however, are confined to their home countries. Products and processes are not complex, with a long life cycle for products, and a short development time. • The fourth cluster (14 companies) consists of large multinationals with more than 1,000 employees with a high labour turnover. Their market, operations and R&D activities are globally oriented. The product development time and product life cycle are short. In their research, Chapman et al. (2000) analysed the enablers typically associated with each of these clusters and found that a certain emphasis on particular enablers can be identified for especially the first two clusters. Companies in the first cluster particularly employ project planning and control, as well as computer-based technologies. This indicates that for small companies producing niche, customized products, good project management
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procedures, resources’ allocation and scheduling are important means in affecting learning behaviour. The second cluster shows a similar preference, that is, a lot of managerial effort in project planning and control, and design tools and methods. However, in these companies computer-based technologies seem to be lagging behind. Companies in the third and fourth cluster do not really show a preference for particular enablers, but for these companies, relations with other companies and research centres seem to be important for their innovation activities. Before making statements on the correctness of existing theory, the issue of validity of measurement instruments has to be discussed. The problem of validity is probably most critical in empirical research since it goes into the question whether the indicators that are used indeed reflect the abstract concept that is to be measured. In the CIMA research project, it is assumed that the operationalizations of learning behaviour and enablers have content validity as their development is based upon an extensive literature review, in-depth discussions among academics and practitioners within expert communities and peer groups, and upon field testing. In order to answer our research questions regarding the psychometric qualities of the operationalization of learning behaviour, and what managerial decisions and activities are effective in stimulating learning behaviour require exploration and verification of a theory. A first important conclusion that can be drawn from our study is that the two dimensions of learning behaviour, i.e. frequency and diffusion, are not independent. From an analytical point of view this indicates that there is no necessity in distinguishing between them. In practice, this seems to indicate that for managers to improve learning behaviour there is no major difference in which dimension to target first. A second conclusion is that the statistical analyses reveal that it is possible to constitute a reliable scale for measuring learning behaviour (from an information-processing perspective) by means of 16 items. A third conclusion of our study is that six of the eight enablers as distinguished within the CIMA model appear to be effective in stimulating learning behaviour: process definition, organizational integration mechanisms, HRM policies, project planning and control, performance management and design tools and methods. Contrary to what is stated in literature, product family strategy and computer-based technologies are not significantly related to learning behaviour. Explana-
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tions for these findings can be found in the wording of the questionnaire, but also in the way the respondents perceived these enablers. Discussing the results of the CIMA methodology with practitioners has revealed that, in general, managers in product innovation processes are not always aware of the possibilities of using enablers for improving learning. Much too often managers are aimed at realizing (short-term) project goals, more specifically performance within budget and time constraints, and thereby neglecting longterm effects of improving learning behaviour. In future research several interesting issues can be explored. First of all, one could think of an in-depth study of the process of changing behaviour as a result of applied enablers. This type of research might give more insight into the way the enablers operate. This will also require further research into the effectiveness of more specific enablers in specific contexts. Another interesting study could be aimed at improvement of the measurements and might consist of asking raters to give concrete examples of learning behaviours that could illustrate why they give a particular rating to a particular item. It is expected that a certain amount of sifting of responses will occur. The differentiation between item meanings will probably increase and the scale homogeneities will less, but the end result will be that the ratings are explicitly founded on empirical verifiable observations of learning behaviour. If this proves successful, the validity of the instrument will increase and be easier to clarify. The latter refers to the fact that demonstrative examples given by raters could give an insight into the intrinsic content of learning behaviours in organizations. The way in which this can be done is by means of highly structured interviews. They are more dynamic in that possibilities for putting extra questions on a certain topic are within the researcher’s reach.
Acknowledgement The authors gratefully acknowledge the work made within the CIMA project by its Consortium partners: Politechnico di Milano (I), MIP (I), ETASS (I), Trinity University Dublin (Ire), CORE Chalmers University Gothenburg (S), CENTRIM University of Brighton (UK), Twente University Enschede (NL), INCITE University Western Sydney Macarthur (Aus), Monash University Melbourne (AUS), and Edith Cowan University Perth (Aus).
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Notes 1 See Gieskes (2001, p. 35) for a variety of definitions on organizational learning indicating the scattered nature of the field. 2 In line with Huber (1991), the words information and knowledge will be used interchangeably. It is recognized that on theoretical grounds a distinction is possible (for instance knowledge being information with a context), but for the line of argument in this contribution this discussion is not called for. 3 Such as standardized design methodologies and procedures, libraries of standard design solutions and integration procedures.
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Hyland, P.W., Gieskes, J.F.B. and Sloan, T.R. (2001) Occupational clusters as determinants of organisational learning in the product innovation process. Journal of Workplace Learning, 13(5), 198–208. Imai, K., Nonaka, I. and Takeuchi, M. (1985) Managing the new product development process: How Japanese companies learn and unlearn. In K.B. Clark, R.H. Hayes and C. Lorenz (eds), The uneasy alliance. Managing the productivitytechnology dilemma. Harvard Business School Press, Boston MA, pp. 337–75. Jelinek, M. (1979) Institutionalizing innovation. A study of organizational learning systems. Praeger, New York. Jones, A.M. and Hendry, C. (1992) The learning organization: a review of literature and practice. London: HRD Partnership. Jöreskog, K.G. and Sörbom, D. (1993) Lisrel VIII: User’s reference guide. Scientific Software, Mooresville. Kanter, R. (1989) The new managerial work. Harvard Business Review, 76(6), 85–92. Kim, D.H. (1993) The link between individual and organizational learning. Sloan Management Review, 35(1), 37–50. Kolb, D.A. (1984) Experiential learning. Experience as the source of learning and development. Prentice Hall, Englewood Cliffs NJ. Kolb, D., Fubin, I. and McIntyre, J. (1973) Organizational psychology. A book of readings. Prentice Hall, Englewood Cliffs NJ. Kozlowski, S.W.J. and Kirsch, M.P. (1987) The systematic distortion hypothesis, halo, and accuracy: An individual-level analysis. Journal of Applied Psychology, 72, 252–61. Lei, D., Slocum, J.W. and Pitts, R.A. (1997) Building co-operative advantage: managing strategic alliances to promote organizational learning. Journal of World Business, 32(3), 203–23. Leonard-Barton, D. (1992) The Factory as a Learning Laboratory. Sloan Management Review, 34(1), 23–37. Levitt, B. and March, J.G. (1988) Organizational learning. Annual Review of Sociology, Vol. 14. JAI Press, Greenwich CT. McGill, M.E., Slocum Jr., J.W. and Lei, D. (1992) Management practices in learning organizations. Organizational Dynamics, 21(1), 5–17. McKee D. (1992) An organizational learning approach to product innovation. Journal of Product Innovation Management, 9, 232–45. Miller, M.J. (1996) Rater individual differences and accuracy in performance appraisal. A PhD thesis submitted to the office of Graduate Studies of Texas A&M University. Miner, A.S. and Mezias, S.J. (1996) Ugly duckling no more. Pasts and futures of organizational learning research. Organization Science, 7(1), 88–100. Morgan, G. (1986) Images of Organizations. Beverly Hills, Ca: Sage. Morgan, R.E., Katsikeas, C.S. and Appiaha-Adu, K. (1998) Market orientation and organizational learning capabilities. Journal of Marketing Management, 14, 353–81.
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Nelson, R. and S. Winter (1982) An evolutionary theory of economic change. Harvard University Press, Cambridge MA. Nevis, E.C., DiBella, A.J. and Gould, J.M. (1995) Understanding organizations as learning systems. Sloan Management Review, 36(2), 75–85. Nonaka, I. (1991) The knowledge creating company. Harvard Business Review, 69(6), 96–104. Nonaka, I. and Takeuchi, H. (1995) The knowledge creating company. Oxford University Press, New York. Norusˇis, M.J. (1993) SPSS for Windows. Base System User’s Guide. Release 6.0. SPSS Inc., Chicago. Pedler, M., Boydell, R and Burgoyne J. (1989) Towards the learning company. Management Education and Development, 20(1), 1–8. Pedler, M., Burgoyne, J. & Boydell, T. (1991) The learning company: a strategy for sustainable development. McGraw-Hill, London. Pentland, B.T. (1995) Information systems and organizational learning: the social epistemology of organizational knowledge systems. Accounting, Management & Information Technology, 5(1) 1–21. Peters, T.J. and Waterman, R.H. (1982) In search of excellence: lessons from America’s best-run companies. Harper & Row, New York. Ronchi, S., Chapman, R. and Corso, M. (2000) Knowledge Management in Continuous Product Innovation. A Contingent Approach. Proceedings 3rd International CInet conference on Continuous Improvement, Aalborg Denmark, 18–20 September, pp. 375–388. Senge, P.M. (1990) The Fifth Discipline: Mastering the five practices of the learning organization. Doubleday, New York. Shaw, R.B. and Perkins, D.N.T. (1991) Teaching organizations to learn. Organizational Development Journal, Vol. 9(4), 1–12. Shristastava, P. (1993) A typology of organizational learning systems. Journal of Management Studies, 20(1), 7–28. Sligo, F. (1996) Disseminating knowledge to build a learning organization. The International journal of Human Resource Management, 7(2), 508–19. Stata, R. (1989) Organizational learning – The key to management innovation. Sloan Management Review, 30(3), 63–74. Stevens, J. (1996) Applied multivariate statistics for the social sciences, 3rd edition. Lawrence Erlbaum Associates, Mahway NJ. Tyre, M.J. and Orlikowski, W.J. (1994) Windows of opportunity: temporal patterns of technological adaptation in organizations. Organization Science, 5(1), 98–118. Walsh. J.P. and Ungson, G.R. (1991) Organizational Memory. Academy of Management Review, 16(1), 57–91. Weick, K.E. (1996). The role of renewal in organizational learning. International Journal of Tecnology Management, Special Publication on Unlearning and Learning, 11(7/8), 738–46. Wijnhoven, F. (1995) Organizational learning and information systems. PhD Thesis University of Twente, The Netherlands.
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José F.B. Gieskes (MSc, PhD) worked as a consultant and researcher at the School of Business, Public Administration and Technology of the University of Twente. She has been involved in projects on developing time standards for professionals, quality management, improvement management and organisational learning. Her PhD was on how to stimulate learning behaviour in product innovation processes. Currently she works as a manager of a number of outdoor patient clinics of Medisch Spectrum Twente, a large hospital in Enschede, The Netherlands. Beatrice I.J.M. van der Heijden (PhD) is a professor of Organizational Behaviour at the Maastricht School of Management, The Netherlands. She graduated in 1990 from the Department of Work and Organizational Psychology at the Catholic University of Nijmegen and has a PhD (1998) in career development from the University of Twente, where she is still part-time employed as a professor at the department of HRM, School of Business, Public Administration and Technology. Her main research areas are (1) career development (2) employability and (3) aging at work. Currently she co-ordinates, among others, a cross-cultural European study on career success among ICT-professionals. She serves as a member of the editorial boards of Career Development International, Human Resource Development International, and SAM, Advanced Management Journal. She also does some consultancy work on Human Resource Management topics. E-mail address for correspondence:
[email protected]; or
[email protected].
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Transitioning Towards Creativity and Innovation Measurement in SMEs Rodney McAdam and William Keogh The aim of this paper is to explore the transition from traditional measures to creativity and innovation measures within a number of small to medium-sized enterprises (SMEs) case studies. The need for increased competitiveness has created an impetus for increased creativity and innovation in SMEs. However, the measures associated with the process of creativity and innovation in organisations sometimes do not follow cause-and-effect rationale, reflecting non-linear behaviour. A multiple SME-based case research methodology is used to explore the transitioning effects from traditional to more creativity and innovation based measures. The cases were part of a longitudinal creativity and innovation intervention programme, which combined taught modules and Critical Action Learning networks over a two-year period. These networks involved sub-groups applying critical theory-based study to the learning they had received in the modules. The findings reveal that the transition dynamics include a complex mix of cause and effect rationale, phenomenology, incremental change, radical change, quantitative, qualitative and linear and complex contrasts and comparisons. Thus, managers must facilitate an eclectic approach to creativity and innovation measures.
Introduction
I
ncreasing market changes resulting in increased competition in traditional SME markets has led to a need for increased creativity and innovation and, therefore, programmes of creativity and innovation in SMEs (Choueke & Armstrong, 1998). Effective creativity and innovation incorporation, resulting in increased competitiveness, involves intervention programmes with supporting measures, rather than relying solely on natural progression or ‘innovation under the gun’ (Amabile, Hadley & Kramer, 2002). The process of innovation in organizations is often phenomenologically based, rather than being dependent on cause and effect rationale. It can be non-linear, fuzz or illdefined (Ford, 2000). This complexity is compounded in SMEs where issues such as scarce resources, lack of skills, scepticism towards formal training, the need for flexibility and lack of systematic measurement must be addressed (Vossen, 1999). If understanding about the longitudinal transitioning of SMEs towards creativity and innovation measures can be increased, then there will be a contribution to the areas of
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designing creativity and innovation programmes to increase competitiveness (Klein & Sorra, 1996). As suggested by Gorton (2000), SME learning and competitiveness will be increased through defining creativity and innovation more consistently and applying supportive measures. A multiple SME-based case research methodology is used to explore the transitioning effects from traditional to more creativity and innovation-based measures. The cases were part of a longitudinal creativity and innovation intervention programme, which combined taught modules and Critical Action Learning networks over an 18-month period.
Creativity and Innovation Measures in SMEs Many SMEs are founded on a single technological innovation, which leads to the design and manufacture of a new product. Often, the owner/managers are the originators of the idea and are engineers, scientists and computer and espouse ‘traditional thinking’ rather than developing ‘exploration competencies’ in relation to innovation (Wolpert, 2002). When
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Positivistic
Phenomenological
Socially constructed. Meaning and complexity.
Cause and effect Fact based.
Figure 1. Epistemological Continuum for Creativity and Innovation Learning and Measurement in SMEs
these organizations develop and grow there can be an over-reliance on technological innovation to address the need for secondgeneration innovation within the SMEs (Raymond, Bergeron & Rivard, 1998). Correspondingly, the broader discourse and concepts of innovation are not sufficiently addressed and incorporated. The reasons are often historical (Raymond, Bergeron & Rivard, 1998), related to a legacy of inadequate training and development (Sadler-Smith, Sargeant & Dawson, 1998), due to skills shortages (Chaston, Badger & Sadler-Smith, 1999), a belief in innovation as being solely innate rather than also being socially constructed (Deazin, Glynn & Kazanjian, 1999), overriding leadership influence: e.g. behaviour of the owner/manager or a general failure to recognize the broad basis of innovation and associated learning approaches (Amabile, Hadley & Kramer, 2002). Freel (2000) concludes that, while SMEs are disproportionately responsible for near-to-market innovations, they are hindered by lack of creativity and innovation measurement. Robertson, Swan and Newell’s (1996) study showed that lack of supporting measures limits the systematic and longitudinal inter and intra-organization adoption of creativity and innovation. Thus, the development of broad based creativity and innovation measures to support creativity and innovation in SMEs, is often limited or subsumed within productionoriented measures (Freel, 2000). Furthermore, there is a lack of supporting creativity and innovation measurement infrastructure such as measurement collection systems, as scarce resources are channelled towards more ‘certain’ outcomes (Vossen, 1999). When seeking to develop creativity and innovation learning and measures in an SME context, an epistemological continuum (avoiding a ‘one right way approach’) can be considered where definitions, methodologies and organizational application may vary (Willmott, 1993), as seen in Figure 1. Willmott (1993) points out that this tension is reflected throughout change management
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Figure 2. Development of Creativity and Innovation Measures in SMEs (adapted from Grint & Willcocks, 1995)
evaluation and learning literature. Furthermore, Rickards (1999) refers to similar issues in regard to creativity and innovation management. There is a lack of consensus on the most effective paradigm; there is no one right way. Hassard (1995) states that these differing paradigms are not incommensurate and can mutually co-exist in organizations. Shaw (1999), in recognizing the need for differing perspectives to be applied to SME issues noted: ‘the emerging preference for phenomenological approaches to small firm studies’. Furthermore, Culkin and Smith (2000) contend that there is a ‘naive, over simplistic understanding of the motivation of those in the small firm sector’, thus there is a need for fundamental in-depth understanding so that new and improved approaches to creativity and innovation measures can be developed and the transformations shown in Figure 2 obtained. Both positivistic and phenomenological views of innovation and the many variants can be represented by the concept of the ‘process of innovation’ (Figure 3) within an organisation as discussed by King (1992) and Tidd, Bessant and Pavitt (2001).
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Creativity
Innovation Knowledge Management (KM)
TQM/CI
Knowledge Idea Idea Creation Generation Screening (IS) (KC) (IG)
Structure
Business Process Innovation
Benchmarking
Figure 3. A Process Approach to Creativity and Innovation King (1992) states that ‘there is increasing awareness that innovation is a process’ although the process is ‘fluid without a fixed sequence of stages’. Moreover he refers to ‘untidiness’ and ‘backtracking’ within the process. In a review of the literature Slappendel (1996) refers to this approach as ‘the interactive process perspective’ to innovation and calls for more research in this area.
Guidelines for Creativity and Innovation Measures in SMEs In critiquing measurement frameworks, Neely et al. (2000) argue that they are in the main too prescriptive (i.e. cause-and-effect based) and fail to account for the diversity and dynamics within individual organizations. To avoid this impasse Neely et al. (2000) suggested that the antecedents of the measurement frameworks should be considered, namely: ‘a set of design guidelines designed to inform the development of a process for performance measurement system design’. Neely et al. (2000) elucidated these guidelines, based on SME action research, for the entire business operation, and structured them in a ‘process-based approach’. Thus, consistent with earlier epistemological arguments, the guidelines were set in a recursive and non-prescriptive process, allowing for dynamics and contextual issues, as opposed to a more regimented framework approach. Neely et al.’s action research study showed the need for simplification due to ‘too many barriers to entry’ when applied to SMEs. Thus a simplified set of the guidelines for the measurement of the process of creativity and innovation are as follows:
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• Performance measures should be derived from the company’s strategy. • The purpose of each performance measure should be made explicit. • There should be clear data-collection methods. • All stakeholders should be involved in the selection of the measures. • The measures should be changeable based on organizational and environmental dynamics. Thus, each part of the area under consideration in the present study, namely the process of creativity and innovation (Figure 3) as defined by Woodman, Sawyer and Griffin (1993) and Amabile et al. (1996), must be subjected to the measurement development principles. The overall contributions to this approach are shown in Figure 4.
Research Methodology The main research questions in relation to the aims of the paper are: how can SMEs longitudinally transition from traditional performance measures to include measures of creativity and innovation, as a stimulant for increased competitiveness, based on a programme of critical action learning interventions? Furthermore, what are the success and failure factors for applying Neely et al.’s (2000) measurement guidelines to the process of creativity and innovation in the SMEs?
Multiple Case Analysis The research method chosen was that of building understanding using a number of case studies in an exploratory manner – referred to
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Creativity and innovation measurement approaches • Possible new data-gathering and analysis approaches • Meaning and sensemaking rational • Phenomenological epistemology • Need for training and development
Existing measurement approaches •Existing measurement system •Historical success •Data-gathering and analysis systems in place •Cause-and-effect rationale •Mainly positivistic epistemology
Addition; Modification; Combination; Removal; Comparison with measurement principles
Broad based measures for SMEs
SME business characteristics •Record of development in Business Improvement •Scarce resources •Importance of leadership •Flexibility •Lack of training and development
Figure 4. The Transition towards Creativity and Innovation Measures in SMEs
as exploratory multiple case studies by Yin (1994). The exploratory multiple case strategy was used as the study focuses on achieving insights based on ‘how’ and ‘what’ type questions (Eisenhardt, 1989; Yin, 1994).
Selection of the Cases Initially, 20 SMEs were selected as candidates for the study. These SMEs were known to be involved in applying business improvement methodologies and were experiencing growth and development. SMEs with between 50 and 250 employees were chosen. Eight of the SMEs (Table 1) were selected for the study which were what Dale and Lascelles (1997) categorize as ‘improvers’ on the Total Quality management/Business Excellence journey with Business Excellence Model (BEM- similar to the Baldrige Model) scores in the 400–450 point band and were attempting the transition towards creativity and innovation measures. The eight cases were found to give significant replication and construct rigour, indicators that were suggested by Creswell (1994) and Yin (1994) in multiple case design.
Longitudinal Data Collection and Preparation The university received EU funding to design and implement a creativity and innovation learning programme for SMEs. The interventions consisted of eight three-day modules for the members of the participant SME management teams. Furthermore, a series of Critical Action learning networks were established
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composed of clusters of the SMEs (Neely et al., 2000; Pedlar, 1998), which met on a regular basis in each of the organization’s premises (on a rotational basis) over a two-year period. Data collected for each case included organizational information, archive data, artefacts, meetings and semi-structured interviews with the person most responsible for creativity and innovation. Each person was formally interviewed at least three times, with many other short contacts being made for clarification. Transcripts and detailed case write-ups were then prepared and coded (Remenyi et al., 1998).
Results Following the coding of the results, a transitional dynamics matrix was constructed, as shown in Table 2. The matrix was used to cross map each activity of the creativity and innovation process (left-hand side) against each of Neely et al.’s (2000) measurement principles (across the top). In each cell the coded findings are summarized showing the transitional dynamics issues involved in moving from traditional SME measures to include those involved in creativity and innovation. Thus, the comments in each cell do not reflect an initial or end state, rather they show the transitional situation.
Discussion The discussion of the results is structured under each of the measurement principles as
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Table 1. Case SMEs Case
Sector
No. employed
Market trend
Case 1
Manu control devices
58
Increasing
Case 2
Manu general eng.
51
Case 3
Manu pumps
Case 4
BEM score
Other improvement initiatives
Culture and learning
400–450
CI/TQM BEM Multi-skilling
Increasing
Direction and culture
400–450
CI/TQM Teams
70
Increasing
Leadership and culture
400–450
CI/TQM BEM Process imp.
Manu textiles
85
Increasing
Structure, processes and decision making
400–450
CI/TQM Teams Six Sigma
Case 5
Manu drinks
220
Increasing
Learning and decision making
400–450
CI/TQM BEM IiP
Case 6
Manu pharma products
170
Increasing
Structure, process and decision making
400–450
CI/TQM BEM Training needs
Case 7
Manu agri products
55
Increasing
Structure, process and culture
400–500
CI/TQM IiP ISO 9000:2000
Case 8
Manu medical devices
110
Increasing
Learning and decision making
400–450
CI/TQM BEM
listed earlier and shown in abbreviated form across the top of the transitional dynamics matrix (Table 2).
Performance Measures should be Derived from the Company’s Strategy All of the case organizations had attempted to devise business strategies consistent with creativity and innovation principles. However, as shown by Chaston, Badger and Sadler-Smith (1999), SMEs rely on developing strategy as a result of their flexibility and opportunism in the market place. Thus, when transitioning towards creativity and innovation measures they found that the company strategy ‘was not exactly a guiding light’ to quote a case-study company business improvement manager.
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Innovation focus
The creativity process – strategy dynamics revealed that KC needed much more support at a strategic level. For example, external networks, customers and suppliers had been identified as sources of KC but there was a lack of necessary infrastructure to make this happen. A similar situation existed in regard to IG, with a need to further empower and recognize employees as key sources of KC and IG. The strategy was more closely linked with IS, which had been successfully used in the case TQM/CI programmes. The closer links to strategy for IS reflected the cases being more comfortable with constructs that were more tangible, less subjective and which had some degree of cause-andeffect rationale. Thus, it was necessary to constantly challenge the lack of clear linkage with
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Commitment to increased external networking; Customer and supplier development; Systematic benchmarking; addressing innate ‘not invented here’ barriers; increased belief in employee socialization processes as sources of knowledge
Development of strategy for comprehensive and systematic approach; identification of key strategic themes for idea generation; use and evaluation of multiples sources; need to address lack of use of ideas in the past; strategy must be communicated to show progression beyond TQM/CI
Knowledge Creation
Idea Generation
Links to strategy
Communicating the purpose of the measures to multiple sources; avoiding traditional critique of ideas and showing creativity and innovation measurement purpose; overcoming past disillusionment of rejected ideas; showing the ideas may have a more relevant purpose later
Improving understanding of knowledge creation as contributing to competitiveness; accepting increased subjectivity; identifying measures; seeing the purpose of intangible measures; acceptance of KC measures at employee, customer and supplier levels
Purpose of measures
Developing much more comprehensive idea measurement and analysis; e.g. sources, levels of employee, customers, suppliers, networks; idea generation becoming more structured and regular with increased number of sources; system for giving feedback for ideas used and those to be reinvestigated at a later date within resource limits
Fundamental change to data collection and analysis methods to include subjective and intangible measures; difficulties in relating KC measures to bottom-line improvements; increased training and development in the new methods and measures; overcoming the ‘it cannot be measured – therefore ignore it’syndrome
Data collection and measurement analysis
Concerns about resources and payback and raising expectations of employees; fear of giving best ideas without any payback, undue early criticism of ideas, lack of learning from outside sources especially customers and suppliers and network contacts
Confidentiality issues regarding two way flow of knowledge; concerns regarding employee involvement in the decision-making process; training and development issues and lack of confidence in their creativity and innovation contribution; need for more customer and supplier inputs
Involvement of stakeholders in measurement selection
Table 2. Transitional Dynamics Matrix – Key Issues (Activities of the Creativity and Innovation Process versus Measurement Principles)
Reviews tended to focus on the more tangible aspects of idea generation; lack of systematic review of the measures used and their sources; need for measures to be more established before a meaningful review can take place
Difficulties and lack of confidence in selecting measures for KC led to a lack of systematic review; there was some review of environmental sources such as customers and suppliers; some difficulty with the concept of measures needing to change rather than reviewing results
Measurement review dynamics
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Develop screening rules consistent with strategy; constantly check for inbuilt bias; changing resource priorities based on strategy; involvement of employees in screening
Changing structure to reflect innovation strategy; support and development of communities of practice and inter company networks; devolve decision-making
Innovation Structure
Links to strategy
Idea screening
Table 2. Continued
June 2004 Sowing that measures of decision-making and empowerment of employees can directly affect the process of innovation and creativity; showing commitment to the support of communities of practice and networks through measures
Communication of the need for convergence and the cost and resource implications that must be measured; demonstrating that the screening rules and measures are consistent with the new approach to creativity and innovation
Purpose of measures
Using the data analysis to show the contribution of employees, networks, customers and suppliers to creativity and innovation leading to investment in knowledge beyond that of the owner/manager and the associated decision-making process
Redesign of the screening process to cover more creative and innovative ideas coupled with scarce capital and resources; communicating the constraints and opportunities to employees
Data collection and measurement analysis
Managers want the structure to support creativity and innovation without the risk of anarchy; employees: see the introduction of creativity and innovation-based structures as leading to increased empowerment and involvement in the decision-making process
Heightened awareness of the cost of taking one idea to market, the dander of selecting the wrong idea and the morale implications of rejecting ideas; require more involvement in the screening process, have difficulty in accepting screening rules which reject their ideas
Involvement of stakeholders in measurement selection
The old organizational structures were wellknown and tested, however the creativity and innovation-based structure changes had led to cultural change, the measurement of which was still in a state of flux; difficulties in obtaining a stable state of measures in these circumstances
Lack of rigorous review of existing idea screening rules and measures led to creativity and innovation being filtered out; the changing environment and business strategy along with the introduction of creativity and innovation created the need for ongoing dynamic change to screening rules and measures
Measurement review dynamics
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Building on TQM/CI strategy, culture and approaches; clarifying the difference between incremental and more innovative improvement at a strategic formulation level; going beyond TQM/CI strategy; overcoming the complacency of TQM/CI success
Developing strategic process approaches to creativity and innovation; applying radical approaches to strategic process improvement; devising strategic process benchmarking
TQM/CI
Business Process Innovation
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Showing how business processes can incorporate creativity and innovation through measurement; demonstrating the links to increased competitiveness; increasing focus on the end customer measures of the business processes
Using the existing TQM/CI measures and purpose to communicate the need to build on creativity and innovation for increased competitiveness; overcoming the incrementalisn of CI ingrained in past practice; instilling the purpose of creativity and innovation measures into TQM/CI teams
Taking advantage of business process measurement systems to build in creativity and innovation measures; developing and analysing measures for the process of creativity and innovation; focus on business processes which contribute most to the company’s strategic objectives and which reach the end customer
Build on the established TQM/CI data gathering and analysis system, e.g. teams, customers; realizing the need to expand beyond these systems to incorporate creativity and innovation measures and analysis; going beyond cause and effect rationale and taking a more phenomenological approach to data gathering and analysis
Aware of the risk associated with large scale business process change, creativity and innovation is seen as adding even more risk; concerned about changes to business processes that affect their roles and responsibilities, will increased creativity and innovation require more process skills on top of their already multifunctional roles?
Owner/Managers see the need to build on the success of TQM/ CI and further develop to achieve creativity and innovation, difficulty with the need for new approaches rather than solely extrapolation of past approaches; need training and development to see the differences and synergies between TQM/CI and creativity and innovation
Business processes were found to be well suited to developing creativity and innovation measures; limited by the overriding need for production measures associated with business processes; need to extend process and measurement thinking within customers and suppliers as part of a measurable customer supply chain in creativity and innovation
The TQM/CI measures were well developed and systematically reviewed using the Business Excellence Model; lack of challenge to existing TQM/CI measures to include creativity and innovation; difficulties in going beyond the Business excellence concept of cause and effect measures
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Developing benchmarking as part of a strategy for acquiring new knowledge; benchmarking to support creativity and innovation strategy at organizational, process and product levels; overcoming the not invented here syndrome
Establishing KM as a strategic issue; integrating KM with creativity and innovation strategy; acceptance of employee empowerment as helping to make a contribution to KM and strategy; addressing the effect of KM on power relations
Knowledge Management
Links to strategy
Benchmarking
Table 2. Continued
June 2004 Using KM as a system to gather and synthesize the contributions to knowledge into measures with a clear purpose in regard to creativity and innovation; moving beyond the ‘nice to do’ stage; assigning responsibilities for those who already have multiple roles
Increasing the use of outside knowledge as a key catalyst for innovation and creativity; developing measures to show the contribution from different types of benchmarking to achieve increased creativity and innovation
Purpose of measures
Clarification of data, information and knowledge terminology; Linking ad-hoc approaches to KM; simplifying large organization solutions (sometimes from customers); ensuring the KM is flexible enough to cope with the inherent flexibility of the SME
Systematic benchmarking analysis for formal and informal benchmarking depending on resource constraints; overcoming the tendency to avoid intangible and subjective measures in creativity and innovation.
Data collection and measurement analysis
Wants the benefits of a KM system but has insufficient resources for a more developed system; able to adapt between formal and informal KM systems provided training and development is given showing the importance of KM in relation to creativity and innovation; Customers and suppliers give new perspectives
Sees the need to contextualize benchmarking findings to suit the current markets of the SME; tendency to oversimplify benchmarking findings leading to unrealistic expectations, especially when looking at best practice in larger organizations
Involvement of stakeholders in measurement selection
Efforts to revise the plethora of KM measures into a manageable set which could be supported by the company’s systems and resources; need for more comprehensive training and development to understand and develop KM measures, especially in showing the link to the ‘bottom-line’
More revision of benchmarking measures was needed to contextualize the findings of creativity and innovation benchmarking findings; lack of understanding of ‘moving benchmarks’; more rigorous creativity and innovation benchmarking studies within resource limitations
Measurement review dynamics
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strategy in a reflective and reflexive manner. In this respect the relative informality and flexibility of the SMEs strategy was advantageous, in that changes could be readily incorporated. The activities of the innovation process had closer links with the strategy in that TQM/CI was well established in all the cases with ‘measurement systems linked to strategic key success factors’. Moreover, the TQM/CI programmes were successfully used to demonstrate the need for both incremental and radical change in the organisations, as found by Raymond, Bergeron and Rivard (1998). The use of the Business Excellence Model in TQM/CI programmes reinforced the concept of cause and effect through the enabler–results structure, thus making it more difficult to introduce phenomenological approaches. The strategic business process innovation and benchmarking activities refocused attention on the need for new knowledge and hence KC. The process approach was linked to the strategy by extending the processes into supplier and customers. The largest issue in transitioning towards effective KM measures linked to the strategy was senior management’s acceptance of employees ability to generate new knowledge in communities of practice and networks (Pedlar, 1998).
Making the Purpose of the Measures Explicit In cases where the measurement purpose was not fully understood, the measures remained as impositions and distractions from the perceived goals of the company (Neely et al., 2000). There were two key issues relating to the purpose of the measures. First, there was a need for clarity and understanding at all levels and in all areas of the cases of the purpose of creativity and innovation. This knowledge came gradually throughout the study, thus the realization of the purposes of the creativity and innovation measures took considerable time. Second, understanding of the purpose of the creativity and innovation measures was dependent on an acceptance by managers and employees that a clear link to competitiveness existed. Thus, there was a need to show how measures related to company strategy and markets (Vossen, 1999), as discussed in the previous section. This dynamic interplay between the measurement principles was also noted by Neely et al. (2000). In the creativity process in relation to KC and IG, cause-and-effect rationale was initially applied in seeking to trace and understand the purpose of highly subjective and often intangible phenomena and related measures, such as the strength of relationships and networks
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(Amabile et al., 1996; Robertson, Swan & Newell, 1996). For example, some measures of failure were immediately categorized into error classes with punitive purposes attached, rather than seeing these measures as an opportunity develop. Idea Screening (IS) benefited in those cases, which involved employees from all levels in the screening process. This approach led to a more in-depth understanding of creativity process and measures by increasing dialogue throughout the company as found by Klein and Sorra (1996). Understanding and acceptance of the purpose of innovation process measures benefited from existing knowledge of TQM/CI. Managers attempted to portrait innovation measures as an extension of TQM/CI rationale as suggested by Grint and Willcocks (1995). However, this approach was hindered by incrementalism as the previous success of TQM/CI was such that the philosophy of step by step improvements and cause and effect tools and techniques (e.g. fishbone and Pareto diagrams), was so ingrained that making the conceptual leap to radical phenomena and measures was difficult and time consuming. The use of business process innovation and benchmarking approaches helped to alleviate this problem as more radical changes and measures could be more readily understood in a process context, with supporting evidence from benchmarking studies (Raymond, Bergeron & Rivard, 1998). The links to strategy and purpose for creativity and innovation measures challenged the cases to move from KM rhetoric and adhoc approaches, towards a more comprehensive and integrated approach. Impediments to progress were lack of resources, especially capital for information systems, and lack of training and development in KM approaches. In some cases the number of measures had to be rationalised as ‘too many measures result in a watered down unfocused set that loses its significance’ (Kuczmarski, 2001). Thus, there was a move away from large checklists of measures towards a smaller number of more important measures used to pinpoint the area of need as suggested by Kuczmarski (2001). In summary, the principle of making the purpose of creativity and innovation explicit had helped to challenge managers and employees in relation to their understanding of creativity and innovation and how it can lead to increased competitiveness (Amabile et al., 1996).
The Need for Systematic Data Collection and Measurement Analysis Data collection and measurement analysis for creativity and innovation represented a sig-
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nificant challenge to the case SMEs. Difficulties in establishing and clarifying strategic links and measurement purpose were now being compounded with the need for use of scarce resources (especially time and capital). Also, in the earlier stages of the transition, the existing capital expenditure processes and rationale could not cope with the longer term, intangible and subjective possibilities offered by creativity and innovation investment (Robertson, Swan & Newell, 1996). In the creativity process, the main challenge was to collect and measure intangibles and subjective data. This data, information and knowledge was incongruous with, and conflicting with, existing systems as found by Deazin, Glynn and Kazanjian (1999). For example, data fields could not readily be adapted to take qualitative indicators in most existing systems. Expenditure included the design, purchase and installation of the data collection and analysis system, training and development of the analysis and the receivers of the resultant measurements. Although most of the cases offset these costs with government and local government grant assistance, there was still a considerable outlay and disruption for each company. Thus, at this stage it was important to emphasize the measurement purpose and the links to strategy and competitiveness in the longer term (Neely et al., 2000). The IS part of the creativity process benefited most tangibly from the new and improved measures systems in that ideas could be gathered and screened much faster. The data-collection and measurement systems were effectively used in supporting the revised creativity and innovation structures (e.g. communities of practice and networks) within the case organizations. Moreover, the increased sharing of measures led to increased empowerment in the workforce (Slappendel, 1996). The new or improved data-collection and measurement approaches benefited existing TQM/CI programmes in the cases, although attempts to incorporate creativity and innovation measures within an expanded Business Excellence Model failed due to the inadequacy of the underlying cause-and-effect rationale. In conclusion, the data-collection and measurement systems became the engines of the KM approaches within the cases. Thus, links with strategy and purposive measurements of creativity and innovation became much more possible and real leading to more support within each of the cases. Comments such as: ‘there is an abundance of knowledge not being transferred to lower levels and decision makers’, were replaced by: ‘the appetite for
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change is growing and we are keen to share [knowledge]’.
Involvement of Stakeholders in Measurement Selection The discussion on stakeholders is limited to that of employees, management, customers and suppliers because of space constraints. Initially, the cases suffered from a ‘not invented here syndrome’ in relation to stakeholders, hence customer and supplier voices were treated in a normative manner (with the exception of TQM/CI projects and activities). This situation was compounded by management not recognizing the employees as a valuable and contributing stakeholder. Therefore, first, considerable efforts were made to both identify and recognize the key stakeholder groupings. Progress was epitomized by one manager who stated: ‘the workforce is at the centre of the creativity and innovation process as they have their ears to the ground and know what is going on’. The KC and IG elements of the creativity process initially created a dichotomy for some of the owner/managers. They desired increased competitiveness: however the involvement of customers, suppliers and employee stakeholders, amongst others, in generating new knowledge ideas and resultant measures was viewed as diluting management responsibility. Culkin and Smith (2000) indicate that the ability to make decisions rapidly is an innate strength of SMEs. Therefore, the inputs of other stakeholders had to improve creativity and the decision-making process, as perceived by management. The integration of customers, suppliers and employee stakeholders in developing creativity measures led to closer coupling of the customer supply chain process. Ford (2000) indicates that most profitable ideas come from interaction with the customer. Similarly, one of the senior managers concluded that: ‘we can never have enough emphasis on the customer contribution to creativity and innovation’. The TQM/CI programmes, business process structure and benchmarking approaches reinforced a team-based structure where teams had reasonable autonomy to decide innovation measures and targets (Amabile et al., 1996). These teams often involved customers and suppliers who brought multiple perspectives to creative problem solving. For example, one customer representative introduced and trained (informally) a case-team in rich picture techniques when an impasse was reached with existing cause-and-effect approaches.
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The KM systems acted as overall stakeholder involvement mechanisms. Both formal and informal KM approaches led to multiple stakeholder involvement in data gathering, analysis and measurement throughout the creativity and innovation process. The common need for competitiveness mollified tensions between the stakeholders.
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measurement review and alignment with environmental changes. In summary, creativity and innovation measures were reviewed during the transition period for appropriateness and effectiveness. If SMEs are to use these measures in support of their innate flexibility in pursuing market opportunities, then these measures must be dynamically reviewed.
The Measures should be Changeable based on Organizational and Environmental Dynamics
Conclusions and Recommendations
Having encouraged creativity and innovation as a source of competitive advantage there was a danger at a meta level that too much rigidity in the resultant measures could restrict the innate flexibility of the SMEs in developing niche markets (Choueke & Armstrong, 1998). Thus, there was a need during the transitional period to ensure the data collection, data analysis and measures were adaptable to different scenarios, dependant on organization and environmental change dynamics. In relation to the creativity process, especially for KC and IG, there was a need to change measures. A transitional period existed, with measures were being continually developed and modified as understanding increased. Initially this led to lack of confidence in the measures. However, systematic benchmarking led to increased validation of the measures used. Moreover, there was a conceptual thinking difficulty in accepting that for KC and IG, review of which measures to use (e.g. team effectiveness, customer contribution) was as important as reviewing results (e.g. number of ideas, number of customer ideas). The cases then compared these additional measures with the overall portfolio to avoid using too many measures (Kuczmarski, 2001). Dynamic review of measures was found to be essential at the idea-screening stage, as the SMEs were in rapidly changing markets where agility was essential. Therefore, ineffective review of screening measures sometimes led to missed market opportunities and wasted scarce resources. In relation to the innovation part of the process the principles of measurement review had been established in many of the case’s TQM/CI programmes, along with the move towards empowered teams. However, the use of the Business Excellence Model in supporting and reviewing measures tended to minimize the effect of creativity and innovation measures as they are not fully addressed in the model. The business process innovation and benchmarking approaches were well suited to
The aim of this paper was to explore the transition, from traditional measures to that of creativity and innovation measures, within a multiple-case SME study. The literature section revealed that creativity and innovation measurement must be systematically addressed if this area of study is to become an essential part of an SME’s strategy for increased competitiveness. Measurement must not be seen as obtrusive and contradictory within the process of creativity and innovation; rather, the measures should be dynamic and changeable, supporting development and closure (Neely et al., 2000). Lists of before and after measures were prevalent in the literature. However, there is a paucity of studies, which focus on the transitional dynamics in moving towards creativity and innovation for SMEs. To structure the findings from the study key measurement principles (Neeely et al., 2000) were cross-mapped with the process elements of creativity and innovation (Table 2). The conclusions are based on each of the measurement principles. In relation to the need to link measures to the strategy, the largest issue in making the transition towards effective creativity and innovation measures linked to the strategy was senior management’s acceptance of employees ability to generate new knowledge in communities of practice and networks (Pedlar, 1998). The principle of making the purpose of creativity and innovation measures explicit acted as a catalyst in making management and employees think through how creativity and innovation could lead to increased competitiveness. This increased understanding helped strengthen the links to strategy and in developing appropriate training and development as found by Rickards (1999). The principle stating the need for datacollection and measurement systems led to KM approaches being the engine of measurement within the cases. This approach strengthened the links with strategy and purposive
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measurements of creativity and innovation, leading to more support and less resistance within each of the cases. The principle of involving stakeholders in selecting measures led to KM systems acting as overall stakeholder involvement mechanisms. The main stakeholders considered were employees, management, customers and suppliers. However, it is noted that many other networked stakeholders existed. The need for the measurement review principle was found to be essential in supporting the innate flexibility of SMEs in responding to market needs and changes. Measures were dynamically reviewed, which supported the innate flexibility of the SMEs in pursuing market opportunities. Overall, the inquiry into the transitional dynamics of creativity and innovation measurement has found that the multiple case cross-mapping of Neely et al.’s (2000) measurement principles with the process elements of creativity and innovation has led to a fuller and deeper understanding. It is concluded that the measures are not an end point but a dynamic phenomena that must be continually reviewed and developed during the transitional period when creativity and innovation is developed. The implications for managers in organizations are twofold. First, the importance of measuring creativity and innovation must be given more strategic and operational importance, rather than being treated as unknown territory. Second, a wide or eclectic range of measures should be adopted, reflecting the diversity within creativity and innovation.
References Amabile, T., Conti, R., Coon, H., Lazenby, J. and Herron, M. (1996) Assessing the work environment for creativity. Academy of Management Journal, 39(5), 1154–84. Amabile, T., Hadley, C. and Kramer, J. (2002) Creativity under the Gun. Harvard Business Review, August, 52–61. Chaston, I., Badger, B. and Sadler-Smith, E. (1999) Small firm organisational learning: comparing the perceptions of need and style among UK support service advisors and small firm managers. Journal of European Industrial Training, 23(1), 36–43. Choueke, R. and Armstrong, R. (1998) The learning organisation in small and medium-sized enterprises: A destination or a journey. International Journal of Behaviour and Research, 4(2), 129–40. Creswell, J. (1994) Research design: Qualitative and quantitative approaches. Sage, London. Culkin, N. and Smith, D. (2000) An emotional business: a guide to understanding the motivations of
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small business decision takers. Qualitative Market Research: An International Journal, 3(3), 145–57. Dale, B. and Lascelles, D. (1997) Total quality management adoption: revisiting the levels. TQM Magazine, 9(6), 418–28. Deazin, R., Glynn, M. and Kazanjian, R. (1999) Multilevel theorising about creativity in organisations: a sensemaking perspective. Academy of Management Review, 24(2), 286–15. Eisenhardt, K. (1989) Building theories from case study research. Academy of Management Review, 14, 532–50. Ford, C. (2000) Creative developments in creativity theory. Academy of Management Review, 25(2), 284–85. Freel, M. (2000) Barriers to product innovation in small manufacturing firms. International Small Business Journal, 18(3), 60–81. Gorton, M. (2000) Overcoming the structure – agency divide in small business research. International Journal of Behaviour and Research, 6(5), 276–92. Grint, V. and Willcocks, L. (1995) Business Process Reengineering in Theory and Practice: Business Paradise Regained. New Technology, Work and Employment, 10 (2), 99–109. Hassard, J. (1995) Sociology and Organisation Theory: Positivism, Paradigms and Postmodernity, Cambridge University Press, Cambridge. Kuczmarski, D. (2001) Five fatal flaws of innovation metrics. Marketing Management, 10(1), 34–9. Klein, K. and Sorra, J. (1996) The Challenge of Innovation Implementation. Academy of Management Review, 21(4), 1055–1088. King, N. (1992) Modelling the innovation process: an empirical comparison of approaches. Journal of Organisational and Occupational Psychology, 65(2), 89–91. Neely, A., Mills, J., Platts, K., Richards, H., Gregory, M., Bourne, M. and Kennerley, M. (2000) Performance measurement system design: developing and testing process-based approaches. International Journal of Operations and Production Management, 20(10), 1119–1145. Pedlar, M. (1998) Critical Action Learning. In Burgoyne, J. and Reynolds, M. (eds) Managing Learning. Sage, London. Raymond, L., Bergeron, F. and Rivard, S. (1998) Determinants of business process Reengineering success in small and large enterprises: An empirical study in the Canadian context. Journal of Small Business Management, 36(1), 72–85. Remenyi, D., Williams, B., Money, A. and Swartz, E. (1998) Research in Business and Management. Sage, London. Rickards, T. (1999) Creativity and the Management of Change. Blackwell, Oxford. Robertson, M., Swan, J. and Newell, S. (1996) The role of networks in the diffusion of technological innovation. Journal of Management Studies, 33(3), 333–59. Sadler-Smith, E., Sargeant, A. and Dawson, A. (1998) Higher level skills training and SMEs. International Small Business Journal, 16(2), 84– 94.
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Shaw, E. (1999) A guide to the qualitative research process: evidence from a small firm study. Qualitative Market Research: An International Journal, 2(2), 59–70. Slappendel, C. (1996) Perspectives in innovations in organisations. Organisation Studies, 17(1), 107–129. Tidd, J., Bessant, J. and Pavitt, K. (2001) Managing Innovation: Integrating Technological, Market and Organisational Change. Wiley, Chichester. Vossen, R. (1999) Relative Strengths and Weaknesses of Small Firms in Innovation. International Small Business Journal, 16(3), 88–94. Willmott, H. (1993) Breaking the Paradigm Mentality. Organisation Studies, 14(5), 681–720. Wolpert, J. (2002) Breaking out of the Innovation Box. Harvard Business Review, August, 77–83. Woodman, R., Sawyer, J. and Griffin, R. (1993) Toward a theory of organisational creativity. Academy of Management Review, 18(2), 293–321. Yin, R. (1994) Case study Research: design and methods. Sage, Thousand Oaks CA.
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Dr Rodney McAdam is Reader in Management at the Faculty of Business and Management, University of Ulster. He has recently received The Distinguished Research Fellowship Award from the University of Ulster. He has a number of publications (120+) in the area of Knowledge, Innovation, Quality Management and Business Improvement. University of Ulster, School of Business, Organisation and Management, Jordanstown Campus, Belfast BT37 OQB, UK. E-mail
[email protected] Professor William Keogh is the professor of enterprise and entrepreneurship at Heriot-Watt University. He has 100+ publications in the area of small business, innovation and the business environment. He is the Director of the Scottish Enterprise Institute and sits on the board of a number of companies and editorial boards.
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Book Review Larisa V. Shavinina (2003) The International Handbook on Innovation. Pergamon, Amsterdam. Hback, 1208 pp, ISBN 008044198X The importance of innovation for the competitiveness of firms and as an engine of growth at a regional or country level is widely recognized. Researchers, practitioners and policy makers do agree that the process of innovation is of immense social interest and impact. By delivering a compelling edited volume, Larisa Shavinina tries to enrich our understanding of innovation as a multidimensional, multifaceted and interdisciplinary research domain. Moreover, this handbook on innovation does not only present a comprehensive picture of contemporary innovation research, but it also has the intention to outline directions for further research, advancing the field of innovation. The handbook is divided into 15 parts. The first part provides a general introduction to the work by Shavinina. Parts 2 to 14, consisting of 69 chapters, offer a broad analysis of what innovation is, how it is developed, how it is managed, how it is assessed and how it affects individuals groups, organizations, societies and the world as a whole. In the final part of the handbook, Larry Vandervert integrates the results, insights and recommendations of the different chapters. He both develops an evolutionary ‘arrow’ of innovation and applies mapping approaches to grasp and frame the great diversity of ideas and approaches to innovation that are brought forward in this handbook. Because of the large amount of chapters, it is impossible to provide a detailed description of all of them. Therefore, I have chosen to highlight some ‘critical research themes’ that emerge out of the different chapters. I will present these themes by looking at three different levels of innovation: the individual, the firm and the national level.
Innovation at the Individual Level: the Nature of Individual Innovation In this handbook, a large number of authors (e.g. Bailey & Ford; Vandervert; Shavinina & Seeratan; Renzulli; Root-Bernstein; Kaufmann; Weisberg; Colangelo et al.; Simonton; Heinzen
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& Vail; Holton; Shavinina; Swede) pay attention to the individual nature of innovation. Specifically, they try to explain why some people behave in a creative, inventive or innovative way, while others do not. Interesting hypotheses in this respect are formulated by different authors. Root-Bernstein, for instance, argues that people are creative and innovative only when they need to do something that cannot yet be done. Kaufmann, questioning the existing positive causal link between positive mood and creativity, stresses that, under certain conditions, negative and neutral moods may facilitate the emergence of creative solutions to problems. The study by Heinzen and Vail provides empirical support for these statements. Assessing innovations by frail elderly, living in nursing homes, they argue that (1) the impetus for innovation may be external, unpleasant and unwelcome (p. 312); (2) innovation does not require a ‘creative personality’, ordinary personalities in extraordinary circumstances will attempt to innovate (p. 313); (3) frustration and suffering can nurture innovation (p. 314). These chapters indicate that the environment is an important variable to take into consideration when we want to explain the nature of individual innovation. Therefore, following Heinzen and Vail, I think selecting ‘creative environments’ instead of ‘creative persons’ as unit of analysis, seems to be a promising research strategy to study the nature of individual innovation.
Innovation at the Firm Level: How do Firms Balance Between Structure and Chaos? According to a large amount of authors in this handbook (e.g. Bessant; Boly, Morel & Renaud; Carayannis, Gonzalez & Wetter; Cooper; Gassmann & von Zedtwitz; Georgsdottir, Lubart & Getz; Gutmann; Hadjimanolis; Hauschildt; Katz; King; Miyata; Nag, Corley & Gioia; Nightingale; Prencipe; Souitaris; Zhou & Woodman) innovation is crucial for the longterm survival and growth of the firm.
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However, most of these contributions also illustrate that managing innovation is not a straightforward task. Katz, for instance, argues that organizations, because of the need both to function efficiently today and to innovate effectively tomorrow, face paradoxical requirements with respect to managing technological innovation. After all, organizations must build internally those contradictory and inconsistent structures, competencies and cultures that not only foster more efficient and reliable processes but that will also encourage the kinds of experiments and explorations needed to recreate the future (Katz, p. 776). Similarly, Nag, Corley and Gioia stress that organizations need to balance between structure, needed to exploit existing technologies and chaos, necessary to explore new technologies and market opportunities. Based on these findings, innovation seems to be a process in which tensions and conflicts are inherently present. Concepts like the ambidextrous organization (Katz), managed chaos (Nag, Corley & Gioia), and the cloudy-to-component process (Gassmann & von Zedtwitz) are brought forward to help organizations to overcome these tensions successfully. These alternative options are not only interesting for academics who want to research the process of technological innovation within firms, but can also help managers to improve the innovative performance of their own organization.
Innovation at the National Level: How Can Governments Stimulate Innovation? Innovation can also be studied at a national level. Each nation has its own practices and policies to stimulate and organize innovation. Such national innovation systems are discussed in Part XIII of this handbook, in which several authors (e.g. Chung; Conceição & Heitor; Grupp, Lacasa & Friedrich-Nishio; Harding; Hsu & Chen; Inzelt; Mehra; Nonaka, Sasaki & Ahmed; Persuad, Kumar & Kumar; Tang & Yeo; Wilhelm) discuss the innovation systems of different countries. A criticism that often returns in these chapters is that governments still consider innovation as a linear process. Marinova and Phillimore, by presenting a historical overview of innovation models, argue that such a linear model can not explain the variety of interactions necessary for the success of innovation. Therefore, policy makers need to reconsider how innovation can be stimulated and organized on a national level. Within this handbook several suggestions are formulated in this respect. Wilhelm, by studying the Swiss innovation system, pro-
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poses a shift from the linear model to a network model in which universities, firms and governmental institutions are strongly embedded. Major and Cordey-Hayes, by looking at national innovation schemes within the UK, propose that the government should encourage intermediary organizations to bridge the knowledge translation gap that nowadays limits the innovative potential of small firms. In my opinion, this handbook is helpful especially for people who are searching for new and challenging research questions within the field of innovation. After all, this handbook not only contains excellent overviews on specific innovation topics, written by leading innovation researchers, it also brings forward critical questions and provocative statements that stimulate the creation of creative and innovative research projects. Moreover, this handbook contains a large amount of new methodological approaches that can support this kind of research. Looking at non-normative populations (Heinzen & Vail), applying portfoliobased measures of innovation (Souitaris) or combining literature-based and workshopbased approaches (Kostoff), are just a few examples of such ‘innovative’ methodologies. I would like to end this review with one critical remark: within the preface of the handbook, Shavinna states that ‘the handbook can be considered as the first serious attempt to unify the field of innovation and, consequently, as the beginning of unified science of innovation’. In my opinion, the handbook has not fully accomplished this mission. Although the handbook comprises chapters of various research domains such as psychology, economics, organization theory and even neurophysiology, cross-fertilization between the different domains is limited. Moreover, I think that, if we want to achieve a ‘unified science of innovation’, we first of all have to agree on what innovation actually stands for. Therefore, I was disappointed by the fact that each chapter used its own definition of innovation. Some chapters, for instance, made a clear distinction between invention and innovation, while others did not. Nevertheless, for the impressive range of up-to-date material, the book deserves a place as a reference text for academics, practitioners and policy makers. Moreover, by providing critical questions and outlining new research directions, it makes a welcome addition to the innovation field. Dries Faems Researcher at the Incentim Research Division, Catholic University of Leuven
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