EDITORIAL
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Editorial
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his first issue of 2011 contains two regular articles and three articles based on papers presented at the EIASM-IPDMC conferences in Twente (2009) and Murcia (2010). The opening article is from the Murcia conference. Katja Hutter, Julia Hautz, Johann Füller, Julia Mueller and Kurt Matzler introduce the concept of ‘communitition’. Companies are increasingly using online design contests to foster the generation of creative solutions. Virtual platforms allow users both to competitively disclose their creative ideas to corporations and also to communicate, discuss and share their insights and experiences with likeminded peers. This article shows with rich data that contest communities and companies benefit from ‘communitition’, the simultaneous stimulation of co-operation and competition in an online design contest. The second article is also based on a paper from the Murcia conference and concerns a highly related topic. Karsten Frey and Christian Lüthje investigate the antecedents and consequences of interaction quality in virtual end-user communities. Drawing on data collected through a web-based survey, this study explores the innovation activities of 127 virtual end-user communities. The findings confirm that interaction quality is positively related to the innovativeness of virtual communities. Concerning the antecedents of interaction quality, the authors show that trust is a key prerequisite to co-operative behaviour. The level of competition, however, only affects interaction quality if a high level of trust among members is present. Community managers need to create an environment that facilitates interaction among the members of innovation communities. Furthermore, they should ensure a minimum level of trust is established within the community before stimulating competition. The third article, originally presented in Twente, presents research by Claudio Dell’Era, Tommaso Buganza, Camilla Fecchio and Roberto Verganti on the Language Brokering Process. The Language Brokering Process can enrich the dialectic between managers and designers and, consequently, it can improve both current and future innovation projects. This methodology elucidates the structure and process adopted by several designers and also © 2011 Blackwell Publishing Ltd
illustrates an effective framework for communicating choices to managers. Results are presented from a student application of this methodology in the development of a new product-service system for Aquarius (a brand of the Coca-Cola Group) for two target demographics: ‘desperate housewives’ and ‘young adults’. The upcoming 18th EIASM International Product Development Management Conference will be held in Delft (5–7 June 2011) and will focus on innovation through design (see www.eiasm.org). We aim to publish outstanding papers from that conference in 2012. In the fourth article, Sven Hemlin and Lisa Olsson present a study that examines how group leaders in academic and industrial research settings stimulate creativity. Using a modified version of the critical incident technique with 75 participants, the authors identify four kinds of creativity-stimulating leadership behaviours, related to providing expertise, group co-ordination, task assignments and group support. In the final article, Pierre Desrochers and Samuli Leppälä bring together the discourses on creative cities and innovation management. They document how economically diversified cities provide a fertile environment for the discovery and development of new technological combinations. The study illustrates how a better understanding of the linkages between creativity and urban agglomerations would benefit from a multidisciplinary approach that studies both phenomena simultaneously. The issue closes with a book review by Carmen Kobe of The Routledge Companion to Creativity, edited by our founding editors Tudor Rickards and Susan Moger together with editorial board member Mark Runco. This impressive collection of readings on creativity and innovation contains many worthwhile contributions by members of the CIM community! As has become a tradition, in the editorial of each March issues we present to you the shortlist of papers nominated as best CIM paper of 2010. The five selected papers for the Tudor Rickards and Susan Moger CIM Best Paper Award 2010 are:
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• Björk, Jennie, Paolo Boccardelli & Mats Magnusson, Ideation Capabilities for Continuous Innovation, Volume 19, Issue 4. • Bullinger, Angelika C., Anne-Katrin Neyer, Matthias Rass & Kathrin M. Moeslein, Community-Based Innovation Contests: Where Competition Meets Cooperation, Volume 19, Issue 3. • Isaksen, Scott G. & Göran Ekvall, Managing for Innovation: The Two Faces of Tension in Creative Climates, Volume 19, Issue 2. • Jong, Jeroen de & Deanne den Hartog, Measuring Innovative Work Behaviour, Volume 19, Issue 1.
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• Kleinschmidt, Elko, Ulrike de Brentani & Søren Salomo, Information Processing and Firm-Internal Environment Contingencies: Performance Impact on Global New Product Development, Volume 19, Issue 3. They will be available for free download from our website. The winning paper will also be announced on the website and in our June issue. Klaasjan Visscher Olaf Fisscher Petra de Weerd-Nederhof
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Communitition: The Tension between Competition and Collaboration in Community-Based Design Contests caim_589
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Katja Hutter, Julia Hautz, Johann Füller, Julia Mueller and Kurt Matzler Following the concepts of crowdsourcing, co-creation or open innovation, companies are increasingly using contests to foster the generation of creative solutions. Currently, online idea and design contests are enjoying a resurgence through the usage of new information and communication technologies. These virtual platforms allow users both to competitively disclose their creative ideas to corporations and also to interact and collaborate with like-minded peers, communicating, discussing and sharing their insights and experiences, building social networks and establishing a sense of community. Little research has considered that contest communities both promote and benefit from simultaneous co-operation and competition and that both types of relationships need to be emphasized at the same time. In this article, it is argued that the firm-level concept of co-opetition might also be relevant for an innovation’s success on the individual level within contest communities. Our concept of ‘communitition’ should include the elements of competitive participation without disabling the climate for co-operation, as numerous user discussions and comments improve the quality of submitted ideas and allow the future potential of an idea to shine through the so-called ‘wisdom of the crowd’.
Introduction
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orged by globalization and digitalization, it is now possible for billions of individuals scattered all over the planet, connected by the tenuous strands of the Internet, to actively participate in idea generation. This has caused a fundamental change in the innovation process. Following the concepts of crowdsourcing (Kozinets, Hemetsberger & Schau, 2008), co-creation (Winsor, 2005) and open innovation (Chesbrough, 2003), applications such as web-based toolkits (Thomke & von Hippel, 2002), virtual concept testing (Dahan & Hauser, 2002) and virtual worlds (Hemp, 2006; Kohler, Matzler & Füller, 2009) are used to enhance co-operation between users to benefit from collaborative innovation. Several studies show that network effects, reputational gains, the revealing of related innovations by others, the desire to give back to the community, or the hope of feedback from a knowledgeable audience are motives for consumers to © 2011 Blackwell Publishing Ltd
participate in joint innovation activities (Franke & Shah, 2003; Harhoff, Henkel & von Hippel, 2003; Füller, Jawecki & Mühlbacher, 2007). On the other hand, the idea of using contests to reach a broad audience of people with various backgrounds, skills and expertise has a long tradition. For decades, design contests featuring competition between participants competing for the best idea have played a major role in the design of new buildings, technology inventions and breakthrough ideas – in other words, the foundation of novel services or the presentation of new design concepts within several kinds of branches and industries (Fullerton et al., 1999; Che & Gale, 2003). Currently, online idea and design contests are enjoying a resurgence through new information and communication technologies. In contrast to traditional contests, these virtual platforms allow users both to competitively disclose their creative ideas to the corporations and also to interact and collaborate with
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like-minded peers, communicating, discussing and sharing their insights and experiences, building social networks and establishing a sense of community (Bullinger et al., 2010). These patterns of co-operating and competing behaviour presented in online design contests resemble the concept of co-opetition between firms (Brandenburger & Nalebuff, 1996; Albert, 1999; Martinelli, Dussauge & Garrette, 2002; Walley, 2007), defined as a ‘situation where competitors simultaneously co-operate and compete with each other’ (Bengtson & Kock, 2003). This balance of the co-operative and competitive interactions between companies could also be identified by recently emerging studies of innovationrelated co-opetition, with a focus on the level of the firm (Cassiman, Di Guardo & Valentini, 2009; Ritala & Hurmelinna-Laukkanen, 2009) or at unit level in multiunit organizations (Tsai, 2002). In this way, OSRAM – one of the world’s leading light manufacturers – created an online idea contest in which its community members jointly developed new and consumer-oriented LED light solutions (OSRAM, 2009). By observing communication paths and participation behaviour among users over time, we can discover that an important characteristic of virtual idea design contests is indeed co-opetition (Brandenburger & Nalebuff, 1996; Walley, 2007), or the balance between co-operative behaviour – by providing useful comments – and competitive behaviour – by trying to outperform others. Little research has studied elements of co-opetitive behaviour in design contests and the question of whether and – if so – how idea contests benefit from simultaneous co-operation and competition behaviour simultaneously. By integrating these considerations with the concepts of idea contests, our study sheds light on the following research questions: (1) Are competitive as well as co-operative elements required for successful co-creation outcomes of online idea and design contests? (2) What types of user contributions can be identified and how do they support successful co-creation? (3) What roles, with different implications for the competitive and co-operative aspects of online idea and design contents, can be identified and how do they contribute to successful innovation outcomes? The rest of the paper is structured as follows: we briefly review the evolution of idea tournaments and the relevant literature on open-source projects, online communities and virtual consumer integration to identify relevant behaviour patterns in innovation communities. Then, we present the design of our study and the results of our analysis.
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Finally, we conclude with a discussion of theoretical as well as practical implications of our findings.
Literature Review Using Contests to Unlock the Potential of the Crowd Research tournaments and contests for ideas are reward structures in which compensation is based on relative rank. Participants compete with each other for rare prizes for their submitted ideas (Morgan & Wang, 2010). Such tournaments have played a major role in the economic growth of nations since the early stages of the Industrial Revolution (Fullerton et al., 1999). In 1714, the British Parliament, for example, offered a prize of £20,000 (with a value today of about £6m) for finding a reliable method of determining the longitude of a ship’s location. The Longitude Prize was established not only to lead to the invention of a superior piece of equipment, but also to further fix the British Empire’s dominion over the sea (for additional background information on the British Longitude Prize, see Sobel, 1996). More recently, research tournaments and contests have been organized to create a variety of new, innovative products, such as high-tech fighter aircraft for the military, digital televisions and the first manned space mission to Mars (Fullerton et al., 1999; for additional information, see Zubrin, 1996). These tournaments are proposed by innovative corporations, governments or non-profit organizations as a vehicle to spur innovations (Morgan & Wang, 2010). In the past, organizations promoted their contests through the corresponding channels whereby they might reach experts. However, ever since the emergence of the Internet and the existence of novel information and communication technologies, contests have been run through virtual platforms. Companies invite interested users to engage with questions and problems regarding a certain topic or product range, to show their talent by uploading their creative content and to compete for prizes. On the one hand, these idea and design contests encourage competition between participants competing for the best idea and thus win the tournament. On the other hand, these virtual platforms allow users to both disclose their ideas to firms and also to offer community functionalities – the creation of a user profile, discussion boards, chat functionalities, voting systems. This, in turn, allows for the further discussion and sharing of insights with like-minded people, who vote © 2011 Blackwell Publishing Ltd
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on which idea or design they like best, discuss various topics by leaving comments on other users’ message boards, interact with other like-minded peers, build social networks, establish a sense of community, receive assistance from other community members and generally derive benefits through collaborative innovating activities. These idea and design contests add a great deal of value to a company’s innovation process and are evidence of the fact that people are indeed willing to share their ideas, submit their innovative solutions, give valuable feedback and provide insights for improvement. Thus, in these community-based design contests, the announced prize or the act of winning the tournament is no longer the only motive to induce the submission of ideas; instead, there are additional motivations and benefits that are crucial for successful co-creation.
Collaborative Innovation and Competition among Community Members The phenomenon of ‘online innovation communities’ – both users and manufacturers who produce ideas and inspirations for new product development – has become the subject of considerable interest in research and in practice (von Hippel, 2005; von Krogh & von Hippel, 2006; Schröder & Hölzle, 2010). Drawing on the rich body of research founded in related fields such as open-source projects (Hars & Ou, 2002; Hertel, Niedner & Herrmann, 2003; Lakhani & Wolf, 2005; Nov, 2007; David & Shapiro, 2008; Oreg & Nov, 2008; Schroer & Hertel, 2009), virtual communities of practice (McLure Wasko & Faraj, 2000, 2005; Ardichvili, Page & Wentling, 2003; Sharatt & Usoro, 2003; Daugherty et al., 2005; Ardichvili, 2008), and user innovation communities and virtual consumer integration (Hemetsberger, 2002; Franke & Shah, 2003; Füller, 2006), we are offered rich insights into the motives behind why community members participate in innovation communities and the benefits of revealing their knowledge, as well as into how and why they support each other. Collaboration in communities is based on the participants’ willingness to freely reveal their knowledge and expertise and openly work together (von Hippel & von Krogh, 2003). Free revealing means ‘that all existing and potential intellectual property rights to that information are voluntarily given up by that innovator and all interested parties are given access to it – the information becomes public’ (Harhoff, Henkel & von Hippel, 2003, p. 1753). Well-known community examples of free revealing and open collaboration can be © 2011 Blackwell Publishing Ltd
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found in the context of open-source software development. Expert programmers at various levels, supporters and users are voluntarily contributing to a collaborative software project. They freely reveal the source code they have produced (von Hippel & von Krogh, 2003) in order to create and collectively improve software programs. Franke and Shah (2003) showed that members of sports communities also assist each other in developing their innovations. The free revealing of assistance, information and innovation was identified as behavioural patterns within the studied communities. However, the study also showed that the level of collaboration and mutual support drastically decreases when community members become rivals, are competing against each other, for example, in surf races, and are aiming to win a tournament and the corresponding prizes. While competition reduces collaboration, it also spurs community members’ interest in innovation activities. Research in the context of basketball communities has shown that community members like to self-initiate idea and design competitions to stimulate their innovation activities (Füller, Jawecki & Mühlbacher, 2007). Community member like to engage in the self-stated tournaments, in which they can compare themselves to each other and compete for the best designs. Such contests trigger intense interactions, numerous contributions and countless loops of ‘trial and error’ experimentations that finally lead to superior innovations (Füller, Jawecki & Mühlbacher, 2007). Recently, it has been shown that community-based contests may show similar conditions (Bullinger et al., 2010). Participants of community-based contests may compete and collaborate with each other at the same time: they interact with each other and jointly discuss their innovations, but at the same time, are trying to contribute the best solution to outperform the other contributors. The co-operating and competing behaviour present in community-based design contests may resemble the concept of co-opetition between firms (Brandenburger & Nalebuff, 1996; Albert, 1999; Martinelli, Dussauge & Garrette, 2002; Walley, 2007), defined as a ‘situation where competitors simultaneously co-operate and compete with each other’ (Bengtson & Kock, 2003). According to Zineldin (2004), co-opetition ‘is a relationship based on a value net of involved actors – suppliers, distributors, subcontractors, “complementors”, competitors – who collectively add value to one another’s organizations’. In particular, innovation activities are conducted in co-opetitive relationships in which global
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competitors work together, building cooperative relationships to improve performance by collaborating and sharing resources, knowledge and information. On the other hand, they simultaneously compete as they work independently in other domains to increase their own performance (Luo, 2007). Advantages of co-opetition are greater knowledge development, technological progress (Lado, Boyd & Hanlon, 1997) and the acquisition of new skills (Hamel, 1991). Co-opetition allows firms to reduce risk, costs and uncertainties associated with new product development and innovation (Luo, 2007). However, co-opetitve relationships also bear some risks, such as a resource-demanding establishment of the relationship, hidden costs, dependencies, large investments of time and attention paid on co-ordination and control mechanisms (Zineldin, 2004). Thus far, co-opetition research has been focused on the firm level (Cassiman, Di Guardo & Valentini, 2009; Ritala & Hurmelinna-Laukkanen, 2009; Faems, Janssens & Van Looy, 2010) or on the unit level in multiunit organizations (Tsai, 2002). Few insights exist into the co-opetitive behaviours of the individual in community-based contests. Like organizations, individual contest participants collaborate while simultaneously competing with each other to win the contest. However, unlike the players at the organizational level of these contest communities, users may collaborate and share their knowledge with other members, because they desire to socialize, to interact and form social relationships with others who share similar interests, and thereby establish a sense of community. To capture this intense form of collaboration, we introduce the term ‘communitition’ – community-based collaboration among competing contest participants – to refer to the phenomenon of co-opetition in contest communities. This study aims to shed light on communitition behaviour in community-based idea and design contests. In order to explore communitition, we have developed the following propositions based on the literature: 1. In contest communities, competitive as well as co-operative behavioural elements can be observed simultaneously. 2. Based on the adoption of either competitive, co-operative or co-opetitive behaviour, different user contributions associated with different user roles can be found in a contest community. 3. A combination of active competition to win with simultaneous collaboration yields the highest potential for successful innovation outcomes in online idea and design contests.
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Data and Method Community Selected for Study To answer these research questions, we conducted an explorative study (Glaser & Strauss, 1967; Eisenhardt, 1989) with data derived from the OSRAM LED design contest (see Figure 1). OSRAM, one of the top lighting manufacturers in the world, invited designers and creative consumers from all over the world to engage in an online idea and design contest to propose new, creative consumer-oriented LED light solutions. The contest was open to designers and engineers, as well as to all people with a general interest in LED technology, light solutions and related topics. The contest was conducted in two phases: in Phase I, creative ideas for new LED light solutions could be submitted by anybody. These were subsequently evaluated and discussed by the community itself. The evaluations conducted by the community served as a filter mechanism for a jury of experts to select the most interesting ideas for Phase II. These selected ideas could be further developed and improved by all community members through the submission of further design improvements and suggestions, applications or technical solutions. In total, more than 952 participants joined the OSRAM LED contest to showcase their creativity, to submit their ideas or to provide feedback and knowledge. Participants posted 541 ideas in Phase I, which ran from 8 May to 23 July 2009. The jury determined the winners of Phase I and selected ten designs, which were further developed in Phase II, running from 23 July to 4 August 2009. In the community voting, members made more than 1,890 evaluations and contributed 3,285 qualitative and very detailed comments. These activities were also rewarded in Phases I and II. Each contribution to the community platform had a certain value, which was then calculated in the activity counter (see Appendix I). The interaction and exchange of possibilities enabled participants to build relationships among members and further establish a lively community.
Methods In our analysis, we used data from contributions to the OSRAM LED – Emotionalize Your Light contest in the form of submitted ideas and qualitative comments, through which members explored and built relationships, supported each other, provided feedback and challenged others. We combined structural and interpretive methods to enhance the trust© 2011 Blackwell Publishing Ltd
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Figure 1. OSRMA LED – Emotionalize Your Light Contest Source: http://www.led-emotionalize.com/ worthiness and reliability of our data (Denzin & Lincoln, 1994). We applied (i) a qualitative content analysis as a first step to analyse the context of behaviour in the content community, (ii) complemented this analysis by identifying the structural positions in the contest community through the use of social network analysis (SNA), and (iii) linked the qualitative and quantitative analyses to verify, confirm and refine the findings of the previous steps.
Content Analysis Based on Qualitative Comments An interpretative analysis was conducted based on evaluating the content of the qualitative, very detailed comments, which users posted regarding the uploaded designs of others. This approach allowed the researchers to indentify and understand members’ behaviour, their social roles and the meaning of interactions in the context in which they took place and developed. We used Atlas.ti, a © 2011 Blackwell Publishing Ltd
computer-assisted qualitative data analysis software for content analysis of text data, which allowed us to administer, browse, code, mark, complete and categorize data (Lewins & Silver, 2006).
Social Network Analysis Based on Log-File-Data Through SNA, complex social phenomena such as groups of interacting individuals, community structure and evolution, and the importance of network members and their contributions in the network are not limited to the investigation via qualitative tools but rather can be explored quantitatively (Granovetter, 1973). SNA provides new insights into interaction patterns and members’ roles and contributions in online innovation communities, while revealing the importance of members and their types of contributions that may otherwise be misidentified (Nolker & Zhou, 2005; Panzarasa, Opsahl & Carley, 2009). In our structural analysis, we viewed
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the OSRAM LED contest community as a social network connected by member– member relationships. Computer-mediated social interaction and communication create digital records of relationships between the content creator and others, while they view, reply, annotate, comment, rate and link to one another’s content (Smith et al., 2009). We were able to go back to the server database that logged any activity on the community website in order to obtain this digitally created network data. This integrative reliance on structural data and the detailed qualitative analysis of the content and meaning of interactions allowed for a more holistic and productive approach to refine the understanding of social roles and users’ behaviour (Gleave et al., 2009) than following only one of these methods.
Results Qualitative Study – Content Analysis In order to establish the context and content of the relations and behaviour in the OSRAM LED contest community, we analysed 3,285 qualitative, very detailed comments – of 33 words on average – corresponding to the uploaded designs. Two people on the research team individually coded content data based on established content categories (Maxwell, 2008). Users’ qualitative contributions were categorized into the following six different types of contributions: ‘sharing experience’, ‘asking questions’, ‘offering suggestions’, ‘evaluating ideas’, ‘criticizing ideas’ and ‘defending ideas’ (see, e.g., Hemetsberger & Reinhardt, 2006; Burnett & Illingworth, 2008). We were also open to upcoming concepts to develop content categories inductively (Glaser & Strauss, 1967), such as ‘accepting feedback’, ‘comment on contest’ and ‘comparison with other designs’. We analysed each category as being more competitive, more co-operative or both. In order to ensure inter-rater reliability and to reduce individual coding biases, the meanings of the categories were continuously negotiated and checked with the primary texts, and synonyms were merged. All in all, we discovered 25 different categories in regard to the nature of the contestants’ behaviour (see Appendix II for a detailed description and examples for each category). Behaviour was either only co-operative or had both a co-operative and competitive nature simultaneously. In the OSRAM LED contest community, commenting was the main tool for participants to collaborate with other community members based on participants’ willingness to freely reveal their knowledge and
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expertise and to openly work together (von Hippel & von Krogh, 2003). Hence, comments were not purely competitive in nature. However, if people do not comment on the ideas of others, they do not seem to be willing to collaborate, as no knowledge is revealed or transferred. In total, 129 community members engaged in the competitive behaviour of submitting ideas to the contest without engaging in commenting at all. As most comments consisted of more than one sentence or thought, they were coded simultaneously into several categories. Also, one category could show both competitive and co-operative features depending on the respective content and were therefore separately analysed. In total, 357 comments showed competitive activities, 1,833 comments represented co-operative behaviour, and 848 comments had features of competitive and co-operative actions. At the end, 247 codes could not be categorized because they were not related to any contest-related activity. The findings of this content analysis imply that although participation in a contest intuitively is aimed at winning rare awards, most individual behaviour in the contest community actually engages in co-operation, thus establishing a collaborative overall context (see Figure 2). Figure 3 shows how the different types of behaviour are distributed across the time dimension and compares Phases I and II. It can be seen that the distribution across the three types of behavioural patterns does not differ during the two phases. At all points in time, the community is characterized by a very co-operative atmosphere, which also expresses some competitive features as well. Thus, competitive and co-operative behaviour could be found in all phases of the contest. Based on this interpretative analysis, we conclude that the nature of the contest community is of a co-opetitive configuration. However, we still need to complement this investigation with a structural approach, using SNA in order to examine the macro social structure in which these behavioural patterns exist (Nadel, 1957).
Quantitative Study – Social Network Analysis Our network dataset covered the two different phases of the design contest, where each phase was considered and analysed separately. All users who contributed during Phase I and Phase II to the interactions of the network by either sending or receiving one comment were included in our structural analysis. Users who © 2011 Blackwell Publishing Ltd
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Figure 2. Behaviour of Users across Category Types
Figure 3. Number of Comments during Contest during Phase I and Phase II
simply registered in the design contest, but did not participate in the interaction, were not included. A relationship between two users in the network was established when one user commented on the designs of another participant. In defining the network, we further adopted a weak notion of social relationship (Granovetter, 1973) with directional ties, whereas the direction of a relationship indicates who commented and who received the comment. In this context, a directed tie is established between two users if one user writes a single comment for another user, even if no answer to this initial contact occurs. During the observation period of Phase I, a total of 320 users was recorded, who engaged in a total of 3,014 comments, while 271 comments were written by 49 users in Phase II. In order to identify competitive versus co-operative structural positions in our contest community, the top 5 per cent of contributors among all network members during Phases I and II were identified (Dwyer, 2007; Dawson, 2010). This top 5 per cent provided a high number of one of the two ways to contribute to the contest, including ideas and comments. Table 1 lists the 26 identified top contributors in the network during Phase I. Users who are not included in these top contributors automatically constitute passive users, numbering 862 in the total contest community. Among these top contributors, competitive, co-operative or a combination of both structural positions © 2011 Blackwell Publishing Ltd
can be identified by applying well-established relation-based social network constructs of in-degree and out-degree centrality (Freeman, 1979; Zemljic & Hlebec, 2005). Those metrics are predictors of the importance of an individual’s position and his or her contributions to a network (Freeman, 1979; Kratzer & Lettl, 2008; Panzarasa, Opsahl & Carley, 2009). Out-degree centrality captures the number of outgoing relationships of a node. Hence, it measures the number of direct comments that a user writes concerning the ideas of others or direct replies to other comments. In the case of the contest community, it can be used to measure the level of how actively a user participates in communication with other community members. As the interpretative analysis has shown that most of the comments are co-operative in nature, a high out-degree of a user indicates that he/she is most likely engaging in a high level of co-operative activities. In-degree centrality captures the number of incoming interactions of a user and is often used to define the popularity of a user (Panzarasa, Opsahl & Carley, 2009). However, it has to be considered that the comments a user receives are directed towards the particular designs he/she has submitted. Therefore, we apply in-degree to measure the potential of a user’s ideas to generate a high level of attention (Hautz et al., 2010). Thus, the number of comments a user receives can be seen as an indication of the potential of his/her idea to
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Table 1. Different Structural User Roles in the Network PHASE I User ID
Idea count
712 261 653 526 620 31 407 163 269 397 233 686 210 61 389 321 130 393 195 112 197 201 193 467 173 505
high
In-Dgree
Out-Degree
high high high
high high high high high high high high high high high high
high high high high high high high high high high high high high
User ID
Idea count
In-Dgree
31 459 261 112 197
high high high high
high high high high high high high high high high
high high high high high high high
Nature of structural position competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive competitive both both both both both both both
PHASE II
winner of phase II
high high high
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Nature of structural position
high
competitive competitive competitive both both
high high
selected for phase I
capture attention and arouse curiosity. By applying an in-degree centrality, users who do not engage in writing or answering comments themselves, but only receive comments without further engaging in communication, can be captured in the network. As underscored by Hautz et al. (2010), the number of submitted ideas is also an important factor. In the case of an innovation community
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with the goal to generate new breakthrough ideas and innovations, the user-level analysis should focus not only on the interaction behaviour of the participating users but also on the user-generated content. As users can contribute through their comments as well as through their submitted designs, the number of designs uploaded by a single user is used to capture his/her idea-generating ability. It can © 2011 Blackwell Publishing Ltd
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be assumed that people are submitting a higher number of designs in order to increase their chances of winning the contest or to showcase their talent in a much broader, more comprehensive way (Fullerton et al., 1999; Morgan & Wang, 2010).
Structural Positions Studies have shown that if people are not willing to share their knowledge and freely reveal innovation-related information, then rivalry is usually very high (Franke & Shah, 2003). Hence, a non-co-operative behaviour implies a high level of rivalry and competing conditions. Participants are therefore labelled as having a competitive network position if they do not engage in the writing of comments, even if they have submitted a very large number of ideas (which increases their chances of winning the competition). Members occupy a competitive position as well if they do not write comments on their own but have submitted a few but very attractive ideas that receive a large number of comments and feedback from others. Those users actively engage in the competition with the clear aim of winning the contest, but they simultaneously avoid participating actively in network interaction through revealing knowledge, giving feedback or evaluating the designs of others. Those users who do not participate in collaboration with other network members disregard this important opportunity to add to the community. Users with co-operative network positions, on the other hand, are characterized by their active engagement in commenting on other designs and are therefore also highly involved in conversations and discussions sharing their experiences, thereby providing a great deal of quality feedback. These users often do not even submit a single design in the contest, which reflects their lack of interest in winning the design contest. These users facilitate the information transfer and knowledge sharing processes while collaborating in the online community; therefore, they represent a very collaborative structural position in the network. Finally, among the top contributors, there are those who combine competitive as well as co-operative network features, as seen in a large number of submitted ideas combined with a large number of outgoing as well as incoming comments. The large number of outgoing interactions of these users shows active engagement in social interactions, communication and discussions, and thus the facilitation of the transfer of information, knowledge sharing and collaboration processes. In addi© 2011 Blackwell Publishing Ltd
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tion, these users are also rank high on in-degree centrality, indicating that they also receive a large number of comments. It can therefore be assumed that their designs have the potential to arouse a great deal of the attention in the contest community. Further, the large numbers of incoming comments also provide a lot of feedback, knowledge and suggestions, and allow these users to benefit from the opportunity to collaborate in the creative process in order to enhance and perfect their individual ideas through online and in-contest collaboration. This high volume of comments generated by the community also allows the emerging wisdom of the crowd to assess the future potential of a design and the alleged buzz and acceptance it can generate among customers (Kozinets, Hemetsberger & Schau, 2008). Finally, all of these users have submitted a large number of ideas, increasing their chances of winning the contest. Hence, these particular users engage in both competitive as well as collaborating activities. As Phase II of the contest was much shorter than Phase I and required a further development of selected ideas rather than the submission of new designs, only six users provided the majority of contributions. Figure 4 shows the network of interactions between users during Phase II. The three nodes in the shape of a sphere represent the three winners of this phase. User 31 engaged in a high number of comment contributions, even though he/she did not present one single idea during Phase II, thereby clearly engaging in collaborative actions. User 459, who was not among the top contributors in Phase I, showed a competitive structural position by submitting many ideas, thus increasing his/her chances of winning. This user might have been more interested in further developing and improving existing ideas and providing suggestions, like those required in Phase II, instead of developing a new design from scratch in Phase I. User 261 extended his/her very competitive position from Phase I to the second phase and continued to submit many ideas without giving a single comment himself/herself. As in Phase I, the two users 197 and 112 retained their positions by providing both the highest number of ideas as well as the highest number of comments simultaneously.
Linking SNA and Content Analysis As a next step for each top contributor, we brought together and combined the structural positions identified by the SNA – userlevel indices and their idea-generating
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Figure 4. Network of Interactions Taking Place in Phase II of the Contest
activities – with the findings of the nature of users’ individual comments (see Table 2). For the identification and assignment of structural positions to either competitive or co-operative structural positions, it has been assumed that the content of comments is directed at collaboration based on the interpretative analysis. However, it has to be borne in mind that the specific individual content of each particular comment is not included in the SNA. This means that, although the overall context of the comments was identified as being co-operative, a large number of submitted comments does not necessarily indicate that this user really sent comments with cooperative content. The linking process allowed us to confirm or refine structural findings with individual content. In addition, it is important to note that merely considering the qualitative content was not enough to analyse user behaviour and roles. Table 2 shows that the combination of SNA and qualitative analysis is necessary to complement the interpretive findings in the case of participants who did not submit one single comment and were therefore not captured in the interpretive analysis. Based on linking our qualitative and quantitative results, four different member roles regarding competitive or collaborating behaviour can be identified. Figure 5 shows how competitors, co-operators, communititors and passive users contribute to an online innova-
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tion community in different and very specific ways. Again, user types were assigned to the top contributors. Competitors are users who are mainly interested in showcasing their talent through their designs or who are primarily motivated to win the contest either to gain the monetary prizes and other awards or just the prestige of being the winner. Therefore, these users are characterized by a large number of ideas or several very attractive ideas submitted during the contest in order to increase their chances of achieving these particular goals. Further, competitors view other community members as direct competition and, therefore, do not actively participate in interactions and collaboration, do not reveal or share their knowledge and do not provide improvement suggestions. They are structurally shown in very low outdegree centralities. In some cases, competitors can also submit a large number of comments if those comments contain both collaborative as well as competitive content, for example, criticizing or discouraging others combined with constructive feedback. Co-operators are characterized by their active engagement in commenting on the designs of others. They occupy a structural position in the network which includes a high number of outgoing relationships. These members facilitate the information transfer and knowledge sharing processes in the online community, © 2011 Blackwell Publishing Ltd
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Table 2. Linking Social Network Analysis and Qualitative Analysis PHASE I User ID
Nature of structural position
Nature of comments
User type
712 261 653 526 620 31 407 163 269 397 233 686 210 61 389 321 130 393 195 112 197 201 193 467 173 505
competitive competitive competitive competitive co-operative co-operative co-operative co-operative co-operative co-operative co-operative co-operative co-operative co-operative competitive competitive competitive competitive competitive both both both both both both both
no no co-operative both co-operative co-operative both both co-operative both both co-operative both co-operative co-operative co-operative co-operative co-operative both both both both both co-operative both both
competitor competitor communititor competitor co-operator co-operator co-operator co-operator co-operator co-operator co-operator co-operator co-operator co-operator communititor communititor communititor communititor competitor communititor communititor communititor communititor communititor communititor communititor
User ID
Nature of structural position
Nature of comments
User type
31 459 261 112 197
co-operative competitive competitive both both
both both competitive both both
co-operator competitor competitor communititor communititor
PHASE II
winner of phase II
selected for phase I
which are the key prerequisites for further improvements and collaborative innovation. The findings of the SNA regarding the co-operative network positions were confirmed by the content analysis on the individual level. The context of the provided comments is found to be mostly co-operative, comprising positive evaluations of ideas, encouragement, suggestions for further © 2011 Blackwell Publishing Ltd
improvements, or sharing of experience, thereby providing a large amount of quality feedback and the option to further develop ideas. Communititors engage in competitive as well as co-operative behaviour with the same individuals at the same time. Content analysis supported the co-operative structural position identified by the SNA and further identified
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Figure 5. Different User Types Identified in the Community users with competitive structural positions as engaging actively in collaboration through comments of a co-operative nature. Hence, communititors either have a competitive structural position or combine the structural features of co-operators and competitors. Communititors show competitive behaviour by submitting a large number of ideas or a few very attractive ideas, thereby directly and actively competing with all the other users in the contest. Their large number of designs or their potential to attract attention reflects the intention of communititors to purposely participate in the competition and to increase their chances of winning the contest and thus the offered prizes and incentives (Morgan & Wang, 2010). At the same time, they support the community through their active engagement by providing a large number of comments or several very co-operative comments. Therefore, communititors are characterized by a high out-degree centrality, with comments mostly including content co-operative in nature, with the intention to help and support each other and to contribute to improvements and further developments of the ideas of other contest members. Finally, observers sign up and browse designs and discussions for different reasons (Preece, Nonnecke & Andrews, 2004) but neither submit many designs nor contribute with a large number of comments. However, observers are also needed as they contribute to the
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community’s critical mass, or the number of people needed to make an online community viable, to attract others and to hold the interest of existing members (Preece, 2000). In addition, observers can use the online innovation community to virtually learn, to get inspired and excited in advance about potential products, and to spread the word about them (Brown, Broderick & Lee, 2007). However, if little or no content is provided, a large number of silent observers can become a problem because so much is happening on the Internet that people do not return to quiet communities (Preece, Nonnecke & Andrews, 2004).
What Kinds of Behaviour and Roles Pay Off? After identifying simultaneous co-operation and competition in the contest community, how these aspects may contribute to successful innovation outcomes is analysed and whether a certain kind of behaviour or structural position might ultimately be associated with high-quality outcomes or even winning the contest. Therefore, as a first step we analysed the winners in detail. The three activity awards and two of the three design awards did not go to competitive users who only cared about winning, but rather to communititors. Two of those communititors, 112 and 197, won the activity awards as well as the design contest itself. Both users occupied a © 2011 Blackwell Publishing Ltd
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co-opetitive structural role during Phase I and retained these positions in Phase II. They actively commented on other designs, although they aimed at winning the contest and the activity award with 29 and 18 submitted ideas and 906 and 582 comments, respectively. The great number of comments both increased their activity points and also included many very valuable suggestions to other users as well as constructive questions about their designs, which allowed other users to improve and further develop their own designs. Content analysis further provided support for the assumption that the large number of submitted comments was not rooted in the intention to win the activity award. Co-operators as well as communititors predominantly posted longer and more meaningful comments than ‘I like it’ or ‘Cool’. As assumed, they really engaged in co-operative behaviour through their comments and suggestions to other users, they asked constructive questions about their designs, they challenged and positively evaluated ideas, and they shared their knowledge and experience. Despite their winning intentions, these users actively collaborated with others. In addition, these users not only sent a lot of comments, they also received a large number of comments, arousing a very high level of the attention in the contest community. This reciprocal engagement in social interactions, communication and discussions facilitates the transfer of information and knowledge sharing and allows collaboration processes to emerge within the network. Although these findings imply that at least in the case of these two users the combination of competitive as well as co-operative behaviour provided beneficial conditions to support the creation of a high-quality, breakthrough idea that wins the contest, it has to be kept in mind that other important factors could have affected this outcome. Obviously, those two people were very active and invested a lot of effort and time in their participation in the contest, which could have positively influenced their chances of winning. Therefore, we went beyond the winners of the contest determined through jury evaluation and extended our analysis to the top 30 designs, based on the community evaluation in Phase I of the contest. Surprisingly at first glance, many passive users can be found among the top 30. However, as compared to the relative number of user types in the community, passive users show a low probability of being found among the top 30. This is particularly true for communititors, who submitted a large proportion of the top 30 © 2011 Blackwell Publishing Ltd
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ideas based on their relative number in the contest community. Also a large proportion of competitors seemed to be able to submit ideas that were very highly ranked; however, their low number in the community has to be considered. However, these preliminary results highlight that further research is needed to analyse the impact of the communititive strategy on an individual’s innovation success. In this context, communitition and its innovation outcomes have to be further examined in additional contests in different settings in order to exclude the possibility that these findings are based on mere coincidence.
Discussion and Implications Contests aimed at fostering innovation and new ideas have always played an important role in the economic and business environment (Fullerton et al., 1999). Contests have taken place wherever experts are found, so it comes as no surprise that contests have moved onto the Internet, thereby leading to the phenomenon of ‘online innovation communities’ (von Hippel, 2005; von Krogh & von Hippel, 2006) and online idea design contests. Such online contests provide rare prizes for winners and offer community functionalities, such as user profiles, discussion boards, chat functionalities and voting systems, thus offering a competitive and collaborative environment at the same time. Exploring the OSRAM LED design contest, our findings demonstrate that different behaviours ranging from competitive to collaborative can be found. Our findings also show that collaborative and competitive behaviour was stable over time. Overall, users showed rather collaborative commenting behaviour with most comments falling into categories such as ‘asking questions’, ‘positive evaluating ideas’ and ‘sharing experience/information’. The extensive list of different behavioural patterns complements the findings of existing research (see, e.g., Hemetsberger & Reinhardt, 2006; Burnett & Illingworth, 2008). None of the 25 discovered categories of behaviour fall solely into competitive activities. Hence in the OSRAM LED contest community, commenting itself was used as a tool to reveal and share knowledge and information. Not engaging in this form of collaboration by not submitting a single comment may therefore be interpreted as competitive action. Further, our research confirmed that users in contest communities differ in their structural positions in the network based on their level of activity and the relevance of interac-
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tions (Nolker & Zhou, 2005; Zemljic & Hlebec, 2005; Lettl, Herstatt & Gemuenden, 2006; Hinds & Lee, 2008; Panzarasa, Opsahl & Carley, 2009). We complemented these findings by taking the qualitative nature of the comments into consideration. Four user types were identified: (1) competitors, mainly interested in showcasing their talent and winning the contest; (2) collaborators, characterized by active engagement in commenting, suggesting improvements and providing quality feedback; (3) communititors, combining the features of the former two by providing valuable feedback as well as promising breakthrough designs; and (4) observers, browsing the contest out of curiosity, without submitting designs or providing feedback. These structural and behavioural patterns were found to indeed resemble the coopetition phenomenon observed between companies. Therefore, in this study, we could show that co-opetitive behaviour takes place not only at the firm level (Cassiman, Di Guardo & Valentini, 2009; Ritala & Hurmelinna-Laukkanen, 2009) or at the unit level in multiunit organizations (Tsai, 2002), but also at the individual level. As these co-opetitive activities have been discovered in an online community, we introduce the concept of ‘communitition’ to the literature. Our concept of communitition includes elements of competitive behaviour without disabling the climate of community-based collaboration, as the numerous user discussions and comments within the contest community improve the quality of submitted ideas and allow the future potential of the idea to shine through so-called ‘wisdom of the crowd’ (Howe, 2008). The implications of our research are manifold: in our paper we showed how qualitative and quantitative analysis could be combined to provide a data basis primed for conclusions. Moreover, our results revealed a community behaviour we termed ‘communitition’ (in resemblance to co-opetition). Finally, not only could we identify the phenomenon of communitition in the context of an online idea and design contest, but we were further able to show that ideas submitted by communititors – users combining co-operative as well as competitive features – show a higher probability of being highly ranked by community evaluation and winning. These findings indicate that engaging in competitive behaviour aimed at winning the contest while simultaneously participating in community collaboration may positively correlate with the quality of the submitted designs. Hence, our study shows that participants’ innovative, high-quality contributions may be explained both by their competi-
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tive intention to win the contest and also by building on the concepts of social network theory. Our findings add to the body of literature that has found an individual’s structural position to determine the flow and the quantity of information that influence its outcomes, including innovative outcomes and characteristics such as innovativeness or lead userness (Granovetter, 2005; Kratzer & Lettl, 2009; Bullinger et al., 2010). Further research is needed to deepen the preliminary understanding of individual communitition as related to the quality of contributions. Our findings have very important practical implications for companies. In the future, more and more companies may consider using design and idea contests like the one presented in our study to enrich their development and innovation activities. Based on our results, companies should devise and align their actions with an appropriate management of online innovation communities, community rules and norms. First, it is important to provide community functionality that allows members to collaborate through communication and interaction. Such functionalities enable the contest community to go beyond the limits of a contest in which users simply submit their ideas. Co-operators and communititors need to be enabled through appropriate means, as their reciprocal engagement in social interactions, communication and discussions facilitate a transfer of information and knowledge sharing, which, in turn, foster collaborative processes within the network (Füller, Jawecki & Mühlbacher, 2007). The results of our study also prove the need for appropriate rewards and encouragement for users who are actively contributing to supporting the needs and health of the community. Both users who compete via a large number of ideas and also users who show a high level of collaborative engagement via their comments and votes need to be encouraged through different incentives and tasks. Communititors in particular need to be attracted, as these users embody the necessary combination of competitive as well as co-operative behaviour to support the creation of high-quality, new ideas, which are ultimately the goal of idea and design contests. Furthermore, highlighting communititors as promising contest participants might help companies to uncover the most promising designs out of the huge number of submitted ideas while reducing the risk of eliminating potential winners. Hence, the identification of the communititors in the community network can help to preselect ideas that have a high probability of meeting experts’ criteria. © 2011 Blackwell Publishing Ltd
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However, to be able to extend the concept of communitition and its implied strategies beyond the context of the OSRAM LED design contest, future research on competitive and co-operative elements is needed. Future studies should comprise contest communities with various goals, tasks and backgrounds of participants in order to be able to gain a deeper and more comprehensive understanding of the relevance and value of communitition.
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Katja Hutter (
[email protected]) is Assistant Professor at the Innsbruck University School of Management. She holds a doctorate degree in social and economic sciences from the University of Innsbruck. Her research focus is on innovation management, online communities, co-creation and user-generated content. Julia Hautz (
[email protected]) is Assistant Professor at the Innsbruck University School of Management. Julia holds a doctoral degree in international economics and business sciences and business administration. In her research, Julia focuses on online innovation communities, social networks and corporate diversification strategies. Johann Füller (
[email protected]) teaches at Innsbruck University School of Management. He is a research affiliate at MIT Sloan School of Management and board member of Hyve AG, a company specializing in virtual customer integration. He received his PhD in business administration at the Innsbruck University School of Management. Johann holds a master’s degree in international management, a degree in mechanical engineering and a degree in industrial engineering and management. His research interests are in the field of innovation creation in online
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communities and in virtual consumer integration into new product development. Julia Mueller (
[email protected]) is Assistant Professor at the Department of Strategic Management, Marketing and Tourism at the Innsbruck University School of Management, Austria. She teaches graduate courses in strategic management, knowledge management and international management. Her major research areas include knowledge management and corporate culture. In her PhD thesis, she dealt with the influence of corporate culture on knowledge sharing processes between project teams. She has published several articles and presented her work at international conferences. Kurt Matzler (
[email protected]) is a Professor of Strategic Management at the Innsbruck University School of Management. His primary research and teaching interests are in the area of strategy and innovativeness, leadership and co-creation. He is the academic director of the Executive MBA programme at the Management Center Innsbruck (MCI) and teaches at several MBA Programmes in Switzerland and Austria. He is also a partner of IMP, an international consulting firm with its headquarters in Innsbruck, Austria.
Appendix I Activity
Phase 1: contribution of one idea Phase 2: contribution of one design Phase 2: contribution of one technical solution Detailed evaluation of one idea Upload of profile picture (once) Providing an idea with one comment Leaving a message to another member Intuitive evaluation of one idea
Contest phase
Value
1
20
2
10
2
10
1 and 2
5
1 and 2
5
1 and 2
3
1 and 2
3
1 and 2
2
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Co-operative or Asking questions includes the need to receive more information competitive because of a poor description or the lack of differentiating features to or both existing designs (i.e., competitive), showing a real interest in getting further details, needing help and offering suggestions (co-operative).
Co-operative or competitive or both
Co-operative or competitive or both Co-operative
Comparing designs with other designs can be competitive, if the user wants to criticize the newness of an idea, but can also be co-operative if users compare a design with another excellent design or offer suggestions by giving inspiration.
Confessing a problem is used if an idea is criticized (i.e., competitive) or if users want to show suggestions for further improvements (i.e., co-operative).
Congratulations are a very positive evaluation of ideas.
Comparison with other designs
Confessing problem
Congratulation
Co-operative or Defending an idea or comment is competitive in nature because competitive feedback is not accepted; however, sometimes clarifications are given or both so defending the idea shows that feedback was accepted and applied to the new design.
Demanding feedback includes questions of designers to specified users or the community as a whole to give their opinion about the design.
Defending comment/idea
Demanding feedback
Co-operative
Criticizing ideas can be competitive if the idea is just negatively evaluated, but can also be co-operative if further suggestions for improvement are included.
Criticizing ideas
Co-operative or competitive or both
Co-operative or competitive or both
‘wow, I’d love to have this; this is great stuff for parties! :-)’ (comment #3) ‘It is really a good idea – but sorry to say – I got a design honour mention prize with the same idea in 2005 . . .’ (comment #1431) ‘Sorry, I am still not sure what this is but I would like to know more!’ (comment #852) ‘Can you explain further what would make this different than other things that are like this on the market already?’ (comment #1295) ‘Poor description, I don’t understand well your idea’ (comment #3012) ‘Very well thought – do you also have a design for it so we can imagine better?’ (comment #3036) ‘. . . Maybe they have a special shaker at the paint store and it only is guaranteed if you paint with it within 24–48 hours?’ (comment #453) ‘Since I had the same idea I made a research recently and this kind of lamp is already available: . . .’ (comment #2584) ‘this looks better than sicker with bulb’ (comment #1499) ‘It would be interesting to develop it further to see if you could get the patterns to change the same way Rorschach’s mask did in The Watchmen . . .’ (comment #2293) ‘I am not sure I understand either.’ (comment #3013) ‘. . . Can you explain what you see in this idea? I am not sure if it is a language barrier or not, we would like to know more about it. Thanks.’ (comment #854) ‘Great work and very cool design – there are some ideas heading this direction yet yours is unique in many ways! Congrats – also to your other work – wow!’ (comment #3034) ‘I don’t really get this idea . . . where are the LED-lights?’ (comment #169) ‘I like the idea a lot, but I think the color of those lights in the main image should be brighter, maybe a cyan?’ (comment #74) ‘I agree that the positioning is not the best, but the idea is the point not the placement . . .’ (comment #1926) ‘. . . Yes, I was thinking that the ball, or outer form would be a seamless molded shell either soft or semi ridged so once it was put together, it didn\’t come apart . . .’ (comment #982) ‘Could you please comment my idea?! What do you think?’ (comment #193)
Co-operative
Asking questions
Apologizing
Agreeing
‘it exist a remote . . . so you can change the colour to . . . lime-green or warm-white or UV . . . these colours are not so bright you can mix. Yes, a sensor is a good idea ;-)’ (comment #381)
Example
Co-operative
Accepting feedback could be identified if users were posting on their own design and the content was an answer to a question, a critique or an improvement suggestion showing that they agreed with the commenter. Agreeing is having the same opinion as other users, who have previously commented on a certain design. Apologizing can refer to expressing regrets that users have to criticize others’ designs (which still is competitive) or that they were not able to understand the design/comment.
Accepting feedback
Behaviour
Description
Category of comment
Comment Categories and Their Description
Appendix II
18
59
86
80
75
169
457
22
307
56
No. of comments
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Co-operative or competitive or both
Co-operative or competitive or both
Giving a link to web pages always appears with a question, a suggestion or the wish to share information. So, it depends on the context if it is co-operative or competitive.
Positive evaluating ideas can be co-operative or competitive. Competitiveness is shown if positive statements do not give further information and is merely focused on collecting activity points to win the activity award. Co-operation is shown if suggestions or questions are related to this. Sharing experience can either imply that someone wants to show off or really wants to help others.
Outside link
Positive evaluating ideas
Thanking
Sharing experience/ information
Thanking is a reaction to support and feedback.
Co-operative
Mostly, giving details about a design is attached to a co-operative question or a critique showing that feedback is accepted. Joking is not very helpful in advancing ideas, but nevertheless they create a good atmosphere which facilitates collaboration. Offering suggestions comprise hints where their design might be used or who the target group could be, which material could be used, which colours might look better, etc.
Giving details about design Joking
Offering suggestions
Co-operative
Expressing needs include the real-life desires that users have concerning lights. These comments either focus on wanting to have the provided design (i.e., design is good as it is) or is accompanied by suggestions for improvements.
Expressing needs
Co-operative
Co-operative or competitive or both
Co-operative
Co-operative
Co-operative
Users encourage other users to go on working on their design.
Encouraging
‘They don’t even have to be that close together. I use a set up like that on my rain barrel. I have a 250 gallon barrel collecting water from my roof with a standard tap connected to a 12v pump. When the water reaches the top 6 inches, two metal prongs close a circuit and start the pump which waters the garden through a seeper hose . . .’ (comment #1144) ‘Thanks, I was kinda worried about the conveyance of the idea. I’m glad that it portrays the idea well.’ (comment #289)
‘I love it more than the work of Helen Evans and Heiko Hansen (modular light system) and other light graffiti artists. . . . People overvalue the originality! You will win my friend, continue this way!’ (comment #759) ‘Wow I would really like to have such thing in my house:)’ (comment #6) ‘Nice idea . . . now I wish someone would design something to hold my book that would allow me to turn the pages, stick \′mark\′ on and I’m sold.’ (comment #1560) ‘Just a quick note, I did take your advice and post an idea based on light around the screen, called Screen Light . . .’ (comment #1576) ‘Yes, we can know when to stop making noise in a party before the police come. :)’ (comment #3248) ‘Yes of course. I wasn’t implying that it was identical or anything, just the same. I think it would be great to be able to go into home depot and buy rolls of this stuff the same as wallpaper and be able to download your pattern as you saw fit. It would be great for theme parties, or Halloween or Winter Holidays, or that Toga party you throw every year. Just point, click and by the Power of Greyskull your wall changes.’ (comment #691) ‘Use this in a bar to send anonymous messages for example to the cute brunette in the corner booth.’ (comment #2378) ‘Nice idea – though it’s unfortunately too similar to the ideas at http:// www.ambientdevices.com/’ (comment #43) ‘Nice idea . . . cool stuff . . . I saw something like at Philips . . . it is called Lumalive but I believe is really expensive and a top of the edge technology because you can only rent it from them. I believe that this material has a lot of potential maybe you could make it more affordable. http://www.lumalive.com/’ (comment #732) ‘nice idea’ (comment #2) ‘I like the idea, I’d prefer different shapes though. Could you provide examples?’ (comment #338)
293
745
1211
113
1178
248
400
191
33
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Antecedents and Consequences of Interaction Quality in Virtual End-User Communities caim_592
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Karsten Frey and Christian Lüthje Research has identified virtual communities as a valuable source of innovation. This study aims to provide an understanding of what makes some end-user communities more successful in creating innovations than others. Specifically, we explore how the attractiveness of innovations is influenced by the quality of interaction between the community members. Additionally, we consider trust in benevolent behaviour and competition for reputation, as well as their interaction effect, as being possible antecedents of interaction quality. Drawing on data collected through a web-based survey, this study explores the innovation activities of 127 virtual end-user communities within the fields of sports, car and motorbike tuning and model building. The findings confirm that interaction quality is positively related to the innovativeness of virtual communities. As regards the antecedents of interaction quality, the analysis indicates that trust is a key prerequisite to co-operative behaviour among the members of virtual communities. The level of competition, however, only affects interaction quality if a high level of trust is present among members. The results highlight the need to create an environment that facilitates interaction among the members of innovation communities. Furthermore, community managers should ensure that a minimum level of trust is established within the community before stimulating competition.
Introduction
T
he Internet offers new possibilities for building networks for exchanging information. Virtual communities enable groups of distributed individuals, dispersed across time, location, organizational boundaries and social entities, to organize themselves, to interact, and to share resources via electronic communication tools (Lee & Cole, 2003). During the last decade virtual end-user communities have been growing rapidly on the Internet, covering literally all fields of interest (Ridings, Gefen & Arinze, 2002; West & Lakhani, 2008). Communities that form around a shared interest in a given product category have been recognized as offering great advantages for innovating firms (Sawhney, Verona & Prandelli, 2005; Füller, Matzler & Hoppe, 2008). Several studies indicate that volunteering participants in interest communities frequently develop innovations of high value (Lüthje, 2004; Füller et al., 2006; Jeppesen & Lakhani, 2010). Given that online groups often comprise a high number of participants, online commu-
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nities and open user innovation platforms offer a great opportunity for firms to access a large pool of information at comparatively low cost (von Hippel, 2005; Sawhney, Verona & Prandelli, 2005; Jeppesen & Frederiksen, 2006). As a consequence, a growing number of firms have started to integrate user knowledge in their own innovation processes by using existing groups on the Internet or implementing their own end-user communities (Pisano & Verganti, 2008; Ebner, Leimeister & Krcmar, 2009). More and more researchers are interested in investigating how companies should manage the collaboration with these virtual groups in order to exploit the creative potential of end-user communities (Füller, Jawecki & Mühlbacher, 2007; Schröder & Hölzle, 2010). Understanding what makes some end-user communities more productive than others in creating innovations is a prerequisite for managing virtual communities of interest effectively. A high level of interaction between participants is often suggested to be the basic ingredient of innovative communities. After all, people join a community to exchange © 2011 Blackwell Publishing Ltd
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information, to provide support for each other and to participate in communal activities. The glue that binds individuals together is the members’ willingness to collaborate on the basis of a common interest or a shared goal. What holds true for the functioning of communities in general should also be true for performing innovation-related tasks within those groups of interest. Innovation activities within end-user communities require a minimum number of people who are willing to contribute to the public good of innovative solutions by interacting with each other (von Krogh & von Hippel, 2006). A process of collective invention therefore builds upon participants who communicate, help each other and contribute to specific innovation tasks (von Hippel, 2005). However, even the proponents of innovation communities acknowledge that interaction may also inhibit the development of creative inventions. Many researchers on creativity and teamwork have elaborated upon the problems associated with interaction in groups, including information overload, idea blocking through groupthink, communication difficulties and conflicts (Mullen, Johnson & Salas, 1991; Dougherty, 1992; Singh & Fleming, 2010). To conclude, some disagreement remains as to whether intensive interaction in voluntary communities fosters or inhibits the generation of substantial innovations. The first goal of this study is to investigate the relationship between the interaction quality and the innovative outcomes of virtual end-user communities, leading to the following research question: (1) Does the interaction quality affect the innovativeness of virtual end-user communities? We leverage the existing research work on the role of interaction quality in organizational work teams to understand the effects of interaction in the context of online communities. Although interaction is a constitutive element of communities, not all end-user groups on the Internet display the same level of interaction. When considering the possible critical role of interaction quality, it is important to develop a deep understanding of factors that stimulate or hamper close interaction among contributors. To our knowledge, however, existing studies provide only preliminary insights regarding the drivers of interaction (Ridings, Gefen & Arinze, 2002; Franke & Shah, 2003). Prior research on user innovation communities has focused largely on investigating individual characteristics of community members, namely motives and skills, rather than exploring the interaction between the participants (e.g., Hertel, Niedner & Herrmann, 2003; Lakhani & Wolf, 2005; Grewal, Lilien & Mallapragada, 2006; © 2011 Blackwell Publishing Ltd
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Roberts, Hann & Slaughter, 2006; Shah, 2006; Füller, Matzler & Hoppe, 2008). In the present study, we explore two potential antecedents of interaction quality: the level of interpersonal trust in benevolent behaviour and the nature of the competitive climate in the communities. This leads to the second research question: (2) Do the level of trust and the level of competition affect interaction quality? Trust is the foundation of every interpersonal exchange and can also be expected to impact on interaction within virtual end-user communities. Ensuring the presence of trust in virtual communities seems to be particularly difficult because online interaction does not include face-to-face contacts and usually happens between strangers. It is therefore of utmost importance to shed more light on the role of trust as an antecedent of high levels of interaction quality. Competition may also impact on interaction in virtual end-user groups. While researchers have noted that competition for reputation is prevalent and widespread in virtual user communities (Lampel & Bhalla, 2007), there is little knowledge about the relationship of competition and interaction. In organizational and psychological research, competition between individuals trying to outperform each other has been found to have both functional and dysfunctional effects on interaction (Kohn, 1992; Beersma et al., 2003; Tjosvold et al., 2003). Competition may therefore also act as a double-edged sword in virtual communities. To examine our hypotheses empirically, we conducted a survey involving moderators of end-user communities on the Internet. The data collected from 127 communities of interest in different sports and leisure areas was analysed by applying partial least squares regression (PLS) analysis. This paper starts with a review of the relevant literature in order to develop our research hypotheses on the antecedents and effects of interaction quality. We then go on to describe the empirical process for collecting the data on virtual end-user communities. Next, we present the analysis and results including the analysis of the measurement model and the results of the structural model analysis. Finally, we discuss the outcomes of this study and outline the practical implications of the findings.
Research Model and Hypotheses Development The research model aims to explain which factors ensure a high level of interaction and how interaction quality, in turn, impacts on
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Trust
H2 + H3b +
Competition
Interaction Quality
H1+
Attractiveness of Innovations
H3a − Main effect Interaction effect
Figure 1. Research Model
innovation-related outcomes of virtual enduser communities. Within this framework, interaction quality is conceived as a higherorder construct of communication, coordination and mutual support. Interaction quality is positioned as the central mediating construct. It is expected to be related to the ability of communities to create innovations that are attractive to many users (H1). The model also accounts for interpersonal trust (H2) and the competitive climate (H3a) as being antecedents to interaction quality in communities and, additionally, captures the interaction effect between trust and competition on interaction quality (H3b). Figure 1 illustrates our research model.
Interaction Quality and the Attractiveness of Innovations Interaction is a fuzzy concept. Numerous group-related terms are used when referring to the notion of interaction between individuals, such as collaboration, integration, co-operation, communication, co-ordination or teamwork. When conceiving interaction quality, we built upon research on workgroups and virtual teams in organizational settings. According to the work of Seers (1989) as well as Högl and Gemünden (2001), interaction can be best understood as a multi-dimensional construct comprising different activities of group members working together. To capture the complex nature of interaction, we adapted the construct of teamwork quality specified by Högl and Gemünden (2001) to the empirical context of this study. The construct comprises three dimensions measuring different facets of task-related interaction that are involved in the course of joint invention activities in communities: communication, co-ordination and mutual support. The quality of communication depends on how frequently individuals decide to share information and how appropriate the information is that they receive from other
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people (Moenaert et al., 1995; Fisher, Maltz & Jaworski, 1997). Co-ordination refers to the definition of shared goals, the development of working plans and the prioritization of work packages in processes of joint problem solving (Gladstein Ancona & Caldwell, 1992). Mutual support captures the willingness of community members voluntarily to assist others in advancing their tasks (Högl & Gemünden, 2001; Franke & Shah, 2003; Jeppesen, 2005; Schröder & Hölzle, 2010). Success of project teams in organizations has often been attributed to high levels of interaction quality. In organizational and innovation research studies, intensive interaction in teams has been found to be a key route for the successful development of new products and services (e.g., Gladstein Ancona & Caldwell, 1992; Pinto, Pinto & Prescott, 1993; Souder & Song, 1998; Kahn, 2001; Högl, Weinkauf & Gemünden, 2004). The positive relationship between team members’ interaction and team performance has also been supported by numerous conceptual articles, cases studies and quantitative research on virtual teams (Maznevski & Chudoba, 2000; Montoya-Weiss, Massey & Song, 2001; Zakaria, Amelinckx & Wilemon, 2004). Virtual teams can basically be interpreted as networks of communicative structures. Following this understanding, a coherent interaction is probably the most important element of effective work in virtual teams (Francovich et al., 2008). We expect interaction quality to play a similarly important role in the performance of end-user communities in innovation-related activities. Several considerations support this expectation. Most importantly, interaction quality is a necessary precondition for promoting learning processes among individuals. By interacting with each other, community members advance their understanding and skills in a specific field of interest. Another positive effect is related to the heterogeneous composition of virtual communities. As communities often involve individuals with © 2011 Blackwell Publishing Ltd
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different sets of knowledge, skills and preferences, interaction can be expected to foster creative combinations. After all, innovation often occurs by joining disparate and complementary solution elements in a novel way (Weisberg, 1993; Hargadon & Sutton, 1997; Dahlander & Wallin, 2006). Interaction also facilitates specialization in subtasks in the inventive process and allows for the harmonization of individual contributions of work in order to reach overall goals (Franke & Shah, 2003). Communication literature suggests that interaction allows for the development of mutual knowledge and that a minimum body of shared knowledge is, in turn, integral to the co-ordination of actions, particularly in dispersed or virtual groups lacking a given common ground (Cramton, 2001). A high level of interaction quality should also increase the efficiency of innovation activities, since users will be able to benefit from the input of others instead of being forced to acquire new, solution-related knowledge on their own. Finally, a high interaction quality may reduce the risk that the innovations developed by community participants will reflect only a very narrow set of user needs. Interacting users should develop a better understanding about the needs of other community members. In a similar manner, users interacting with other users will receive feedback on their preliminary solutions, which helps them to develop innovations that are attractive to many users. The literature on work teams and networks sheds a partially negative light on the effect of close interaction between members of organizational entities. In particular, groups using computer-mediated communication have been found to focus on only a small portion of available information (Cramton, 2001). Interestingly enough, the risk of a biased discussion sometimes becomes higher the more the individuals interact. A closer interaction seems to increase the tendency to communicate pieces of information commonly held by all participants rather than exchanging information only known to one or few people (Hightower & Sayeed, 1995). Similarly, the performance of organizational groups has often been shown to be impaired by engaging in groupthink (Janis, 1989). Group members tend to believe that the rapid completion of a task and the commitment of groups members to the task outcomes are best achieved through conformity of opinions and compliance with the group majority (McGrath, 1984; Potter & Balthazard, 2002). The risk that a group uncritically strives for unanimity is particularly high if the group members emphasize personal goals of affiliation – a motive that has been shown to be relevant for explaining participation in virtual © 2011 Blackwell Publishing Ltd
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communities (e.g., Hertel, Niedner & Herrmann, 2003; Shah, 2006; Füller, Matzler & Hoppe, 2008). When groupthink tendencies prevail, higher levels of interaction enforce rather than weaken the tendency to conform. This, again, would imply negative effects of interaction quality on the innovationrelated performance of end-user communities. Increasing levels of interaction may not only be associated with a higher likelihood of group biases but can also lead to information overload and production blocking. Research on innovation teams has shown that the marginal effects of interaction may decrease or even become negative in groups exceeding a necessary level of interaction (Kratzer, Leenders & van Engelen, 2004). However, we suggest that the positive effects of interaction will prevail in virtual enduser communities on the Internet, i.e., the unit of analysis of this study. Firstly, discussion biases and groupthink problems may be less relevant in groups exclusively communicating across electronic channels. Computermediated communication is not as rich as face-to-face discussion and therefore reduces the ability of a majority to exercise influence on the entire group through verbal and nonverbal cues (e.g., tone of voice, body language; Bernard et al., 1998). Secondly, the type of relationship between participants that is prevalent in most online communities should also mitigate any negative effects of high levels of interaction. The members of (large) virtual enduser communities are usually strangers who are only linked by a shared interest in products or brands. This enables community members to engage in rather anonymous interaction which should be far less sensitive to social factors that usually influence private or professional relationships in face-to-face settings. Anonymity tends to lower the salience of social controls (Hightower & Sayeed, 1995). Thirdly, end-user communities on the Internet are composed of volunteers (Shah, 2006; von Krogh & von Hippel, 2006). Participants are usually free to leave a virtual community whenever they perceive their membership as becoming disadvantageous. Apart from being excluded from a community, members do not have to fear any significant sanctions for their behaviour and they usually have the option of joining other communities dedicated to the same field of interest. Under these lowsanction conditions, lock-in effects do not play a significant role. Participants should be more inclined to challenge opinions of others and they should be more willing to provide information that they consider to be relevant for solving innovation-related tasks. Accordingly, we hypothesize:
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H1: The quality of interactions is positively related to the attractiveness of innovations.
The Effect of Trust and Competition on Interaction Quality Trust is the foundation of every interpersonal exchange and solves the problem of acting without knowing ex ante the reaction of the exchange partner (Luhmann, 1979; Leimeister, Ebner & Krcmar, 2005). Research has shown that people co-operate better with people they trust and that they generally avoid co-operating with people they distrust (Blau, 1964; Jarvenpaa, Knoll & Leidner, 1998; Hsu et al., 2007). The literature on virtual teams emphasizes the crucial importance of intrateam trust (Jarvenpaa, Knoll & Leidner, 1998; Zakaria, Amelinckx & Wilemon, 2004). Trust in virtual communities, however, differs from trust in other virtual groups such as dispersed virtual teams in organizations. Because communication in virtual end-user communities is typically directed towards a broad and generally unknown audience, trust develops between an individual and a group of unknown individuals: the community. Members therefore have to trust the community as a whole in order to share the innovation-related information they hold. On account of this, trust has to be seen on an aggregated, collective level (McKnight, Cummings & Chervany, 1998; Kramer, 1999; Ridings, Gefen & Arinze, 2002). Research has shown that it is more difficult to built trust in a virtual context due to the lack of face-to-face contact and because of the difficulty of evaluating the behaviour of others in a many-to-many interaction setting (Kanawattanachai & Yoo, 2002; Lee, Kang & McKnight, 2007). Additionally, members face a high risk of opportunistic behaviour due to the lack of formal rules in virtual communities (Ridings, Gefen & Arinze, 2002). Recent research has identified trust as a central success factor of virtual communities and as being crucial in order for members to open up and participate (Ridings, Gefen & Arinze, 2002; Hsu et al., 2007). In a trusting environment, users should be more willing to support each other (Luhmann, 1979) and to divide work into interdependent subtasks (Jarvenpaa, Knoll & Leidner, 1998). Such sharing activities within virtual communities imply high levels of co-operation and information exchange (Ridings, Gefen & Arinze, 2002). We therefore propose: H2: The level of trust is positively related to the quality of interaction. Organizational research has elaborated upon the distinctive effects of competition
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between individuals on the performance of groups. Most authors are critical of interpersonal competition within workgroups and teams and emphasize the dysfunctional effects of competition (Tjosvold et al., 2003). They persuasively argue that competitive reward structures hinder communication and promote aggressive behaviour leading to poor interpersonal relationships (Deutsch, 1949; Kohn, 1992). These destructive effects of competition may also be prevalent in virtual user communities. Unlike most teams that operate in organizations, user communities often lack an institution that could offer tangible incentives such as bonuses or job promotions. The participants compete rather for intangible rewards. Prior research has identified the aspiration for recognition and reputation as being one such incentive that is important for participation in virtual communities (Hars & Ou, 2002; Chan et al., 2004). Some users even aim to create career opportunities by signalling their reputation to firms active in the product category of interest (Lerner & Tirole, 2002). The reputation of a community member is likely to be the outcome of a social comparison of his/her achievements with the contributions of other participants. Assuming that recognition is a scarce resource, users participating in a virtual community may perceive their own reputation as being in negative correlation with the reputation of others: if a participant gains reputation, others lose it. Prior research supports this argument by showing that strong rivalry conditions diminish the willingness to freely reveal innovation-related information (e.g., Harhoff, Henkel & von Hippel, 2003; von Hippel & von Krogh, 2003). Making information available to others reduces the provider’s competitive advantage that originates from exclusively possessing this information. Thus, competition between users represents a disincentive to share information and therefore might work as a barrier to interaction among community participants. Accordingly, we expect dysfunctional effects of competition in virtual end-user communities. H3a: The level of competition for recognition is negatively related to interaction quality. Contrary to the argumentation above, various studies indicate that intra-team competition for incentives can stimulate the group to achieve extraordinary performance (Parks, Henager & Scamahorn, 1996; Stanne, Johnson & Johnson, 1999; Tjosvold et al., 2003). Competition has been perceived as promoting innovation because it stimulates individuals to outperform each other (Beersma et al., 2003). We argue that the positive effects of © 2011 Blackwell Publishing Ltd
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intra-community competition may outweigh the negative effects on interaction quality under certain conditions. Prior research by Parks, Henager and Scamahorn (1996) suggests that trust may be one such condition. This research involved analysing low-trust and high-trust individuals’ reaction to messages of intent from other participants in a prisoner’s dilemma. The findings revealed that, under low-trust conditions, a competitive message decreases co-operation. In high-trust conditions, however, the co-operation was unaffected by the competitive message. These findings support a positive interaction effect of trust and competition on interaction quality. Another argument builds upon the welldocumented finding that many communities are characterized by strong norms of prosocial behaviour and reciprocity. This implies that participants may gain reputation only if they share information and provide assistance to others (McLure Wasko & Faraj, 2000). In these situations, interaction may be perceived to be instrumental to success in the competition for reputation. Though this perception may be a necessary condition for engaging in interaction with others, it may not be sufficient on its own. In the presence of trust, community participants believe that clear norms of interaction and fairness will guide the participants in their pursuit of reputation. The more competition for reputation is perceived to be free of opportunistic behaviour, the more inclined the community members will be to benefit from the constructive effects of competition and to interact intensively with their counterparts. We therefore expect a high level of trust to accentuate the positive effect of competition on interaction quality: H3b: Trust and competition for recognition have a positive interaction effect on interaction quality.
Methodology Sampling Procedure and Sample Characteristics The research model is tested in end-user communities active on the Internet. Many of these virtual groups are dedicated to discussing specific product categories or to sharing information about fields of special interest. Since prior research on user innovations has documented that users often invent new items for their hobbies (Shah, 2000; Franke & Shah, 2003; Lüthje, 2004; Sawhney, Verona & Prandelli, 2005; Hienerth, 2006; Füller et al., 2006), this study focuses on communities in four differ© 2011 Blackwell Publishing Ltd
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ent fields of leisure activities: sport, car tuning, motorbike tuning and model building. Following Ridings, Gefen and Arinze (2002), we applied two selection criteria for ensuring a sample of communities with a minimum activity level: the communities have to consist of at least 50 members and the most recent postings must not be older than four weeks. Furthermore, we decided to concentrate on independent communities that are run by end-users and are not sponsored by firms. Popular Internet search engines were used for the search procedure. In order to ensure a complete count of existing online communities, a great variety of key words combined with Boolean operators were applied in the identification process. We also used references by asking moderators to indicate other communities on the Internet that they know about. Using this method, we identified a total of 378 communities. Data was collected through a web-based survey defining an entire community as the unit of analysis. The questionnaire was addressed to the community moderators who were asked to assess the level of trust, competition, interaction quality and innovativeness of the community as a whole. We contacted the moderators of all 378 communities by e-mail or private message on the community platform, inviting them to participate in the survey. The e-mail contained a hyperlink to the online questionnaire. All non-responding moderators were reminded by e-mail after one week and again after two weeks. Overall, 127 responses were received using this procedure. This equals a response rate of 33.6 per cent. Descriptive analyses of the data revealed that 82.7 per cent of the sampled communities have created improved or new product solutions (see Table 1). These findings support our expectation that participants of virtual end-user communities often engage in developing ideas and concepts for innovations. Table 1. Innovative Potentiala Frequency of innovations
Percentage of sample
Several times a week Several times a month Several times a year Only a few times since the community has existed Never
3.9 15.0 37.8 26.0
a
17.3
n = 127.
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Twenty-seven cases were eliminated from further analysis because of missing values. This reduced the effective sample size to 100 responses. Of these communities, 24 were active in the area of sports, 23 in car tuning, 27 in motorbike tuning and 26 in model building. The communities in our sample have a mean membership size of 3,551 with a median of 1,140. The mean age of the communities is 4.3 years with a median of 4.0. To test for a potential non-response bias, we compared survey respondents’ membership size with the membership size of a random sample of 50 communities taken from the study population using an unpaired t-test. The results show that the respondents’ membership size does not differ significantly from the membership size of the random sample (p = 0.43; mean membership size: 4,704; median: 1,961). We can therefore conclude that the survey respondents resemble the study population.
members. Mutual support is measured by the degree to which the participants in a community help each other in carrying out their tasks. Co-ordination is measured by the intensity with which the participants in a community integrate and harmonize individual contributions to innovation. The construct trust is conceptualized as trust in integrity and benevolence among the community members. The items are adapted from Ridings, Gefen and Arinze (2002) and Jarvenpaa, Knoll and Leidner (1998). Competition is conceived as the competitive climate within the community. The community moderators were asked to assess the level of competition for recognition and reputation within the community and the importance of design competitions and member rankings.
Measures
We tested the hypothesized structural relationships in our model using partial least squares (PLS) path modelling with SmartPLS 2.0 M3 (Ringle, Wende & Will, 2006). PLS is a variance-based structural equation modelling approach and its advantages include its relatively small sample size requirements, its flexibility in modelling higher-order constructs and its ability to model direct, indirect and interaction effects (Chin, 2010). Since all these factors are present in our study, we consider the PLS approach to be the most suitable statistical method for analysing our model. PLS estimates the model parameters by simultaneously assessing the measurement model and the structural model (Wold, 1982). The interpretation of the model is, however, divided into two subsequent steps. The first step involves the assessment of the reliability and validity of the measurement model at the item and construct levels. The second step is dedicated to the analysis of the structural relationships.
Each construct in the research model was measured using several indicators. Whenever possible, existing measures from related research were adopted. For most of the measures, a five-point Likert scale anchoring on strongly disagree (1) and strongly agree (5) was applied. Since the survey addressed communities in four different fields of interest, we slightly adapted the wording of a few items. All variables were measured at the collective level of the social entity. The complete list of items is provided in the Appendix. The measure attractiveness of innovations consists of a variety of items that assess the extent to which innovations originating from the community typically diffuse. Drawing on the work of Franke and Shah (2003), the attractiveness of innovations is captured by assessing the number of users within and outside the community that, on average, would benefit from the realization of the ideas generated by the community. We also asked the moderators to rate the market potential that the inventions usually have. The construct interaction quality is conceptualized and operationalized as a second-order construct. Interaction quality is considered in this study as a reflective construct of communication, co-ordination, and mutual support. The reflective measurement items for the firstorder construct are adapted from new product development (NPD) team studies (Högl & Gemünden, 2001; Kahn, 2001; Steinheider, 2001) and modified to fit the empirical setting of this study. Communication is operationalized as the frequency and perceived quality of information sharing among community
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Results
Analysis of the Measurement Model To assess the measurement model, we computed construct and indicator reliability, convergent validity and discriminant validity, as well as validity of the second-order construct. As summarized in Table 2, all first-order constructs show satisfactory levels of indicator and composite reliability: most of the loadings are above the threshold of 0.707, i.e., more than 50 per cent (0.7072) of the variance in the observed variable is shared with the construct (Henseler, Ringle & Sinkovics, 2009). Two items fall below this threshold. Both items, however, have loadings above 0.6 and are set © 2011 Blackwell Publishing Ltd
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Table 2. Construct Reliability of First-Order Constructs Construct
No. of items
CR
AVE
l (PLS)
4 3 3 3 3 4
0.88 0.83 0.82 0.90 0.80 0.86
0.65 0.63 0.60 0.75 0.57 0.61
0.77–0.84 0.73–0.83 0.65–0.85 0.79–0.92 0.68–0.80 0.74–0.83
Trust Competition Communication Co-ordination Mutual support Attractiveness of innovations
Table 3. Discriminant Validity (Correlation of Constructs)a
1. 2. 3. 4. 5. 6. a
Trust Competition Communication Co-ordination Mutual support Attractiveness of innovations
Mean
SD
1
2
3
4
5
6
4.11 2.69 4.30 2.83 4.10 2.58
0.95 1.35 0.80 1.02 0.88 1.19
0.80 -0.16 0.37 0.32 0.49 0.28
0.79 -0.13 0.00 -0.24 -0.07
0.78 0.28 0.55 0.32
0.86 0.23 0.49
0.75 0.17
0.78
Bold numbers on the diagonal show the square root of the AVE.
Table 4. Construct Reliability of Second-Order Construct Second-order construct Interaction quality (CR = 0.83)
First-order constructs
l (PLS)
t-Values
Communication Co-ordination Mutual support
0.81 0.68 0.77
15.74 7.31 14.80
within a group of similar indicators with loadings above 0.707 (Chin, 1998). All constructs in our measurement model have a composite reliability above the cutoff value of 0.8, indicating sufficient reliability even for studies being conducted in more advanced stages of research (Nunnally & Bernstein, 1994). Furthermore, all values of the average variance extracted (AVE) are higher than the threshold value of 0.5. This indicates that, on average, more than half the variance of the indicators is explained through the latent variable (Chin, 1998). Finally, the AVE of the latent variable is greater than the squared correlation between constructs for all reflective measurement scales (see Table 3), showing that the constructs are distinct from each other and can be interpreted as separate entities (Fornell & Larcker, 1981). © 2011 Blackwell Publishing Ltd
Validity of the Second-Order Construct Interaction quality is conceived as a secondorder construct reflecting the first order factors of communication, co-ordination and mutual support. Interaction quality was estimated using the approach of repeated indicators, also known as the hierarchical components model suggested by Wold (Lohmöller, 1989, pp. 130–3; Chin, Marcolin & Newsted, 2003). Table 4 shows the estimation of the secondorder construct. The paths from the secondorder construct to the first-order factors communication and mutual support are greater than the cutoff value of 0.707. The path from interaction quality to co-ordination is higher than 0.6, and therefore, according to Chin (1998), is still adequate. The composite reliability is higher than 0.8 which indicates a
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Table 5. Structural Model Resultsa Structural relation Trust → Interaction quality Competition → Interaction quality Trust ¥ Competition → Interaction quality Interaction quality → Attractiveness of innovations a
Analysis of the Structural Model For the estimation of the structural relationships in our model we used a bootstrap routine with 500 iterations. To create the two-way interaction term between trust and competition, the standardized indicator values of the two exogenous variables were multiplied using the integrated routine in SmartPLS. Cohen’s f 2 (Cohen, 1988) was calculated to assess the effect size of interaction terms. f 2 values of 0.02, 0.15 and 0.35 can be interpreted respectively as small, medium and large effects. Predictive Power and Predictive Relevance The predictive power of the structural model is assessed by R2 values and the Stone–Geisser test (Stone, 1974; Geisser, 1975) for predictive relevance. An acceptable ratio of the variance of the two dependent variables is explained (see Table 5). The R2 for the dependent variable attractiveness of innovations is 0.193 and the R2 for the dependent variable interaction quality is 0.346. Additionally, we calculated the predictive relevance using the sample reuse technique by Stone (1974) and Geisser (1975) integrated in SmartPLS. Q2 evaluates how well omitted data is estimated by the model. Following the blindfolding procedure as suggested by Chin (1998), the omitted data can be estimated from the cross-validated communality (H2) and the cross-validated redundancy (F2). With F2 of 0.117 (interaction quality) and 0.097 (attractiveness of innovations) and H2 of 0.325 and 0.354, all blocks of indicators have an acceptable level higher than 0, implying predictive relevance of the model (Chin, 1998). Main and Interaction Effects Finally, we evaluate the hypothesized structural relationships. H1 predicted a positive relation-
Number 1
t-Values
0.527*** -0.017 0.270** 0.439***
5.15 0.25 2.34 5.63
R2
0.346 0.193
n = 100; ** p < 0.05, *** p < 0.01.
high level of internal consistency (Nunnally & Bernstein, 1994). In summary, our measurement model satisfies all relevant reliability and validity criteria and can be used to test the structural model and the corresponding hypotheses.
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ship between interaction quality and the attractiveness of innovations. H1 is supported. The path from interaction quality and attractiveness of innovations is significant (b = 0.439, p < 0.01). H2 suggested a positive association between trust in benevolent behaviour and interaction quality. The coefficient of the path is again positive and significant (b = 0.527, p < 0.01). H3a argued that the level of competition for reputation has a negative effect on the quality of interaction within communities. The coefficient of the path is negative but not significant (b = -0.017, t-value = 0.25). Thus we find no support for H3a. Coming to the interaction effect, we find the hypothesized positive effect of trust and competition on the quality of interaction within communities. The coefficient of the path is positive and significant with a small to medium effect size (b = 0.270, p < 0.05, f 2 = 0.11). We therefore claim support for H3b. Table 5 shows the estimated standardized parameters together with the corresponding t-values indicating the level of significance.
Discussion and Implications This study investigates the antecedents and consequences of interaction quality in virtual end-user communities. We hypothesized that interaction quality has a positive impact on the attractiveness of innovations generated by members of the community. With respect to the antecedents, we argued that interaction quality would be affected by the level of trust and competition among participants of communities. Analysis of survey data on 127 virtual enduser communities dedicated to several leisure activities supported our expectations. The first key finding reveals that a high level of interaction quality among community members is likely to lead to innovations that are attractive to many users within and outside the community. Interaction, in the form of communication, co-ordination, and mutual support, ensures that individuals contributing to the development of an innovation can specialize in elements of the task that fit © 2011 Blackwell Publishing Ltd
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their personal interests and knowledge best. High levels of interaction quality also help to synchronize individual contributions for joint problem-solving and to ensure that the development process is guided by a broader spectrum of requirements reflecting the needs of many users rather than individual user problems. Before inventing, interaction prompts the contributors to consider use-related problems and the needs of other community participants. After developing initial solution concepts, interaction between inventors and other participants may elicit comments on the generated concepts and prototypes, helping the inventors to adapt their initial solution to that feedback. As a whole, this study shows that the downstream effects of interaction quality that have been verified for non-virtual organizational entities, particularly for NPD teams, are also observable for virtual end-user communities on the Internet (e.g., Gladstein Ancona & Caldwell, 1992; Kahn, 1996; Högl & Gemünden, 2001). The second finding highlights that interaction quality prevails in communities characterized by high levels of trust. This is consistent with prior research by Ridings, Gefen and Arinze (2002) and Jarvenpaa, Shaw and Staples (2004) as well as Lin and Lee (2006) on virtual work teams. In the presence of trust, people seem more inclined to interact because there is less risk of opportunistic behaviour. In a trusting environment, participants may also believe that helping and communicating will be beneficial for them in the long term since it is the basis for upholding the norm of reciprocity in a community. In a similar manner, trust in benevolence should make community members more disposed to ask for information because they can expect others to follow the principles of honesty and openness when complying with information requests. Our third finding is related to the level of competition and its effects on interaction quality. Following conceptual work on the free revealing of information, we hypothesized a negative relationship between the level of competition and interaction quality (e.g., Harhoff, Henkel & von Hippel, 2003; von Hippel & von Krogh, 2003). The results of our analysis do not support this proposition and show only a weak negative effect of competition on interaction quality. This result indicates that competition may have functional and dysfunctional effects on interaction in virtual communities leading to a nonsignificant total effect. We find, however, that the relationship between competition and interaction quality is more positive and significant in communities characterized by a trusting environment than in virtual groups where © 2011 Blackwell Publishing Ltd
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trust in benevolent behaviour is absent. A trusting environment, characterized by established, positive and lasting relationships, has a clear effect on the way in which individuals behave in competition for reputation and makes participants more inclined to concentrate on the constructive side of competition. Overall, the findings emphasize the importance of trust. Creating a climate of trust among the participants of communities is the key to increasing the innovation performance of end-user communities. Firstly, trust directly impacts on the level of interaction among participants and therefore indirectly enhances the generation of innovations with higher adoption rates by users within and outside the community. Secondly, trust is necessary in order to foster the constructive effects of competition. Before starting attempts to stimulate competition, community managers have to ensure that a minimum level of trust is present. In the context of virtual communities, interpersonal trust evolves mainly on the aggregated and collective level since communication and support are typically directed towards the general audience of the community, or rather towards anonymous counterparts (Ridings, Gefen & Arinze, 2002). Research has shown that it is comparatively challenging to build trust in a virtual context due to the lack of face-to-face contact and the difficulty in evaluating the behaviour of others (Kanawattanachai & Yoo, 2002; Lee, Kang & McKnight, 2007). In addition, unlike virtual teams in organizational settings, most virtual end-user communities lack a strong governance structure. This may increase uncertainty, which, in turn, is likely to hinder the emergence of trust in benevolent and fair behaviour. For companies aiming to build their own innovation community, therefore, it is of paramount importance to implement mechanisms suitable for nurturing trust under the challenging conditions of virtual relationships. Managers of communities may decide to foster the development of trust by encouraging community members to confide personal information about themselves – for instance by implementing personal profiles as in social networks such as Facebook or XING. It seems reasonable to believe that community members willing to disclose information about their knowledge, their skills and their preferences regarding the common interest field or topic should send a strong signal that they have trust in the community. This will encourage others, particularly community newcomers, to trust them in return (Ridings, Gefen & Arinze, 2002). In addition, getting to know some personal information about other community members helps to stretch the relation-
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ship beyond the mere exchange of information on the topic at hand and to develop personal relationships over time. It may also be beneficial to offer opportunities for face-to-face contacts in the course of meetings and events. The adult fans of Lego (AFOLs) offer a good example of an end-user community combining intensive online communication centred on the creation of innovative Lego models, with regular offline events such as Brickworld or Legoworld, where Lego enthusiasts present their models and compete in Build-On-The-Spot challenges.
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Montoya-Weiss, M.M., Massey, A.P. and Song, M. (2001) Getting It Together: Temporal Coordination and Conflict Management in Global Virtual Teams. Academy of Management Journal, 44, 1251– 62. Mullen, B., Johnson, C. and Salas, E. (1991) Productivity Loss in Brainstorming Groups: A Meta-Analytic Integration. Basic & Applied Social Psychology, 12, 3–24. Nunnally, J.C. and Bernstein, I.H. (1994) Psychometric Theory. McGraw-Hill, New York. Parks, C.D., Henager, R.F. and Scamahorn, S.D. (1996) Trust and Reactions to Messages of Intent in Social Dilemmas. Journal of Conflict Resolution, 40, 134–51. Pinto, M.B., Pinto, J.K. and Prescott, J.E. (1993) Antecedents and Consequences of Project Team Cross-Functional Cooperation. Management Science, 39, 1281–97. Pisano, G.P. and Verganti, R. (2008) Which Kind of Collaboration Is Right for You? Harvard Business Review, 86, 78–86. Potter, R.E. and Balthazard, P.A. (2002) Virtual Team Interaction Styles: Assessment and Effects. International Journal of Human-Computer Studies, 56, 423–43. Ridings, C.M., Gefen, D. and Arinze, B. (2002) Some Antecedents and Effects of Trust in Virtual Communities. Journal of Strategic Information Systems, 11, 271–95. Ringle, C.M., Wende, S. and Will, A. (2006) Smartpls 2.0 M3. URL http://www.smartpls.de [accessed on 30 December 2010]. Roberts, J.A., Hann, I.-H. and Slaughter, S.A. (2006) Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects. Management Science, 52, 984–99. Sawhney, M., Verona, G. and Prandelli, E. (2005) Collaborating to Create: The Internet as a Platform for Customer Engagement in Product Innovation. Journal of Interactive Marketing, 19, 4–17. Schröder, A. and Hölzle, K. (2010) Virtual Communities for Innovation: Influence Factors and Impact on Company Innovation. Creativity and Innovation Management, 19, 257–68. Seers, A. (1989) Team-Member Exchange Quality: A New Construct for Role-Making Research. Organizational Behavior and Human Decision Processes, 43, 118–36. Shah, S.K. (2000) Sources and Patterns of Innovation in a Consumer Products Field: Innovations in Sporting Equipment. MIT Sloan School of Management Working Paper # 4105, Cambridge, MA. Shah, S.K. (2006) Motivation, Governance, and the Viability of Hybrid Forms in Open Source Software Development. Management Science, 52, 1000–14. Singh, J. and Fleming, L. (2010) Lone Inventors as Sources of Breakthroughs: Myth or Reality? Management Science, 56, 41–56. Souder, W.E. and Song, X.M. (1998) Analyses of US and Japanese Management Processes Associated with New Product Success and Failure in High and Low Familiarity Markets. Journal of Product Innovation Management, 15, 208–23.
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Stanne, M.B., Johnson, D.W. and Johnson, R.T. (1999) Does Competition Enhance or Inhibit Motor Performance: A Meta-Analysis. Psychological Bulletin, 125, 133–54. Steinheider, B. (2001) Supporting the Co-Operation of R&D-Teams in the Product Development Process. Proceedings of the 5th Conference on Engineering Design and Automations, Las Vegas, ACM. Stone, M. (1974) Cross-Validatory Choice and Assessment of Statistical Predictions. Journal of the Royal Statistical Society. Series B (Methodological), 36, 111–47. Tjosvold, D., Johnson, D.W., Johnson, R.T. and Sun, H. (2003) Can Interpersonal Competition Be Constructive within Organizations? Journal of Psychology, 137, 63–84. Weisberg, R.W. (1993) Creativity: Beyond the Myth of Genius. Freeman, New York. West, J. and Lakhani, K.R. (2008) Getting Clear About Communities in Open Innovation. Industry & Innovation, 15, 223–31. Wold, H. (1982) Systems under Indirect Observation Using Pls. In Fornell, C. (ed.), A Second Generation of Multi-Variate Analysis. Praeger, New York, pp. 325–47. Zakaria, N., Amelinckx, A. and Wilemon, D. (2004) Working Together Apart? Building a KnowledgeSharing Culture for Global Virtual Teams. Creativity and Innovation Management, 13, 15– 29.
Karsten Frey (
[email protected]) is a research associate and doctoral candidate at the Institute of Information Systems, Chair of Information Management, at the University of Bern, Switzerland. He graduated in business administration from the University of Lüneburg, Germany and concomitantly obtained a Master’s degree in business and economics from the University of Karlstad, Sweden. His research interests focus on factors influencing the success of open innovation communities. He has presented his research at various conferences. Christian Lüthje (c.luethje@tu-harburg. de) heads the Institute of Marketing and Innovation at Hamburg University of Technology (TUHH). Before coming to TUHH in 2008, he held the position of a tenured professor at the University of Marburg, Germany and at the University of Bern, Switzerland. He received his PhD in Business Administration from the Ludwig Maximilian University in Munich. Christian Lüthje specializes in the areas of Innovation Marketing and Customer-Oriented Product Development. He has published in the Journal of Product Innovation Management, Research Policy, R&D Management and International Business Review. His expertise lies in several industries, particularly in medical technology and sports equipment.
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Appendix Table A1. Overview of Constructs and Items Construct
Items
References
Trust
Members of the community know that they can rely on the support of others when questions and problems arise. Community members have no reason to question the intentions of other members. The community believes that all members should be accepted and valued to the same extent. Community members consider each other to be trustworthy.
Jarvenpaa, Knoll and Leidner (1998); Ridings, Gefen and Arinze (2002)
Competition
Individuals often want to demonstrate with their contributions that they know more than others. Many members compete with each other for recognition and reputation within the community. How great is the importance of the assessment of individual members or their contributions (e.g., rankings, status points)? (very low – very high)
Communication
The members of our community communicate frequently with each other. Community members often share their personal experiences with other members. Community members are satisfied with the quality of the contributions they receive from other members.
Högl and Gemünden (2001)
Co-ordination
If several persons are working on an idea for improved or new [. . .], their contributions are mutually well co-ordinated. If several persons are working on an idea for improved or new [. . .], a clear division of labour results which is accepted by all. Community members agree on how one should proceed when realizing a new idea or design.
Högl and Gemünden (2001)
Mutual support
Community members help and support each other mutually. When differences in opinion arise between community members, these are resolved rapidly and without further ado. The suggestions and ideas of individual members are quickly received by the community and further developed there.
Högl and Gemünden (2001)
Attractiveness of innovations
When you reflect on the best ideas for improved or new [. . .] that were developed or realized in your community in the past, . . . . . . how great was the benefit for others? (very small – very great) . . . assuming that this idea had been realized, how great would its market potential have been? (very low – very high) . . . how many members within the community adopted these ideas? (very few – very many) . . . how many people outside the community adopted these ideas? (very few – very many)
Franke and Shah (2003)
All of the items, except where noted, were measured with five-point Likert scales anchoring at strongly disagree (1) and strongly agree (5).
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Language Brokering: Stimulating Creativity during the Concept Development Phase caim_584
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Claudio Dell’Era, Tommaso Buganza, Camilla Fecchio and Roberto Verganti To improve product styling and ergonomics, a growing number of companies are exploring new ways to involve design consultants in their innovation processes. Many studies have underlined the importance of designers in the innovation processes of successful companies, and some designers have achieved ‘superstar’ status. By capturing, recombining and integrating socio-cultural knowledge and product semantics across social and industrial settings, designers can help create breakthrough product meanings. The relationship between briefs written by managers and solutions developed by designers is quite complex. Very often managers are unable to appropriately communicate and commercialize new products and services conceptualized by designers because they know only the final output of the innovation process rather than its entire story. The Language Brokering Process can enrich the dialectic between managers and designers, and consequently, it can improve both current and future innovation projects. This methodology elucidates the structure and process adopted by several designers and also illustrates an effective framework for communicating choices to managers. We present results from a student application of this methodology in the development of a new product-service system for Aquarius (a brand of the Coca-Cola Group) for two target demographics: ‘desperate housewives’ and ‘young adults’.
Introduction
I
nnovation is often necessary for firms to compete successfully in the marketplace, and improving product design is one way that firms can innovate. To improve product styling and ergonomics, a growing number of companies are exploring new ways to involve design consultants in their innovation processes. Many studies have underlined the importance of designers in the innovation process of successful companies (Cillo & Verona, 2008; Verganti, 2009), and some designers have achieved ‘superstar’ status – for example, Jonathan Ive for Apple, Jacob Jensen for Bang & Olufsen, and Philippe Starck for several furniture companies, as well as Nike and Puma. A widely used practice in many industries is to collaborate with external designers to source fresh insights, creativity and new knowledge. Case studies, including Alessi, Apple, Bang & Olufsen, Kartell, Philips, Sony and Swatch,
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demonstrate how designers are becoming key actors in terms of product innovation and strategic renewal (Ravasi & Lojacono, 2005). Industrial design practitioners and academics alike understand that management of the semantic dimension of design is important for product and service innovations. Designers provide access to knowledge of product languages and meanings. Design deals with the meanings ascribed to products and with the language that can be used to convey those meanings to the point that some scholars go so far as to state that design is ‘making sense of things’ (Krippendorff, 1989). Each product, along with its functionality and performance, has a meaning, which is the underlying reason why people buy it and use it. Product signs and languages allow products to speak and convey precise meanings. Verganti (2003) illustrates the unique approach that successful Italian manufacturers are using to involve designers in their innovation processes. They © 2011 Blackwell Publishing Ltd
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collaborate with companies to introduce radical innovations in product meanings and act as brokers of languages to do so. Capturing and integrating knowledge about different socio-cultural contexts and industry settings, designers combine different product languages to propose breakthrough product meanings. In other words, they play a crucial role as brokers of languages. The Apple iMac G3 (1998) represents an interesting example because it adopted a design language that was novel for the industry (translucent coloured plastics), but already diffused in other industries. The same translucent plastic and the same colours had spread into household products in the early 1990s. The emerging language of objects in homes inspired the iMac because it was meant to live in houses. Steve Jobs selected Jonathan Ive (an independent design consultant who operated mainly in the bathroom and plumbing industries) to design the iMac G3 because he understood that personal computers should speak the friendly language of modern household products rather than the cold, remote language of business and offices. Ive gave Apple the opportunity to access the world of household meanings and languages unknown to any other computer company. Several literature contributions describe the processes used by design consultants in order to capture and combine different pieces of knowledge (Twigg, 1998; Tennity, 2003; Verganti, 2003). At the same time very often managers (and more generally companies) are not able to appropriately communicate and commercialize new products and services conceptualized by designers because they know only the final output of the innovation process rather than the entire story behind the product (Sonnenwald, 1996; Ramesh & Tiwana, 1999; Chiu, 2002). An enriched dialectic between managers and designers can improve the performance of innovation projects. How can managers improve their interactions with designers during concept generation? How can they share their diverse knowledge and approaches in the concept development phase? In this paper, we propose a Language Brokering Process for stimulating this creativity during the concept development phase, and facilitating collaboration between managers and designers. Using two student design teams, we have explored this methodology in the development of a new product-service system commissioned by managers at Aquarius (a brand of the Coca-Cola Group). This paper is organized as follows. The next two sections establish a theoretical context by introducing the concept of radical design-driven innovation, and then exploring the designer’s critical con© 2011 Blackwell Publishing Ltd
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tribution to the innovation process. We then go on to introduce and ground our methodology, proposing the Language Brokering Process. Results from the two student design teams are then presented, and in the final section we discuss these results and their managerial implications.
Semantic and Semiotic Innovation Both the industrial design and academic worlds (Csikszentmihalyi & Rochberg-Halton, 1981; Margolin & Buchanan, 1995) have recognized the importance of the semantic dimension of products in the development of new goods and services. The semantic dimension is able to modify the meanings embedded in products to allow them to evolve with society. Peirce (1935) proposes one of the most widely cited theories about semiotics, whereby product messages, and therefore meanings, are represented by signs such as indexes, symbols and icons that are in turn embedded within products. According to Peirce (1935), a sign is not a thing or an object but a relation, and it can be defined as ‘something that stands for something to somebody in some respect or capacity.’ This theory of semiotics can be applied to products, and in this case, the set of signs used to make a product speak can be called product language. Consistent with this idea, Butter and Krippendorff (1984) define ‘product semantics’ as ‘the study of the symbolic qualities of man-made forms in the cognitive and social context of their use and application of knowledge gained to objects of industrial design.’ Verganti (2009) defines radical designdriven innovation as ‘an innovation where novelty of message and design language is significant and prevalent compared to novelty of functionality and technology.’ According to Verganti (2008), innovation may concern a product’s functional utility, its meaning, or both. Moreover, functional innovation may imply an incremental or radical improvement of technical performance (Chandy & Tellis, 1998; Garcia & Calantone, 2002); at the same time innovation of the semantic dimension may also be more or less radical. The proposal of a product language aligned with the current evolution of socio-cultural models allows us to introduce an incremental innovation; while a radical innovation of meanings happens when a product has a language and delivers a message that implies a significant reinterpretation of meanings. Design-driven innovation is based on the idea that each product has a particular meaning; style is just a possible language that can be exploited to communicate it.
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The Swatch, launched first in 1983, was a radical design-driven innovation. It completely transformed the interpretation of watches from jewels or time instruments into fashion accessories (Glasmeier, 1991; Verganti, 2009). The Family Follows Fiction product line introduced by Alessi in 1993 adopted signs and languages completely different from classic products of the kitchenware industry (plastic material, translucent surfaces and daring colours) in order to stimulate new user experiences such as the need for tenderness, delicacy and intimacy (Dell’Era & Verganti, 2009). The Nintendo Wii has redefined the meaning of playing on a game console; it is no longer defined as a passive immersion in a virtual world targeted at young players, but as active form of entertainment in the real world for people of all ages and demographics (Verganti, 2009). According to this interpretation, the Nintendo Wii can be considered a breakthrough in product meanings. Product signs and languages can also be analysed from the standpoint of company differentiation, particularly when product re-design is interpreted as a means to continuously improve a product portfolio. Conversely, a consistent product identity can increase brand recognition, differentiate the company and its offerings from those of competitors, and create coherence across different markets, product categories and over time (Karjalainen, 2001). Kapferer (1994), Aaker (1996) and Holt (2004) underline the importance of identity in terms of values and meanings shared with the customers. Olins (1990) identifies three mains areas that can be exploited to reinforce the identity: products/services, environments and communications. Several studies, such as Warell (2001), Muller (2001), Karjalainen (2004) and McCormack and Cagan (2004), demonstrate that product design conveys messages to customers and, consequently, can develop meaningful visual recognition and brand-specific associations. In an analysis of the automotive industry, and more specifically the Volvo, Nissan, Volkswagen and Citroën case studies, Karjalainen and Warell (2005) describe design elements through which users distinguish products. They argue that similar connotations allow a consistent message to develop and create a product/brand identity. Beginning with the assumption that a strong identity on the market is increasingly important for product development and manufacturing companies, Warell and Nåbo (2002) point out the necessity of developing products that speak a coherent language. In this sense, it can be important for customers to recognize products developed by the same company when
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new models or generations are introduced on the market.
Designers as Brokers of Product Languages Many recent studies underline the importance of designers in the innovation process of successful companies (Krippendorff, 1989; Gotzsch, 1999; Gierke, Hansen & Turner, 2002; Lloyd & Snelders, 2003; Tennity, 2003; Verganti, 2003, 2006, 2009; Boland & Collopy, 2004; Durgee, 2006). Some even go so far as to point out the rise of the design ‘superstars’ like Jonathan Ive for Apple, Jacob Jensen and David Lewis for Bang & Olufsen, and Philippe Starck for several furniture companies, as well as Nike and Puma. Gierke, Hansen and Turner (2002) argue that designers play a unique role in predicting trends and patterns. They say that ‘Like an almanac of wisdom, designers can help to prepare a company for the weather on the way.’ Design can help to build a strong brand identity that differentiates the company or product from competitors, that makes an emotional appeal through style or personality and that communicates benefits. Design acts as an interface between company and customer, ensuring that the company delivers what the customer wants in a way that adds value in all of these ways. Designers can support companies in the identification and interpretation of future trends. Designers can propose new meanings to modify future scenarios. The involvement of designers in the innovation process is a channel through which a firm can gain knowledge about its customers and their needs. Designers may act as crucial gates that provide a firm with access to different socio-cultural contexts (Verganti, 2008). They are bridges between different industries, and therefore facilitate the transfer of knowledge of meanings and languages. Designers are able to interpret different cultures and may be regarded as cultural gatekeepers. The opportunity to collaborate with companies on different categories of products (i.e., chairs, kitchens, sofas, lamps, etc.) and in different industries allows designers to transfer languages from one sector to another (Capaldo, 2007). As a result, in many cases product signs and languages are not industry-specific. The nature of product languages enables their transfer from one product typology to another or from one industry to another. The role of brokers able to move technological knowledge among different industries has been studied recently (Harada, 2003); similarly, some research has analysed the © 2011 Blackwell Publishing Ltd
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brokering role played by designers (Bertola & Texeira 2003; Hargadon 2003). For example, Hargadon and Sutton (1997) demonstrate that IDEO (one of the most successful design firms in the world in the last 20 years) acts as a technology broker, providing access to 40 different industries and exploiting its network position to move solutions across industries (Hargadon & Sutton, 1997). Designers act as brokers of knowledge of languages as well as technologies. From a managerial perspective, this property implies great innovative and creative stimulus. There are many examples of how product languages have moved across industries. For example, the product line ‘Family Follows Fiction’ launched by Alessi in 1993, several products developed by Kartell in the 1990s and Apple’s iMac introduced in 1998 all use similar materials, transparency and colours. Designers support manufacturers, particularly during the concept generation phase. From a transaction-cost economics perspective (Williamson, 1985, 1996; Shelanski & Klein, 1995) and a knowledge-based view perspective (Kogut & Zander, 1992, 1996; Conner & Prahalad, 1996), literature on outsourcing presumes that firms use outsourcing when concerns over specific assets and appropriability are low and when advantages of intra-firm learning, communication and identity are less important than those offered by outsourcing. The collaboration with different clients allows specialized suppliers such as designers to develop superior expertise in professional knowledge in comparison to internal teams. The opportunity to aggregate requests and briefs coming from different clients allows designers to accumulate knowledge of and experience in problem solving and idea generation. Twigg (1998) argues that companies must look to the network of suppliers for design and process expertise. This is particularly relevant in design-intensive industries because the knowledge about the subtle and unexpressed dynamics of socio-cultural models is distributed and tacit. In contrast to traditional socio-cultural investigations, which describe extrapolations of current phenomena, designdriven innovation foresees the proposal of new meanings able to modify the current scenario (Verganti, 2009). Leading Italian manufacturers such as Kartell and Alessi develop a continuous dialogue on socio-cultural models about patterns of consumption, behaviour and societal values because they understand that knowledge about socio-cultural models is diffused within their external environment. Raw material suppliers, universities, design schools and especially designers develop their own © 2011 Blackwell Publishing Ltd
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investigations, representing a sort of large research laboratory. Each actor participating in this dialogue can support the company in the identification and interpretation of emerging phenomena as well as influence the meanings, aspirations and desires held by users by affecting their daily lives.
Language Brokering Process Managers are very often unable to appropriately communicate and commercialize new products and services conceptualized by designers because they know only the final output of the innovation process rather than its entire story. Taking this into consideration, this paper proposes a Language Brokering Process that aims to stimulate creativity during the concept development phase and facilitate collaboration between managers and designers. It comprises four sequential steps, each of which takes inspiration from literature streams previously introduced (see Figure 1). Step 1 – Semantic and semiotic introspection aims at identifying meanings and languages that represent the identity of the company. This step is particularly critical because the Language Brokering Process aims at developing innovations able to reinforce the company identity and product recognition. As Dell’Era and Verganti (2007) argue, in the trade-off between variety and brand identity in product languages, innovators are more attentive to the latter than are imitators. Innovators of the Italian furniture industry avoid proposing a wide range of product signs and languages to protect brand identity. They tend to adopt strategies that allow customers to easily reconnect specific product signs to their brands. Gilmore and Pine (2007) describe the concept of authenticity as the new business imperative, especially through the case studies of Disney and Starbucks. They show that today’s consumers are looking for authenticity where and when they buy. Step 2 – New meaning development represents the core of the process. Several studies demonstrate the fact that consumers increasingly make brand choices on the basis of the aesthetic and symbolic value of products and services. Verganti (2009) explores how firms create innovations that customers do not expect but that they eventually love. Until now, the literature on innovation has focused either on radical innovation pushed by technology or incremental innovation pulled by the market. Design-driven innovations do not come from the market, they create new markets. They do not push new technologies, they push new meanings. Exploring case
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Figure 1. Language Brokering Process studies such as Nintendo Wii, Apple iPod and WholeFoods, Verganti (2009) investigates an innovation paradigm based on collaboration with a network of interpreters that allows new meanings and values to be proposed. Step 3 – Language scouting operationalizes the concept of language brokering proposed by Verganti (2003). As previously mentioned, similar to technology brokers (Hargadon & Sutton, 1997), designers are able to transfer product languages and meanings across industries, exploiting their connections and networks. Kolb (1984) says that ‘knowledge results from the combination of grasping and transforming experience.’ His Experiential Learning Theory describes two dialectically related modes of grasping experience: concrete experience and forming abstract concepts. He also describes two modes of transforming experience: observation and reflection, and testing in new situations. The construction of knowledge arises from the creative tension among the four learning modes. The process is drawn as a circle or, better yet, as a spiral to signify a recursive exercise in which the learner ‘touches all the bases’: experiencing, reflecting, thinking and acting. Step 4 – Language translation exploits potentialities provided by rhetorical figures. According to Casakin (2007), metaphors help designers to understand unfamiliar design problems by juxtaposing them with known situations. The implementation of metaphors in design practice can contribute to creative
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thinking and thereby to more innovative products. The relevance of metaphors to problemsolving is pertinent to three fundamental steps (Gentner et al., 2001): • The first step consists of extracting a variety of unfamiliar concepts from remote domains, where possible relationships with the problem at hand are not always evident. • The second step involves establishing a map of deep or high-level relationships between the metaphorical concept and the problem. Correspondence between the two comes in the form of abstractions and generalizations. Relationships of secondary importance are discarded, and only structural correspondences between the metaphorical source and the problem are retained. • The last step deals with transferring and applying structural correspondences associated with the metaphorical source to the problem at hand, which at the end generally leads to a novel solution. In this way, metaphors not only assist in problem reflection, but also help to break away from limitations imposed by initial problem constraints (Snodgrass & Coyne, 1992), to explore unfamiliar design alternatives and to establish novel associations with the design problem (Coyne, 1995; Casakin, 2006). Karjalainen (2001, 2007) interprets metaphor as a tool for brand/product identity analysis and argues that metaphorical connections can be created between existing brands (or products) © 2011 Blackwell Publishing Ltd
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from totally different product categories, offering great potential for value-added associations. With these reflections in mind, we have explored the following methodology in the development of a new product-service system commissioned by managers of Aquarius to two student design teams. Each design team, comprising five Italian design students (24 years old), developed the project over a period of three months. Especially during Step 1 – Semantic and semiotic introspection, each team was supported by an Aquarius Marketing Manager to collect information and materials (products, catalogues, brochures, leaflets, TV spots, etc.) that allowed them to interpret meanings and languages that represent the identity of the company. More precisely, each design team dedicated 12 hours per week over three months to the development of the project. Four hours were dedicated to design review in collaboration with the authors, while eight hours were dedicated to team activities.
Empirical Results The brief proposed by Aquarius was quite specific – they wanted to develop different product-service systems that, through the use of a beverage product, improve an otherwise stressful supermarket shopping experience. Each student design team worked on a specific target customer. The first team analysed the specific target market of ‘desperate housewives’. These are women with more than one child, little time for themselves, and who are busy running the house and shopping for their family. When they go to the supermarket, their shopping trolley is always filled with several kinds of products. The second team worked on the target market of ‘young adults’. This group consists of men and women between 20 and 30 years old who are predominantly students living away from home. They go to the supermarket only at the weekend to buy foodstuffs for the next week and are substantially less time-constrained than the ‘desperate housewives.’
Desperate Housewives The students began with a detailed analysis of meanings and languages that connote the brand and principal products of the company, such as joy or freshness associated with its logo, feeling fit and healthy based on the ingredients of the drink, or practicality transferred by the shape of the bottle (step 1). The student design team then identified the specific needs of the target customers (e.g., to ease their © 2011 Blackwell Publishing Ltd
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workload, to find enough time to relax, etc.) and developed new meanings and messages to introduce in a new product-service system (step 2): for example, ‘you can stop for a while, relax, re-hydrate and regenerate yourself’ or ‘after this break you will be ready to deal with your work day’. During this phase the design student team paid great attention to the original meanings of Aquarius to propose coherent innovations. In the third and fourth steps, they searched for languages adopted by other companies to convey these messages (step 3) and then used the same languages to create the new product-service system (step 4). To do so, they chose four different product lines (see Figure 2): • From Estathé, the iced tea from Ferrero with the cheerful and easy-to-use glass packaging, they picked the ergonomic benefit of an easy opening and attached a drinking straw. • From Kinder Pinguí, a snack with milk and chocolate proposing to give new energy to children and adults alike, they took the idea of a fresh and satisfying beverage. This feeling was conveyed by focusing on ingredients and some graphical elements like lemon, drops and ice cubes. • From Dove with its skin, body and hair care products and its attention to women and real beauty, they picked the concept of a rehydrating beverage infused with mineral salts. • From Mastro Lindo, the floor cleaner line from Procter & Gamble positioned as a ‘magical ally for housekeeping,’ they extracted a service idea: an ‘Aquarius-team’ positioned near the supermarket check-out, ready to help the consumer with a shopping bag. The students tried to combine these messages and design elements taken from the four brands to create a new visual identity (see Figure 3). They chose to discard the original bottle shape and, instead, to use a package shaped like that of Estathé, which conveys a feeling of familiarity and emphasizes relaxation. With the spherical shape of the glass they gave special importance to the tactile experience. This shape was chosen to convey a sense of pleasure and softness. Finally, the students designed a new logo to communicate a sensation of freshness with colours (light blue, white and yellow) and with graphical elements (slice of lemon, ice cubes, and water). In terms of service, the student design team adopted a position near the check-out where a ‘desperate housewife’ could find an Aquarius team member who could help her put her
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Figure 2. Language Scouting (Target: ‘Desperate Housewives’)
Figure 3. Language Translating – Visual Identity (Target: ‘Desperate Housewives’)
purchases in her shopping bag. She can then take advantage of this moment to rehydrate herself with the soft drink and satisfy her thirst (see Figure 4).
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Young Adults The second design team identified other meanings and languages connected with the © 2011 Blackwell Publishing Ltd
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Figure 4. Language Translating – Storyboard (Target: ‘Desperate Housewives’)
Aquarius brand and its products: spontaneity, freshness, sharing and a capacity to recharge and regenerate the energy spent during daily activities (step 1). They then considered the needs and requirements of the specific target: a desire to have fun with friends, to share amusing experiences, to transform a boring moment (weekly shopping) into a moment of joy and conviviality and to have customized products (step 2). In the next two phases, students identified four brands that have these values and meanings, studied how these messages are expressed, and strategized how to transfer them in a new product-service system (step 3 and 4). The four chosen brands were (see Figure 5): • Air Action Vigorsol, a chewing gum with a fresh mint liquid inside that promotes a sensation of freshness. • The Pocket Coffee by Ferrero, a chocolate candy with espresso coffee inside, that gives an energy boost any time of day. • The new Fiat 500, from which they extracted personalization and the ability to express yourself. • Hard Rock Café, from which they extracted the idea of a fun experience that is memorable and an opportunity to show off. © 2011 Blackwell Publishing Ltd
Combining the elements from their analysis, the design team created a new visual identity for the drink and connected it with a new service model for the supermarket. Their redesigned bottle has an opaque surface made of satin-finished aluminium that can be written on with a pen. The logo is written in calligraphy to convey the appearance of being handwritten. The colours imply freshness and dynamism (light blue, acid green and white). The bottle has a shape that looks like long drinks or beers that you can drink in pubs and lounge bars. The intention was to differentiate Aquarius from other energy drinks or fruit juices with a relaxing or party-like atmosphere (see Figure 6). The associated service was a game to play inside the supermarket. Before entering the shopping centre, the ‘young adults’ would find an Aquarius stand where they could buy a drink, personalize their bottle, and receive a special PIN to start a game. During their shopping inside the supermarket, they could then try to find another person with the same pin. If two people with the same pin came back to the stand together, they receive a discount ticket that they can spend in the shopping centre. The aim of this service is to make the weekly shopping at the supermarket more pleasant
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Figure 5. Language Scouting (Target: ‘Young Adults’)
Figure 6. Language Translating – Visual Identity (Target: ‘Young Adults’) and to give users the potential to find new friends (see Figure 7).
Conclusions Many recent studies underline the importance of designers in the innovation process of successful companies, and even point out that
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some are considered ‘superstars.’ By capturing, recombining and integrating knowledge about socio-cultural models and product semantics in several different social and industry settings, designers help in creating breakthrough product meanings. The relationship between product briefs written by managers and solutions provided by designers is quite complex. According to Borja de Mozota (2003) © 2011 Blackwell Publishing Ltd
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Figure 7. Language Translating – Storyboard (Target: ‘Young Adults’)
and Phillips (2004), the design brief initially developed by managers is often reiterated in a document issued by designers explaining its interpretation of the problem. This co-evolution of the design brief is essential for designers to absorb and prioritize the information outlined in the brief and align the relationship. In several situations, managers need more information to understand the reasons for designers’ solutions. Managers (and more generally companies) are not able to appropriately communicate and commercialize new products and services conceptualized by designers because they know only the final output of the innovation process rather than its entire story. The Language Brokering Process can enrich the dialectic between managers and designers, and consequently improve both current and future innovation projects. The proposed methodology can help designers improve concept development and help managers understand how designers developed new product ideas. The concepts developed by our design student teams demonstrate that this methodology may help managers and designers share knowledge and collaborate to develop solutions. According to Aquarius © 2011 Blackwell Publishing Ltd
managers, product-service systems are not only innovative in themselves, but they are particularly interesting because they provide concrete tools to communicate the innovation to several stakeholders: for example, they used the output of the Language Brokering Process to brief the advertising agency that developed the communication strategy about the concept dedicated to ‘Young adults’. Moreover, they used the visual identity and the storyboard about the concept dedicated to ‘Desperate housewives’ in order to propose the project to the Aquarius top management. The Language Brokering Process can represent a collaborative platform where managers and designers can interact, adding value through a mix of specific competences. Furthermore, this methodology can support managers in the appropriation of basic concepts that connote the new product-service system, and consequently it allows them to better present and narrate the innovation. The Language Brokering Process represents a design tool based on different literature streams such as brand and product identity (Kapferer, 1994; Aaker, 1996; Karjalainen, 2001; Holt, 2004; Dell’Era & Verganti, 2007;
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Gilmore & Pine, 2007), radical innovation of product meanings (Csikszentmihalyi & Rochberg-Halton, 1981; Margolin & Buchanan, 1995; Verganti, 2009), brokering of technologies and languages (Kolb, 1984; Hargadon & Sutton, 1997; Verganti, 2003), and metaphors as a design tool (Gentner et al., 2001; Karjalainen, 2001, 2007; Casakin, 2007). Very often managers provide specific knowledge about the industry where they operate, while designers combine bits of knowledge coming from different contexts. This methodology elucidates the structure and process adopted by several designers and also illustrates an effective framework for communicating choices to managers. In addition, the connections created among brands and metaphors employed provide additional insights and incentives during the concept generation. The results obtained during these two student projects can provide additional insights to improve the Language Brokering Process. Future research is needed to verify its application for different product categories and industries. Specifically, we believe that attention to ‘language translation’ (Step 4) can enrich the capability to combine and recombine signs and languages (e.g., rhetorical figures, metaphors) in ways that can improve brand and value to the customer.
Acknowledgements The authors would like to acknowledge all the practitioners who collaborated with us in the field during the data gathering process. They would also like to acknowledge the design students in the course ‘Gestione dell’Innovazione’ and managers at Aquarius. Naturally, any mistakes or omissions are the sole responsibility of the authors. Financial support from the FIRB fund ‘ART DECO – Adaptive InfRasTructures for DECentralized Organizations’ is greatly appreciated.
References Aaker, D.A. (1996) Building Strong Brands. The Free Press, New York. Bertola, P. and Texeira, L.C. (2003) Design as a Knowledge Agent. How Design as a Knowledge Process is Embedded into Organizations to Foster Innovation. Design Studies, 24, 181–94. Boland, R.J. and Collopy, F. (2004) Managing as Designing. Stanford University Press, Palo Alto, CA. Borja de Mozota, B. (2003) Design Management – Using Design to Build Brand Value and Corporate Innovation. Allworth Press, New York.
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Butter, R. and Krippendorff, K. (1984) Product Semantics – Exploring the Symbolic Qualities of Form. The Journal of the Industrial Designers Society of America, Spring, 4–9. Capaldo, A. (2007) Network Structure and Innovation: The Leveraging of a Dual Network as a Distinctive Relational Capability. Strategic Management Journal, 28, 585–608. Casakin, H.P. (2006) Assessing the Use of Metaphors in the Design Process. Environment and Planning B: Planning and Design, 33, 253–68. Casakin, H.P. (2007) Metaphors in Design Problem Solving: Implications for Creativity. International Journal of Design, 1, 21–33. Chandy, R.K. and Tellis, G.J. (1998) Organizing for Radical Product Innovation: The Overlooked Role of Willingness to Cannibalize. Journal of Marketing Research, 35, 474–87. Chiu, M.L. (2002) An Organizational View of Design Communication in Design Collaboration. Design Studies, 23, 187–210. Cillo, P. and Verona, G. (2008) Search Styles in Style Searching: Exploring Innovation Strategies in Fashion Firms. Long Range Planning, 41, 650–71. Conner, K.R. and Prahalad, C.K. (1996) A ResourceBased Theory of the Firm: Knowledge versus Opportunism. Organization Science, 7, 477–501. Coyne, R. (1995) Designing Information Technology in the Postmodern Age: From Method to Metaphor. MIT Press, Cambridge, MA. Csikszentmihalyi, M. and Rochberg-Halton, E. (1981) The Meaning of Things: Domestic Symbols and the Self. Cambridge University Press, Cambridge. Dell’Era, C. and Verganti, R. (2007) Strategies of Innovation and Imitation of Product Languages. Journal of Product Innovation Management, 24, 580– 99. Dell’Era, C. and Verganti, R. (2009) Design-Driven Laboratories: Organization and Strategy of Laboratories Specialized in the Development of Radical Design-Driven Innovations. R&D Management, 39, 1–20. Durgee, J.F. (2006) Freedom of Superstar Designers? Lessons from Art History. Design Management Review, 17, 29–34. Garcia, R. and Calantone, R. (2002) A Critical Look at Technological Innovation Typology and Innovativeness Terminology: A Literature Review. Journal of Product Innovation Management, 19, 110– 32. Gentner, D., Bowdle, B., Wolff, P. and Boronat, C. (2001) Metaphor is like Analogy. In Gentner, D., Holyoak, K.J. and Kokinov, B.N. (eds.), The Analogical Mind: Perspectives from Cognitive Science. MIT Press, Cambridge, MA, pp. 199–253. Gierke, M., Hansen, J.G. and Turner, R. (2002) Wise Counsel: A Trinity of Perspectives on the Business Value of Design. Design Management Journal, 13, 10–17. Gilmore, J.H. and Pine, B.J. (2007) Authenticity – What Consumers Really Want. Harvard Business School Press, Cambridge, MA. Glasmeier, A. (1991) Technological Discontinuities and Flexible Production Networks: The Case of Switzerland and the World Watch Industry. Research Policy, 20, 469–85. © 2011 Blackwell Publishing Ltd
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Gotzsch, J. (1999) Creating Products with Symbolic Value. 3rd European Academy of Design Conference, Sheffield, 30 March 30–1 April. Harada, T. (2003) Three Steps in Knowledge Communication: The Emergence of Knowledge Transformers. Research Policy, 32, 1737–51. Hargadon, A. (2003) How Breakthroughs Happen: The Surprising Truth about How Companies Innovate. Harvard Business School Press, Boston, MA. Hargadon, A. and Sutton, R.I. (1997) Technology Brokering and Innovation in a Product Development Firm. Administrative Science Quarterly, 42, 716–49. Holt, D.B. (2004) How Brands become Icons: The Principle of Cultural Branding. Harvard Business School Press, Boston, MA. Kapferer, J.N. (1994) Strategic Brand Management: New Approaches to Creating and Evaluating Brand Equity. The Free Press, New York. Karjalainen, T.M. (2001) When is a Car like a Drink? Metaphors as a Means to Distilling Brand and Product Identity. Design Management Journal, 12, 66–71. Karjalainen, T.M. (2004) Semantic Transformation in Design – Communicating Strategic Brand Identity through Product Design References. Doctoral Dissertation, University of Art and Design, Helsinki. Karjalainen, T.M. (2007) It Looks like a Toyota. Educational Approaches to Designing for Visual Brand Recognition. International Journal of Design, 1, 67–81. Karjalainen, T.M. and Warell, A. (2005) Do You Recognise This Tea Flask? Transformation of BrandSpecific Product Identity through Visual Design Cues. Proceedings of International Design Congress – IASDR 2005, Taiwan, 31 October–4 November. Kogut, B. and Zander, U. (1992) Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology. Organization Science, 3, 383– 97. Kogut, B. and Zander, U. (1996) What Firms Do? Coordination, Identity, and Learning. Organization Science, 7, 502–18. Kolb, D.A. (1984) Experiential Learning: Experience as the Source of Learning and Development. PrenticeHall, Englewood Cliffs, NJ. Krippendorff, K. (1989) On the Essential Contexts of Artifacts or on the Proposition that ‘Design is Making Sense (of Things)’. Design Issues, 5, 9– 38. Lloyd, P. and Snelders, D. (2003) What was Philippe Starck thinking of? Design Studies, 24, 237–53. Margolin, V. and Buchanan, R. (eds.) (1995) The Idea of Design: A Design Issues Reader. MIT Press, Cambridge, MA. McCormack, J.P. and Cagan, J. (2004) Speaking the Buick Language: Capturing, Understanding, and Exploring Brand Identity with Shape Grammars. Design Studies, 25, 1–29. Muller, W. (2001) Order and Meaning in Design. Lemma Verlag, TU Delft, Utrecht.
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Olins, W. (1990) Corporate Identity. In Oakley, M. (ed.), Design Management – A Handbook of Issues and Methods, Basil Blackwell, Oxford. Peirce, C.S. (1935) Hartshorne, C. and Weiss, P. (eds.),Collected Papers of Charles Sanders Peirce, Vols 7–8. Harvard University Press, Cambridge, MA. Phillips, P. (2004) Creating the Perfect Design Brief – How to Manage Design for Strategic Advantage. Allworth Press, New York. Ramesh, B. and Tiwana, A. (1999) Supporting Collaborative Process Knowledge Management in New Product Development Teams. Decision Support Systems, 27, 213–35. Ravasi, D. and Lojacono, G. (2005) Managing Design and Designers for Strategic Renewal. Long Range Planning, 35, 51–77. Shelanski, H.A. and Klein, P.G. (1995) Empirical Research in Transaction Cost Economics: A Review and Assessment. Journal of Law, Economics, & Organization, 11, 335–61. Snodgrass, A. and Coyne, R. (1992) Models, Metaphors and the Hermeneutics of Designing. Design Issues, 9, 56–74. Sonnenwald, D.H. (1996) Communication Roles that Support Collaboration during the Design Process. Design Studies, 17, 277–301. Tennity, M. (2003) What Clients Want in Consultants. Design Management Journal, 14, 10–14. Twigg, D. (1998) Managing Product Development within a Design Chain. International Journal of Operations & Production Management, 18, 508–24. Verganti, R. (2003) Design as Brokering of Languages: The Role of Designers in the Innovation Strategy of Italian Firms. Design Management Journal, 3, 34–42. Verganti, R. (2006) Innovating through Design. Harvard Business Review, 84, 114–22. Verganti, R. (2008) Design, Meanings, and Radical Innovation: A Metamodel and a Research Agenda. Journal of Product Innovation Management, 25, 436–56. Verganti, R. (2009) Design Driven Innovation – Changing the Rules of Competition by Radically Innovating what Things Mean. Harvard Business Press, Boston, MA. Warell, A. (2001) Design Syntactics – A Functional Approach to Visual Product Form, Doctoral Dissertation, Chalmers University of Technology, Gothenburg. Warell, A. and Nåbo, M. (2002) Handling Product Identity and Form Development Issues in Design Management using Design Format Modeling. Proceedings of the 11th International Forum on Design Management Research & Education, Design Management Institute, Northeastern University, Boston, MA, 10–12 June. Williamson, O.E. (1985) The Economic Institutions of Capitalism: Firms, Markets, Relative Contracting. The Free Press, New York. Williamson, O.E. (1996) The Analysis of Discrete Structural Alternatives. Administrative Science Quarterly, 36, 269–96.
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Claudio Dell’Era (claudio.dellera@polimi. it) is Assistant Professor in the Department of Management, Economics and Industrial Engineering of Politecnico di Milano, where he serves also as Co-Director of MaDe In Lab, the Laboratory of Management of Design and Innovation of MIP Politecnico di Milano (http://www. madeinlab.it). Research activities developed by Claudio Dell’Era are concentrated in the area of Management of Innovation. His research interests are concentrated in two main areas: first, on innovation strategies developed by leading companies that operate in design-intensive industries where symbolic and emotional values represent critical success factors to generate competitive advantage (Management of Design-Driven Innovation); and, second, on analysing approaches and practices adopted during innovation processes by high-tech companies that face turbulent environments (Management of Technological Innovations in Turbulent Environments). He has published in relevant international journals, such as Journal of Product Innovation Management, Long Range Planning, R&D Management, International Journal of Operations & Production Management, Industry & Innovation and International Journal of Innovation Management. Tommaso Buganza is Assistant Professor of Management of Innovation at the Faculty of Design and at the School of Management of Politecnico di Milano. Tommaso Buganza’s papers investigating the development of new products and services in turbulent environments won the Best Paper Award at the EIASM (European Institute for
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Advanced Studies in Management) International Product Development Management Conferences in 2003 and 2004 and the runner-up diploma in 2002. Camilla Fecchio graduated in 2007 in Industrial Design at the Faculty of Design of the Politecnico di Milano, with a specialization in Communication Design. She conducts research in the field of design-driven innovation, collaborating on projects for the generation of new scenarios and innovative product-service systems in designintensive industries. Roberto Verganti is Professor of Management of Innovation at the Politecnico di Milano, where he also serves as the Director of MaDe In Lab, the laboratory for education in management of design and innovation. He is also chairman of PROject Science, a consulting institute focusing on strategic innovation, a visiting professor of Design Management at the Copenhagen Business School and Adjunct Professor of Design Innovation at the University of Vaasa, Finland. He is a member of the Editorial Board of the Journal of Product Innovation Management and of the Advisory Council of the Design Management Institute. He has published over 100 papers, including 35 papers in leading international journals (such as the Journal of Product Innovation Management, Management Science and Harvard Business Review) and seven books. He was awarded the ‘Compasso d’Oro’ in 2001 (the most prestigious design award in Italy) for the Italian Design System research project for which he served as a member of the Scientific Organising Committee. His most recent book is Design-Driven Innovation, published in August 2009 by Harvard Business Press.
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Creativity-Stimulating Leadership: A Critical Incident Study of Leaders’ Influence on Creativity in Research Groups caim_585
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Sven Hemlin and Lisa Olsson This study examines how group leaders in academic and industrial research settings stimulate creativity in group members. The study uses a modified version of the critical incident technique to collect creative incidents as perceived and reported in interviews with research group members. These incidents were content analysed according to the reported creative situation and the creativity-stimulating leadership behaviours. Reasons for the importance of the incidents are given (each incident is subdivided into categories and subcategories). The highest ranked categories deal with how leaders provide expertise in research meetings and in supervisory situations, in particular for the advancement of research. Four types of creativitystimulating leadership behaviours are also discussed. The study finds few differences between how leaders in universities and industries stimulate creativity.
Introduction
A
significant body of research argues that good leadership is vital to creativity and successful innovation in work groups (Amabile et al., 2004; Anderson, De Dreau & Nijstedt, 2004; Basadur, 2004), in research and development (R&D)1 groups (Pelz & Andrews, 1966; Hollingsworth & Hollingsworth, 2000; Elkins & Keller, 2003; Hemlin, 2009) and in organizations (Woodman, Sawyer & Griffin, 1993; Ford, 1996; Amabile, 1997; Puccio, Murdock & Mance, 2007). However, leadership is seldom studied as the driver of creativity (Mumford et al., 2002; Amabile et al., 2004; Byrne et al., 2009). In R&D groups, in particular, there is a lack of such research (Elkins & Keller, 2003). Research group leaders are involved with activities related to creativity in the groups they lead. Such activities include group composition, resource procurement, and management of projects and goals (Byrne et al., 2009). By using their research experience and leadership qualities, leaders are influential in stimulating creativity among their group members. However, it is not a given that leaders can always exert this influence. To take one © 2011 Blackwell Publishing Ltd
example, idea generation and idea implementation phases pose various constraints on creativity requiring a variety of leader behaviours (Elkins & Keller, 2003; Basadur, 2004). Therefore it is of interest to study not only leader behaviours but also the conditions where creative leadership is effective (Hackman & Wageman, 2007).
Leadership Behaviours Leadership behaviour is characterized as taskoriented, relationship-oriented or changeoriented (Yukl, Gordon & Taber, 2002). First, task-oriented leaders are concerned with getting the job done through effective management of work routines, i.e., clarifying, monitoring and short-term planning. Task-oriented behaviours may seem contradictory to creativity in research where it is expected that members need autonomy and, to a great extent, self-manage according to group goals. Second, relationship-oriented leadership is concerned with supporting, developing, consulting, recognizing and empowering followers. Such a leadership style may seem suitable
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for stimulating creativity in research groups. Third, leaders who promote change in their organizations are capable of stimulating creativity and innovation (Puccio, Mance & Murdock, 2007). The change-oriented leader behaviours, which include visioning, intellectual stimulation, risk-taking and external monitoring as described by Yukl, Gordon and Taber (2002), appear frequently in creative research environments. This three-fold taxonomy of task, relation and change behaviours is applied in this study. Researchers say that leaders who not only promote creativity but are creative themselves provide intellectual challenges to their followers, encourage them to take risks and monitor their innovative efforts (Byrne et al., 2009). A creative leader may be better at evaluating new ideas using unconventional criteria (Reiter-Palmon & Illies, 2004) and may be more willing to postpone idea evaluation until a promising alternative appears. A creative leader may also be a role model for group members (Jaussi & Dionne, 2003). Finally, creative leadership is needed for change (Puccio, Murdock & Mance, 2007). For these reasons, it is suggested that creative leaders are better leaders for research groups where innovating, risk-taking and experimenting characterize the work. This study examines how research group members perceive their leaders to stimulate their creativity. We studied research group leadership in the fields of biomedicine and biotechnology where science-based knowledge and innovations appear and develop, perhaps more rapidly than in other fields (Hollingsworth & Hollingsworth, 2000). Leaders in these fields should be especially proactive since they must be able to spot opportunities and be willing to take risks. In short, they must be creative. Because we were also interested in learning whether institutional borders explain differences in how research group leaders stimulate group creativity, we focused on research leadership in academic institutions and in industry. Hence, our primary research question is: When and how do research group leaders in universities and industries stimulate creativity? Our second question is: Why is the creative incident important? We used the critical incident technique (CIT) to address these questions. CIT has been used successfully to reveal critical incident behaviours in various fields and situations, e.g., leadership by combat leaders and industrial foremen (Flanagan, 1954). CIT is preferable to ordinary interviews because it prompts interviewees to report in considerable detail their most recently observed critical incident behaviours.
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Method Procedure In our study we applied CIT by collecting leader-related incidents of creativity. We began by asking research group members from academia and industry to recall the most recent incident when their group leader stimulated their creativity. Once they had recalled such an incident, we posed the following three questions, asking them to answer them in order: What was the situation in which the incident occurred? Describe as precisely as possible what your group leader did that stimulated your creativity? Was this incident important to your work; and if so, why? We used this question/answer procedure three times except in the instances when participants could not recall more incidents. Both authors participated in some initial sessions, alternating between questioning and taking notes. In later sessions the second author, using a tape recorder, performed both tasks. Immediately after each session we added clarifying information to our notes.
Participants The study participants were members of either academic or industrial research groups. We located these groups by searching university web pages and a Swedish biomedical and biotechnical network site (http://www. swedenbio.com). We had specific selection criteria. Each group had to be research-based, with at least two members and a leader. After selecting the groups, we asked the group leaders to invite group members to join the study. We specifically asked the leaders to invite men and women of various nationalities. We asked the industry leaders to invite co-workers with various work experiences, and we asked the academia leaders to invite co-workers at different levels of academic seniority. Although we interviewed 93 participants, 18 participants could not recall a relevant incident.2 Therefore our final sample, from 34 institutions, consisted of 75 participants (42 from universities, 33 from industry). In total, 54.7% of the participants had doctoral degrees (university: 47.62%; industry: 63.6%), and 45.2% of the university participants were doctoral students. There were no doctoral students among the industry participants. The industry group members were primarily engineers. A total of 19 industry participants worked in small companies or start-ups (<10 employees) located near universities, 11 industry participants worked for companies having about 10–100 employees and three © 2011 Blackwell Publishing Ltd
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industry participants worked at a larger company (110 employees). The university participants were doctoral students, post-doctoral students, and laboratory assistants. There was an overall equal gender distribution (50.7% males, 49.3% females), but women predominated in the university groups (64.3%) and men in the industry groups (69.7%). Of the group leaders, 85.3% had doctoral degrees and 68.0% were male. The size of the groups ranged from 2 to 13 members (M = 5.7, SD = 3.2). The university groups were both larger in number (M = 6.3, SD = 3.2) and older (M = 7.7, SD = 5.0) than the industry groups (M = 3.5, SD = 2.4, t(73) = -2.07, p = 0.042 and M = 4.8, SD = 3.0, t(61.5) = -4.66, p = 0.001).
Data Analysis We applied content analysis in five steps to derive categories from the participants’ reported incidents (see Miles & Huberman, 1994). First, we inserted each incident description into a matrix that had a separate column for each of our three interview questions. We included only incidents that referred to a specific situation and contained a description of leader creativity-stimulating behaviour. Second, we organized the incidents according to meaning content under tentative category labels for incident situations, leader behaviours that stimulated creativity, and participants’ reasons for the importance of the incidents. In this step, we made individual codings and categorizations, discussed issues of codings and categories during the work process, and checked each other’s codings and categorizations. In the third step, we decided which categories to retain and which category labels to use. In the fourth step, we merged the categories into conceptually meaningful categories. In the fifth and final step, we made a reliability check to determine whether our codings and that of a third (independent) person agreed. Agreement was moderate for the situations (k = 0.52), substantial for the behaviours (k = 0.62), and fair for the reasons (k = 0.33), according to Landis and Koch’s (1977) classification. The lower (although reliable) figure for ‘reasons’ may be explained by the inferences the participants had to make. Since making such inferences is more difficult than describing a situation or behaviour, the figure for ‘reasons’ may in part explain the lower agreement between the evaluations. Binomial p was calculated to test whether the observed number of incidents in the university or industry settings in any of the categories differed from what was expected (p < 0.05). © 2011 Blackwell Publishing Ltd
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Results We analysed 153 critical incidents of which 62% (N = 95) were reported by university participants and 38% (N = 58) were reported by industry participants. University participants (M = 1.85, SD = 1.18) reported more incidents than industry participants (M = 1.39, SD = 0.97, t(91) = -2.00, p = 0.049).
Situations The six situations used to categorize the occurrence of critical incidents, detailed in Table 1, are the following: Research meetings; Supervisor/Expert advice; Professional challenge; Travelling and new collaborations; Social issues; and Creativity-stimulating techniques. Research meetings and Supervision/Expert advice accounted for more than 50% of the reported situations. University participants reported the two situations, Supervision/Expert advice (p = 0.046) and Travelling and new collaborations (p = 0.022), more often than industry participants. Research meetings were for project planning in groups, for research discussions on current projects, and, at the universities only, for meetings where articles were discussed. A typical incident was ‘The planning meeting we had in [a resort outside the office] 2008’. Research meetings also involved strategic decision making, and, at the universities only, individual career plans. Supervision/Expert advice situations dealt with how to improve methods and scientific communication and how to complete tasks. For instance, one respondent said his leader caused him to look at his data in a new way: ‘The data – I’m not really satisfied, but he said it might be a good thing. And then I continued and it proved that he was correct in a way. Not completely, but yes, correct’. Professional challenge included industry situations requiring problem solving related to new responsibilities in the research process or university situations related to teaching and supervision. Situations involving Travelling and new collaborations included collegial collaboration and exchanges with other research groups/visiting researchers as well as attending conferences, making new contacts and taking courses abroad. Social issues related to situations that supported positive group climates or counteracted negative group climates (more in industry than in universities). Some participants reported that their leaders had implemented Creativity-stimulating techniques such as inviting an industrial designer to make sketching exercises.
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Table 1. Categories/subcategories of creative leader related or critical incident (CI) situations reported by research group members (n = 75) Category/subcategory
1 Research meetings a) Project planning • Group future • Individual future b) Research discussion c) Journal club 2 Supervision/Expert advice a) Scientific communication b) Methods c) Idea generation d) Finalization 3 Professional challenge a) Problem solving situation b) New responsibility c) Carry out a task 4 Travelling and new collaborations a) Collaboration and exchanges (visits, contacts) without travelling abroad b) Conferences c) Study or research periods abroad 5 Social issues a) Positive group climate b) Negative group climate 6 Creativity-stimulating techniques Total no. of CI (%)
U (n = 42)
I (n = 33)
Total (% of total incidents)
29 13 (6) (7) 11 5 29 15 8 5 1 11 0 7 4 20 11
16 9 (9) (0) 7 0 9 0 4 3 2 14 10 0 4 4 1
45 (29.4%)
4 5 5 5 0 1 95 (62%)
3 0 12 8 4 3 58 (38%)
38 (24.8%)*
25 (16.3%)
24 (15.7%)*
17 (11.1%)*
4 (2.6%) 153 (100%)
Notes: U = university, I = industry. Binomial p was calculated to determine if the observed number of university or industry CIs differed. * p < 0.05.
Leader Behaviours The six leader behaviours that appeared to stimulate group members’ creativity, detailed in Table 2, are categorized as follows: Provide expertise; Co-ordinate group research; Assign tasks; Support group conditions; Enhance external contacts; and Promote independence. Nearly half of these behaviours related to leaders’ expertise and their co-ordination of tasks (leaders’ expertise dominated). We found no significant differences between university leader and industry leader behaviours. The leader behaviour reported under Provide expertise included the generation of research ideas, alternative approaches and new perspectives, as well as dissemination of needed information and completion of research evaluations. This category also
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involved supporting group members, e.g., by additional clarification of task objectives. University group members reported that leaders provided emotional and cognitive support to degree candidates before their dissertation defence and informed group members of new research. A typical answer was ‘[the leader] clearly told me [. . .] what is important in each slide, what you should show [. . .] it’s not important to have so much text on each slide. The message will be conveyed very briefly. So he played a major role in actually improving my skills’. Industry group members reported leaders’ decision making and prioritizing of tasks, including two negative behaviours that triggered participant creativity. One was when a leader was doing a poor job when he described an experiment of his group member, which stimulated the group member himself © 2011 Blackwell Publishing Ltd
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Table 2. Categories/subcategories of creative leader or critical incident behaviours reported by research group members (n = 75) Category/subcategory
1 Provide expertise a) Provide ideas and perspectives b) Evaluate research process c) Provide required support d) Introduce new knowledge e) Decide 2 Coordinate group research a) Initiate research project discussion b) Organize meetings c) Career advise 3 Assign tasks 4 Support group conditions a) Reward b) Demonstrate concern and enthusiasm c) Improve physical work environment d) Handle conflict 5 Enhance external contacts a) Form external contacts b) Encourage group member external exchange 6 Promote independence a) Provide freedom and responsibility b) Inquire for group member opinion and expertise Total no. of CI (%)
U (n = 42)
I (n = 33)
Total (% of total incidents)
33 10 11 5 6 1 14 5 6 3 13 9 1 5 3 0 14 7 7 12 8 4 95 (62%)
19 8 4 2 0 5 11 7 3 1 7 11 7 0 1 3 5 3 2 5 2 3 58 (38%)
52 (34.0%)
25 (16.3%)
20 (13.1%) 20 (13.1%)
19 (12.4%)
17 (11.1%)
153 (100%)
Notes: U = university, I = industry. Binomial p was calculated to determine if the observed number of university or industry CIs differed. * p < 0.05.
to do it better. Another negative behaviour was a leader who questioned the importance of a group member’s business travel which made them realize they could save money by not going. Creativity was thus not enhanced by encouraging travel, but rather by managing time and money efficiently. In the behaviour Co-ordinate group research, group members reported that leaders initiated discussions on research projects and future careers and organized meetings. One respondent said her leader ‘for one thing, initiated this [the meeting]. And then she led the discussion. And it was completely open-ended. In juggling ideas back and forth, quite a few good ideas emerged’. The behaviour Assign tasks referred to the assignment of tasks such as leaders’ delegation of the design of new experiments. For instance, a group member reported her leader once told her do whatever she liked with ten mice. The behaviour Support group conditions © 2011 Blackwell Publishing Ltd
referred to rewarding members, showing enthusiasm and care and managing conflict. Enhance external contacts consisted of leaderinitiated, external contacts with other researchers, encouragement of external exchanges and promotion of foreign travel. Promote independence referred to giving group members work autonomy and responsibility. Inquiries about group members’ opinions and expertise were also included in this behaviour category.
Reasons: The Meaning of the Critical Incident Using the six behaviour categories, Table 3 details the group members’ answers to the question ‘Was this incident important to your work; and if so, why’? The group members gave different reasons for the importance of the incidents. More than half of the reasons fell into two categories: Advancing research and Scientific exchange. Reasons given in the categories
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Table 3. Categories/subcategories of reasons: the meanings of the critical incidents reported by research group members (n = 75) Category/subcategory
1 Advancing research a) Improvements b) Possibility to proceed c) Research communication d) Reach closure e) Stabilized future plans 2 Scientific exchange a) Receive ideas and help b) Provide ideas and help c) From literature 3 Psychosocial ends a) Group climate b) Appreciation c) Trust 4 Advancing professional development a) Learning b) Careers 5 Autonomy 6 Uncertainty Total no. of CI (%)
U (n = 42)
I (n = 33)
Total (% of total incidents)
25 11 5 6 3 0 22 13 7 2 13 5 4 4 22 11 11 11 2 95 (62%)
22 11 7 0 1 3 13 5 7 1 13 7 4 2 3 3 0 6 1 58 (38%)
47 (30.7%)
35 (22.9%)
26 (17.0%)
25 (16.3%)*
17 (11.1%) 3 (2.0%) 153 (100%)
Notes: U = university, I = industry. Binomial p was calculated to determine if the observed number of university or industry CIs differed. * p < 0.05.
of Psychosocial ends and Advancing professional development (university participants gave more reasons than industrial participants, p = 0.004) were about equal in frequency, while reasons in the category of Autonomy and Uncertainty were somewhat fewer. The reason Advancing research related to incidents that promoted research progress (through improvements in ideas, methods, applications and, in the universities, research communication). Additional reasons in this category were leaders’ experience, position and support for projects. A good example of Advancing research is when a group member described how the leader created a database which ‘made it easier to look at the specific characteristics of the bacteria that I was going to work with’. Other reasons categorized as Advancing research included finalizing articles, and, in industry, stabilizing future plans. The reason Scientific exchange related to ideas and help from others that gave a fuller picture of the research. Such exchanges encouraged more interaction among researchers and increased their involvement in creative processes. One respondent expressed the
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meaning of an incident like this: ‘very creatively challenging, specifically to meet people who have different perspectives and as a PhD student to get the opportunity to present your research and later discuss it with these people’ which was categorized as Scientific exchange. We categorized more than 17% of the reasons as Psychosocial ends (positive group climates, feelings of appreciation by leaders and trust in leaders). University participants (p = 0.004), gave the reason Advancing professional development more often than industry participants. In this category, they reported feelings of learning and progress, an increase in confidence and skills and better career opportunities. In the reason category Autonomy, the participants indicated that they felt creative when they were allowed to complete tasks or solve problems without detailed leader interference. They reported they were more innovative when they could discover their own solutions and follow their individual interests. One respondent said that ‘For me, this was fantastic. This made me sit down and think what do I want to do? [. . .] I think it was it was entirely crucial for my career and for my future as a © 2011 Blackwell Publishing Ltd
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researcher on the whole’, which is an example of Autonomy. Finally, the three participants who gave the reason Uncertainty meant that certain incidents were potentially creative, but they were unclear about their consequences. One of them said that ‘we found no solution and instead raised a number of new questions [. . .] I can’t answer that [referring to the importance of the incident]. I still haven’t decided where we are going, what we are going to do with it.’
Conclusions We began this research with the following questions: When and how do research group leaders stimulate creativity? Why is the reported creative incident important? Our analysis of creative incidents reported by group members in research environments resulted in six categories each of creative incident situations, of leaders’ creativitystimulating behaviours, and reasons given for the importance of the incidents as creativitystimulating. The number of reported incidents by university and industry participants differed significantly in only four of the 18 categories. The following sub-sections focus on leaders’ behaviours since our main interest was the investigation of the leaders’ role in creative research incidents. Moreover, the inter-rater agreement was stronger for leaders’ behaviours than for the incident situations and the reasons for their importance.
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oriented behaviour. Finally, the category Promote independence has one relationshiporiented subcategory (member opinions) and one change-oriented subcategory (freedom). In our summary of the behaviour subcategories, after dividing the category Assign tasks equally between task- and change-oriented behaviours, we counted 47 task-oriented behaviours, 31 relationship-oriented behaviours, and 75 change-oriented behaviours. While we acknowledge these results are approximations of leadership behaviour, we think it is notable that about half of the identified behaviours reflected change-oriented leadership, as might be expected in the creative research environment. Although task behaviours were more frequent at face value than relation behaviours, we do not argue that there is a significant difference between them. Still, task behaviours appear more frequently than we had assumed. This result implies that under certain conditions it is useful for leaders to promote creativity by assigning obligatory tasks.
The Main Creativity-Stimulating Behaviours of Leaders The creativity-stimulating leader behaviours were sometimes directed at the individual and sometimes at the group. The emphasis on the individual was more pronounced among university group members, and the emphasis on the group was more pronounced among industry group members. Provide Expertise
General Leader Behaviours vs. Creative Leader Behaviours In our study we applied the taxonomy of general leadership behaviours that includes task, change and relationship orientations (Yukl, Gordon & Taber, 2002) in order to identify leader behaviours that stimulate creativity among followers. In the Provide expertise category, we identified three behaviour subcategories as task-oriented (evaluate, support and decide) and two subcategories as changeoriented (ideas and new knowledge). In the Co-ordinate group research category, we identified one behaviour subcategory as possibly task-oriented (organize meetings), one subcategory as relationship-oriented (career advice), and one subcategory as change-oriented (project discussion). We found that the behaviours in the category Assign tasks are both taskand change-oriented behaviours and those in the category Support group condition are relationship-oriented. We identified the category Enhance external contacts as change© 2011 Blackwell Publishing Ltd
When leaders demonstrate new ideas, exhibit new knowledge or provide feedback, followers perceive such activities as conducive to creativity. However, a leader is also dependent on external contacts for his/her expertise in knowing whom to contact and where to find knowledge sources (Ancona & Caldwell, 1992). In rapidly developing research fields, e.g., biotechnology, leader networks seem to be a more vital component of leader expertise than was previously realized (Avolio, 2007). In this research, group members described a number of incidents where leaders suggested new ideas for development that were taken seriously. If leader-generated ideas are not appreciated, there is little hope that they will be pursued (Basadur, 2004). Therefore, leaders must gain the confidence of their followers if they wish to gain acceptance of their ideas. Group members also reported that their leaders prompted them to generate ideas. In agreement with the social networks approach to R&D creativity, as described by Chen and Kaufmann (2008), we argue that such
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interpersonal interaction, as evidenced by the exchange of generated ideas between leaders and members, is at the core of creative activity. Group Co-ordination This study revealed that group members depend on co-ordinated leadership when creativity is the goal. In research, sharing ideas frequently takes place in a variety of structured meetings and seminars. The formality of such co-ordinated activity means that imaginative hunches and spontaneous discussions are insufficient for the creative process to flourish. Rather, a leader-initiated get-together may release the creativity in groups and thereby advance the research. Task Assignments The group members reported that their leaders instructed them to undertake certain tasks that were perceived as creative. We found that, since creative research is problem solving of ill-defined tasks, leaders need to structure problems that permit followers to self-manage their task assignments (Hemlin, 2006a). Although severe restrictions on independence do not promote creativity (Hemlin, 2006b), task assignments may be beneficial for creativity in line with Boden’s (1994) argument that constraints are generally necessary for creativity. Group Support Our findings point to a variety of relationshiporiented leader behaviours that influence group climates and thereby stimulate creativity. The relationships may be between the leader and the group or between the leader and the individual. Feist (2006) argues that scientists are more introverted than the rest of the population, which may suggest that research group leaders should pay more attention to individual researchers. Another dimension of group support behaviour concerns leaders’ rewards to their followers: gifts, praise and expressions of trust. In our study, the group members who reported receiving such rewards perceived them as motivating their creativity. Although scientists should be intrinsically motivated, since they are in a creative profession (Amabile, 1996), we suggest that rewards positively influence their attitudes towards their leader and towards the creative process. This conclusion contradicts the idea that leaders should not express interpersonal regard for followers (Mumford et al., 2002). We conclude that leaders can increase followers’ creativity through praise.
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Creativity Promotion: University Leaders vs. Industry Leaders First, the university group members reported more creative incidents than the industry group members. The reason for this difference may be that the university group members actually experience more creative incidents since they have more opportunities to generate ideas. Industrial researchers do not enjoy such latitude since their work is confined to commercial R&D goals. Second, there were no differences in reported creativity-stimulating leader behaviours in the two settings. Third, university group members reported more situations of Supervision/Expert advice and Travelling and new collaborations than industry group members. Situations involving relational issues, on the other hand, appeared more frequently in the industry group members’ incidents, which may be explained by the more collaborative character of industrial R&D. Finally, among the university group members, professional development was viewed as the outcome of a creative incident although it was not among the industry group members. Here the explanation may be the significant numbers of doctoral students among the university participants.
Methodological Considerations We did not ask participants to report incidents where leaders hindered creativity since we were interested in creativity-stimulating leadership. Although research is needed to identify the situations where leaders fail to stimulate creativity, it is unlikely such research can be conducted using the critical incident technique. Even when we asked for clearly recalled incidents of observable leader behaviours, we risked overstating the leader’s role in stimulating creativity. Also, participants may have felt subtly pressured to present a positive image of their leaders (despite our assurance to the contrary). As a result, they may have also reported incidents where creativity was not a major factor. In addition, by using the critical incident technique we prevented participants from reporting ongoing, leader-related creative processes or characteristics that cannot be connected to a specific incident. This means we may have disregarded critical elements of creativity. We also consulted an independent assessor who examined the incidents in order to establish the reliability of our categorizations of leadership behaviour. This comparative examination resulted in satisfactory agreement with our results. © 2011 Blackwell Publishing Ltd
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Recommendations We found empirical support for the argument that providing expertise and providing support to individuals and groups are the most significant leadership behaviours required for leading creative people successfully (Mumford et al., 2002). In addition, participants perceived creative incidents as leading to scientific progress. We noted one main difference between the perceptions of the university participants and the industry participants concerning leadership behaviour. The reports revealed the more individual character of academic research and the stronger group character of industrial R&D. A few recommendations arise from this research. First, leaders should use their expertise in interpersonal interactions with their group members. This means that leaders should spend a considerable amount of time with each group member. Another recommendation is that, although research group members are to a great extent self-managing, it is vital that leaders frequently assemble group members to discuss on-going research issues. A related recommendation deals with how to help doctoral students or new group members solve ill-defined problems. A creative leader should provide support by structuring research problems and by assigning openended tasks. Finally, we recommend that leaders express praise and offer rewards to group members in R&D settings as a way to promote creativity.
Future Research Currently, we know little about how leadership behaviour in knowledge networks stimulates creativity (Avolio, 2007). Therefore, we suggest that future studies examine if, when and how leaders’ networks influence creativity in research groups. Second, as our study concerns only the group members’ reports of leader creativity-stimulating behaviour, new studies could explore leaders’ and/or neutral observers’ reports of creative leadership behaviour. Finally, we propose longitudinal studies of research groups in order to observe the interactions between leaders and group members during recurrent time intervals as a way to understand creative processes in this environment.
Notes 1. This study deals with both academic research groups and industrial R&D groups. In the following, the term ‘R&D’ refers to work in the © 2011 Blackwell Publishing Ltd
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industrial setting only; the term ‘research’ is used to refer to work conducted in both academic and industrial research settings. 2. We propose two explanations for some researchers’ inability to recall a creative incident. First, the researchers were less dependent on their leaders and more autonomous than their colleagues. Therefore they were able to conduct research without creativity-stimulating leadership. In addition, they may have been highly creative individuals who did not need much leadership (Tierney, Farmer & Graen, 1999). Second, some leaders rarely, if at all, inspired creativity in the research group.
References Amabile, T.M. (1996) Creativity in Context, Westview Press, Boulder, CO. Amabile, T.M. (1997) Motivating Creativity in Organizations: On Doing What you Love and Loving What you Do. California Management Review, 40, 39–58. Amabile, T.M., Schatzel, E.A., Moneta, G.B. and Kramer, S.J. (2004) Leader Behaviors and the Work Environment for Creativity: Perceived Leader Support. The Leadership Quarterly, 15, 5–32. Ancona, D.G. and Caldwell, D.F. (1992) Bridging the Boundary: External Activity and Performance in Organizational Teams. Administrative Science Quarterly, 37, 634–65. Anderson, N., De Dreau, C.K.W. and Nijstedt, B.A. (2004) The Routinization of Innovation Research: A Constructively Critical Review of State-of-theScience. Journal of Organizational Behavior, 43, 147– 73. Avolio, B.J. (2007) Promoting More Integrative Strategies for Leadership Theory-Building. American Psychologist, 62, 25–33. Basadur, M. (2004) Leading Others to Think Innovatively Together: Creative Leadership. The Leadership Quarterly, 15, 103–21. Boden, M.A. (1994) What is Creativity? In Boden, M.A. (ed.), Dimensions of Creativity, MIT Press, Cambridge, MA, pp. 75–117. Byrne, C.L., Mumford, M.D., Barrett, J.D. and Vessey, W.B. (2009) Examining the Leaders of Creative Efforts: What do they do, and what do they think about? Creativity and Innovation Management, 18, 256–68. Chen, M.-H. and Kaufmann, G. (2008) Employee Creativity and R&D: A Critical Review. Creativity and Innovation Management, 17, 71–76. Elkins, T. and Keller, R.T. (2003) Leadership in Research and Development Organizations: A Literature Review and Conceptual Framework. The Leadership Quarterly, 14, 587–606. Feist, G.J. (2006) The Psychology of Science and the Origins of the Scientific Mind, Yale University Press, New Haven, CT. Flanagan, J.C. (1954) The Critical Incident Technique. Psychological Bulletin, 51, 327–58. Ford, C.M. (1996) A Theory of Individual Creative Action in Multiple Social Domains. Academy of Management Review, 21, 1112–42.
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Hackman, J.R. and Wageman, R. (2007) Asking the Right Questions about Leadership. American Psychologist, 62, 43–47. Hemlin, S. (2006a) Managing Creativity in Academic Research. Could Creative Action and Management be Reconciled in Research? Science Studies, 19, 83–92. Hemlin, S. (2006b) Creative Knowledge Environments for Research Groups in Biotechnology. The Influence of Leadership and Organizational Support in Universities and Business Companies. Scientometrics, 67, 121–42. Hemlin, S. (2009) Creative Knowledge Environments. An Interview Study with Group Members and Group Leaders of University and Industry R&D Groups in Biotechnology. Creativity and Innovation Management, 18, 278–85. Hollingsworth, R. and Hollingsworth, E.J. (2000) Major Discoveries and Biomedical Research Organizations: Perspectives on Interdisciplinarity, Nurturing Leadership, and Integrated Structure and Cultures. In Weingart, P. and Stehr, N. (eds.), Practicing Interdisciplinarity, University of Toronto Press, Toronto, pp. 215–44. Jaussi, K.S. and Dionne, S.D. (2003) Leading for Creativity: The Role of Unconventional Leader Behavior. The Leadership Quarterly, 14, 475– 98. Landis, J.R. and Koch, G.G. (1977) The Measurement of Observer Agreement for Categorical Data. Biometrics, 33, 159–74. Miles, M.B. and Huberman, A.M. (1994) Qualitative Data Analysis. An Expanded Sourcebook, Sage, London. Mumford, M.D., Scott, G.M., Gaddis, B. and Strange, J.M. (2002) Leading Creative People: Orchestrating Expertise and Relationships. The Leadership Quarterly, 13, 705–50. Pelz, D. and Andrews, F. (1966) Scientists in Organizations: Productive Climates for Research and Development, Wiley, New York. Puccio, G. J., Murdock, M. C., & Mance, M. (2007) Creative Leadership. Skills that Drive Change. Sage, Thousand Oaks, CA.
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Reiter-Palmon, R. and Illies, J.J. (2004) Leadership and Creativity: Understanding Leadership from a Creative Problem-Solving Perspective. The Leadership Quarterly, 15, 55–77. Tierney, P., Farmer, S. M., and Graen, G. B. (1999) An Examination of Leadership and Employee Creativity: The Relevance of Traits and Relationships. Personnel Psychology, 52, 591– 620. Woodman, R.W., Sawyer, J.E. and Griffin, R.W. (1993) Toward a Theory of Organizational Creativity. Academy of Management Review, 18, 293– 321. Yukl, G., Gordon, A. and Taber, T. (2002) A Hierarchical Taxonomy of Leadership Behavior: Integrating a Half Century of Behavior Research. Journal of Leadership and Organizational Studies, 9, 15–32.
Sven Hemlin (
[email protected]) is Associate Professor in Psychology and is Senior Researcher at Gothenburg Research Institute, School of Business, Economics and Law, Senior Lecturer at the Department of Psychology, University of Gothenburg, and Visiting Professor at the School of Technology and Society, University of Skövde. He has devoted the last ten years mainly to research on creativity, innovation, leadership and management. He has published his research in journals such as Creativity and Innovation Management, Creativity Research Journal, Science Technology & Human Values and Scientometrics. Lisa Olsson (
[email protected]) is a PhD student in Psychology at the Department of Psychology, University of Gothenburg. She recently finished her licentiate thesis entitled Leadership and Creativity in Research Groups.
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Creative Cities and Regions: The Case for Local Economic Diversity caim_586
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Pierre Desrochers and Samuli Leppälä In their recent discussion of the Richard Florida and Jane Jacobs-inspired ‘creative cities’ policy literature, Hospers and Pen argue that despite increasingly more effective ‘space shrinking’ technologies, cities remain among the most suitable locations for creative activities of all types. This paper supplements their contribution by documenting more concretely how economically diversified cities provide a fertile environment for the discovery and development of new technological combinations. In doing so, we try to illustrate how a better understanding of the linkages between creativity and urban agglomeration would benefit from a multidisciplinary approach that studies both phenomena simultaneously.
Introduction ities (or nowadays metropolitan areas)1 have long been recognized as primary cradles of artistic and other advances, but much debate remains as to the causality link between urbanization and economic development processes (Lampard, 1955; Hall, 2000; Polese, 2005). In their recent discussion of the Richard Florida (2002, 2005, 2008) and Jane Jacobs (1969)-inspired ‘creative cities’ policy literature (Rantisi, Leslie & Christopherson, 2006; Scott, 2006), Hospers and Pen (2008, p. 259) build on a ‘geography of innovation’ literature mostly known to management scholars through Michael Porter’s (1990) The Competitive Advantage of Nations to argue that urban agglomerations are the primary engines of economic development because they are locations ‘where knowledge, creativity and innovation flourish.’ This scholarship emphasizes the commonsense notions that innovative activities within firms are interactive learning processes that often involve outside actors (potentially including individuals working for other firms or educational institutions); that innovative small firms especially benefit from being embedded in regionally based networks of similarly innovative firms; and that so-called ‘knowledge spillovers’ and the communication of tacit knowledge remain heavily dependent on face-to-face interactions and are therefore especially sensitive to the friction of
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geographical space (Clark, Feldman & Gertler, 2000; Polese, 2005). Few scholars in this line of inquiry, however, have looked up the work of students of human creativity. It is probably fair to say that the few who did found it of little use in terms of explaining why, historically, cities such as Athens, Florence, London, Paris and New York were for a time hotbeds of creative thinking and innovation. This assessment was perhaps best expressed by a major figure in the field of urban studies, Sir Peter Hall (2000, p. 642), who observed a decade ago that little ‘in the vast literature on creativity’ is of relevance to his corner of academia ‘because virtually none of it addresses the question of location. Psychologists and psychoanalysts treat it almost exclusively in terms of the individual personality; so do students of management, who have looked at company innovation. Few studies mention the social context; even fewer are specific.’ While Hall makes a valid point, it is worth noting that the geography of innovation literature has itself been criticized on several counts ranging from the fact that it is built on illdefined and overlapping concepts or frameworks (from ‘industrial districts’, ‘innovative milieux’ and ‘clusters’ to ‘learning regions’, ‘regional innovation systems’ and ‘technoregions’) and that its contributors tend to neglect human agency by unduly emphasizing instead the role of social constructs such as
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‘networks’ or ‘milieu.’ It has also been increasingly recognized that geographical proximity is neither a necessary nor a sufficient condition for innovation and learning to occur and that many innovative activities involve the collaboration of employees of the same multinational firms (or their suppliers or research partners) based in different geographical locations, a process often conveyed by the expression ‘global pipelines’ which is contrasted to the ‘local buzz’ of individuals in close physical proximity of one another (Moulaert & Sekia, 2003; Boschma, 2005; Simmie, 2005). Despite conceptual and theoretical problems, however, it cannot be denied that some of the key processes emphasized in this literature, most notably that urban agglomerations greatly facilitate frequent face-to-face interactions between individuals belonging to different organizations, and that some places are more conducive to entrepreneurial activities and innovative behaviour than others, are undoubtedly real and important. As such, the world is far from being ‘flattened’ by new information and transportation technologies and locating in certain areas rather than others can still deliver some important economic benefits. Our main goal in this paper is to attempt to build a bridge to mutual enrichment between the ‘geography of innovation’ and ‘creativity and innovation management’ literatures. We do so by discussing and illustrating the inherent benefits of a more diversified local economic structure for innovative behaviour, a stance which goes against the long-standing pro-regional specialization prescription of traditional economic analysis. Our paper is structured as follows. First, we briefly cover the economic rationale of urban agglomerations and highlight how such settings can facilitate innovative advances and entrepreneurial activities. This is followed by a presentation of the advantages most commonly associated with a more diversified local economic structure and, through theoretical insights well-known to readers of this journal and additional illustrative case illustrations derived from a qualitative survey of Canadian individual inventors, of the specific mechanisms and patterns through which entrepreneurial ventures and established plants located in such contexts can more easily and ‘spontaneously’ benefit from ideas and knowhow used in other lines of work. Unveiling these processes, we argue, gives us a more comprehensive understanding of how a given location can facilitate analogical thinking (Gassmann & Zeschky, 2008) and new product development (Song, Montoya-Weiss & Schmidt, 1997; Ernst, 2002) at both the individual and firm level.
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Urbanization and Economic Development The systematic study of business location decisions and regional development processes has for more than a century generated a voluminous literature in disciplines ranging from geography, economics and urban planning to engineering, management, political science and sociology. Analysts have generally sought to develop theories in response to three empirical observations: (1) a large portion of world output is produced in a limited number of highly concentrated core regions; (2) firms in similar or related industries tend to co-locate in particular places; and (3) both of these patterns appear to be sustainable over time. This outcome has typically been attributed to what are now termed ‘agglomeration economies’, i.e., the economic benefits that individuals and firms obtain when locating near one another, including shared infrastructures and suppliers. Several authors, however, have also long observed that the geographical concentration of numerous human beings greatly facilitates sustained face-to-face interactions and creates a social environment that is most conducive to innovative behaviour. For example, the French economist Frederic Bastiat (2007/1850, p. 103) wrote more than a century and a half ago that the ‘density of population not only enables us to reap more advantage from the machinery of exchange, it permits us to improve that machinery, and increase its power.’ Indeed, he added, ‘on leaving the metropolis for a time, and going to reside in a small provincial town, one is astonished to find that in many instances the most ordinary services can only be obtained at great expense, and with time and difficulty’ (idem). Large concentrations of people also gave humans ‘more facility in dividing their employments, in uniting their powers, and in combining to found churches and schools, to provide for their common security, to establish banks and insurance companies, in a word, to procure themselves all the common enjoyments with a much smaller proportion of efforts’ (idem, p. 104). Decades later, the social reformer Frederic C. Howe (1915, p. 1), an author whose stance on economic issues was in direct opposition to that of Bastiat, similarly observed that education, culture, a love of fine arts, science, invention and industry had always ‘coincided with a highly developed city life’ because urbanization allowed a greater division of labour which in turn created ‘the wealth which such division makes possible.’ Of course, ‘the larger the city and the more minute the specialization, the greater the co-operation and the more easy [sic] the © 2011 Blackwell Publishing Ltd
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production of wealth.’ Arguably the most lasting contribution among early analysts is the economist Alfred Marshall’s (1920/1890) concept of an ‘industrial district’. Besides mentioning the external benefits that singleactivity or closely related producers derive from sharing the fixed costs of such common resources as specialized infrastructure and services, skilled labour pools and specialized suppliers, Marshall emphasized that through co-location and frequent interaction, producers share a common knowledge base, learn from and continuously build on each other’s advances. Numerous other scholars at the time made similar observations and highlighted the self-reinforcing nature of innovative processes in large urban agglomerations (Krzyzanowski, 1927). By the middle of the twentieth century, however, technological changes, economic growth and their resulting enhancement of labour and entrepreneurial mobility had led most analysts to conclude that the type of geographically concentrated industries identified by Marshall and others had ‘become increasingly rare’ while, by contrast, ‘external economies on the broader basis of urban size and diversity [had] remained a powerful locational force’ (Hoover & Giarratani, 1984/1970, p. 121). Furthermore, the development and/or refinement of analytical (mathematical) tools in which innovation was treated as a taken-forgranted black box resulted in the increased dominance of mechanistic and static ‘resources allocation’ or ‘location scanning’ perspectives among urban and regional scholars. These theoretical approaches, however, proved unable to account for the spontaneous and spectacular rise in the 1970s and 1980s of a number of regions, including Silicon Valley and Route 128 in the United States, as well as the so-called Third Italy, whose main characteristics were the spatial clustering of related, highly innovative and (for the most part) relatively small firms. Scholars in numerous disciplines thus began to (re)discover and further develop more qualitative and dynamic concepts and insights in an attempt to explain how the industrial and social characteristics of a given place (ranging in scale from streets to cities and regions) provide (or not) fertile soil for innovative behaviour, along with the continued relevance of dense and localized networks of small innovative firms. Of course, several of the realities described by academic researchers were well understood by successful businesspeople. To give but one illustration, the scientist/entrepreneur Ralph Landau (1996, p. 20) attributed the success of his small R&D organization to the fact that it was located in the Greater New York City area, thereby © 2011 Blackwell Publishing Ltd
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allowing his employees to benefit from an ‘extremely cosmopolitan perspective’ and ‘many of the features that only a large city can offer.’ He added: In fact, the kind of person who is attracted to New York is very often the kind who would not fit into the culture of a large company. For New York one can substitute few other major cities in the United States. Nevertheless, research organizations are often located on predominantly semi-rural or rural campuses where it is supposed that people can think more effectively. I have often felt that this is not always so and that the research environment for an industrial organization requires a feeling of intense energy – even pressure – and the knowledge that there are important problems that must be solved every day (idem). Fundamentally, the recent geography of innovation literature asks two questions: 1) Why are some regions more innovative than others? and 2) How does a specific location influence the continuous upgrading of firm capabilities? The answers most commonly provided still revolve around the importance of geographical proximity between actors, which greatly facilitate formal and informal collaborations between firms (be they potential competitors or in a user–producer relationship) and/or between firms and research institutions; the spin-off of new firms; and the transmission of tacit knowledge (through frequent face-to-face interactions and the inter-firm mobility of skilled workers). The case made on behalf of each factor is now briefly described.
Local Linkages and Collaboration Geographical proximity, because of the frequent interactions and long-term contracts or commitments between people that it allows (whether in working environments or in social activities), is often said to play a crucial role in building the trust bonds that are needed to share sensitive information and develop a successful customer–supplier relationship. Lissoni (2001) refers to these linkages as ‘epistemic communities’ within which information is circulated.
Spin-off Formation Entrepreneurship, especially in terms of employees creating new firms in close proximity to former employers (so-called ‘spin-offs’ or ‘start-ups’), is said to be greatly facilitated in some regional contexts (Breschi & Malerba, 2001). On the one hand, an entrepreneurial culture in which individuals continually leave
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their employers to launch new firms provides ample demonstration effect which further reinforces this tendency. On the other, localized industries provide easy access to specialized labour, inputs and customers which, along with the presence of knowledgeable investors, further facilitates the launch of innovative firms. Spin-offs also tend to create a local or regional environment in which individuals working for different organizations interact more with one another than would otherwise be the case.
Tacit Knowledge The more specialized and innovative an activity is, the more likely it is to be geographically concentrated. The more standardized it becomes, the more it tends to migrate toward customers or inputs. This pattern can be attributed in part to the fact that the crucial knowledge in any innovative industry is not standardized information, routine patterns or the public knowledge of science, but rather what is new, what are the latest changes, and the specialized know-how that individuals have acquired through practice and mistakes. Thus, knowledge from which innovations stem is not freely available, thereby providing firms that locate near its sources with a competitive advantage. As such, globalization and improvements in telecommunication technologies have not crowded out the need for proximity, but conversely have strengthened it in cases where crucial knowledge is only available locally (Audretsch, 2003; Gertler, 2003). And even though most of the suppliers and customers of a firm might be located outside its regional setting, being located in an innovative area typically allows creative and entrepreneurial individuals to absorb thinking processes, along with specialized know-how and ways of doing things, while also increasing the probability of useful informal encounters (Cohen & Levinthal, 1990; Nooteboom, 2000). Such a setting also makes it easier for entrepreneurs, managers and technicians to monitor emerging technologies closely and to find answers to their questions more rapidly, in the process lessening the probability of being caught off guard by new breakthroughs. While much evidence points toward the continued importance of geographical location for fostering creativity and innovation in some specific contexts, this argument should be handled more cautiously than it often is for reasons ranging from the ‘fuzziness’ of the main concepts used in the ‘geography of innovation’ literature; the continued importance of both traditional agglomeration economies
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and non-regional networks and linkages in explaining the locational decisions and practices of countless firms; and the fact that individuals born in or enjoying less advantageous locations are sometimes able to overcome geographical disadvantages (Desrochers, 2001a; Boschma, 2005). Perhaps most problematic, however, is that the geography of innovation literature has, by and large, remained confined to the study of innovation within one line of work and has thus far neglected the processes underlying the cross-fertilization of knowhow across different lines of work and the facilitating role that a more diversified local economic base might play in this respect. We will turn our attention to this issue after having first summed up the other well-known advantages of diversified local economies.
Local Diversity and Economic Resilience Following David Ricardo’s writings on comparative advantage, most economic analysts have considered the local specialization of economic activities as both a natural and desirable outcome of trade liberalization. By concentrating on the production of what they do relatively better than others and through subsequent exchange, all individuals (and regions) enjoy a greater standard of living than if they were attempting to produce a wider range of goods and services in their local community. Regional economic specialization is also said to allow producers to tap into the types of formal and informal assets discussed in the previous section (Porter, 1990). However, as Marshall (1920, p. 273) wrote several decades ago, ‘a district which is dependent chiefly on one industry is liable to extreme depression, in case of a falling-off in the demand for its produce, or of a failure in the supply of the raw material which it uses’; an outcome which still seems unavoidable (Chapman, 2005). Not surprisingly, Marshall (idem) observed that this problem was ‘in a great measure avoided by those large towns or large industrial districts in which several distinct industries are strongly developed.’ Hoover and Giarratani (1984) similarly pointed out that regional economic diversification had long been viewed as a ‘ “healthy” structural feature worth striving for’ although ‘the grounds for this view . . . have never been clearly articulated.’ In their opinion, this case can be traced back to the assumption that ‘a region with a diversified structure (many different kinds of activities and an absence of strong specialization) is necessarily less vulnerable to cyclical swings of general business © 2011 Blackwell Publishing Ltd
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conditions and demand’ and that multiple employment and investment opportunities create more opportunities for workers, entrepreneurs and investors, thus providing ‘a better chance for new kinds of business to get a start and to survive the hazardous years of infancy.’ It has also long been held that a more diversified local economy inherently enjoys a greater ‘multiplier effect’ when new activities are added to existing ones, at least inasmuch as a greater range of local suppliers are likely to be called upon.2 While the previous arguments have long been discussed, in the last two decades a new consideration has increasingly been raised in policy discussions. In short, spurred by economists Robert Lucas (1988) and Ed Glaeser et al. (1992), who traced the insight back to urban theorist Jane Jacobs (1969), several researchers have attempted to assess whether or not internally diverse regions might be better incubators of innovative activities. These researchers, however, have typically limited their analysis of ‘Jacobs spillovers’ to the idea that a more diversified local economy inherently promotes the diffusion of ideas across different lines of work despite the fact that Jacobs’ framework is broader and puts much more emphasis on the importance of traditional urbanization economies for entrepreneurial activities. While there is now no lack of statistical research on localized knowledge spillovers, there is, however, a general concern that the econometric studies that link together regional measures, such as the degree of economic specialization and growth, do not yield any direct proof of the very existence of knowledge spillovers (Breschi & Lissoni, 2001; Hansen, 2002; Beaudry & Schiffauerova, 2009). We now turn to a more in-depth discussion of this subject.
Local Diversity, Human Creativity and Jacobs Spillovers Local Diversity and Human Creativity As stated above, the basic idea underlying ‘Jacobs spillovers’ is that the crucial know-how underlying technical advances do not come from the reuse or diffusion of knowledge among competitors in similar lines of work, but rather from different activities. In other words, while creative individuals can be found in all locations, they are faced with more numerous and different kinds of problems and given more opportunities to address them in more economically diverse environments, especially in terms of being able to interact with people that possess different expertise than their own. Therefore, besides the creativ© 2011 Blackwell Publishing Ltd
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ity and innovation management activities taking place as a matter of course in firms, more diversified local economies are inherently more likely than more specialized ones to foster innovative behaviour and activities within corporate settings. If true, strategic location decisions should therefore factor in to some extent considerations other than traditional factors such as input (labour, energy, etc.) availability, proximity to markets, transport infrastructure, taxation and regulations. Of course, the fact that all innovations are the result of new combinations of pre-existing and different know-how, skills, ideas, processes, materials and artifacts has long been known and discussed by both students of human creativity and technological innovation. It has also long been recognized that multidisciplinary teams most efficiently link concepts developed in one technological area to problems arising in another by helping individuals overcome the blinkers created by their particular expertise (Babbage, 1832; Carter, 1939; Fores, 1979; Twiss, 1980/1974; Schroeder et al., 1989; Desrochers, 2001b).3 Conversely, the typical pitfall of a highly specialized local economy on the creative potential of its inhabitants was obvious to Keir (1919, p. 47) almost a century ago: From the point of view of employees, [geographically-specialized] localization is bad because it also tends toward narrowing the minds of the townspeople. A young man brought up in Fall River [Massachusetts], say, has but little choice of occupation; he must become a weaver or a loom-fixer or some other artisan connected with cotton manufacture, because by upbringing, education and example he is forced into that path, and furthermore he goes to work at an early age. It may happen that many a square peg is rammed into a round hole in this way, or a life constricted which might under better conditions have expanded. There is something deadening to the human mind in uniformity; progress comes through variation, therefore in a town of one industry a young man loses the stimulus for self-advancement. But while these points are well taken, very little has been written on the specific processes through which local economic diversity can actually facilitate innovative behaviour. We now turn to our own attempt to document these processes.
Jacobs Spillovers in the Canadian Context To gain a better understanding of the circumstances through which local economic diversity can facilitate the development of new
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combinations of artifacts, ideas and skills, we set out to study individual inventors, for whom moving frequently between different lines of work and/or regularly borrowing ideas from fields other than their own seems to be a dominant characteristic.4 Two rounds of semi-structured interviews covering, among other subjects, life history, formal education and training, work experience, creative thought processes and habits, and specific inventions were conducted with individuals based in Canada’s two most economically diverse regions. The first, completed in collaboration with the now defunct FrenchCanadian inventor’s association Le monde des inventions québécoises between 1997 and 1999, involved 45 Southern Quebec inventors. As it turns out, however, the majority of the interviewees were reluctant to engage in any form of long-distance business relationships with English-speaking individuals because of linguistic deficiencies. In order to address this issue, another round of interviews was conducted between 2006 and 2009 with a group of 40 English-Canadian inventors in collaboration with the Toronto-based Concept to Creation Cooperative. Unlike the more culturally homogeneous first group, these individuals’ backgrounds turned out to be remarkably diverse in light of the fact that several of them were born, educated and often had work experience in foreign countries. From the evidence gathered and our preparatory and supplemental literature review, we identified three broad, although not mutually exclusive, sets of circumstances through which individuals found new uses or applications for existing products and created new combinations of existing products, processes and materials: (1) by adding to, switching or adapting specific know-how to other lines of work; (2) by observing something in another line of work and incorporating it into one’s own line of work; and (3) through formal and informal multidisciplinary teams working towards the creation of new products and processes. We are reasonably confident that, despite the obvious geographical and size limitations of our empirical study and limits of our literature review, these basic processes are at the root of virtually all cases of Jacobs spillovers. The following will provide relevant illustrative examples.
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sional backgrounds of the individuals interviewed. A representative case is that of an individual who regularly moved to other fields in search of new challenges and who ended up working in the electronics, digital devices and early IT and telephone industries. Another example is that of an industrial technician who worked in the steel, chemical, aeronautical and armament industries before launching his own ceramic-making business. This widespread pattern of employment across different lines of work seems to be attributable at least in part to the fact that technically creative individuals tend to get bored very quickly with routine work. Gaining knowledge from other lines of work, however, need not always imply moving between firms and therefore the mechanism is broader than the generally understood definition of job mobility. Employees may acquire useful knowledge by moving between different divisions within a large firm or when a firm expands into new lines of business. Whatever the cause, however, this observed widespread pattern of job mobility facilitates the spontaneous transfer of know-how across otherwise seemingly unrelated lines of work. For example, one interesting case involved the transfer of some basic know-how from the newspaper printing business to asphalt production. A recurring problem in the latter line of work was the question of how to clean up residual asphalt found sticking to the inside of tanks after long periods of inactivity. At a particular asphalt firm, people actually climbed into the tank to scrape the residual off, a process that was both laborious and potentially damaging to the equipment. After noticing this, the individual interviewed pointed out to his then new employer that, in the printing business where he had previously been employed, large tanks were cleaned by pouring hot water into them. This technique was tried and eventually proved to be successful, saving the company a significant amount of resources. Of course, in many (if not most) cases, implementing know-how or ideas in new contexts will typically be but one step towards the creation of a new or improved product or process. Several other ideas, along with a significant amount of development work, will also be required.
Adding to, Switching or Adapting Specific Know-How to Other Lines of Work
Observing Know-How and Materials and Incorporating Them in a Different Production Setting
Benefiting from knowledge gained from previous jobs and tasks was one of the main knowledge spillover mechanisms observed, particularly in light of the very diverse profes-
Sometimes observation and subsequent learning can be sufficient for the creation of interindustrial knowledge spillovers. One such example among our interviewees is a chemical
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engineer who once worked for a company with plants in remote locations. At the time, his employer needed to reduce his manpower, but was reluctant to do so in isolated plants for fear that employees working alone would be left unattended for several hours if hurt. This individual knew of devices that alerted emergency response personnel when a button was pushed, but this approach would obviously be inadequate if a worker was knocked unconscious. The engineer contacted a company supplying this service and requested that motion detectors be incorporated in their system so that an emergency call would automatically be placed if no motion was detected after a predetermined amount of time. As a result of this new combination, the company was able to save a considerable amount of money without risking the safety of its employees. An additional feature was then added to the system to allow it to work as a burglar alarm when activated by the employee. Our interviewee does not know if similar safety systems are now being used elsewhere, but an article on this particular invention was published in a trade magazine. Other cases we documented include a shower brush inspired by a car wash brush; a mouse pad arm rest combined with an office chair that was inspired by some classroom furniture; a controllable sled inspired in part by the movements of ice skates; a production shop for a new type of baby bag inspired by the division of labour in a restaurant kitchen; and a device to conduct time studies that drew on ideas from chess clocks, stop watches and computers, among others.
Multidisciplinary Team Made up of Individuals Possessing Different Skills Firms are social environments where people with very different backgrounds can interact on a regular basis for the specific purpose of creating new combinations. From the perspective of one inventor interviewed: ‘If you have experience with one thing, if you are inventor, this is very useful for you. But the most useful thing from maybe . . . last five years was that I have knowledge, I receive knowledge from other people.’ After having worked in a number of different firms and industries, he found that learning from colleagues with different skills significantly improved his creative capacities. Of course, this interpersonal and interdisciplinary aspect of creativity has long made firms interested in promoting cross-functional new product teams (Song et al., 1997). On other occasions, though, multidisciplinary teams can be composed of individuals © 2011 Blackwell Publishing Ltd
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working for different employers and collaborating or providing input on a project, either formally or informally. Thus, the interaction can take place within inter-firm or social networks (Kogut, 2000; Balconi, Breschi & Lissoni, 2004), as well as within intra-firm teams. Again, this basic insight has a long history. For example, J.S. Mill (1848, Book III, Chapter XVII) considered the interaction among persons with dissimilar modes of thought and action one of the primary sources of progress. One interesting case brought to our attention is a bicycle rack for domestic (or home) use. The inventor interviewed originally got the idea from a friend who pointed out that no such thing existed yet. The reasons for this soon became obvious as he began researching the topic. The rack needed to be light enough to be carried, heavy enough to hold the bicycles and prevent thefts, have a nice design, be maintenance-free and suitable for four bicycles (two adult and two children’s bicycles), be they racing or mountain bikes. Finally, it should be affordably priced. A metallic structure would have met most of these requirements, but would have been too heavy to carry. Aluminium was a lighter option, but was too expensive. The inventor then thought of using plastic, but realized quickly that it would be too light. He contacted an industrial draughtsman with whom he had worked in the past on a specially designed water container for long-distance running. His former collaborator suggested that the rack should be made by blowing rather than casting (i.e., filling a plastic mould) plastic. That way it would be empty inside, which would make it light enough to carry, but heavy enough to hold the bicycles in place after it was filled with water. This solution would finally prove to be the best one. Interestingly enough, although this solution could be seen post facto as a direct implementation of the main principle involved in their previous collaboration, the inventor still needed his previous collaborator to conceive of this approach.
Local Economic Diversity and the Fostering of Jacobs Spillovers Assessing the specific impact of large and diversified metropolitan areas on interindustrial knowledge spillovers is not as straightforward as documenting the existence and importance of knowledge spillovers in highly specialized industrial districts. Indeed, in most cases, the new combinations we documented could probably have been developed in many other large urban agglomerations, especially when they were inspired by ‘nonlocal’ observations such as watching television
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or travelling. Nonetheless, a number of recurring observations and patterns can be identified from our cases. The first is that Jacobs spillovers are only one facet of the economic advantages of large and diverse agglomerations. Indeed, just as Jacobs (1969) herself had strongly emphasized, traditional urbanization economies, especially the widespread availability of a broad range of supply goods, were judged crucial by inventors. Individuals who had lived in both a large urban agglomeration and a highly specialized one were especially adamant on this point. The greater facility of face-to-face interaction between individuals possessing different expertise made possible by close physical proximity was also made abundantly clear to us. The reasons given in this respect ranged from traditional ones, such as establishing trust and jointly addressing innumerable hurdles in development phases, to one that is more specific to Jacobs spillovers, i.e., making sure that individuals with different expertise truly understood each other and that the final product reflected the vision of the project leader. Interestingly, while our interviews spanned a decade which saw drastic improvements in information and communication technologies, electronic communication and the Internet did not seem to affect inventors’ strong preference for face-to-face interactions and local suppliers. Of course, the fact that the Greater Toronto area is one of the most economically diversified urban agglomerations in advanced economies certainly played a role in this respect. Another recurring theme was, not surprisingly, that a large urban agglomeration provides many unplanned learning opportunities by spontaneously allowing creative individuals to observe processes and ways of doing things in different contexts. The main channel in this respect seems to be job mobility between different lines of work, a process that is obviously facilitated by the fact that a large and diverse metropolitan area gives creative individuals the possibility to do so without having to relocate their family or lose their friends and social networks. Admittedly, the expertise and capacities possessed by an individual influence the number of possible job opportunities available to him. But while many companies are limited to a specific sector or a few end products, many industrial capacities are generic in nature and can be applied in many different contexts. Finally, it can be pointed out that some social networks proved especially conducive to Jacobs spillovers, chief among which were the inventors associations themselves. In short, since each individual member’s background is
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limited in various ways, belonging to an association whose members have diverse and complementary expertise typically proves valuable. While opening up to other individuals often proves difficult for inventors, as the limits of their know-how became apparent during the development phase of their invention, they typically became more willing to discuss their ideas as they came to understand the trade-offs between secrecy and the sharing of insights and expertise with individuals whose own know-how was often complementary to theirs. Besides networking with other inventors in order to tap into different skill sets, intellectual stimulation and friendship, an important aspect of these associations is the support their members can provide to each other in terms of locating manufacturers for the supply or fabrication of specific parts, sources of capital and help with marketing and distribution, business activities that are typically of a more generic nature.
Conclusion Economically diversified cities and regions have long been recognized as being more resilient and offering more opportunities than mono or less diversified industrial settings. Despite the fact that specific materials, products and processes have always cut across ‘industrial sectors’, economic specialization has long been held by students of regional growth as the optimal economic setting to promote development and growth. Jacobs (1969), on the other hand, argued that local diversity increases the probability of combining different resources. Indeed, it seems hard to argue against the premise that a diversified city is more likely than a more specialized one to facilitate the transfer of know-how from one area of industry to others that are unrelated in terms of final products. By offering a greater number and variety of problems to be solved, as well as a much wider pool of expert knowledge and other resources, a diversified city can only increase the probabilities of new combinations. More concretely, the exchange of ideas across industries seems to result from a few recurring processes: (1) by adding to, switching or adapting specific know-how to other lines of work; (2) by observing something in another line of work and incorporating it into one’s own line of work; and (3) through formal and informal multidisciplinary teams working towards the creation of new products and processes. It would therefore seem plausible to suggest that, when other things are relatively equal (from taxation levels to the availability of key © 2011 Blackwell Publishing Ltd
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inputs), a conscious decision on the part of an entrepreneur to locate their venture in a large diversified economy is more likely to spontaneously facilitate the absorption of know-how from other economic sectors within their organization. A better understanding of the ways in which creative individuals combine existing resources in different configurations, however, requires that familiar research designs in disciplines such as economics and geography be reconsidered and, at the very least, supplemented by insights that are probably familiar to most readers of this journal. The gains from such an exchange would seem to be twofold. On the one hand, the geography of innovation literature can help unveil the effect of regional factors on firms’ and individuals’ innovative capabilities and hence provide relevant insights for management scholars and entrepreneurs alike. While creativity and innovation are by their nature difficult to manage directly, firms can find ways that indirectly foster them, location choices being one important issue in this regard. On the other hand, creativity has largely been given a background role in the geography of innovation studies. The creativity and innovation management literature can hence in turn shed some light on the micro-foundations of learning which have puzzled urban and regional scholars for some time (Duranton & Puga, 2004).
Notes 1. A metropolitan area includes not only the population of a well-known political entity (e.g., Paris, London or New York), but also its suburban, ex-urban and sometimes surrounding rural populations, all of whom are part of the same economic entity in terms of employment, transportation and commerce. 2. Of course, a specialized region can experience faster and more significant employment and wealth creation than a more diversified local economy when there is a high demand for its main product. 3. Not surprisingly in light of the importance of new combinations in any creative act, some social scientists have addressed the inter-industrial diffusion of technological know-how through frameworks and concepts such as ‘technological convergence’, ‘technoeconomic paradigms’, ‘general purpose technologies’ and ‘recombinant growth’ (Weitzman, 1998; Lipsey, Carlaw & Bekar, 2005), while students of human creativity have written extensively on ‘associative ability’, ‘bisociation’, ‘lateral thinking’ and ‘analogical reasoning’, among others (Koestler, 1964; De Bono, 1992; Weber & Perkins, 1992; Csikszentmihalyi, 1997; Sternberg, 1999; Desrochers, 2001b; Kaufmann, 2004; Berkun, 2007). © 2011 Blackwell Publishing Ltd
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4. An individual inventor chooses the field in which he works, employs his own resources or acquires them from others who exercise no control over his work, and stands to gain or lose directly from his inventive success or failure. Unlike corporate inventors, an individual inventor typically works with limited resources and with colleagues subject to his guidance and leadership (Jewkes, 1969, p. 72).
References Audretsch, D.B. (2003) Innovation and Spatial Externalities. International Regional Science Review, 26, 167–74. Babbage, C. (1832) On the Economy of Machinery and Manufactures, 2nd edn, Charles Knight, London. Balconi, M., Breschi, S. and Lissoni, F. (2004) Networks of Inventors and the Role of Academia: An Exploration of Italian Patent Data. Research Policy, 33, 127–45. Bastiat, Frederic (2007/1850). The Bastiat Collection, Volume 2 (Harmonies of Political Economy), Ludwig von Mises Institute, Auburn, AL. Beaudry, C. and Schiffauerova, A. (2009) Who’s Right, Marshall or Jacobs? The Localization versus Urbanization Debate. Research Policy, 38, 318–37. Berkun, S. (2007) The Myths of Innovation, O’Reilly Media Inc., Sebastopol, CA. Boschma, R. (2005) Proximity and Innovation: A Critical Assessment. Regional Studies, 39, 61–74. Breschi, S. and Lissoni, F. (2001) Knowledge Spillovers and Local Innovation Systems: A Critical Survey. Industrial and Corporate Change, 10, 975– 1005. Breschi, S. and Malerba, F. (2001) The Geography of Innovation and Economic Clustering: Some Introductory Notes. Industrial and Corporate Change, 10, 817–33. Carter, H.D. (1939) If You Want to Invent, The Vanguard Press, New York. Chapman, K. (2005) From ‘Growth Centre’ to ‘Cluster’: Restructuring, Regional Development, and the Teesside Chemical Industry. Environment and Planning A, 37, 597–615. Clark, G.L., Feldman, M.P. and Gertler, M.S. (2000) The Oxford Handbook of Economic Geography, Oxford University Press, Oxford. Cohen, W.M. and Levinthal, D. (1990) Absorptive Capacity: A New Perspective on Learning and Innovation. Administrative Science Quarterly, 35, 128–52. Csikszentmihalyi, M. (1997) Creativity: Flow and the Psychology of Discovery and Invention, Harper Perennial, New York. De Bono, E. (1992) Serious Creativity: Using the Power of Lateral Thinking to Create New Ideas, Harper Business, New York. Desrochers, P. (2001a) Geographical Proximity and the Transmission of Tacit Knowledge. The Review of Austrian Economics, 14, 25–46. Desrochers, P. (2001b) Local Diversity, Human Creativity and Technological Innovation. Growth and Change, 32, 369–94.
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Duranton, G. and Puga, D. (2004) MicroFoundations of Urban Agglomeration Economies. In Henderson, J.V. and Thisse, J.-F. (eds.), Handbook of Regional and Urban Economics, Vol. 4. Elsevier, Amsterdam, pp. 2063–117. Ernst, H. (2002) Success Factors of New Product Development: A Review of the Empirical Literature. International Journal of Management Reviews, 4, 1–40. Florida, R. (2002) The Rise of the Creative Class: And How it’s Transforming Work, Leisure, Community and Everyday Life, Basic Books, New York. Florida, R. (2005) Cities and the Creative Class, Routledge, New York. Florida, R. (2008) Who’s Your City? How the Creative Economy is Making Where to Live the Most Important Decision of Your Life, Basic Books, New York. Fores, M. (1979) The History of Technology: An Alternative View. Technology and Culture, 20, 853– 60. Gassmann, O. and Zeschky, M. (2008) Opening up the Solution Space: The Role of Analogical Thinking for Breakthrough Product Innovation. Creativity and Innovation Management, 17, 97– 106. Gertler, M. (2003) Tacit Knowledge and the Economic Geography of Context, or The Undefinable Tacitness of Being (There). Journal of Economic Geography, 3, 75–99. Glaeser, E.L., Kallal, H.D., Scheinkman, J.A. and Shleifer, A. (1992) Growth in Cities. The Journal of Political Economy, 100, 1126–52. Hall, P. (2000) Creative Cities and Economic Development. Urban Studies, 37, 639–49. Hansen, N. (2002) Dynamic Externalities and Spatial Innovation Diffusion: Implications for Peripheral Regions. International Journal of Technology, Policy and Management, 2, 260–71. Hoover, E.M. and Giarratani, F. (1984/1970) An Introduction to Regional Economics, 3rd edn, Alfred A. Knopf, New York. Hospers, G.J. and Pen, C.J. (2008) A View of Creative Cities Beyond the Hype. Creativity and Innovation Management, 17, 259–70. Howe, F.C. (1915). The Modern City and Its Problems. Charles Scribner’s Sons, New York. Jacobs, J. (1969) The Economy of Cities, Random House, New York. Jewkes, J., Sawyer , D. and Stillerman, R. (1969) The Sources of Invention, 2nd edn, MacMillan, London. Kaufmann, G. (2004) Two Kinds of Creativity – But Which Ones? Creativity and Innovation Management, 13, 154–65. Keir, M. (1919) The Localization of Industry: How it Starts; Why it Grows and Persists. The Scientific Monthly, 8, 32–48. Koestler, A. (1969/1964) The Act of Creation, Hutchinson of London, London. Kogut, B. (2000) The Network as Knowledge: Generative Rules and the Emergence of Structure. Strategic Management Journal, 21, 405–25. Krzyzanowski, W. (1927) Review of the Literature of the Location of Industries. Journal of Political Economy, 35, 278–91.
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Lampard, E. (1955) The History of Cities in the Economically Advanced Areas. Economic Development and Cultural Change, 3, 81–136. Landau, R. (1996) Entrepreneurs, Managers, and the Importance of Finance. Daedalus, 125, 19–37. Lipsey, R.G., Carlaw, K.I. and Bekar, C.T. (2005) Economic Transformations: General Purpose Technologies and Long-Term Economic Growth. Oxford University Press, Oxford. Lissoni, F. (2001) Knowledge Codification and the Geography of Innovation: The Case of Brescia Mechanical Cluster. Research Policy, 30, 1479– 500. Lucas, R.E. (1988) On the Mechanics of Economic Development. Journal of Monetary Economics, 22, 3–42. Marshall, A. (1920/1890) Principles of Economics, 8th edn, Macmillan, London. Mill, J.S. (1848) Principles of Political Economy with some of their Applications to Social Philosophy, 7th edn, Longmans, Green and Co., London. Moulaert, F. and Sekia, F. (2003). Territorial Innovation Models: A Critical Survey. Regional Studies, 37, 289–302. Nooteboom, B. (2000). Learning by Interaction: Absorptive Capacity, Cognitive Distance and Governance. Journal of Management and Governance, 4, 69–92. Polese, M. (2005) Cities and National Economic Growth: A Reappraisal. Urban Studies, 42, 1429– 51. Porter, M. (1990) The Competitive Advantage of Nations, The Macmillan Press, London. Rantisi, N., Leslie, D. and Christopherson, S. (2006). Guest Editorial: Placing the Creative Economy: Scale, Politics and the Material. Environment and Planning A, 38, 1789–97. Schroeder, R.G., Van de Ven, A.H., Scudder, G.D. and Polley, D. (1989) The Development of Innovation Ideas. In Van de Ven, A.H., Angle, H.L. and Poole, M.S. (eds.), Research on the Management of Innovation: The Minnesota Studies, Harper and Row, New York, pp. 107–34. Scott, A.J. (2006) Creative Cities: Conceptual Issues and Policy Questions. Journal of Urban Affairs, 28, 1–17. Simmie, J. (2005) Innovation and Space: A Critical Review of the Literature. Regional Studies, 39, 789– 804. Song, X.M., Montoya-Weiss, M.M. and Schmidt, J.B. (1997) Antecedents and Consequences of CrossFunctional Cooperation: A Comparison of R&D, Manufacturing, and Marketing Perspectives. Journal of Product Innovation Management, 14, 35–47. Sternberg, R.J. (ed.) (1999) Handbook of Creativity, Cambridge University Press, Cambridge. Twiss, B.C. (1980/1974) Managing Technological Innovation, Longman, London. Weber, R.J. and Perkins, D.N. (1992) Inventive Minds: Creativity in Technology, Oxford University Press, New York. Weitzman, M.L. (1998) Recombinant Growth. The Quarterly Journal of Economics, 113, 331–60.
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Pierre Desrochers (pierre.desrochers@ utoronto.ca) is Associate Professor of Geography at the University of Toronto. His main research interests are economic development, technical innovation, business– environment interactions, and energy and food policy. He maintains a detailed website at http://epsem.erin.utoronto.ca/ desrochers/ Samuli Leppälä is Research Associate in Economics at the University of Turku, Finland. He received his Masters degree from Turku School of Economics in 2004 and is currently finalizing his doctoral thesis. His research interests include markets for information, research activities and incentives, and the geography of innovation. His research has been published in journals such as Journal of Economic Behavior and Organization and International Regional Science Review.
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Book Review
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Rickards, T., Runco, M.A. and Moger, S. (eds.) (2009) The Routledge Companion to Creativity, MIT Press, Cambridge, MA. $150, 382 pp, ISBN 978-0-415-77317-1.
C
reativity, the ability to, the process of, and the result of creating new and useful thoughts and solutions – there are as many ways to foster creativity of individuals, organizations or networks as there are different views on what creativity is. This book yields an enormous variety of theoretical viewpoints on creativity and practical starting points to foster creativity. To do so authors from multiple disciplines (Business, General Management, Strategy, Design Management, Innovation Management, Marketing, Leadership, Entrepreneurship, Organizational Change, Organization Theory, Organization Management, Organizational Science, Organizational Behaviour, Organizational Psychology, Personality Psychology, Social Psychology, Human Development, Industrial Psychology, Economic Psychology, Cognitive Science, Philosophies of Mind) were invited to contribute. Some 41 creativity experts contributed in total 30 chapters. Seven themes are featured. Theme 1 ‘Creativity and design’ includes a general chapter on ‘the creative potential of design in business’ and chapters on special aspects such as improvisation, sound and workplaces. Theme 2 ‘Environmental influences’ focuses mainly on collaboration (win–win collaborations, consumer innovation, knowledge relationships) except for the chapter on the impact of turbulences. Theme 3 ‘Innovation and entrepreneurship’ is represented by a chapter on ‘evolutionary models of innovation and creativity’, one chapter on ‘creativity and entrepreneurship’ and one on ‘combining expertise in complex innovations’. Theme 4 ‘Knowledge Management’ includes one chapter arguing for a holistic view on knowledge and creativity management and the second chapter outlining a theory on knowledge creation. Theme 5 ‘Meta-theories of creativity’ introduces several theories: one chapter connects general creativity (C) with artificial intelli-
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gence studies, one chapter develops a multilevel level framework of individual and collective creative actions, one introduces the investment theory of creativity and refers to concepts from the economic domain, one chapter challenges assumptions about novelty from a deconstructive perspective. The last chapter proposes ‘idea activity’ as an alternative to assess economy’s innovativeness. Theme 6 ‘Personal creativity’ looks at the personal creative ability in terms of outstanding talents, intellectual styles, personality traits and occupations, thinking styles of creative leaders, work roles from a social and a symbolic perspective, and change-centred leadership. Theme 7 ‘Structured interventions’ presents several approaches to foster creative thinking including prototyping, CPS, Lateral Thinking, and computer-supported idea generation. The themes are interesting and all chapters are well written. Many chapters, especially in Theme 5: ‘Meta-theories of creativity’ acknowledge that creativity is not only a result of creative behaviour of individuals, but also of teams, organizations, formal co-operation and networks. Additionally, creativity in context with other related topics is dealt with: design (Theme 1), innovation and entrepreneurship (Theme 3), knowledge management (Theme 4). Showing and discussing these connections is a very valuable approach. Three of four classical viewpoints on creativity (person – Theme 6, process – in terms of intervention in the process, Theme 7, press/situation – Theme 2) are dealt with, but what may still be missing is the viewpoint on the creative product, a challenge which may be taken up by Creativity and Innovation Management in its subsequent issues. Overall this book’s enormous variety makes it a perfect companion for creativity experts. Beginners and readers looking for a more restricted and structured overview of the field © 2011 Blackwell Publishing Ltd
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of creativity may find difficulty tapping in. Like a knowledgeable discussion partner, the book can show interesting aspects of creativity you have never thought of yourself and provoke new insights and research questions. Edited by this journal’s founding editors (Moger and Rickards) jointly with the editor of
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the Creativity Research Journal (Runco), this book is a must-read for members of the CIM community! Carmen Kobe ETH Swiss Federal Institute of Technology Zurich
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Volume 20
Number 1
doi:10.1111/j.1467-8691.2011.00587.x
2011
© 2011 Blackwell Publishing Ltd
ANNOUNCEMENT
© 2011 Blackwell Publishing Ltd
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Volume 20
Number 1
2011
doi:10.1111/j.1467-8691.2011.00588.x
CREATIVITY AND INNOVATION MANAGEMENT
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21st EUROPEAN DOCTORAL SUMMER SCHOOL ON TECHNOLOGY MANAGEMENT Technology Management Crossing Boundaries Sabanci University, Istanbul, Turkey, 5–9 September 2011 Supported by radma (www.radma.org) and Creativity and Innovation Management (www.blackwellpublishing.com/caim) caim_590
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The Summer School is a valuable experience for anyone involved in doctoral work in the area of technology and innovation management. It provides a unique opportunity for doctoral students in technology management (TM) to learn from presentations by leading academics in the field and to meet colleagues with similar research interests. During the intensive one-week course, the participating students have the opportunity to discuss their research programmes with senior professors and with other PhD students in interactive workshops, and to meet the editors of the journals R&D Management and Creativity and Innovation Management.
Technology Management Crossing Boundaries The theme of the Summer School is to highlight the similarities and differences in the technology management practices across countries. For example, nearly a quarter of the literature in 2007 was created with the contribution of researchers in developing countries. However, the TM literature created in developing countries on the whole differs from its counterpart generated in the developed world. PhD students who are the next generation of researchers in the field should be aware of the variety and richness of technology and innovation management. The lectures are organized to lay the ground in key research areas where attendees will benefit from the intellectually challenging environment. The seminar will be held at the Sabanci University, Turkey. The programme will start on 5 September 2011 and is scheduled to end on 9 September 2011. Applications: Students will be selected according to the novelty and the quality of their research interests and by an indication that they will be able to benefit and learn effectively from their participation. Students should at least have finished their first PhD year in order to be eligible. They must show that they will be able to contribute to the event. Interested doctoral students should apply on-line via www.eiasm.org no later than 15 June 2011 For detailed information and programme: http://www.eiasm.org/frontoffice/event_announ cement.asp?event_id=802
Volume 20
Number 1
doi:10.1111/j.1467-8691.2011.00590.x
2011
© 2011 Blackwell Publishing Ltd
