careers, communities, and industry evolution: links to ...

International Journal of Innovation Management Vol. 5, No. 2 (June 2001) pp. 239 –255 © Imperial College Press

CAREERS, COMMUNITIES, AND INDUSTRY EVOLUTION: LINKS TO COMPLEXITY THEORY

MICHAEL B. ARTHUR* AND ROBERT J. DEFILLIPPI† Sawyer School of Management Suffolk University, 8 Ashburton Place Boston, MA 02108, USA *e-mail: [email protected] †e-mail: [email protected] VALERIE J. LINDSAY Department of International Busines, The University of Auckland Private Bag 92019 Auckland, New Zealand e-mail: [email protected]

Received 30 October 2000 Revised 21 February 2001 Accepted 22 February 2001

Traditional views of industry evolution focus on the company as their principal unit of analysis. We offer an alternative view that links between workers’ careers and successive community, company and industry effects. We apply this view to evidence from independent film-making, and suggest a conception of the career, involving three “ways of knowing”, to underlie these links. We next explore two more industry examples, the New Zealand boat building industry and the Linux operating system in the software industry, which provide further support for the alternative view proposed, as well as extending it to consider the influence of the World Wide Web. We see all three industry examples as illustrating a range of ideas in complexity theory. We propose that a career-centric view provides a useful basis for the further exploration and application of complexity theory to industrial life. Keywords: clusters, career, knowledge, complex systems, communities

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M. B. Arthur, R. J. Defillippi, & V. J. Lindsay

Introduction The pace of change in company fortunes and related employment arrangements has overtaken traditional assumptions about workers’ careers. What were once seen as “orderly” progressions of occupational or organisational prestige (Wilensky, 1961) are now seen to be in disarray. The pace of technological change and the opening up of global markets have unraveled the old orthodoxy about what successful careers involved. We submit this may be a good thing. The changes afoot suggest a different understanding of careers, and in turn a different understanding of both the companies and industries to which careers contribute. Increasingly, careers — sequences of individual work experiences over time — do not have any predetermined shape. Rather, their shape is provided by the worker, in enacting his or her career (Weick, 1996), often within rapidly changing company, industry or societal environments. As this occurs, workers contribute to the structuring of the work arrangements in which they participate. Furthermore, contemporary careers predictably unfold across successive employment and institutional settings. In this more dynamic set of arrangements, few companies will host whole careers, but companies of all shapes and sizes will host episodes in people’s careers. As careers progress through successive host companies, they become repositories of personal learning, and like bees bearing pollen, bring new learning to each company along the way. It is this contribution of careers to larger patterns of company and inter-company learning that is the focus of this article. This view of careers sees the person, rather than the firm or organisation, as the underlying element in economic organising. It resonates with recent ideas from complexity theory, and with the application of those ideas to social and economic life (Cilliers, 1998). However, in asserting that the person is the element behind contemporary life, it also invites us to rethink the role of the company, which remains the principal focus of attention in both management and economic theory.

Contrasting Views of the Links Among Careers, Communities, Companies and Industry Clusters In the discussion that follows, we link ideas about the concepts of career, community, company and industry. Figure 1 represents the traditional view of the relationships among these phenomena. What Galbraith (1971: p. 9) once called the “modern large corporation” was seen as a having a critical influence over the nature of the host industry. Communities were seen as the work groups that prevailed within the employment boundaries of the corporation. Careers were seen to evolve largely through established work groups into supervisory roles, or across work

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groups in the cause of “management development” towards the most senior corporate positions. Smaller companies were largely left out of the above picture. Large corporations, it was argued, could tolerate market uncertainty, absorb technological change, control prices and consumer demand, access financial capital and plan for the future in ways that smaller companies could not match. Industries, and the planning that contributed to their evolution, were seen to be “in unabashed alliance with (corporate) size” (Galbraith, 1971: 31). This emphasis on the large corporation and its advantages persists in more recent ideas about strategic management (Ghoshal & Bartlett, 1997; Hamel & Prahalad, 1994) and human resource management (Cascio, 1998).

Figure. 1. Industry and careers: the traditional view.

Figure 2 presents a different view, proposing an alternative set of causeeffect relationships. It is a cyclical view that begins with the person’s career, and envisions successive consequences for the development of communities, companies and whole industries. We do not claim this different view is the way things always happen. However, we do claim it is the way things frequently happen, and with important consequences for both individuals and smaller companies, as well as for the larger outcomes of industry evolution and learning. Our starting point is the “boundaryless career”, a response to increasing evidence that careers do not typically conform to the company-centric approach previously described (Arthur & Rousseau, 1996). Most people change employers several times over the course of their careers. Moreover, the evidence is that most employment mobility comes at people’s own volition, and is stimulated by a desire for fresh learning (Arthur et al., 1999). The notion that people enact

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their careers across sequential employment opportunities (Weick, 1996) provides an alternative, and we submit a more helpful, point of departure. However, the enactment of careers does not necessarily imply an era of free agency, in the sense of people pursuing their self-interests regardless of the larger consequences. Rather, people enacting their own career futures have an increased need to engage in communion, that is in community-building. This involves the nurturing of connections and relationships in one’s own career that the traditional view of lifetime employment presumed the company would provide. As Weick (1996) argues, a person’s community attachments can span the discontinuities created by shifting employment boundaries. The same attachments can also enable the macro-organising and trust-building through which learning can occur. Thus “those who can integrate communion and agency should develop faster than those who can’t. They develop faster because they learn more”. (Weick, 1996: 47). As an outcome of people’s community investments, we can anticipate company effects through various channels (Maskell, 2001). One would be where established relationships among participants create the top management team behind the formation of a new company (Boeker, 1997). Another would be where workers’ shared affiliation with others as either industry or occupational specialists served to enhance a company’s internal routines (DeFillippi & Arthur, 1996). Other kinds of community attachments, such as those with family or with fellowalums from academic or other shared experiences, have also been described to have company effects (Parker, 2000). Communities formed around particular projects may have special significance, because of both the range of expertise they bring together and the enduring connections that can persist after project completion (Jones, 1996). Company effects may be particularly pronounced in geographically-confined industry clusters, such as the Silicon Valley, California, high technology cluster (e.g. Saxenian, 1994), the Italian tile and knitwear clusters (Piore & Sabel, 1984), the Oxfordshire, UK automobile racing cluster (Pinch & Henry, 1999), or the Boston, Massachusetts financial services cluster (Kanter, 1995: Chapter 8). Such clusters can underlie and facilitate the local movement of both people and knowledge across company boundaries (Maskell, 2001). As William Hewlett, co-founder of Hewlett-Packard, once said “If you want to succeed here (in Silicon Valley) you need to be willing to do three things: change jobs often, talk to your competitors, and take risks — even if it means failing.” (Saxenian, 1996). In an industry cluster, the company becomes a participant in a larger learning system, consistent with Porter’s (1990) and various economic geographers’ conception of regional competitive advantage. Industry clusters allow the acceleration of knowledge flows across connections between companies. The

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companies serve to both receive and store knowledge in a larger industry-wide system. This arrangement increases a company’s access to new knowledge, which would otherwise be limited by the tightness of the company’s boundaries, and the associated predisposition to knowledge hoarding. Accordingly, the firm may be seen primarily as fulfilling a distributive function (for knowledge) rather than a production function (Boisot, 2000).

Figure. 2. Industry and careers: an alternative view.

The previous Figure 1 represented four different sets of actors and groups of actors (individual, community, company and industry) that were traditionally conceived as distinct levels in a vertical hierarchy. By contrast, Figure 2 does not deny a place for hierarchy, but sees it in a less rigid way. In doing so, it incorporates the more adaptive characteristics of hierarchies associated with complex systems (Cilliers, 2001). For example, the four parts of the figure have a high level of interpenetration (a career actor may also be a company owner and an industry association representative) and are constantly transformed (existing industry arrangements may inspire creative career behaviour and the diffusion of new ideas through communal work activities). These characteristics are rarely associated with the more traditional hierarchical views shown in Figure 1.

The Example of the Film-Making Industry The independent film-making industry, which appears to have outshone the old (large corporation) production system, suggests itself as a triumph of Figure 2 over Figure 1 thinking. The emergent industry logic begins with the career behaviour of participant workers. Typically, producers, directors, screenwriters and others generate the ideas from which new film-making projects are born.

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Interpersonal networks built through previous collaborations provide the mechanism through which new film crews and temporary film-making companies are formed (Jones, 1996). The new film-making experience provides a shared learning opportunity for project members, and extends the community attachments among the various specialist groups through whom work gets done. The learning dissipates to the industry on project completion, to be drawn upon and extended as people are attracted to new opportunities (DeFillippi & Arthur, 1998). However, the conclusions about film-making and its applicability to other industries remain controversial. The counter-argument to the above suggests that the major “studios” of today, which still finance, distribute and lease production facilities for films, are simply externalising risk onto dependent, captive suppliers and subcontractors. Moreover, the industry seems prone to “hold-up” of a few successful “stars”, and the dissolution of personnel after a film’s completion interferes with the accumulation of company-specific competencies (Phelan & Lewin, 1999). The debate about the film-making industry emerges as a debate about perspective. If we start with traditional industrial organisational assumptions, we are likely to draw on arguments that conform to the influences depicted in Figure 1. However, if we start with an alternative set of assumptions, we are more likely to draw on arguments that relate to Figure 2. One way to develop the above debate might be to see it on different terms, and in particular on the terms suggested by complexity theory. Cilliers (1998: 119 –123) has recently suggested a series of characteristics of complex social systems. Such systems consist of “a large number of elements”, which for Cilliers means people not firms. Those elements have “fairly rich”, dynamic, patterns of interaction, which appears truer for the participants under the independent film-making model than under the studio-based model. Systems are also open to other systems, and operate “far from (the kind of) equilibrium” that the old studio system appeared to seek. Moreover, systems function even though their individual elements (people) remain “ignorant of the behaviour of the whole system in which they are embedded”. Firms can come and go in film-making, while a healthy industry endures. Cilliers’ views concur with those of other complexity theory writers who argue that adaptive capability is more important for survival than efficiency and that adaptive capability stems from self-organising within networks. Diversity at the individual level (microdiversity and exploratory non-average behaviour) is fundamental to evolutionary change of a complex system (Allen, 2001). Selforganising occurs among diverse elements (Cilliers, 2001), but the degree of diversity also influences self-organising capacity. Too little diversity implies limited interaction and little new knowledge or learning (Boisot, 1999). Too much diversity implies too great a cognitive distance between players and results in a loss of shared meaning (Maskell, 2001).

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In sum, self-organising within independent film-making stems from the ability of nodes (people) within industry networks to rapidly come together, separate and reform in different permutations (film-making projects) according to need, while maintaining long-term relationships throughout the network. The example reflects a number of the features of complex systems and suggests that independent film-making may be better explained by complexity theory than by traditional company-centric approaches. It invites a question about the relevance of the film-making example to other industries, and a related question about how we might think about careers to explore that relevance further.

Careers as Three “Ways of Knowing” We turn now to a brief description of people’s career behaviour, and their investments in three interdependent “ways of knowing” (DeFillippi & Arthur, 1996). We do so to extend the argument on how career behaviour may be linked to the cyclical view of career to industry effects previously proposed, and to lead towards a more generalised argument about the processes involved. The first way of knowing is called knowing-why, and addresses the question of why we perform the kind of work we do. In the film-making industry, this might reflect a willingness to accept the inconvenience of irregular hours and shifting work locations, as well as the uncertainty about long-term employment. As the widespread literature on careers affirms, much of a person’s knowingwhy stems from the combination of the overlapping identity, values, temperament, interests and motivation he or she brings to the workplace. The second way of knowing is called knowing-how, and addresses the question of how — that is, with what skills and expertise — we go about our work. In the film-making industry, this might involve the particular experience a camera operator or set designer brings to the film-shooting activity. This way of knowing covers the combination of formal and on-the-job learning we bring to our work, and includes tacit knowledge, namely that which we know but cannot tell, such as in Polanyi’s (1967) popular examples of being able to ride a bike or to swim. The third way of knowing is called knowing-whom, and addresses the question of with whom we work. In the film-making industry, this would involve the trust and reputation earned from previous film-making episodes, as well as new relationships being developed in a present endeavor. This way of knowing spans the range of relationships we hold within and beyond the workplace. These cover such groups as work colleagues, supervisors, external contacts, mentors, family, friends and fellow-alums from educational, military or other past experiences. The three ways of knowing also interact with each other. For example, a person’s (knowing-why) motivation to pass an examination in accounting may

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lead to affirmation of (knowing-how) competence in the field and subsequent (knowing-whom) socialisation with other accountants. Or, a discouraging piece of feedback from a (knowing-whom) manager at work may lead to a weaker level of (knowing-why) identification with the company and reduced efforts to learn new (knowing-how) skills on the company’s behalf. Our argument about learning stemming from the interplay of the three ways of knowing is similar to Gardner’s (1993) argument about the interplay of the principal factors that underlie individual creativity.

The Links to Collective Engagement The three ways of knowing may in turn be linked to a growing body of work on “communities of practice” (Brown & Duguid, 1991; Wenger, 1998), namely, the largely voluntary, social arrangements through which work gets done and learning takes place. Communities of practice engage people’s (knowing-why) motivation to support and readiness to identify with a spirit of joint enterprise. They also incorporate people’s (knowing-how) ways of performing and interacting at work into a shared repertoire, and draw on members’ (knowing-whom) social investments in each other in a pattern of mutual engagement (Wenger, 1998). More broadly, Mirvis (1997) argues that communities involve “the (knowingwhy) emotive experience of feeling close to others”, and (knowing-whom) interaction through “living at least some of your life with others” in pursuit of shared (knowing-how) obligations and commitments. The ways of knowing may also be related to what have been described to be the three principal arenas of a company’s “core competencies” (Hall, 1992). First is a company’s culture, which engages with the shared (knowing-why) beliefs and values of its members and their overall investment in its mission (Barney, 1986). Second is a company’s overall know-how, which draws on both the (knowing-how) explicit and tacit knowledge of its members, working alone or collectively, in order to perform the company’s work (Grant, 1996). Third is a company’s networks, of suppliers, customers, alliance partners, industry contacts and so on embedded in its members’ (knowing-whom) relationships (Powell, 1998). Finally, the same view of the career appears embedded in Porter’s (1990; 1998) views on industry clusters. Porter (1998: 82) asserts that these geographic concentrations of companies and institutions in the same industry field sustain a “major share of the economy” and “an overwhelming share” of trade that is “exported” to other clusters. He cites (Porter, 1998: 81) participants’ underlying (knowing-why) motivation to both collaborate and compete, the continuing learning that gets built from an existing pool of workers with “specialised (knowing-

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how) skills and experience”, and the (knowing-whom) interpersonal relationships and community ties that “foster trust and facilitate the flow of information”. The Silicon Valley high-technology region provides a prominent example of these kind of regional dynamics, fuelled by a larger “Valley culture” concerned with producing breakthrough engineering, and where leading firms, such as HewlettPackard, are explicit about the greater good of the industry and its engineers (Saxenian, 1996). Table 1 summarises the described links between career behaviour, as reflected through the three ways of knowing, and the ideas behind collective engagement that other authors describe. These ideas about collective engagement can be expected to overlap. People hearing William Hewlett’s exhortation to change jobs often in Silicon Valley may be attracted towards successive new communities of practice, and also host companies, in which their affiliation with the Valley’s technological ideals might be expressed. People engaged on inter-company collaboration may be attracted to possibilities for their host industry that their collaboration reveals. People practicing partisular specialisations may be drawn to find support and affirmation through occupational communities (Zabusky & Barley, 1996). In sum, people are likely to engage in collective engagement spanning all three of the forms described in Table 1.

Table 1. Careers (Defillippi & Arthur, 1996) Knowing-why Knowing-how Kowing-whom

The links from career investments to industry effects.

Communities (Wenger, 1998)

Company “Core Competencies” (Hall, 1992)

Industry Clusters (Porter, 1998)

Joint enterprise Shared repertoire Mutual engagement

Culture Know-how Networks

Motivation Learning Relationships

These ideas extend the links to complexity theory. In particular, they affirm the blurring of internal and external boundaries which complexity theory views as fundamental (e.g. Boisot, 2000; Cilliers, 2001). The three overlapping forms of collective engagement may also allow for the diversity within a network that can facilitate more effective knowledge flows (Allen, 2001). This seems particularly evident at the level of the host cluster, which — as we have already noted — offers a potentially superior context for knowledge acceleration (Boisot, 2000; Maskell, 2001). The three forms of collective engagement also suggest channels through which the rates of firm-level and industry-level co-evolution interact, and thereby modulate the pressures for change inside and outside the company (Arthur et al., 1999). The role of both people and collectives is also

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implicit in complexity-based views which see information as largely embedded in relationships, rather than simply in individual minds (e.g. Boisot, 2000; Cilliers, 2001). Our present argument is confined to activity within a specified industry cluster. However, the same kind of argument may be applied to inter-industry collaboration, as well as to the competitiveness of nations (Lundvall & Maskell, 2000). Also, the previous examples of careers within industries suggest more expansive community attachments stemming from overlapping career interests. One set of such interests already mentioned can involve occupational specialisation. Another can involve alumni links from shared educational or employment experiences, as with business school alums, who have a long-standing reputation for staying connected with fellow-graduates. The same can happen with former employees, where, for example, we have heard that alums from Apple Corporation are a more influential group in the high technology industry than present Apple employees. These community formation processes lend further support to the conception of industry development reflected in Figure 2. They also suggest that connections exist between geographic clusters as well.

Inter-Cluster Relationships The traditional argument behind industry clusters highlights the benefits of geographic concentration among firms, in contrast to more differentiated industry arrangements. Moreover, clusters have survived the proliferation of postal, telephone and other post-war communications advances, and local institutional structures are still seen to be necessary for industry success (Maskell, 2001). What is new, however, is the World Wide Web, and its potential for accelerated intercluster connection and knowledge transfer activities. In the last part of this article, we will introduce two examples of international intercluster development, one where the Web is starting to make a difference, and the other born within the Web environment. These examples are discussed in the context of recent thinking about complexity theory as it applies to management and organisations. Intercluster links are supported by Cilliers’ (2001: 6) notion that “parts of a system may exist in totally different spatial locations.” The role of the World Wide Web is also consistent with thinking about complex systems, whereby “(t)he connections between different components could be seen as virtual and, therefore, the system itself may exist in virtual space.” (Cilliers, 2001: 6). The first example is the New Zealand boat building industry, the second is the Linux computer operating system.

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New Zealand boat building New Zealand has a rich tradition linking its competitive sailing and boat building activities. Centred in Auckland, the “City of sails”, the boat building industry has long been a magnet for sailing enthusiasts seeking to indulge their (knowingwhy) passion through their work. Specialist companies — for example, in mastmaking, hull design and instrumentation — have sprung up around the (knowinghow) specialisation of their founders and workers. Boats ordered through any one company have been manufactured through (knowing-whom) collaboration among established industry players. Further (knowing-whom) connections with local users have provided early and persistent feedback spurring continuous improvement, and a shared sense of involvement, in the industry as a whole. The system has earned international prominence through New Zealand’s competitive boat racing achievements, not least through successive victories in the prestigious America’s Cup. The cluster’s emergence illustrates a number of ideas in complexity theory. It reflects a co-evolutionary process, as individuals have interacted and formed companies to take advantage of their particular skills and contributions (Allen, 2001; McKelvey, 2001). Cluster participants have also been both open and responsive to the environment, in supporting an increasingly successful New Zealand international yacht-racing presence. Participants have self-organised into what international comparison suggests as an effective, diverse and richly connected boat building cluster. In other words, the industry has found its own complementarities as a result of the microdiversity of its individual experts and their companies (Allen, 2001). Knowledge flows among cluster participants and between the cluster and its boat-racing collaborators have reflected a dynamic, innovation-centred process rather than any more structured or mechanistic arrangements. Cluster companies serve as nodes to communal knowledge-processing activities (Boisot, 2000), nurtured by both internal links to other companies and external links to occupational peers, competitive sailors and direct customers. As the profile of New Zealand boat building has grown, intercluster links have begun to evolve internationally. Out of these early international connections, a new “company” has been born, the New Zealand Marine Export Group (or “MAREX”). We use the term company loosely, but still within the spirit of our Figure 2, since MAREX is an industry association formed to promote export business for its member firms. MAREX has been particularly active in the “super yacht” industry, nurturing connections with yacht designers, niche manufacturers, marketing specialists and customers in the international arena. MAREX was instrumental, for example, in arranging for New Zealand to host a super-yacht race and exhibition in Auckland as a prelude to the last America’s Cup (Export

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News, 2000). The executive director’s career, as both an international yachtsman and businessman, has much in common with the careers of the community of boat builders MAREX is commissioned to support (Lindsay, 2000). The links between MAREX members and the international community are becoming more substantial, as communications involve, for example, sophisticated collaboration with a remote boat designer or continuing negotiation with a distant customer. As Maskell (2001) notes, the success of a cluster is “dependent on the ability of its firms to bridge the gap to bodies of knowledge residing elsewhere in order to ensure a substantial process of knowledge creation”. Increasingly, this ability is developed and maintained by Internet-based communications, through e-mail correspondence and websites, in what MAREX members see as a natural evolution of their earlier, more local, activities. Through its international intercluster links, the Auckland boat-building cluster is now part of a wider system, with other parts spatially separated (Cilliers, 2001). As both the sourcing and customisation of boats are moving increasingly into the international arena, MAREX, the company formed out of the shared career interests of New Zealand boat builders, is giving rise to a new round of industry evolution. This evolution, accelerated by the availability of the World Wide Web, completes the full cycle of career to industry evolution depicted in Figure 2. The Linux operating system In 1992, Finnish graduate student Linus Torvalds posted his “Linux” operating system — so called after the originator’s first name and the system’s “Unix” platform — to an Internet software newsgroup. Torvalds posted his source code as a disciple of the “open software” movement, whose shared (knowing-why) passion was to work (or “hack”) on programming challenges unconstrained by proprietary constraints. Soon after, he began to receive e-mails from Linux users containing “patches” (error corrections and improvements), stemming from the users’ (knowing-how) programming capabilities. He incorporated the best of these patches into subsequent Linux releases, which went out to a growing number of (knowing-whom) system adopters and testers. Soon Linux user groups began to sprout up around the world, and the Linux project became the nexus of a global community of open software developers, testers and marketers/distributors. This virtual community of regional sub-communities grew exponentially, affirming its participants’ career investments and bringing them further (knowing-whom) reputation as recognised contributors to and experts on the Linux system. The Linux open source community illustrates several ideas from complexity theory, as summarised by Cilliers (1998: 119 –123). Although Torvalds is a leader and figurehead, the Linux community has no organisational, or traditionally “nested”

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hierarchy (Cilliers, 2001). However, it does have a large number of elements (Linux contributors number over 40,000), which interact dynamically as the release of each new version of the Linux system precipitates a new round of nonlinear interactions among community participants. These interactions have a short range, insofar as the discourse is locally focused on specific programming challenges of the latest Linux operating system release. The community can be seen as a collection of subsections with various functions for which there exist hierarchies, which create frameworks of meaning (Cilliers, 2001) in the community. However, in accordance with Cilliers’ perspectives on hierarchy, the vitality of the Linux community lies in its ability to transform hierarchies as the context changes (Kuwabara, 2000). The community represents an open system — open to anyone who can understand the language of Linux source code. Conditions are far from equilibrium, in that the Linux system is always evolving in response to community member contributions. Each new release also repeats an evolutionary process of variation, selection and retention as community members offer many prospective patches, only some of which are selected for inclusion in the next operating system version. As a result of its evolutionary development, Linux has emerged as one of the most stable and crash-proof operating systems, which — along with its functionality, accessibility and attractiveness to programmers — has contributed to its commercial appeal. Consistent with our Figure 2, the Linux phenomenon has also created a wave of company start-ups that have utilised the free, nonproprietary Linux system to develop applications and services with a commercial value. In 1999 alone, Linux-based initial public offerings achieved market capitalisations of over one hundred billion dollars (Paulson, 2000). The entrepreneurs within these companies included both Linux development contributors and independent software writers exploiting the market opportunities that the Linux programmer community had made available. A particularly visible example is Red Hat, a distributor of shrink-wrapped versions of Linux and a publisher of Linux books, open source tools and technical support. It completed its initial public offering in 1999, and in less than two months achieved a market capitalisation of more than seven billion dollars (Raynovich, 1999). As this article goes to press, the market for high technology stocks has cooled, but the influence of Linux has continued — as most recently illustrated by IBM, which has committed one billion dollars for 2001 to make its entire product line, from PCs to mainframe, Linux-compatible (Economist, 2001). Red Hat provides an attractive employment setting for Linux community members that sustains their involvement in Linux-related development. Red Hat employment also provides tangible career benefits from the availability of free Linux code from other developers, and intangible benefits of loyalty and credibility

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from computer system manufacturers, corporate customers, distributors and more (Tapscott et al. 2000: 123). Moreover, the way Red Hat officials describe the relationship between their internal software developers and the open source Linux community is instructive. According to Red Hat’s Chief Operating Officer, Tim Buckley: “The last thing we want to do is start getting isolated from the (Linux) community, which we are accused of a bit, but only because we are getting bigger and have a reputation…(It) makes us want to double our efforts. We…give everything back to the community. (We) have three or four of the top (Linux) kernel developers on our payroll and they’re not developing Red Hat stuff — that’s just another sign that we’re trying to make sure the community and the kernel development remains solid.” (MacCormack & Herman, 1999: 11). In sum, the company’s careful nurturing of Linux workers’ place in their industry encourages them to take on new career investments, so completing and restarting the cycle that our Figure 2 depicts.

Conclusion: Careers and Complex Systems The underlying argument presented here may be summarised as follows. People are the underlying elements in social and economic organising. Careers reflect the way people enact their working lives, which typically involve journeys in personal learning across a range of successive employers. This point of departure suggests a cyclical view of industry evolution — which we have called Figure 2 — from career to community to company to industry effects. This view is in contrast to the still popular company-centric view. Industry clusters provide a particular opportunity for the rapid cycling and recycling of Figure 2 activities. The example of the independent film-making industry appears to reflect Figure 2, as well as to exhibit a range of features associated with complexity theory. Careers in film-making and elsewhere may be understood as involving three “ways of knowing” — knowing-why, knowing-how and knowing-whom — through which, for example, people’s motivation, skill development and work relationships interact with one another. We have argued that these ways of knowing underlie other authors’ interpretations of collective behaviour within community, company and industry clusters — that is within each of the collective arrangements reflected in Figure 2. We have also argued that these links to collective behaviour deepen the association drawn with complexity theory. Further examples introduced in this paper, concerning New Zealand boat building and the Linux operating system, appear similar to the film-making case in both the career behaviour exhibited and the unfolding industry consequences.

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These examples illustrate the recent influence of the World Wide Web in accelerating (New Zealand boat building) or facilitating (Linux) Figure 2 connections, and in particular in promoting intercluster activities. Both examples also affirm the links between Figure 2 and complexity theory. Cilliers (1998: 11) has argued that traditional analytic approaches have usually involved “splitting the structure of the system, and the meaning of that structure, into separate levels” much like the approach to industrial organising we have called Figure 1. It would be ironic if our attempts to apply complexity theory perpetuated the same approach, by grounding our interpretations at the “separate level” of the company or firm, rather than at the elemental level of the individual person. We submit that what we have called Figure 2 — with its persistent recycling among individual career, community, company and industry activities — offers a more helpful point of departure. However, given the characteristics of complexity theory, it is impossible to know the full extent of all the components and interactions involved (Allen, 2001; Cilliers, 2001). We therefore recognise that our model is inevitably part of a larger system, other parts of which have not been included in the considerations represented here. Acknowledgements We are indebted to Richard Hall and Peter Maskell for their supportive comments on an earlier draft of this paper. References Allen, P.M. (2001) A complex systems approach to learning in adaptive networks. International Journal of Innovation Management, 2(2), forthcoming Arthur, M.B., Inkson, K. & Pringle, J. M. (1999) The New Careers: Individual Action and Economic Change. London: Sage Barney, J.B. (1986) Organizational culture: can it be a source of sustained competitive advantage? Academy of Management Review, 11, 656–665 Boeker, W. (1997) Executive migration and strategic change: the effect of top management movement on product-market entry. Administrative Science Quarterly, 42(2), 213–236. Boisot, M. (2000) Knowledge, information and networks. Presentation to the workshop on “Organisational Networks as Distributed Systems of Knowledge.” University of Lecce, Italy, July 2–5 Brown, J.S. & Duguid, P. (1991) Organizational learning and communities of practice: toward a unified view of work, learning and innovation. Organization Science, 2(1), 40 –57 Cascio, W. F. (1998) Managing Human Resources: Productivity, Quality of Work Life, Profits. New York: Irwin/McGraw-Hill

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