Not Your Stepping Stone: Collaboration and the Dynamics of Industry Evolution in Biotechnology
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Not Your Stepping Stone: Collaboration and the Dynamics of Industry Evolution in BiotechnologyKenneth Koput Walter W. Powell University of Arizona Stanford University Rough Draft for Organization Science Winter Conference February, 2000 INTRODUCTION Contemporary research on organizations and industrial performance is replete with reports of a marked upsurge in various forms of interorganizational collaboration, including research consortia, joint ventures, strategic alliances, extensive subcontracting and/or outsourcing of key functions. Astute observers of these developments, such as Richard Rosenbloom and William Spencer (1996), suggest that industrial competition today resembles less a horse race and more a rugby match in which players frequently change uniforms. A recent National Research Council analysis of trends in industrial research and development (R&D) reports that the innovation process has undergone a significant transformation over the past decade (Merrill and Cooper, 1999). This transformation appears to be both “substantial” in magnitude and consequential to economic performance, both positively and negatively (p. 104). The four components of this reorienting of R&D are: 1.) A shift in the industries and sectors that dominate R&D towards new emerging technologies and nonmanufacturing industries; 2.) A change in the time horizons of R&D, with industry focusing more on shorter-term development and relying more on universities for basic research; 3.) A change in the organizational structure of R&D, with greater decentralization of research activities and increased reliance on both outsourcing and collaboration among firms, universities, and government laboratories; and 4.) Changes in the location of R&D, with successful research increasingly dependent on geographic proximity to clusters of related organizations. A companion National Research Council survey of eleven industries, purposefully diverse in character and technology but all resurgent in the 1990s, notes that common to each industry is: 1.) Increased reliance on such external sources of R&D as universities, consortia, and government laboratories; 2.) Greater collaboration with domestic and foreign competitors, as well as customers, in the development of new products and processes (Mowery, 1999: 7). National Science Foundation data show a marked increase in the number of international alliances between U.S. and Western European countries between 1980 and 1994; but by the mid-1990’s, the formation rates for intranational alliances linking U.S. firms with their domestic competitors outpace international linkages (National Science Foundation, 1998). Similarly, there is now ample research showing the growing links between U.S. firms and universities (Cohen et al 1994), a greater involvement by firms and government labs in research joint ventures (Link, 1996; 1999), and a much greater foreign presence in U.S. R&D through collaboration with U.S. universities (NSF, 1998). In the realm of science, Hicks and Katz (1996) find that research papers are more and more likely to be co-authored and involve authors with multiple institutional affiliations spanning the public and private sectors. In short, as Mowery (1999: 9) observes, “the diversity of institutional actors and relationships in the industrial innovation process has increased considerably, even as the investments by U.S. firms now appear to focus on shorter time horizons.” Complex networks of firms, universities, and government labs now play a critical role in many industries, and especially so in a number of newer industries such as computers, semiconductors, pharmaceuticals and biotechnology (Powell and Owen-Smith, 1998; Mowery and Nelson, 1999). Divergent Accounts Taken together, these developments in industry and science suggest a significant restructuring of organizations, work arrangements and the organization of innovation. There is, however, considerable debate about both the causes and consequences of this restructuring, and much scholarly and popular discussion about the purported new economy. We cannot resolve these large issues here, rather we focus on one aspect: the role of the small science-based startup firm. The startup firm, whether as a spinoff out of existing companies or universities or as a stand-alone entity, has played a greater role in the U.S. economy over the past two decades. Moreover, these smaller units appear to operate according to a different organizing logic, with extensive linkages to other organizations and partnerships with outside parties for key business functions. But beyond these observations, there is disagreement about both the contributions and the developmental path of smaller firms. While small firms may be bountiful, some dismiss them as trivial and controlled by larger firms. Harrison (1994) argues that we are witnessing the growth of decentralized power, where there is growing concentration of corporate power but without centralization. He dubs this phenomena the “lean and mean” strategy, and provides anecdotal data drawn selectively from a few firms such as Nike to portray an intensive spider’s-web world of outsourcing, contract labor, demanding work practices, but growing control at the center where corporate power is lodged. In his view, small firms are largely dependent on corporate giants. Another perspective on recent developments is offered by ecologist Glenn Carroll (1985; 1994; Carroll and Hannan, 1995: 215-21), who suggests a resource-partitioning process that involves the simultaneous expansion in the number of small firms and a contraction in number but a concentration in size of large firms. Carroll (1994) notes that there has been a proliferation of smaller organizational units, with the average size of a firm declining by roughly 30 – 40% over the period 1960-1989. Some of this transformation is due to compositional shifts in the U.S. economy, reflected in service sector growth and manufacturing decline. But Carroll and his colleagues offer a resource-based argument that applies especially to fields in which production or marketing activities exhibit economies of scale and price competition. As competition for scale economies increases, only a few generalist organizations survive, and they do so by offering fairly homogeneous products or services to a mass market audience. But the interesting twist is that the concentration of generalists on the mass market opens small pockets of resources on the periphery of the market, where smaller specialist firms emerge and thrive. Thus, in the words of Carroll and Hannan (1995: 217) “increasing market concentration enhances the life chances of specialist organizations.” Such a process has been observed in the newspaper, beer, wine, microprocessor, music, and book industries. In this account, small firms proliferate by catering to specialized tastes An alternative view is found in recent studies of the innovation process, cited above. Rather than dependency or specialism, these analysts suggest a refashioning of the division of labor in which smaller firms, and the linkages between them and centers of innovative activity play a much more prominent role, especially in research-intensive fields. A somewhat discordant chorus of voices are found in this camp, with some suggesting that networks represent an alternative means for governing economic exchange (Powell, 1990), while others point to a profound blurring of organizational boundaries and a remaking of the production process (Sobel, 1991), and still others contending that new information technologies allow more disaggregated, and flexible means for organizing production and delivering services (Morton, 1991; Brynjolfsson et al, 1994; Shapiro and Varian, 1999). Older, Bigger, Wiser? We want to add some empirical flesh to these discussions of the structure of the firm, and to debates over the relevant role of small firms and the growing salience of alliances and various types of collaborations. We have the advantage of having good longitudinal data on firm arrangements over the period 1988-1999. We have the disadvantage that the data are based on only one industry --biotechnology. Nevertheless, the commercial field of the life sciences is purportedly one of the key components of the new economy, so it is a strategic site for analysis. Moreover, the data we describe below are based on formal contractual agreements and not informal ties, handshake deals, or social embedding, hence they afford a strict test of whether horizontally based external relationships are a critical feature of the contemporary science-based firm.1 One way to sift through the divergent arguments concerning the structure of contemporary organizations is to examine a sample of firms in the same field over a sufficient time period that changes at the firm-level and field-level, as well transformations in the larger economy, can be observed. Viewed through the lens of more than a decade’s changes, one can examine patterns of growth for individual firms, changes in the nature and number of interorganizational relationships, and industry evolution. To account for changes in the repertoire of organizational practices, we analyze whether there is persistence, decline, or expansion in the use of external collaborations. The crux of the argument for changes in strategy and structure is that interorganizational networks are an increasingly fundamental cornerstone that enables firms to both gain and hold competitive advantage, rather than a transitional stage. Thus, we attempt to measure how organizational strategy and structure have evolved in one industry. We assess the consequences of organizational growth, aging, and success for the types of collaborative arrangements that firms in the commercial field of biotechnology employ. Each process -- growth in size, the gaining of experience, and the successful launching of a new product -- presents a challenge to a firm in terms of how it chooses to organize. Growth brings problems of communication and coordination as the number of employees grows. As an organization ages, its stock of knowledge increases and its routines for organizing core tasks become more well developed. With a successful product, an organization faces the challenge of reproducing its initial success but now has new resources to deploy. Viewed differently, growth, aging and success are mileposts for organizations, and we can look at these road markers and see whether the mix of arrangements that were used to reach a particular milepost are continued, disbanded, or diversified as movement toward the next marker occurs. In our earlier work on biotech firms, which covered a much shorter time period than the analyses presented here, we showed that centrality in the industry network heightened a firm’s reputation and generated access to resources. Firms so positioned attracted new employees, participated in more new ventures, and developed deeper experience at collaborating with other parties. Put colloquially, a firm grew by becoming a player; it did not become a player by growing. Growth and financial success resulted from centrality in industry networks (Powell, Koput, Smith-Doerr, 1996; Powell, Koput, Smith-Doerr, Owen-Smith, 1999). We begin these analyses by asking how achieving growth influences subsequent behavior. As firms add employees and expand their operations internally, they face a series of choices. Organizations could opt to pursue more activities internally and fewer externally as they increase internal capacity. Or they could use additional staff to assist in expanding the number of outside collaborations. Moreover, growth could result in increased differentiation internally (following Blau’s [1970] classic arguments about growth leading to an expansion of roles and structures), or promote a diversification externally into collaborations for different types of activities. Finally, added internal capacity could lead to more tangential external relations, or could allow for deeper and/or more intensive external linkages. Stated formally, we test to see whether: As firms grow in size, they deepen their portfolio of collaborations; expand their number of external ties; diversify the types of collaborative activities they engage in; and engage in more complex arrangements. (Hypothesis 1). The effects of age have been well studied in the organizations literature. Building on Stinchcombe’s (1965) key insights, there has been a great deal of attention paid to the liability of newness (Hannan and Freeman, 1989: 245-70). Younger firms need to build credibility with consumers, suppliers, creditors and the like and overcome initial reservations toward a new entity. Given these obstacles, it is not surprising that startup companies turn to venture capital firms, law firms, and established companies for assistance, as well as rely on universities and government laboratories for key technologies. Moreover, many startup science-based firms are spin-offs from universities and, less frequently, government laboratories and established firms. Consequently, survival often hinges on location in a supportive network in order to overcome initial questions about credibility and reliability. As a small firm ages, it faces a choice. The company can become less reliant on external parties. Or as the firm matures and expands its activities downstream from its initial research focus into product development, production, and sales, it may opt to become involved with more outside partners as it takes on new tasks. More pivotally, firms may engage with a wider span of partners for key activities, selecting and being selected by a heterogeneous group of collaborators for critical functions such as R&D, production, or sales. Put simply, as companies age, they make decisions about both the volume and the span of activities done internally or externally. Hence we test to see whether: As firms grow older, they become involved in a wider variety of external activities, with a more heterogeneous group of partners for each activity. (Hypothesis 2). In many emerging industries with a strong science base, companies spend much of their early years burning up investors’ money on costly initial research. External support is the lifeblood during this phase. As the research program develops and moves into application and testing, the prospect of a new product looms larger. As the product cycle unfolds, companies have differential needs, and the nature of the reliance on others shifts depending on the stage of development. For the successful firm, products are eventually released and sales generated. Some firms plow revenues back into R&D, others generate profits to repay investors who have been patient during the development stages. We have argued that companies in knowledge-intensive businesses are involved in learning races, that is, in a cycle of learning in which initial success generates the resources that allow advancement to the next level (Powell et al, 1999). The key question is whether that initial success triggers changes in current organizational arrangements or “restarts” the process again in pursuit of new avenues of research. Thus the fruits of initial success present a branching point for many young companies. The founders could choose to “take the money and run,” cashing out by selling the company or agreeing to a merger. The founders could take the money and attempt to build a vertically integrated firm, with the full range of organizational functions, and with key tasks performed only internally. The cycles of learning argument that we have posited suggests that organizations respond to the initial success of sales and/or profits by expanding their absorptive capacity (Cohen and Levinthal, 1989; 1990), that is, by enhancing BOTH their ability to generate new products internally as well as their portfolio of external research affiliations. An organization’s absorptive capacity allows it to make sense of news generated elsewhere and to make news on its own (Nelson, 1994). Seen in this light, we assess whether, as firms reach an initial “finish” line, they reinvest in the process of research exploration, choose to pursue research internally, or choose to exit. More formally stated, we test the argument that: As companies first reach an initial plateau of earnings, they subsequently engage in more external R&D collaborations. (Hypothesis 3). Researchers from several disciplines have stressed the importance of research prowess as an admission ticket to information networks in science-based fields (Mowery and Rosenberg, 1989; Arora and Gambardella, 1994; Powell et al, 1996). A persistent finding from a diverse set of empirical studies is that R&D intensity and the level of technological sophistication are positively correlated with the number and intensity of strategic alliances (C. Freeman, 1991; Hagedoorn, 1995). More generally, there is widespread agreement that in technologically advanced sectors, the locus of innovation is often found in networks of relationships (Powell et al, 1996) or sectoral innovation systems (Mowery and Nelson, 1999). But we do not have a clear sense of which actors bind these innovation networks together, providing them with coherent agendas. Indeed, one would expect substantial variation in network structure based on differences in technology, the supportive institutional infrastructure, public policy, and the endowments of large and small participants. We cannot provide a complete picture of this complex process here. Rather we are interested in the role and evolution of the small science-based firm. Consider the following range of possible roles performed by startups. Small firms may provide the ideas that jumpstart the innovation process. Because these firms are both closer to the underlying basic science and have a deeper understanding of the technology, they continue to exert influence as the ideas are translated into commercial products. In this scenario, the small firm is able to use its knowledge to orchestrate production through an innovation network. In contrast, small firms could serve as the sources of new ideas or novel products, but, due to their small scale they are unable to develop, produce, or market the final product. Under this scenario, the small firm would remain a specialist research boutique that generates ideas, while larger and more established firms would pick off the most promising leads and thus reap the lion’s share of the benefits from innovation. Alternatively, an inner circle of key participants may dominate the innovation network, and these centrally positioned actors are able to reap greater rewards from their strategic location in the chain of production. This inner circle might well compromise an elite mix of large and small firms, research institutes, financiers, and providers of other key resources that play a disproportionally large role. Finally, industrial structure might be highly fluid, with different organizations taking on more central roles at different times and in different places, as well as for different stages of the product life cycle. Under this latter scenario, there is neither an inner circle of participants, nor a boutique or orchestrator role for small firms, but a changing division of labor in which industrial leadership varies according to capability and resource availability. We assess the prevalence of these divergent accounts of the divisions of labor by testing the following arguments: Small firms play an active role in each stage of product development rather than solely in research and development. (Hypothesis 4A). There is a heterogeneous group of participants for each stage of product development, rather than an elite cadre that dominates all stages. (Hypothesis 4B). Small firms play a linking role, hence they are active in all stages of product development, while other participants play more specialized roles. (Hypothesis 4C). Background on Industry Origins The science underlying the field of biotechnology had its origins in university laboratories. The scientific discoveries that sparked the field occurred in the early 1970s. These promising discoveries were initially exploited by a handful of science-based start-up firms founded in the mid to late 1970s. The year 1980 marked a sea change, with the U.S. Supreme Court ruling in the Diamond v. Chakrabaty case that genetically engineered life forms were patentable. Congress passed the Bayh-Dole Act in the same year, which allowed universities, nonprofit research institutes, and small businesses to retain the intellectual property rights to discoveries funded by federal research grants. And Genentech, which along with Cetus was then the most visible biotech company, had its initial public offering, drawing great interest on Wall Street, with a single day stock price run up exceeding any previous one-day jump. Over the next two decades, hundreds of biotech firms (BFs) have been founded, mostly in the United States but more recently in Canada, Australia, Britain, and Europe. The initial breakthroughs – most notably Herbert Boyer and Stanley Cohen’s discovery of recombinant DNA methods and George Köhler and Cesar Milstein’s cell fusion technology that creates monoclonal antibodies – drew primarily on molecular biology and immunology. The early discoveries were so path-breaking that they had a kind of natural excludability, that is, without interaction with the university scientists who were involved in the research, the knowledge was difficult to transfer (Zucker, Darby and Brewer, 1994). But what was considered a radical innovation two decades ago has changed considerably as the science diffused rapidly. Genetic engineering, monoclonal antibodies, polymerase chain reaction amplification, and gene sequencing are now a standard part of the toolkit of microbiology graduate students. To stay on top of the field, participants have to be at the forefront of knowledge-seeking and technology development. Moreover, many new areas of science have become inextricably involved in the biotech enterprise, ranging from genetics, biochemistry, cell biology, general medicine, and computer science, to even physics and optical sciences. The commercial potential of biotechnology appealed to many scientists and entrepreneurs even in its embryonic stage. In the early years, the principal efforts were directed at making existing proteins in new ways, then new methods were developed to make new proteins, and today the race is on to design entirely new medicines. The firms that translated the science into feasible technologies and new medical products faced a host of challenges. Alongside the usual difficulties facing start-up firms, biotech firms needed huge amounts of capital to fund costly research, assistance in managing themselves and in conducting clinical trials, and eventually experience with the regulatory approval process, manufacturing, marketing, distribution, and sales. In time, established pharmaceutical firms were also attracted to the field, initially allying with BFs in research partnerships and in providing a set of organizational capabilities that BFs were lacking. Eventually, the considerable promise of biotechnology led nearly every established pharmaceutical corporation to develop, to varying degrees of success, both in-house capacity in the new science and a wide portfolio of collaborations with BFs (Arora and Gambardella 1990; Gambardella 1995). Thus, the field is not only multi-disciplinary, it is multi-institutional as well. In addition to research universities and both start-up and established firms, government agencies, nonprofit research institutes, and leading hospitals have played key roles in conducting and funding research, while venture capitalists and law firms have played essential parts as talent scouts, advisors, consultants, and financiers (Gilson and Black 1996; Lerner and Merges 1998; Powell and Owen-Smith 1998). Biotechnology emerged at a time, in the 1970s and 1980s, when a dense transactional infrastructure for relational contracting was being developed, especially in Silicon Valley (Suchman 1994; Powell 1996). This institutional infrastructure of venture capital firms, law firms, and technology talent scouts greatly facilitates interorganizational collaboration. Taking all these elements into account, two factors are highly salient. One, all the necessary skills and organizational capabilities needed to compete in biotechnology are not readily found under a single roof (Powell and Brantley 1992). Two, in such fields such as biotech, where knowledge is advancing rapidly and the sources of knowledge are widely dispersed, organizations enter into an array of alliances to gain access to different competencies and knowledge. Progress in developing the technology goes hand-in-hand with the evolution of the industry and its supporting institutions. Following Nelson (1994), we argue that the science, the organizations, and the associated institutional practices are co-evolving. Universities are more attentive to the commercial development of research, BFs are active participants in basic science inquiry, and pharmaceuticals are much more involved with BFs and universities. Download 154.14 Kb. Share with your friends:
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