University research and public-private interaction
DominiqueForay,* FrancescoLissoni†‡
May 2009
*Chaire en Economie et Management de l'Innovation, Ecole Polytechnique Fédérale de Lausanne
† DIMI, Università degli studi di Brescia
‡ KITeS, Università ‘L.Bocconi’, Milano
Prepared for: Hall B.H., Rosenberg N. (eds)Handbook of Economics of Technical Change
Table of Contents
1.Introduction
2.Government laboratories and research universities: two different public research organizations
3.A conceptual approach to the problem of managing complementarities between universities’ and industry’s research
3.1Economic opportunities
3.2Institutional obstacles
3.3Structural factors for managing complementarities
4.The empirical literature: issues and results
4.1From university to industry: the quest for “relevant knowledge”
4.2Universities in the market place
4.3From industry to university: individual and system level interactions
4.4Bridging institutions
5.Policy issues and open questions
5.1Academics in the market place: overcoming the dilemmas
5.2Manipulating incentives: from a “by-product economy” to a “joint product economy”
5.3Directions for future research
1.Introduction
The university is among the oldest institutions active today in allthe developed countries.Over the course of its long history it has managed not only to adapt to many external shocks, but also to expand considerably, both in size and diversity of activities(Ben-David, 1977). In present times, its role is to couple basic research and teaching – two activities of wide relevance in the economy to the extent that they provide for the generation of externalities in the form of human capital and basic knowledge, both of which have the characteristics of quasi public goods (Clark, 1993).[1]As countries progressively shift towards knowledge-based economies,there is a positive supply response on the part of universities to the increasing demand for basic knowledge and highly skilled people. In this respect, universities play a critical, but indirect role in the productivity growth and expansion of industry and services.
Universities also contribute directly to innovation, by providingindustry and services with technical solutions or devices, or by getting involved in applied research activities. Such a role is in accordance with a view of the university as a “permeable institution” (Lécuyer, 1998), which allocates efforts and attention to problem-solving activities that have immediate relevance for business firms (most often the national or local ones). Such a view is not at all new, as it dates back at least to the nineteenth century, sometimes in co-existence, sometimes in competition, with the emphasis on basic research and teaching (Rothblatt and Wittrock, 1993). More recently, however, governments and large sections of the public opinion have placed more emphasis on demands that universities fulfil this type of task by commercializing their own academic inventions. This requires them to get involved into the creation and management of intellectual property rights, and even into entrepreneurial activities such as the foundation of new firms (Slaughter and Leslie, 1997; Martin, 2003, Yusuf and Nabeshima, 2007).A major witness of this change is the wave of legislation aimed at encouraging universities to take patents and license them under profitable conditions, started in the US with the Bayh-Dole Act of 1980 and continued elsewhere with many imitations of this Act and, in several European countries, with the abolition of the “professor’s privilege” typical of the German academic model.[2]The increase ofdirect government funding of research projects (as opposed to general university fundsor “block grants”), many of which are explicitly targeted at technology areas, can also be interpreted as the result of this new attitude.[3]
This change of perspective has gone hand in hand with the increasing attention paid by industry to universities’ research, as part of a general strategy to move away from a “vertical” model of R&D to a “network strategy” of innovation, based upon the exploitation of external knowledge resources.[4]Since the 1980s, industrial funding of academic science in OECD countries has grown considerably both in real terms and as a percentage of GDP.Public funding has also grown in real terms, but it has not kept up with the growth both of GDP and of industrial funding, so that in 2003 the share of government-funded academic research was down to 72%, from over 80% in 1981. In the meantime, the share of industrial funding had doubled, from 3% to 6%; and universities’ self-financing share has gone up from 13% to 16%, thanks largely to the expansion of new entrepreneurial activities both in the field of education and in technology commercialization (Vincent-Lancrin, 2006). Although governments are still eager to pay most of the bill for academic science, these are further signals that those same governments increasingly expect universities to look elsewhere for resources, and in particular to research partnerships with industry and to markets for technologies.
At the present time, the most research-oriented of modern universities look quite like the “multi-versity” envisaged by Clark Kerr, theprescient president of the University of Californiaof the 1960s: a “knowledge factory … to which policy wonks turn for expertise, industrialists turn for research, government agencies turn for funding proposals, and donors turn for leveraging their philanthropy into the greatest impact”(Wagner, 2007); and, one may wish to add, university administrators turn for self-financing.[5]
All of these stakeholders combine to mould the fundamental incentivestructures of academic scientists, setting the balance between the marginal returns respectively associated to basic research, education and involvement in commercialization. This evolution both generates opportunities and entails the risk to damage to the overall universities' contribution to scientific advancement and human well being.
In particular, fears have been expressed that universities will be forced to limit their production of basic research and teaching, the quasi-public goods thatmarket-oriented organizations often fail to provide. Such a risk appears paradoxical, at a time when the provision of such public goods is of strategic importance as countries progressively shift towards knowledge-based economies.
In short, two types of interaction between universities and industryseem to co-exist, bothof which aim at realizing effectively the potential for complementarities between the two in the domain of innovation. Interactions can be of the traditional type, covering networks of people, collaborative funding of research programs, and informal contacts. The recruitment of graduates in the business sector is part of this concept and is often the strongest channel of interaction between the two worlds. The other type of interaction is that from universities better exploiting their inventions – through professional management of intellectual property, opening technology licensing offices, and launching their own spin-offs and start ups.
It is clearly difficult to know whether this second, emerging model of university-industry interactionwill contribute to scientific advancement and long term economic growthmore or less than those that preceded it. It is also hard to tell how generalized and effective has been the transition to the new model in countries other than the US, which have been the most important institutional laboratory for academic life since World War II, and where the new model of the university has made the most inroads.However, both economic theory and applied studies have already produced enough material for a first assessment, as well as significant guidelines for future researchdirections.
In what follows, we place the role of universities in context, and show that their centrality within the public research systems has been increasing over time, even in countries which traditionally entrusted public research to different institutions (section 2). We then develop a general formulation of the opportunities and problems generated by the interaction between university and industry (section 3). In section 4 we examine the main issues explored by the growing empirical literature on the economics of university-industry technology transfer. Finally, in section 5we discuss policy implications and directions for future research.
2.Government laboratories and research universities: two different public research organizations
Knowledge – defined as a quasi public good – requires special socioeconomic institutions upon which society can rely to produce and allocate it in an efficient manner. Private markets (involving intellectual property rights as well as other mechanisms to help private agents to capture economic rents) and the public sector form the two main institutions which weneed tostudyin order to design an empirically and analytically informed knowledge policy. This chapter focuses on their interaction, but first we discuss the public sector institutions in a bit more detail.
In the public sector, there are clearly (at least at the conceptual level) two different types of institutions (Dasgupta, 1988): the first consists in the government engaging itself directly in the production of knowledge; the second consists in private agents undertaking the research, who in turn are subsidized for their effort by the public purse. While the first arrangement characterizes the so-called government research laboratories (GRLs), the second one characterizes research universities (RUs).[6] The RU solution is a decentralized mechanism, in which production decisions are independently taken by members of a self-regulating profession (scientists), and whose work is subsidized by the government, while the GRL arrangement is closer to a kind of “command mode of planning,” such that the decision of what to produce and how much to produce is made by the government.GRLscomprise both the large institutes dedicated to fundamental research activities (such as Max Planck in Germany or CNRS inFrance) and a number of mission-oriented organizations dedicated to the advancement of specific scientific fields and technologies, often under direct ministerial supervision (such as nationalspace agencies, institutes of health, or atomic energy organizations). Networks of laboratories for applied research and development, most often in support of small and medium enterprises (SMEs) can also be regarded as GRLs, a classical example being the Fraunhofer Gesellschaft in Germany (Beise and Stahl, 1999; Harding, 2001). While several GRLshost laboratories that often operate according to a logic and under provisions which are closer to that of RUs (sothat their scientists regard themselves as part of the academic community), most of them pursue more strictly defined objectives, even when they rely on academic scientists’ services (such as contract research or consultancy).[7]
GRLs and RUs form what is commonly known as public sector research, and are related by exchanges of knowledge, personnel, and finances (large GRLs are often in charge of administering public funds directed also at universities, and recruit scientists in the same labour market of RUs). Yet it is important to maintain the distinction between the two forms of public research because the economic incentives and resources allocation mechanisms are fundamentally different. In the RU system, individuals are free to pursue research targets of their own choice (although the system of grants often selects a few main research areas). In return for financing, individuals and institutions must provide educational services, such as teaching and supervision of qualificationinto professional associations (such as those of medical doctors, lawyers, and engineers). Modern scientists receive a fixed salary for their teaching and examination tasks, in addition to other rewards (e.g. promotions and increased reputation) for successful research.[8] By contrast, in the GRL system research is organized by the state in relation to targeted objectives. Individuals are not as “free” as in RUs, due to commitments to follow certain research directions. It follows that they do not have to provide as many other services, such as lecturing, in order to create a fair balance of advantages and constraints.
Both GRLs and RUs have significant shortcomings as methods of resource allocation. In the RU system, mechanisms for the allocation of research grants to individuals and teams exhibit hysteresis effects (reputation increases the probability of receiving a new grant which, in turn, has the effect of increasing reputation even more). This may weaken the system’s capacity to identify and maintain the “best” researchers. RU systems face tremendous difficulties in generating (in a decentralized way) new disciplines or research activities at the interstices of existing fields.In the GRL system, problems of asymmetric information make it difficult for research administrators to manage the scientists’ activity. Government failures (instead of market failures) may occur. In addition, large basic-science- and mission-oriented GRLs projects are high risk ventures, with a few large bets are placed on a small number of races. These ventures may also create distortions in competition, to the extent that they favour selected industries and the “national champions” therein.
These two arrangements have specific functionalities and are therefore complementary. These differences are reflected in the way knowledge flows to industry and society are managed in the two systems. While maximizing knowledge externalities is the raison d’être of the RU system, this is not the case in the GRL system. Spillovers from the latter can be either massive or very weak, depending on the administrators’ intentions; in any case, they cannot be consideredthe key rationale for the public funding of GRLs.
Historically, most countries that are now at the technological frontier have experienced a slow shift from a system involving government laboratories and teaching universities as the main “knowledge institutions” to a system characterized by the research centrality of RUs. There are of course variations across countries (for example, in France the GRL role as a R&D performer has been maintained at high level), but the direction of the trend is clear across most OECD countries (Figure 1).[9]
FIGURE 1 ABOUT HERE
Heavy reliance on GRLs can be seen as a legacy of the past: it was appropriate at a certain stage of economic development, when the main challenge for Western countries was to build a science and technology infrastructure, and the fastest way to do so was to create these “mission-oriented” institutions.However, as those countries approach the technological frontier (i.e. are no longer catching up and imitativebut rather are leading the international innovation process[10]), the need for more resources in RUs is obvious. RUs can generate externalities in the form of both human capital and basic research that have the status of “joint products” (giving rise therefore to economies of scope and internal spillovers) while GRLs break the intimate relations between research and high education and only provide a small fraction of the total amount of positive externalities that RUs are able to provide. As explained by Zucker and Darby (1998, p.62):
“the idea of research institutes sounds very attractive, particularly in a small country that sees them as a vehicle to achieve a critical mass by concentrating the nation’s best scientists in one place. In fact, we ourselves would like to have our research well funded until retirement and the opportunity to build a more permanent research group without the need to educate and train successive generations of graduate students and post doctoral fellows. Despite the personal attractions, we can also see how that situation might cool the entrepreneurial spirit as well as our impact on the most important objective of any knowledge institution: the generation of high quality human capital.”
The focus of the rest of this chapter is onRUs, for two reasons. First and most importantly, research universities have become more central to the knowledge economy and innovation systems than government laboratories. Second, the literature on the organization and impact of government laboratories is more limited and sparse than that on RUs.[11]
3.A conceptual approach to the problem of managing complementarities between universities’ and industry’s research
A report written by David and Metcalfe (2008) for the expert group “Knowledge for Growth” of the European Commission makes a strong argument that there is much more to the process of innovation than R&D. Achievement of innovation requires accessing and combining many more types of knowledge and capabilities than is summed up by the phrase “science and technology”, such as knowledge of markets and organizations, as well as of the availability and quality of inputs. Production of these knowledge assetsisa key aspect of the innovation process, but it does not take place in universities or other public research organizations. Universities are not organized and governed to be producers of innovations in their own right – they are first and foremost designed to achieve a new understanding of natural phenomena and technologies: in this task they are naturally inventive. Conversely, in modern free market economies, it is firms that have the incentives and governance structures to make innovation their central goal, and are expected to be the almost exclusive sources of innovation. In the realm of innovation, a public research organization will never be more than a second rank institution.
So it seems wise to acknowledge the virtues of the division of labour between universities and business firms regarding the knowledge production function and to allocate the innovation function to the business sector. However, as with any division of labour, the increased efficiency of the various tasks (invention on one side and innovation on the other side) comes at the priceof introducing problems of connection between the two worlds: boundary issues may impede interactions between the various organizations.
3.1Economic opportunities
A large number of economic opportunities exist for exploiting potential transfers from academic research to industry. When the two systems are institutionalized in specialized, dedicated organizations that permit their respective advantages to be exploited most fully, their interactions are complementary and, historically, have proved to be highly conducive to sustaining long term economic growth and improvements in human welfare and well-being. Three sources of interactions are typically identified (David, 1993). One sourceis found at the macroeconomic level and consists in the “externalities” that advancements in fundamental scientific knowledge provide to applied researchers (see David, Mowery and Steinmueller, 1992).
A second and no less important economic opportunitylies in the connection between the effective training of researchers and research managers and the profitability of corporate R&D programs. The coupling of open science research activities with graduate training of scientists and engineers has turned out to be particularly effective not only for the quality of human capital created, but also in providing industrial employers with an efficient and very inexpensive process for screening talent.