‘Economists understand technology less deeply than some might hope. But they understand the world of technology far better than they do the world of science’.

– Partha Dasgupta and Paul David, 1987, p. 519.

 

THE emerging global order has ushered in changes in the roles the state and market play in determining the conduct of science and technology and the manner in which they relate to the economy and society. This paper seeks to provide a brief account of the issues related to the changing mode of funding science and technology. This entails a discussion on how knowledge, science and technology have been conceptualized from an economic perspective. The discussion culminates with highlighting the emerging role of the universities and research networks in knowledge creation and its dissemination in the context of the changing dynamics in funding science and technology globally.

Baumol (2007: 165) identifies four sites of production of scientific output. They are the universities, government funded research institutions, research laboratories of individual-inventor engineers and the industrial laboratories of giant corporations. Though the first two spheres, the universities and the publicly funded research organizations are not generally supposed to be under the grip of the market forces, issues related to the mode of funding of science and technology and the structure of costs and incentives faced by scientists and industry have gained significance over the years in terms of their impact on the two sets of institutions. Before we dwell on how these two spheres are increasingly responding to economic factors, we intend to engage with an exercise of economic conceptualization of knowledge, science and technology and the specific features of the markets for information and knowledge.

In the context of growth and the growing income differences amongst nations, many economists felt compelled to delve deep into the factors determining technological advancement achieved by a nation. In the early phase of growth analysis (e.g., Solow 1956), technology was considered to be exogenous to the modelling of economic growth.¹ However, in the new growth theory, often referred to as endogenous growth theory (e.g., Lucas 1988; Romer 1986, 1990, Mankiw, Romer and Weil 1992), technology is considered to be endogenously determined within the model by the optimizing economic agents who invest on education and acquisition of skills and dedicate resources for research and development, thereby contributing to the formation of human capital which is explicitly incorporated in the growth models along with other conventional factors. However, what could be a good proxy for human capital in view of its various forms and channels through which it can affect growth has remained debatable.² 

Romer (1990) made a crucial distinction between the notions of human capital as embodied in persons and technology which is to be better understood in the form of ‘ideas’, designs or even instructions which make machines more productive. Unlike human capital which is embodied in a person and hence seen as rival and non-reproducible, an ‘idea’ generated by the person is in the nature of a public good, e.g., non-rival and non-excludable unless its use is restricted by suitable exclusionary policies, like patenting and copyrights.³ So broadly speaking, ‘idea’ was considered to be a good proxy for technology.⁴

 

Arrow (1962), Stiglitz (1999) and others have earlier defined knowledge as a public good and in this old economics of science (OES), no distinction is made between information and knowledge (Tyfield 2012: p.15). The market for knowledge fails to ensure a socially optimal level of production as it does for any typical public good.⁵ However, initial investment required to produce knowledge is generally on the higher side whereas the cost of reproduction of the knowledge, once it is made available in the public domain after being created, is negligible due to the advancement in communicative and digital technologies. This aspect of knowledge or ‘idea’ is very crucial for understanding the relative roles of state and the market in the conduct of science and technology. If exclusion of the users from the market of information or knowledge becomes difficult, the market fails as the number of free riders swells leading to the non-recovery of the cost of knowledge generation.

 

There are more problems with the markets for knowledge generation. Apart from the problem of ‘free riders’, there would be occasions where the market for knowledge is likely to be absent as the society remains oblivious of the usefulness of the knowledge. The state has to fund risky and uncertain areas of knowledge creation which are futuristic, like defence related research or ‘blue-sky research’ in fundamental/basic sciences, without there being any concern whether it would have any commercial value or not or could address any societal need. The recovery of the cost of funding basic science is also not desirable as spillover effects may be substantial for both commercial and non-commercial uses. The lag between discovery in science and its commercial application is also often very high. Crucial discoveries have been made in the universities and society has been able to appropriate the gains over a period of time as new products were subsequently developed by the industry. An economic analysis of research and development expenditure would depend upon the peculiar characteristics of information or knowledge as an economic commodity.

Market failure is greater for information than for material goods. There are three additional factors which complicate the functioning of a market for knowledge: extreme indivisibility and durability, asymmetry in information leading to complications in negotiations of contracts, and its cumulative and interactive nature (Tyfield 2012: 15).⁶ 

 

It is argued in economic theory that since the benefits arising out of the use of knowledge which accrue to society cannot be appropriated by the producer of knowledge largely because of the missing market phenomenon, private investment in knowledge falls short of what is socially optimal. In the case of private funding, exclusion is enforced legally and either knowledge is made available at a price which is synonymous with copyrights and/or patenting of the knowledge created or it is used to produce differentiated output. In either case, cost of knowledge creation is recovered to sustain the process of knowledge creation. Therefore, prima facie it follows that state funding is a prerequisite for society to gain from knowledge creation. Since the degree of excludability is amenable to policy, private funding in knowledge generation has gone up despite market failure because private funding comes with the objective of enforcing the exclusion principle in the use of knowledge. The mode of funding would therefore determine the degree of excludability and, hence, the extent of publicness (or, privateness) of the knowledge produced.⁷ 

Though funding of science has been shifting away from the public to the private domain due to political and economic compulsions, the neo-liberal agenda to make knowledge goods private has met with limited success because of the public good character of knowledge.⁸ This is partly comprehensible if we look at the discipline-wise composition of science funding. Space and atomic research continue to be largely funded by the state whereas private funding has witnessed a rapid rise in biomedical research where the potential for commercial exploitation abounds.

 

The apparent confusion arising out of the interchangeability amongst the notions of information, knowledge and science is circumvented in the new economics of science (NES) spearheaded by Dasgupta and David (1987) (Tyfield 2012: p. 16).⁹ They highlight two important features: one , broader definition of knowledge which includes ‘tacit’ dimensions, and two, that science is determined by social norms. Dasgupta and David begin by questioning whether science and technology should be distinguished for the sake of analytical clarity. Secrecy is practised in the institutions of technology to maximize private rents, whereas disclosure is the norm in the institutions of science where the scientists strive to gain credibility amongst the peer groups driven by the urge to establish priority of discovery, though both the institutions are engaged in the production of knowledge.

 

In the former, it is a private good and behaviour is market driven while in the latter, it is a public good as science is guided by norms and societal mores. Each community would be guided by different methods of training, incentive structure, attitudes and mores prevailing in their respective institutions. Science and technology are regarded as a functionalist pair. Notwithstanding, NES continues to treat knowledge as a commodity since allocative efficiency to maximize scientific output continues to remain a matter of concern (Tyfield 2012: pp. 15-16).

Dasgupta and David (1987) argue that undermining of science as a social entity today is attributable to the technological community’s conception of knowledge as a form of productive capital (ibid. 158). Science is riskier in the sense that it is uncertain whether additions to the stock of knowledge and communications of their research findings would have any practical applications at all. The value of information to be used as an input for further research is conjectural in nature. But, common purpose of science is in consonance with society’s aim and the need is to ensure efficient allocation of resources.

 

A wave of reform measures in higher education have effected changes in the governance of the government funded institutions and at the same time, private participation in higher education and funding of research has been rising in both the developed and the developing countries. Fiscal constraints and faith in the market have led the governments to ease themselves out of public provision and explore new ways of designing and promoting a permeable interface between knowledge businesses and public education at all levels. The mode of public funding has undergone change with increased focus on outcome and accountability.

Recent developments in the mode of funding have led to the blurring of distinction between science and technology. The pursuit of science should ideally remain immune to the market signals because the market suffers from myopia on the part of market participants and the market signals cannot often capture genuine societal needs to guide funding allocation in science in particular. Science unlike technology requires self-regulation and public support (Dasgupta and David 1987). For self-regulation, what is required is collective effort from the scientists to ensure compliance with the norms. But to the extent scientists respond to the carrots, the incentive structure which is often designed by the industry leads to the weakening of the collective effort.

 

But recently, the self-regulatory mechanism of science has come under stress. Not only has public funding of science declined, the nature of such funding has changed. Infusion of corporate principles with increased thrust on outcome and accountability in governing the funding mechanism under the disguise of new public management (NPM) (Marginson 2010: 139) which imagines business models in higher education, research, and creative arts has become the accepted norm world over.¹⁰ NPM is an example of policy synchrony in the global world of creation (ibid.). NPM essentially relies on the efficacy of incentives to foster competition in order to achieve efficiency with emphasis on surveillance, relevance of the research area, transparency of outcomes and its ‘impact’ on research.

The goal of improving national competitiveness in the global context is argued to be one reason behind the adoption of NPM. A pertinent question however remains: how does NPM affect creativity in the world of science and technology as compared to a system governed by self-regulation with academic freedom? Competitive funding under NPM may promote more ad hoc and short-term research where evaluation and incentive structures focus on quantifiable and immediate outputs. Since sustained funding is not guaranteed, scientists may be more averse to risk taking in their endeavours eventually undermining basic research (Marginson 2009; Stephen 2012).

Why is NPM being advocated for some universities and research organizations with delivered appreciable output in the past and continue to do so even today? Possibly because a good number of universities have failed to deliver despite being governed by self-regulation and these universities are generally low in the pecking order. In general, infrastructural constraints, poor governance and an uninspiring academic culture do not augur well for the level of motivation teachers and scientists in the universities down the order. Arguably, NPM has the potential to rejuvenate the system and ensure efficient utilization of resources with the adoption of corporate culture albeit at the cost of undermining basic science and its self-regulatory character, the hallmark of university and science as argued by Dasgupta and David (1987).

 

The ability to combine teaching and research has conferred on the university a unique status and command in the world of knowledge creation. The university today is entangled in the whirlpool of state versus market debate against the backdrop of advancement in communicative technologies and the global dynamics of asymmetrical power and economic relations. Developments in the realm of financing have affected the university the most as a key institution in the world of knowledge generation.

Research universities carry out two functions. One, curiosity driven or fundamental research and two, advanced educational credentialing for the upper level career. With the change in the funding mechanism and emergence of specialized research institutions, the role of university in the sphere of knowledge creation has suffered a setback. While the top universities are earning revenue from patenting, the remaining universities have decided to focus more on the delivery of market-oriented courses and production of knowledge more as a private good to earn revenue.

 

However, industry’s share in financing university research in all nations remains modestly low at six per cent (Marginson 2010: 142). Patenting witnessed rapid growth since the decade of 1970s, while it doubled during 1979 to 1984, again in 1984-89 and 1989-97 and reached its peak in 1999. Around top 100 universities along with other academic institutions, mostly government funded, account for this high growth (Tyfield 2012: 104-105). Stephan (2012) argues how economics shapes science in the context of the government funded institutions, universities and research institutes.

In the USA, the universities and medical schools produce 75 per cent of all articles published in scientific journals and carry out 60 per cent of basic research. Economics matters because doing research costs a lot of money and incentives play an important role in how resources are allocated across various competing areas of research and the pace of discovery. USA spends 0.3 to 0.4 per cent of GDP on research and development at the universities and medical schools. Costs determine the way in which scientists carry out research starting with lab materials to the qualifications of the researchers deployed in the lab (ibid. pp. 2-3).

Scientists respond to incentives, pay packages offered, and where to submit articles for publications. A share in royalty income or incentives is offered to begin start-up companies. Pay packages are lucrative enough in the USA to attract scientists from the rest of the world including Europe and as a result, the hegemony of USA in the sphere of knowledge production has continued to remain unchallenged. Increments in pays are linked to productivity of the scientists.¹¹ Choice of career in science and attraction of talents is determined by the expected pay packages in addition to fame, recognition and prestige. Dasgupta and David (1987: 172) argue that unless scientists are socially conditioned to be imbued with scientific spirit, the high pay packages offered by the giant corporations would lure them away.

 

The flow of knowledge has not been a one-way street from the academe to the industry. The faculty may consult industry officially or informally to identify research problems and more importantly collaborate with them to carry out research. The industry funding is concentrated in health sciences and biotech. Decline in government funding puts pressure on the faculty to accept projects sponsored by the industry and in the process, they seize opportunities to identify commercially exploitable research areas. Transfer of knowledge takes place when university PhD degree holders are absorbed in the industry. Industry representatives attend the conferences held by universities and read their articles. Industrial scientists have played a crucial role in the transfer of knowledge produced by university research (Rosenberg 2006: 84).

 

Baumol (2002) argues that innovation is the primary source of capitalist growth miracle. In his analysis, it is the role of entrepreneurship which spurs economic growth. An independent innovator, who experiments and explores possible ways to be bold and imaginative, introduces new products and new processes. ‘Non-routine innovation’ does not emerge from regular planning (Lowrey (2007) quotes Baumol, Sheshinski et al: 73). The innovation system must be built on a foundation of free competition and free enterprise in the presence of small business.

Rosenberg also argues that growth has become endogenous as decision making agents maximize and respond to signals and opportunities transmitted by normal market forces. Rosenberg (2006: 81) states, ‘I believe that the growth of endogeneity has led to the production of much excellent science, but that does not mean that I am advocating an indefinite expansion of the reliance upon market forces in directing the scientific enterprise; nor that I would be unconcerned over a decline in the share of support allocated to blue-sky research.’

R&D expenditure is devoted to improve new products and not necessarily for breakthrough innovations of the Schumpeterian type. Schumpeter’s theory of creative destruction assigns a role to innovation and argues why imperfectly competitive market fosters innovation in sharp contrast to the understanding of competitive market in which price competition is at the focus.¹² The role of market is envisaged in terms of granting property rights, IPRs, and a sound, reliable and fast legal system and not in terms of price flexibility. Engineering discipline has contributed to the endogeneity of science (Rosenberg 2006: 86).¹³ 

To deal with uncertainty, the corporations invest in each other’s research operations, participate in joint ventures and share the technological fruits. This is a new development which has to be probed in view of the conventional understanding of market in spurring innovation and growth.¹⁴ 

 

Community based research initiatives defy economic principles where cooperation rules in place of self-interest and market-driven initiatives. It is an example of social production where the networked information economy has emerged as an outcome of decentralized individual action who coordinate, cooperate and connect without there being any mediation through the market (Benkler 2006). Information assumes the status of public goods as it is made available to all mainly through the internet. Some universities have also taken up steps in favour of making knowledge free through ensuring easy access to materials uploaded on their sites free of cost. Neo-liberals who seek to construct a global market for knowledge under the overarching framework of WTO-GATS regime have failed to explain this communicative sociability and the growing share of open source knowledge goods mediated by the internet. The neo-liberal drive towards universal commodification of knowledge has been challenged by this new mode of knowledge generation (Marginson 2010).

In continuation with this, new models of open science for production and innovation are coming up fast with communities, the government, and industry collaborating both within the nation and across the international border. The new models of open science are heralding a new regime which is in some opposition with intellectual property rights (Peters 2012).

 

Knowledge has been characterized as a global public good as knowledge can transcend international boundaries (Stiglitz 1999; Peters et al, 2010). The internet has affected the way research is being carried out in the context of globalization. One popular way of imagining the world of higher education and research is in terms of WTO-GATS regime. As argued by Marginson et al (2009), this view has now been challenged where knowledge has acquired the status of a global public good.

Policy makers have expressed concern as to why do Indian universities not feature in the global ranking of universities. Global university ranking is an attempt to map the world of knowledge production arguably in a fairly objective manner. However, ranking methods suffer from subjectivity in terms of the choice of indicators and opinions expressed by the academia, disregard for diverse socio-economic contexts and, above all, differences in mission and mandate of universities which makes the university-society linkages specific and contextual. Notwithstanding, this ranking method has gained credibility over the years and it has been able to exert considerable influence on the university’s role in knowledge production.

 

The nature of flow of students and faculty across the globe tends to perpetuate the hierarchy as the best minds are attracted towards the best of the universities and at the same time, the best of the universities attract the most talented. This global market for higher education is characterized by what is called selection-based efficiency rather than the conventional X-efficiency. This has enabled the top ranking universities to maintain their rankings at the top of the table. It has also led to segmentation in the higher education sector (Marginson 2010: 208-09).

Mobility of scientists and skilled professionals across the globe, and access to internet have been on the steady rise. Nearly 44 per cent of PhDs in science and engineering are temporary residents in the USA, 60 per cent post-docs are also so, and 35 per cent faculty are foreign born (Stephan 2012: 183-193).¹⁵ Evidence suggests that foreign born scholars do better than their counterparts in the USA. Ranking helps the university leaders and policy makers to strategize depending on their modes of funding and mission to build networks of researchers across the universities primarily for the purpose of competing in the global arena. This, exclusionary tendency has further led to the consolidation of the hierarchical nature of the ranking and segmentation of the universities (Marginson 2010). Knowledge flows are therefore stratified at the global level by the concentrations of economic, political and cultural power in cities and regions, uses of internet, IT, use of English, market power of various knowledge intensive industries, and cross border activities of the universities and more over by research capacities (ibid.).

 

The hegemony of the universities from the USA has remained entrenched over the years. Nearly half of the universities in the top 200 are from the USA. However, universities from a few Asian nations like Korea, China and Singapore have now entered the ranking. In 2005, USA produced 2,05,320 papers in scientific journals, compared to 55471 from Japan, 45,572 from UK, Germany contributed 44125, China 41,596 and India 14,608 (Marginson 2010: p. 214). USA spends relatively much more on higher education in terms of GDP than all the others.¹⁶ The US hegemony is likely to remain unchanged despite high growth witnessed in some nations like China.

English continues to dominate as a main medium of communication in knowledge production and dissemination and this in turn, influences the flow of human capital across the nations which has further contributed to the continuation of the US hegemony. In consonance with this, USA accounts for more citations than share in papers in the global context.¹⁷ USA attracts creative talent globally and the focus is not on revenue earning but on talents. This asymmetrical global flow, mainly from the developing world to the developed ones, continues but the hegemony of USA is somewhat dented (Peters 2010: 258-260. Multiple centres of science are evolving in the world of science. The European Union, Japan, China and Russia as well as India and South Korea have gained strength. Contribution to scientific production from the developing countries saw an increase from 7.5 per cent of world papers in 1981 to 17.1 per cent in 2000. This questions the global aspect of knowledge being defined as a global public good. The top countries account for a very high share of citations compared to the rest of the countries indicating disparity in impact of scientific output.

 

This paper examines the implications of changing pattern in the funding of science and technology and how economic factors impinge on the conduct of science in the university. Though the share of private funding has increased over the years and has become crucial in determining how scientific research is being carried out even in the universities, the rapid expansion in communicative technologies being spurred by the IT and internet have sought to reinforce the public good character of knowledge at the global level. Private funding has increased in the areas of IT and biotech which has negated to some extent the status of knowledge as a public good.

Since research is expensive and it is knowledge which would largely determine how a nation and a firm do in the emerging global scenario, both private funding and state funding would continue to play their respective roles, however the target areas in science and technology would differ. What is a matter of concern is the manner in which the mode of funding science is undergoing irreversible changes under the overarching framework motivated largely by the NPM. This has led to the blurring of the distinction between science and technology.

 

Globally, the differences between the developed world and the developing world will continue though collaborative research is gaining significance. The latter albeit partially challenges the inherent asymmetry in the global realm of knowledge production which is fostered by the one-way mobility of human capital and differences in research capacities across the nations.

 

Footnotes:

1. In one of its earliest models of economic growth formulated by Solow (1956), an aggregate production function of the type Y = A. F(K,L) was invoked to locate the sources of growth where A was considered to be the proxy for technology along with capital (K) and labour (L). A is exogenous as the factors for technological advancement were not specified.

2. Some of the proxies which are considered as school enrolment in class VIII, R&D expenditure, or even quality of school education. The impact of human capital on growth would vary in accordance with each proxy.

3. It was Arrow (1962) who conceptualized information or knowledge as a public good. As per the conventional definition (Samuelson 1956), a public good has the characteristics of non-rivalry in consumption and non-excludability. After being created, once it is made available in the public domain, it becomes available to one and all as the marginal cost of reproduction of the knowledge is much on the lower side. Knowledge in the form of formula like E = mc2 or a theorem is generally a pure public good.

4. Productivity rises when an idea or an instruction as often embodied in a new machine combines the same set of raw materials would produce more output with higher value. This is typically the case for the computers becoming more and more advanced mainly because of the advancement in the hardware and the software with chemical properties of the materials virtually remaining the same.

5. In Romer (1990), idea or knowledge is a private productive capital and the industry has to fund its generation to compete in an imperfectly competitive market as in such a market, surplus is left to recover the cost of knowledge generation after remunerating the factors of production in accordance with their marginal productivities. In the older version of the growth models, technology was more like a public good which was available to all.

6. Extreme indivisibility and durability means once the piece of knowledge is acquired, there is no need for the second time and it can be used umpteen number of times. Asymmetry in information means that the attributes cannot be known before it is acquired which creates difficulty for negotiation of contracts. Knowledge accumulates as ideas interact with each other. If knowledge is kept secret, it does not allow for productive interaction.

7. In the earlier definition of pubic good (Samuelson 1956), technical feature of a good would determine whether a good is a public good or a private one. Marginson (2007).

8. There has been a rise in the private participation in the higher education sector producing degrees and certificates which are private goods, but new knowledge produced in research and existing knowledge the students learn are both public goods. Further, private funding for knowledge has to be reconciled with the proliferation of open source knowledge goods mediated by internet as opposed to mediation by market for private goods (Marginson: pp. 142-143).

9. In the old economics of science (OES) as discussed above, knowledge is basically commodified which allows for interchangeability amongst the notions of information, knowledge and science. This becomes problematic because OES did not distinguish between codified and tacit knowledge embodied in the scientists and the experts. In OES, characterisation of knowledge as non rival and non-appropriable is more akin to information. However, knowledge can be ‘tacit’ as it is embodied in person which, in effect, is rival, excludable and non-depreciating as use of knowledge makes it further refined and enriched. As discussed earlier that Romer (1990) did make a distinction but it was in the context of growth theory. Tyfield (ibid.) does not refer to Romer (ibid.) in the context of the discussion on economics of knowledge.

10. We may note that the economics of the pure world of science and its associated features cannot be treated at par with economics of the world of art. In Marginson’s analysis, the differences between the two worlds are glossed over.

11. Grants awarded by the Department of Science and Technology to the universities is based on what is called H-index which is now mentioned in the biographical sketches of the faculty and the scientists. H-index measures the productivity of a researcher as well as the impact the research based on the collection of researcher’s most cited papers and the number of citations in other people’s publication. Recently, the University of Delhi has been awarded with the highest amount of grants for doing research. (The Hindu, 25 September 2013).

12. Romer (1990) also argued in the context of the growth theory why investment in knowledge requires imperfect competition to allow for profit for cost recovery and reinvestment to sustain the process.

13. To the extent of 30 per cent of basic research in the USA was funded by the industry though it would not be inappropriate to presume that the private profit making enterprises did have expectations about financial payoff.

14. Venture capital is an example of mediation between an idea and capital. This type of capital promoted innovation in IT, and biotechnology. Small enterprises are often starved for capital. Those who want to invest capital, screen prospective projects and firms, and assume the role of mentors to budding capitalists (Blinder 2007: 305). The dark sides of this sort of capital are instability and wastage. This innovation machine must be fueled by excessive optimism.

15. In USA, scientists earn much more compared to Europe which explains why USA has been a magnet for the productive European scientists. In addition, increased availability of fellowships, job opportunities and facilities all contribute to make USA a preferred destination. Over 90 per cent of PhD scholars from China and 81 per cent from India stay back in the USA (Stephan 2012: 191).

16. In 2003, USA spent 2.9 per cent of GDP on higher education which was seven times as in material terms as did the next nation (Marginson 2010: 214). Around 0.3 to 0.4 per cent of GDP is dedicated for research and development at universities and medical schools (Stephan 2012: p. 2).

17. In 2001, USA accounted for 44 per cent citations in the scientific literature based on a less than a third of the output (ibid.).

 

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