Chapter 3

Review of Literature and Theoretical Perspectives

3.0 Introduction

The institutional processes of knowledge production, knowledge transfer and the

relationship of industry to the sources of knowledge have lately undergone considerable

change from an earlier era when academia and industry were viewed as two clearly

defined and distinct entities. Over the rears, academia both accommodated and induced

change and apart from the sole responsibility of teaching, it gradually indulged into

research activities. However, beyond building research capacity in emerging and

interdisciplinary fields the capability of academic research institutions to utilize the

knowledge resources has been recognised. This also means strategising for utilisation of

its intellectual assets that have potential for commercialisation in a judicious manner, such

that academia does not lose its academic credibility. In this context, the emergence of

entrepreneurial university draws our attention wherein it is asserted that this kind of a

research university translates its research findings into use through a variety of

mechanisms such as liaison offices, contracts with firms, patenting, licensing, and so on,

which gives the university some aspects of a business, while retains its previous classical

functions (Tomatzky and Gray, 2003).

This chapter reviews relevant literature on knowledge production and knowledge

transfer from academic research institutions and explores innovation studies relevant to

. academia-industry linkages. This chapter also reviews the transformation of the

relationship between academia, industry and government and the effect this transformation

has had, and is currently having, on the knowledge production system. The approach is

that the essence of the relationships between the institutions can be captured from among

the different concepts on innovation including the 'triple helix' framework. This chapter

83

begins wi.th the discussion on the role and behaviour of academic institutions, historically

tracing the development from the 'first academic revolution' where the sole focus was

teaching and subsequently research responsibility was appended to the mission of

knowledge generating institutions; to the 'second academic revolution' of academic

institutions increasingly getting engaged in contributing to economic development of the

sector/region/nation. The subsequent section, which is the heart of this chapter, entails

discussion on the theoretical concepts primarily on knowledge production and transfer and

innovations: namely the 'National Systems of Innovation' (NSI); 'Mode l' and 'Mode 2';

and 'Triple Helix'. Discussion on challenges before academic institutions constitutes the

next segment which also focuses on interaction between academia and industry. The next

section on literature survey of knowledge production and knowledge transfer, start-up

firms, incubation units and studies on the factors contributing to success and failure of

technology transfers, is followed by a discussion on emergence of entrepreneurial

university. The main objective of exploration and literature review in the chapter is to

develop an appropriate theoretical framework and perspective for study of IITs. This

exercise of critical literature review is seen to be helpful and at the same time important to

derive some operational hypotheses for the empirical study of IITs later in Chapters 4 and

5 i.e. the chapter on knowledge production and academia - industry relations: the modes of

knowledge transfer at IITs.

&4

3.1 First and Second Academic Revolutions

According to Spariosu (2004: 167), the history of university can be traced as far

back as Pythagoras, Eudoxus of Megara, Isocrates, Plato and Aristotle; while its modem

avatars begin in the 11 th century at Bologna and in the twelfth century at Paris and Oxford.

The history of higher education in the Asian subcontinent would list out ancient

institutions in China in different dynasties (Western Zhou, Han or Jin dynasty) and in

India during the Gupta Empire (Takshila and Nalanda). However the modem institutions

of higher education in these two countries came up only in the late eighteenth century1l4.

In the middle ages, universities began by training people such as lawyers, physicians, and

churchmen (today's middle-class professionals). In their first medieval phase, universities

were seen as cultural forces that attempted to pull away from the prevailing aristocratic

values towards their middle-class counterparts In other words they were seen as

"democratizing" forces in a feudal society. The conflict between aristocratic and middle­

class values in academia can also be recognized in the present day academic institutions.

Moving from medieval to modem phase, the academic institutions gradually got more and

more influenced by the philosophical faculties. According to Reading (1996: 14), the r-

history of ~ous-ways~of understanding the functions of the university could be roughly ~ ••• r~~ ._ ... ____ - -~ - _--,"~

summarized by saying that the modem university has had three ideas: the Kantian concept -- ----------- ---, - -_.- ~

of reason, the Humboldtian idea of culture and now the techno-bureaucratic notion of ~ c - -, ,----~---- ~ ~

excellence. He says "reason on the one hand, provides the ratio for all the disciplines; it is ----their organizing principle. On the other hand, reason has its own faculty, which Kant

names 'philosophy' which in contemporary terms would mean 'humanities'. In his

thinking on the university, Kant also posed the problem of how reason and the state, how

knowledge and power, might be unified. Under the rubric of culture, the university is

assigned the dual task of research and teaching, respectively the production and

inculcation of national self-knowledge".

114The history of modem higher education in China is approximately of 100 years duration. Beijing University, established in 1898 is one of the earliest foundations. In India, the first higher education institution was in !he form of an industrial school established at Guindy, Madras, in 1842, which ultimately became the Guindy College of Engineering and got its affiliation to the Madras University in 1858. The first engineering college however, was established in the United Province in 1847 for training civil engineers at Roorkee (http://www.education.nic.in/tecedu.asp). Later on in 1857, three prominent universities were established in University ofCa1cutta, Bombay and Madras.

85

Initially conceived as institutions of cultural conservation, preservation, and

transmission, the medieval institutions existed solely for that purpose for many years. The

way systems of higher education developed harks back to the principal German referential

model having origins in the philosophy of the Wilhelm von Humboldt. This Humboldtian

model laid special emphasis on faculty autonomy and placed utmost importance on the

duty of university to conduct both teaching and research. Humboldt's philosophy also

stressed Hildung (the overall education of the individual) versus Ausbildung (education

specifically geared towards employment)lIs.

In the United States, the first academic revolution came up in the mid nineteenth

century at institutions like Harvard and Colombia where professors, often inspired by their

German doctoral mentors, sought to initiate research training programs and advanced

degrees (Etzkowitz, 2002). The transformation of universities from institutions of cultural ._-_.-'" --.-preservation and maintenance of knowledge to institutions for the creation of new

knowledge-is~kn;w~ ~~ th-~ academic revolutionll6. Here the role of ~-tat~ ~as

considered important. The second academic revolution, which entails the translation of

research into products and into new enterprises started almost at the same time as the first;

the former almost immediately engendering the latter (Etzkowitz et aI., 1998: 2). In the

contemporary period, the research university assumes a third function that of economic ---

development (also see OECD, 1987; Martin and Etzkowitz, 2000; cj~~ 1998) .,.,.,.-

Many of the changes that universities went through during the industrial revolution

and that remain relevant in the present context are reflected in John Henry Cardinal

Newman's The Idea of a University first published in 1852 but revised by the author in

1859 and in 1873 117. According to Spariosu (2004: 166), two conflicting impulses have

115 Albritton, Jr. Humboldt's Unity of Research and Teaching: Influence on the Philosophy and Development of Higher Education in the U.S. from http://ssm.com/abstract=939811 accessed on 12 February 2008 116 The reference about first academic revolution is found in Christopher and Reisman (1968) which was made in the context of having an egalitarian environment and an education system emphasizing on meritocracy. According to Grant and Murray (1999: 224), "the first academic revolution was congruent with the dominant societal values of individualism and an emphasis on equal opportunity that presumed radical inequality of outcomes based on individual effcrt and talene. 117Newman grapples with the same conflict between middle·class educational values (which he largely deplores) and aristocratic values (which he largely idealizes) in his concept of higher education as a gentlemanly, disinterested pursuit toward institutional excellence. For Newman, university is "a place of teaching universal knowledge". At top of the

86

laid the foundations for two academic paradigms that have emerged since the 19th century

as dominant ones in western academia and have also been exported to other parts of the

World. In the first paradigm the university is organised as_<!~tadel O~}~llq~l~gge~'_~n~/ ------corresponds to the aristocratic or elitist impulse. In the second paradigm university is

structured as a "fac!2ry of knowl<;:Qg~ and corresponds to the democratic or popular.............-­

impulse. These impulses h<l:ve been present all along, in one form or another, in most, if

not all historical institutions of higher learning ll8. Here the author's description of the

'products' from the 'factory of knowledge' is indicative of the knowledge base and other

forms of knowledge assets (intellectual property, publications etc.) which this study

addresses to.

As mentioned abov~, the modern academic institutions in the contemporary phase,

have yielded to the techno-bureaucratic notion of excellence, and this phenomena has

occurred in many countries, under the impact of globalisation, wherein according to

Reading (1996: 47) "the State does not disappear, it simply becomes more and more

managerial, increasingly incapable of imposing its ideological will, which is to say,

incapable of imposing its will as the political content of economic affairs". Here the

question that Reading poses is if the university, once stripped of its cultural mission, can

be something other than a bureaucratic arm of the unipolar capitalist system. The three

functions that are still invoked in the contemporary university are research, teaching and

administration. The last of these is, of course, the most rapidly expanding field in terms of

the allocation of resources and its expansion is symptomatic of the breakdown of the

German idealist contract between research and teaching (Reading; 1996: 125).

pyramid one can find the Ivy league schools in US, 'Oxbridge' in England, and Grandes Ecoles in France (Spariosu: 2004: 172). 118These two paradigms are noted to be seen in a relationship of reciprocal causality generating complex feedback loops. University as Citadel of knowledge entails that there is the aristocratic idea of knowledge as power-whether it is under the guise of a free, disinterested, and leisurely intellectual pursuit-that must remain the privilege of a few and therefore must be guarded and defended from the assault and penetration of masses. In 2nd case, where university is organised as 'factory of knowledge', one perhaps develops the factory analogy by describing specific academic forms of Fordism, Taylorism, and their contemporary 'neo and post' variants, as well as other bureaucratic rationalizations of intellectual labour, typical of academic mass production. Spariosu (2004), describing the academic institutes as 'factory of knowledge' says that academic sweatshops as a source of cheap intellectual labour, under today's nea-Iiberal and bureaucratic academic paradigm, concerned mainly with techno-sciences, have become relatively cheap source of intellectual labour for the corporate world.

87

The emergence of positivist ways of thinking in the late 19th century might in the

end have contributed to the bureaucratization of academia and vice-versa. Positivist

thinking might thus have contributed to the rise of positivistic scientific culture, the

explosion of industrial technology, the proliferation of narrowly conceived fields of

specialization, and the corresponding fragmentation of traditional disciplines, the

formation of a technocratic mentality and the establishment of a managerial educational

model (Spariosu, 2004: 180). Harpur (2006) echoes a caveat stating that the transformation

proposed via the entrepreneurial university may become the only tool for assessing

solutions and attributing value and regressively, it contains a strand of positivist thinking

that had shifted out of philosophy but clearly not out of technology influenced thinking .

. ~ A Further Academic·Revolution

The principal writings of Etzkowitz et aI., (1998: 1) draws attention to a new

common form of academic institution that has emerged in the late 12th century-from its

medieval origin as a corporation of scholars to the contemporary entrepreneurial

university. The entrepreneurial academic institutions characterise their role as the source

of future industrial development, both by establishing organizational mechanisms to

transfer knowledge and technology and by playing a strategic role in regional

development. The entrepreneurial university retains the traditional academic roles of

social reproduction and extension of certified knowledge but places them in a broader

context as part of its new role in promoting innovation (Etzkowitz, 2003). In an

entrepreneurial academic institution, the academic research groups, consisting of faculty,

graduate students, post-doctoral fellows, technicians etc become <quasi-firms', taking on

some of the organizational characteristics of a firm in industry. ARls, bringing together

research groups across disciplines, often in collaboration with firm and government

researchers, take this process a step further.

The entrepreneurial university in the analysis of Etzkowitz et aI. (2000) has

essential characteristics which are found in them as emergent structures and

developmental mechanisms. The first is Interna! Transformation in which ~aditional

academic tasks are redefined and expanded according to requirements of n~wly emerging

functions. The authors explain that as the university enlarges its role in innovation,

88

controversies anse such as the propriety of extension of academic mISSIon from

dissemination to capitalization of knowledge, but over time new rules and roles are

defined and legitimated such that the university reformulates its mi-ssion to incorporate the

entrepreneurial paradigm. Second characteristic is the Interface Process where the

entrepreneurial university needs an enhanced capability for intelligence, monitoring and

negotiation with other institutional spheres in particular, government and industry. Here in

due course of time through centralization or decentralization, the entrepreneurial paradigm

takes hold of interface capabilities across the university. By centralized interface

capabilities they mean TIOs or spin-offs facilitators. Faculty and other technical ..---personnel are assigned responsibility to assess the commercial salience of research

findings and are encouraged to have interaction with external partners. Third characteristic

is Recursive Effects where university as entrepreneur, besides establishing links with

existing organisations, develops capabilities to aid in the creation of new organisations in

the form of academia spawned firms, or leadership in forming regional organisations. The

consequences are the genesis of trilateral organisations where interface leading to

likelihood of collaboration in creating cross-institutional entities is anticipated. Special

centres that have personnel from all three institutional spheres and joint ventures involving

firms are thus possible. Fourth characteristic is the Trans-institutional Impact where in

university-industry-govemment relationships explain the current transitions in the research

system; the two spheres apart from uniyersity also increasingly develop similar

intermediary capabilities. Gradually formats for collaboration are institutionalised in legal

and customary formats I 19. The implications and consequences associated with such

characteristics may describe the transformation of a research university to an

entrepreneurial one. /'

Raines and Leathers (2003: 225) observe that the emergence of entrepreneurial

university viewed from the perspective of Veblen's analysis of universities' behaviour, is

a logical development in the continuation of the evolutionary process of change that was

underway in the early 1900s. The modem entrepreneurial university is simply the latest

~-

Ilq Example of such development is the US Co-operative Research and Development Agreement (CRADA)

89

manifestation of Veblen's 'educational enterprises' (Veblen, 1918 (1993: 140) as quoted

in Raines and Leathers, 2003).

This study thus attempts to explore the issue if ARIs such as fITs that exist today

are increasingly seen to shift their functioning from being just a 'factory of knowledge' to

addressing research function in addition to teaching. Further, this study is also concerned

with the issue of the shift of institutions towards largely embracing the notion oj

'entrepreneurial university'. The study thus also explores the shift that is observed in IITs.

3.1.1 Challenges Confronting Academia in Knowledge Production & Transferl20

Although academic research institutes (ARIs) are gradually being looked as

potential source of innovations by industry, many of the firms nevertheless view them

primarily as source of trained persons and skills, and as centres for problem solving. Many

academic researchers also oppose technology transfer and other commercial activities,

believing that it takes resources away from research. Many scholars have expressed their

concern over academic institutions losing their basic role (Lee, 1996; Nelson, 2002;

Rogers, 1986) and that promoting commercialisation in academic institutions would

change the institutional rules in the manner research is conducted (Dasgupta and David,

1994). These issues come across as prime challenges before an academic research institute

which are historically rooted in range of literature on culture of science, education,

economic systems, innovation, management, and so on. Moreover, the involvement of

academia for economic development, in protection of intellectual property and the notion

of 'entrepreneurial university' suggest a major shift in their functioning, adding to the

concerns of people who oppose such developments. There are studies which suggest that

iQcreased property rights to knowledge and innovation would facilitate exchange of

knowledge and development of further innovation (Teece, 1986 & 1996; Arora, 1995,

Etzkowitz et aI., 1998). Thus the important issue here is that many ARIs go by this logic

120 As the focus of the thesis is on addressing the issue of knowledge production and transfer in academic institutions particularly in the light of these opera:ing in a new economic order that place academi:! as source of innovation, this study does not get into the larger debate of discussing knowledge as a public good (see Lee, 1996; Nelson, 1994, 2004; David and Dasgupta, 1994; Bok. 1990) or the tussle between culture of science and culture of research (see Latour, 1998).

90

and note that intellectual property rights to knowledge assets tend to facilitate investment

in knowledge production which also leads to trading in the patented results of research.

Having looked at some of these concerns, we ought to look at the literature on

knowledge production and knowledge transfer in the context of academic research

institutes in much more detail. The idea is to highlight some of the issues in the literature

and relate them to this empirical study on IITs. But before we overview the literature, it

would be appropriate to list some of the studies in the wider field of academia industry

interaction emphasising on studies in India.

Apart from those we have already discussed in the prevIOus sections, the

interaction of the US universities with industry has been studied by many researchers

(Cohen et aI., 1993, 1998; 2000; Graff et aI., 2002; Henderson et aI., 1998; Shane, 2002;

Colyvas et aI., 2002; Siegel et aI., 2003). Berman (1990) has shown that, despite an

estimated lag in converting research into hard products or processes in the market place,

"collaboration not only increases future industrial research, but also speeds up the transfer

and utilisation of academic research in industry"m.

In India, the interaction of academia with industry in the traditional sense -of being

a source of well educated and trained graduates has been dominant over all other benefits

arising out of mutual interaction. Academia as a source of problem solving institutions for - .~-, ---- --~.-- ---... -- -"

industry is also given due importance. As a matter of concern, lack of trust and sense of

respect for each other have been highlighted as major problem areas for the relationship

between the two entities. -'<:'<,------

Academia-industry interface in India, though in dormant and implicit state, existed

even before independence in 1947. The pioneering efforts of P C Ray in Bengal through -interaction between Indian School of Chemistry and Bengal Chemicals in early 1920s;

inauguration of university-industrial relationship by S S Bhatnagar's Chemical laboratory

J~J There are studies in other countries, studying the university and industrial transfonnation, for instance see Webster (1994) for an international evaluation of academia-industry relations in a broader innovation system; Jacob et al. (2003) for study on Sweden; Geuna (2001) on European Universities; Inzelt (2004) on Hungary; Kondo (2004) and Fujigaki and Nagata (1998) on Japan, and Sutz (2000) on Latin America.

91

in Lahore in 1926, where a series of industrial problems were undertaken; are examples in

this direction (Krishna, 1993). The importance of university-industry linkages in India

was recognized in a major way in 1961, when Thacker Committee stressed the need for

the establishment of various forms and mechanisms of cooperative relationship between

industry and academic institutes. The journey since then has continued with the

establishment of several commissions, committees, councils and institutions by the Indian

govemmentl22. Studies on academia-industry linkages in India are strikingly few taking

into account the studies depicting research capabilities of higher academic research

institutions and their output to industryl23. Some of the generic studies on the subject are

by Vidyasagar et aI., (1996) that focus on greater need for high quality technical education

to produce technically skilled manpower in India; by Mehrotra (1982) who emphasises on

closer university-industry cooperation and the benefits of the latest advances in scientific

knowledge and innovation that can be made more readily available for the welfare of the

society, thus enhancing the image of science; by Joseph and Parthasarathi (2'()03) who

address academia-industry interface and its dynamics from a policy perspective; by Rajan

and Wadhwa (1999) where they describe the problems in absorption and adaptation of

technologies in India. Chidambaram (1999) highlights the patterns and priorities in Indian

research and development and reflects that as India increasingly becomes globally

competitive, technology would be denied more and more for commercial reasons like it

was being done in strategic areas. He discusses the intellectual property right issues which

122 As mentioned by Kharbanda (2000), Kothari commission in 1964-66 and Bhide in 1969 did suggest useful methods of promoting linkages between universities, R&D laboratories and industryl~2. The other committees at the national level advocating the need for a stronger and closer university-industry collaboration include discipline-oriented expert committee of University Grants Commission (UGC) and National Council of Science and Education (NCSE); research committees of Council for Scientific and Industrial Research (CSIR), Indian Council of Medical Research (ICMR), Indian Council for Agricultural Research (ICAR); Review committee on Post-Graduate Education and Research in Engineering and Technology (1971); Satish Chandra Committee on UGC (1980) and so on. The principal agencies making efforts in this direction of enhancing cooperation and interaction between academic institutes and industry are All India Council for Technical Education, Ministry of Human Resource and Development, UGC and Department of Science & Technology (DST). The efforts have culminated in establishment of Technology Transfer Organisations (NRDC) way back in 1953, Industry-University cells, Science and Technology Entrepreneurs Parks (STEPs), University-Industry Consortia and so on. They have also resulted in schemes promoted by the DST like Home Grown Technologies, Programme aimed at Technological Self Reliance (PATSER), and Technology Development Fund. m Morehouse (1977) study focused on the role of public research laboratories and their industry interaction rather than academic institutions. He noted that scientists in the laboratories were not sure about the economic feasiibiity of the inventions before the research is performed. Although studies have been done in India examining the cases of technology transfer (Qureshi et a\., 1984; Nath, 1988; Subrahmanian, 1985; Desai, 1980) they are limited in number and involve public funded research laboratories. Swaminadhan (I 995} and Raju (1995) speak on the linkages and interaction between technical educational institutions and user agencies such as industry, R&D and -design organisations and development sectors which they suggest are not sufficiently strong.

92

according to him, would become progressively more significant and as a result Indian

industry would increase its interaction with indigenous R&D ... it would therefore link up

with national laboratories and university system, which is essential for strengthening the

in-house effort. The absence of literature in this area is probably because. the trend has

been that the firms still overlook academia as potential source of innovation and import

technologies to meet their requirement. The building up of industrial capacity of the

country has proceeded almost totally on the basis of imported technology (Parthasarathi,

1987; Desai, 1980; Rajan and Wadhwa, 1999). Closely associated with the feature of

globalisation, is the policy discourse rod trend of un~versity-industry relations and the

corporatisation of academic science, this aspect has been discussed in Krishna (2001)

whereiii-iCis 61Js;~~d that in a situati~n of stagnating financial budgets for higher

educational institutions, there is a severe pressure on the part of universities, Indian

Institutes of Technology (IITs) and other educational institutions to redefine their

objectives to institutionalise the needs and demands of industrial clients, particularly the ~<

Trans-national Corporations (TNCs) in the current phase of liberalisation. There are

studies on academia-industry interaction elaborating on nature and form of interaction by

Ansari and Sharma (1991) and Chandrakant et al. (1982); on the linkages of research

institutions with academic institutions and industrial organisations NISTADS (1989); and

on the nature and scope of industry-institute interactions in India by Natarajan (1998)124.

Raghunath (1997) notes that industry-academia interaction is a rarity in India but, with the

corporatisation of the economy and the increasing need for trained manpower, corporate

. organisations are willing to play a proactive role in the development of university and

professional education in India. Sandelin (2006) also observes that very little

University/Industry collaboration exists in India, there is limited research by Universities

which is more so at research institutes. /

There are apparently no studies specifically on IITs and their research contribution

to industry from a social science perspective. There are limited studies from which

scattered view-points are known on the functioning and industry interface ofIITs125. For

124 Also see Parthasarathi (1998) for a general view; Siddhartha (2002) for role of IPR in technology commercialisation 125 One generic study on I1Ts is by Deb (2004) who primarily gives an account of the functioning of IITs. It is more of an inside account of the life in an itT system and successful profile of liT graduates and alumni.

93

instance V S Raju (1995) opines that, there is a crucial need for building bridges between

academia and industry. In the Indian context, IITs are one of the earliest to promote and

have institutional mechanisms for working with industry. Indiresan (2004) observes IITs

as premier institutes in terms of their academic credibility and excellence but he also

highlights the problems they face. Indiresan's (2003) study is a report presented on

Research Projects on India- 2025 on the theme of technology policy in a vision for the

future where he highlights the role of IITs. According to Indiresan and Nigam (1993)

while the achievements of the liT -system are considerable, it has faced criticism on issues,

such as, high cost of technical education, brain drain, urban and elitistic orientation, and

inadequate interaction with industry. Indiresan (2004) however observes that Indian

industry has not particularly been interested in technology development; it has little use

for the kind of expertise the IITs possess. A similar opinion is that of Sengupta (1999)

where he observes that Indian industry has so far preferred to go for international

collaborations rather than to academic or domestic R&D organisations in search of new

technologies, or even when technological solutions are called for to address issues like up­

gradation Or modernisation of the existing process. Nevertheless the problem also lies with

.academic institutes, who have apparently not been successful in building trust with

industry in terms of not being able to commercialise their intellectual property. Here

although there are very few empirical studies it has been noted that Indian laboratories

boast of many innovations but few of them ever reach the market (Indiresan, 2003). The

more recent accounts specifically on research output of academic research institutions can

be seen in Chandra (2003) that gives an empirical account of the industry interaction of

liT Delhi, its technology transfers and the role of a technology transfer office.

Bhattacharya and Arora (2007) discuss the industrial linkages and their implications in

seven Indian universities, including the IITs, establishing that growth in academia­

industry interaction is not universal although perception is changing towards utilising

academic intellectual property.

In India, as this thesis would show, that university, industry and government have

been trying various methods to create an environment for interchange of knowledge and

thereby increase productivity and economic growth. The government has emphasised that

94

education and research must be geared to relevance, competence, excellence,

entrepreneurship and development. It is increasingly being advocated that higher

educational and research institutions should be involved not only in generating but also in

transferring such knowledge to industry and to the society at large. They should act as

seedbeds for technological innovation and new industrial ideas. This has been noted by

Menon (2002), where he says that part of the university function can be seen as

generators, storehouses and transmitters of new scientific knowledge to science based

industries. They are the vital participants in the technology transfer process.

Having briefly reviewed the historical transition of academia and noted the

significant transitions from the function of teaching to research to entrepreneurial

activities, noting the challenges confronting the academia in knowledge production and

transfer system, and discussing on academia-industry interface in the Indian context, it is

appropriate to further explore the relevant literature that has been reported more so in the

last two decades. It may be pointed out that the role of universities or more precisely the

role of academic sector has drawn the research attention of scholars not only from

innovation and science and technology policy studies but from social sciences. The

current phase of globalisation and the discourse on knowledge societies and knowledge

based economies has drawn unprecedented attention on the role of universities as

important source of innovations. Further, universities as knowledge generators and as an

important link to innovations with industry are given special emphasis in science,

technology and innovation policies (Turpin and Krishna, 2007; OEeD, 1997). In the light

of this the study reviews relevant perspectives and propositions to construct a theoretical

framework for the exploration of IITs.

95

,

3.2 Relevant Theoretical Concepts and Perspectives126

Looking at the broad approaches to address the Issues of academia-industry

interaction principally in the context of knowledge generation and transfer, there are three

important conceptual theoretical frameworks namely 'National Systems of Innovation'

(NSI); New Production of Knowledge or the 'Mode 2'; and 'Triple Helix,I27. Each of

these theoretical frameworks emphasise the importance of greater bonding between

academia and other institutional actors in the system. The NSI, 'Mode 2" and 'triple

helix' frameworks for conceptualizing the role of the research university within the

innovation processes of knowledge-based economies emphasize the importance of strong

links between universities and other institutional actors in these (read industrial)

economies (Mowery and Sampat, 2004). Even though these frameworks are used to

construct a theoretical perspective, the 'triple helix~~~ework seems t? "~e direCtl~

relevant for this study. This framework is pertinent because 'triple helix' observes

academic institutions to be playing a dominant role in the innovation system and in this

study we are studying the IITs as a representative set of academic research institutes (in

science and engineering) in India.

'Triple helix' has evolved gradually from a simple understanding of university­

industry 'double helix' to trilateral reciprocal relationships between academia, industry

and government and lately to a more intricate adaptation of innovation and· sustainability

as 'triple helix twins' working together as a dynamic yin/yang pair that advance

sustainable economic and social development128• The NSI framework emphasizes how

innovations are introduced and spread inthe context of a country and attempts to explain

as to why national economies differ. To a certain extent, it also explains why certain actors

are important to the overall dynamism in the system of innovation. The New Production oj

Knowledge (Gibbons et aI., 1994) explain two distinct ways in which knowledge is

126 This study uses the terms 'framework', 'model', 'concept' and 'perspectives' in a somewhat synonymous mode even though they can be analysed and defined separately. In There are other noteworthy frameworks especially in terms of explaining the enhanced role of knowledge in economy and society, which basically focus on reorganisation of university-industry-govemment relationships-namely "research systems in transition" (Cozzens et ai., 1990; Ziman, 1994) or the "post modem research system" (Rip and Van der Meulen, 1996 as cited in Etzkowitz and Leydesdorff, 2000). 118 For details see upcoming sections; Etzkowitz and Zhou (2006)

96

produced: 'Mode I' and 'Mode 2'. In 'Mode 1', knowledge is generated in an autonomous

university: in self-defined and self-sustained scientific nisciplines and specialities, and is

governed by peer group scientists who have a say in telling what constitutes science and

truth and what doe/to Here according to some experts academia-indus~ry interface is

non-existentI29• In case of 'Mode 2', knowledge particularly in science is characterised by

interdisciRlinarity and plurality and is no longer produced only in university settings but is ~ _ .. _----- ...,/"

also found increasingly in many different loci, like government laboratories,' industries

and other think-tanks and that it tends to be produced in context of application. It is

extremely important to note the prediction about universities in the new mode of

knowledge production where the authors say "the universities in particular will comprise

of only a part, perhaps only a small part of the knowledge producing sector" (Gibbons et

al., 1994: 85)J30.

The three conceptual frameworks operating in a selection environment that largely

reflects· the neo-liberal economic order, have addressed the important role of academia in the

system of innovation. The NSI concept has lately emphasised the significant role of

universities in the national systems of innovation even though the focus ofNSI has been on

firms l3l. This is evident from Lundvall (2002: 9), drawing upon Nelson's (1993)

observation of Universities being widely cited as a critical institutional actor in national , innovation systems, when he says that "the universities have become more directly involved

in market-driven processes and more exposed to competition from other producers of

knowledge ..... universities now have 'a third task' with focus on their direct contribution to

a more dynamic deVelopment of the business sector". In 'Mode 2', even though the

prediction of Gibbons et aL (1994: 85) which we mentioned in the above paragraph, on the

diminishing role of universities, needs to be questionedPthere has been a conscious effort to

re-Iook at the role of universities in a distributed and diverse knowledge production system.

1~9 See Shinn (2002) 130 Diversification of loci of scientific production is empirically shown by Hicks and Katz (1996), who emphasise the growth of non-university research. But Godin and Gingras (2000) note the diversification and decline of academic institutions as two ditTerent things and opine that one cannot infer the lauer from the former as is implicitly done by Gibbons et al. rather they show that far from declining, university research is stable, and even growing. Academic institution is still at the heart of the system of knowledge production and various actors rely heavily on their expertise and knowledge. 131 In LundvaIr s view (1988, 1992), the role of demand and supply, i.e. market forces are important in determining the rate and direction of the process of innovation and firms are largely the carriers of innovation process.

97

This is observed in Gibbons (1998: 36) where he says that "the academic institutions

engaged in research will be able to synthesise collaboration and use of shared resources into

the heart of their value system. However to achieve this, a substantial re-organisation in

academic institutions will be required". 'Mode 2' is seen to focus more on the existing

network of knowledge disciplines, industries and national governments. According to

Etzkowitz and Leydesdorff (2000: lIS), 'Mode 2' is characterized as an outcome and

should be considered as an emergent system which essentially means that it builds its hyper­

network on the existing network 132. In 'triple helix', the privileged actor among others

(industry and government) is university. As per Etzkowitz and Leydesdorff (2000: 109), the

underlying model of 'triple helix' assumes an analytically different approach from the

national system of innovation (NSI) which considers the firm as having the leading role in

innovation 133, and from the 'Triangle' model of Sabato (1975), in which government is

privileged. Before we address the important role of academia as one of the main actors of

innovation system drawn from all these three networks, it is appropriate to briefly review

what these frameworks mean, and discuss some important features noted by leading experts.

3.2.1 National Systems of Innovation

A national system of innovation (NSI) has been defined by Freeman (1987) as " ...

the network of institutions in the public and private sectors whose activities and

interactions initiate, import, modify and diffuse new technologies", while Lundvall (1992)

defines NSI as "... the elements and relationships which interact in the production,

diffusion and use of new, and economically useful, knowledge ... and are either located

within or rooted inside the borders of a nation state.". Nelson (1993) defines NSI as " ... a

set of institutions whose interactions determine the innovative performance of national

firms". According to Patel and Pavitt (1994), NSI is constituted by " .. .the national

institutions, their incentive structures and their competencies, that determine the rate and

132 Also see Weingart, 1997; Godin, 1998 133 In neoclassical economics wherein the focus is on markets as networks in tenos of input/output relations among individual agents; focus of analysis by evolutionary economists has changed to firms as the specific and bounded carriers of an innovation process. The dominant view for NSI refers to the role of demand and supply i.e. market forces in detenoining the rate and .direction of process of innovation (as quoted in Freeman, 1982: 211). Since Etzkowitz and Leydesdorff (2000: 115) observed that innovation systems need to be considered as dynamics of change in systems of both production and distribution, they tried to explain that by bringing in government as a third sphere where trilateral networks and hybrid organisations (formed as a result of such network) are created, and social and economic crises could be addressed.

98

direction of technological learning (or the volume and composition of change generating

activities) in a country,,134

The concept of NSI is based on the assumption that understanding the linkages

. among the actors involved in innovation is the key to improving technology

performanceI35• Innovation and technical progress are the result of a complex set of

relationships among actors producing, distributing and applying various kinds of

knowledge (OECD, 1997). According to the studies undertaken, the innovative

performance of a nation depends largely on how the involved actors relate to each other as

elements of a collective system of knowledge creation and its usage. Actors involved in

innovation are primarily private enterprises, public research organisations, academic

institutes and the people within them. The linkages can take the form of joint research,

personnel exchanges, cross-patenting, joint publications and a variety of other channels.

In the early stages of NSI, Lundvall and Christensen (1999), citing Nelson (1988),

noted that the US-approach linked the NSI concept mainly to hi tech- industries and put

the interaction between firms, the university system and national technology policy at the

centre of the analysis. However, Freeman (1987) introduced a broader perspective that

took into account national specificities in the organization of firms, where he emphasised,

for instance, how Japanese firms increasingly used 'the factory as a laboratory'. In

Freeman's discussion of Japan, the key institutions he included were: government policy,

corporate R&D, the education and training system, and the structure of industryl36. The

'Aalborg approach' (Lundvall, 1985; Andersen & Lundvall, 1988) was inspired by the

analysis of national production systems pursued by the French structuralist school in ,-,

Grenoble. Here the production system was the basis of national systems of innovation and

it also emphasised on the institutional dimension137• However, Porter (1990) brought in

134 As per definitions in (OECD, 1997) 135 As per Lundvall (1992), a national system of innovation is constituted by institutions and economic structures affecting the rate and direction of technological change in the society .. .it must, for example include not only the system of technology diffusion and R&D system but also institutions and factors determining how new technology affect productivity and economic growth 136 Also see studies in the context of understanding the innovation systems in Japan: Freeman (1987), Odagiri and Goto (1996); Kneller (1999) 137 Definition of institutions is taken from Johnson (1988) theoretically either as nonns and rules or as materialised in the fonn of organisations

99

regimes of competition as important dimension of national systems wherein some of his

crucial ideas were inherent in the innovation system concept particularly on vertical

interaction and innovation as an interactive process that surface in his analysis of

industrial clusters. Lundvall and Christensen (1999) however focused on production and

human resource development system. The NSI-concept also gained much currency

through the publication edited by Freeman and Lundvall (1988) on small countries, in the

edited book on technic~l change and economic theory with contributions from Freeman,

Nelson, Lundvall and Pelikan (Dosi et aI., 1988) and later on through three books edited

by Lundvall (1992), Nelson (1993) and Edquist (1997)138. In Nelson's edited volume, the

innovation systems were studied in fifteen countries where it suggested that NSI is shaped

by factors such as size and resource endowments effecting comparative advantage at a

basic level. Nelson (1993: 508) also says that NSI tends to reflect conscious decisions to

develop and sustain economic strength in certain areas, that is, it builds and shapes

comparative advantage.

The systemic characteristic of innovation at other levels of the economy is evident

from the literature on 'regional systems of innovation' that has grown rapidly since the

middle of the nineties (Cooke, 1996; Malmberg and Maskell, 1997) and on the concept of

'sectoral systems of innovation' by Franco Malerba and colleagues (Breschi and Malerba,

1997 and Malerba, 2002).

The study of innovation systems and its application to developing countries is

recent and critical attempts are being made to evaluate performance of developing and

newly industrialized countries (See Kim, 1993; Krishnan, 2003, Gu, 1999; Sarma, 2003;

Abrol, 2003; Nath, 2003; Wong, 1996; Patrapong, 2002).

1}8 There have been quite a few critiques of the NSI framework, for instance, Edquist (1997:14), notes the systems of innovation approach is about the determinants of innovations, and not about their consequences (in terms of growth, quantity of employment, working conditions, etc). Further the functional boundaries of the systems are very vaguely defined. Neither are relations between variables described in a rigorous manner. Because of this, the system of innovation approach does not deserve the status of a 'theory' of innovation, but must rather be called a conceptual framework (Edquist 1997: 28-29). The other problem associated with system of innovation approach as per Edquist (1997) is that it partly neglects other kinds of learning than innovation processes such as R&D, learning-by-doing, learning-by-using and learning-by-interacting. This approach to a large extent neglects learning in the form of education which has been ignored by other researchers except Bengt-Ake Lundvall.

100

3.2.1.1 Academia as a Significant Actor in Innovation System

The literature on national innovation systems emphasizes the importance of strong

linkages among the various actors in improving national innovative and competitive

performance, and this emphasis (although addressed recently) applies in particular to

universities within national innovation systems. Nelson (1993) notes that universities are

being widely cited as a critical institutional actor in national innovation systems. Nelson

(1993: 11) observes that " ... universities play an extremely important role in technical

advance, not only as places where industrial scientists and engineers are trained, but as

source of research findings and techniques of considerable relevance to technical advance

in industry".

The importance of academic research institutions gammg recognition m having a

significant place in the national systems of innovation has been due to two factors. The

primary reason seems obvious that academic research has the potential to contribute to

innovation system in the form of technological innovations, new knowledge, novel

products, services etc. In addition to teaching and research the universities now have 'a

third task' with focus on their direct contribution to a more dynamic development of the

business sector (Lundvall, 2002). The other reason is more due to the external pressures in

the form of declining government monetary support, which allow academic institutions to

capitalise on their research and other intellectual assets. There are numerous evidences

that show such state of affairs. Cohen et aI., (1998) elucidates the situation of American

public research academic institutions, whilst Slaughter and Leslie (1997) explain the

situation in UK, USA, and Australia. Universities throughout the OECD also have been

affected by tighter constraints on public funding since 1970. Faced with slower growth in

overall public funding, increased competition for research funding, and continuing cost

pressures within their operating budgets during the past two decades, at least some

universities have become more aggressive and 'entrepreneurial' in seeking new sources of

funding (Mowery and Sampat, 2004).

101

Lundvall (2002) observes that the universities have become more directly involved

in market-driven processes and more exposed to competition from other producers of

knowledge. This, according to him, is occurring in a situation where knowledge

production is characterised by increases in the degree of internationalisation and

networking. He further elucidates that as universities open themselves up; there is a need

for changes in the institutional framework to ensure that the long-term, creative and

critical aspects of academic research can survive. But for him, it becomes important also

to consider the ethical and social dimension of universities' knowledge production in

order to support the long-term viability of the learning economy and that merely exposing

the universities to market processes is not tenable, neither for university nor for society:

This concern is parallel to several others (see Nelson, 2004; Lee, 1996; Bok, 1982, 1990;

Geiger, 1993). Lundvall, thus suggests the need for a strategy of diversification and

differentiation of knowledge production, both internally, within university, and between

different kinds of organisations engaged in knowledge production. This, according to him,

might be the only way to ensure simultaneous interaction with and rapid adaptation to the

surrounding environment on the one hand and the further development of the university's

classical responsibility as a respected 'central bank of reliable knowledge' on the other

hand.

Mowery and Sampat (2004) also observe that rather than 'ivory towers' devoted to

the pursuit of knowledge for its own sake, a growing number of industrial-economy and

deVeloping-economy governments seek to use universities as instruments for knowledge

based economic development and change. In case of Japan (Odagiri, 1999) argues that

universities did play an important role in Japan's industrial and technological development

since the Meiji Restoration of 1867. More recent works in this context are from Kondo

(2004); Sakamoto and Kondo (2004). In the case of other Asian countries there are studies

from Wong Poh Kam (1996); Sharif and Baark (2005) and Kim (1993) among others.

Sharif and Baark (2005) argue that the university sector is likely to be the main public

actor in the innovation system, even if current initiatives are likely to increase the number

of government-sponsored research institutes serving specific sectors.

102

With academic institutions making an impact in the national systems of

innovation, it is important to know and understand the kind of role they play, the factors

on which their role differ and how crucial has this role been in different countries.

Although universities fulfil broadly similar functions in the innovation systems of most

industrial and industrializing economies, the importance of their role varies considerably,

and is influenced by the structure of domestic industry, the size and structure of other

publicly funded research performers, and numerous factors. Universities play

important roles in the "knowledge-based" economies of modem industrial and

industrializing states as sources of trained "knowledge workers" and ideas flowing from

both basic and more applied research activities (Mowery and Sampat, 2004). The limited

studies that have been done show that in the present times, the universities are expected to

contribute directly to the creation of new products and services particularly in the field of

biotechnology, and related life science fields, where there has been a dramatic shortening

of the time from scientific breakthrough to commercial use. Similar but somewhat less

dramatic changes have taken place in the fields of software and communication

technologies. New developments in the university .. industry relationships in these fields in

the US have increased the expectations to the contribution of European universities. For

universities to be direct contributors, to economy, there have to be large number of

changes in the university system in India (Ananth, 2006)139. He further notes that industry­

supported research is almost 40 per cent in the US as compared to India. lIT is as good an

example as any and research support from industry is about 10 to 15 per cent but it is

increasing.

Mowery and Sampat (2004) however place a caveat that conventional (and,

perhaps, evolutionary) economic approaches to the analysis of institutions are very

difficult to apply to universities, for two main reasons. First, because inter-university

'competition' has been limited in most national systems of higher education barring US

and UK and secondly because analyzing universities as economic institutions requires

some definition of the objectives pursued by individual universities. They further observe

that even if academic institutions, mostly in developed countries, have recently shown

139 Ananth (2006) also observes the need for public-private partnership (PPP) models and improving infrastructure.

103

their influence on the innovation system, there are not many stu~ies that give us a fair

understanding of the typical role of academic institutions in NSI. The development of

useful theoretical or conceptual tools or models for analyzing universities as economic or

other institutions within knowledge-based economies is seriously hampered by the lack of

data on the roles of universities that enable comparisons across time or across national

innovation systems.

Thus we see that universities world over are seen as instruments for knowledge

based economic development and change, they are getting directly involved in market­

driven processes, they are getting more exposed to competition from other producers of

knowledge and are seen to contribute directly to the creation of new products and services.

In other words, universities are increasingly seen as a significant actor in the national

system of innovation.

IITs in this context, we presume, are putting a strong foothold in creating a

knowledge research base that contributes to the innovation system. IITs as such in recent

years have come to playa significant part in the Indian innovation system. They are seen

as frontiers of science based innovations pushing them towards enterprising institutions to

be human capital provider and seed-bed of new firms. The presumption draws largely _ ,

from the current jimctioning of IITs which have a greater bearing on the historical ...---- - - ,. - -- - _.

developments _in IITs. This also implies that the adoption of MIT model. its typical .-------- .-

characteristics, and assistance of four nations have a notable role in supplementing the

IITs as an important actor in India's innovation system 140.

3.2.2 The New Production of Knowledge: 'Mode l' & 'Mode 2'

The second perspective in S&T policy studies that has come into sharp focus in the

last decade and half is that of Gibbons et al. (1994): New Production of Knowledge. The

authors explain two modes of knowledge production: "Mode l' and 'Mode 2'. In 'Mode

1', academia revolves around an autonomous university, self defined and self sustained

scientific disciplines and specialities, and the determination by specific peers of what does

140 Adoption of 'MIT model' by the liT system, their characteristics and features have been discussed in chapter 2.

104

and does not constitute science and truth. In 'Mode 2' knowledge is generated in the

context of application where industry plays an important role. The knowledge production

in 'Moue 2' is the outcome of a process in which supply and demand factors can be said to

operate, but the sources of supply are increasingly diverse, as are the demands for

differentiated forms of specialised knowledge and it is these processes or markets that

specify what is meant by context of application (1994: 4). The concept given by Gibbons

and his co-authors gained importance when the matter of expansion of higher education,

its massification and appropriation caught attention. This implied that with the spreading

out of higher education, the number of potential sites where knowledge was being

produced or where recognisably competent research was being performed also increased.

More simplistically, the mode of production that has the characteristics of disciplinary

research institutionalised largely in universities is termed as 'Mode 1', while 'Mode 2' is

characterised by transdisciplinari~y and institutionalisedcjn_a_Il19re_h<;J~XQge~o~_and­

flexible sociall/distributed system (Gib!>ons, 1998). Even though Gibbons et al. (1994: 3)

~learly distinguish between two modes of knowledge production, elucidating that while

'Mode-I' is disciplinary, characterised by homogeneity, is organisationally hierarchical

and tends to preserve its form; 'Mode 2' is transdisciplinary and is characterised by

heterogeneity" . .Qrganisationally is more heterar~hicaLand_is_transient (see Table 3.1). ,------- ----------------Within 'Mode I' new knowledge was produced primarily through disciplinary research

mainly in universities and academic research institutes. Such knowledge usually had

limited connection to societal requirements (Schmidt, 2003). According to Gibbons (1998:

31) scientific and technological knowledge production are presently pursued not only in

universities but also in industry and government laboratories, think tanks, research

institutions, and consultancy firms etc. The emergence of 'Mode 2' is believed to be more

profound and calls into question the adequacy of familiar knowledge producing

institutions, whether universities, government research establishments, or corporate

laboratories (Gibbons et aI., 1994: 1). Thus according to the authors, 'Mode 2' is more"

socially accountable and reflexive by way of having wider, more temporary and

heterogeneous set of practitioners collaborating on a problem defined in a specific and

localised context.

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Table 3.1: The Characteristics of Mode 1 and Mode 2

MODEl MODE 2 Knowledge is generated in an autonomous Knowledge is no longer produced only in university university settings but is also found increasingly in many

different loci, like government laboratories, industries and other think-tanks

Knowledge is produced in self-defined and self- Knowledge particularly in science is characterised by sustained scientific disciplines and specialities. interdisciplinarity (or transdisciplinarity), and 'Mode l' is disciplinary, characterised by plurality. 'Mode 2' is characterised by heterogeneity, homogeneity, is organisationally hierarchical and is organisationally more heterarchical and is transient tends to preserve its form. 'Mode l' is governed by peer group scientists who Knowledge is institutionalised in a more have a say in telling what constitutes science and heterogeneous and flexible socially distributed truth and what does not system Academia-industry interface is non-existent Knowledge tends to be produced in context of (Shinn, 2002) application; movement across established categories,

greater permeability of institutional boundaries, and a greater blurring of professional identities

Source: Compiled from Gibbons et al. (1994); Gibbons (1998, 2003)

. In his later contribution, Gibbons (2003) argues that the prevailing social contract between

society and science has been structured primarily on the basis of knowledge creation,

education and training. Universities have been established to undertake research and

teaching. They are in the business of knowledg~ cr:~~tion_and_the_tQmsf~he t

knowledge through ed~ation. From public funds available, universities generate new -knowledge in the form of scientific discoveries and educate people in the theories that

form the basis of those discoveries who in tum interpret and apply that knowledge in

practical situations such as in corporate or public research and development activities.

This is essentially a mode 1 orientation.

Building on mode 2 analysis, Gibbons (2003) goes further and argues that the separation

between the major institutions of society have b~~_ to bre~_.gown. He argues, for

example: "The once clear lines of demarcation between government, industries and the

universities and the technology of industry, between basic research, applied research and

product development, between careers in academia and those in industlY seem no longer

to apply. Instead there is a movement across established categories, greater permeability

of institutional boundaries, greater blurring of professional identities, and greater

diversity of career patterns. In some, major institutions of society have been transgressed

106

as institutions have crossed on to one another's terrain. In this, science has been, both

invading, but also invaded by countless demands from society" 14 I / ,,./''''-

Here one draws similarities with the 'triple helix' framework where reciprocal and

reflexive relationships among the three spheres of academia, industry and government

shape a conducive environment for innovations to occur. The difference however appears

to be in the role of academic research institutions. The key role of universities is to

advance knowledge and thus teaching and research functions become much more

significant unlike 'triple helix' where contributing to economic development is considered

equally important.

'Mode 2' framework claimed a new paradigm shift for science. According to the

authors, in view of the changing context and socialisation of knowledge, the process of

knowledge production and conduct of research has also changed fundamentally. Nowotny

et al. (2001) in Re-thinking Science took the argument of Gibbons et al. (1994) further

suggesting that the pattern of industrial research responsibilities _~etwe~n i~dust!Y and

government underwent substaIrtial change. This change was visible in industry -------------- -" --invol~ment in the development of national research programmes to ensure a prominent

place in national economic objectives. According to Shinn (2002: 600), the argument is

that the way in which scientific knowledge, technical practises, industry, education and

society at large are organized and function today lies in sharp contrast with the

relationships in earlier times. Shinn (2002) further says that by contrast, 'Mode 2'

knowledge production perceives the weakening or collapse of the modern university, the

disappearance of scientific disciplines and the atrophy of peer control over the direction

and content of research programmes. 'Mode 2' science is characterised by

interdisciplinarity, by the fluent movement of short tenn task force teams of experts to

problem domains and by the primacy of social and economic problems in establishing

what spheres of knowledge should be developed.

As per Shinn (2002), New Production of Knowledge lacks the methodological

motor that is necessary to drive any research programme forward. This approach lacks a

141 As quoted in Howard (2004: 20)

107

theoretical referent. Shinn (2002: 603) goes to the extent of saying that "the nucleus of

New Production of Knowledge is located in a single voiume, in which are expressed

claims about the demise of universities, scientific disciplines and academic laboratories

and rise in interdisciplinarity, economically and socially relevant research themes, and the

appearance of perpetually fluid business linked research task forces in the framework of a

new kind of socially useful epistemology". Here Shinn (2002: 600) also argues that there

is allegedly no interaction between academia and industry. One should however note that

much of these criticisms were apparently addressed later by Gibbons (1998, 2003). The

issue of source of new knowledge (which is developed in the context of application) has

remained in the core of the discussion.

It has been widely appreciated that specialist knowledge which is new be it in the

form of technological innovation or know-how is often a key factor in determining a

firm's comparative advantage. It is argued that specialised knowledge comes at a premium

but acquiring it is difficult and often exceptionally expensive for individual firms to

replicate in its entirety in-house. Thus the firms resort to collaborative arrangements that

involve academia, government and other firms. As it is also understood that markets are

dynamic and knowledge plays a crucial role, the parallel expansion in the numbers of

knowledge producers on the supply side and the expansion of the need for specialised

knowledge on the demand side are creating the conditions for the emergence of a new

mode of knowledge production. Thus according to Gibbons et aL (1994), the new mode

has implications for all kinds of institutions-whether academic institutions, government

research organisations or industrial laboratories-all those who have a stake in knowledge

production. The emergence of markets for specialised knowledge implies that for each

institution type, the strategies are different although the ways and degree of adopting

changes in order to accommodate or create new knowledge may vary. Gibbons (1998: 33)

observes that some firms have taken on the organisational attributes of universities.

The above discussion possibly gives an inkling that 'Mode 2' is in contrast with

'Mode I', but Gibbons clarifies that the former is an offshoot of the latter (1998: 33). He

states that 'Mode 2' is not supplanting but rather is supplementing 'Mode 1'. Though

108

some of the cognitive and social norms typical to 'Mode 2' contrasts sharply with deeply

held beliefs about how reliable theoretical and practical knowledge are generated, Gibbons

elucidates that they should not for that reason be regarded as either superior or inferior to

those operating in 'Mode l' rather they simply stand unlike.

However, for 'Mode 2' to realize a dominant place in the knowledge production

system, the proponents of this concept observe that there are several challenges before it.

The government would have to create national institutions that would require them to be

de-centred, to be made more permeable. The policies from government would promote

change in this direction. The policy approach will require an integration of education,

science, technology, and competition policies into a comprehensive innovation policy

which is sensitive to the fact that knowledge production is socially distributedl42• Ziman

(2000) argues that Mode 2 (as Mode I) may also include traditional scientific values.

Howard (2004) differentiates the two modes of production as he brings the notion of

quality control. While quality control in 'Mode l' knowledge production is seen as

supporting a quest for truth, in "Mode 2', quality control may be seen as supporting a

quest for performance, outcomes and results.

There are researchers who claim that there is little evidence that 'Mode 2' as a

concept is new (see David et al. 1999). They place their debate on their understanding that

'Mode 2' has always existed and is a complement to publicly funded research although the

intensity of knowledge being produced at different sites has intensified particularly during

the 1990S143•

3.2.2.2 Academic Institutions in 'Mode 2'

The 'Mode l' gave much more importance to academic institutions wherein

Gibbons (2003) specifically observe that universities are in the business of knowledge

creation and the transfer of the knowledge through education. The publicly funded

141 According to Gibbons (1999), in Europe, particularly, national policies that will enhance the potential of national institutions need to be developed in concert with those of the European Union 143 To support this Godin & Gingras (2000) observe that the share of Mode I in knowledge production has increased.

109

universities generate new knowledge in the form of scientific discoveries and educate

people in the theories that fonn the basis of those discoveries who in turn interpret and

apply that knowledge in practical situations. The emergence of a new knowledge

production system in the fonn of 'Mode 2' has implications for organisation of both

teaching and research functions within higher education institutions. According to

Gibbons (1998: 35), " ... perhaps the most difficult adjustments that universities will have

to make derive from the fact that knowledge production is becoming less and less a self­

contained activity". He says that because of the complexity of the questions that are

addressed and the costs involved, research is increasingly getting dependent on sharing of

resources whether financial, intellectual or physical with a broad range of institutions, not

only with other academic institutions. The academic institutions engaged in research will

be able to synthesise collaboration and use of shared resources into the heart of their value

system. However to achieve this, a substantial re-organisation in academic institutions wifl

be required. But to probe further, would this mean that there will be a shift from a culture

of science to a culture of research and will this culture of research, which presumably will

be oriented towards application and problem solving, will have its own structural

organisational imperative?J44 The author believes that the universities big or small are now

confronted with the challenge of how to accommodate themselves to the emergence of

distributed knowledge production system. In the contemporary period, leading edge

research has become more participatory and the solution for which would be expected

from teams comprising of several experts in different organisations.

'Mode 2' concept assuredly is consistent with some characteristics of modern

innovation systems, notably the increased inter-institutional collaboration that has been

remarked upon by numerous scholars. But· this concept's claims that the sources of

knowledge within modern innovation systems have become more diverse do not imply

any decline in the role of universities as fundamental research centres. Studies like Hicks

and Hamilton (1999) and Howard (2004) support the 'Mode 2' assertion that cross­

institutional collaboration and diversification in knowledge sources have grown, but at the

144 If we look at the work of Latour (1998), where he distinguishes the culture of science with culture of research, we tend to locate the above discussion in seeking answer to the question - whether a culture of research is better than a culture of science in serving the needs of developing societies. This issue however is not the focus of this thesis.

110

same time studies for instance Mowery and Sampat (2004); Godin and Gingras (2000)

indicate no such decline in the role of universities. Implications of all these issues remain

ambiguous as it remains unclear if 'Mode l' is substituted by 'Mode 2' or if they co-exist.

As per Etzkowitz and Leydesdorff (2000: 116), the so called 'Mode 2' is not new; it is the

original format of science before its academic institutionalisation in the 19th century.

'Mode 2' represents the material base of science, how it actually operates. The authors

further explicate that 'Mode 2' is a construct, built upon that base in order to justify

autonomy for science, especially in an earlier era when it was a fragile institution and

needed all the help it could get.

From the above discussion and understanding of 'Mode 2' framework, it is

observed that the once clear lines of demarcation between government, industries and the

universities and the technology of industry, between basic research, applied research and

product development, seem no longer to apply and instead there is a movement across

established categories, with greater permeability of institutional boundaries and greater

blurring of professional identities~e also understand that knowledge plays a crucial role

in a dynamic market environment. With parallel expansion in the numbers of knowledge

producers on the supply side and the expansion of need for specialised knowledge on the

demand side, the new mode of knowledge production has implications for all kinds of

institutions-whether academic institutions, government research organisations or

industrial laboratories-all those who have a stake in knowledge production. For

universities engaged in research, the willingness to synthesise collaboration and use of

shared resources will require substantial re-organisation within them. The challenge before

universities will be to figure out how to accommodate them to the emergence of

distributed knowledge production system . . For fITs, in this context, the question that we ask is whether the knowledge

production in 'Mode 1 ' has been eclipsed by the new mode 'Mode 2' in all the five fITs?

Whether knowledge produced in fITs is characterised by interdisciplinarity and plurality

and if it is transient? If the knowledge that is being produced in fITs is done in the context

of application?

III

3.2.3 The Triple Helix Framework

Over the last decade, 'triple helix' has emerged as a theoretical perspective in the

context of changing structure of universities and it is projected as one of the important

strategies of innovation studies. In the 'triple helix' framework the interaction among

university-industry-government is claimed to be the key to improving the conditions for

innovation in a knowledge-based society. In 'triple helix', industry is a member as the

locus of production; government as the source of contractual relations that guarantee

stable interactions and exchange; and university as a source of new knowledge and

technology. Although the 'triple helix' originated as a model of discontinuous innovation

in the U.S., based on networking among institutional spheres, it has also been utilized to

integrate disconnected resources in collapsed innovation systems and to enhance

incremental innovation in developing countries (Etzkowitz, 2003). The construction of a

'triple helix' includes the creation of institutions for the production and transmission of

knowledge; a consensus building process through which potential partners come together

to collectively identify niches and design organizational mechanisms to realize an

innovation strategy.

Thf,! growing literature on 'triple helix' framework places university as the

knowledge producing and disseminating institution, that plays a central role in innovation,

more so in technological innovationl45• As per Etzkowitz and Leydesdorff (various years),

'triple helix' thesis holds that university is increasingly central to discontinuous innovation

in knowledge based societies, superseding the firm as the primary source of future

economic and social development. 'Triple Helix' framework contends that university can

play an enhanced role in innovation and that this would increasingly be in the case of

knowledge based societies and more specifically in those industries where innovation is

more knowledge based (Etzkowitz & Leydesdroff, 2000). The Triple Helix argument is

that "as knowledge becomes an increasingly important part of innovation. the university

145 Triple He!!x conferences are held once every other year at different places across the globe on different themes. First conference was in 1996 at Amsterdam; second one at Purchase, New York in 1998 followed by Rio-de·Janeiro in 2000. Fourth in Copenhagen & Lund in 2002, fifth at Turin, Italy in 2005; sixth in 2007 at Singapore, while seventh is scheduled in 2009 at Glasgow.

112

as a knowledge producing and disseminating institution plays a larger role in industrial

innovation ... in a knowledge based economy, the university becomes a key element of the

innovation system both as human capital provider and seed-bed of new firms" (Etzkowitz

et al., 2000: 313)

The triple helix model comprises of three basic elements: (1) a more prominent

role for the university in innovation, on a par with industry and government in a

knowledge-based society; (2) a movement toward collaborative relationships among the

three major institutional spheres in which innovation policy is increasingly an outcome of

interactions among the spheres rather than a prescription from government or an internal

development within industry; (3) in addition to fulfilling their traditional functions, each

institutional sphere also "takes the role of the other" operating on a y-axis of their new

role as well as an x-axis of their traditional function. The triple helix model posits that

universities in transitional and developing countries take a leading role in catalysing

regional growth spaces (Etzkowitz, 2003).

Firms, academia and government each have their distinctive purpose and mission

and continue to perform their original functions. As they interact, each sphere is

transformed by 'taking the role of the other'. Government supports entrepreneurship

through chances in the regulatory environment, tax incentives and provision of public

venture capital. Academia is a source of firm-formation in addition to providing trained

persons and support to existing firms.

Rather than only serving as a source of new ideas for existing finns, universities

are combining their research and teaching capabilities in new formats to become a source

of new finn formation, especially in advanced areas of science and technology (Etzkowitz,

2003). Further, an industrial penumbra arises around universities as they become involved,

often in a leadership role, in regional coalitions for economic and social development.

Interaction among university-industry-government is the source of the origin and/or

development of incubator movements, interdisciplinary research centres and venture

capital, whether private, public or social (Etzkowitz and Zhou, 2006). However with the

passage of time and subsequent changes in the university-industry and government

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systems, the Triple Helix thesis has also gradually transformed. For instance the dqminant

role of academia in achieving innovation is now seen to accommodate such an approach

and intensity wherein even industry or government can take the lead to attain innovation

(Etzkowitz and Zhou, 2006: 79).

The 'triple helix' model contends that as innovation moves outside of a single

organization, lateral relationships across boundaries, rather. than hierarchical bureaucratic

structures, become more important 1 46. As per Etzkowitz and Leydesdorff (2000: 113),

innovation systems and the relationships among them are apparent at the organisational,

local, regional, national and multinational levels. The interacting sub-dynamics, that is,

specific operations like markets and technological innovations are continuously

reconstructed yet differently at different levels. The sub-dynamics and the levels are also

reflexively reconstructed through discussions and negotiations in the triple helix. In order

to explain the observable reorganisations in university-industry-government· relations, one

needs to transform the sociological theories of institutional retention, re-combinatorial

innovation, and reflexive controls (Etzkowitz and Leydesdorff, 2000: 112)147.

Emergence of Triple Helices

Triple Helix studies arose from analysis of the university-industry 'double helix'

and the realization that the government was an essential part of the innovation equation;

even when it was suppressed for ideological reasons or given too great a weight because

of political exigencies (Etzkowitz and Zhou, 2006). The authors observe that the topic

morphed from university-industry to university-industry-government relations a decade -----~ .

'ago, to t~ into account the predominant role of government in structuring these

relationships in some societies and its relative absence in others. It is worth mentioning

the claim as said in (Leydesdorff and Etzkowitz, 2001) that the 'triple helix' model

improves on the 'national systems of innovation' model by declaring "governance" as a

variable since the different levels of government (European, national, regional, and local)

146 The discussions at the 4th Triple Helix conference focused on the mle of universities in shaping new innovation environments for both entrepreneurial initiatives and public participation. The thought behind is that formulation of public demand for technological innovations rriay hel;> to stimulate the transition to an increasingly knowledge based economv. 147 A Triple Helix where each strand relates to other two can be expected to develop an overlay of communications networks, and organisation among the helices.

114

can be studied in a coherent framework. Further, the 'triple helix' shares with 'Mode 2'a

focus on a dynamic overlay of negotiations and alliances between and among the

institutional carriers of the overlay.

Figure 3.1: An etatistic model of university-industry-government relations or TH-I, (reproduced

from Etzkowitz and Leydesdorff, 2000: Ill)

The 'triple helix' model for innovation emerges from different societal starting points but

converges to a common format (Etzkowitz, 2003). First there is Triple Helix- I (TH-I), in

which the state encompasses academia and industry and directs the relations between

them. This model was evident in the erstwhile Soviet Union, Eastern European socialist

countries as well as in France. Weaker versions of TH-I was found in many Latin

American countries and to some extent in Scandinavian countries such as Norway

(Etzkowitz and Leydesdorff, 2000).

The TH-I model was a visible framework before the mid 20th century, as the

government played a dominant role in innovations. During the same time in the late

1960s, as a development strategy for countries with weak industrial sectors, an Argentine

physicist and science policy analyst, Jorge Sabato, developed a triadic innovation model in

which government was expected to take a leading role in promoting high-tech

development projects, especially in areas of national security, and bring together the

115

resources to realize objectives. Sabato later in his study (1975) and with Mackenzie

(1982), further elaborated that in his 'Triangle model', the universities typically played

only a supporting role, primarily in providing training to persons to work in the state

bureaucracies, other large organizations and traditional professions. Although during the

socialist era, research and production were formally linked by intemiediary organizations,

the focus of government was on quantity production, not qualitative innovation. Thus

mass production became popular despite the fact that the bureaucratic structures and

controls were an impediment to introduction of local inventions through technology

transfer (Etzkowitz, 2003). Despite having an inefficient system for organizing technical

change, the process of exchange was dominant across boundaries informally, taking place

laterally rather than going through the official planning process. From a stringent and

regulatory phase where government was powerful, the transition busted the hierarchical

structures to give way for government, industry and academic spheres as independent

entities or the TH-II.

At the time of former Soviet Union, SInce innovation was discouraged rather than

encouraged, TH-I is largely viewed as a failed developmental model (Etzkowitz, 2003).

The second Triple Helix or TH-II model comprises of separate institutional spheres where

government, university and industry operate apart from each otherl48•

Figure 3.2: A 'Iassiez-faire' model of university-industry-govemment relations (reproduced from

Etzkowitz and Leydesdorff, 2000: Ill)

148 The linkages among the three spheres were supposed to behave in this manner in the US

116

TH-III consists of overlapping institutional spheres; each taking the role of the other and

with hybrid organizations emerging at the interfaces. In one form or another, most

countries and regions are trying to attain some form of TH-IU, with its university spin-off

firms, tri-Iateral initiatives for knowledge based economic development and strategic

alliances among firms, government laboratories and academic research groups.

Figure 3.3: The Triple Helix Model (TH-III)

Trilateral Networks & Hybrid Organizations

[reproduced from Etzkowitz & Leydesdorff, (2000: 111)]

Graduating from TH-II, the third version of triple helix evolved after observing a

lot of development in the innovation system. According to Etzkowitz (2003), the ability to

advance within and across technological paradigms might be conceptualised as occurring

within three 'growth spaces': knowledge, consensus and innovation. Here he explains that

knowledge space provides the epistemological source for technological development;

consensus space denotes the process of getting relevant actors to work together, while

innovation space indicates an organisational invention that can enhance the development

process.

Etzkowitz and Leydesdorff (2000: Ill) observed that TH-lII IS generating a

knowledge infrastructure in terms of overlapping institutional spheres, with each taking

the role of the other and with hybrid organisations emerging at the interfaces (see figure

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3.3). Such reciprocal relationships among the three entities are claimed to be instrumental

in creating and strengthening the innovative capacity of a country and contributing to its

economic development. The 'triple helix' model can be understood in terms of the role of

respective institutional spheres where entrepreneurial university acts as a push force

through knowledge and technology transfer, state plays the role of a combination of

pull/push through its regulatory activities and financing schemes, while industry acts as a

pull force to helix

Etzkowitz (2003) observes that the 'triple helix' of university-indus try-government

relations is emerging as a common format that transcends national boundaries. Such

format is seen in joint projects where strong interrelations subsist in hybrid formats seen to

embody elements in two or more institutional spheres whilst preserving relative autonomy

of their respective sphere. When we typically observe the development of hybrid

organisations such as incubators, interdisciplinary research centres and venture capital

firms whether private, public or social, the source of such formations lie in the interaction

among university-industry-govemment spheres. These organizational innovations are as

important to the flow of innovation as technical advance (Etzkowitz et al; 2005). Here we

draw parallel with such organisational as well as institutional formations in IITs that are

significant in nurturing innovations in India. However, we also need to note that such

hybrid organisations are not seen in India where IITs are one of the actors in the trilateral

network.

However, much criticism and genuine concerns came from different scholars with

respect to the structure of 'triple helix' framework suggesting missing links and actors in

the form of incorporating an additional sphere be it labour, venture capital, informal sector

or civil societyJ49. Nowotny et al. (2001) noted that ideally the role of citizens or in other

words, interaction with public as the fourth central actor, needs to be included in the

context of interplay between science and society. Etzkowitz and Zhou (2006) in response

to some of the criticisms elucidated that while in the 'triple helix' innovation model,

university-industry-govemment work together to achieve regional or national innovations

149 Much criticism came at the 5th Triple Helix Conference held at Turin, Italy when scholars like Giovanni Dosi, Paul David among others suggested changes. Similarly in the 6th Triple Helix C{)nference at Singapore, David Mowery, Charles David, Philippe Mustar, Venni Krishna among others debated on the appropriateness of the framework.

118

in science and technology, forming a relationship of mutual benefit among them; anyone

adapting this model can take the liberty to modify the analytical and normative

framework, to take local circumstances better into account. However, rather than adding a

fourth helix, it might be best to conceptualise 'triple helix' as a dual set of helixes or

'triple helix twins'. According to them, adding a fourth helix might cause the triadic

model to lose its creative dynamic but nevertheless an expanded concept is required to

incorporate a crucial missing dimension. To resolve this paradox, they proposed an

alternative university-public-government (yin) 'triple helix' as a complement to the

university-industry-government (yang) 'triple helix'. By creating a parallel interacting

axis, a critical element might be introduced into the model without losing the dynamic

properties of a tertius gaudens (Etzkowitz and Zhou, 2006:79)150. The complementary

templates of the 'triple helix' twins create a mechanism for reproduction and

transformation. The Yang 'triple helix' exemplifies the different forms of cooperative

arrangements among university-industry-government to induce innovation while the Yin

one of pUblic-university-:-government represents the dynamic of controversies over

technological innovations. The two helices operate in tandem. The university-industry­

government 'triple helix' works to promote innovation and growth while the university­

government-public one serves as a balance wheel to ensure that innovation and growth

take place in ways that will not be harmful to the environment and health. Hence

Etzkowitz and Zhou (2006) conceptualise that the interaction of the 'triple helix' twins

constitutes a social organisation that integrates a positive entrepreneurial dynamic into

civil society and caution that when helices are out of alignment, imbalances would occur.

Thus we observe that there has been a gradual shift in the 'triple helix' framework, right

from its conceptual development from a single to the most recent dual set of helices: the

'triple helix twins' of innovation and sustainability.

The 'triple helix'of university-industry-govemment relations is emerging as a

common format that transcends national boundaries. As this takes place there is a shift ,

from bi-Iateral to trilateral interactions from 'single' and 'double helixes' to university

industry-government joints projects like the land grant universities in the US, the research

ISO As per Etzkowitz and Zhou (2006: 82), Tertius galldells is the third person who takes advantage from a dispute between others or otherwise plays an intermediary role

119

schools program in Sweden and the incubator movement in Brazil. Whether starting from

statist or laissez faire regimes, the movement is to a midpoint of relative autonomy of

institutional spheres, on the one hand, and stronger interrelations and creation of new

hybrid formats embodying elements of two or more institutional spheres, on the other.

However, in order to analyse these developments and to guide the future growth of

relationships and interactions among the three entities, a new model of the relationship

among the institutional spheres and their internal transformation would be required. The

nature of such associations or linkages as suitable to local flavour and conditions is what . developing countries like India should look for in their pursuit of creating and nurturing

innovations. For the purpose of this study, the 'triple helix framework is being used and it I / is hypothesised that the university-industry-government related triple helix thesis may be~, partially applicable to the Indian context.

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3.3 Modes of Knowledge Production

In its seminal years, the university's existence hinged upon the performance of

their first mission of production, preservation and propagation of knowledge and culture.

The incorporation of research into the agenda of the university apart from teaching,

constituted the first major shift in its ideology. As we have already discussed, Humboldt in

the 19th century, developed a new paradigm of university in Germany where not only

teaching, but also research, was performed. Humboldt's fundamental assumption was that

the university should be the place where Wissenchaft (fields of pure scholarly learning)

would be cultivated. The universities were considered as one of the best places to carry

out research. In 'Republic of Science', Polanyi (1962: 67) highlighted this: " ... the only

justification for the pursuit of scientific research in universities lies in the fact that the

universities provide an intimate communion for the formation of scientific opinion, free

from corrupting intrusions and distractions. For though scientific discoveries eventually

diffuse into all people's thinking, the general public cannot participate in the intellectual

milieu in which discoveries are made. Discovery comes only to a mind immersed in its

pursuit. For such work the scientist needs a secluded place among like-minded colleagues

who keenly share his aims and sharply control his performances. The soil of academic

science must be exterritorial in order to secure its rule by scientific opinion (Polanyi 1962:

67)." Apart from university as an ideal place for research, Polanyi also argued for

autonomous government aided institutions which would have the freedom to set priorities

and decide on what was good science. The study by Bernal (1939) asked for strong

government intervention wherein allocation of funds to academic institutions would be

guided by weighing of social needs. Bush (1945) strongly advocated public funding of

science and supported basic research. In the post-World War II United States, a seminal

report Science - Endless Frontier (1945) by Vannevar Bush emphasized that innovation

starts with fundamental research as he proposed more funds to basic research J51• In other

words Bush was in a way advocating for the' linear model of innovation' w~ich postulates

151 Bush (1945: 18) uses the term basic research to be defined as --research perfonned without thought of practical ends"

121

that innovation starts with basic research, appends applied research and development and

ends with production and diffusion.

According to Godin (2005), the linear model of innovation is developed over time in three

steps: The first linked applied research to basic research, the second added experimental

development, and the third added production and diffusion. He further states that these

three steps· correspond in fact to three scientific communities and their successive entries

into the field of science studies and/or science policy, each with their own concepts. First

were natural scientists developing a rhetoric on basic research as the source for applied

research or technology; second were researchers from business schools studying industrial

management of research and development of technologies and the third were economists,

bringing forth the concept of innovation into the discipline.

There have been efforts to modify or replace the 'linear model' particularly with

respect to its impact. The alternative models suggest multiple feedback loops (Kline and

Rosenberg, 1985). There have been several critics of this model: considering them as

unsuccessful (see Rosenberg, 1994; Arimoto, 2002)

Kharbanda (1999) also opmes that while this 'linear model' had been quite

successful in the US (basing his argument on the lines of Vovakova, 1998: 210) this has

not met with much success in most of the developing countries including India and China.

While in India it was supplanted by an import substitution model during the 1960s and

1970s, which was only partially successful, in China the model operated in an ideological

environment where technology was considered as a public good which contradicted the

economics of innovation.

Thus academic institutions were promoted to carry out research in addition to their

teaching function. The universities responded to the developments and there were specific

studies undertaken on scientific communities. Bush (1945) argued for self-governing

scientific community, who could prioritise research activities and monitor their

orientation. Robert Merton (1973) in the form of CUDOS-communitarianism,

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universalism, disinterestedness, and organized scepticism-identified and laid out canons of

science for scientists. Merton had earlier also (1957) observed that the primary motivation

of university scientists is recognition within the scientific community. This to him comes

from publications in peer-reviewed journals, presentations at prestigious conferences, and

through the successful application and award of federal research grants. The knowledge

products that Merton talked about largely exist in an open space, accessible to all. The

above studies recognise science base as largely open, reigning and as the basis of

invention and innovation I52. Thus the universities were responsible for generating

knowledge which the welfare economists regarded as a public good, namely, one whose

value does not diminish as access increases (Samuelson, 1969). Economists often have

argued that keeping science open is the most effective policy for enabling the public to

draw practical benefits from it (Nelson, 2004). Open access permits many potential

inventors to work with new knowledge.

We find echoes of the above discussion in the vision statement of IITs indicated in

the Interim Report of Sarkar Committee (1946), and the findings of Nayudamma

Committee (1961) and Rama Rao Committee (2004). The priority is clearly on education

(teaching), followed by research and extension. Educational excellence is reflected in the

vision statements of all the IITs (see the vision at the time of establishment of IITs and the

vision in 2004 of the respective IITs in Appendix 3.1).

Getting into the specificities, we note that literature on modes of knowledge

production addresses multiple issues which involve different entities in the process: the

academic institutions as source of knowledge and their characteristics in terms of

organisation structure, personnel, culture etc; the knowledge products or objects of

transfer for instance publications, patents or other forms of IPR, scientific knowledge,

1;1 The more recent studies on recognition of 'open science' are by Nelson (1993,2004); (Pavitt, 1991, 1998, 2001) and Mowery and Nelson (1999). Ziman (1978) also notes that because the results of scientific research are laid in the public domain for testing and further development, the bulk of scientific knowledge accepted by the community is reliable.

123

technical know-how etc; and mutual knowledge facilitators like consulting, research

contracts, informal meetings, joint ventures etc. We discuss them in the next -section.

The sources of knowledge in this section are restricted to the involvement of ARIs

even though the 'Mode 2' institutions also comprise of industry in-house R&D,

government think tank organisations, national and private research laboratories. There are

several studies on institutional change and adaptation linked to economic and social

change (see Nelson, 1998; North, 1990; Cohen, Linda and Noll, 1998). Rahm et al. (1988)

examine the participation of university and government in terms of characteristics of their

respective research units to be involved in such knowledge production which have

commercial utility. Here they found out that involvement in knowledge production was

stronger for those research units who had diversity of research missions. The study by

Etzkowitz (1994), gives an account of the nature of faculty members who had an

entrepreneurial character. Based on the interviews conducted, Etzkowitz found that

considerable change in the norms of academic scientists and in institutional culture, led to

an environment which was much more conducive to industrially relevant work. The

establishment of new institutions on the foundation of embedded structures, culture and

given rules tend to redefine the relationships between involved institutions. An earlier

study by Lee (1996) involved interviews with faculty and administrators affianced in

academia-industry relations wherein he found strong support for faculty role in technology

based regional economic development and increasing faculty interaction with industry

scientists. The faculty were found to be less enthusiastic about business partnerships with

industry scientists.

The above discussion inspires the debate on why the academics are shifting their

research that is more industry oriented or in other words why there is a shift from basic to

applied research. Lee (1996) explains the development using two theories: the Social

Responsibility Theory (Bok, 1982, 1990; Geiger, 1993) and the Utility Maximization

Theory (Bell, 1993; Fairweather, 1989; Feller, 1990; Geiger, 1993). The Social

Responsibility Theory holds that the academics are engaged in the production of 'public

goods' and they have a social responsibility for national imperatives. Much of this we

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have discussed in the previous sections (on the lines of 'Humboldtian Model' and 'Mode

1 '). The Utility Maximization Theory, on the other hand, links institutional behaviour to

the need for research money. It views the present academic reorientation essentially as a

strategy to maximize on institution's revenue streams. The shift in university system to the

model university, which is inclined towards the utility maximization view and has a role

in economic development, has several consequences. Not only it is a new academic

function but it also transforms the professorial role even at the level of the universe of

discourse that faculty make.

Having discussed knowledge production both as a 'public good' and as having

'utility value' for generating revenue, there are studies that focus on the challenges and

concerns that need to be critically addressed on the issue of intellectual property rights

(IPRs) in both the categories. Nelson (2004: 463) observes that the outputs of scientific

research almost never themselves are final products, or even close, but have their principal

use in further research, some of it aimed to advance the science farther, some to follow

leads that may enable a useful product or process to be found and developed. The concern

is not with patents on the outputs of scientific research that are directly useful or close to

that, so long as the scope of the patent is limited to that particular use. Rather the concern

is about not hindering the ability of the scientific community, both that part interested in

advancing the science farther. and that pillt interested in trying to '!.~~lulOwl~ll1~c In ihl!

search for u~t!h>J rnniuotl tQ Work frl!t!iy wilh ana from new scientific findings. The

advantage of conducting research in academia lies in the fact that by experimenting in

basic sciences, one can test the proposed benefits of the research outcome without

engaging in full-scale operations. Thus, strong science enables the process of designing

and inventing to be more productive and powerful than it would be were the science base

weaker (Nelson, 2004: 458). Faculty who have been seriously involved in such knowledge

production that have commercial potential, describe their technologies at a certain level of

generality and do not get specific for the fear of potential intellectual property rights that

could be given away (Etzkowitz, 1996). Earlier faculty would have been willing to be

more open or perhaps to disclose their knowledge to a company as a consultant for a small

fee, but now their interaction with industry is carefully calculated based upon the

125

expectation that their university wishes to market that knowledge and/or that the faculty

member might themselves wish to form a company based on that commercialisable

knowledge (Etzkowitz and Webster, 1998).

At a general level of understanding the mode of knowledge production in IITs is

more likely to be influenced by Humboldtian values of achieving teaching and research

excellence and promotion of open research publications rather than market driven

commercialization of research, even though the latter assumes considerable significance.

Historically speaking, which we discussed in the previous chapter, the underwriters of IIT

have promoted these important institutions of higher learning as a process of national

building towards achieving technological self-reliance. Advancing knowledge and greater

emphasis on excellence in science and engineering graduate teaching are in many ways

expression of this national building exercise.

In the context of IITs, we presume that despite the institutional and organisational

reforms, and increasing faculty interaction with industry personnel, many faculty and

researchers would be less enthusiastic about business partnerships with industry. This

could be reasoned in the notion that academic institutions as sources of knowledge have

deep rooted institutional values and responsibilities to their operational sphere. Another

reason could factor the not so high yielding commercial activities in academia owing to

consuming considerable time and often involving considerable risks. This discussion thus

raises a hypothesis that IITs recognise the importance of open science and scrutinise their

efforts to protect their knowledge assets. Thus, knowledge production in IITs is by and

large driven by research publications compared to patents. This orientation of knowledge

production is no way seen be to detrimental to the mode of knowledge transfer in IITs.

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3.4 Modes of Knowledge TransferIS3

Knowledge or technology transfer as a concept is the movement of know-how,

technical knowledge, or technology from one organisational setting to another, further the

term is used to describe and analyse an astonishingly wide range of organisational and

institutional interactions involving some form of technology related exchange (Roessner,

in press as quoted in Bozeman, 2000). According to Sahal (1981), technology and

knowledge transfer are not separable-When a technological product is transferred or

diffused, the knowledge upon which its composition is based is also diffused. Without the

knowledge base the physical entity cannot be put to use, thus knowledge base is inherent

not ancillary.

In academic research institutes, sponsored research and industrial consultancy are

among the most important channels for knowledge transfer. There are literary

contributions on knowing the impact of knowledge transfer from academic institutions

particularly by consulting, and sponsored research (Cohen et al. 1998; Mansfield 1995;

Zucker et al. 1994, 1998). Mansfield (1995) finds that university researchers who receive

research grants from industry report that the problems they worked on in their academic

research are frequently or predominantly developed out of their industrial consulting-and

in many cases, the cited academic researchers' government-funded work stem from ideas

and problems they encounter whilst pursuing industrial consultancy. Goldfarb et al. (200 I)

observe that at times, consultancy is a very effective method of technology transfer.

However, as evidence suggests, they say, it is much more difficult to provide high­

powered incentives to encourage academic involvement in the commercialization of their

ideas when consulting is the only tool. Ananth (2006) observes that industry-supported

research is vital for better academia industry relations. In the US, there is almost 40 per

cent research support, while when compared with India and lIT as good an example as

any, the figure is about 10 to 15 per cent although it is increasing.

153 Here knowledge transfer and technology transfer are being used interchangeably as we are addressing academic research institutes that yield technical know-how and new technology as research output for commercialisation

127

While there are enOITIlOUS contributors to cross-national knowledge transfer

literature, which was the prevalent theme prior to 1980s, the increase in number of studies

involving knowledge transfer from academic research institutes has been substantial154.

One of the most important issues pertaining to transfer media is the influence of

intellectual property policies. There is a vast body of literature covering the concern. The

significant development is that legally it is now possible to protect (getting an IPR) some

of the results of basic research. In 1980, the US congress passed the Bayh-Dole Act which

strongly encouraged the universities to take IPR on their research outcomeIS5. After the

implementation of Bayh-Dole Act in 1980, there are studies on its impact and the changes

in public policy pertaining to technology transfer and competitiveness in the US (Rahm et

aI., 1988; Papadakis, 1994; Mowery et ai. 1999; 2001a; 2001b; Correa, 1994)156. In the

context of growing interface between academia and industry in India, commercialisation

of intellectual property in academic institutes has not been much emphasised by anyone

even though there are demands voiced for a legal instrument similar to Bayh-Dole Act in

India by Knowledge CommissionI57. In more recent work by Bhattachrujee (2008), the

intention of the Indian government is noted for its preparation to introduce legislation that

it hopes will reverse the traditional hands-off attitude at most Indian universities toward

commercializing the results of basic research.

Most of the literature on industrial impact of academic research and knowledge

transfer from university has focused either on the role of patents and publications in the

transfer processl58 (Adams, 1990; Henderson et aI., 1998; Jaffe et aI., 1993; Owen-Smith

154 Cross-national technology transfer primarily focus on technology transfer from industrialised nations to less developed countries. 155 The other legal interventions include the Federal Court Improvement Act of 1982, which created the Court of Appeals of the Federal Circuit and led to stronger IP protection, and the National Cooperative Research Act of 1984, which encouraged firms to participate in research joint ventures Markiewicz, \vww.faculty.haas.berkeley.edu/markiewilII050.pdf. 156 Similar laws came up in several countries for instance the Technology Licensing Organisations Law of 1998 in Japan. In Sweden, government policies and programs have encouraged universities to form -Holding Companies' to purchase intellectual property rights from professors. In 1997, the Swedish universities were given athird mission in the Higher Education Act, besides education and research, to support economic and social development and playa greater role in explaining academia to the broader public (see Etzkowitz et aI, 2005 ). Though there is no equivalent to the Bayh­Dole legislation in Brazil, a new law on innovation passed in 2004 has made it easier for faculty members to receive royalties and creative firms. 157 Knowledge Commission, Go I, 2007; Biospectrum, July 2005 15sThere has been much emphasis on patents and licenses due to accessibility of patent data that lends itself well to quantitative analysis

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and Powell, 2001). In their survey, Cohen, Nelson, and Walsh (2002) found that the most

important channel for knowledge transfer from ARIs or government labs is publication of

the research, followed by infonnal exchange, public meeting or conference, and

consulting. Patents were ranked as one of the least important transfer -channels. The study

by Pavitt (1998) also suggests that patenting by universities is not a potentially useful

measure of university research perfonnance. Cohen, Nelson, and Walsh (2000) in another

study highlighted that the most important pathway through which people in industry

learned of and gained access to what was coming out of public research was through

publications, and open conferences. Industry got most of its benefit from academic science

through open channels. There are studies that say that patenting complements publication

(Agrawal & Henderson, 2002) and also which say that patenting and publication help in

the creation of new finns (Zucker, et aI., 1998; Lowe and Gonzalez.;.Brambila, 2004).

Interestingly the 1980 trend for a more aggressive role for the State in supporting

technology transfer was not confined to US as can be seen in the study by Irvine et ai.

(1981); Crow and Nath (1990, 1992) and Fujisue (1998). Sampat (2006) study specifically

focuses on patenting and US academic research in the 20th century both before and after

the Bayh-Dole legislation. Few studies that have been done studying Indian academia­

industry interface emphasize that, analogous to what Zucker, Darby and Brewer (1998),

Siegel, Waldman and Link (1999) have found for the US, personal contacts are essential

for effective knowledge transfer (e.g., Chandra, 2003; Sengupta, 1999).

Mowery, Sampat and Ziedonis (2002a) in a study on university learning with

respect to patenting activity and other factors like influence ofTIOs; analyse the trends in

patenting characteristics by US universities during 1980s and 1990s. Their results indicate

that the importance of entrant institutions' patents improved during the given period

drawing a closer gap with incumbents. The authors conclude that a broader process of

learning based on spillovers among universities may account for the convergence in

importance between the patents of incumbent and entrant universities (also see Mowery

and Shane, 2002). University patenting and its effects on academic research in Europe has

also been studied by Geuna and Nesta (2006), where they explore the fragmentary data on

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the growth of university-owned patents and university-invented patents in Europe. The

outcome shows a surge in university patenting. However, the phenomenon remains

heterogeneous across countries and disciplines.

According to Kneller (1999), exclusive IPRs are particularly important for small

companies, which depend on exclusive control over technology to attract the capital

necessary for product development and commercialisation 159. A similar outcome was seen

in a study by Chandra (2003) that examined technology transfers from an engineering

institution (lIT Delhi). The study revealed that often it did not matter to industry if the

potential technology had an IPR or not, it only made a difference in case of technologies

in select sectors where competition was fierce.

Extending our hypothesis on the importance of open science in the previous

section, we state that the importance of filing for an IPR is well recognised by IITs in

select sectors like biotechnology, information technology, pharmaceuticals, and applied

chemistry while in other sectors embryonic technologies do seek protection.

3.4.1 Other Specific Modes of Knowledge Transfer

Just as knowledge production, knowledge transfer process also involves various

modes or channels of connectivity to users or clients of research from academic research

institutions such as: (a) the transfer channels (licensing, signing of agreements, equity

participation); (b) the intermediaries (technology transfer office, industry liaison agency,

contract research centres, sciencelresearch parks); and (c) other instruments.

(a) Transfer Channels (licensing agreements, equity participation)

Licensing has emerged as an important mode of knowledge transfer from research

institutions to user clients or industry in recent times. Several recent studies provide some

insights on the nature of university licensing (Jensen and Thursby 2001, Mowery et al.

2001 a, b; Siegel et aI., 1999; Thursby and Kemp, 1999; Thursby et aI., 2001). More

1,9 These become even more significant in certain industries, such as biotechnology and pharmaceuticals, where the costs of developing and proving the safety of new products are high whereas the costs of imitating final products are low moreover small businesses are fn:quently the test beds for embryonic university technologies.

130

recently and more so in the US, there is an attempt to comment on the growing policy

debates on Bayh-Dole Act of 1980, which gave the right to license inventions from State

funded research (Mowery et aI., 1999; Thursby and Thursby, 2002)160. The study by

Thursby and Thursby (2002) shows that changes in the direction of faculty research

appear relatively less important than other factors, such as the dramatic increase in the

propensity of administrators to patent and license faculty inventions. The authors find that

licensing growth has resulted largely from an increased willingness of faculty and

administrators to engage in licensing. Cohen et al. (1998, 2000) examine the relative

importance of the set of transfer channels from the perspective of the knowledge recipient

firms. Shane (2000) investigates the question of when it is best for a university to license

an invention by considering the effectiveness of different transfer channels subject to the

nature of technology and its appropriateness.

Feldman et ai. (2002) emphasise on the increased use by university licensors of

equity investment as a tool for technology transfer and commercialisation. The authors

explain the inter-institutional differences by developing a behaviour model in which the

use of equity is conditional on licensing experience, past performance, TTO operations

and the organizational structure of the university. Agreements in which a university takes

equity position in a company in exchange for providing the right to use university

intellectual property is becoming an emerging mechanism and the focus of interest of

many universities (Feldman et aI., 2002). Jensen and Thursby (200 I) argue that equity

investments not only provide the same development incentives as royalties but also

generate greater revenue.

(b) Intermediaries (technology transfer office, contract research centres,

science/research parks)

There have been very few studies to discuss, in any real depth, the role that an

industrial liaison office (or its equivalent function within the university system) can play

in the knowledge transfer process. The views from limited pool of experts in this area

160 Here one may also mention that a similar 1998 Technology Transfer Law in Japan does not alter the basic principle that inventors retain the right to patent their inventions; yet it gives them the option of assigning their inventions to TTOs but does not require them to do so.

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nevertheless provide much insight into the role of technology transfer office (TTO) in

academic institutes, which is a rather new phenomenon in India.

According to Webster and Etzkowitz (1991) a wide range of collaborative links as

well as intermediary agencies through which academic research can be commercialised

have developed. Apart from the traditional short-term contract-research relationship, joint

programmes between academia and industry or government research centres (Gluck,

1992; Blumenthal, 1992), regional technology transfer networks (Sheen, 1992) and

incubator facilities (Seigel et aI., 1999; Thursby et aI., 2001; Venancio, 2000) have grown

in the area of technology transfer from academia. However the extent to which these

changes herald an evolutionary shift in the form of linkages between academia and

industry has been debated in Peters (1987). Slaughter and Rhoades (1990) explore the

costs that these interactions involve.

Limited studies have been done on the role of ITO (Graff et aI., 2002; Etzkowitz,

2002; Teece et aI., 1997) but they are mostly based on studies done in large universities in

USA and Europe. Organisational innovations like technology transfer offices provide a

window on academic discoveries with commercial potential and a point of contact to reach

the academics who originated them (Etzkowitz, 2002). According to Rogers et al. (2000),

the diffusion ofTTOs in US was due to 1980 Bayh Dole Act; due to the growth of the bio­

technology and other life sciences industries and their reliance on academic research and

its resulting patents. Mowery et al (2001) attribute the rise in patenting due to the

strengthening of U.S. intellectual property rights, during the 1980s, which resulted from a

combination of judicial decisions that made life forms patentable.

The creation of TTOs has introduced organisational changes that have created

many new opportunities for technology commercialisation and have made academia­

industry relationships more transparent and efficient (Graff et aI., 2002). Academic

Scientists differ greatly in their interest in realising financial gains from their discoveries

and in their ability to pursue the practical implications of their research. Even if they do

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not have a pecuniary motivation themselves, TIOs can make arrangements to protect and

license discoveries on their behalf and that of institute (Etzkowitz, 2002).

The importance of having a separate unit, yet being a part of the institute has been

emphasised by researchers. Some studies specifically focus on professional aspects of

TIO. The skills necessary for successful technology commercialisation are largely tacit

and are developed through a process of learning-by-doing (Teece, 1981). As a result these

skills are'not sold effectively in markets (Teece et aI., 1997). According to Shane (2002),

the best solution for university technology commercialisation requires that economic

actors who have a comparative advantage in that activity should commercialise that

technology. He notes that on the average, the inventors of university technology do not

have a comparative advantage III technology commercialisation. Technology

commercialisation involves a set of skills-including identifying customer needs,

developing product concepts, designing products and processes, proto typing, and

manufacturing-that university inventors rarely possess. In the absence of problems in

market for knowledge, the licensing of inventions to those advantaged in technology

commercialisation provides a mechanism for allocating inventions to those actors who are

best able to commercialise them (Teece, 1980).

Debackere and Veugelers (2005) explore the role of TTOs in improving industry

science links. They explore the evolution of 'effective' university based technology

transfer mechanisms and analyse how the creation of appropriate decision and monitoring

processes within a TIO has brought about critical elements in fostering an 'effective'

commercialisation of the academic science base. One of the very few studies on assessing

the impact of organizational practices on the relative productivity of university technology

transfer offices is done by Siegel et ai. (2003). This exploratory study gives both

quantitative and qualitative evidence on the relative productivity of TIOs and suggests

that TTO activity is characterised by constant returns to scale and that environmental and

institutional factor explain some of the variations in performance. According to them

productivity may also depend on organizational practices. Their study reveals that the

most critical organizational factors are faculty reward systems, ITO

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staffing/compensation practices and cultural barriers between universities and firms.

Rogers, Yin and Hoffmann (2000) assess the effectiveness of TTOs at US research

universities and lay down the characteristics of universities that are relatively more

effective in technology transfer namely higher average faculty salaries, a large number of

staff for technology licensing, a higher value of private gifts, grants and contracts, and

finally more R&D funding from industry and federal sources. However there are many

myths associated with TTO but the reality is different (see table 3.2)

Table 3.2: Knowledge Transfer through a TTO/TLO MYTH REALITY Royalties are a significant source of revenue With exception of 'big winners' - licensing revenue

is small Quick return on technology investment is expected Most finns want quick time to market Firms are eager to accept new technology from Academia spawned technology is embryonic, and it academic research institutions requires investment and time Technology transfer office finds the licensee Inventor is the best source for leads to potential

licensees Source: CompIled usmg mputs from TTO/Industry liaison agencies at IITs/Websltes of MIT and Stanford

The use of Contract Research Organisation (CRO) as agenCIes for enhancing

technology transfer between academia to industry is a well-accepted norm especially in

the OECD countries. As per Webster (1994a), there are Public Sector contract research

organisations like German Fraunhofer Gesellschaft, lAGB; Dutch Toegepast Natuur­

Wetenschappelijk Onderzoet (TNO) as well as private CROs such as AEA Technology in

UK and the California based SRI International that are engaged in technology transfer

activitiesl61• Government of India initiatives in promoting academia-industry linkages and

by extension in facilitating commercialisation of technologies include setting up of

technology transfer organisations like the National Research Development Corporation

(NRDC); intermediaries like consortia to promote multilateral linkages and success rates

of joint projects and industry-university ceIls.162 On many occasions, consultants play an

161 There are other notable larger CROs such as MIRA, SIRA (specialists in optical, electronic and mechanical engineering) and Smith Associates (with strong defence links) in UK; Bertin in France; Centro Informazione Studi Esperienza CISE) in Italy; Batelle in USA. A IT Bell Labs, GTE Labs and Alcoa Laboratories are private corporations in USA, operating on behalf of both their parent company and industrial clients. 16~ Government initiatives also include setting up of programmes & policies: the Science and Technology Entrepreneur Park scheme (STEP) was initiated in 1984 by the National Science and Technology Entrepreneurship Board (NSTEDB) under Department of Science and Technology (DST). The Technology Information Forecasting and Assessment Council (T1FAC), an autonomous body under DST initiated the Home Grown Technologies pfCIgram which monitors and matches the available technologies in academia and nationai laboratories with the needs of industry. Programme aimoo

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important role in facilitating knowledge transfer (Bessant and Rush, 1-995). The role of

professional associations is also highlighted for instance Sandelin (2006) notes that

professional associations are relatively new in Asia as compared to the Association of

University Technology Managers (AUTM) which started in 1975 in the us. In India a

similar initiative has been started in 2005 in the name of Society for Technology

Management (STEM).

Science Parks as an institutional medium play an important role in technology

transfer but the studies are limited, for instance Felsenstein (1994) whi,Ie comparing 160

high technology firms in Israel, located both within and outside the science parks, found

that there was no direct contribution to innovation for firms located inside the science park

but the park did confer status and prestige to the firms which indirectly promoted

technology transfer. Macdonald and Joseph (2001) explore the technology business

incubator and science and technology parks scheme in Philippines. The authors critically

evaluate the scheme and show that because uncertainty plagued its implementation, so

what was achieved was more attributable to the determination of individuals than to

ambitions and conflicting policies. In India, Rao (2006) notes, many science and

technology parks have been established in various engineering colleges. ICICI has set up a

knowledge park in Hyderabad with (a) physical facilities (b) knowledge network with

RTIs, nCT and ICCB and (c) VC fund from ICICI, for technology incubation.

As we mentioned earlier that the establishment ofITOs in India is a relatively new

phenomenon, there are studies in India supporting the view. Basant and Chandra (2007)

observe that not all institutions seem to have an adequate knowledge base to participate in

knowledge based networking activity. Moreover, only a few of these institutions have

systems in place to undertake formal knowledge transfer. Mohan (2006) brings about the

functioning of TTOs operating in contrasting cultures of academia and industry and

further'notes that the TTOs in academia are not so successful. Citing the example of IISc

at Technology Self Reliance (PA TSER) initiated by Department of Scientific and Industrial Research (DSIR) provides partial financial support for R&D and design projects that are undertaken jointly by industry and academic institutelnationallaboratory. Technology Development Fund was created by the DST, which appointed a Technology Development Board to monitor, fund and support commercial application of indigenous technologies (See Kharbanda and Jain, 1999; Chandra, 2003).

135

Bangalore he observes that technology transfer without technology creation is of no value.

He further says "academics don't have proper exposure to the industry requirements and

as such do not extend their basic research activity for industrial applications". The other

reason is that as individual scientists can neither form the -groups themselves nor can

effectively interact with industries, the success in increasing awareness among academic

community to transfer their innovation is limited.

The lIT Review Committee Report, 2004 reported two distinct models that have

evolved in the IITs for fostering academia industry linkages: an internal cell completely

within the system and an autonomously governed industry-interface foundation. As per

the review committee chaired by Professor Rama Rao, the latter has certain advantages:

the relationships between the user agencies and the institution can be managed with

greater flexibility, because of its autonomous character, it does not depend on the IITs for

budget support other than the initial seed fund for establishment and is thus able to obtain

finances from wide-ranging sources. Furthermore, the autonomous centre can appoint

non-academic professionals without burdening the institution which allows better business

development and interface with industry.

Based on the above discussion, we hypothesise that the modes of knowledge

transfer and academia-industry relations in IITs is more likely to be influenced and

driven by the conventional routes of consultancy and sponsored research links with

industry compared to Triple Helix influenced mode of ITO based knowledge transfers.

Further in view of the organisational culture and practice in IITs, as also the professional

aspects of a traditional ITO (as e~plained above by Shane, 2002; Teece, 1980), we

hypothesise that the establishment of ITOs as an intermediate agency internally, and

having a pecuniary motivation is unlikely to play a significant role as a mode of

knowledge transfer.

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(c) Other instruments: government policy, subsidy, venture capital, market & non­

mal"ket factors, informal transfers)

There is enormous literature ,m this area emphasising on government policy,

market pull and market push strategies (Feller, 1987, 1997; Dalpe et aI., 1992; Gander,

1986; Baker et aI., 1967; Langrishet al. (l972); Myers and Marquis (1969); Utterback,

1974 etc.). Most of the studies, however, focus on government research laboratories and

the public sector's role in shaping demand and markets for technology. Azzone and

Maccarrone (1997) in their study on flow of scientific knowledge from academic institute

to small and medium enterprise in Italy, show that demand is influenced by a 'flexible

infrastructure' rather than a set of fixed, institutionalised resources and suggests that the

critical mass of demands for technologies and technical competencies in biomedical

industry is a primary factor in determining market impact and the success of technology

transfer. Goldfarb and Henrekson (2003) give a comparative account of policies that

influence commercialisation of university intellectual property in the US and Sweden. Di

Gregorio and Shane (2003) have empirically shown that intellectual eminence of

universities attracts venture capital, which is a substantial boundary in firm formation.

More often, universities organise networking events to nurture partnerships in the

financial, scientific, and technological field (Mustar, 1997). Nicolaou and Birley (2003)

also show that networks can aid the emergence of ventures by providing four significant

benefits namely, augmenting the opportunity identification process, providing access to

loci of resources, engendering timing advantages, and constituting a source of trust.

Avnimelech and Teubal (2006) give an account of industry life cycle model of venture

capital. The paper by Langford et al. (2006) analyse the attempts made by Canadian

government to encourage and measure commercialisation of university knowledge for

socio-economic improvement. The primary issues that emerge show that the emphasis is

on licensing and spin-offs and several important paths of knowledge flow are not

measured. Secondly, if the goals and incentives of the actors in the 'triple helix' are

skewed or misinterpreted by indicators, universities and firms may engage in

counterproductive activities. The authors suggest additional indicators to help prevent

, measurable dimension from becoming the policy driver to the detriment of overall goals.

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In most of the cases the technology transfer literature presumes that firms are the recipient

of technologies, there are specific studies addressing the government as the user of the

research outcome (Bozeman et al., 1978; Lambright, 1979; Doctors, 1981). On

effectiveness of transfer to recipients, there are studies done by Kingsley and Farmer

(1997); Kingsley et aI., (1996) that indicate that public regulations often strongly affect

technology transfer. Transfers are more successful between government source and

recipients.

In the Indian context, there are studies that highlight the government policies in

promoting knowledge transfer. (Gupta and Dutta, 2005) give a detailed account of

government initiatives through different departments like the science and technology,

scientific and industrial research, information technology and others. The authors note that

Government of India has created an impressive infrastructure (since the major thrust that

came in 1958 in the form of Scientific Policy Resolution) in terms of institutions and

R&D units; policies; and schemes for promoting knowledge transfer from academia.

There are other studies of similar nature, for instance while Srinivasan and Abhyankar

(2002) focus on national funding mechanisms for promotion transfer and management of

technology Chandrakant et ai. (1982) stress upon IITs and their industry interaction. There

are limited studies on Indian venture capital industry. As per Gupta and Dutta (2005), the

origin of modem venture capital in India can be traced to the setting up of a Technology

Development Fund (TDF) in the year 1987-88 through the levy of a cess on all technology

import payments. TDF was meant to provide financial assistance to innovative and high

risk technological programs. The other noted studies on venture capital are by Holt (1999)

and Mohan (2004) giving the nature and status of venture capital in India.

Many university discoveries are transferred informally. According to Kneller

(1999), the informal transfers occur in many ways. Professors consult with companies,

corporate researchers working in university laboratories communicate research results

back to their companies. Graduates find employment in companies. Another study by

Bozeman et al. (1995) focuses on the informal relations among scientists. The other

transfer media cumprises of training of personnel, who are instrumental in managing

technology transfer (Grosse, 1996, Hicks 1993).

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3.4.2 Studies on Success and Failure of Technology Transfer

Various studies on technology transfer have identified key factors that either

stimulate or stifle the technology commercialisation process. Even though most of these

studies have been carried out clearly looking at the technology transfer process from

national or public/private research and development laboratories to industry, they raise a

lot of issues and give much insight, when technology commercialisation takes place from

academic institute to industry.

The Science Policy Research Unit at the University of Sussex carried out Project

SAPPHO (SPRU, 1972), which identified key factors that distinguish innovations as

having achieved commercial success from those which have not. The study presumed that

innovation is a complex sequence of events, involving scientific research and

technological development, management, production and marketing and therefore

allowance must be made for multi~factor explanations rather than single factor

interpretations. The study comprised of examining 29 pairs of successful and failure cases,

17 in chemical and 12 in instruments industries. The results indicated a consistent pattern

of differences between success and failure in innovation, which can be summarized in the

following five statements:

User Needs: Successful innovators have a much better understanding of the user needs

conversely, the neglect of user needs or failure to address and interpret such needs in the

R&D work leads to the failure in innovation.

Marketing: Successful innovators pay much attention to marketing, whereas failures are

characterized by neglect of market research, publicity and user education and failure to

anticipate customer problems.

R&D Strength: Successful innovators perform the development work more efficiently, but

not necessarily more quickly. They eliminate technical defects from the product or process

before they launch it.

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Communication: More effective use of outside technology and scientific advice by

successful innovators is done, even though most of their development work is done in­

house.

Management Strength: The responsible individuals in the successful innovations are

usually more senior and have greater authority than their counterparts who fail. The

greater power is reflected in satisfactorily controlling the project, establishing effective

internal and external communication networks and integrating the project into overall

company strategy.

In the study by Doctors (1969), barriers in the process of technology transfer were

highlighted. According to him the possible barriers are insufficient mission orientation of

the technical personnel in most of the agencies, conflicting policies concerning legal rights

to patentable innovation and other proprietary data, institutional barriers to information

flow, vertical nature of institutions for transfer, low value being placed on the transfer

function by scientific and technological personnel engaged in federally sponsored R&D,

poor and antiquated methods of information & retrieval and poor understanding of the

process among several others. Based on a survey, Rothwell (1977) summarized the key

factors for an innovation to succeed, which included having good communication and

effective collaboration both at the inter and intra-firm level between institute and industry,

the use of careful planning and management techniques, having an organic and open

management style with both commitment and enthusiasm for each project, understanding

the influence of government assistance, being responsive to recognition of user needs,

ensuring the presence of important individuals, and paying attention to after-sales-service.

I

Several studies have examined the mechanisms that trigger an innovation and from

a review of those it was noted (Utterback, 1974) that 60-80 percent of important

innovations in different fields were in response to market demands (need-pull factor), and

the remaining 2040 percent had their origin from scientific and technological advances or

opportunities. Baker and Rubenstein (1 %7) postulated that two events are necessary

precursors for the generation of an idea for innovation. (i) need event, i.e. recognition of

the need, problem or opportunity which is perceived to be relevant to organizational

140

objectives; and (ii) means event i.e. recognition Df a means or technique by which to

satisfy the need, solve the problem or capitalize on the opportunity. From a survey of

innovations, they found that the. 'need event' usually occured prior to the 'means event'.

Studiesl63 have shown that only a small subset of invention disclosures generate any

commercial interest which further aid in technology transfer from university to industry.

The rule of the thumb in university technology transfer is that for every 100-invention

disclosures, 10 patents and 1 commercially successful product result (Blake, 1993).

Although studies have been done in India examining the cases of technology

transfer (Nath, 1988; Qureshi et aI., 1984; Subrahmanian, 1985; Desai, 1980; Morehouse,

1977) they are limited in number and are based on public funded research laboratories.

Morehouse (1977) noted that scientists in the laboratories were not sure about the

economic feasibility ofthe inventions before the research was performed.

Having discussed varied opinion on academia-industry interaction, the process of

knowledge production, knowledge transfer, their constituents, their influencing factors and

the theoretical frameworks, it would be imprudent not to discuss about the emerging

concept of 'entrepreneurial university'.

163 The studies include: Jensen and Thursby (200I), Mowery et al. (l999), Feller e! al. (2000). In a survey done by Jensen and Thursby it was evident that only about 12% of the licensed technology is ready for commercialization. The majority of licensed technology requires significant development work and ongoing cooperation by faculty to realize commercial success.

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3.5 Emergence of Entrepreneurial University

In recent years the concept of entrepreneurial university has come into sharp focus

in the literature on Triple Helix. As new technologies and science based innovation come

to play a significant part in the knowledge based economies, the role of universities is

drawing more and more attention. Together with TTOs, patenting and IPR regimes,

institutional and organisational measures to promote entrepreneurship, incubation centres

and spin-off firms come to characterise the emergence of entrepreneurial university. The

emergence of entrepreneurial university concept first in the US (Etzkowitz et aI., 2000)

perhaps made an aspiring normative form of organisation which has later spread to UK

and other countries of Asia such as Singapore, Hong Kong and China. According to

Etzkowitz (2005) and Clark (1992) an entrepreneurial university is emerging as a common

academic and economic development format in both advanced industrial and developing

countries. Etzkowitz and Zhou (2006) predict that entrepreneurial universities would play

a leading role in regional innovation and in encouraging start-ups. The other two spheres:

industry and government would play similar roles, the former would reorganise itself in a

network mode to be more receptive to external inputs and latter would develop

programmes cooperatively with the other actors to support enhancement of academia­

industry and the links between them. They say that the three spheres would act as a

common subject and cooperatively implement an economic growth strategy. In simple

terms Etzkowitz (2002), says that a new academic model-the entrepreneurial university is

being created as universities combine teaching and research with the capitalization of

knowledge.

, Having already discussed the characteristics of the 'entrepreneurial university' as

laid out by Etzkowitz et al. (2000) in the introductory section, wherein internal

transformations, interface processes, recursive effects and trans-institutional impacts

bring out the features of entrepreneurship in academia, there are yet other literature on a

wide variety of issues dealing with organisational, cultural, and economic matters related

to academic entrepreneurship and spin-off firms l64• An entrepreneurial academic strategy

164 See recent articles by Etzkowitz (2003a); Lehrer and Asakawa (2004) and Meyer (2003)

142

IS the capacity to mme research for use through an array of technology transfer

mechanisms that close the gap between invention and innovation (Owen-Smith, 2001;

Owen Smith and Powell, 2003 as quoted in Etzkowitz, 2005). According to Jacob et al.

(2003: 1556), entrepreneurial university is a term now being used to refer to universities

which possess a wide range of new infrastructural support mechanisms for fostering

entrepreneurship within the organisation as well as packaging entrepreneurship as a

productl65• Jacob et al. (2003) give an account of one Swedish university's ongoing efforts

. to develop an in-house system for commercialisation of knowledge that meets both the

traditional and new role of the university.

Tijssen (2006) apparently introduces a conceptual framework to conduct

comprehensive analyses of university's 'industrially relevant research' in relation to the

science based entrepreneurial orientation of university units. The caveat however is that

the study is restricted to research related activities, outcomes and impact and thus does not

include teaching, training and consultancy activities with a commercial value. The results

suggest that many structural factors determine academia-industry interactions and the

potential for entrepreneurial orientation. The connectivity indicators namely public-private

co-authored research articles and references (citations) within corporate research articles

to university research articles according to Tijssen appear to be of minor importance as

compared to a university's country of location and magnitude of its research activities in

industrially relevant fields of science.

Although there are studies on universities that are established for profit orientation

(see Ruch, 2001; Gose, 1999) there is a visible difference in their characteristics and that

of 'entrepreneurial universities'. 'For-profit' presidents (of such universities) resemble

traditional CEOs more than they do academic leaders. They are focused on setting and

implementing institutional strategy and especially on the managing of resources and

operation (Ruch: 109).

165 However this study does not focus on the latter part where phenomena such as courses in entrepreneurship and restructuring of the organisational structure of universities that would allow active promotion of entrepreneurship are dealt with

143

In the context of IITs, we therefore presume that the mode of knowledge transfer is

more likely to be manifested in varying forms ranging from conventional sponsored and

consultancy projects to the mode of Triple Helix and rise of entrepreneurial culture.

3.5.1 New Firms, Spin-offs and Incubators

Many scholars believe that as the scope of academic activities widen, academia is

able to make a greater and better contribution to the economic needs of the region. Not

only have these beliefs and perceptions strengthened the viewpoints of several people but

it has been increasingly recognised now that closer association with industry and

collaborative research especially in the new science-based industries, has proven to be a

steady source of entrepreneurship and fresh economic competitiveness, often leading to

the creation of new finns or spin-offs and contributing to the obsolescence of others.

The spin-offs are simply defined as the companies that evolve from academic

institutions through commercialisation of intellectual property and transfer of technology

developed within academic institutions. The outcome of a University Spin-off (USO) is

profit oriented firm formation and all current definitions are unanimous in this respect

(Carayannis et aI., 1998; Clarysse et aI., 2000; Klofsten et aI., 2000 as quoted in Djokovic

and Souitaris, 2004). Smilor et ai. (1990) have defined spin-offs as a new company that is

fonned (1) by individuals who were former employees of a parent organisation and (2) is

based on a core technology that is transferred from the parent organisation. As cited in

Djokovic and Souitaris (2004), the definition given by Smilor et ai. (1990) was broadened

by Nicolaou and Birley (2003) who noted that a usa includes: (l) the transfer of a core

technology from an academic institution into a new company and (2) the founding

member{s) may include the inventor academic(s) who mayor may not be currently

affiliated with the academic institutionl66• Also, Pirnay et ai. (2003) after systematically

analysing a number of different definitions of university spin-offs concluded to the

following: "University spin-offs are new firms created to exploit commercially some

knowledge, technology or research results developed within a university".

166 Radosevich (1995) has differentiated between inventor--entrepreneurs and surrogate--entrepreneurs who did not invent the technology but acquired the rights to commercialise it from the academic institution.

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There are studies which highlight the reasons for the fonnation of spin-offs. For

instance Samsom and Gurdon (1993) observe the need to resolve institutional tensions

which commercially orientated activity creates within the university, without radically

severing the protagonists' links to academia as one of the prime reasons. Stankiewicz

(1994: 102) interprets the fonnation of spin-offs as an attempt to create an institutional

space for activities which do not quite fit into the established structures of academia and

business; a space which would allow the scientists and engineers to preserve their

professional identities while acquiring new roles in the process of commercial ising

technology.

A few studies have focused on the process of academia spin-offs formation and

evolution. Ndonzuau et at. (2003); Vohora et at. (2004); Carayannis et al. (1998); Roberts

& Malone (1996) all of them typically describing the process with a number of phases.

Ndonzuau et al. (2003) identify four main process phases - that of business idea

generation from research; finalisation of new venture projects out of ideas; third phase of

launching spin-off finns from projects and finally strengthening the creation of economic

value 1 67. Vohora et al. (2004) on the other hand offer an evolutionary perspective on the

process of the spin-off phenomenon. They identify four stages, which these spin-offs

undergo during their fonnation, namely the research phase, the opportunity framing phase,

the pre-organisation, and the re-orientation before reaching onto the next stage, which

again comprises of four phases: opporfunity recognition, entrepreneurial commitment,

threshold of credibility and finally threshold of sustainability.

There have been an increasing number of literatures focusing on the role of new

finns as vehicles for commercialising university inventions but not many scholars have

voiced their opinion on spin-offs. However, these studies show a mixed opinion- some

good, some critical. For instance, Harmon, et al. (1997) point out that spinouts have very

little impact on the economy or job creation. Others like Tijssen (2006); Pries and Guild

167This study as per Djokovic and Souitaris (2004) did not offer much explanation of the progression from one stage to the other.

145

(2007) and O'Shea et ai. (2007) have positive attitude towards university

commercialisation activities and believe that "the economic development momentum thut

has been generated at institutions in recent years should be vigorously pursued in a

proactive manner" (Chrisman et aI., 1995 as quoted in Djokovic and Souitaris, 2004: 8).

Zucker et ai. (2002) focus on the role of scientific talent in the creation of

university start-ups when they argue that scientific ability is central to the founding and

performance of new biotechnology companies. They also examine the effect of the

scientific ability of biotechnology firm's founders on performance of new biotechnology

firms. They find that firms founded by "star scientists" outperform other finns even after

accounting for the location of these firms and the amount of venture capital they receive.

Landry et ai. (2006) addresses the issue of university researchers more likely to be

successful in creation of spin-offs. Their findings suggest that the traditional and

entrepreneurial versions of university research complement each other when one looks at

the resources mobilised by researchers to create spin-offs. Shane (2000) links the

formation of finns to intellectual property where he observes that the university faculty,

staff, and students are more likely to find firms so as to commercialise their inventions

when these technologies do not enjoy strong patent protection. He further says that non­

inventors are more likely to commercialise those inventions when patent protection is

strong. Shane and Stuart (2002) examine the related question of why some university

start-ups are more successful than the others. They observe that the magnitude of venture

funding is an important determinant of the likelihood of a successful Initial Public Offer

(IPO). Candel and Jaffe (1999) in their study on the impact of public research funding in

Massachusetts found that the spill-over effect from the new knowledge and new products

developed by academic and academically trained researchers had a considerable positive

long-tenn impact on the Massachusetts economy. Rothaermel and Thursby (2005)

investigate the research question of how knowledge actually flows from universities to

incubator firms and assess the effect of these knowledge flows on incubator firm-level

differential perfonnance. Mian (1996) goes one step further and assesses the value added

contributions of university technology business incubators to their new technology-based

tenant firms.

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The rising number of universities involved in commercialisation activities such as

licensing and spinning out have also been well reported and documented in several

surveys like the University Companies Association (UNICO) survey, Nottingham

University Business School Survey (NUBS) and the Association of University

Technology Mangers or the AUTM survey in USA. UNICO (2001) and AUTM (2002)

show that academic institutions in USA and UK are creating company spinouts at an

increasing rate. Mustar (1997) shows how French academics create hi-tech companies and

explores the conditions for success and failures. Bray and Lee (2000) observe that

spinning-out is a far more effective technology transfer mechanism compared to licensing,

as it creates 10 times higher income, and therefore argues that license positions are only

taken when "technology is not suitable for a spin-off company".

Apart from the academia driven efforts towards creation of spin offs, there are

market driven forces that have concerted the formation of firms. Empirical studies, not

necessarily pertaining to academic research, have correlated high technology firm

formation with research and development intensity (Cohen and Levin, 1989, Scherer

1980), and appropriability conditions (Arrow 1962, Levin et al. 1987, Nelson and Winter

1982) not to mention other crucial factors like capital accessibility, industrial

concentration, size of the firm and such factors. Lowe (1993) also provided a framework

of favourable market preconditions when he observed that spinout companies were most

likely to be formed when the availability of complementary assets were high to the

academic institution and/or to the inventor(s) and secondly when the technology used was

under strong legal and technical protection. He further elucidated that licensing

agreements are realized when availability of complementary assets are poor. Lowe also

argued that spinouts were more likely to evolve in emerging industries where

technological trajectories are still evolving and where innovation is radical. However

empirical evidence on this framework is still lacking. Djokovic and Souitaris (2004)

propose that the reputation of the university can be art important variable that affects the

licensing versus spinout decision. There are other factors as well that influence spin-offs

formation for instance the career-reward structure that academia puts forward for

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academics. Klofsten and Dylan (2000) have shown that barriers to taking temporary leaves

to start firms (which are common in USA) has made Swedish academics concentrate on

consulting which can be accomplished beside academic position. Olofson and Wahlbin

(1984 as cited in Djokovic and Souitaris, 2004) linked academic exodus with growth rate

of the firm, finding that spinouts with highest growth rates were the ones involving

academics who left the university.

Shane's (2002a) study of 134 start-ups from MIT revealed that direct and indirect

relationships of the spin-off creators with venture investors were more likely to receive

venture funding and were less liable to fail. His finding therefore advocates that social

capital endowments, through their impact on the fund-raising process, have long-term,

positive impact on the performance of new venture. Smith and Ho (2006) have studied the

performance of spin-off companies from Oxford University, Oxford Brookes University,

Cranfield DCMT at Shrivenham and its seven government-funded and privatised public

research laboratories. Their study shows that the number of spin.,.offs in Oxfordshire has

increased rapidly as the result of evolving national policy and the entrepreneurial culture

of the universities and laboratories. However the study also shows that academics and

scientists were already entrepreneurial in the 1950s, less so in 1960s but increasingly in

1970s and thereafter, particularly in Oxford University which at that time was the largest

generator of spin-offs in the region.

Lockett et al. (2003) show the importance of networks, at the level of academic

institutions. Vohora et al. (2004) investigate the development of university spin-offs and

show that these ventures face 'critical junctures' in terms of the resources and capabilities

that they need to acquire to progress to the next phase. For a successful spin-off the

authors identify four different 'critical junctures' that the ventures need to overcome

namely- opportunity recognition, entrepreneurial commitment, credibility and

sustainability. Without such availability of venture capital, and network second rank

universities cannot commercialise their intellectual property through firm formation and

cannot gain trust from venture capitalists due to their lack of spinout expertise. Thus, it

can be argued that second-rank academic institutions, which could be more involved in

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spinning out new ventures, are bounded to licensing due to their lack of ties to venture

capitalists and industrial partners.

There are no studies that exclusively study the impact of spin-offs in India, even

though there are quite a few articles related to success stories primarily at the IITs. For

instance Rao (2006) note that lIT Delhi has incubated and spun-off 7-8 technology-based

firms as commercial enterprises, while at another centre in lIT Mumbai, Society for

Innovation and Entrepreneurship (SINE) has facilitated the conversion of research activity

into entrepreneurial ventures. Success stories from the incubator include Herald Logic

which develops products in enterprise information, rule-based engine; Voyager2 Infotech,

which built a creative ideas portal; Myzus Technologies, which develops products and

services in the areas of wireless gateways and connectivity bridges.

In the light of the above discussion we hypothesise that IITs in recent years have

embraced or come to advance the concept of entrepreneurial university in parallel to the

dominant orientation of teaching and research excellence. T71is is primarily due to the

evidence of dynamic formations such as the technology transfer offices, intellectual

property policy, patent cells, rising sponsored research projects and industrial

consultancy assignments and more importantly the establishment of incubation units at

IITs. To be specific, we hypothesise that IITs seem to adapt the spin-off route to

commercialisation of R&D knowledge transfer much more than the mode of licensing and

royalty earning.

3.5.2 Indirect Spin-offs

There are numerous studies that have elaborated upon and analysed on the direct spin-offs

from academia. In this thesis we generate a scope for focusing on the indirect spin-offs

from academia primarily by taking academic entrepreneurs (read lIT alumni) as the unit of

analysis, linking the spin-off phenomenon with entrepreneurship theory on identification

of an opportunityl68. In other words the emphasis is on knowing those entrepreneurs who

168 For a similar concept see Shane and Venkataraman, 2000; Ardichvili et aI., 2003.

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have been alumni of an academic institute and have fonned companies or finns thus

contributing to economic and social development of the country. In one of the studies

assessing the contribution of people from IITs Saxenian (1999) notes that approximately

10 per cent of all start-ups in Silicon Valley be,tween 1995 and 1998 were by Indians,

most of whom had come from the lIT system. It has been suggested that the IITs have,

perhaps, produced more millionaires per capita than any other undergraduate academic

institution in the world. It is not surprising that most of the IITs' successful alumni credit

their alma mater with playing a foundational or leading role in their achievements (Murali,

2003).

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3.6 Concluding Discussion and Summary of Hypotheses

We discussed and raised issues about contemporary academic research institutes

increasingly seen to shift their functioning from being just a 'factory of knowledge'

addressing teaching and research to making contributions in economic development by

capitalising on their intellectual assets. We overviewed a number of related studies on

academia-industry interaction and discussed specific literature survey on knowledge

production examining knowledge products and their influencing factors. We also

discussed literature related to knowledge transfer - transfer channels, technology transfer

offices, success and failure factors, contemporary literature on start-up firms and

incubation units and finally on the emergence of 'entrepreneurial universities'.

One of the most important discussions in this chapter centred on the theoretical

frameworks for an inclusive understanding of the role of academic research institutes in

the system of innovation. Since we explored the literature on 'National System of

Innovation" 'New Production of Knowledge-Mode 2' and 'Triple Helix'; we have

attempted to conceptualise a framework which is suitable for IITs. We understand that in

order to analyse the developments and to guide the future growth of relationships and

interactions among the three entities (academia-industry-government as said in 'triple

helix'), a new model of the relationship among the institutional spheres and their internal

transformation would be required. The nature of such associations or linkages as suitable

to local flavour and conditions is what the developing countries like India should look for

in their pursuit of creating and nurturing innovations.

3.6.1 Situating the IITs in a suitable framework

The IITs have been in existence for over SIX decades making significant

contributions in terms of knowledge production, creating highly skilled, well educated

graduates and post graduates in engineering, science, social science and management l69•

These institutions have also played a consequential role in imparting quality teaching and

169 As has been discussed in the section on origin and development of IITs in the previous chapter, five lITs were set up in ten year span starting from 1951 but lIT Guwahati was set up as the sixth lIT in 1994 while liT Roorkee came into the lIT system in 200 I.

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research through exceptionally good faculty and staff. However, the involvement of -IITs

in making use of their intellectual assets for economic deVelopment and also for

generating revenue has gained considerable attention in the last one decade or so. Our

discussion on theoretical frameworks has evaluated the shift of the universities in this

direction worldwide and we relate these phenomena to the observations in IITs as a

representative set of higher ARIs (particularly in science and engineering) in India. The

inter-relationships and linkages that exist between these knowledge producing institutions

and users of the knowledge along with intermediary agencies are identified and portrayed

in the context peculiar to India. This context is based on India's higher education system,

industry linkages, government establishments, innovation capability, human resources and

the linkages with their foreign counterparts. From the literature on 'NSI' which has lately

emphasised on the role of universities as integral component of innovation system, we

may ask if IITs in this context are putting a strong foothold in creating a knowledge

research base that contributes in economic development and technical change. We may

also evaluate if IITs are seen as frontiers of science based innovations pushing them

towards enterprising institutions that compete from other producers of knowledge? The

discussion on 'New Production of Knowledge or 'Mode 2' further incites issues which

raise important questions whether knowledge production in 'Mode I' has been eclipsed by

the new mode 'Mode 2' in all the five IITs? Whether knowledge produced in I1Ts has

been characterised by interdisciplinarity and plurality and if it is transient and more

importantly if knowledge is being produced only in the context of application?

Since we have said that university lies at the centre of analysis in 'triple helix', this

study draws much more theoretical understanding from the same. Having discussed the

framework we also observe that 'triple helix' is yet to yield major empirical or research

advances, and its value as a guide for future empirical research appears to be limited

(Mowery and Sampat, 2004). To probe deeper into the intricacies of the framework we see

that one of the most significant weaknesses in the 'triple helix' argument are the

underestimation of the complexity in establishing strategic alliances and joint ventures and

then managing them in the transaction space, and assumptions of commonality in values

and attitude relating to the purpose and conduct of research (Howard, 2004). Even where

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III principle agreement is reached for collaborations, there are often insurmountable

hurdles to be crossed in resource allocations and reconciling institutional differences and

priorities and the risks of compromise to institutional purpose. This peculiarity has been

noted and observed earlier that there are institutional differences and problems of mutual

trust, particularly with industry (Chandra, 2003; Nath, 1992; Indiresan, 2000; Indiresan

and Nigam, 1993). Here we may pose a question if the university-industry-govemment

related triple helix model is partially applicable to the Indian context. In other words, we

might establish that only a bilateral relationship exists between academia and industry or

between academia and government.

Howard (2004) says that the idea of convergence between institutions of higher

education, industry and state, with each taking on the characteristics of the other not only

suffers from a conceptual weakness, but it is also inappropriate in that it compromises the

ability of institutions to achieve high levels of performance in relation to their foundation

purposes. He notes that the efforts of higher education institutions to operate as businesses

in a commercial environment have been largely unsuccessful and major problems have

emerged in relation to the integrity of their missions relating to teaching and research

when this is attempted. Similarly businesses have not embraced the contribution of higher

education institutions to industrial innovation. There are other problems that have been

reflected in 'triple helix' most of them arising after using the framework in various

empirical studies 170. The helix's emphasis on a more 'industrial' role for universities may

be valid, although it overstates the extent to which these 'industrial' activities are

occurring throughout universities, rather than in a few fields of academic research 1 7

I.

Benner and Sandstrom (2000) address the issue of institutional mechanisms which either

facilitate or impede the development of new forms of knowledge production. This issue

according to them has been neglected in 'triple helix' frame of reference. The authors

suggest an 'institutionalist' complement to the triple helix model where they analyse

170 According to Bunders et al. (1999), the main argument is that in 'triple helix', by limiting the process of technological innovation to industry, university and government the room for technological change is essentially constrained. The ileglect of users in the innovation process is a major limitation in this model. (Howard, 2004: 37) observes the views in 'triple helix' have a heavy 'statist' orient:!tion, implying an important role tor government, but overlook fundamental market issues relating to the sale and purchase of commercially applicable knOWledge. 171 The general criticism about 'triple helix' that prevails is that this scholarship devotes little attention to the 'transformations' in industry and government that are asserted to complement those in universities.

153

institutional regulation of acade~ic research emphasising on the way norms in the

academic system are constituted through research funding. They infer that the forces of

change and continuity are engaged in the negotiation process about the nonnative

regulation of academic research. In the case of IITs, the lIT system is governed by the lIT

Act (1961) and the nonns and guidelines, statutes and ordinances are all guided by this

Act. The policies for knowledge transfer in particular, that attribute to changes in the

organisational and institutional reforms in academia should greatly involve the opinion of

academic experts.

Coming back to the discussion on the recognition of importance of open science

we may presume, based on our literature survey, that IITs scrutinise their efforts to protect

their knowledge assets. The importance of filing for an IPR is well recognised by IITs in

select sectors like biotechnology, information technology, phannaceuticals,

nanotechnology, and applied chemistry while in other sectors embryonic technologies do

seek protection. We may also presume that exclusive IPRs do not seem to be particularly

. important for small companies which are believed to provide benefit so as to depend on

exclusive control over technology and be able to attract capital necessary for product

development and commercialisation. However for SME's in certain industries, such as

biotechnology and pharmaceuticals, where the costs of imitating final products are low

these become significant.

Owing to our discussion on those ARIs that have built considerable research

capability, produced innovations, established strong networks with angel investors and

industry, and earned ample reputation; who happen to create spin-offs rather than second­

tier institutions that lack these factors or have not yet achieved a desired level, we would

see in our empirical findings if IITs are seen to adapt the spin-off route to

commercialisation much more than licensing and royalty earning mode. Here the study

might establish that IITs have in a way formulated their own strategy to capitalise on

knowledge although the process of knowledge production and transfer may have a

universal reflection prominently visible in the institutions of industrialised economies and

that Indirect Spin-offs do play an important role.

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Finally, since we noted the developments and characteristics of·an 'entrepreneurial

university' in the form of 'internal transformations', 'interface processes', 'recursive

effects' and 'quasi firms'; the empirical research mayor may not reflect similarities in

IITs. This could be found in the development of 'institutional policies to knowledge

transfer', the rise in 'sponsored research and industrial consultancy assignments', the

establishment of 'technology transfer offices', 'patent cells', 'incubation units' and 'spin­

offs'. This comparisOIi might establish if the evidence of the above mentioned dynamic

formations can brand IITs to be entrepreneurial. On the contrary we might see that

traditional role of ARIs to teach and research gains due prominence and recursive effects

are subdued in the Indian context.

The next chapter deals with the knowledge production in IITs giving a detailed

account (although not comprehensive) of the intellectual and infrastructural capabilities of

five IITs namely Delhi, Bombay, Kanpur, Kharagpur and Madras. This study however

does not compare the institutions for their resource generation or assets creation but

focuses on knowledge generation and facilities for the same.

3.6.2 Summary of Hypotheses

During the course of our review of literature and discussion on theoretical perspectives,

we listed a few hypotheses that the empirical study in the forthcoming chapters would test. '\

The summary of all the hypothesis and their guiding force are listed below.

Table 3.3: Summary of Hypothesis

No. Hypothesis The Driving Preslmlption 1 IlTs as such in recent years have come to playa IlTs, we presume, are putting a strong

significant part in the Indian innovation system. foothold in creating a knowledge research They are seen as frontiers of science based base that contributes to the innovation system. innovations pushing them towards enterprising The presumption draws large(v from the institutions to be hllman capital provider and current functioning of IlTs which have a seed-bed of new firms. greater bearing on the historical

developments in IlTs. Further, the adoption of MIT model, its typical characteristics, and assistance offollr nations have a notable role in supplementing the IlTs as an important actor in India 's innovation system

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2

3

4

5

6

7

At a general level of understanding the mode of knowledge production in fiTs is more like~v to be influenced by Humboldtian values of achieving teaching and research excellence and promotion of open research publications rather than market driven commercialization of research. even though the latter assumes considerable significance.

IITs recognise the importance of open science and scrutinise their efforts to protect their knowledge assets. In other words. knowledge production in fiTs is by and large driven by research publications compared to patents. Also. the importance offilingfor an IPR is well recognised by /ITs in select sectors. This orientation of knowledge production is no way seen to be detrimental to the mode of knowledge transfer in fiTs.

The knowledge production in 'Mode 1 . has been eclipsed by the new mode 'Mode 2' in the five /ITs.

The university-indus try-government related triple helix thesis may be partially applicable to the Indian context.

Modes of knowledge transfer and strengthening of academia-industry relations in fiTs is more likely to be influenced and driven by the conventional routes of consultancy and sponsored research links with industry as compared to Triple Helix influenced mode of ITO based knowledge transfers. In other words the establishment ofTTOs as an intermediate agency internally. and having a pecuniary motivation is unlike(v to playa significant role as a mode of knowledge transfer Mode of knowledge transfer in /ITs is more likely to be manifested in varying forms ranging from conventional sponsored and consultancy to the mode of Triple Helix and rise of entrepreneurial culture. The /ITs are more like(y to adapt the spin-off route to commercialisation of R&D knowledge transfer than the mode of licensing and royalty earning. Thus. the fiTs are moving towards large(y embracing the notion of entreprenellrial unil'ersity

Historically speaking. the underwriters of liT have promoted these important institutions of higher learning as a process of nation building towards achieving technological self-reliance. Advancing knowledge and greater emphasis on excellence in science and engineering graduate teaching are in many ways expression of this national building exercise. In the context of /ITs. we presume that despite the institutional and organisational refornls, and increasing faculty interaction with industry personnel. many faculty and researchers would be less enthusiastic about business partnerships with industry. This could be reasoned in the notion that academic institutions as sources of knowledge have deep rooted institutional values and responsibilities to their operational sphere. Another reason could factor the not so high yielding commercial activities in academia owing to consuming considerable time and often involving considerable risks. Knowledge produced in /ITs is characterised by interdisciplinarity and plurality and it is transient. The knowledge that is being produced in fiTs is done in the context of application. The nature of such associations or linkages as suitable to lOcal flavour and conditions is what developing countries like India should lookfor in their pursuit of creating and nurturing innovations. This is in view of the significant role of sponsored research and industrial consultancy projects in fostering academia-industry linkages as also observed in the organisational culture and practice at /ITs. and understanding the professional aspects of a traditional TTO.

/ITs in recent years have embraced or come to advance and promote the concept of entrepreneurial university in parallel :0 the dominant orientation of teaching and research excellence. This is primari~y due to the evidence of institutional and organisational factors sllch as intellectual property policy. and establishments like technology transfer offices. and incubation units at fiTs.

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