A Socio-Cognitive View of Technology Commercialization and Public Policy

Tahir Hameed
SolBridge International School of Business, Daejeon, South Korea

Ki-Seok Kwon
Hanbat National Unievrsity, Daejeon, South Korea

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Peter Von Staden
Kedge Business School, Marsielle, France

Abstract
South Korea’s R&D investments touched around 4.3% of her GDP (GERD) in 2014 which is the highest in the world (Van Noorden, 2016). While Korean R&D productivity in terms of publications and patents has also raised many folds as a result of successful R&D policy interventions since 2000, the performance of its technology transfer (commercialization) of the newly created science and technological knowledge from its universities and R&D organizations to businesses has remained dismal in comparison to the other OECD nations. Universities and R&D organizations in many OECD nations have received much higher returns than Korea in terms of licensing royalties, new ventures, and new collaborative research projects. According to one estimate, income of Korean universities from technology transfer royalties is only 5% of that of major American universities (KISTI, 2013). Therefore, it would not be incorrect to view Korean technology transfer policies as inefficient while Korean national innovation system gears up to compete at global technology frontiers.

Public policies and their impact on promotion of technology transfer, whether studied from supply side or demand side, has traditionally looked at developed countries and innovation systems, and that too at national and organizational levels mostly (For example, see Bozeman, 2000; Etzkowitz & Leydesdorff, 2000; Wright, Clarysse, Lockett, & Knockaert, 2008; Yusuf, 2008). Recently, some studies technology transfer and commercialization by catching-up and post-catchup innovation systems have also emerged but they are also focused on national and/or organizational levels (Kwon, 2011; Kwon, Park, So, & Leydesdorff, 2012; Wong, Ho, & Singh, 2007).

This paper introduces a socio-cognitive view of public policy and technology transfer at individual actor level. It explicates that individuals involved in technology transfer individually interpret public policies and shared organizational interpretations (organizational frames) based on their individual cognition (individual frames) (See Bandura, 1986; Neisser, 1976; Davidson, 2002). As a result, they manifest (their own realities of) the technology transfer opportunities, the most suitable inputs (ideas/strategies/actions) for the technology transfer process, and the basis of evaluation for the inputs and outputs (See Garud and Rappa, 1994 and Garud and Ahlstorm, 1997 for a treatment in a close context). The conflicts between individual frames of technology creators, technology recipients, technology transfer managers and technology transfer monitors lead to inefficiencies in recognizing the best commercialization opportunities and seizing them successfully. Moreover, feedbacks from the technology transfer outputs, individual’s actions and interactions help the actors modify or reinforce their individual frames and further actions about technology transfer.

The paper tests the above socio-cognitive model with four empirical case studies of leading Korean science and technology research and technology transfer organizations. The case studies demonstrate clear differences in individuals’ frames about the technology transfer process and arising conflicts. As a result, technology transfer process is not fully controllable and is highly contextual. We argue, whereas public policy in countries approaching technology frontier provides essential support for defining and exploiting best practices (routines/pathways) for technology transfer at organizational level, they have not matured enough to support the timely identification and resolution of conflicts between individual actors, hence the inefficiencies. Therefore, among others, public policy for technology transfer could consider allowing an inclusive approach to recognition of best practices for technology transfer and innovation processes, increased social interactions between technology transfer actors, and their training on resolution of individual level cognitive conflicts.