The International Consortium on Agricultural Biotechnology Research (ICABR)

 

Learning Networks in Agrobiotechnology:
Evidence from the US and EU

James N. Barn,
(EMAC)
Economics and Management of Agro-biotechnology Center

Nicholas G. Kalaitzandonakes,
University of Missouri-Columbia.

The biotechnology industry has since its inception been characterized by many private-public relationships (Theodorakopoulou and Kalaitzandonakes). Powell (1990) finds that sources of innovation do not reside exclusively inside firms; instead, they are commonly found in the interstices between firms, universities, research laboratories, suppliers, and customers. Consequently, new opportunities for innovation are a function of the extent to which firms participate in outside relationships (Levinthal and March, 1994; Pisano 1991 and Powell 1996).

Such relationships encourage an industry structure that is both competitive and collaborative. Firms can innovate using internal capabilities and race for patents as Schumpeter (1934) described, which creates an industry structure of intense competition. Or, firms can choose to collaborate through on-going relationships with alliance partners with mutual, but possibly different strategic interests. Access to knowledge through relationships quickly and reliably produce competitive advantage (Nelson 1990 and Stinchcombe 1990). The interaction of both innovation strategies by firms reveals a highly competitive, yet also cooperative, industry structure of biotechnology.

Relationships are particularly significant in encouraging learning, which is important especially in innovation that involves tacit knowledge. In this way, the structure of networks is significant. The structure of collaborations has been found to significantly influence organizational learning (Hamel, 1991). Learning from the alliance partner primarily involves the acquisition of two types of knowledge: (a) information and (b) know-how (Kogut and Zander, 1992). The quest to understand how firms learn within (Doz, 1996; Arino and de la Torre, 1998) and across a portfolio of alliances (Anand and Khanna, 2000) has generated empirical results that indicate intra- and inter-organizational learning, indeed, has a positive relationship on firm and network performance.

Because of their significance, learning networks have been pursued vigorously with explicit public funds in many regions, such as the European Union (EU), Japan, and the U.S. in the case of biotechnology. Specific policies that promote certain firms and network structures have been used to promote learning and innovation, but network performance has varied considerably.

Significant innovation performance differences have been observed among US and EU biotechnology firms (Theodorakopoulou and Kalaitzandonakes, Kalaitzandonakes, Senker). In this paper we test the hypothesis that differences in the structure of EU and US plant biotechnology networks are responsible for their different rates of learning and innovation performance. Specifically, the following hypotheses are tested:

Innovation performance of agrobiotechnology firms in the US and the EU is higher when they are involved in networks due to learning

Firms and networks in the US learn faster and innovate more than their counterparts in the EU

Network structure explains a large part of the differences in learning and innovation performance.

We use network analysis as our methodology for testing these hypotheses. Network analysis reveals the collaborative and competitive nature of this industry allows for further investigation in the underlying learning process. From our findings, we draw conclusions about relevant industrial and science and technology policies in the two regions.


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