A matching model of university–industry collaborations

Abstract

In this paper, we present a model of university–industry collaborations with heteroge- neous agents. It develops one of the original intuitions by Leyden and Link (Small Bus Econ 41:797–817. doi:10.1007/s11187-013-9507-7, 2013b) about the mechanisms by which innovative firms search for collaborative research partners. We study the charac- teristics of the matching process between universities and innovative firms that makes this exchange in technology transfer (TT) either efficient or unfeasible. We show that the functioning of the TT market implies dual-trading externalities. These arise because there is a high probability that a firm searching for a university collaboration will not meet a suitable researcher, and another positive probability that an unemployed researcher will not find a suitable innovative firm, whatever the market prices and the costs are. According to the matching model literature, we refer to these externalities as congestion

Technology transfer with search intensity and project advertising

“…M 0 captures public policies that promote collaborations between firms and universities by establishing, for example, efficient TT offices (TTOs). When M 0 increases, the number of matches also increases (Calcagnini et al 2015b). 2 The variables a and b are market averages.…”

“…In this paper we study the functioning of a decentralized and heterogeneous Technology Transfer (TT) market, in which technology transfer is the result of a matching process between heterogeneous universities' Knowledge Transfer Offices (KTOs) and innovative firms. We improve previous microfounded theoretical literature on university-industry (U-I) collaborations (Leyden and Link 2013b;Calcagnini et al 2015b) by embedding TT into a competitive model of utility and profit maximization (Shi and Wen 1997). In other words, our model endogenizes the process that drives the dynamics of university researchers in search and firm vacant projects by assuming that unemployed researchers choose their search intensity and firms their projects' advertising expenditure.…”

“…In general, the project-matching probability is an increasing function of the search intensity of the other side of the market, but this dependence is ignored by single agents. We refer to these externalities as congestion because they are generated by the tightness -as measured by the ratio between vacant projects and researchers in search -that firms and researchers cause to each other during search (Pissarides 2000;Calcagnini et al 2015b).…”

Selection Between One-Time Transfer and University-Industry Cooperation in Technology Transfer: A Matching Model

“…On one hand, based on the endogenous growth theory, knowledge spillover theory of entrepreneurship (KSTE) tries to expand the microeconomic foundation by identifying and adding some factors of knowledge spillover into the original model to describe their behaviors and performances on affecting economic growth of a region or a country [3][4][5][6]. On the other hand, some other studies focus on the relationships between universities and firms in the process of technology transfer, e.g., how to improve the "Industry-Science Links" and remove the obstacles among them [7][8][9], and how to select appropriate modes of cooperation for different kinds of scientists under different kinds of situations [2,10]. While there are large sums of studies on the former kinds of topics, the latter ones have not been fully investigated yet, and to the best of our own knowledges, lack an integrated model to describe the different characters and jointly behaviors of the agents in different forms of TT.…”

“…Similar researches have been done by Calcagnini etc. [8], but this paper is just based on the situation of cooperating, so this paper is extended from this.…”