Efficiency and evaluation analysis of a network of technology transfer brokers

Technology Transfer‖ (―TT‖) is a concept subject to different interpretations, according to the discipline of research (i.e. Economics, Anthropology, Sociology and Management), as well as according to the purpose of research. The different research views, while not converging on how to interpret the phenomenon, share the same basic idea behind TT, which can be synthesized as a movement of know-how, technical knowledge and/or technology from one (or more) source (termed ―donor‖) to another entity (termed ―recipient‖). Among the actors involved in a TT process, the present work focused mainly on the role of the broker, or innovation intermediary, facilitator of the TT process origin and development. Its main objectives and activities can be summed up as follows: determine the opportunities for technology transfer in terms of specific requirements; identify appropriate sources of technical breakthroughs, scientific information and other technological developments (or findings) that should meet the identified needs; build bridges between donor and recipient; follow through initial contacts with other complementary services (e.g. on IPR and innovation finance), skills and inputs to accommodate the transfer of the technology. In the present work, in particular, we focused on organized structure of brokers (―network‖), which allows to provide clients higher added value services (rather than those offered by a single broker), thanks to the possibility of leveraging on a wider spectrum of expertise and offering a higher number of opportunities (Bessant, 1995). The paper is organized as follows: after a brief introduction to explain the object of the study, Section 2 is devoted to a reconnaissance of the literature on innovation intermediaries and most relevant contributions on efficiency assessment in TT literature. In Section 3, attention is paid to brokers organised as a ―networked‖ system, meaning a system formed by several interconnected nodes with a formal or informal structure that pursue a common goal: the commercialisation and transfer of technology. After the description of the business model of IRC network, six research hypotheses are presented to test the effects of exogenous factors on the IRC units‘ efficiency. Section 4 is devoted to the empirical analysis. After describing how data have been gathered and the methodology implemented, the models and related statistics are showed. In particular, our research concentrated on the data (drawn through an appropriate survey) of the Technology Transfer Network IRC (Innovation Relay Centre). We used such data to analyze the performances of the units belonging to such network, in order to investigate how endogenous and exogenous factors affect their efficiency. The influence of endogenous factors has been taken into account by performing a DEA (Data Envelopment Analysis), by selecting (thanks to a thorough analysis of the business model) the most appropriate inputs and outputs. Exogenous factors have been taken into account by utilizing ordered probit regressions (which used as dependant variable the scores obtained through DEA, transformed into a ―categorical variable‖). Six hypotheses have been tested, with the goal of verifying the influence of some control variables, as well as the effect of variables detected through our survey. According to our analysis: a limited influence is played by the control variables we used (which should express in some way the level of development and innovativeness of the regions where the brokers operate); ―pull-oriented‖ units (more focused on serving markets needs rather than promoting solutions in search of problems) are more likely to be efficient than the ―push-oriented‖ ones; lasting relationship with clients strongly affects the units (DMUs) efficiency; DMUs with a higher share of SMEs in the portfolio tend to outperform the other ones; clients with a higher orientation towards innovation are critical to allow the brokers to achieve higher performance. In Section 5 we draw the implications of our study and the main consequences at managerial and policy level. Results showed how, on the one hand, brokers can pursue more productive and targeted strategy in order to increase their impact and improve performance (inter alia, by taking into account a ―pull‖ approach to technology and the need of long-lasting relation with the clients – SMEs in particular). On the other hand, policy makers can get interesting insights on how to tune existing initiatives to foster innovative activities and design new ones from scratch. Finally, in Section 6 the limits of our analysis are addressed and further developments are envisaged. A remark recalled in the present work is the need of combining quantitative aspects with qualitative ones.