Technology transfer motivation analysis based on fuzzy type 2 signal detection theory

Abstract

This paper presents a complete study based on signal detection theory (SDT) for deciding the motivation factors that motivate academic researchers to participate in the technology transfer process (university–industry relationship). Moreover, this study determines the researchers’ perception about the motivations strategies designed in universities. The paper focuses on positive motivation factors such as academic prestige, competition, generation of resources, the solution of complex problems, professional challenge, personal gains, personal gratification and the solution of society problems. The negative motivation factors studied in the paper are as follows: innovation environment, time required, and lack of incentive and fear of contravening university policies. The importance of SDT lies in the fact that it is a theory that can deal with observer perception and the ways in which choices are made. This paper proposes fuzzy sets type 2 in SDT to expand its potential and understand the decision of the researchers during the technology transfer process under conditions of uncertainty. Although fuzzy type 1 detection theory (FDT) allows signals to overlap (non-binary description), a complete representation of uncertainty is not incorporated. Thus, fuzzy type 2 signal detection theory (FDT2) is proposed to model the uncertainties and noise condition under technology transfer process. High standards of motivation can maintain and attract competent researchers at universities; thus, this paper deals in a deep fashion with all the main aspects about those motivation factors using FDT2.