Increasing numbers of Taiwanese higher education institutes are pursuing innovation operation. However, these institutes generally rely greatly on academic research to evaluate innovation performance. Nevertheless, the performance of innovation may be affected by numerous factors that are often beyond the scope of a single academic study. Thus, to address this concern, this paper constructs an innovation support system (ISS) for Taiwanese higher education institutes to comprehensively evaluate their innovation performance. Previous research often evaluates performance by independently considering a number of criteria. However, this assumption of independence does not model the so-called “real world”; thus, we present a novel conjunctive multiple criteria decision-making (MCDM) approach that addresses dependent relationships among each measurement criteria. As such, we utilize a decision-making trial and evaluation laboratory (DEMATEL), a fuzzy analytical network process (FANP), and a technique for order preference by similarity to an ideal solution (TOPSIS) forming order to develop an innovation support system (ISS) that considers the interdependence and the relative weights of each measurement criterion.
Relation:
Expert Systems with Applications 37(3), p.1981-1990
