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.
Due to a recent drop in the birthrate, an increase in the number of higher educational institutions, and Taiwan’s recent membership in the WTO, higher educational institutions in Taiwan will not have competitive advantages when faced with competitions from the West and Asia (Chen, 2005). Thus, the need to increase innovative operations, improve performance, and develop core competitive abilities is an urgent issue currently faced by higher educational institutions in Taiwan (Chen & Chen, 2008).
The most utilized evaluations used for innovation performance by Taiwanese higher educational institutions emerge from academic research (Chen & Chen, 2008). However, the factors that can affect innovation performance are numerous. One way to overcome the problem of evaluation performance with regard to numerous factors involves the use of multiple criteria decision-making (MCDM), which is often characterized by multiple, conflicting criteria (Hwang and Yoon, 1981 and Liou et al., 2007). Along these lines, various research studies have produced different measurement dimensions, and criteria (Chen and Chen, 2008, Chin and Pu, 2006, Lin et al., 2006 and Tang, 2006). Some of this research assumes independence of criteria; however, in the real world, most criteria are not mutually independent.
In this paper, a decision-making trial and evaluation laboratory (DEMATEL) method is adapted to model complex interdependent relationships and construct a relation structure using measurement criteria for innovation evaluation. A fuzzy analytic network process (FANP) is conducted to address the problem of dependence as well as feedback among each measurement criteria. A technique for order preference by similarity to an ideal solution (TOPSIS) is finally utilized to find optimal alternatives for innovation configurations. Here, we combine DEMATEL, fuzzy ANP and TOPSIS approaches to develop a novel innovation support system (ISS).
Given a recent drop in birthrates, an increase in the number of higher educational institutions, and a new membership in the WTO, Taiwanese higher educational institutions are facing increased competition. As such, they have recently tried to upgrade their innovation capabilities and innovation performance by using various evaluative tools. In doing so, they mainly focus on academic research. However, the factors influencing innovation in higher education are various. In accordance with the potentially numerous criteria useful in evaluating innovation performance in higher educational institutions, we have combined DEMATEL, fuzzy ANP and TOPSIS approaches to develop an innovation support system (ISS) that considers the interdependence and relative weights of each measurement criterion and different types of universities. As a result, we hope that ISS will help future innovation improvements to be more practical, efficient and efficacious.
