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- W2402478862 abstract "Introduction Collaborative innovation is a trans-disciplinary approach for developing the wholeness synergy to improve the competitiveness of an organization through holistic, competitive and complementary interactions between and among innovation participants in a specific environment (Bommert, 2010; Swink, 2006). The collaborative innovation system essentially consists of three sectors: industry, universities, and the government, with each sector interacting with the others, while at the same time playing its own role. Collaborative innovation system is a complex conglomerate of interacting independent parties. The network of institutional relations among universities, industries, and governmental agencies has been considered as a Triple Helix (TH). Collaborative innovation system (CIS) is based on a multi-input, multi-output transformation relation. It is an important issue to investigate the performance related to the transformation process of limited innovation resources for improving collaborative innovative outputs. Previous studies have been done to evaluate the performance of collaborative innovation. However, those studies failed to consider the complexity of the collaborative innovation system. Data envelopment analysis (DEA) is a method for measuring the efficiency of peer decision making units (DMUs). Recently network DEA models been developed to examine the efficiency of DMUs with internal structures. The internal network structures range from a simple two-stage process to a complex system where multiple divisions are linked together with intermediate measures. In this study, we propose a network DEA with parallel production systems to measure the efficiency of University-Industry Collaborative Innovation. The purpose of the present study is to construct a complete measurement framework characterizing the CIS’ production framework from original S&T investment to final outputs, and measure the CIS’ process-oriented technical efficiency, which is implemented in China’s context. It is hoped that this study will benefit China’s collaborative innovation policy-making." @default.
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- W2402478862 date "2015-01-01" @default.
- W2402478862 modified "2023-09-23" @default.
- W2402478862 title "Network DEA Approach for Measuring the Efficiency of University- Industry Collaboration Innovation: Evidence from China." @default.
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