期刊
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
卷 292, 期 1, 页码 199-212出版社
ELSEVIER
DOI: 10.1016/j.ejor.2020.10.011
关键词
Data envelopment analysis; Innovation performance; High-tech companies; Second order cone programming; Global optimum
资金
- National Natural Science Funds of China [71828101]
This study examined the innovation performance of high-tech companies in China using a dynamic network DEA approach. The findings revealed disparities in innovation performance among different companies and investigated the sources of innovation heterogeneity and inefficient performance.
This study examines innovation performance of high-tech companies in China, using a dynamic network data envelopment analysis (DEA) approach. The innovation process is decomposed into a research and development (R&D) stage and a commercialization stage. In addition, innovation is conceptualized as a consecutive event that goes through multiple time intervals, requiring a dynamic structure of the methodological framework. Using a newly developed dynamic network DEA, the current study calculates a R&D performance index and a commercialization index for the R&D stage and commercialization stage, respectively. The multi-process innovation system is integrated with dynamic carryover items. This results in a highly non-linear dynamic network DEA model. Second order cone programming and nested partitions strategies are employed to solve the nonlinear dynamic network DEA model. Our empirical study indicates disparities in innovation performance among different Chinese high-tech companies. The innovation heterogeneity and inefficient performance sources are also investigated. (C) 2020 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据