Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 116, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2022.105405
Keywords
Technological innovation efficiency; Super-efficiency SBM-DEA model; Interval type-2 fuzzy sets; The high-tech industry
Categories
Funding
- National Science Foundation of China (NSFC) [71771051, 72071045]
- Key Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province, China [2017ZDIXM014]
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As an important leading industry in China's economy, the high-tech industry requires systematic analysis of technological innovation activities to measure technological innovation efficiency and promote sustainable development. This study proposes an interval type-2 fuzzy evaluation method to assess the efficiency of China's high-tech industry, considering the uncertainty of qualitative information. The proposed model combines the super-efficiency slack-based measure (SBM)-Data envelopment analysis (DEA) method with interval type-2 fuzzy sets to handle undesirable outputs and rank multiple efficient decision-making units.
As an important leading industry in China's economy, the high-tech industry needs to systematically analyze technological innovation activities, thereby measuring the technological innovation efficiency and further improving sustainable development. The high-tech industry in different provinces benefits from individual policies due to their geographical locations. However, since the intensity of policy implementation in the technological innovation activities of the provincial high-tech industry is qualitative information, which is difficult to be expressed by quantitative data and rarely considered in the efficiency assessment. Therefore, this study adopts interval type-2 fuzzy sets to characterize the uncertain qualitative information and constructs an interval type-2 fuzzy evaluation method to measure the technological innovation efficiency of China's high-tech industry. More specifically, considering the handling of undesirable outputs and the ranking of multiple efficient decision-making units, the super-efficiency slack-based measure (SBM)-Data envelopment analysis (DEA) method has been selected as the basic evaluation model. Then, the super-efficiency SBM-DEA model has been extended into an interval type-2 evaluation approach by considering the uncertain variables. Moreover, the ������-cuts and best-and-worst methods are introduced to conduct the decomposition of the proposed evaluation model and aggregate the ultimate efficiency. Finally, a comparative analysis of technological innovation efficiency in the regional high-tech industry has been performed to validate the applicability of the proposed model.
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