@revista_internacional{835,
  keywords = {Technological innovation efficiency, Super-efficiency SBM-DEA model, Interval type-2 fuzzy sets, The high-tech industry},
  author = {Xiaoqing Chen and Xinwang Liu and Qun Wu and Muhammet Deveci and Luis Martínez},
  title = {Measuring technological innovation efficiency using interval type-2 fuzzy super-efficiency slack-based measure approach},
  abstract = {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 α-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.},
  year = {2022},
  journal = {Engineering Applications of Artificial Intelligence},
  volume = {116},
  pages = {105405},
  issn = {0952-1976},
  url = {https://www.sciencedirect.com/science/article/pii/S0952197622004006},
  doi = {https://doi.org/10.1016/j.engappai.2022.105405},
}