No abstract

Regional innovation capability is an important indicator of both regional innovative and long‐term development. The purpose of this study is to build an evaluation index system for regional innovation capability in order to identify regional differences and support innovation more effectively. After establishing a reasonable evaluation value for regional innovation capability, a combination of simulated annealing optimized projection pursuit (SA–PP) and N‐layer nested fuzzy comprehensive evaluation models is used to assess China's regional innovation capabilities. The results show that the SA–PP model effectively mitigates the risk of erroneous evaluation results caused by index weight uncertainty, resulting in a more reasonable, robust, and intelligent assessment of regional innovation capability. Furthermore, the nested fuzzy comprehensive evaluation model is capable of easily resolving the evaluation factor set's heterogeneity and multilayer problems. The most significant influences on China's regional innovation capability are knowledge acquisition and enterprise innovation. The comprehensive score of the proposed combinational evaluation model manifests that provinces with strong regional innovation capabilities are mainly concentrated in the southeast coastal regions. The research results allow for precise weight determination and object ranking.

The importance of enterprises significantly improving their innovation performance by working closely with customers throughout the innovation process has been emphasized in recent literature. However, the role of organizational innovation environment in customer creativity and the impact of customer knowledge matching on the innovation environment are not sufficiently explored. Based on the Social cognitive theory and Flow theory, his investigate the factors that influence enterprise innovation performance in the context of customer participation in innovation, as well as how businesses can foster an online innovation environment that fosters customer creativity. The mixed-methods study, which combines qualitative and quantitative research, is used to create the scale item that measures the study’s main variables. Structural equation modeling and bootstrapping estimation was performed on survey data collected via questionnaire from 392 consumers who participated in online service innovation in an online virtual brand community between June 2018 and May 2019. The study obtain the following main results. First, the innovative environment of customer online participation in service innovation fosters customer creativity. Second, two mediation interactions exist: creative self-efficacy and positive emotions, both of which partially mediate the relationship between customer creativity and the innovation environment. Third, while customer knowledge matching influences the intermediary effect of creative self-efficacy on innovation environment and customer creativity, it has no effect on the intermediary effect of positive emotion on innovation environment and customer creativity.