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China has resolved to pay more and more attention to the sustainability of ecological construction and social development. The country has proposed a low-carbon economy policy; development and management of enterprises are also actively responding to the call for a low-carbon economy. Through a series of innovations and changes, it intends to realize its own low-carbon production and business development, thereby promoting transformation and optimization of industrial institutions. Innovation is a significant driving force of national economic development. In order to build China into an innovative country, there is a need of national innovation strategy and innovation system. The state vigorously promotes the implementation of innovation-driven development strategies. Enterprises are not only an important carrier for the state to implement mass entrepreneurship and innovation but also a powerful driving force for development of economy. There is a dire need and importance to identify techniques to evaluate impact of corporate innovation on development effects with low-carbon economy. Considering this aforementioned problem, random initialization parameters in back propagation network are used. This evaluation process can easily lead to the functioning of the model falling in the local optimum. The work designs an impact evaluation model (IGWO-BP) with improved gray wolf algorithm (IGWO) in order to optimize BP network. To improve optimization ability for GWO, the study uses the chaotic map to initialize the population. The nonlinear convergence factor strategy as well as dynamic weight strategy is used to promote GWO, so as to optimize initial weight as well as threshold point for the BP network. The IGWO-BP is applied to perform evaluation of the impact in case of enterprise innovation relevant to development effects with low-carbon economy.

Shengtai Zhang and Baoliang Xu contributed equally to this study.

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PurposeThe increasing social media use has been widely recognized for its adverse effects, such as social media fatigue. With the continuously increasing friends on social media, the dissimilarity of individuals in terms of age, personality, and values has increased. It is unclear whether perceived dissimilarity with others is associated with social media fatigue. The authors attempted to bridge this gap by constructing a “perception–emotion–behavioral” research framework. This study investigated the influence of individual perceived dissimilarity on social media fatigue. The authors further investigated the mechanisms mediating the three dimensions of social anxiety in the model.Design/methodology/approachThis study examined the mechanisms by which individual perceived dissimilarity influences social media fatigue, particularly using WeChat application. A field survey study conducted in China with 408 subjects of WeChat app users was used in this study to analyze the study model.FindingsThe obtained results demonstrate that individual perceived dissimilarity has a significant positive effect contributing to social media fatigue, perceived dissimilarity is positively correlated to social anxiety. Social anxiety positively affects social media fatigue, and social anxiety partially mediates the positive effect between perceived dissimilarity and social media fatigue.Originality/valueFirst, the study confirmed the influence of perceived dissimilarity on social media fatigue, which may enrich the antecedent mechanisms of social media fatigue. Second, the authors demonstrated the social anxiety-mediated development of fatigue. The findings provide an in-depth understanding of users' fatigue. Third, the findings of this study provide valuable insights for preventing of social media fatigue.

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