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This study aims to investigate the influence of network power on exploratory and exploitative innovation and examines the moderating effects of power distance and procedural justice on these untested relationships.

This study uses survey data collected from firms in China and explores the influential mechanisms of network power, power distance and procedural justice in firm innovation.

This study empirically shows that network power has an inverted U-shaped effect on exploratory and exploitative innovation. Power distance weakens the effect of network power on exploratory and exploitative innovation, and procedural justice enhances the effect of network power on exploratory and exploitative innovation.

This study extends resource dependence theory and contributes to the literature on innovation management. Future studies should use different collection channels or research methods to provide more evidence for model promotion. In addition, the dynamic power game among network members and the roles of other mediators or moderators warrant further consideration.

Managers should exercise power strategies properly and ensure that their innovation income exceeds expenditures. Managers need to pay serious attention to power distance and procedural justice in the network and formulate suitable cooperation strategies based on actual conditions.

This study applies the resource dependence theory to investigate the influence of network power on exploratory and exploitative innovation. In addition, the moderating roles of power distance and procedural justice in the above relationships, which have rarely been discussed in previous studies, were tested.

Resource mobilization has come to dominate contemporary discourse on the making and survival of social enterprises (SEs). Emphasizing the socially constructed nature of idiosyncratic firm resource environments, this study integrates bricolage and social exchange theory to explore the means at hand and the kinds of practices SEs in China employ to mobilize resources to address persistent social problems.

Adopting a qualitative multiple case design, the research contribution is developed in the context of four SEs based in two cities in China selected through a two-stage process. The main data for the inquiry come from 21 face-to-face, semi-structured interviews conducted with key informants in 2018 and 2019. The authors supplemented this with secondary data about each SE curated from social media platforms and publicly available documentary sources, including press statements, reports and popular press video interviews.

The research findings suggest that SEs in China tend to follow a two-step resource mobilization process: fraternize and exchange. Leveraging the means at hand – “social practice know-how” and the practice of “proactiveness,” SEs strategically engage with actors in their environment (fraternize) to understand and explore the possible sources of the resources they require. Nevertheless, fraternization alone is not sufficient; SEs must demonstrate exchange values (social, economic, functional and regulatory) to convince resource owners to either directly release resources (funds, the right of use of empty spaces, technologies, time and efforts) or offer them indirect support (certification, government procurement). The process of fraternizing within the contingencies of organizing, intertwined with social exchange practices, constitutes the success of resource mobilization. The combination and reconfiguration of the expanded repertoire of mobilized resources provide opportunities for the SEs to make do and, in return, help them maintain their status as valued SEs in China.

This study extends the understanding of bricolage through a social exchange lens to unpack the process through which SEs in China mobilize appropriate resources for their businesses. Emphasizing the importance of the social dimension of bricolage in resource mobilization, a two-step model, comprising fraternization exhibited in the form of social practice know-how and proactiveness and social exchange, is presented as an essential mechanism in SEs’ resource mobilization in China.

Construction enterprises increase their competitive advantage by joining the project ecosystem, but the dual nature of the enterprise’s niche has attracted attention, and existing research has gaps in understanding niche and ecosystem governance issues. This study aims to promote ecosystem compliance governance by exploring the impact of the niche of the key role of construction enterprises on compliance behavior.

First, the study proposes a model on the impact of the enterprise's niche on its compliance behavior and the mediating role of the enterprise's perception of sanctions and the moderating role of a shared vision for compliance of ecological partners within these relationships. Second, we used 205 samples, who were Chinese contractors with international construction project experience through a questionnaire survey. Third, the study conducted a hierarchical regression to test the hypothesis.

The results show that construction enterprises with a wider niche or with a higher degree of niche overlap are more inclined to performance compliance. Enterprises' perception of sanctions plays a part in mediating the enterprise's niche and compliance behavior. The relationship between enterprises' perception of sanctions and compliance behavior can be moderated by the shared vision for compliance of ecological partners. Given a low compliance shared vision of ecological partners, the impact of enterprise perception of sanctions on compliance behavior is positively stronger.

The findings provide valuable evidence upon which ecosystem governance needs to focus and leverage the role of key members, using the advantageous resources of key members as a fulcrum to leverage a larger governance scope. Construction enterprises should keep improving their niche and the shared vision for partners' compliance to promote the evolution and upgrading of cooperation to an ecosystem model that creates greater value.

This study provides new insights for future compliance governance in the project ecosystem by introducing the concept of niche and answering whether construction enterprises with a higher niche in the project ecosystem are more willing to implement compliance behavior.

This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.

The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.

First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.

This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.

In traditional Chinese medicine (TCM), the mechanism of disease (MD) constitutes an essential element of syndrome differentiation and treatment, elucidating the mechanisms underlying the occurrence, progression, alterations and outcomes of diseases. However, there is a dearth of research in the field of intelligent diagnosis concerning the analysis of MD.

In this paper, we propose a supervised Latent Dirichlet Allocation (LDA) topic model, termed MD-LDA, which elucidates the process of MDs identification. We leverage the label information inherent in the data as prior knowledge and incorporate it into the model’s training. Additionally, we devise two parallel parameter estimation algorithms for efficient training. Furthermore, we introduce a benchmark MD identification dataset, named TMD, for training MD-LDA. Finally, we validate the performance of MD-LDA through comprehensive experiments.

The results show that MD-LDA is effective and efficient. Moreover, MD-LDA outperforms the state-of-the-art topic models on perplexity, Kullback–Leibler (KL) and classification performance.

The proposed MD-LDA can be applied for the MD discovery and analysis of TCM clinical diagnosis, so as to improve the interpretability and reliability of intelligent diagnosis and treatment.