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This study examines the relationship between guanxi human resource management (HRM) practices and psychological withdrawal behavior and its mechanism, and examines the mediating role of psychological contract breach and the moderating role of employee resilience.

This study collected 287 three-stage questionnaires from 62 teams from public institutions, large state-owned enterprises and private enterprises in Sichuan Province, and used regression analysis, PROCESS and Amos structural equation model to test the research hypothesis.

Guanxi HRM practices positively influenced the employees’ psychological withdrawal behavior, and psychological contract breach played a mediating role in the relationship. Employee resilience not only moderated guanxi HRM practice and psychological contract breach but also moderated the mediating effect of psychological contract breach between guanxi HRM practice and psychological withdrawal behavior.

This study revealed the impact of guanxi HRM practices on employees’ psychological withdrawal behavior, which often serves as an early indicator of mental health issues. This finding has important implications for the research on relation-oriented HRM practices.

Aspect category-based sentiment analysis (ACSA) has been widely used in consumer preference mining and marketing strategy formulation. However, existing studies ignore the variability in features and the intrinsic correlation among diverse aspect categories in ACSA tasks. To address these problems, this paper aims to propose a novel integrated framework.

The integrated framework consists of three modules: text feature extraction and fusion, adaptive feature selection and category-aware decision fusion. First, text features from global and local views are extracted and fused to comprehensively capture the potential information in the different dimensions of the review text. Then, an adaptive feature selection strategy is devised for each aspect category to determine the optimal feature set. Finally, considering the intrinsic associations between aspect categories, a category-aware decision fusion strategy is constructed to enhance the performance of ACSA tasks.

Comparative experimental results demonstrate that the integrated framework can effectively detect aspect categories and their corresponding sentiment polarities from review texts, achieving a macroaveraged F1 score (Fmacro) of 72.38% and a weighted F1 score (F1) of 79.39%, with absolute gains of 2.93% to 27.36% and 4.35% to 20.36%, respectively, compared to the baselines.

This framework can simultaneously detect aspect categories and corresponding sentiment polarities from review texts, thereby assisting e-commerce enterprises in gaining insights into consumer preferences, prioritizing product improvements, and adjusting marketing strategies.

The main goal of this paper is to present a synthetic multiple criteria group decision-making (MCGDM) methodology for assessing the enterprise digital maturity with linear Diophantine fuzzy (LDF) setting.

This paper utilizes the presented LDF generalized Dombi operator to aggregate assessment information of experts. The developed combined weight model through merging the rank sum (RS) model and symmetry point of criterion (SPC) method is used to ascertain the comprehensive importance of criterion. The evaluation based on distance from average solution (EDAS) approach based upon regret theory (RT) is presented to achieve the sorting of candidate enterprises.

Firstly, the proposed method has strong stability. Secondly, the proposed method takes into consideration the psychological behavior of experts during the decision-making process which further enhances the rationality of the decision results. Finally, the proposed method integrates expert and criterion weight determination models which provides a practical evaluation framework for assessing the digital maturity of enterprises. The research outcomes confirm that the proposed approach fails to resolve the decision problems with unknown weight information flexibly, but also reflect the psychological behavior of expert in decision process. The presented weight approach also provides a rational algorithm to ascertain the weight more accurate.

A composite LDF group decision-making approach is presented by aggregating the proposed generalized Dombi operator, combined weight model and the EDAS model, which make the outcome more reasonable. Sensitivity analysis and comparison study are conducted to reflect the superiority of the proposed approach.

The paper aims to explore and explain sustainable behaviours in an organizational context using self-determination theory, suggesting that individuals are likely to be engaged in green practices when supported by their needs.

The study used three waves of longitudinal design, consisting of 702 executives in leadership roles across public and private companies with an average of 15–20 years of work experience. Professionals working throughout PAN India, the USA, Germany and Australia provided us with the data.

Green transformational leaderships play a pivot in fostering optimism in employees when recrafting their work. Employees being encouraged to evaluate their jobs within the organization’s capacity would bring meaningful change and envision a sustainable future. All the study hypotheses were supported, highlighting the importance of green-focused leadership with individual agencies in line with the organization’s green values.

Using sustainable practices advances organizations in providing green commitment through leadership. Implementing this in the organization can help achieve long-term success by ensuring sustainable practices are embedded in culture rather than a peripheral initiative promoting sustainable decision-making and behaviours.

The study provides insights into the factors influencing decisions to maintain and adopt sustainable practices by providing a deeper understanding of green behaviour change and strategies for promoting pro-environmental strategies in organizations.

This paper aims to reveal the green governance role played by stock connect in transition economies from the perspective of corporates’ environmental violations and provides implications for the coordination and optimization of subsequent stock market liberalization and green transformation policies in pursuit of carbon peaking and carbon neutrality goals.

With the data of Chinese listed enterprises, this paper takes the Shanghai-Hong Kong Stock Connect or Shenzhen-Hong Kong Stock Connect in China as a quasi-natural experiment and applies the multi-period difference-in-difference (DID) model to identify the impact of stock market liberalization on the corporates’ environmental violations.

The findings reveal that the stock market liberalization significantly restrains the corporates’ environmental violations. These findings are robust to a series of sensitivity tests, including excluding two-way effects, adjusting the year of policy implementation, replacing the core variables, introducing the regional fixed effects and excluding the interference effect of other relevant policies during the sample period. Furthermore, the stock market liberalization is beneficial for upgrading information disclosure quality, improving internal governance capability, strengthening environmental protection incentives, and thus restrains corporates’ environmental violations. Meanwhile, heterogeneity tests show that the inhibitory effects are more significant in those grouped samples which is large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden.

We make two marginal contributions to the current literature. First, this paper enriches the literature on the factors influencing corporate environmental violations by focusing on how the macro-level financial policy influences the micro-level corporate environmental violations. One the one hand, prior studies mainly focused on the consequences of corporate environmental violations; however, there is still a puzzle that the effect of stock market liberalization cannot be fully justified to influence corporate environmental violations. The findings help explain this puzzle by examining that stock market liberalization can restrain corporate environmental violations. Moreover, prior studies mainly focused on corporate share price (Yunsen Chen et al., 2022), market liquidity (Han Kim and Singal, 2000), information disclosure (Liang, Lin, and Chin 2012), corporate governance (Bae and Goyal, 2010) and corporate violations (Lingyun Xiong et al., 2021), but not on corporate environmental violations. We assume that the suppression effect of stock market liberalization on corporate environmental violations can help reduce corporate environmental violations, improve corporates’ awareness of environmental compliance. Second, this paper contributes to a better understanding of the literature on stock market liberalization by investigating the restraining effect of Stock Connect on corporate environmental violations from the perspective of information channel, corporate governance channel and motivation channel, which is of practical significance. Moreover, we investigate the differences in the inhibitory effects of stock market liberalization on different enterprises' environmental violations, from firm size, property rights, enterprise assessment results, tax burden to geographical location, which is conducive to the construction of a green financial system and the promotion of sustainable economic development. Our results show that firms which are large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden tend to compliance with environmental laws. These findings emphasize the importance and benefits of Stock Connect.