Green innovation is essential for achieving sustainable development goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure) and SDG 12 (Responsible Consumption and Production), as it fosters environmental and social benefits while also creating new economic opportunities. Despite previous studies actively conducting empirical analyses on green innovation, research on guiding the green innovation process through artificial intelligence remains scarce. This study aims to explore key variables that affect green innovation, thereby promoting the sustainable development of organizations, and to investigate the incentive mechanisms behind it. By uncovering the internal and external factors that drive green innovation and their interactions, we can better understand and optimize the process of fostering green innovation. Unlike previous studies, this research not only explores variables and verifies main effects but also provides and validates a research model related to the occurrence of green innovation. Additionally, this study determines the extent to which artificial intelligence management influences green innovation through knowledge sharing and examines whether an innovative culture moderates the impact of artificial intelligence management and knowledge sharing on green innovation, as well as whether it moderates the mediating effect of knowledge sharing within the model. Therefore, this study collected data from 331 adult employees of SMEs across 23 provinces, cities, and districts in China and conducted empirical analyses, including confirmatory factor analysis (CFA) and reliability analysis. The results indicate that artificial intelligence management directly affects green innovation and indirectly affects it through the partial mediating role of knowledge sharing. Furthermore, an innovative culture significantly moderates the mediating role of knowledge sharing between artificial intelligence management and green innovation. In exploring the variables of green innovation, this study established an adjusted mediating model and verified its significance. In summary, the causal relationship between artificial intelligence management and green innovation, as demonstrated through this process, contributes to the expansion of the research field and the advancement of SDGs, specifically Goals 9 and 12. The study’s findings highlight the importance of integrating artificial intelligence management to enhance green innovation, which is vital for the sustainable development and economic growth outlined in the SDGs.

The purpose of this research was to explore which variables facilitate Chinese SMEs employees’ workplace deviance and focused on uncovering the processes that lead to deviant behavior. Unlike previous studies, rather than simply focusing on variables exploration or main effect verification, we provided and verified the research model related to process by which workplace deviance occurs. Specifically, this research verified exploitative leadership influences workplace deviance through negative emotions and examined the moderated mediation role of fear of negative evaluation. Therefore, this study conducted a data survey on adult employees in SMEs from 25 provinces, municipalities, and regions in China. Ultimately, 305 valid samples were used in the empirical analysis and utilized SPSS 26.0, AMOS 23.0, and PROCESS Macro 3.4.1 to analyze the results. As expected in this study, all hypotheses were supported except hypothesis 6. In addition, based on research results, expected effects are provided in terms of theory and practice. Theoretically, it discloses the mediating role of negative emotions between exploitative leadership and workplace deviance, as well as the moderated mediating role of fear of negative evaluation, broadens the comprehension of the relationships. In practice, it facilitates organizations in identifying and managing exploitative leadership, mitigates workplace deviance, and simultaneously alerts managers to pay attention to the employees’ negative emotions and fear of negative evaluation. Overall, the causal relationship between exploitative leadership and workplace deviance through a process, which can be seen as an expansion of the research field and is considered a contribution of this study.

With the global economic downturn, the impact on internal systems of Chinese SMEs has also received great attention. However, the provocative and destructive nature of retaliation behavior by SME employees shifts resources meant for organizational system development towards addressing internal balance issues. Employees’ retaliation behavior poses significant harm to organizations systems, limiting their long-term sustainability and competitiveness in the long run. This study argues for a close relationship between employee behavior and leadership management style, particularly in the context of inadequate management systems in SMEs, which can easily subject employees to direct influence from their leaders. For example, abusive supervision or oppressive practices at the management level can trigger resistance and rebellious behavior among employees, leading them to choose retaliatory actions as a response to the organizational system. This study aims to explore the causal relationship between abusive supervision and retaliation behavior within the system. We aim to clarify the pathway through which abusive supervision triggers retaliation behavior among employees within the system and examine the serial multiple mediating effects of psychological distress and negative emotions as well as the moderating effect of workplace incivility. To validate the hypotheses proposed in this study, a survey was conducted among employees of Chinese SMEs. The data provided by 303 employees were analyzed using SPSS ver. 26.0, AMOS ver. 23.0, and SPSS PROCESS Macro 3.4.1 Model 6. The findings indicate that abusive supervision has an indirect effect on employee retaliation behavior through the serial multiple mediating effects of psychological distress and negative emotions. Workplace incivility moderated the influence of negative emotions on retaliation. This study explored the process by which abusive management triggers retaliative behavior through a serial multiple mediation model, providing theoretical evidence for related research. This study explicitly reveals the process leading to retaliation behavior within the system and presents the differences from previous research. Additionally, this study demonstrates the interactive effect between abusive supervision and incivility through the moderating role of incivility in determining the level of retaliation behavior. Ultimately, this study has pioneering significance in exploring the causes of retaliation behavior within the Chinese SME organizational system and how to prevent the occurrence of retaliation behavior.