As environmental sustainability pressures intensify and AI technologies rapidly evolve, the integration of AI into green marketing strategies has become increasingly prominent. This systematic review examines the application of artificial intelligence (AI) in green marketing, with a focus on studies published between 2020 and 2024. This review addresses two key research questions: the effectiveness of different types of artificial intelligence in green marketing applications, and the role of AI in supporting enterprise development in this context. A comprehensive search of SpringerLink, Web of Science, and Google Scholar initially identified 200 records. After duplicate removal and multi-stage screening, 47 articles were deemed to meet the inclusion criteria. Only peer-reviewed journal articles in English were included. Study quality was appraised using established evaluation criteria to ensure methodological rigor. Among these, Thinking AI, Mechanical AI and Feeling AI appeared in 45 studies, 23 studies and 15 studies, respectively. The selected studies span 34 journals and 28 countries, reflecting both the rising academic interest and the interdisciplinary character of this emerging field. However, this review also identifies notable deficiencies in the current body of work. This review integrates these AI types with the 4Ps framework to form a concise conceptual mapping of their respective functions. Although AI has been positioned as a powerful driver of green marketing, research remains fragmented, with limited assessment of AI’s sustainability, weak data and ethical safeguards, and insufficient long-term and global perspectives. This underscores the need for a deeper and more systematic understanding of AI to better achieve the goals of green marketing and improve its practices.

Open burning of straw is the most significant problem of environmental pollution in rural areas. Returning straw to the fields is beneficial to rural environmental management and rural development. Comprehensive utilization of straw in the field not only reduces environmental pollution, but also benefits food production and farmers’ income. Because planting farmers, enterprises, and local governments have different interests, it is difficult for the straw return system to operate soundly. In this study, a three-party evolutionary game model of farmers, enterprises, and local governments was constructed to analyze the evolutionary stability of the strategic choices of the three subjects, explore the influence of each element on the strategic choices of the three parties, and use Matlab2022b simulation to further analyze the dynamic evolution of the game behavior of the system subjects under the given benefits and the given subjects, respectively. The study findings showed that the higher the preferences given by the local government, the higher the probability of farmers and enterprises participating in the straw return system. Only with the participation of local governments can the straw return system be operated robustly. Our study findings also revealed that the interests of farmers must be fully protected in order to mobilize the main body and stimulate market dynamics. The overall findings of this study provide useful insights for promoting government agencies to govern the local environment, increase local revenues, and build integrated waste utilization systems.

Development inequities and environmental pressures are both growing globally. We must actively investigate green development strategies to address the problems of development inequality. First, using RIF regression, we find that releasing the value of ecological products has a considerable beneficial influence on farmers' income. We also utilised quantile regression to find that the effect of income rise was stronger for low-income earners than for high-income earners, confirming the conclusion that the gap might be narrowed. Then, using regressions of moderating effects, we investigate how we can sustain this efficacy and discover that social capital, collective action, and institutional provision can play key positive moderating roles. Finally, we employ heterogeneity analysis to find that the longer the time period, the more effective the income growth, with the northeastern region seeing poor income gains due to intensive industrial development patterns. The findings offer policy suggestions for developing countries to alleviate development inequities.