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This science mapping analysis aims to discern current, emerging and future trends of pro-environmental behavior and the theory of planned behavior (TPB).

Bibliometric analysis through bibliographic coupling and co-word analysis were used to reveal the progress of this phenomenon. Of the 1,120 documents search in Web of Science (WoS) database, 1,031 were used in this analysis after restricting to journal publications and studies after the year 2000.

The results show that four themes emerged, namely the fundamentals of TPB for pro-environmental behavior, antecedents of pro-environmental behavior, integration of TPB with the norm activation model and value belief theory and studies of pro-environmental behavior in developing countries. Environmental concern, environmental awareness, environmental knowledge and environmental education were the most commonly integrated variables.

This research is unique in the sense that the integration between TPB and other prominent theories of pro-environmental behavior is vital to predict individual pro-environmental behavior and understand the fundamental scientific importance of the domain. The norm activation model has been integrated with TPB in many pro-environmental behaviors. Mainstream media stakeholders should design and implement a plan for strategic communication and awareness campaigns in the community to encourage consumers to engage in many behaviors that lead to environmental sustainability.

This study presents a science mapping approach to uncover crucial knowledge structure related to pro-environmental behavior and the theory of planned behavior.

This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.