Dr Gilang Maulana Majid

The growing interest in intelligent automation adoption and development in tourism presents many potential solutions for sustainable tourism issues. To map the current landscape of research on intelligent automation in sustainable tourism, a systematic review was conducted of 213 scholarly articles. Five major themes were identified: intelligent automation to enhance tourist experience, preserve heritage, promote quality of life, measure tourist experience, and conserve the environment. Scholarly work on this topic has paid more attention to the economic and sociocultural aspects of sustainability but less to addressing environmental issues. To uncover further research gaps, this study outlines sustainability transition pathways using two dimensions: sustainability inclusion and tourist involvement. Twenty-three distinct AI-based innovations were mapped onto the pathways to reveal future research directions. The findings explain the lack of AI-based solutions that offer high levels of sustainability inclusion and tourist involvement. Thus, this study proposes the “AI4GoodTourism” framework, inferring that intelligent automation with high sustainability inclusion levels can scale up the marginal contributions that tourists provide collectively. This framework serves to guide future research and development for various stakeholders who are progressing sustainable tourism agendas through intelligent automation.

Recent advancement in Generative Conversational Artificial Intelligence (AI) has opened the possibility of promoting chatbots for nudging. Tourists returning home from destinations that enforce sustainable transport regulations might be nudged to continue traveling sustainably. Through exploratory qualitative research, this study conceptualizes a chatbot to facilitate pro-environmental behavior spillover among domestic tourists in the Gili Islands, Indonesia. The Service Design approach and Grounded Theory were applied throughout the data collection process involving semi-structured in-depth interviews, focus group discussions and field observations. Insights obtained from stakeholders from multidisciplinary backgrounds were used to provide an overview of how the chatbot can be developed and the potential impact it could bring. A theoretical model predicting factors that play important roles in adopting the proposed chatbot and its respective nudges was developed. It informs policymakers and practitioners about the potential use of AI to help transform tourist experiences and shape lasting responsible behaviors.

Given proper facilitation, pro-environmental behaviour in tourist destinations may spill over to the daily lives of tourists. Recent advancements in conversational artificial intelligence (AI) may lead to the emergence of more effective technology that will encourage people to become more environmentally friendly. However, limited research has been devoted to understanding the complexity of using such technologies for pro-social nudging. This study applies rigorous scale development procedures to test how advanced conversational AI, like chatbots, can be effective in encouraging pro-environmental behaviour spillover. The conceptual model introduces seven factors that predict people’s intention to use the chatbot and three factors that predict their intention to embrace the target behaviour. Performance expectancy and timing were the most significant in predicting the intention of individuals to adopt the technology. Efficiency and government support were the chief drivers of the intention to adopt pro-environmental behaviour. The findings suggest that although introducing a technology-mediated nudging mechanism can trigger people’s intention to behave pro-environmentally, other factors must be fulfilled in order to ensure sustained behaviour change in society.