Work

AI‐Powered Sustainable Tourism: Unlocking Circular Economies and Overcoming Resistance to Change

Year: 2025

Type: article

Abstract: ABSTRACT This study examines the integration of artificial intelligence (AI) with circular economy (CE) principles in Thailand's tourism industry. It explores the interactions between AI‐Enhanced Predictive Waste Analytics (AI‐PWA), Regenerative Resource Integration (RRI), Dynamic Material Flow Optimization (DMFO), and AI‐Induced Resistance to Change (AIRC). Using a mixed‐methods approach, qualitative insights from industry stakeholders are combined with quantitative analysis via Partial Least Squares Structural Equation Modeling (PLS‐SEM). Findings reveal that AI‐PWA improves real‐time resource management, driving DMFO and supporting regenerative practices through RRI. However, AIRC moderates AI's effectiveness in sustainability transitions, with concerns such as job displacement, mistrust, and complexity hindering adoption. This study provides actionable strategies to mitigate resistance, enhance stakeholder collaboration, and scale AI adoption in resource‐constrained settings, contributing to SDG 12 and SDG 13. The findings offer practical insights for aligning AI innovations with sustainable development in high‐variability industries.

Source: Business Strategy and the Environment

DOI: 10.1002/bse.4276

Authors: Hwang Bang‐Ning, Siriprapha Jitanugoon, Pittinun Puntha

Institution: National Yunlin University of Science and Technology

Language: English

Topic: Diverse Aspects of Tourism Research

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production, Decent work and economic growth, Climate action

Open Access status: bronze

OpenAlex ID: W4408989468

FWCI: 57.16

Cites: 174

Cited by: 32

Related to: 10