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

Hwang Bang‐Ning,

Siriprapha Jitanugoon, Pittinun Puntha

et al.

Business Strategy and the Environment, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

ABSTRACT This study examines the integration of artificial intelligence (AI) with circular economy (CE) principles in Thailand's tourism industry. It explores 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 quantitative analysis via Partial Least Squares Structural Equation Modeling (PLS‐SEM). Findings reveal that AI‐PWA improves real‐time resource management, driving DMFO supporting regenerative practices through RRI. However, AIRC moderates AI's effectiveness sustainability transitions, concerns such as job displacement, mistrust, complexity hindering adoption. provides actionable strategies mitigate resistance, enhance stakeholder collaboration, scale AI adoption resource‐constrained settings, contributing SDG 12 13. The findings offer practical for aligning innovations sustainable development high‐variability industries.

Language: Английский

Harnessing Marketing Intelligence and AI to Understand Consumer Behavior in the Education Sector in Smart Cities DOI
Amit Pandey,

Vijit Chaturvedi,

Jaya Yadav

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 25 - 48

Published: Feb. 27, 2025

New-age marketing intelligence and AI are shaping the way education sector harnesses consumer understanding in smart cities where digital infrastructure technology integration is at its boom. AI-driven systems like predictive analytics machine learning algorithms allow institutions to analyze large datasets, uncover correlations, predict trends. For example, this data could help identify essential segments such as students, parents, educators, allowing them target with tailored strategies. These kinds of city using IoT devices real-time deliver adaptive according various urban demands. can empower decision-making process greater accuracy relevance campaigns. Challenges ethical use, privacy concerns, equitable access will have be addressed. Leveraging marketing/sales include more audiences, drive creativity innovation into generation that complement sustainability developments cities.

Language: Английский

Citations

0
AI‐Powered Sustainable Tourism: Unlocking Circular Economies and Overcoming Resistance to Change DOI Open Access

Hwang Bang‐Ning,

Siriprapha Jitanugoon, Pittinun Puntha

et al.

Business Strategy and the Environment, Journal Year: 2025, Volume and Issue: unknown

Published: March 28, 2025

ABSTRACT This study examines the integration of artificial intelligence (AI) with circular economy (CE) principles in Thailand's tourism industry. It explores 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 quantitative analysis via Partial Least Squares Structural Equation Modeling (PLS‐SEM). Findings reveal that AI‐PWA improves real‐time resource management, driving DMFO supporting regenerative practices through RRI. However, AIRC moderates AI's effectiveness sustainability transitions, concerns such as job displacement, mistrust, complexity hindering adoption. provides actionable strategies mitigate resistance, enhance stakeholder collaboration, scale AI adoption resource‐constrained settings, contributing SDG 12 13. The findings offer practical for aligning innovations sustainable development high‐variability industries.

Language: Английский

Citations

0