人工智能驱动的可持续旅游：开启循环经济，克服变革阻力

IF 12.5 1区管理学 Q1 BUSINESS

Business Strategy and The Environment Pub Date : 2025-03-31 DOI:10.1002/bse.4276

Hwang Bang‐Ning, Siriprapha Jitanugoon, Pittinun Puntha

{"title":"人工智能驱动的可持续旅游：开启循环经济，克服变革阻力","authors":"Hwang Bang‐Ning, Siriprapha Jitanugoon, Pittinun Puntha","doi":"10.1002/bse.4276","DOIUrl":null,"url":null,"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.","PeriodicalId":9518,"journal":{"name":"Business Strategy and The Environment","volume":"36 1","pages":""},"PeriodicalIF":12.5000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"AI‐Powered Sustainable Tourism: Unlocking Circular Economies and Overcoming Resistance to Change\",\"authors\":\"Hwang Bang‐Ning, Siriprapha Jitanugoon, Pittinun Puntha\",\"doi\":\"10.1002/bse.4276\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":9518,\"journal\":{\"name\":\"Business Strategy and The Environment\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":12.5000,\"publicationDate\":\"2025-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Business Strategy and The Environment\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1002/bse.4276\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business Strategy and The Environment","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1002/bse.4276","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}

引用次数: 0

摘要

本研究探讨了泰国旅游业中人工智能（AI）与循环经济（CE）原则的整合。它探讨了人工智能增强的预测性废物分析（AI - PWA）、再生资源整合（RRI）、动态物料流优化（DMFO）和人工智能诱导的变化抵抗（AIRC）之间的相互作用。采用混合方法，通过偏最小二乘结构方程建模（PLS‐SEM）将行业利益相关者的定性见解与定量分析相结合。研究结果表明，AI - PWA改善了实时资源管理，推动了DMFO的发展，并通过RRI支持了可再生实践。然而，AIRC缓和了人工智能在可持续性转型中的有效性，因为人们担心失业、不信任和复杂性会阻碍人工智能的采用。本研究提供了可操作的策略，以减轻阻力，加强利益相关者合作，并在资源受限的情况下扩大人工智能的采用，从而为可持续发展目标12和13做出贡献。研究结果为将人工智能创新与高可变性行业的可持续发展相结合提供了实际见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Business Strategy and The Environment Multiple-

CiteScore

22.50

自引率

19.40%

发文量

336

期刊介绍： Business Strategy and the Environment (BSE) is a leading academic journal focused on business strategies for improving the natural environment. It publishes peer-reviewed research on various topics such as systems and standards, environmental performance, disclosure, eco-innovation, corporate environmental management tools, organizations and management, supply chains, circular economy, governance, green finance, industry sectors, and responses to climate change and other contemporary environmental issues. The journal aims to provide original contributions that enhance the understanding of sustainability in business. Its target audience includes academics, practitioners, business managers, and consultants. However, BSE does not accept papers on corporate social responsibility (CSR), as this topic is covered by its sibling journal Corporate Social Responsibility and Environmental Management. The journal is indexed in several databases and collections such as ABI/INFORM Collection, Agricultural & Environmental Science Database, BIOBASE, Emerald Management Reviews, GeoArchive, Environment Index, GEOBASE, INSPEC, Technology Collection, and Web of Science.