{"title":"AI adoption for green performance: An understanding of moderated mediation model","authors":"Arooj Azhar , Nabeel Rehman , Tahir Alyas , Bilal Iftikhar Makki","doi":"10.1016/j.ijhm.2025.104191","DOIUrl":null,"url":null,"abstract":"<div><div>As organizations globally turn to sustainable practices, the integration of Artificial Intelligence (AI) into Green Human Resource Management (GHRM) emerges as a pivotal strategy. In hospitality sector, this approach is gaining traction as a means to enhance green performance. This study examines the role of AI adoption in enhancing GHRM practices to improve green performance through the mediation of green commitment and employee retention. Employee technological readiness is examined as a moderator between AI adoption and GHRM practices. Data was collected from hotel managers in Pakistan, and was analyzed using SMART PLS 4.0. The results indicate that AI adoption significantly enhances GHRM practices which improve green performance through increased green commitment and employee retention. Additionally, employee technological readiness strengthens the relationship between AI adoption and GHRM practices. These findings provide critical insights for the hospitality sector, highlighting the potential of AI-driven GHRM practices to foster sustainability and improve organizational performance.</div></div>","PeriodicalId":48444,"journal":{"name":"International Journal of Hospitality Management","volume":"129 ","pages":"Article 104191"},"PeriodicalIF":9.9000,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hospitality Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0278431925001148","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
引用次数: 0
Abstract
As organizations globally turn to sustainable practices, the integration of Artificial Intelligence (AI) into Green Human Resource Management (GHRM) emerges as a pivotal strategy. In hospitality sector, this approach is gaining traction as a means to enhance green performance. This study examines the role of AI adoption in enhancing GHRM practices to improve green performance through the mediation of green commitment and employee retention. Employee technological readiness is examined as a moderator between AI adoption and GHRM practices. Data was collected from hotel managers in Pakistan, and was analyzed using SMART PLS 4.0. The results indicate that AI adoption significantly enhances GHRM practices which improve green performance through increased green commitment and employee retention. Additionally, employee technological readiness strengthens the relationship between AI adoption and GHRM practices. These findings provide critical insights for the hospitality sector, highlighting the potential of AI-driven GHRM practices to foster sustainability and improve organizational performance.
期刊介绍:
The International Journal of Hospitality Management serves as a platform for discussing significant trends and advancements in various disciplines related to the hospitality industry. The publication covers a wide range of topics, including human resources management, consumer behavior and marketing, business forecasting and applied economics, operational management, strategic management, financial management, planning and design, information technology and e-commerce, training and development, technological developments, and national and international legislation.
In addition to covering these topics, the journal features research papers, state-of-the-art reviews, and analyses of business practices within the hospitality industry. It aims to provide readers with valuable insights and knowledge in order to advance research and improve practices in the field.
The journal is also indexed and abstracted in various databases, including the Journal of Travel Research, PIRA, Academic Journal Guide, Documentation Touristique, Leisure, Recreation and Tourism Abstracts, Lodging and Restaurant Index, Scopus, CIRET, and the Social Sciences Citation Index. This ensures that the journal's content is widely accessible and discoverable by researchers and practitioners in the hospitality field.