{"title":"Sustainability risk management: Exploring the role of artificial intelligence capabilities through an information-processing lens.","authors":"Kai Yuan Kong, Kum Fai Yuen","doi":"10.1111/risa.17448","DOIUrl":null,"url":null,"abstract":"<p><p>The global sustainability movement is reshaping the operational requirements and managerial approaches of maritime firms, resulting in the emergence of unprecedented and complex risks in the sector. This has driven maritime firms to leverage digital tools, such as artificial intelligence (AI) capabilities, to enhance their sustainability risk management (SRM) endeavors. Drawing on the organizational information-processing theory (OIPT), this study proposes four AI capabilities: customer value proposition, key process optimization, key resource optimization, and societal good. It examines their influence on sustainability-related knowledge management capabilities (SKMC), stakeholder engagement, and SRM. A survey questionnaire was used to gather responses from 157 maritime professionals across various sectors of the industry, providing empirical data for analysis. Employing structural equation modeling, the findings reveal that AI capabilities can improve SKMC. These findings enhance existing literature by using OIPT concepts to investigate the interplay among the constructs that lead to better SRM in maritime firms. Furthermore, the study offers managerial guidance by providing insights into AI capabilities that maritime firms should incorporate into their operations, fostering best practices to effectively manage sustainability risks and ensure the firm's long-term survival.</p>","PeriodicalId":21472,"journal":{"name":"Risk Analysis","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Risk Analysis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/risa.17448","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The global sustainability movement is reshaping the operational requirements and managerial approaches of maritime firms, resulting in the emergence of unprecedented and complex risks in the sector. This has driven maritime firms to leverage digital tools, such as artificial intelligence (AI) capabilities, to enhance their sustainability risk management (SRM) endeavors. Drawing on the organizational information-processing theory (OIPT), this study proposes four AI capabilities: customer value proposition, key process optimization, key resource optimization, and societal good. It examines their influence on sustainability-related knowledge management capabilities (SKMC), stakeholder engagement, and SRM. A survey questionnaire was used to gather responses from 157 maritime professionals across various sectors of the industry, providing empirical data for analysis. Employing structural equation modeling, the findings reveal that AI capabilities can improve SKMC. These findings enhance existing literature by using OIPT concepts to investigate the interplay among the constructs that lead to better SRM in maritime firms. Furthermore, the study offers managerial guidance by providing insights into AI capabilities that maritime firms should incorporate into their operations, fostering best practices to effectively manage sustainability risks and ensure the firm's long-term survival.
期刊介绍:
Published on behalf of the Society for Risk Analysis, Risk Analysis is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and commentaries dealing with risk issues. The topics covered include:
• Human health and safety risks
• Microbial risks
• Engineering
• Mathematical modeling
• Risk characterization
• Risk communication
• Risk management and decision-making
• Risk perception, acceptability, and ethics
• Laws and regulatory policy
• Ecological risks.