Maria Chiara De Lorenzi, Marta Menegoli, Maria Laura Giangrande
{"title":"Igniting twin transition through artificial intelligence and stakeholder value: The case of platform-based agri-food companies","authors":"Maria Chiara De Lorenzi, Marta Menegoli, Maria Laura Giangrande","doi":"10.1016/j.jengtecman.2025.101920","DOIUrl":null,"url":null,"abstract":"<div><div>This study presents an original and relevant exploration of how platform-based companies can leverage Artificial Intelligence to address sustainability challenges, particularly in compliance with European Sustainable Development Goals. Starting by the observation of platformization as a process bringing to Business Model Innovation and focusing on the intersection of Artificial Intelligence and sustainability, the study fills a critical gap in existing literature, which often overlooks the specific implications of Artificial Intelligence integration in various business scenarios. A comprehensive conceptual framework that guides the study’s investigation into Artificial Intelligence as a boost for the twin transition with a focus on advancing stakeholder legitimacy within agri-food platform-based companies was designed. The study was based on a qualitative research approach through a three-phases methodology. The results of study derived from a Systematic Literature Review within content analysis and multiple case study that using desktop analysis on a 52 platform-based agri-food companies sample. Follow a discussion through inside-out and outside-in perspective underline results evidence in order to build academic evidence for practice and empirical evidence for academia. The use of Artificial Intelligence in sustainable practices provides concrete evidence that enhances the understanding of how value is created, captured, and delivered within platform-based business models for sustainability. Moreover, the impact of these AI-driven practices on stakeholder perceptions offers updated empirical insights into Stakeholder Theory, particularly regarding the practical mechanisms through which normative legitimacy is built or undermined in the context of advanced technologies. The research agenda outlines critical avenues for future investigation. These directions aim to deepen our understanding of the complex interplay between advanced technologies, sustainable transformation, and societal acceptance.</div></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":"78 ","pages":"Article 101920"},"PeriodicalIF":3.9000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering and Technology Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S092347482500061X","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
Abstract
This study presents an original and relevant exploration of how platform-based companies can leverage Artificial Intelligence to address sustainability challenges, particularly in compliance with European Sustainable Development Goals. Starting by the observation of platformization as a process bringing to Business Model Innovation and focusing on the intersection of Artificial Intelligence and sustainability, the study fills a critical gap in existing literature, which often overlooks the specific implications of Artificial Intelligence integration in various business scenarios. A comprehensive conceptual framework that guides the study’s investigation into Artificial Intelligence as a boost for the twin transition with a focus on advancing stakeholder legitimacy within agri-food platform-based companies was designed. The study was based on a qualitative research approach through a three-phases methodology. The results of study derived from a Systematic Literature Review within content analysis and multiple case study that using desktop analysis on a 52 platform-based agri-food companies sample. Follow a discussion through inside-out and outside-in perspective underline results evidence in order to build academic evidence for practice and empirical evidence for academia. The use of Artificial Intelligence in sustainable practices provides concrete evidence that enhances the understanding of how value is created, captured, and delivered within platform-based business models for sustainability. Moreover, the impact of these AI-driven practices on stakeholder perceptions offers updated empirical insights into Stakeholder Theory, particularly regarding the practical mechanisms through which normative legitimacy is built or undermined in the context of advanced technologies. The research agenda outlines critical avenues for future investigation. These directions aim to deepen our understanding of the complex interplay between advanced technologies, sustainable transformation, and societal acceptance.
期刊介绍:
The Journal of Engineering and Technology Management (JET-M) is an international scholarly refereed research journal which aims to promote the theory and practice of technology, innovation, and engineering management.
The journal links engineering, science, and management disciplines. It addresses the issues involved in the planning, development, and implementation of technological capabilities to shape and accomplish the strategic and operational objectives of an organization. It covers not only R&D management, but also the entire spectrum of managerial concerns in technology-based organizations. This includes issues relating to new product development, human resource management, innovation process management, project management, technological fusion, marketing, technological forecasting and strategic planning.
The journal provides an interface between technology and other corporate functions, such as R&D, marketing, manufacturing and administration. Its ultimate goal is to make a profound contribution to theory development, research and practice by serving as a leading forum for the publication of scholarly research on all aspects of technology, innovation, and engineering management.