{"title":"In consilium apparatus: Artificial intelligence, stakeholder reciprocity, and firm performance","authors":"Douglas Bosse , Steven Thompson , Peter Ekman","doi":"10.1016/j.jbusres.2022.113402","DOIUrl":null,"url":null,"abstract":"<div><p>Firms are increasingly using forms of AI to serve stakeholders across various business functions, resulting in both positive and negative outcomes. Stakeholder theory explains how firms create and destroy value via their stakeholder encounters, making it an ideal foundation for understanding AI deployment on firm-level performance. As AI continues to evolve, both when it comes to the activities and roles it takes and the stakeholders it affects, the AI-stakeholder framework developed herein identifies and situates key managerial decisions related to the adoption and deployment of AI that drive the firm’s likelihood of creating or destroying value through stakeholder encounters. The AI–stakeholder framework focuses on stakeholder justice and is supported by testable propositions about the conditions most likely to affect the outcomes of incorporating AI into business processes. The framework also supports future research and practical managerial guidance by articulating the challenges and potential of AI for managing stakeholder encounters.</p></div>","PeriodicalId":15123,"journal":{"name":"Journal of Business Research","volume":"155 ","pages":"Article 113402"},"PeriodicalIF":10.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business Research","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0148296322008670","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: 3
Abstract
Firms are increasingly using forms of AI to serve stakeholders across various business functions, resulting in both positive and negative outcomes. Stakeholder theory explains how firms create and destroy value via their stakeholder encounters, making it an ideal foundation for understanding AI deployment on firm-level performance. As AI continues to evolve, both when it comes to the activities and roles it takes and the stakeholders it affects, the AI-stakeholder framework developed herein identifies and situates key managerial decisions related to the adoption and deployment of AI that drive the firm’s likelihood of creating or destroying value through stakeholder encounters. The AI–stakeholder framework focuses on stakeholder justice and is supported by testable propositions about the conditions most likely to affect the outcomes of incorporating AI into business processes. The framework also supports future research and practical managerial guidance by articulating the challenges and potential of AI for managing stakeholder encounters.
期刊介绍:
The Journal of Business Research aims to publish research that is rigorous, relevant, and potentially impactful. It examines a wide variety of business decision contexts, processes, and activities, developing insights that are meaningful for theory, practice, and/or society at large. The research is intended to generate meaningful debates in academia and practice, that are thought provoking and have the potential to make a difference to conceptual thinking and/or practice. The Journal is published for a broad range of stakeholders, including scholars, researchers, executives, and policy makers. It aids the application of its research to practical situations and theoretical findings to the reality of the business world as well as to society. The Journal is abstracted and indexed in several databases, including Social Sciences Citation Index, ANBAR, Current Contents, Management Contents, Management Literature in Brief, PsycINFO, Information Service, RePEc, Academic Journal Guide, ABI/Inform, INSPEC, etc.