Artificial intelligence-driven decision making and firm performance: a quantitative approach

IF 4.1 3区管理学 Q2 BUSINESS

Management Decision Pub Date : 2024-06-10 DOI:10.1108/md-10-2023-1966

Chiara Giachino, Martin Cepel, Elisa Truant, Augusto Bargoni

{"title":"Artificial intelligence-driven decision making and firm performance: a quantitative approach","authors":"Chiara Giachino, Martin Cepel, Elisa Truant, Augusto Bargoni","doi":"10.1108/md-10-2023-1966","DOIUrl":null,"url":null,"abstract":"PurposeThe purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making.Design/methodology/approachWe surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data.FindingsResults indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making.Originality/valueThese findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.","PeriodicalId":18046,"journal":{"name":"Management Decision","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Management Decision","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/md-10-2023-1966","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

PurposeThe purpose of this study is to investigate the relationship between artificial intelligence (AI) and decision making in the development of AI-related capabilities. We investigate if and how AI-driven decision making has an impact on firm performance. We also investigate the role played by environmental dynamism in the development of AI capabilities and AI-driven decision making.Design/methodology/approachWe surveyed 346 managers in the United States using established scales from the literature and leveraged p modelling to analyse the data.FindingsResults indicate that AI-driven decision making is positively related to firm performance and that big data-powered AI positively influences AI-driven decision making. Moreover, there is a positive relationship between big data-powered AI and the development of AI capability within a firm. It is also found that the control variables of firm size and age do not significantly affect firm performance. Finally, environmental dynamism does not have a positive and significant moderating effect on the path connecting big data-powered AI and AI-driven decision making, while it exerts a positive moderating effect on the development of AI capability to strengthen AI-driven decision making.Originality/valueThese findings extend the resource-based view by highlighting the capabilities developed within the firm to manage big data-powered AI. This research also provides theoretically grounded guidance to managers wanting to align their AI-driven decision making with superior firm performance.

查看原文本刊更多论文

人工智能驱动的决策与企业绩效：一种定量方法

本研究旨在探讨人工智能（AI）与决策之间在发展人工智能相关能力方面的关系。我们研究人工智能驱动的决策是否以及如何对企业绩效产生影响。我们使用文献中的既定量表对美国的 346 名管理人员进行了调查，并利用 p 模型对数据进行了分析。结果结果表明，人工智能驱动的决策与企业绩效正相关，大数据驱动的人工智能对人工智能驱动的决策有积极影响。此外，大数据驱动的人工智能与企业内部人工智能能力的发展之间存在正相关关系。研究还发现，企业规模和年龄这两个控制变量对企业绩效没有显著影响。最后，环境动态对大数据驱动的人工智能与人工智能驱动的决策之间的连接路径没有积极和显著的调节作用，而对人工智能能力的发展却有积极的调节作用，从而加强了人工智能驱动的决策。原创性/价值这些研究结果扩展了基于资源的观点，强调了企业内部发展的管理大数据驱动的人工智能的能力。这项研究还为希望将人工智能驱动的决策与卓越的公司业绩相结合的管理者提供了有理论依据的指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Management Decision Multiple-

CiteScore

8.20

自引率

8.70%

发文量

126

期刊介绍： ■In-depth studies of major issues ■Operations management ■Financial management ■Motivation ■Entrepreneurship ■Problem solving and proactivity ■Serious management argument ■Strategy and policy issues ■Tactics for turning around company crises Management Decision, considered by many to be the best publication in its field, consistently offers thoughtful and provocative insights into current management practice. As such, its high calibre contributions from leading management philosophers and practitioners make it an invaluable resource in the aggressive and demanding trading climate of the Twenty-First Century.