Suheil Neiroukh, Okechukwu Lawrence Emeagwali, Hasan Yousef Aljuhmani
{"title":"Artificial intelligence capability and organizational performance: unraveling the mediating mechanisms of decision-making processes","authors":"Suheil Neiroukh, Okechukwu Lawrence Emeagwali, Hasan Yousef Aljuhmani","doi":"10.1108/md-10-2023-1946","DOIUrl":null,"url":null,"abstract":"PurposeThis study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.Design/methodology/approachDrawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.FindingsThe results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.Originality/valueThis study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.","PeriodicalId":4,"journal":{"name":"ACS Applied Energy Materials","volume":"44 10","pages":""},"PeriodicalIF":5.5000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Energy Materials","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/md-10-2023-1946","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
PurposeThis study investigates the profound impact of artificial intelligence (AI) capabilities on decision-making processes and organizational performance, addressing a crucial gap in the literature by exploring the mediating role of decision-making speed and quality.Design/methodology/approachDrawing upon resource-based theory and prior research, this study constructs a comprehensive model and hypotheses to illuminate the influence of AI capabilities within organizations on decision-making speed, decision quality, and, ultimately, organizational performance. A dataset comprising 230 responses from diverse organizations forms the basis of the analysis, with the study employing a partial least squares structural equation model (PLS-SEM) for robust data examination.FindingsThe results demonstrate the pivotal role of AI capabilities in shaping organizational decision-making processes and performance. AI capability significantly and positively affects decision-making speed, decision quality, and overall organizational performance. Notably, decision-making speed is a critical factor contributing significantly to enhanced organizational performance. The study further uncovered partial mediation effects, suggesting that decision-making processes partially mediate the relationship between AI capabilities and organizational performance through decision-making speed.Originality/valueThis study contributes to the existing body of literature by providing empirical evidence of the multifaceted impact of AI capabilities on organizational decision-making and performance. Elucidating the mediating role of decision-making processes advances our understanding of the complex mechanisms through which AI capabilities drive organizational success.
期刊介绍:
ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.