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AuthorRana, Nripendra P.
AuthorChatterjee, Sheshadri
AuthorDwivedi, Yogesh K.
AuthorAkter, Shahriar
Available date2023-06-12T11:43:56Z
Publication Date2021-08-01
Publication NameEuropean Journal of Information Systems
Identifierhttp://dx.doi.org/10.1080/0960085X.2021.1955628
CitationRana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2022). Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364-387.
ISSN0960-085X
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85111903831&origin=inward
URIhttp://hdl.handle.net/10576/44408
AbstractThe data-centric revolution generally celebrates the proliferation of business analytics and AI in exploiting firm’s potential and success. However, there is a lack of research on how the unintended consequences of AI integrated business analytics (AI-BA) influence a firm’s overall competitive advantage. In this backdrop, this study aims to identify how factors, such as AI-BA opacity, suboptimal business decisions and perceived risk are responsible for a firm’s operational inefficiency and competitive disadvantage. Drawing on the resource-based view, dynamic capability view, and contingency theory, the proposed research model captures the components and effects of an AI-BA opacity on a firm’s risk environment and negative performance. The data were gathered from 355 operational, mid-level and senior managers from various service sectors across all different size organisations in India. The results indicated that lack of governance, poor data quality, and inefficient training of key employees led to an AI-BA opacity. It then triggers suboptimal business decisions and higher perceived risk resulting in operational inefficiency. The findings show that operational inefficiency significantly contributes to negative sales growth and employees’ dissatisfaction, which result in a competitive disadvantage for a firm. The findings also highlight the significant moderating effect of contingency plan in the nomological chain.
SponsorThe Open Access funding for this research has been provided by the Qatar National Library.
Languageen
PublisherTaylor & Francis
SubjectArtificial intelligence
business analytics
firm dis-performance
firm’s competitiveness
operational inefficiency
Patrick Mikalef, Aleš Popovic, Jenny Eriksson Lundström and Kieran Conboy
TitleUnderstanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness
TypeArticle
Pagination364-387
Issue Number3
Volume Number31
ESSN1476-9344
dc.accessType Open Access


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