The impact of big data analytics on firms’ high value business performance

Detalhes bibliográficos
Autor(a) principal: Popovič, Aleš
Data de Publicação: 2018
Outros Autores: Hackney, Ray, Tassabehji, Rana, Castelli, Mauro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.1007/s10796-016-9720-4
Resumo: Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209-222. https://doi.org/10.1007/s10796-016-9720-4
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spelling The impact of big data analytics on firms’ high value business performanceBig data analyticsBusiness valueCase analysisOperations performanceTheoretical Computer ScienceSoftwareInformation SystemsComputer Networks and CommunicationsPopovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209-222. https://doi.org/10.1007/s10796-016-9720-4Big Data Analytics (BDA) is an emerging phenomenon with the reported potential to transform how firms manage and enhance high value businesses performance. The purpose of our study is to investigate the impact of BDA on operations management in the manufacturing sector, which is an acknowledged infrequently researched context. Using an interpretive qualitative approach, this empirical study leverages a comparative case study of three manufacturing companies with varying levels of BDA usage (experimental, moderate and heavy). The information technology (IT) business value literature and a resource based view informed the development of our research propositions and the conceptual framework that illuminated the relationships between BDA capability and organizational readiness and design. Our findings indicate that BDA capability (in terms of data sourcing, access, integration, and delivery, analytical capabilities, and people’s expertise) along with organizational readiness and design factors (such as BDA strategy, top management support, financial resources, and employee engagement) facilitated better utilization of BDA in manufacturing decision making, and thus enhanced high value business performance. Our results also highlight important managerial implications related to the impact of BDA on empowerment of employees, and how BDA can be integrated into organizations to augment rather than replace management capabilities. Our research will be of benefit to academics and practitioners in further aiding our understanding of BDA utilization in transforming operations and production management. It adds to the body of limited empirically based knowledge by highlighting the real business value resulting from applying BDA in manufacturing firms and thus encouraging beneficial economic societal changes.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNPopovič, AlešHackney, RayTassabehji, RanaCastelli, Mauro2019-10-23T22:26:35Z20182018-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article14application/pdfhttps://doi.org/10.1007/s10796-016-9720-4eng1387-3326PURE: 3236645http://www.scopus.com/inward/record.url?scp=84992743798&partnerID=8YFLogxKhttps://doi.org/10.1007/s10796-016-9720-4info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T04:38:20Zoai:run.unl.pt:10362/85246Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:36:35.852482Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The impact of big data analytics on firms’ high value business performance
title The impact of big data analytics on firms’ high value business performance
spellingShingle The impact of big data analytics on firms’ high value business performance
Popovič, Aleš
Big data analytics
Business value
Case analysis
Operations performance
Theoretical Computer Science
Software
Information Systems
Computer Networks and Communications
title_short The impact of big data analytics on firms’ high value business performance
title_full The impact of big data analytics on firms’ high value business performance
title_fullStr The impact of big data analytics on firms’ high value business performance
title_full_unstemmed The impact of big data analytics on firms’ high value business performance
title_sort The impact of big data analytics on firms’ high value business performance
author Popovič, Aleš
author_facet Popovič, Aleš
Hackney, Ray
Tassabehji, Rana
Castelli, Mauro
author_role author
author2 Hackney, Ray
Tassabehji, Rana
Castelli, Mauro
author2_role author
author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Popovič, Aleš
Hackney, Ray
Tassabehji, Rana
Castelli, Mauro
dc.subject.por.fl_str_mv Big data analytics
Business value
Case analysis
Operations performance
Theoretical Computer Science
Software
Information Systems
Computer Networks and Communications
topic Big data analytics
Business value
Case analysis
Operations performance
Theoretical Computer Science
Software
Information Systems
Computer Networks and Communications
description Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. Information Systems Frontiers, 20(2), 209-222. https://doi.org/10.1007/s10796-016-9720-4
publishDate 2018
dc.date.none.fl_str_mv 2018
2018-01-01T00:00:00Z
2019-10-23T22:26:35Z
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dc.language.iso.fl_str_mv eng
language eng
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PURE: 3236645
http://www.scopus.com/inward/record.url?scp=84992743798&partnerID=8YFLogxK
https://doi.org/10.1007/s10796-016-9720-4
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