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dc.contributor.authorSivarajah, Uthayasankar
dc.contributor.authorKumar, S.
dc.contributor.authorKumar, V.
dc.contributor.authorChatterjee, S.
dc.contributor.authorLi, Jing
dc.date.accessioned2024-03-10T17:10:57Z
dc.date.accessioned2024-04-09T15:20:55Z
dc.date.available2024-03-10T17:10:57Z
dc.date.available2024-04-09T15:20:55Z
dc.date.issued2024-05
dc.identifier.citationSivarajah U, Kumar S, Kumar V et al (2024) A study on big data analytics and innovation: From technological and business cycle perspectives. Technological Forecasting and Social Change. 202: 123328.en_US
dc.identifier.urihttp://hdl.handle.net/10454/19875
dc.descriptionYes
dc.description.abstractIn today’s rapidly changing business landscape, organizations increasingly invest in different technologies to enhance their innovation capabilities. Among the technological investment, a notable development is the applications of big data analytics (BDA), which plays a pivotal role in supporting firms’ decision-making processes. Big data technologies are important factors that could help both exploratory and exploitative innovation, which could affect the efforts to combat climate change and ease the shift to green energy. However, studies that comprehensively examine BDA’s impact on innovation capability and technological cycle remain scarce. This study therefore investigates the impact of BDA on innovation capability, technological cycle, and firm performance. It develops a conceptual model, validated using CB-SEM, through responses from 356 firms. It is found that both innovation capability and firm performance are significantly influenced by big data technology. This study highlights that BDA helps to address the pressing challenges of climate change mitigation and the transition to cleaner and more sustainable energy sources. However, our results are based on managerial perceptions in a single country. To enhance generalizability, future studies could employ a more objective approach and explore different contexts. Multidimensional constructs, moderating factors, and rival models could also be considered in future studies.en_US
dc.language.isoenen_US
dc.publisherElsevier
dc.rights© 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.subjectBig data analytics
dc.subjectTechnological cycle
dc.subjectTechnological innovation
dc.subjectFirm performance
dc.subjectBusiness cycle
dc.subjectIncremental change
dc.titleA study on big data analytics and innovation: From technological and business cycle perspectivesen_US
dc.status.refereedYes
dc.date.application13/03/2024
dc.typeArticle
dc.type.versionPublished version
dc.identifier.doihttps://doi.org/10.1016/j.techfore.2024.123328en_US
dc.rights.licenseCC-BYen_US
dc.date.updated2024-03-10T17:10:59Z
refterms.dateFOA2024-04-09T15:22:24Z
dc.openaccess.statusopenAccess
dc.date.accepted08/03/2024


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