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• W4387668328 abstract "AbstractAcademics and practitioners have identified the potential of Big Data Analytics capability (BDAC) and Lean Social-Technical system to improve sustainability performance. Nonetheless, there is still a limited understanding of how companies’ BDAC efforts can contribute to Lean Practices and transform this relationship into sustainability-related benefits, impacting economic, social, and environmental performance. A comprehensive conceptual model to assess the mediating effect of Lean Social Practices (LSP) and Lean Technical Practices (LTP) on the relationship between BDAC and economic, social, and environmental performance was developed and tested with a sample of 108 respondents, from Brazilian industrial companies. The results obtained using Partial Least Squares Structural Equation Modeling (PLS-SEM), showed that the relationship between BDAC and economic performance is completely mediated by LTP. However, LSP does not mediate the relationships between BDAC and sustainability performance. The findings provide guidance to companies regarding resource allocations for BDAC and Lean to foster sustainability.Keywords: Big data analytics capabilitylean technicallean socialsustainability performancestructural equation modeling AcknowledgmentsThe third author acknowledge Fundação para a Ciência e a Tecnologia (FCT – MCTES) for its financial support via the project UIDB/00667/2020 and UIDP/00667/2020 (UNIDEMI).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was financially supported by Fundação para a Ciência e a Tecnologia (FCT – MCTES) via the project UIDB/00667/2020 and UIDP/00667/2020 (UNIDEMI).Notes on contributorsLígia Lobo MesquitaLígia Lobo Mesquita is a Ph.D. in Industrial Engineering from the Federal University of São Carlos – UFSCar, São Carlos, Brazil, in 2022. She is an Associate Professor at the Department of Industrial Engineering at the Federal University of Alagoas – UFAL, where she teaches quality control, quality management systems, production planning and control, and factory design and layout. Her research interests focus on the relationships between Industry 4.0 Technologies, Lean Manufacturing Practices and sustainability performance. Mainly on improving economic, environmental and social performance through the relationship between Industry 4.0 and Lean.Fabiane Letícia LizarelliFabiane Letícia Lizarelli is an Associate Professor at the Production Engineering Department on Universidade Federal de São Carlos, Brazil. She holds B.Sc., M.Sc., and Ph.D. degrees from the Federal University of São Carlos, São Carlos, Brazil, in 2005, 2008, and 2013, respectively. Her research interests are in continuous improvement programs such as Six Sigma, Lean and Lean Six Sigma and she has been studying the relationship of these programs with Industry 4.0 technologies, mainly Big Data Analytics. She has studied and published in renowned and refereed journals and conferences on these topics for the past ten years.Susana DuarteSusana Duarte holds a Ph.D. in Industrial Engineering. Presently she is an Assistant Professor of Industrial Engineering at School of Science and Technology of the Universidade NOVA de Lisboa, Portugal. She lectures several courses on topics related to industrial engineering including, production management, industrial management and strategy, industrial engineering, logistics, lean and six sigma, among others. She is a research member of UNIDEMI Research Centre where develops their investigation in lean manufacturing, green management, lean-green supply chain, and performance measurement systems. She has published scientific papers in several international refereed journals and international conferences proceedings. She was awarded the Outstanding Paper Award (Awards for Excellence) from Emerald Group Publishing, a Teaching Excellence Award from IEOM society and three paper awards from International Conferences. She is a member of the board of the Portuguese Institute of Industrial Engineering." @default.
• W4387668328 created "2023-10-17" @default.
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• W4387668328 date "2023-10-16" @default.
• W4387668328 modified "2023-10-17" @default.
• W4387668328 title "Big data analytics and lean practices: impact on sustainability performance" @default.
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