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Status已发表Published
TitleCan big data and predictive analytics improve social and environmental sustainability?
Creator
Date Issued2019-07-01
Source PublicationTechnological Forecasting and Social Change
ISSN0040-1625
Volume144Pages:534-545
Abstract

Although literature indicates that big data and predictive analytics (BDPA)convey a distinct organisational capability, little is known about their performance effects in particular contextual conditions (inter alia, national context and culture, and firm size). Grounding our investigation in the dynamic capability views and organisational culture and based on a sample of 205 Indian manufacturing organisations, we empirically investigate the effects of BDPA on social performance (SP)and environmental performance (EP)using variance based structural equation modelling (i.e. PLS). We find that BDPA has significant impact on SP/EP. However, we did not find evidence for moderating role of flexible orientation and control orientation in the links between BDPA and SP/EP. Our findings offer a more nuanced understanding of the performance implications of BDPA, thereby addressing the crucial questions of how and when BDPA can enhance social/environmental sustainability in supply chains.

KeywordBig data Dynamic capability view Environmental sustainability Predictive analytics Social sustainability Supply chains
DOI10.1016/j.techfore.2017.06.020
URLView source
Indexed BySSCI
Language英语English
WOS Research AreaBusiness & Economics ; Public Administration
WOS SubjectBusiness ; Regional & Urban Planning
WOS IDWOS:000471735700048
Scopus ID2-s2.0-85023643537
Citation statistics
Cited Times:446[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6889
CollectionResearch outside affiliated institution
Corresponding AuthorPapadopoulos, Thanos
Affiliation
1.Montpellier Business School,Montpellier Research in Management,Montpellier,2300 Avenue des Moulins,34000,France
2.School of Business and Public Administration California State University,Bakersfield,Bakersfield 9001 Stockdale Highway,93311-1022,United States
3.Plymouth Business School,Plymouth University,Plymouth,PL4 8AA,United Kingdom
4.Kent Business School,University of Kent,Kent,Sail and Colour Loft, The Historic Dockyard, Chatham,ME4 4TE,United Kingdom
5.Computer Science & Engineering,Southern University of Science and Technology,Shenzen,1088 Xueyuan Blvd.,518055,China
6.Toulouse Business School,Toulouse University,Toulouse,20 Boulevard Lascrosses,31068,France
Recommended Citation
GB/T 7714
Dubey, Rameshwar,Gunasekaran, Angappa,Childe, Stephen J.et al. Can big data and predictive analytics improve social and environmental sustainability?[J]. Technological Forecasting and Social Change, 2019, 144: 534-545.
APA Dubey, Rameshwar., Gunasekaran, Angappa., Childe, Stephen J., Papadopoulos, Thanos., Luo, Zongwei., .. & Roubaud, David. (2019). Can big data and predictive analytics improve social and environmental sustainability?. Technological Forecasting and Social Change, 144, 534-545.
MLA Dubey, Rameshwar,et al."Can big data and predictive analytics improve social and environmental sustainability?". Technological Forecasting and Social Change 144(2019): 534-545.
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