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Status已发表Published
TitleExamining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour
Creator
Date Issued2018-09-20
Source PublicationJournal of Cleaner Production
ISSN0959-6526
Volume196Pages:1508-1521
Abstract

The organizations engaged in sustainable development programmes are increasingly paying serious attention towards synergetic relationships between focal firms and their partners to achieve the goal of sustainable consumption and production (SCP) via big data and predictive analytics (BDPA). The study examines the role of BDPA in collaborative performance (CP) among the partners engaged in sustainable development programme to achieve the goal of SCP. The study further investigates the contingent effect of organization fit on the impact of BDPA on CP. We used variance based structural equation modelling (PLS SEM) to test research hypotheses using a sample of 190 respondents working in auto-components manufacturing organizations in India drawn from the ACMA and Dun & Bradstreet databases. The results indicate that BDPA has a significant positive impact on the CP among partners and the organizational compatibility and resource complementarity have positive moderating effects on the path joining BDPA and CP. The study contributes to the understanding of BDPA and collaboration literature in the context of sustainable development. These findings extend the dynamic capability view (DCV) to create a better understanding of contemporary applications of big data and predictive analytics capability, while also providing theoretically grounded directions to managers who seek to use information processing technologies to continuously improve the collaboration in supply chain networks. We have also noted some of the limitations of our study and identified numerous further research directions.

KeywordCollaboration Inter-organizational fit Resource complementarity Sustainable consumption Sustainable operations Sustainable production
DOI10.1016/j.jclepro.2018.06.097
URLView source
Indexed BySCIE ; SSCI
Language英语English
WOS Research AreaScience & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology
WOS SubjectGreen & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences
WOS IDWOS:000444364400129
Scopus ID2-s2.0-85048757480
Citation statistics
Cited Times:113[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6901
CollectionResearch outside affiliated institution
Corresponding AuthorLuo, Zongwei
Affiliation
1.Montpellier Business School,Montpellier Research in Management,Montpellier,2300 Avenue des Moulins,34185,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.Computer Science and Engineering Department,Southern University of Science and Technology of China,Shenzen,1088 Xueyuan Blvd.,518055,China
5.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. Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour[J]. Journal of Cleaner Production, 2018, 196: 1508-1521.
APA Dubey, Rameshwar., Gunasekaran, Angappa., Childe, Stephen J., Luo, Zongwei., Wamba, Samuel Fosso., .. & Foropon, Cyril. (2018). Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour. Journal of Cleaner Production, 196, 1508-1521.
MLA Dubey, Rameshwar,et al."Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour". Journal of Cleaner Production 196(2018): 1508-1521.
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