Examining the role of big data and predictive analytics on collaborative performance in context to sustainable consumption and production behaviour

Dubey, Rameshwar1; Gunasekaran, Angappa2; Childe, Stephen J.3; Luo, Zongwei4; Wamba, Samuel Fosso5; Roubaud, David1; Foropon, Cyril1

2018-09-20

10.1016/j.jclepro.2018.06.097

Journal of Cleaner Production   影响因子和分区

0959-6526

1879-1786

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. (C) 2018 Elsevier Ltd. All rights reserved.

Sustainable consumption Sustainable production Collaboration Inter-organizational fit Resource complementarity Sustainable operations

SCI ; EI ; SSCI

英语

通讯

Science and Technology Innovation Committee Foundation of Shenzhen[JCYJ20170817112037041]

Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology

Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences

WOS:000444364400129

ELSEVIER SCI LTD

20182605360100

Industrial research ; Planning ; Predictive analytics ; Supply chains ; Sustainable development

Data Processing and Image Processing:723.2 ; Industrial Engineering and Management:912 ; Production Planning and Control; Manufacturing:913

Web of Science

1.Montpellier Business Sch, Montpellier Res Management, 2300 Ave Moulins, F-34185 Montpellier, France
2.Calif State Univ Bakersfield, Sch Business & Publ Adm, 9001 Stockdale Highway, Bakersfield, CA 93311 USA
3.Plymouth Univ, Plymouth Business Sch, Plymouth PL4 8AA, Devon, England
4.Southern Univ Sci & Technol China, Comp Sci & Engn Dept, 1088 Xueyuan Blvd, Shenzhen 518055, Guangdong, Peoples R China
5.Toulouse Univ, Toulouse Business Sch, 20 Blvd Lascrosses, F-31068 Toulouse, France

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.

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.

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.