Big Data analytics in supply chain management: some conceptual frameworks
by Kuldeep Lamba; Surya Prakash Singh
International Journal of Automation and Logistics (IJAL), Vol. 2, No. 4, 2016

Abstract: The plethora of processes involved in supply chain management (SCM) along with modern information technology laden infrastructure viz., RFID-enabled devices, internet of things, cloud computing, etc. have made it very convenient to collect hugely voluminous data which essentially possesses the 3V characteristics of Big Data, i.e., volume, velocity and variety. This Big Data has huge potential to unravel the hidden business insights that can help an organisation outperform its competitors. Due to the substantial benefits of Big Data in SCM, the field of Big Data and predictive analytics has been continuously growing from just an emerging area, not a long back to a full-fledged research area at present, drawing attention of practicing professionals from industry as well as academicians worldwide in equal measures. Many theoretical frameworks on Big Data for SCM have been proposed. However, the complexities associated with the 3V criterion of Big Data have generally not been addressed in these frameworks. The paper proposes three new Big Data frameworks in SCM domains viz., procurement, joint procurement, and facility layout problem.

Online publication date: Tue, 15-Nov-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Automation and Logistics (IJAL):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com