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Big Data and RFID in Supply Chain and Logistics Management: A Review of the Literature and Applications for Data Driven Research

Papadopoulos, Thanos and Gunasekaran, A. and Dubey, R. and Balta, M. (2016) Big Data and RFID in Supply Chain and Logistics Management: A Review of the Literature and Applications for Data Driven Research. In: Supply Chain Management in the Big Data Era. Business Science Reference, pp. 108-123. ISBN 978-1-5225-0956-1. (doi:10.4018/978-1-5225-0956-1.ch007) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:60926)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.4018/978-1-5225-0956-1.ch007

Abstract

Big Data refers to complex and unstructured data that is difficult to analyse and utilize with traditional applications and analyses. Big Data comes from a variety of sources, including tracking and sensor devices which are widely used in logistics and supply chain management, and relate to Radio Frequency Identification (RFID) technology. Thus, this chapter reviews the literature on RFID adoption in supply chain/logistics management from 1995-2015. We identify current trends in the literature, drawing on the three levels of decision making, that is, strategic, tactical, and operational. We suggest that more research needs to be conducted with regards to the intangible benefits of RFID, the use of RFID big data for achieving higher performance, and to shift the focus from the ‘what' and the impacts on performance to the ‘how' and the ways RFID is adopted and assimilated in organizations and supply chains. Finally, the managerial implications of our review as well as the limitations and future research directions are outlined.

Item Type: Book section
DOI/Identification number: 10.4018/978-1-5225-0956-1.ch007
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Maria Balta
Date Deposited: 15 Mar 2017 11:38 UTC
Last Modified: 05 Nov 2024 10:54 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/60926 (The current URI for this page, for reference purposes)

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