Enhancing supply chain performance using RFID technology and decision support systems in the industry 4.0: a systematic literature review

Unhelkar, Bhuvan, Joshi, Sudhanshu, Sharma, Manu, Prakash, Shiv, Mani, Ashwin Krishna and Prasad, Mukesh (2022) Enhancing supply chain performance using RFID technology and decision support systems in the industry 4.0: a systematic literature review. International Journal of Information Management Data Insights, 2 (2). pp. 1-12. ISSN 2667-0968

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Abstract / Description

Supply Chain processes are continuously marred by myriad factors including varying demands, changing routes, major disruptions, and compliance issues. Therefore, supply chains require monitoring and ongoing optimization. Data science uses real-time data to provide analytical insights, leading to automation and improved decision making. RFID is an ideal technology to source big data, particularly in supply chains, because RFID tags are consumed across supply chain process, which includes scanning raw materials, completing products, transporting goods, and storing products, with accuracy and speed. This study carries out a systematic literature review of research articles published during the timeline (2000-2021) that discuss the role of RFID technology in developing decision support systems that optimize supply chains in light of Industry 4.0. Furthermore, the study offers recommendations on operational efficiency of supply chains while reducing the costs of implementing the RFID technology. The core contribution of this paper is its analysis and evaluation of various RFID implementation methods in supply chains with the aim of saving time effectively and achieving cost efficiencies.

Item Type:	Article
Uncontrolled Keywords:	RFID technology; Industry 4.0; supply chain performance; decision support system; information management
Subjects:	600 Technology > 650 Management & auxiliary services
Department:	Guildhall School of Business and Law
SWORD Depositor:	Pub Router
Depositing User:	Pub Router
Date Deposited:	24 Jun 2022 14:38
Last Modified:	24 Jun 2022 14:38
URI:	https://repository.londonmet.ac.uk/id/eprint/7706

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