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Enablers to supply chain performance on the basis of digitization technologies

Enablers to supply chain performance on the basis of digitization technologies
Enablers to supply chain performance on the basis of digitization technologies

Purpose: The aim of this study is to identify and prioritize a list of key digitization enablers that can improve supply chain management (SCM). SCM is an important driver for organization's competitive advantage. The fierce competition in the market has forced companies to look the past conventional decision-making process, which is based on intuition and previous experience. The swift evolution of information technologies (ITs) and digitization tools has changed the scenario for many industries, including those involved in SCM. Design/methodology/approach: The Best Worst Method (BWM) has been applied to evaluate, rank and prioritize the key digitization and IT enablers beneficial for the improvement of SC performance. The study also used additive value function to rank the organizations on their SC performance with respect to digitization enablers. Findings: The total of 25 key enablers have been identified and ranked. The results revealed that “big data/data science skills”, “tracking and localization of products” and “appropriate and feasibility study for aiding the selection and adoption of big data technologies and techniques ” are the top three digitization and IT enablers that organizations need to focus much in order to improve their SC performance. The study also ranked the SC performance of the organizations based on digitization enablers. Practical implications: The findings of this study will help the organizations to focus on certain digitization technologies in order to improve their SC performance. This study also provides an original framework for organizations to rank the key digitization enablers according to enablers relevant in their context and also to compare their performance with their counterparts. Originality/value: This study seems to be the first of its kind in which 25 digitization enablers categorized in four main categories are ranked using a multi-criteria decision-making (MCDM) tool. This study is also first of its kind in ranking the organizations in their SC performance based on weights/ranks of digitization enablers.

Best Worst Method, Big data analysis, Blockchain technology, Digitization tools, Industry 4.0, Internet of things, Supply chain management
0263-5577
1915-1938
Gupta, Himanshu
5fba70c4-3015-497e-849b-312dcaaa04d5
Kumar, Sarangdhar
34540064-31b4-4996-8b9d-e1c965678b04
Kusi-Sarpong, Simonov
a7e68240-2b34-456e-9849-c01bd10c68f7
Chiappetta Jabbour, Charbel Jose
9a8e99a7-43a3-415d-9f27-acebafc5df8c
Agyemang, Martin
3acf48d4-ea36-426a-9fd7-028fc18d9f47
Gupta, Himanshu
5fba70c4-3015-497e-849b-312dcaaa04d5
Kumar, Sarangdhar
34540064-31b4-4996-8b9d-e1c965678b04
Kusi-Sarpong, Simonov
a7e68240-2b34-456e-9849-c01bd10c68f7
Chiappetta Jabbour, Charbel Jose
9a8e99a7-43a3-415d-9f27-acebafc5df8c
Agyemang, Martin
3acf48d4-ea36-426a-9fd7-028fc18d9f47

Gupta, Himanshu, Kumar, Sarangdhar, Kusi-Sarpong, Simonov, Chiappetta Jabbour, Charbel Jose and Agyemang, Martin (2021) Enablers to supply chain performance on the basis of digitization technologies. Industrial Management and Data Systems, 121 (9), 1915-1938. (doi:10.1108/IMDS-07-2020-0421).

Record type: Article

Abstract

Purpose: The aim of this study is to identify and prioritize a list of key digitization enablers that can improve supply chain management (SCM). SCM is an important driver for organization's competitive advantage. The fierce competition in the market has forced companies to look the past conventional decision-making process, which is based on intuition and previous experience. The swift evolution of information technologies (ITs) and digitization tools has changed the scenario for many industries, including those involved in SCM. Design/methodology/approach: The Best Worst Method (BWM) has been applied to evaluate, rank and prioritize the key digitization and IT enablers beneficial for the improvement of SC performance. The study also used additive value function to rank the organizations on their SC performance with respect to digitization enablers. Findings: The total of 25 key enablers have been identified and ranked. The results revealed that “big data/data science skills”, “tracking and localization of products” and “appropriate and feasibility study for aiding the selection and adoption of big data technologies and techniques ” are the top three digitization and IT enablers that organizations need to focus much in order to improve their SC performance. The study also ranked the SC performance of the organizations based on digitization enablers. Practical implications: The findings of this study will help the organizations to focus on certain digitization technologies in order to improve their SC performance. This study also provides an original framework for organizations to rank the key digitization enablers according to enablers relevant in their context and also to compare their performance with their counterparts. Originality/value: This study seems to be the first of its kind in which 25 digitization enablers categorized in four main categories are ranked using a multi-criteria decision-making (MCDM) tool. This study is also first of its kind in ranking the organizations in their SC performance based on weights/ranks of digitization enablers.

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More information

Accepted/In Press date: 15 October 2020
e-pub ahead of print date: 23 September 2021
Published date: 23 September 2021
Keywords: Best Worst Method, Big data analysis, Blockchain technology, Digitization tools, Industry 4.0, Internet of things, Supply chain management

Identifiers

Local EPrints ID: 444620
URI: http://eprints.soton.ac.uk/id/eprint/444620
ISSN: 0263-5577
PURE UUID: 9de17c99-089b-432c-a117-77e52ff9de59
ORCID for Simonov Kusi-Sarpong: ORCID iD orcid.org/0000-0003-1618-2518

Catalogue record

Date deposited: 27 Oct 2020 19:56
Last modified: 27 Apr 2022 04:41

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Contributors

Author: Himanshu Gupta
Author: Sarangdhar Kumar
Author: Charbel Jose Chiappetta Jabbour
Author: Martin Agyemang

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