Prioritization of policy initiatives to overcome Industry 4.0 transformation barriers based on a Pythagorean fuzzy multi-criteria decision making approach. Issue 1 (1st January 2021)

• Record Type: Journal Article
• Authors: Sumrit, Detcharat
• Editors: Lou, Ping
• Is Part Of: Cogent engineering. Volume 8:Issue 1(2021)
• Publication Date: 2021-01-01
• Subjects: Industry 4.0 -- barriers to industry 4.0 -- multi-criteria decision making -- Pythagorean fuzzy set -- TODIM; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2021.1979712
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: Industry 4.0 (hereafter I4.0) transformation in manufacturing sectors is considerably gaining a lot of attention from both researchers and practitioners. To increase the success rate of I4.0 transformation, manufacturers and policymakers need to understand barriers and how to overcome them. This paper proposes an analytical framework to prioritize the policy initiatives to overcome I4.0 transformation barriers, which have so far been ignored in previous studies. Since the prioritization of policy initiatives involves many evaluating criteria, multi-criteria decision-making (MCDM) is an effective method to evaluate and rank the best alternatives. Notwithstanding, the uncertainty is a major issue in any decision-making process. One of the latest emerging tools in dealing with the uncertainties is Pythagorean fuzzy set (PFS). The use of PFS allows experts with a larger domain to determine both membership and non-membership degrees. In this study, TODIM (an acronym in Portuguese for Interactive Multi-Criteria Decision-Making) under PFS is employed to prioritize policy initiatives to overcome I4.0 barriers. The proposed framework presented herein is illustrated by the case of Thai food processing industry. The results of this study can help the policymakers aiming to drive I.40 transformation to implement the policy initiative in a prioritize manner. Although the present work is focused on the food processing industry, the proposed framework can be further applied to other similar industries.