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Article
Publication date: 19 December 2023

Santosh B. Rane, Gayatri J. Abhyankar, Milind Shrikant Kirkire and Rajeev Agrawal

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL…

Abstract

Purpose

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

Design/methodology/approach

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

Findings

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

Research limitations/implications

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

Practical implications

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

Originality/value

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 3 February 2020

Milind Shrikant Kirkire, Santosh B. Rane and Gayatri Jayant Abhyankar

The purpose of this paper model and prioritizes barriers to product development in medical device manufacturing industries using an integrated “structural equation modelling”…

Abstract

Purpose

The purpose of this paper model and prioritizes barriers to product development in medical device manufacturing industries using an integrated “structural equation modelling” (SEM) and “fuzzy technique for order performance by similarity to ideal solution” (FTOPSIS) framework.

Design/methodology/approach

Barriers to medical device development (MDD) are adopted from literature. The initial structural model is proposed, exploratory factor analysis and confirmatory factor analysis are used to determine factor loading and model fit, respectively. Further, FTOPSIS is used to rank the barriers and sensitivity analysis is carried to check the robustness of results. The results are discussed in detail and the recommendations to overcome the barriers are presented.

Findings

Barriers analysed and prioritized in this research significantly hinder the MDD. The expert survey is used to develop an initial structural equation model of barriers to MDD, find the reliability and validity of the model. Based on the opinion of the experts, the barriers are divided into three categories – internal, policy and induced barriers. FTOPSIS is applied to rank and prioritize the barriers based on views from these three classes of experts. More reliance on imported devices leading to increased imports (B11) and lack of uniform regulatory standards (B6) are found to have the highest rank together, indicating these to be the most important barriers from the perspective considered here. Sensitivity analysis indicates that the factors are less sensitive to the weights of criteria further confirming the reliability of the initial solution.

Research limitations/implications

The prioritization of barriers may vary based upon experts. Policymakers, existing and new device developers need to give utmost importance to these barriers, which will help to accelerate the indigenous development of medical devices to overcome the present dependence on imports.

Practical implications

This paper demonstrates an integrated structural based modelling and prioritization technique for statistical modelling and prioritization of barriers to MDD. The results and recommendations will help policymakers and manufacturers to increase the indigenous share of medical devices. The integrated methodology can be effectively applied where the need for the combined quantitative and qualitative approach is there.

Originality/value

This paper demonstrates an effective structural based modelling and prioritization technique. It can be effectively applied in various fields, it will help policymakers and manufacturers to increase the indigenous share of medical devices.

Details

Journal of Modelling in Management, vol. 15 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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