Digitalization of supply chains in Industry 4.0 environment of manufacturing organizations: conceptualization, scale development & validation

Ruchi Mishra, Rajesh Kr Singh, Angappa Gunasekaran

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Digitalization of the supply chain represents using several advanced digital technologies to support and synchronize organizational interactions by making services more valuable, accessible, and affordable for customer satisfaction. Given the growing significance of supply chain digitalization, developing a valid and reliable instrument to assess the level of digitalization of supply chain practices is imperative. However, no systematic and scientific study has been carried out to develop such an instrument. This study aims to conceptualize, develop, and validate a multifaceted scale for assessing the digitalization practices in the supply chain. Data for the study are collected from 246 organizations, and measurement scales are evaluated and validated using structural equation modelling. Using competing model strategy, five alternate competing models are developed and tested to identify the best fitting parsimonious model. Following the well-established procedure of instrument development, the study confirms the existence of four dimensions of digitalization practices, namely sourcing digitalization, operations digitalization, distribution network digitalization and digitalized strategic planning with adequate levels of reliability, convergent validity, discriminant validity and nomological validity. The study theoretically conceptualizes and operationalizes digitalization associated with Industry 4.0 as a multi-dimensional construct tapping its four key dimensions. The findings contribute to the existing literature by offering an understanding of the multi-dimensional scale of digitalization practices, which will be highly valuable for future research on the digitalization of the supply chain in the industry 4.0 environment.

Original languageEnglish (US)
Pages (from-to)1278-1297
Number of pages20
JournalProduction Planning and Control
Volume35
Issue number11
DOIs
StatePublished - 2024

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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