An Industry 4.0 readiness model for new technology exploitation

Abstract

PurposeConsidering the importance and the broad applications of the Fourth Industrial Revolution in various organizations and industries and enjoying the many benefits of this digital transformation framework, organizations need to measure their Industry 4.0 readiness as a starting point and take steps to achieve the strategic goals of Industry 4.0. This study aims to design a comprehensive and practical model that can determine Industry 4.0 readiness level, allowing organizations to implement and exploit technological constituents of this phenomenon.Design/methodology/approachA systematic literature review (SLR) methodology was used to evaluate and summarize a clear and comprehensive literature overview of Industry 4.0 readiness models and to certify the validity and transparency of the review process. After reviewing 71 articles and survey and then the consensus of Industry 4.0 experts, the 10 dimensions of the 4.0 Industry readiness model were finalized with their indicators having the most frequency in the published articles and models.FindingsThe application of the SLR to the development of the new Industry 4.0 readiness model which includes 10 dimensions and 37 indicators and can assess the Industry 4.0 readiness of firms and industries accurately and effectively.Research limitations/implicationsAn extensive review of the previous literature yielded the current Industry 4.0 readiness model. The comprehensiveness of this model leads to its wide application in different companies. Future research suggestions are presented at the end of the manuscript.Practical implicationsThe concept of the Fourth Industrial Revolution and the application of its technologies are vague and complicated for many organizations and managers, while the need to implement the components and technologies of Industry 4.0 is essential to achieve organizational goals. The presented readiness model helps companies to measure their readiness to enter the Fourth Industrial Revolution and achieve long-term goals.Originality/valueIn this study, an attempt was made to examine the Industry 4.0 readiness models thoroughly and extensively and identify their different approaches. Finally, a comprehensive and multi-dimensional readiness model is presented to assess the position of organizations in order to enter Industry 4.0.

MCDM model to rank the performance outcomes in the implementation of Industry 4.0

“…Implementing Industry 4.0 practices will need an innovative organizational culture that promotes risk-taking, embraces new working methods and promotes logical analysis in difficult business situations (Nafchi and Mohelsk a, 2020). The organization has to assess its readiness for Industry 4.0 as a starting point, develop a strategic plan for implementing Industry 4.0's components and technologies and reach the required degree of maturity (Ansari et al, 2023). Monshizadeh et al (2023) emphasize that a variety of factors, from non-technical perspectives (such as the degree of employee preparedness, the company culture), to technological viewpoints (such as adopting new technologies), would be helpful for assessing Industry 4.0 readiness in the organization.…”

“…Implementing Industry 4.0 practices will need an innovative organizational culture that promotes risk-taking, embraces new working methods and promotes logical analysis in difficult business situations (Nafchi and Mohelská, 2020). The organization has to assess its readiness for Industry 4.0 as a starting point, develop a strategic plan for implementing Industry 4.0's components and technologies and reach the required degree of maturity (Ansari et al ., 2023). Monshizadeh et al .…”

Prioritization of critical factors toward Industry 4.0 adoption in service industries: an emerging economy perspective

“…2.1.2.3 Smart services through customer data. Smart services are tailored to the customer via data and intelligent processing, opening up opportunities such as additional revenue, enhanced customer satisfaction, cost reduction, faster decision-making, proactive maintenance and high interconnectedness (Ansari and Barati, 2023;Kamble et al, 2018).…”