Developing an industry 4.0 readiness model using fuzzy cognitive maps approach

Monshizadeh, F; Moghadam, MRS; Mansouri, T; Kumar, M

Abstract

Industry 4.0, or the fourth industrial revolution, is a new paradigm in manufacturing digitalization, which provides various opportunities for enterprises. Industry 4.0 readiness models are worthy methods to aid manufacturing organizations in tracking the development of their businesses and operations. Nevertheless, there are different Industry 4.0 readiness models; no work has yet analyzed Industry 4.0 readiness degree and causal effects relationships using fuzzy cognitive maps. This paper proposes an Industry 4.0 readiness model that consists of readiness requirements obtained from the literature and validated through a mixed-method approach, including literature reviews and questionnaires. To validate the proposed Industry 4.0 readiness model, the exploratory factor analysis and confirmatory factor analysis methods are used. Fuzzy Cognitive Map is utilized to assess readiness, identify relevant concepts to improve readiness degree, implement Industry 4.0, and analyze causal relationships among concepts and dimensions. Through this model and the FCM method, managers can recognize relevant concepts and predict complicated cause-effect relationships among concepts in two states of static and dynamic analyses to increase readiness degree. The paper concludes by emphasizing managerial implications for successful applications in practice as well as future research suggestions on developing the Industry 4.0 readiness model.

Citation

Monshizadeh, F., Moghadam, M., Mansouri, T., & Kumar, M. (2022). Developing an industry 4.0 readiness model using fuzzy cognitive maps approach. International Journal of Production Economics, 255, https://doi.org/10.1016/j.ijpe.2022.108658

• Journal Article Type: Article
• Acceptance Date: Sep 27, 2022
• Online Publication Date: Oct 7, 2022
• Publication Date: Oct 7, 2022
• Deposit Date: Oct 26, 2022
• Publicly Available Date: Oct 8, 2025
• Journal: International Journal of Production Economics
• Print ISSN: 0925-5273
• Electronic ISSN: 1873-7579
• Publisher: Elsevier
• Volume: 255
• DOI: https://doi.org/10.1016/j.ijpe.2022.108658
• Publisher URL: http://doi.org/10.1016/j.ijpe.2022.108658