Identifying Essential Driving Factors of Industry 4.0 Maturity Models Using Fuzzy MCDM Methods

Abstract

Industry 4.0 is still the 'next big thing' for many companies, and they are currently trying to adopt Industry 4.0 in their strategy. While Industry 4.0 continues to evolve, understanding of its driving factors remains crucial for industrial development and economic growth for competitive advantage. Those driving factors are revealed not only by exploiting advanced technology such as automation, robotization, Internet of Things, AI, smart system, or big data analytics but also the human factors, including culture or willingness to change. This paper aims to analyze the essential driving factors for Industry 4.0 maturity models. All factors are identified from a structured literature review. Then, the weights expressing the importance of the factors are calculated by obtaining expert opinions. This study utilizes a linguistic fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and using Decision Making Trial and Evaluation Laboratory (DEMATEL) method for weighting and ranking the driving factors and mapping the relationship between them. The analyzed driving factors identified from 52 references containing maturity models for Industry 4.0 are categorized into six domains and 16 subdomains. The presented study findings in this paper can support academicians and practitioners in comparing, developing, and improving Industry 4.0 maturity models as part of their adoption strategy and development.