Document Type : Original Article


1 Ph.D Candidate in Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran.

2 Associate Professor, Faculty of Management and Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran.

3 Assistant Professor, Faculty of Management and Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran.


Fourth industrial revolution is rapidly changing technology, industry and patterns through increased communications and intelligent automation in the current century. It is crucial to conduct thorough research to determine the importance of dimensions and indicators in assessing the preparedness of Iran's industries for sustainability in Industry 4.0. The goal of this paper is to identify and determine the importance of the influential components on the organization's readiness to move towards the fourth-generation industry. This model should help the organizations and industries understand their industry 4.0 readiness status. In qualitative part of the study, we categorized the data to produce the initial codes, themes and axial codes by examining the theoretical foundations and receiving experts' comments. The result was extracting 60 initial codes and 6 themes. We then used the fuzzy Delphi method on the result of the poll. Experts unanimously voted in favor of 17 sub-criteria. Finally, we used fuzzy DEMATEL method to study the relationships between criteria and sub-criteria. According to this study, ‘functional readiness’ was the most effectible and ‘information technology readiness’ was the most affecting criteria. Among sub-criteria, ‘governmental and institutional laws’ and ‘workplace dynamics’ were identified as the most effectible cause and most affecting effect respectively.


Main Subjects

  1. Abdullah, L.; & Zulkifli, N. (2015). Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management. Expert Systems with Applications, 42(9), 4397-4409.
  2. Akyuz, E.; & Celik, E. (2015). A fuzzy DEMATEL method to evaluate critical operational hazards during gas freeing process in crude oil tankers. Journal of Loss Prevention in the Process Industries, 38, 243-253.
  3. Aslani Liaei, V.; Abedi, S.; Irajpour, A.; & Ehtesham Rathi, R. (2021). Presenting a model for evaluating the multiple capabilities of a sustainable supply chain based on artificial intelligence. The Journal of Industrial Management Perspective, 11(3), 107-129. (In Persian)
  4. Azizi, H.; & Hasanpour, B. (2019). Designing a model for risk in the green supply chain with fuzzy Delphi technique and fuzzy dimtel in Gachsaran Oil and Gas Exploitation Company (Vol. 3, p. 17). Presented at the The third international conference on dynamic management, accounting and auditing. (In Persian)
  5. Bahrin, M. A. K.; Othman, M. F.; Azli, N. H. N.; & Talib, M. F. (2016). Industry 4.0: A Review on Industrial Automation and Robotic, 78(6-13).
  6. Bauer, H.; Patel, M.; & Veira, J. (2014). The Internet of Things: Sizing up the opportunity (p. 7). McKinsey & Company.
  7. Carolis, A. D.; Macchi, M.; Negri, E.; & Terzi, S. (2017). A Maturity Model for Assessing the Digital Readiness of Manufacturing Companies. In Advances in Production Management Systems. The Path to Intelligent, Collaborative and Sustainable Manufacturing (pp. 13-20). Springer, Cham.
  8. Castelo Branco, I.; Cruz-Jesus, F.; & Oliveira, T. (2019). Assessing Industry 4.0 readiness in manufacturing: Evidence for the European Union. Computers in Industry, 107, 22-32.
  9. Danaeifar, H.; Alvani, S. M.; & Azar, A. (2014). Qualitative research methodology in management: comprehensive expertise. Tehran: Safar.
  10. Dapari, R.; Ismail, H.; Ismail, R.; & Ismail, N. H. (2017). Application of Fuzzy Delphi in the Selection of COPD Risk Factors among Steel Industry Workers. Tanaffos, 16(1), 46-52.
  11. Esfahani, A. N.; Sarand, V. F.; & Arian, A. (2015). Explain the Impact of Organizational Factors Affecting Food Safety Performance Using Fuzzy Dematel. International Journal of Management Sciences, 5(7), 531-543.
  12. Gilchrist, A. (2016). Industry 4.0 - The Industrial Internet of Things (Vol. 1). eBook, Apress.
  13. Hizam, M.; Soomro, M. A.; & Abdullah, N. L. (2020). Industry 4.0 Readiness Models: A Systematic Literature Review of Model Dimensions. Information, 11(7), 364.
  14. Hooshmandi Maher, M.; Amiri, M.; & Olfat, L. (2013). An integrated model of choice in information review: Information technology capabilities. The Journal of Industrial management perspective, 2(4), 91-115. (In Persian)
  15. Jamwal, A.; Agrawal, R.; Sharma, M.; & Giallanza, A. (2021). Industry 4.0 Technologies for Manufacturing Sustainability: A Systematic Review and Future Research Directions. Applied Sciences, 11(12), 5725.
  16. Jassbi, A.; Jassbi, J.; Akhavan, P.; Chu, M.; & Piri, M. (2015). An empirical investigation for alignment of communities of practice with organization using fuzzy Delphi panel. VINE, 45(3), 322-343. (In Persian)
  17. Lichtblau, K.; Goerick, D.; Stich, V. (2014(. Industry 4.0 Readiness Online Self-Check for Businesses.
  18. Kabak, O.; Ülengin, F.; Çekyay, B.; Önsel, S.; & Özaydın, O. (2016). Critical Success Factors for the Iron and Steel Industry in Turkey: A Fuzzy DEMATEL Approach. International Journal of Fuzzy Systems, 18(3), 523-536.
  19. Kiani Mavi, R.; & Standing, C. (2018). Critical success factors of sustainable project management in construction: A fuzzy DEMATEL-ANP approach. Journal of Cleaner Production, 194, 751-765.
  20. Kuo, Y.; & Chen, P. (2008). Constructing performance appraisal indicators for mobility of the service industries using Fuzzy Delphi Method. Expert Systems with Applications, 35(4), 1930-1939.
  21. Li, Y.; Hu, Y.; Zhang, X.; Deng, Y.; & Mahadevan, S. (2014). An evidential DEMATEL method to identify critical success factors in emergency management. Applied Soft Computing, 22, 504-510.
  22. Lin, Ch.; & Wu, W. (2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, 34(1), 205-213.
  23. Liu, W. (2013). Application of the Fuzzy Delphi Method and the Fuzzy Analytic Hierarchy Process for the Managerial Competence of Multinational Corporation Executives. International Journal of e-Education, e-Business, e-Management and e-Learning, 3(4), 313-317.
  24. Ma, Zh.; Shao, Ch.; Ma, Sh.; & Ye, Z. (2011). Constructing road safety performance indicators using Fuzzy Delphi Method and Grey Delphi Method. Expert Systems with Applications, 38(3), 1509-1514.
  25. Machado, C. G.; Winroth, M. P.; & Silva, E. H. D. (2020). Sustainable manufacturing in Industry 4.0: an emerging research agenda. International Journal of Production Research, 58(5), 1462-1484.
  26. Magruk, A. (2016). Uncertainty in the sphere of the Industry 4.0 – potential areas to research. Business. Management and Education, 14(2), 275-291.
  27. Mohammadfam, I.; Mirzaei Aliabadi, M.; Soltanian, A. R.; Tabibzadeh, M.; & Mahdinia, M. (2019). Investigating interactions among vital variables affecting situation awareness based on Fuzzy DEMATEL method. International Journal of Industrial Ergonomics, 74, 102842.
  28. Mohammadi, A.; Barahmand, F.; & Shojaei, P. (2019). Providing a framework for evaluating electronic readiness and action for electronic business in Ramek Dairy Company of Shiraz. Information Technology Management, 8(4), 811-832.
  29. Mojibi, T.; MahdiZadeh, A.; & mifar, M. (2012). Evaluation of the level of readiness to implement the comprehensive quality management system (TQM) in the active production cooperatives of the industry sector of Mazandaran province. Journal of Industrial Strategic Management, 9(26), 69-85.
  30. Monshizadeh, F.; Sadeghi Moghadam, M. R.; Mansouri, T.; & Kumar, M. (2023). Developing an industry 4.0 readiness model using fuzzy cognitive maps approach. International Journal of Production Economics, 255, 108658.
  31. Saremi, M.; Mousakhani, M.; & Abedini, M. (2008). Extraction and evaluation of indicators related to the readiness of the automotive industry for ERP implementation. Management knowledge, 77(20), 47-60.
  32. Shabani, S.; & Safaei, A. (2018). Analysis and measurement of factors affecting project risks to optimize the production system of Kale Amel company with the combined approach of fuzzy Delphi and Fuzzy Dimetal. (Vol. 1, p. 8). Presented at the The first international conference on systems optimization and business management.
  33. Schumacher, A.; Erol, S.; & Sihn, W. (2016). A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises. Procedia CIRP, 52, 161-166.
  34. Stock, T.; & Seliger, G. (2016). Opportunities of Sustainable Manufacturing in Industry 4.0. Procedia CIRP, 40, 536-541.
  35. Talebi, Davoud.; & Arashpour, A. (2013). Evaluating educational performance with a comparative approach of network analysis and Dimatel. The Journal of Industrial Management Perspective, 3(2), 85-100. (In Persian)
  36. Wu, W.; & Lee, Y. (2007). Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Systems with Applications, 32(2), 499-507
  37. Zhou, Q.; Huang, W.; & Zhang, Y. (2011). Identifying critical success factors in emergency management using a fuzzy DEMATEL method. Safety Science, 49(2), 243-252.
  38. Zutin, G. C.; Barbosa, G. F.; de Barros, P. C.; Tiburtino, E. B.; Kawano, F. L. F.; & Shiki, S. B. (2022). Readiness levels of Industry 4.0 technologies applied to aircraft manufacturing—a review, challenges and trends. The International Journal of Advanced Manufacturing Technology, 120(1), 927-943.