Document Type : Original Article
Authors
1
Ph.D. student, Department of Industrial Management, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran.
2
Associate Professor, Department of Industrial Management, Faculty of Economics, Management and Accounting, Yazd University, Yazd, Iran.
Abstract
Introduction and objectives: Industry 4.0 has brought significant changes to industries and businesses. This transformation, involving the interconnection of devices, processes, and systems through smart networks and the use of data-driven technologies and artificial intelligence, has created a comprehensive approach in businesses. This development is crucial and has substantial impacts on various areas, including production, services, supply chain, and marketing. Given the increasing stability and future competitiveness of the production sector, the new technologies of the fourth industrial revolution (Industry 4.0) have gained considerable attention from the academic and industrial communities in recent years. However, manufacturers face numerous factors in implementing Industry 4.0, which need to be identified and analyzed. The purpose of this research is to identify the organizational factors influencing the adoption of Industry 4.0 and to present a fuzzy cognitive model.
Methods: This research is considered applied-developmental in terms of its purpose and hybrid (exploratory mixed) in terms of the research type. The statistical population of this research comprised small and medium-sized manufacturing companies, with 12 experts from small and medium-sized manufacturing companies active in the industrial town of Yazd province selected purposefully. Initially, to identify the organizational determinants of Industry 4.0, the meta-combination method was used, and then the relationships of these factors were determined using the fuzzy cognitive mapping method and the Fcmappear and Mental Modeler software.
Findings: The findings of the meta-combination method indicate 36 primary codes and 11 determining factors affecting the acceptance of Industry 4.0 technologies in small and medium-sized manufacturing companies operating in Yazd Industrial Town. These factors include absorption capacity, commercial assets, technical competence in digitization, digitalization knowledge and expertise, participation in the implementation process, strategic management competence for Industry 4.0, organizational culture, organizational structure, availability of resources, social capital, and top management characteristics. Among these factors, participation in the implementation process, absorption capacity, and social capital have the highest influencing capacity, while top management characteristics, digitalization knowledge and expertise, technical competence in digitization, and strategic management competence have the highest impact. Ultimately, the factors of technical competence in digitization, digitalization knowledge and expertise, top management characteristics, and participation in the implementation process obtained the most central indicators.
Conclusion: Industry 4.0 is a vital strategic option for small and medium-sized manufacturing companies, enabling them to keep pace with the digitization race. Small and medium-sized manufacturing companies are significantly behind large organizations in leveraging Industry 4.0 technologies. Additionally, these companies are still grappling with early adoption decisions regarding digital transformation under Industry 4.0, which is a concerning issue. The results identified various organizational determinants that may explain these conditions and provide efficient solutions for small and medium manufacturing companies. This study created an organizational digitalization roadmap that describes the necessary conditions to facilitate the digitalization of small and medium-sized manufacturing companies under Industry 4.0.
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