Journal of Industrial Engineering and Management Studies

Abstract With the occurrence of the Fourth Industrial Revolution worldwide, industries are facing transformation, and Iranian industries will inevitably be part of this transformation. Although some industries, such as transportation and logistics, have embraced these changes, other industries, such as insurance, have struggled to leverage the benefits of these transformations and have lagged behind. The question arises: why have some industries undergone fundamental changes under similar general condi-tions, while others have not? This research aims to provide a roadmap for fundamental changes in domestic industries by com-paring a successful industry with an unsuccessful one. Based on this, four scenarios—digital transformation, digital evolution, startup creation, and change planning—were derived from in-depth expert interviews in startup companies within these indus-tries. Through thematic analysis, a strategic framework has been proposed to determine the roadmap for industry transformation. Companies operating in various industries can utilize this practical framework to design and implement their industry trans-formation roadmap.

Abstract Maturity models mostly assess phenomena in each industry or organization and investigate the readiness to accept those phenomenon and paradigms. The Fourth Industrial Revolution has emerged and revealed as a new phenomenon in various industries, whose maturity model has garnered the attention of numerous experts and specialists. Considering that there is no such a model in the banking service supply chain, the present study sought to design a conceptual model for the maturity of Industry 4.0 with a focus on financial technologies and digital transformation. Thus, by conducting interviews with experts, including bank managers, and university professors, basic themes were extracted using a thematic analysis approach, based on which the final model was then designed, including seven organizing themes of managerial factors, infrastructure factors, information technology factors, human resource factors, cultural factors, economic factors, and business factors. The final model, which included seven sub-models, was validated using factor loading analysis, as a result, the findings of which showed that all sub-models were significant at a 95% confidence level; therefore, the designed model was valid enough in the qualitative section.