Analyzing the interaction of key factors of Sustainable Business Model Innovation in the Digital Age Based on Dynamic Capabilities Using An integrative meta-synthesis and interpretive structural modeling (ISM) approach(مقاله علمی وزارت علوم)
حوزه های تخصصی:
Due to the rapid changes and developments caused by technology in the digital age and the growing importance of achieving sustainability for the survival of businesses, the need to create the capabilities needed to innovate in the business model of organizations has become inevitable. This research is trying to provide a model for business model innovation with the aim of sustainability by considering the external factor of digitalization (digital transformation) and the internal factor of dynamic capabilities. The method of this research is mixed so that in the first stage the qualitative method of Meta-Synthesis is used and in the second stage the quantitative method of Interpretive Structural Modeling (ISM) is used. In this research, based on the systematic review of previous researches in scientific databases, 402 related articles were identified and then 46 final articles were selected during the screening process. Based on the thematic analysis, a total of 4 main categories and 14 factors were extracted. In the second stage of the research, an interpretive structural model (ISM) is developed to show the inter‐relationship of different factors and their levels of importance in the food industry. The 8-level hierarchy model of factors influencing the sustainable business model innovation in the digital age with a dynamic capabilities approach was proposed. Results show that a new component called network value has been added to the traditional business model components. Furthermore, the MICMAC approach has been used to categorise factors according to their driving power and dependence. finally, digital technologies and Sensing were found to be the factors with the highest independence and the highest driving power, and “Economic Sustainability” was identified as the factor with the highest dependence and the least driving power