Transformational Entrepreneurship and Digital Platforms: A Combination of ISM-MICMAC and Unsupervised Machine Learning Algorithms

Pejman Ebrahimi, Hakimeh Dustmohammadloo, Hosna Kabiri, Parisa Bouzari, Mária Fekete-Farkas

For many years, entrepreneurs were considered the change agents of their societies. They use their initiative and innovative minds to solve problems and create value. In the aftermath of the digital transformation era, a new group of entrepreneurs have emerged who are called transformational entrepreneurs. They use various digital platforms to create value. Surprisingly, despite their importance, they have not been sufficiently investigated. Therefore, this research scrutinizes the elements affecting transformational entrepreneurship in digital platforms. To do so, the authors have considered a two-phase method. First, interpretive structural modeling (ISM) and Matrices d’Impacts Croises Multiplication Appliqué a Un Classement (MICMAC) are used to suggest a model. ISM is a qualitative method to reach a visualized hierarchical structure. Then, four unsupervised machine learning algorithms are used to ensure the accuracy of the proposed model. The findings reveal that transformational leadership could mediate the relationship between the entrepreneurial mindset and thinking and digital transformation, interdisciplinary approaches, value creation logic, and technology diffusion. The GMM in the full type, however, has the best accuracy among the various covariance types, with an accuracy of 0.895. From the practical point of view, this paper provides important insights for practitioners, entrepreneurs, and public actors to help them develop transformational entrepreneurship skills. The results could also serve as a guideline for companies regarding how to manage the consequences of a crisis such as a pandemic. The findings also provide significant insight for higher education policymakers.