Toward a comprehensive understanding of the drivers of digital transformation implementation in the apparel industry: An extended TOE framework

Document Type : Original Article

Authors

1 Department of Management, Faculty of Management and Accounting, College of Farabi, University of Tehran, Tehran, Iran E-mail: ostovari_1385@ut.ac.ir

2 Department of Business, Faculty of Management and Accounting, Hazrat-e Masoumeh University, Qom, Iran E-mail: m.jami@hmu.ac.ir

3 Department of Management, Faculty of Management and Accounting, College of Farabi, University of Tehran, Tehran, Iran Corresponding Author E-mail: sm.jafari@ut.ac.ir

Abstract
In recent years, digital technologies have transformed people’s lifestyles and the way businesses operate. These changes have become increasingly evident in various industries, including the apparel industry, especially after the emergence of the Fourth Industrial Revolution. The apparel industry, which has traditionally relied on physical supply chains, traditional design, and face-to-face sales, is now being influenced by drivers of digital transformation such as emerging technologies, organizational restructuring, data analytics, artificial intelligence, digital platforms, and smart design and manufacturing technologies. In such circumstances, companies operating in this industry are forced to redesign their business models, processes, and structures in accordance with the requirements of the digital age in order to remain competitive. Accordingly, digital transformation has become an inevitable necessity for apparel industry players. One of the most important steps in this direction is to extract and integrate the drivers of digital transformation implementation and present them in a five-dimensional framework including strategic, organizational, environmental, operational, and competitive drivers. Using the meta-synthesis method, this study organized the scattered literature on digital transformation into a coherent framework with 139 codes, 25 concepts, and 5 categories, and by calculating the presence of each code in the selected studies, it determined the level of support between studies and the relative consensus of the literature on the drivers. Operational drivers with technology and infrastructure concepts, organizational drivers with diverse concepts at the organization level, and competitive drivers with customer, market, and sales channels concepts had the most scientific support.

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