Document Type : Original Research Manuscripts


1 MA. Knowledge & Information Science- Information Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran

2 Full-Prof., Knowledge & Information Science- Knowledge Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran.

3 Assistant Prof., Knowledge & Information Science- Knowledge Management, Management and Economics faculty, Tarbiat Modares University, Tehran, Iran.


This paper aims to generate a genealogy of Digital Transformation employing visualization techniques of scientific documents which will contribute theoretically to the research field and practically to the business. To reach the genealogy, three relations including ancestors, fathers, and descendants were defined. The ancestors and fathers were respectively determined by Reference Publication Year Spectroscopy (RPYS) and Citation analysis. Identification of the descendants was done through the bibliographic coupling of the documents published in the last two years. Visualization of the ancestors, fathers, and descendants was respectively done via fathers’ reference co-citation analysis, citation analysis on documents, and clustering of the bibliographic couplings using VosViewer. The analysis of each cluster identifies the topics of each relation of the genealogy. The analysis of the ancestors showed that the ancestors have studied theoretical foundations in digital transformation to a great extent. according to the clusters obtained for the fathers, Business models, Strategy and Innovation, Industry 4.0, and Servitization were the dominant topics of this relation. The identified topical clusters of descendants contained Digital Transformation Nature, the Influence of Digitalization on Business, Industry 4.0 and Sustainability, Digital Twins, and other Technologies in Industry 4.0, Digital Transformation, and Medicine, and Digital Transformation, Smart City, and The Effect on Financial and Economic Services showing the focus of latest research in specific technologies and innovation. The generated genealogy can be used to anticipate future trends and measures to be taken by businesses to realize digital transformation. 


Main Subjects

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