Digital Transformation Framework: A Bibliometric Approach

Reihaneh Hajishirzi, Carlos J. Costa, Manuela Aparicio, Mario Romão

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In the age of the digital economy, digital transformation (DT) is a very important topic and is studied in many research articles. Therefore, in this paper we examine the literature to find out which topics have been studied to date concerning DT. Our aim is to discover what the main dimensions are for the adoption and implementation of DT in organisations. The results of a comprehensive study based on a citation and co-citation analysis are presented in this paper. Additionally, resulting from a cluster analysis of the literature, we find that companies tend to focus on four distinct subjects when implementing and adopting DT, namely: organisation, technology, people, and external pressures for deploying solutions. To conclude, we derive a conceptual framework based on these main dimensions with the objective to provide a roadmap for organisations to accelerate their DT.
Original languageEnglish
Title of host publicationInformation Systems and Technologies
Subtitle of host publicationWorldCIST 2022
EditorsAlvaro Rocha, Hojjat Adeli, Gintautas Dzemyda, Fernando Moreira
PublisherSpringer Science and Business Media Deutschland GmbH
Chapter38
Pages427-437
Number of pages11
Volume3
ISBN (Electronic)978-3-031-04829-6
ISBN (Print)978-3-031-04828-9
DOIs
Publication statusPublished - 11 May 2022
Event10th World Conference on Information Systems and Technologies (WorldCist'22) - Budva, Montenegro
Duration: 12 Apr 202214 Apr 2022
Conference number: 10th

Publication series

NameLecture Notes in Networks and Systems
Volume470
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference10th World Conference on Information Systems and Technologies (WorldCist'22)
Abbreviated titleWorldCist'22
Country/TerritoryMontenegro
CityBudva
Period12/04/2214/04/22

Keywords

  • Digital transformation
  • Bibliometric analysis
  • Cluster analysis

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