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Unpacking Digital Transformation: Identifying key enablers, transition stages and digital archetypes

journal contribution
posted on 2024-05-29, 15:28 authored by Fatima Gillani, Kamran ChathaKamran Chatha, Shakeel Sadiq Jajja, Dongmei Cao, Xiao Ma
This study aims to identify recurring Digital Transformation (DT) archetypes within firms and explore the capabilities and values associated with each archetype. Underpinned by the Resource-Based View (RBV) and Socio-Technical Systems (STS) theory, the study provides a framework explicating the enabling factors, their characteristics, interdependencies, operational capabilities, and resultant value creation within the context of digitalizing firm operations. Employing a deductive-inductive approach, an exhaustive literature review combined with an in-depth, multiple case study analysis of sixteen firms provides rich insights into the digital transformation journey. Findings reveal technology, data, human capital, processes, and organization structure as key enablers alongside their critical, complementary roles for transformation. Cross-case analysis identified instances of the DT framework, uncovering three archetypes: process efficiency, responsiveness, and strategic agility. Each archetype exhibits distinct socio-technical enabler configurations and improvements to business processes, resulting in unique operational capabilities and value generation. This research provides actionable guidance for managers in leveraging socio-technical enablers to achieve successful digital transformation. It underscores the need for tailored strategies, recognizing that a one-size-fits-all approach is inadequate. Managers must strategically select desired values and develop the necessary socio-technical system components, processes, and operational capabilities to attain them. Originality: This study develops digital archetypes of firm operations linking sociotechnical components, operational capabilities, and goals of firm operations. To the best of our knowledge, no prior research has developed such digital archetypes.

History

School

  • Loughborough Business School

Published in

Technological Forecasting and Social Change

Volume

203

Issue

2024

Publisher

Elsevier

Version

  • AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in Technological Forecasting and Social Change published by Elsevier. The final publication is available at https://doi.org/10.1016/j.techfore.2024.123335. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

2024-03-14

Publication date

2024-03-26

Copyright date

2024

ISSN

0040-1625

eISSN

1873-5509

Language

  • en

Depositor

Dr Kamran Chatha. Deposit date: 27 May 2024

Article number

123335