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Digital transformation of industrial businesses: a dynamic capability approach

journal contribution
posted on 06.12.2021, 11:56 by Swapan Ghosh, Mathew HughesMathew Hughes, Ian HodgkinsonIan Hodgkinson, Paul Hughes
Industrial firms are under severe pressure to undertake digital transformation and leverage the Industrial Internet of Things (IIoT) and emerging technologies for the integration of industrial machines to share information on a real-time or near real-time basis. Though in recent years researchers have focused their attention on digital transformation, there is limited scholarly guidance for developing capabilities for such transformation. Drawing on dynamic capability theory and exploratory qualitative interviews with senior ‘elite’ executives from five of the world’s largest multinational firms, the study outlines a new conceptual framework for digital transformative capability development. The integrative framework demonstrates how the three core capabilities of digital sensing, digital seizing, and digital reconfiguring manifest through associated capabilities of Strategic Sensing, Rapid Prototyping, Organization Structure, Business Model Transformation, and Cultural/Mindset Transformation. Internal and external contingencies are proposed as moderators of the relationship between IIoT and emerging technologies, and digital transformative capability development. Collectively, the article makes the case for Digital Transformation Capability and sheds new light on the digital transformation process. Implications for theory and practice are highlighted, and limitations are discussed.

History

School

  • Business and Economics

Department

  • Business

Published in

Technovation

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Technovation and the definitive published version is available at https://doi.org/10.1016/j.technovation.2021.102414.

Acceptance date

03/11/2021

Publication date

2021-11-10

Copyright date

2021

ISSN

0166-4972

Language

en

Depositor

Prof Ian Hodgkinson. Deposit date: 4 November 2021

Article number

102414