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The Effect of Digital Twins on Organizational Learning


Type

Thesis

Change log

Authors

Gomez Medina, Francisco 

Abstract

The development of Digital Twins (DT) remains high in the digital transformation agendas of organisations. However, a paucity of field research exploring how DT are implemented in practice means their organisational value is not yet well understood. DT are a digital representation of a physical asset that is dynamically updated with data from its physical twin throughout its lifecycle, and their usage introduces new organisational dynamics that current literature cannot fully explain.

This Thesis contributes to the understanding of DT value by exploring how the usage of DT affects a key source of competitive advantage: Organizational Learning (OL). More specifically, the following research questions are addressed:

  • How do Digital Twins affect Organizational Learning processes?
  • What factors influence and mediate the usage of Digital Twins and their effect on Organizational Learning processes?

The effect of DT on OL is investigated through an extensive, multiple case study of DT implementations in the heavy assets industry. The cases include one in-depth case study with an aircraft engine Original Equipment Manufacturer (OEM) and two supporting case studies from wind renewable OEMs.

Three interrelated DT variables that drive the effect of DT on OL are theorised: Individualisation, Synchronicity, and Organisational Orchestration. Their effects on OL, as well as the organisational outcomes arising from the enactment of each of the variables, are also theorised.

This Thesis also advances our understanding of how the development and implementation of highly complex IT in a B2B context affects OL. In particular, it identifies limitations to the widely accepted notion that IT has a positive effect on Knowledge Acquisition and Information Distribution processes; extends current theory on Exploration and Exploitation processes; validates and extends previous research on the Timing of Learning; contributes towards the validation of theory on the organisational effect of Advanced Information Technology.

Description

Date

2023-08-30

Advisors

Martinez Hernandez, Veronica

Keywords

Adaptive Structuration Theory, Case Study, Digital Twins, High-Value Assets, Industry Study, Maturity Model, Organizational Learning, Organizational Theory

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge
Sponsorship
Engineering and Physical Sciences Research Council (2275081)
EPSRC and Rolls-Royce [grant number EPSRC/DTP G105463-1]