City Research Online

Abstract

This dissertation intends to extend our scholarly and practical understanding of incumbent adaptation to digital disruption. The concept for this work was sparked by the author’s real-life, practical observations of historically successful and technologically advanced incumbent organizations stumbling in their attempts to adapt to digital disruption. Two literature streams, incumbent adaptation and digital transformation, are merged to uncover new and interesting insights – both conceptually and empirically. First, a robust literature review is conducted to lay the groundwork by providing a descriptive and thematic analysis showing how (1) two aggregate actions, recognition and response, overlap incumbent adaptation and digital transformation literatures and (2) five themes serve as multifaceted lenses through which organizations navigate adaptation in digitally disrupted environments. Building on this work, the complex, high velocity nature of digital disruption, and the critical nature of effective problemistic search for an incumbent attempting to adapt to technological change, a configurational model is developed and empirically tested to explain divergence in problemistic search amongst competitors in a close-knit medtech industry sector. Next, an in-depth, inductive historical case study is conducted to explore Red Queen evolution between long-standing duopolistic rivals and how competitive histories can disrupt and derail incumbent adaptation ambitions. I conclude by reflecting on my dissertation journey and presenting limitations, practical implications, and a future research agenda.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Departments:	Bayes Business School > Bayes Business School Doctoral Theses Bayes Business School > Management Doctoral Theses

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