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Title: Depth or breadth : towards a contingency model of innovation strategy in the automotive sector
Author: Rosenberg, Mike
ISNI:       0000 0004 2704 4425
Awarding Body: Cranfield University
Current Institution: Cranfield University
Date of Award: 2010
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The thesis explores the strategic choices made by automotive manufacturers in developing and deploying technology that is discontinuous and potentially disruptive. It studies the deployment of seat belts, airbags, hybrid vehicles and fuel cell electric vehicles, drawing on product deployment histories, patents and the opinions of industry experts. The thesis identifies two fundamental strategies called depth and breadth and shows how the different manufacturers’ approach to these four technologies is arrayed along a continuum between these two choices. The thesis contributes to the theory of the technology-based firm which focuses on the management of scale, scope, time and space by making operational the idea of scope with depth and breadth. It also explicitly links the theory to the literature on coevolution and dynamic capabilities and adds to the understanding of the co-evolutionary dynamics at play in the automotive industry by applying the idea of technological pathways to the technologies under study. This discussion yields some potentially interesting insight for practitioners. The thesis also reviews the literature concerning the potential changes to automotive power train technology and adds to it by using the theory of the technology-based firm as well as environmental literature and the non market strategy lens in order to develop a nonbiased view of the state of development of fuel cell and hybrid technology. Finally, the thesis provides a rigorous review of the use of patents in management science over the last 50 years and makes one of the first attempts in the academic literature to study patents using a patent mapping tool to help make sense of the large amounts of data available in line with the new ideas concerning the importance of developing visualisation techniques in data intensive scientific enquiry.
Supervisor: Bessant, Conrad Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available