Use this URL to cite or link to this record in EThOS:
Title: Competitive modelling : an application to high-technology markets
Author: Bottomley, Paul A.
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 1993
Availability of Full Text:
Access from EThOS:
Forecasting models for application in a competitive environment have not attracted much academic attention despite the importance of the area for most private sector companies. The situation is particularly acute for organisations competing in high technology markets, because of the high levels of technological and market uncertainty. This uncertainty is associated with short product life cycles, dynamic market structures due to high rates of firm entry and exit and imprecise industry definition, because of the introduction of new technologies. Survey evidence suggested that organisations paid little attention to their competitors, let alone potential entrants, while fewer still employed any formal methods of analysis. Typically, competitive forces were handled informally, usually based on the opinions of managers closest to the market. Despite the dominance of managerial judgement in the analysis of competition, formal models have been proposed as an alternative in the economics and marketing science literatures. This thesis proposes to evaluate critically the usefulness of two specific classes of model, namely those of innovation diffusion and discrete choice. Diffusion models, although useful for retrospectively describing the historical development of a market, their predominant application has been forecasting. Consequently, simple timedependent models have tended to dominate the literature which have assumed that the diffusion of an innovation is not influenced by firms' marketing strategies. To relax this assumption, theoretical models have been developed to derive normative propositions concerning the evolution of marketing mix variables over the adoption life cycle, typically under the assumption of monopoly. Whilst analytically elegant, these models lack empirical validation. This thesis aims to empirically analyse the alternative model specifications for incorporating price effects into diffusion models and evaluate the forecasting capability of these and other diffusion models. In the context of telecommunications, discrete choice models have been successfully used to examine North American households' demand for access, as distinct from network usage and more recently, the choice of supplier of long distance telecommunications services. This thesis evaluates the applicability of such models in business telecommunications markets. This is illustrated by examining firms' choice of supplier in the recently liberalised mobile communications markets. The limitations and advantages of the two distinct approaches will be highlighted and recommendations made as to the suitability and potential uses of these modelling approaches. Finally, the possibilities for integrating the two in the development of "micro" based diffusion models and the implications of this for modelling competition in high-technology markets are discussed.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available