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A strategic typology for UK small and medium sized enterprises. An investigation of influential factors and the development of a predictive typology
Kendrick, Sean
Kendrick, Sean
Publication Date
2012
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The University of Bradford theses are licenced under a Creative Commons Licence.
Peer-Reviewed
Open Access status
Accepted for publication
Institution
University of Bradford
Department
School of Management
Awarded
2012
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Abstract
The success of small and medium enterprises (SMEs) is critical to Europe’s
economic health, however, our understanding of SME strategic behaviour is
predominantly based on large enterprise theory. This study uses the Miles and
Snow (1978) typology to examine the strategic behaviour of 150 UK SMEs. It
also investigates whether strategy type, environment adaptation and
organisational performance can be predicted by several contingency factors:
organisation size, age, industry type, and management style.
The findings confirm that the typology is not well suited for categorising SMEs;
organisations that rarely develop through all three domains of the adaptive cycle
to be sufficiently eligible for categorisation by one of the four pure archetypes.
However, similar patterns of strategic behaviour were observed for certain
dimensions, largely independent of the industry type or size of the SME,
suggesting that an optimal configuration of mixed strategies may exist.
Furthermore, Reactors, or those with mixed strategies, were found to perform
similarly as Analysers and better than Defenders.
The study also found that by fitting nominal logistic regression models to
organisation age and size data, it was possible to predict strategic behaviour
and environment adaptation, and to a lesser degree, financial performance.
Surprisingly, the industry type and management style data were observed to
exert minimal influence on the outcome variables.
Finally, this research provides important insight relating to the validity concerns
of the Miles and Snow typology and categorisation method employed, and
demonstrates how these can be avoided.
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Thesis
Qualification name
DBA