Love, N E (2009) Leading indicators of failure: a study of SMEs in the construction sector in Wales and Scotland. PhD thesis, University of the West of England, Bristol, UK.
Abstract
In a dynamic UK economy, small and medium sized enterprises (SMEs) play an important role by contributing to employment and growth. Despite recognition of the importance of SMEs, and the diagnostic value of developing models for the sector, very few research studies have investigated developing failure prediction models for these businesses. Further, previous research studies highlight the importance of developing models on a regional basis rather than on a cross-regional or cross national basis. This study contributes to research in the area of failure prediction modeling in two ways. Firstly, the study successfully develops failure prediction models for construction SMEs in two regions of the UK, Wales and Scotland. Financial ratios, representing 'leading indicators' of failure, were used to develop failure prediction models by applying a range of statistical techniques including factor analysis, discriminant analysis and logistic regression analysis. In addition, the application of logistic regression analysis identified differences in the 'leading indicators' of failure between the two regions. Secondly, the study reflects on the exogenous and endogenous factors that impact on SME performance and concludes that these factors partially explain or inform the leading indicators included in the models developed. Therefore, the study adds to the body of knowledge by suggesting possible causes of success and failure of construction SMEs in Scotland and Wales.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | employment; factor analysis; financial ratio; regression analysis; small and medium sized enterprises; SMEs; UK |
| Index terms: | prediction model, body of knowledge, Wales, financial ratio, construction sector, employment, small and medium sized enterprise, discriminant analysis, regression analysis, modelling, factor analysis, Scotland, logistic regression analysis |
| Subjects: | organization, knowledge management, analytical methods, prediction and forecasting, economic analysis, management, Geography, industry analysis, statistical analysis |
| Topics: | Business Strategy, Research Practice, Information Management, Human Resources, Geographical Context, Engineering Principles |
| Descriptive scope: | 4 PCTA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here