Whitman School of Management at Syracuse University
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Abstract Details

Can Neural Networks Predict Business Failure?: Evidence from Small Firsm in the UK
Vol. Volume 21, Number 1 March/2016

Densil A. Williams
This paper, using a flexible and more robust, analytical tool, neural networks models, analyses the factors that are most important in determining business failure among small, high-technology firms. Using the resource-based view and organisational ecology as the theoretical lens through which to view the problem, the paper modelled a number of variables that stood as proxies for resources. The results suggest that profit, in the form of retained earnings, is the most significant factor that determines failure among these firms. Other factors of importance are governance structure, location, and firm size. Importantly, the issue of governance structure as a resource has received very little attention in the works on business failure, and as such, this paper has made a contribution to the literature by adding governance as an important resource.

Keywords: Failure, Small and Medium Enterprise (SME), High-Technology, Neural Networks