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Bayesian approach to forecasting in small firms

https://doi.org/10.26518/2071-7296-2015-3(43)-173-177

Abstract

The authors, represented the University of Huddersfield in United Kingdom and Omsk financial university in Russia, investigate the problems of forecasting in small firms. On the basis of studying activity of Russian and English forms there are educed the barriers on the way of effective realization of a such important function of management as forecasting. It is proved that for small frims the Bayesian approach is the most acceptable for forecasting, the distinctive peculiarity of which is using, on the way with objective, subjective information, which may be obtained and systematized on the basis of subjective judgements of entrepreneurs who have a small business. As a practice shows, exactly subjective judgements play the significant role in making managerial decisions in small business.

About the Authors

Paul L. Reynolds
Business School of Hudclersfield University
Russian Federation


Alexander Ivanovich Kovalyov
Financial University under the Government of the Russian Federation
Russian Federation


References

1. Ковалев А.И. Формирование и развитие менеджмент- образования в высшей школе: дис… д-ра экон. наук: 08.00.05. Омск, 2003. - 413 с.

2. Ledbetter, W.N. and Cox, J.F. (1977). Operations research in production management: An investigation of past and present utilisation. Managements, 18 (3) pp.84-91.

3. Scott, M. and Bruce, R., (1987), «Five stages of growth in small business», Long Range Planning, 20 no 3, pp. 45-52.

4. St. Andrews University. (2003) Available at: http://www-history/mes/st-andrews/ac/uk

5. Van Stel, A., M. Carree and R. Thurik. The effect of Entrepreneurial Activity on National Economic Growth. Small Business Economics, 2005. no 24 (3). pp. 311-321.


Review

For citations:


Reynolds P.L., Kovalyov A.I. Bayesian approach to forecasting in small firms. The Russian Automobile and Highway Industry Journal. 2015;(3(43)):173-177. (In Russ.) https://doi.org/10.26518/2071-7296-2015-3(43)-173-177

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ISSN 2071-7296 (Print)
ISSN 2658-5626 (Online)