Moving towards a control technique to help small firms monitor and control key marketing parameters: A survival aid

Management Decision

Volumn 39, Issue 2, 2001, Pages 113-120

  Reynolds, Paul L ^a   Day, John ^a   Lancaster, Geoff ^b  

^a UNIVERSITY OF HUDDERSFIELD   (United Kingdom)

^b MACQUARIE UNIVERSITY   (Australia)

Author keywords

Business analysis; Consultancies; Control; Marketing management; Small to medium sized enterprises

Indexed keywords

EID: 84986038293     PISSN: 00251747     EISSN: None     Source Type: Journal    
DOI: 10.1108/EUM0000000005417     Document Type: Article

References (32)

1. Batty, M. (1969), “Monitoring an exponential smoothing forecasting system”, Operational Research Quarterly, Vol. 20 No. 3, pp. 319-25.
2. Bauman, W.S. (1965), “The less popular stocks versus the most popular stocks”, Financial Analysis Journal, Vol. 21, pp. 61-9.
3. Brown, R.G. (1962), reported in Brown. R.G. (1963), Smoothing, Forecasting and Prediction of Discrete Time Series, Prentice-Hall, New York, NY.
4. Churchill, N. and Lewis, V. (1983), “The five stages of small business growth”, Harvard Business Review, Vol. 61 No. 3, pp. 30-50.
5. Cressy, D. (1996), “Small business failure: failure to fund or failure to learn by doing”, ICSB 41st World Conference, Stockholm, pp. 385-410.
6. Department of Trade and Industry (1999), reported in Quarterly Report on Small Business Statistics, July, Domestic Finance Division, Bank of England, London, p. 35.
7. Eggers, J.H., Leahy, T. and Churchill, N. (1994), “Stages of small business growth revisited: insights into growth path and leadership/management skills in low- and high-growth companies”, Frontiers of Entrepreneurship Research, Babson College, Boston, MA, pp. 131-44.
8. Gardner, E.S. (1983), “Automatic monitoring of forecasting errors”, Journal of Forecasting, Vol. 2, pp. 1-21.
9. Geurts, M.D. and Ibrahim, I.B. (1975), “Comparing the Box-Jenkins approach with the exponentially smoothed forecasting model – application to Hawaii tourists”, Journal of Marketing Research, Vol. 12, pp. 182-8.
10. Hanks, S.H., Watson, C.J., Jansen, E. and Chandler, G. (1993), “Tightening the life-cycle construct: a taxonomic study of growth stage configurations in high technology organizations”, Entrepreneurship Theory and Practice, Winter, pp. 5-29.
11. Hogarth, R.M. (1975), “Cognitive processes and assessment of subjective probability distributions”, Journal of the American Statistical Association, Vol. 70, pp. 271-90.
12. Holt, C.C. (1957), “Forecasting seasonals by exponentially weighted moving average”, Office of Naval Research Memo, No. 52.
13. Mabert, V.A. (1975), “Statistical versus salesforce executive opinion short-range forecasts: a time series analysis case study”, working paper, Krannert Graduate School, Purdue.
14. McKenzie. E. (1978), “The monitoring of exponentially weighted forecasts”, The Journal of the Operations Research Society, Vol. 29, May, pp. 449-58.
15. Makridakis, S. and Hibon, M. (1979), “Accuracy of forecasting: an empirical investigation”, Journal of the Royal Statistical Society (A), Vol. 142 Part 2, pp. 97-145.
16. Makridakis, S. and Wheelwright, S.C. (1989), Forecasting Methods for Management, 5th ed., John Wiley & Sons, Chichester.
17. Montgomery, D.C. and Johnson, L.A. (1976), Forecasting and Time Series Analysis, McGraw-Hill, New York, NY.
18. NatWest SBRT Quarterly Survey of Small Business (1999), reported in Quarterly Report on Small Business Statistics, July, Domestic Finance Division, Bank of England, London, p. 18.
19. Newbould, P. (1974), “The exact likelihood function for a mixed autoregressive moving average process”, Biometrika, Vol. 61, pp. 423-6.
20. Reid, D.J. (1969), “A comparative study of time series prediction techniques on economic data”, PhD thesis, University of Nottingham, October, p. 80.
21. Reynolds. P.L. (1986), “The monitoring of short term sales forecasts produced by exponential smoothing”, MSc dissertation, Manchester School of Management, UMIST, pp. 130-42.
22. Reynolds, P.L. and Day, J. (1996), “A semi-automatic scheme for monitoring the adequacy of short-term sales Forecasts”, Marketing Science Conference, University of Florida, Gainesville, FL.
23. Reynolds, P.L. and Greatorex, M. (1988), “The monitoring of short-term forecasts using exponential smoothing”, Proceedings of the 21st Annual Conference Marketing Education Group, pp. 558-86.
24. Reynolds, P.L., Richards, G. and Day, J. (1995), “Marketing management for the SME – a novel approach to monitoring and control”, 1995 MEG Conference, University of Bradford, Bradford.
25. Sarbin, T.R. (1943), “Contributions to the study of actuarial and individual methods of prediction”, American Journal of Sociology, Vol. 48, pp. 593-602.
26. Scott, M. and Bruce, R. (1987), “Five stages of growth in small business,” Long Range Planning, Vol. 20 No. 10 pp. 45-52.
27. Slovic, P. (1972), “Psychological study of human judgement: implications for investment decision making”, Journal of Finance, Vol. 27, pp. 779-99.
28. Storey, D. (1994), Understanding the Small Business Sector, International Thompson Business Press, London.
29. Trigg, D.W. (1964), “Monitoring a forecasting system”, Operational Research Quarterly, Vol. 15 No. 3, pp. 271-4.
30. Trigg, D.W. and Leach, A.G. (1967), “Exponential smoothing with an adaptive response rate”, Operational Review Quarterly, Vol. 18 No. 1, pp. 53-9.
31. Winter, P.R. (1960), “Forecasting sales by exponentially weighted moving averages”, Management Science, Vol. 6, pp. 271-4.
32. Witt, S.F. and Witt, C.A. (1992), Modelling and Forecasting Demand in Tourism, Academic Press, London.