Journal of the Operational Research Society

TABLE 2

FROM:

Forecasting and operational research: a review

R Fildes, K Nikolopoulos, S F Crone and A A Syntetos

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Table 2. Most cited forecasting articles published between 1985 and 2006

Figure and tables index
Rank Article Citations
1Kahneman, D. and Lovallo, D. (1993). Timid choices and bold forecasts—A cognitive perspective on risk-taking. Management Science 39(1), 17–31.214
2Tam, K.Y. and Kiang, M.Y. (1992). Managerial applications of neural networks—The case of bank failure predictions. Management Science 38(7), 926–947.189
3Chen, F. et al. (2000). Quantifying the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information. Management Science 46(3), 436–443.147
4Bolton, R.N. (1998). A dynamic model of the duration of the customer's relationship with a continuous service provider: The role of satisfaction. Marketing Science 17(1), 45–65.133
5Salchenberger, L.M., Cinar, E.M. and Lash, N.A. (1992). Neural networks—A new tool for predicting thrift failures. Decision Sciences 23(4), 899–916.110
6Fisher, M. and Raman, A. (1996). Reducing the cost of demand uncertainty through accurate response to early sales. Operations Research 44(1), 87–99.107
7Hardie, B.G.S., Johnson, E.J. and Fader, P.S. (1993). Modeling loss aversion and reference dependence effects on brand choice. Marketing Science 12(4), 378–394.95
8Erdem, T. and Keane, M.P. (1996). Decision-making under uncertainty: Capturing dynamic brand choice processes in turbulent consumer goods markets. Marketing Science 15(1), 1–20.93
9Haubl, G. and Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Science 19(1), 4–21.92
10Mangasarian, O.L., Street, W.N. and Wolberg, W.H. (1995). Breast-cancer diagnosis and prognosis via linear-programming. Operations Research 43(4), 570–577.83
11Wilson, R.L. and Sharda, R. (1994). Bankruptcy prediction using neural networks. Decision Support Systems 11(5), 545–557.80
12Gardner, E.S. and McKenzie, E. (1985). Forecasting trends in time-series. Management Science 31(10), 1237–1246.74
13Lawrence, M.J., Edmundson, R.H. and Oconnor, M.J. (1986). The accuracy of combining judgmental and statistical forecasts. Management Science 32(12), 1521–1532.72
14Chintagunta, P.K. (1993). Investigating purchase incidence, brand choice and purchase quantity decisions of households. Marketing Science 12(2), 184–208.72
15Bunn, D. and Wright, G. (1991). Interaction of judgmental and statistical forecasting methods—issues and analysis. Management Science 37(5), 501–518.65
16Bult. J.R. and Wansbeek, T. (1995). Optimal selection for direct mail. Marketing Science 14(4), 378–394.65
17Collopy, F. and Armstrong, J.S. Rule-based forecasting—development and validation of an expert systems–approach to combining time-series extrapolations. Management Science 38(10), 1394–1414.57
18Ashton, A.H. and Ashton, R.H. (1985). Aggregating subjective forecasts—some empirical results.Management Science 31(12), 1499–1508.56
19Donohue, K.L. (2000). Efficient supply contracts for fashion goods with forecast updating and two production modes. Management Science 46(11), 1397–1411.53
20Sanders, N.R. and Manrodt, K.B. (1994). Forecasting practices in United-States Corporations—survey results. Interfaces 24(2), 92–100.52
21Cachon, G.P. and Lariviere, M.A. (2001). Contracting to assure supply: How to share demand forecasts in a supply chain. Management Science 47(5), 629–646.50
Figure and tables index
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