The impact of rumors on the judgmental forecasting process

The study investigates the impact of rumors when forecasting changing time series. In this study, the subjects were presented with three types of rumors about the future direction of the time series-correct rumors, incorrect rumors and rumors which provide no information. Results indicate that correct rumors improved the quality of the forecasts; incorrect rumors and rumors with no information content evoked the same quality of the forecasts. The latter relationships persisted and affected forecasting quality in subsequent time series.<<ETX>>

[1]  Spyros Makridakis,et al.  Factors affecting judgmental forecasts and confidence intervals , 1989 .

[2]  Fred Collopy,et al.  Expert Opinions About Extrapolation and the Mystery of the Overlooked Discontinuities , 1992 .

[3]  Fred Collopy,et al.  Management science: D. Bunn and G. Wright, “Interaction of Judgmental and Statistical Forecasting Methods: Issues and Analysis”, 37 (1991) 501–518 , 1992 .

[4]  Marcus O'Connor,et al.  Exploring judgemental forecasting , 1992 .

[5]  Fred L. Collopy,et al.  Error Measures for Generalizing About Forecasting Methods: Empirical Comparisons , 1992 .

[6]  Douglas J. Dalrymple Sales forecasting practices: Results from a United States survey , 1987 .

[7]  Marcus O'Connor,et al.  An examination of the accuracy of judgmental extrapolation of time series , 1985 .

[8]  L. Brown,et al.  Comparing Judgmental to Extrapolative Forecasts: It's Time to Ask Why and When , 1988 .

[9]  D. Turner The role of judgement in macroeconomic forecasting , 1990 .

[10]  R. Tsay Outliers, Level Shifts, and Variance Changes in Time Series , 1988 .

[11]  J. Scott Armstrong,et al.  Evaluation of Extrapolative Forecasting Methods: Results of a Survey of Academicians and Practitioners , 1982 .

[12]  Spyros Makridakis,et al.  Forecasting when pattern changes occur beyond the historical data , 1986 .

[13]  Michael Lawrence An exploration of some practical issues in the use of quantitative forecasting models , 1983 .

[14]  Stephen K. McNees The role of judgement in macroeconomic forecasting: D.S. Turner, Journal of Forecasting 9 (1990) 315-345 , 1991 .

[15]  Spyros Makridakis,et al.  Accuracy measures: theoretical and practical concerns☆ , 1993 .

[16]  D. Bunn,et al.  Interaction of judgemental and statistical forecasting methods: issues & , 1991 .

[17]  Marcus O'Connor,et al.  The use of non‐time series information in sales forecasting: A case study , 1988 .

[18]  Stephen K. McNees The role of judgment in macroeconomic forecasting accuracy , 1990 .

[19]  Steven C. Wheelwright,et al.  Forecasting methods and applications. , 1979 .

[20]  William Remus,et al.  Judgemental forecasting in times of change , 1993 .

[21]  Thomas R. Willemain,et al.  Graphical adjustment of statistical forecasts , 1989 .

[22]  C. F. Stevens,et al.  A Bayesian Approach to Short-term Forecasting , 1971 .

[23]  R. H. Edmundson,et al.  The accuracy of combining judgemental and statistical forecasts , 1986 .

[24]  Henk Sol,et al.  Proceedings of the 54th Hawaii International Conference on System Sciences , 1997, HICSS 2015.

[25]  Fred Collopy,et al.  Causal Forces: Structuring Knowledge for Time-Series Extrapolation , 1993 .

[26]  Larry P. Ritzman,et al.  The need for contextual and technical knowledge in judgmental forecasting , 1992 .

[27]  Lewis W. Coopersmith Forecasting time series which are inherently discontinuous , 1983 .

[28]  Robert L. Winkler,et al.  The accuracy of extrapolation (time series) methods: Results of a forecasting competition , 1982 .