Judgmental demand forecasting constitutes an integral part of inventory management and production planning activities within organizations. Among forecasting academicians and practitioners, there is the generally accepted belief that the presence of scenarios is largely beneficial for future planning and may aid the decision makers in producing these demand predictions. However, there is only circumstantial evidence and some studies report controversial findings. One recent experimental work (Gonul, Goodwin & Onkal, ISF2019) investigated the interaction between the existence of optimistic and pessimistic scenarios and the presence of time-series information alone in the task of generating demand forecasts and the following production order decisions. The findings revealed that providing scenarios worsened forecast accuracy and swayed the production order decisions further away from the optimality. What were the reasons underlying these results? Why did scenarios degrade forecasters’ accuracy? This current work is an attempt to disentangle this puzzle by trying to shed some light on these controversial findings through the application of a Generalized Estimating Equations (GEE) model. The findings from this analysis will be discussed to guide future research on scenarios and judgmental forecasting.
|Number of pages||21|
|Publication status||Published - 5 Nov 2020|
|Event||ISF 2020: 40th International Symposium on Forecasting - Virtual, Rio de Janeiro, Brazil|
Duration: 26 Oct 2020 → 28 Oct 2020
|City||Rio de Janeiro|
|Period||26/10/20 → 28/10/20|