| Abstract: | The growing adoption of demand collaboration initiatives such as Collaborative Planning, Forecasting, and Replenishment (CPFR) has made judgmental adjustments of forecasts, an already widespread forecasting practice, an increasingly routine part of many logistics managers' responsibilities. This article investigates how logistics managers might improve forecast accuracy by judgmentally adjusting statistical forecasts and potential factors that may influence the effectiveness of such adjustments. In particular, our goal is to expand current knowledge in this area by focusing on individual differences, specifically motivation and gender, which have been thus far neglected in the extant literature. Our findings indicate that motivation has a significant effect on accuracy improvement and this relationship is moderated by gender. Managerial implications of these findings and future research opportunities are also presented. |
