EXPLORING THE POTENTIAL EFFECTS OF FORECASTER MOTIVATIONAL ORIENTATION AND GENDER ON JUDGMENTAL ADJUSTMENTS OF STATISTICAL FORECASTS
研究了物流经理如何通过判断调整统计预测来提高准确性，发现动机显著影响改进效果，且性别调节这一关系。
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.