We study the conditions that influence judgmental forecasting effectiveness when predicting
demand in the context of fashion products. Human judgment is of practical importance in this …

Product forecasts are a critical input into sourcing, procurement, production, inventory,
logistics, finance and marketing decisions. Numerous quantitative models have been …

The purpose of this research is to assess the extent to which judgmental forecasts are
improved by having more contextual and technical knowledge. Contextual information is …

This research investigates the benefits in forecast accuracy by combining judgmental
forecasts with those generated by statistical models. Our study differs from prior research …

This paper reviews several of the current controversies in the relative value of judgemental
and statistical forecasting methods. Where expert, informed judgemental forecasts are being …

Various advanced systems deploy artificial intelligence (AI) and machine learning (ML) to
improve demand forecasting. Supply chain planners need to become familiar with these …

This paper examines the accuracy of judgmental forecasts of product demand and the
quality of subsequent production level decisions under two different conditions:(i) the …

This study examines the utility of two widely advocated methods for supporting judgmental
forecasts—providing task feedback and providing judgmental bootstrapping support. In a …

When and to what extent should forecasts rely on linear model or human judgment? The
judgmental forecasting literature suggests that aggregating model and judge using a simple …

Whilst the research literature points towards the benefits of a statistical approach, business
practice continues in many cases to rely on judgmental approaches for demand forecasting …