Integrating human judgement into quantitative forecasting methods: A review
| Autor: | Meysam Arvan, Enno Siemsen, Behnam Fahimnia, Mohsen Reisi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
021103 operations research
Information Systems and Management Computer science Management science Strategy and Management 05 social sciences Judgement 0211 other engineering and technologies Context (language use) 02 engineering and technology Management Science and Operations Research Demand forecasting Procurement 0502 economics and business Contextual information Production (economics) Support system Product (category theory) 050203 business & management |
| Zdroj: | Omega. 86:237-252 |
| ISSN: | 0305-0483 |
| Popis: | Product forecasts are a critical input into sourcing, procurement, production, inventory, logistics, finance and marketing decisions. Numerous quantitative models have been developed and applied to generate and improve product forecasts. The use of human judgement, either solely or in conjunction with quantitative models, has been well researched in the academic literature and is a popular forecasting approach in industry practice. In the context of judgemental forecasting, methods that integrate an expert's judgement into quantitative forecasting models are commonly referred to as “integrating forecasting” methods. This paper presents a systematic review of the literature of judgemental demand forecasting with a focus placed on integrating methods. We explore the role of expert opinion and contextual information and discuss the application of behaviourally informed support systems. We also provide important directions for further research in these areas. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect