Estimating uncertainties using judgmental forecasts with expert heterogeneity
Year of publication: |
2020
|
---|---|
Authors: | Bansal, Saurabh ; Gutierrez, Genaro J. |
Published in: |
Operations research. - Catonsville, MD : INFORMS, ISSN 0030-364X, ZDB-ID 123389-0. - Vol. 68.2020, 2, p. 363-380
|
Subject: | Industries: agriculture/food | decision analysis: research and development | Operations and Supply Chain | decision analysis: agribusiness research and development (R&D) | risk-return trade-off | probability distribution | Lieferkette | Supply chain | Theorie | Theory | Industrieforschung | Industrial research | Agroindustrie | Agro-industry | Risiko | Risk | Entscheidung | Decision | Prognoseverfahren | Forecasting model | Wahrscheinlichkeitsrechnung | Probability theory |
-
Judgment extremity and accuracy under epistemic vs. aleatory uncertainty
Tannenbaum, David, (2017)
-
A Bayesian belief network-based probabilistic mechanism to determine patient no-show risk categories
Simsek, Serhat, (2021)
-
Ranking distributions when only means and variances are known
Müller, Alfred, (2020)
- More ...
-
Using experts' noisy quantile judgments to quantify risks : theory and application to agribusiness
Bansal, Saurabh, (2017)
-
Bansal, Saurabh, (2016)
-
Bansal, Saurabh, (2021)
- More ...