Demand forecasts with judgement bias in a newsvendor problem-Reference-Cited by-同舟云学术

Demand forecasts with judgement bias in a newsvendor problem

Published:2022-08-16 Issue: Volume: Page:1-15
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Zheng Yini¹^ORCID,Fu Qi²^ORCID,Li Juan¹^ORCID,Zhang Lianmin³^ORCID

Affiliation:

1. School of Management and Engineering, Nanjing University, Nanjing, People’s Republic of China

2. Faculty of Business Administration, University of Macau, Taipa, People’s Republic of China

3. Shenzhen Research Institute of Big Data, Shenzhen, People’s Republic of China

Funder

University of Macau

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207543.2022.2102450

Reference47 articles.

1. The Dynamic Newsvendor Model with Correlated Demand

2. Integrating human judgement into quantitative forecasting methods: A review

3. Ban, G. Y., and C. Rudin. 2016. “The Big Data Newsvendor: Practical Insights from Machine Learning.” Available at SSRN: https://ssrn.com/abstract=2559116.

4. Bodies of Knowledge for Research in Behavioral Operations

5. Decision-making and the newsvendor problem: an experimental study

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Effects of behavioral bias regarding demand forecasting in a competitive market;Naval Research Logistics (NRL);2024-03-02

2. A data-driven newsvendor problem: A high-dimensional and mixed-frequency method;International Journal of Production Economics;2023-12

3. Design and Development of Robots for Medical Assistance;Advances in Healthcare Information Systems and Administration;2023-06-30

4. Hybridized artificial neural network with metaheuristic algorithms for bearing capacity prediction;Ain Shams Engineering Journal;2023-05

5. Method for evaluating the resource, energy, and environmental impact of the casting fault rectification process in patternless sand castings;Sustainable Materials and Technologies;2023-04