Behavioral Supply Chain Management
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-89822-9_115-1
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2. Al-Ubaydli, O., & List, J. A. (2015). Do natural field experiments afford researchers more or less control than laboratory experiments? The American Economic Review, 105(5), 462–466.
3. Armstrong, J. S. (2006). Findings from evidence-based forecasting: Methods for reducing forecast error. International Journal of Forecasting, 22(3), 583–598. https://doi.org/10.1016/j.ijforecast.2006.04.006
4. Aruchunarasa, B., & Perera, H. N. (2022). Mitigating the proclivity towards multiple adjustments through innovative forecasting support systems. In N. Subramanian, S. G. Ponnambalam, & M. Janardhanan (Eds.), Innovation analytics: Tools for competitive advantage. World Scientific. https://doi.org/10.1142/q0293
5. Arvan, M., Fahimnia, B., Reisi, M., & Siemsen, E. (2019). Integrating human judgement into quantitative forecasting methods: A. Omega, 86, 237–252. https://doi.org/10.1016/j.omega.2018.07.012
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