2365. Refining demand accuracy for competing retailers
Invited abstract in session TB-33: Behavioural operations 1, stream Behavioural OR.
Tuesday, 10:30-12:00Room: Maurice Keyworth 1.31
Authors (first author is the speaker)
| 1. | Meng Wu
|
| Sichuan University | |
| 2. | Xiaoyin Cao
|
| Sichuan University | |
| 3. | Tian Bai
|
Abstract
With recent advancements in technology significantly boosting forecasting accuracy,
more retailers are investing in enhancing their forecasting capabilities to reduce
demand uncertainty. This paper examines how reducing demand uncertainty affects
demand competition between two retailers in a market where competition is driven by
their supply levels. Utilizing a mean-preserving approach to characterize uncertainty
reduction, we derive equilibrium order quantities and profits. Our findings suggest that
while reducing uncertainty can improve supply-demand matching in monopolistic
settings—benefiting low and high margin products—it may deteriorate supply-demand
matching for medium-high margin products, potentially resulting in profit losses.
Importantly, improved demand accuracy does not always translate into a competitive
advantage, which contrasts with the notion that lower demand uncertainty is always
beneficial in both monopolistic markets and substitution competition.
Keywords
- Behavioural OR
- Inventory
Status: accepted
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