Abstract
Reputation plays an important role in assuring product quality in markets where consumers can only imperfectly judge the quality before consumption. For the retailer, reputation is a valuable asset, as consumers are more likely to trust a company that has a sound reputation. The existing literature on inventory management rarely considers demand as being affected by reputation. In this study, we develop an operational research approach in which the demand rate is affected by the price, remaining shelf-life, and retailer's reputation, as well as by the heterogeneity of consumers in terms of their sensitivity to the latter two factors. We represent the retailer's reputation by the overall average freshness level of the products sold on his shelf (obtained from records), while the retailer's objective is to maximize his profit. Our analysis shows that the optimal pricing policy is only indirectly associated with the retailer's reputation (i.e., overall average freshness level), via the replenishment strategy. We demonstrate analytically that the retailer does not always prefer to achieve a higher reputation level, as this incurs higher costs due to faster replenishment. We show numerically that consumers are barely affected by their own heterogeneity; that is, the selling price barely changes and the retailer's reputation level shows only modest differences, compared with the baseline scenario (homogeneous sensitivities). The retailer, however, is significantly affected, experiencing either an increase or decrease in profits (relative to the baseline) depending on the specific distributions used to model consumer sensitivity values.
Original language | English |
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Article number | 107990 |
Journal | International Journal of Production Economics |
Volume | 232 |
DOIs | |
State | Published - Feb 2021 |
Keywords
- Expiring inventory
- Heterogeneous market
- Optimal pricing
- Reputation
All Science Journal Classification (ASJC) codes
- General Business,Management and Accounting
- Economics and Econometrics
- Management Science and Operations Research
- Industrial and Manufacturing Engineering