Name
Title | ||
|---|---|---|
Preordering in Luxury Fashion: Will Additional Demand Information Bring Negative Effects to the Retailer?* |
Abstract | ||
|---|---|---|
Preordering is an emerging business model in luxury fashion, which provides consumers the opportunity to preorder new collection products immediately after fashion runway shows and helps retailers collect preordering information for updating demand forecast. Based on our observations of industrial practices, we establish stylized analytical models for a supply chain consisting of a luxury brand (supplier) and a retailer. In addition, we explore the consequences of preordering for the supply chain, its members, and conspicuous consumers. Results show that preordering information incentivizes the retailer to increase product scarcity and leverage consumers' conspicuous consumption to charge a premium retail price, which consequently allows the supplier to increase the wholesale price. However, preordering information updating may have negative effects on the retailer due to the increased wholesale price, but this case always benefits the supplier. We recognize that preordering has two effects, aservice-extending effectand aprecision-improving effect, which positively and negatively affect consumers, respectively. Thus, retailers offering the preorder services should provide consumers with incentives (e.g., gifts or coupons) to achieve an all-win scenario with preordering information updating. This finding is consistent with widely observed industrial practices in e-commerce. In addition, our numerical studies interestingly show that all supply chain members can benefit from an increase in the level of conspicuous consumption in the market. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1111/deci.12491 | DECISION SCIENCES |
Keywords | DocType | Volume |
Conspicuous Consumers, Information Updating, Luxury Fashion, Preordering | Journal | 53 |
Issue | ISSN | Citations |
4 | 0011-7315 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Shen | 1 | 431 | 34.86 |
| Ting Zhang | 2 | 0 | 1.35 |
| Xiaoyan Xu | 3 | 0 | 0.34 |
| Hau-Ling Chan | 4 | 0 | 0.34 |
| Tsan-Ming Choi | 5 | 1040 | 75.03 |