| Issue |
E3S Web Conf.
Volume 409, 2023
International Conference on Management Science and Engineering Management (ICMSEM 2023)
|
|
|---|---|---|
| Article Number | 02002 | |
| Number of page(s) | 14 | |
| Section | Decision Support Systems | |
| DOI | https://doi.org/10.1051/e3sconf/202340902002 | |
| Published online | 01 August 2023 | |
Research on Try-before-you-buy Strategy Under Product Fit Uncertainty
1 School of Business, Sichuan University, Chengdu 610065, People’s Republic of China
2 Department of Computing Science, University of Alberta, T6G 2S4, Canada
* e-mail: 457718518@qq.com
With the rapid development of online retail, the drawback of product fit uncertainty in online markets are becoming more and more prominent. In order to alleviate the impact of the product fit uncertainty, online retailers continue to introduce new service strategies. Based on the uncertainty of product matching, this paper constructs and solves the model of direct sales and try-before-you-buy(TBYB) strategy by online retailers under the premise of whether to allow returns. And explore the optimal strategy for the e-retailer in different aiming. The results show that: When the product fit is low, the optimal strategy choice for online retailers is TBYB strategy. When the product fit is high, if products are allowed to be returned, sell the product directly is the optimal strategy choice; if not, both TBYB and direct sales are optimal strategies. When the product fit is moderate, for products that are allowed to be returned, sell products directly when aiming to maximize demand and adopt the TBYB strategy when maximize profits. For products that are not allowed to be returned, Online retailers should sell products directly when aiming to maximize demand.
Key words: Try-Before-You-Buy / Return policies / Hassle cost / Online shopping / Product fit uncertainty
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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