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The optimal product-line selling mode in online platforms

Author

Listed:
  • Huang, Jian
  • Qin, Xuelian
  • Tian, Lin
  • Wei, Hang

Abstract

The burgeoning success of online retailing has prompted numerous manufacturers to sell their product lines through digital platforms. Despite this trend, the optimal product-line selling mode for both manufacturers and online platforms remains ambiguous. This study aims to address this uncertainty by developing an analytical model. In this model, a manufacturer offers a product line consisting of two quality-differentiated products. Concurrently, an e-tailer (online platform) provides both the first-party and third-party modes, catering to consumers with heterogeneous preferences for product quality. The analysis reveals that when the high-quality product's quality level is sufficiently low, the manufacturer achieves maximum profit by wholesaling the high-quality product with the first-party mode but directly selling the low-quality product via the third-party mode; otherwise, the manufacturer maximizes profit by directly selling both products via the third-party mode. For the e-tailer, when the high-quality product's quality level is moderate, he can gain the highest profit by encouraging the manufacturer to wholesale both products with the first-party mode. However, when the high-quality product's quality level is sufficiently low (high), the e-tailer can obtain the highest profit under the case where the manufacturer sells the high-quality product via the third-party (first-party) mode but distributes the low-quality product with the first-party (third-party) mode. The intuition lies in the competition dynamics and the double marginalization effect under different selling modes.

Suggested Citation

  • Huang, Jian & Qin, Xuelian & Tian, Lin & Wei, Hang, 2024. "The optimal product-line selling mode in online platforms," Journal of Retailing, Elsevier, vol. 100(3), pages 486-505.
  • Handle: RePEc:eee:jouret:v:100:y:2024:i:3:p:486-505
    DOI: 10.1016/j.jretai.2024.07.003
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