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Competition or cooperation: Strategy analysis for a social commerce platform

竞赛(生物学) 社会商业 产业组织 业务 计算机科学 运筹学 社会化媒体 万维网 工程类 生态学 生物
作者
Haiqing Song,Rui Wang,Yanli Tang
出处
期刊:European Journal of Operational Research [Elsevier]
卷期号:318 (2): 560-574 被引量:7
标识
DOI:10.1016/j.ejor.2024.05.014
摘要

Consider a market where identical products are sold to consumers via two competing platforms: one traditional and the other social-commerce-based. The social commerce platform operates a virtual community using two strategies: a competition strategy whereby the social commerce platform attracts and engages consumers through its virtual community, leading them to directly purchase products from its e-commerce channel, and a cooperation strategy whereby the social commerce platform integrates links to the traditional platform's online channel within its community. We fully characterize the optimal decisions and corresponding profits and consumer surplus under each strategy. Our findings indicate that while platforms increase prices in a market with full coverage, they (weakly) decrease them in a market with partial coverage if consumer unit travel costs increase. Additionally, we explain how the revenue-sharing rate and spillover effect of a virtual community affect the cooperation strategy and discover that they have a nonmonotonic impact on the effort level of the social commerce platform. Importantly, we show that when the downstream market is partially covered, the cooperation strategy could result in a win-win-win situation for platforms, consumers, and social welfare. When the downstream market is fully covered, however, the cooperation strategy may result in a lose-win-lose, lose-win-win, or lose-lose-win situation for the social commerce platform, traditional platform, and consumers. Implementing the cooperation strategy might reduce social welfare. We also consider three extensions—sequential pricing, the traditional platform investing in its own virtual community, and a cooperation strategy with cost sharing—to check the robustness of the main results.
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