盈利能力指数
业务
产业组织
竞赛(生物学)
供应链
质量(理念)
利润(经济学)
繁荣
营销
经济
微观经济学
生态学
哲学
财务
认识论
生物
经济增长
作者
Lu‐Yu Chang,Yue‐Yue Mi,Chuanxu Wang,Qing Zhang
摘要
Abstract The prosperity of internet sales is stimulating a phenomenal growth of retail platforms and manufacturer encroachment. Encroachment spawns channel competition, potentially threatening the platform's profit, which in turn induces a series of countermeasures by the platform. Motivated by this trend, we develop a game‐theoretical model to explore the strategic and tactical interactions between a manufacturer and a platform, in which the manufacturer determines encroachment strategy and quality differentiation tactic, and the platform determines sales mode strategy and information sharing tactic. We find that the manufacturer is profitable and the platform is damaged from encroachment. Furthermore, the manufacturer's quality differentiation tactic can propel the platform to select reselling that indirectly enhances post‐encroachment profitability. In contrast, sales mode and information sharing can be mono or jointly utilized by the platform to counter encroachment. Significantly, we provide a novel inspection method to systematically analyze the cumulative performance of the platform's two countermeasures by introducing the synergy effect , dysergy effect , and mutual exclusivity effect . Interestingly, we highlight that the performance of mono‐countermeasures may be even more effective than that of combined countermeasures to mitigate the platform's loss caused by encroachment. This finding enriches not only the analytic understanding of received wisdom about whether more countermeasures can invariably hold competition edges but also provides useful managerial guidelines for strategic interaction research. Moreover, the manufacturer's increased encroachment capabilities may promote the platform to shift from reselling to agency selling, which reveals that manufacturer encroachment may be a critical factor in the popularity of agency selling.
科研通智能强力驱动
Strongly Powered by AbleSci AI