三种运营模式下O2O外卖服务供应链质量努力策略研究

O2O外卖作为"互联网+"时代下的新型餐饮模式,日益受到人们的关注。本文研究的O2O外卖服务供应链由一个O2O外卖平台、一个餐饮商家和一个配送骑手构成。O2O外卖平台决策平台的服务质量努力和服务费用,餐饮商家决策产品价格,骑手决策配送服务质量努力程度,同时会受到来自平台或商家的服务质量激励。通过分析商家配送、平台配送和商家自建平台+配送三种运营模式,分别构建O2O外卖服务供应链成员的利润函数,运用博弈理论,优化得到不同模式下O2O外卖服务供应链成员的最优质量控制策略和最优利润。利用公式推导和对比分析,分别探讨了骑手激励金额上限和市场规模对服务供应链最优策略和最优利润的影响。通过数值仿真,可得结论:服务供应链各成员利润均随着市场规模的增大而增大,随着骑手激励金额上限的增加而先增大后减少。当市场规模较小时,平台配送模式下商家最优利润最大。而当市场规模较大时,商家自建平台+配送模式下商家最优利润最大。

Optimal Quality Effort Strategy in O2O Food Delivery Service Supply Chain Based on Three Operation Models

With the emergence of various PC and mobile platforms, online payment has become more perfect than before, which makes catering takeout have a variety of operating modes. O2O food delivery as a new catering mode in the era of "Internet +" has received more attention from people day by day. Since competition in takeout industry is increasingly intense, how supply chain members avoid vicious competition and choose reasonable service quality effort and operation mode to ensure maximum revenue has become a problem to be solved. To address such decision-making challenges, in this paper, we examine such an O2O food delivery service supply chain including an O2O food delivery platform, a catering business and a distribution rider. O2O food delivery platform decides service quality effort and service cost, the catering business decides product price, while the rider who is motivated by the service quality of the platform or the catering business decides the effort level of the delivery service quality. We consider three operation models, merchant distribution, platform distribution and business self-built platform+ distribution, and explore which model is the best for the catering business. We establish profit models among three members by using game theory, and the optimal quality control strategy and the profit of the supply chain members under different conditions obtained. Using formula derivation and comparative analysis, we discuss the influence of the upper limit of the rider's incentive amount and market scale on the optimal strategies as well as profits of the service supply chain. Through numerical simulation, we can get the conclusions: Firstly, the profits of each member of the service supply chain increase with the rise of the market scale, and firstly increase and then decrease with the improvement of the upper limit of the rider's incentive amount. Secondly, when the market scale is small, the optimal profit of the platform is the largest under the platform delivery mode. However, when the market is large, platform + distribution mode is the best choice for catering business.