基於外送平台服務下之業者定價模式探討

外送平台因受疫情影響，導致需求量增大。業者與外送平台合作時需要給予抽成費用，導致業者面臨定價是否該漲價的抉擇。雖然顧客對定價是非常敏感，但是業者也必須考慮到成本。現今有許多種定價方法，本研究以顧客為導向探討定價模式，以獲得較高的平均利潤與顧客滿意度。本研究以粒子群演算法為基礎，利用問卷資料所蒐集到的顧客接受價格透過模擬程式產生平均利潤與顧客滿意度。最終得出最佳組合解，為業者提高利潤與顧客滿意度。研究顯示在粒子群演算法的定價下優於業者定價，另考慮針對不同抽成比率和訂單間隔的一些敏感性分析。抽成比率增加，導致定價上升、平均利潤下降，顧客滿意度下降；訂單間隔增加，導致平均利潤下降，顧客滿意度上升。

關鍵字

外送平台服務；粒子群演算法；定價模式

並列摘要

Delivery platforms are affected by the outbreak, resulting in increased demand. Although customers are very sensitive to pricing, operators must also consider the cost. There are many kinds of pricing methods nowadays, and this study is customer-oriented to discuss pricing models. This research is based on Particle Swarm Optimization, using the customer acceptance price collected from the questionnaire to generate average profit and customer satisfaction through a simulation program. Finally, the best combination solution can be obtained to improve profits and customer satisfaction for the industry. Research shows that the pricing of PSO algorithm is better than the pricing of the industry. In addition, some sensitivity analysis for different commission ratios and order intervals is considered. The increase in the commission ratio leads to an increase in pricing, a decrease in average profits, and a decrease in customer satisfaction; an increase in order intervals leads to a decrease in average profits and an increase in customer satisfaction.