在新冠肺炎疫情影響之下，人們為了避免與他人面對面接觸，轉向更頻繁地透過線上購物平台來購買生活所需的物品。本研究以全聯線上購平台之易腐性商品為例，因商品品質隨著時間快速劣化之特性，使零售商不適合一次大量進貨，其進貨頻率較一般耐久財高。目前全聯線上購平台商品是否顯示缺貨，均倚靠管理階層的經驗作決策，在人為主觀意識的差異下，也使得每間全聯門市經理對於進貨標準不一致，導致商品存貨不足或過期報廢的狀況，進而造成全聯的經濟損失以及食物的浪費。本研究發展零售商的決策支援模式，透過文獻回顧的方式確定平台上消費者需求以及零售商的成本結構，進而建立零售商的連續利潤模型，商品價格以動態定價的方式，應用最佳化控制理論求得控制變數的最佳控制路徑，並透過案例分析的方式驗證模型的有效性。研究結果發現零售商採用每日進貨不同商品數量的策略會帶來較高的利潤，若使用進貨成本函數計算的方式，會明顯地降低零售商的銷貨成本，並且使零售商提高17%的利潤，本研究將此研究結果提供經營管理階層數據資料參考，輔助其作管理上之決策，藉以提升全聯線上購整體的服務品質，並且創造更多的利潤空間，以達企業追求利潤極大化的目標。

During the COVID-19 pandemic, people have increased their online shopping activity to buy essentials and avoid in-person interactions. This study focuses on perishable products sold on the PXGo! online platform. Because these products deteriorate more quickly than shelf-stable goods, retailers can't buy them in bulk, leading to more frequent restocking. Currently, the PXGo! platform relies on manager experience to spot shortages, causing inconsistency in restocking among store managers due to personal differences. This leads to stock shortages, food waste, and ultimately economic losses for PXGo! To address this issue, our research develops a support model for retailers. We analyze customer demands and retailer costs using a thorough literature review. Applying a continuous profit model, we use optimal control theory to set prices dynamically and determine the best way to manage stock. We confirm the model's success through case studies. Our findings suggest that replenishment of varying quantities of different products daily boosts retailer profits. By using the replenishment cost function, we significantly cut selling costs and increase profits by 17%. This research equips operational and management levels with data to enhance decision-making. The findings help PXGo! improve its online shopping quality and increase profits, aligning with the company's goal of maximizing returns.

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