咖啡廳在設定低消、限時或不限時制度時，不能只看單次消費金額或座位周轉率。若低消過高，可能降低顧客進店意願；若限時過短，雖可提高座位周轉，但也可能影響顧客體驗並增加現場服務壓力。因此，本文以台南市咖啡廳為研究範圍，探討連鎖與非連鎖咖啡廳在不同營運條件下，如何配置低消與時間制度，以提升每小時總利潤。
本文建立咖啡廳內用制度最佳化模型，將最低消費金額、限時長度與不限時制度納入同一決策架構，並同時考量有效需求、座位產能、實際服務人數、加點消費與動態限時成本。研究以 Google Maps 顧客評論作為顧客反應資料，再依評論內容標記時間與價格相關負面反應，並透過迴歸分析轉換為顧客對限時與低消之敏感度參考，最後以全域搜尋法求解不同需求情境與參數條件下之最佳制度組合。
數值分析結果顯示，連鎖與非連鎖咖啡廳呈現不同的制度配置邏輯。連鎖店在不同需求情境下皆傾向採取不限時制度，並搭配 160 元低消，表示縮短停留時間未必能提高每小時總利潤；維持較寬鬆的時間制度，並透過加點機會，反而較符合模型結果。相較之下，非連鎖店的最佳制度會隨需求變化而調整。低需求情境下，最佳配置為 160 元低消與 80 分鐘限時；中需求情境下，最佳配置為 170 元低消與 70 分鐘限時；高需求情境下，最佳配置則為 175 元低消與 60 分鐘限時。此結果顯示，非連鎖店在需求較高時需要較短限時以維持座位周轉，但在需求較低時，過短限時可能不利於利潤提升。
敏感度分析結果顯示，顧客對價格與時間限制的反應、現場作業負荷與加點潛力，皆會影響最佳制度選擇。當顧客較在意限時或現場作業負荷提高時，模型會傾向放寬限時；當顧客對價格較不敏感，或加點消費較高時，較高低消或較長停留時間才較容易帶來利潤優勢。整體而言，咖啡廳不應單純以提高低消或縮短限時作為管理方式，而應依店型、需求高低與顧客反應調整制度。本文將低消、限時與不限時制度整合為可量化比較之最佳化問題，並納入顧客評論反應、加點消費與現場作業負荷，提供咖啡廳檢視內用制度之決策參考。

This study examines how cafés should configure minimum spend, time-limit, and unlimited-time policies under different operating conditions. Setting a minimum spend too high may reduce customers' willingness to enter, while an excessively short time limit may improve seat turnover but also weaken customer experience and increase operational workload. Focusing on cafés in Tainan City, this study develops an optimization model to compare chain and independent cafés with the objective of maximizing hourly total profit.
The model integrates three decision variables: minimum spend M, time-limit length T, and the unlimited-time indicator I_inf. It considers effective demand, seating capacity, actual served customers, add-on spending, and dynamic time-limit cost. Google Maps reviews are used to observe customer responses to price and time restrictions. The sample includes 500 reviews from five Starbucks stores in Tainan and 500 reviews from a representative independent café. Time-related and price-related negative comments are coded and transformed into customer sensitivity parameters, and a global search method is applied to identify optimal policy combinations under different demand scenarios and sensitivity settings.
Numerical results show distinct policy patterns for chain and independent cafés. For chain cafés, the optimal result across low, medium, and high demand scenarios is an unlimited-time policy with a minimum spend of NT$160. For the independent café, the optimal policy varies with demand: NT$160 and an 80-minute limit under low demand, NT$170 and a 70-minute limit under medium demand, and NT$175 and a 60-minute limit under high demand. Sensitivity analysis further indicates that customer sensitivity, operational workload, and add-on spending potential all influence the optimal policy choice. The findings suggest that cafés should not rely solely on raising minimum spend or shortening time limits, but should adjust policies according to store type, demand level, and customer responses.

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