在台灣，家戶的車輛數年年攀升，車輛的來往會在起訖兩點產生停車需求，而旅遊是產生車輛來往的關鍵行為之一，民眾多利用自用小客車進行旅遊，在旅遊地區或運輸場站產生停車行為，特別在國內離島旅遊、出國旅遊時，因此種旅遊型態常有過夜需求，須將車輛停放於港口或機場，轉乘船舶或飛機前往目的地，將衍生多日停車之需求。本研究以通往國內最大外島－澎湖的「布袋國內商港」(下稱布袋商港)為例，在布袋商港客船航季期間，多透過汽車至港區的乘船旅客將在上午客船出港時間前湧入、在短時間內產生大量停車需求，而布袋商港的停車模式多為停放3日，該停車模式停放時間較一般停車長，使用者考量之因素可能與一般停車產生差異，惟國內較少文獻研究停車行為之議題，因此本研究為瞭解旅客之選擇行為，參考文獻所提之影響因素設計本研究針對布袋商港之旅客之選擇行為問卷，向至布袋商港停車之旅客進行調查，並得到使用者於布袋商港停車選擇的各項影響因素及滿意程度，包含「停車場計價方式」、「停車時間」、「遮陽設施」、「步行距離」等，再依影響程度建構最佳化模型，供停車場營運者於可預估當日來客車數時，提前藉由最佳化模式，優先提供最佳的停車場予使用者、滿足重點影響因素來提高使用者之滿意度，以達成布袋商港停車場之營運最佳化，另透過問卷調查結果顯示「停車場計價方式」、「停車時間」、「遮陽設施」為影響程度較高之因素，不僅可證實停車時間為使用者選擇停車場之重要因素，亦可提供予停車場營運者思考是否需改善現有停車場、調整停車管理策略，衡量收費方式及停車場設備是否須精進及調整，以更提高服務水準及滿意度。

In Taiwan, the number of vehicles in households has been increasing every year. The coming and going of vehicles generates parking demand between two points. Tourism is one of the key behaviors that generate vehicle movement, and people often use their own cars for travel. Parking behavior occurs in tourist areas or transportation stations, especially during domestic island tourism or international travel when overnight stays are common. Vehicles need to be parked at ports or airports before boarding ships or planes to reach their destinations, resulting in a multi-day parking demand. This study takes "Budai Domestic Commercial Port," which leads to Penghu Island - the largest outlying island in Taiwan, as an example. During the ferry season at Budai Commercial Port, many passengers who arrive by car will flood into the port area before the morning departure time of passenger ships and generate a large amount of parking demand within a short period of time. The parking pattern at Budai Commercial Port is mostly for 3 days, which is longer than general parking duration. Factors considered by users may differ from those for general parking; however, there are few studies on parking behavior in Taiwan's literature. Therefore, this study aims to understand travelers' choice behavior and design a questionnaire based on influencing factors mentioned in previous literature specifically for travelers who park at Budai Commercial Port. By surveying these travelers, we obtained various influencing factors and satisfaction levels related to their choices regarding Budai Commercial Port's parking facilities including "parking fee calculation method," "parking duration," "sunshade facilities," and "walking distance." Based on the degree of influence identified from these factors, an optimization model was constructed so that operators can prioritize providing optimal parking spaces to users based on projected daily visitor numbers using this model ahead of time while meeting key influencing factors to enhance user satisfaction and achieve operational optimization for Budai Commercial Port's parking facilities.

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