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  • 學位論文

應用科技接受模式及聯合分析法初探「交通行動服務(MaaS)」之使用意圖與服務屬性偏好特性

The Analysis of Usage Intention and Preference of Service Attributes for “Mobility as a Service (MaaS)” Using Technology Acceptance Model and Conjoint Analysis

指導教授 : 溫裕弘

摘要


「交通行動服務(Mobility as a Service, MaaS)」為運輸領域的創新服務概念,MaaS亦成為當前許多國家與城市永續運輸政策推行的具體目標。MaaS係涵蓋大眾運輸、共享運具及私人運具之整合運輸服務平台,提供旅運者無縫、及戶之運輸服務。鑑於MaaS為一個創新運輸服務概念,在推行之際,若能先探究瞭解使用者對MaaS之行為意圖與偏好,確實具有研究空間與重要性。 本研究以使用者觀點,初探潛在使用者對MaaS的認知與使用意圖,以科技接受模式為基礎,合併考量創新擴散理論之相容性以及認知風險因素,建構擴展型科技接受模式。同時,亦彙整相關文獻歸納出MaaS的四個重要服務屬性以及屬性內容,以聯合分析模擬使用情境供受測者進行衡量,以瞭解使用者對於MaaS服務屬性與服務內容之偏好。 研究結果發現,本研究擴展型科技接受模式中僅有認知易用性影響態度之路徑關係不成立,其餘路徑關係皆成立,相容性、認知易用性、認知有用性、態度均對MaaS行為意圖具顯著正向影響,而認知風險具負向影響,對行為意圖之影響程度大小依序為:相容性、認知有用性、態度、認知易用性及認知風險。MaaS之服務屬性相對重要程度則依序為:票證形式、平台功能、購買方式及個人化/大眾化選擇。而依聯合分析結果對整體受測者進行集群分析,能劃分出五個偏好結構不同的集群,分別為:票證/購買方式並重群、偏好機動運具群、選項從眾群、嘗新月租群及重視平台功能群,可作為市場區隔之參考。

並列摘要


“Mobility as a Service (MaaS)” is an innovative concept of service in the transportation field. MaaS is enabled by combining transportation services from public transport, shared transport, and private vehicles through a unified platform that creates and manages the trips, which users can pay for with a single account. However, few researches have examined the behavioral intention for MaaS. It is an important topic to analyze the usage intention and preference of service attributes for MaaS in advance of the planning and implementation of MaaS. This study empirically examines cognitions and behavioral intentions for using “Mobility as a Service (MaaS)”. Based on literature analysis, key factors and service attributes of MaaS are identified; namely, platform functions, transport mode integration, payment integration, ticketing integration, booking system, and personalization. This study applied Technology Acceptance Model (TAM) to analyze the relationships among perceived usefulness, perceived ease of use, compatibility, perceived risk, attitude, and usage intention of MaaS. The relationships proposed in the framework are tested using structural equation modeling. Analytical results of TAM demonstrated that compatibility, perceived ease of use, perceived usefulness, and attitude all have positive influences, and perceived risk has a negative influence on usage intention of MaaS. The influences are ranked as compatibility, perceived usefulness, attitude, perceived ease of use, and perceived risk. Furthermore, the preference of service attributes was also examined using Conjoint Analysis. From the results of conjoint analysis, the relative importance of service attributes were identified, namely, ticketing, platform functions, payment, and personalized/ordinary options. From the results of Cluster Analysis, the users were classified into five groups with different preference structures, namely, ticketing and payment concerned group, motorized mode preferred group, ordinary choice group, early adopter/monthly package group, and function concerned group.

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