專屬資產是交易成本理論中最具有預測力的構念，過去專屬資產構念主要是應用在B2B交易情境，本研究欲將專屬資產所衍伸的概念應用在廠商與消費者間的交換關係，並修正目前專屬資產相關量表的一些問題，包括了對專屬資產的衡量並沒有一致性的作法、衡量方式沒有回歸到專屬資產最原始的定義，以及有些研究用單一題項或是代理變數來衡量會產生效度上的問題，因此研究一依循Churchill（1979）及Hinkin（1998）建議的量表發展程序而發展出能應用到B2C情境的消費者專屬資產量表，本研究以兩階段問卷共計1453位受訪者為施測對象，透過探索性及驗證性因素分析發展出六個構面-「特有使用知識專屬資產」、「特有實體設備/軟體或服務專屬資產」、「忠誠客戶優惠專屬資產」、「特有人際關係及溝通效率專屬資產」、「心理層面認同專屬資產」、「特有無形社會壓力專屬資產」共計19題之消費者專屬資產量表，資料顯示量表具有良好的信、效度及因素結構。 研究二為整體模型架構實證，透過文獻整理釐清專屬資產及移轉成本的相同點、相異點及兩者間的關係，並將專屬資產與移轉成本放入消費者信任-滿意-忠誠回應架構中，結果發現專屬資產為移轉成本的前置變數，且專屬資產及移轉成本皆為消費者滿意與忠誠回應間之重要中介變數。 研究三為比較本研究發展的專屬資產量表（AS量表）與傳統專屬資產量表（TAS量表）在構念預測力上是否有顯著差異，結果發現五個產業中有兩產業（專櫃化妝品業與進口車業）AS量表預測力顯著高於TAS量表，三產業（銀行業、美髮業、精品業）無顯著差異。 / Specific asset is the most predictable construct in transaction cost theory. The construct of specific asset has been most commonly used in B2B context in the past. This research aims to extend the application of specific asset to B2C context, and also solve the following 3 issues regarding the present specific asset scales. First, there is no consent about the measurement of specific asset. Second, the definition of specific asset is misunderstood. Third, some researches use single item or proxy variables to measure specific asset, which leads to potential construct validity problems. Therefore, study 1 follows Churchill (1979) and Hinkin (1998) to develop the consumer-specific-asset scale. This study uses two stages of empirical data and collects 1453 valid samples. Through exploratory and confirmatory factor analysis, this study develops a 19-item instrument, including six types of consumer-specific-asset: 1) specific knowledge, 2) specific equipment/software or service, 3) loyalty program, 4) specific relationship and communication, 5) identification, 6) invisible social pressure. The analyzed data shows that this scale has reliability, validity and good factor structure. Study 2 seeks to provide an empirical test of the structural model. The author identifies the similarities, differences and the relationship between specific asset and switching cost first, then put the specific asset and switching cost into the trust-satisfaction-loyalty response model. The results show that specific asset is the antecedent of switching cost, and both specific asset and switching cost are the important mediators between consumer satisfaction and loyalty response. Study 3 focuses on comparing the predictability between the new specific asset scale (developed from study 1) and traditional specific asset scale. The results suggest that among the 5 industries this study chose, the new specific asset scale predicts better in the 2 industries (cosmetic and car) and no significant difference in the 3 industries(bank, hair stylist and luxury goods).