The Development and Application of the Consumer-Specific-Asset Scale

• Main Authors: Chuang, Min Chieh, 莊旻潔
• Other Authors: Chiou, Jyh Shen
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/18004027547297423313

博士 === 國立政治大學 === 國際經營與貿易研究所 === 98 === 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).