A case study on attitude towards online auction use applying quantile regression analysis

Yen Chun Chen, Hsun Chi Chu, Jyun Yi Wu, Nomin Tsembel*, Yung Cheng Shen

*此作品的通信作者

研究成果: 雜誌貢獻期刊論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

This study uses the technology acceptance model (TAM) as a basis, extended by conducting quantile regression to examine the factors influencing the use of an online auction Website and then comparing the results to the conventional linear regression-type approaches. Specifically, the TAM has been widely assessed in various research contexts by using ordinary least squares regression model and structural equation modelling. However, these two methods focus on describing the ‘average’ behaviour of a conditional distribution, thus overlooking extreme value and outlier effect. Following this, this study applied quantile regression model to examine the TAM for online auctions, thereby complementing previous empirical findings about the TAM. Using survey data from 476 online auction users with experience selling items on Yahoo!Auction, the results indicate that perceived ease of use is most important for customers with a more favourable attitude towards the site, whereas perceived enjoyment plays a more crucial role in improving attitudes towards using the site among customers with less favourable attitudes towards the site. Findings also suggest that perceived usefulness is more effective in improving attitude towards using the site among customers with moderately favourable attitudes than among customers with unfavourable and very favourable attitudes.

原文英語
頁(從 - 到)872-892
頁數21
期刊Total Quality Management and Business Excellence
30
發行號7-8
DOIs
出版狀態已發佈 - 2019 五月 19

ASJC Scopus subject areas

  • 商業、管理和會計 (全部)

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