論點診斷性如何影響高涉入消費者的偏誤修正

dc.contributor蕭中強zh_TW
dc.contributorHsiao, Chung Chiangen_US
dc.contributor.author張語晴zh_TW
dc.contributor.authorChang, Yu-Qingen_US
dc.date.accessioned2023-12-08T07:43:48Z
dc.date.available2022-09-16
dc.date.available2023-12-08T07:43:48Z
dc.date.issued2022
dc.description.abstractnonezh_TW
dc.description.abstractThe ELM model developed by Petty and Cacioppo has been used in consumer behavior research for many years to explain how people form and change their opinions and attitudes towards a target. This study aims to find why there is no mention of bias correction in the high involvement of people in the ELM model. Furthermore, we explored a new moderator of argument diagnosticity in this study, and the strong diagnosticity argument was defined as being relevant to the true merit of the target and making consumers more likely to judge the product. The manipulation of high involvement situations and the comparison of four different argument qualities with strong and weak argument diagnosticity under two endorser conditions were employed. Bias corrections will occur when there is weak argument diagnosticity, indicating the argument diagnosticity is a crucial factor.en_US
dc.description.sponsorship全球經營與策略研究所zh_TW
dc.identifier60956014O-42289
dc.identifier.urihttps://etds.lib.ntnu.edu.tw/thesis/detail/2f37b4c630d8500f6c6233b6d2887245/
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/119983
dc.language英文
dc.subjectnonezh_TW
dc.subjectElaboration likelihood modelen_US
dc.subjectBias correction theoryen_US
dc.subjectArgument diagnosticityen_US
dc.subjectArgument qualityen_US
dc.title論點診斷性如何影響高涉入消費者的偏誤修正zh_TW
dc.titleHow Argument Diagnosticity Accounts for Bias Correction to High Involvement Consumersen_US
dc.typeetd

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