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Consumers’ Attitudes towards Online Advertising: A Model of Personalization, Informativeness, Privacy Concern and Flow Experience
Online personalized advertising has been widely adopted in China in the recent years, leading to both positive and negative results. This study endeavors to examine the impact of perceived personalization of online advertising on consumers’ attitudes toward advertising. A total of 472 questionnaires were administered and analyzed using Structural Equation Modeling. The results show that perceived personalization exerts a positive impact through perceived informativeness, and a negative impact through privacy concerns. However, the positive effect was determined to be stronger and thus perceived personalization had an overall positive impact. Additionally, the results showed that both effects were mediated by flow experience. The practical and theoretical implications of the findings were discussed.
Consumers’ Attitudes towards Online Advertising: A Model of Personalization, Informativeness, Privacy Concern and Flow Experience
Online personalized advertising has been widely adopted in China in the recent years, leading to both positive and negative results. This study endeavors to examine the impact of perceived personalization of online advertising on consumers’ attitudes toward advertising. A total of 472 questionnaires were administered and analyzed using Structural Equation Modeling. The results show that perceived personalization exerts a positive impact through perceived informativeness, and a negative impact through privacy concerns. However, the positive effect was determined to be stronger and thus perceived personalization had an overall positive impact. Additionally, the results showed that both effects were mediated by flow experience. The practical and theoretical implications of the findings were discussed.
Consumers’ Attitudes towards Online Advertising: A Model of Personalization, Informativeness, Privacy Concern and Flow Experience
Li Mo (Autor:in) / Xiaosan Zhang (Autor:in) / Yabin Lin (Autor:in) / Zhenghui Yuan (Autor:in) / Zengjun Peng (Autor:in)
2023
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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