The Role of Para-Social Interaction in Enhancing the Willingness of Consumers to Pay for Virtual Influencer-Endorsed Products in China: The Mediating Role of Brand Preference

This research aimed at evaluating the role of “para-social interaction” in enhancing the willingness of Chinese consumers to pay for “virtual influencer-endorsed products” while examining the role of “brand preference”, surveys 352 Chinese consumers with 21 or more years of age and having decent knowledge about virtual influencers to reach its projected outcome. With the emergence of social media in the past few years, influencer marketing has become the first-choice strategy of many brands worldwide to attract audiences and build a loyal customer base. However, this phenomenon is still in its early days in China due to less exposure, making it an area worth researching. The survey responses are analyzed with the help of SmartPLS through the “Structural Equation Modelling (SEM)” method. The analysis has revealed a strong influence of para-social influence on “brand preference” and the “willingness of consumers to pay” for “virtual influencer-endorsed products”, along with the significant impact of “brand preference” on “willingness of consumers to pay”. With these, the role of “brand preference” as a strong mediator in the relationship between the other research variables has also been found. These findings can be valuable for managers to understand their role and the function of virtual influencers in developing “brand preferences” among consumers. Factors to develop a “brand preference” can also be identified and utilized by them with the help of these. Despite these, future researchers are recommended to take the help of the qualitative research method to reach a concrete conclusion in their studies. This is because no descriptive insights can be generated using a quantitative study, which has been the case here. Still, this research reaches its projected outcome systematically by forming hypotheses and accepting or rejecting them based on statistical insights.