Abstract

The emergence and eventual proliferation of the internet over the past three decades has had noteworthy impacts on e-commerce. While this is the case, the presence of large amounts of information have led customers into making irrational purchase options; prompting companies to develop varied automated online product recommendation systems to aid buyers in reducing information overload. Although such systems have proven effective to a certain extent, customers have raised concerns towards providers’ business interesting and their own privacy concerns. Following this controversy, the paper seeks to identify models of enhancing users’ willingness to accept recommendations from automated systems.

The paper proposes that online businesses are taking into account influencer marketing, utilizes the special features that the influencers have. The paper proposes a user recommendation system that prototypes the preference for users and the involved items concurrently. In the realm of the paper, curators ought to enrich it with additional personal insights. The human aspect of the curated system enhances user trust as well as transparency; emotional trust influences purchase options. The paper also hypothesizes that the customers who utilize the curator system would have a higher acceptance rate of its recommendations than the typical recommendation system. Following this, the paper assumes that trust mediates between the willingness to accept the recommendation and the types of system utilized. Lastly, it proposes that higher transparency of the recommendation process systems bolsters the relationship between perception of trust and the willingness to accept recommendations.

The findings of this paper are resounding. The general automatic recommendation includes curators, the consumers’ readiness to accept the recommendation increases. In the realm of the second assumption, while trust influences the customers’ decision to repurchase and to renew subscriptions, there is a full mediation effect between RSs adoption and the users’ desire to accept. In the third assumption, both the expertise and popularity of the curator have a positive impact on the willingness to accept recommendations. The fourth hypothesis was unexpectedly rejected. Most of literatures have proved the otherwise, but some literatures confirmed with the result that the direction of the impact on trust might be depends on circumstances. Moreover, while the online nature of the research and time constraints limited the research, the research provides insights to managers, particularly in comprehending the effective use of curators to increase users’ trust in the automatic recommendation systems.

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