The Influence of Consumers' Trust and Cognitive Absorption on Behavioural Intentions to Reuse Recommender Systems

The Influence of Consumers' Trust and Cognitive Absorption on Behavioural Intentions to Reuse Recommender Systems

There has been a dramatic increase in the quantity and variety of product information available online. This has intensified consumers' perceptions of information overload, making it harder for online shoppers to pick between numerous online products and services. Consequently, e-vendors are progressively outfitting their e-commerce sites with different product recommender systems to assist customers in dealing with this difficulty. Recommender systems (RSs) have gained popularity to assist online shoppers in their purchasing decisions. Recommender systems can provide highly tailored product recommendations, and assist in discovering, comparing, and assessing product information. However, many online shoppers may not be making their online purchasing decisions using a recommender system because they do not yet have trust in them, as evidenced by the current Amazon sales percentage based on recommender systems usage. Regardless of how useful recommender systems are, understanding whether consumers accept and reuse them is crucial. This is a critical yet under-researched topic in existing studies on recommender systems. Using a three-study quantitative research method that employs an online survey, this research explores post-adoption factors influencing the reuse intentions of consumers in relation to recommender systems. In particular, the main research question of this research is 'How do flow experience, trusting beliefs, and perceived usefulness of recommender systems influence consumers' behavioural intentions to reuse recommender systems?

This research proposes three unique research models. The research draws on the ResQue model, the technology acceptance model, trust literature, flow theory and cognitive absorption theory to describe the causal linkages between the determinants of consumers' behavioural intentions to reuse recommender systems. Six important post-adoption factors, trusting beliefs, perceived usefulness, cognitive absorption, focused immersion, temporal dissociation and curiosity were linked to consumers' behavioural intentions to reuse recommender systems.

The primary data for this study was gathered using a questionnaire that represents the research constructs. The online survey was administered by an established research firm employing an Australian consumer panel. A sample of 452 Amazon users who had used recommender systems for at least six months was used to evaluate the predicted correlations between the constructs. Since this is a three-study quantitative research with a deductive approach, it applies Partial Least Squares-Structural Equation Modelling (PLS-SEM) to validate and corroborate the research models by evaluating the hypothesised relationships.

The findings of this research have revealed that trusting beliefs, perceived usefulness, cognitive absorption, focused immersion, and curiosity were linked to consumers' behavioural intentions to reuse recommender systems. The results also confirmed that trusting beliefs and cognitive absorptions mediate consumers' behavioural intentions to reuse recommender systems. Interestingly, in contrast to earlier findings, the relationship between the constructs was statistically insignificant in search and experience products. The findings of this research also confirm that gender serves as a moderator on consumers' behavioural intentions to reuse RSs.

Theoretically, the research findings contribute to and expand upon the body of knowledge built by previous research on the user-centric evaluation of recommender systems. This research advances our understanding of the factors influencing customers' behavioural intentions to reuse recommender systems. This research is one of the very few to examine the role of cognitive absorption in the context of recommender systems. This research is the first to examine unique antecedents of consumer behavioural intentions to reuse recommender systems such as focused immersion, curiosity and heightened enjoyment. For practitioners, the findings emphasise the necessity of tailoring the design of recommender systems such that they are useful, convenient, trustworthy, and improve the holistic consumer experience.

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