Effects of product portfolios and recommendation timing in the efficiency of personalized recommendation

Abstract

Personalized recommendation has important implications in raising online shopping efficiency and increasing product sales. There has been wide interest in finding ways to provide more efficient personalized recommendations. Most existing studies focus on how to improve the accuracy and efficiency of the recommendation algorithms or are more concerned on ways to reduce perceived risks and thus increase consumer satisfaction. Unlike these studies, our study begins from the decision‐making process of consumers, using consumers' two‐stage decision‐making system and preference inconsistency theory as a basis, to reveal the mechanisms involved in consumers' acceptance of recommendations. This paper analyzes the effect of personalized recommendations from two angles, recommendation timing and product portfolio, tries to point out differences in consumer preferences between similar products and related products, and verifies that consumers demand diversity in the recommended content. The study analyzes differences in the acceptance of personalized recommendations between practical products and hedonic products and discovers that recommendations of hedonic products are more effective than that of practical products. Based on the research earlier, the study provides suggestions on how to better plan and operate a personalized recommendation system. Copyright © 2016 John Wiley & Sons, Ltd.

A Influência Do Funcionamento E Da Comercialização Dos Produtos Da Central De Abastecimento Do Pará

“…2.1 O processo de tomada de decisão de compras em dois estágios e a teoria da inconsistência preferencial Yan et al (2016) relatam que, no Modelo de Tomada de Decisão em Dois Estágios, as preferências dos consumidores por produtos recomendados variam em diferentes estágios da tomada de decisão e tanto o portfólio de produtos recomendados, quanto o momento da recomendação devem ser adequados às preferências dos consumidores ou poderão diminuir a satisfação destes e a eficiência da comunicação.…”

“…No tocante ao empoderamento, o seu estudo tem crescido na literatura de marketing e em pesquisas sobre consumo ao longo das últimas décadas (PAPAOIKONOMOU; ALARCÓN, 2016;PRENTICE;HAN;LI, 2016). Assim, esta pesquisa visa contribuir para os profissionais de marketing na compreensão do empoderamento como uma experiência subjetiva do consumidor que pode ampliar sensações de liberdade e controle a partir de escolhas de produtos e serviços (FUCHS;SCHREIER, 2010;YUKSEL, 2014).…”

Online decision aids: the role of decision-making styles and decision-making stages

“…Given that online shopping environment is distinctively different from traditional shopping channels, consumers learn and adapt during the shopping process, which impacts the search process, and eventually impacting consumers' choice (Senecal et al, 2005). Therefore, consumers tend to reduce choice complexity by varying the amount of information processing in two stages of choice formation (H€ aubl and Trifts, 2000;Xiao and Benbasat, 2007;Yan et al, 2016). Consumers might not state their preferences initially in the choice process and construct them later contextually (Simonson and Tversky, 1992;Slovic, 1995).…”

Consumer acceptance of social recommender systems in India

“…Algorithms form the basis of recommender systems, which popularly are content-based, collaborative and hybrid (Yan et al , 2016; Li et al , 2013). Collaborative recommender system suggests products based on preference similarities of consumers (Arazy et al , 2010), content-based recommender system profiles a user's browsing history along with product features to find similar products (Choi et al , 2011) and hybrid recommender system combines both these approaches to increase recommendation performance (Choi et al , 2011).…”