AI recommendations
: impact of product type and number of options on users’ purchase intention and attitude toward the brand

  • Francisca Ribeiro (Student)

Student thesis: Master's Thesis


In a time of ever-growing options and information available, the introduction of AI recommender systems in brands’ websites emerged as a guiding tool for users’ decision-making process. While the complexity in consumer information is managed, still little is known about the impact of product type and the number of options of the recommendation in the users’ purchase intention and attitude toward the brand. To uncover the design that leads to a more successful AI recommendation, an experiment was ran with the manipulation of product type and number of alternatives provided. The results confirm the better adequacy of AI recommender systems for utilitarian products, in comparison to hedonic products, regarding purchase intention. As for the number of options, there is no one-size-fits-all rule for all products. However, for utilitarian products, this study suggests that providing larger choice sets of recommendations is beneficial to attain higher purchase intention in the website shops and to generate more favorable attitudes toward the brand. Both the familiarity and the expertise with AI recommender systems showed some positive influence on the findings above, however, much remains to be explored in this topic to understand how to boost the levels of purchase intention and attitude toward the brand.
Date of Award22 Jan 2024
Original languageEnglish
Awarding Institution
  • Universidade Católica Portuguesa
SupervisorCristina Soares Pacheco Mendonça (Supervisor)


  • AI recommender systems
  • Choice overload
  • Hedonic vs. utilitarian
  • Number of options


  • Mestrado em Gestão e Administração de Empresas

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