A Study on Enhancing Recommendation Systems for Experience Goods

Abstract: This study examines the design and trustworthiness factors of recommendation systems forexperience goods in the e-commerce industry. Experience goods are products that involvesensory experiences and pose challenges for consumers to assess and select online. Theresearch adopts a mixed method approach, combining exploratory and interpretive researchmethods to gain insights into users' interpretations and meanings attached to their experiences.The methodology includes analyzing publications, conducting a survey, and objectivelydocumenting recommendation systems in the alpine industry. The survey collects opinions fromparticipants who have used various recommendation systems, covering aspects such as usermodel, item model, recommendation algorithm, user interface, evaluation, and trustworthiness.A thematic analysis is employed to identify patterns and meaningful themes in the data. Thefindings emphasize the importance of understanding user preferences, balancingrecommendations, improving accuracy, enhancing interface usability, incorporating feedback,and addressing recommendation diversity to enhance trustworthiness. A hybrid filteringapproach with feature-based systems and integrated behavior-based techniques is identified aseffective. While the survey's convenience sampling and limited sample size may limitgeneralizability, the findings provide insights for designing effective recommendation systems forexperience goods in e-commerce. By considering the strengths and limitations of differenttechniques, vendors can create systems that assist customers in purchasing these uniqueproducts. However, recommendation systems should be viewed as a valuable tool rather thanthe sole determinant in purchase decisions for alpine equipment. Further research with a largerand more diverse sample is recommended to validate the findings and improve generalizability.