Service Recommender System Based on Emotional Features and Social Interactions

Abstract

Purpose-Most existing recommendation systems or technologies are functional-oriented. Recommending services, nevertheless, requires the consideration of service experiences perceived by customers being individually unique and emphasizing the emotional experiences and the co-created value-in-use. This paper aims to present a new recommender system to capture customer emotional needs and address social interactions among service stakeholders. Design/methodology/approach-This paper presents a color imagery-based recommender system (CIRS) capable of capturing customer emotional needs and addressing social interactions among service stakeholders that can collectively co-create the individual value-in-use and beneficial outcomes for customers. Based on the Color Image Scale, the recommender system uses the color imagery format as the uniform representation of customers’ psychological expectations, service providers and the service system, to facilitate the scoring and ranking of recommendations. Findings-This study uses an application context of destination tourism to demonstrate and justify the recommender system’s attempted contributions preliminarily. That is, CIRS can recommend destinations and tour services that meet tourists’ emotional needs with a satisfactory precision of 70 per cent. CIRS can also make stakeholders’ image models evolve over time considering the dynamic interactions among stakeholders. CIRS can also help lesser-known tourism destinations be discovered by tourists who can be emotionally satisfied. Originality/value-CIRS uses the color imagery as the uniform representation for customers’ expectations, service providers (e.g. small and medium enterprises) and service system (e.g. tourism destinations), considering the continued interactions among the service stakeholders that collectively co-create the individual value-in-use and beneficial outcomes for each customer.