Informing destination recommender systems design and evaluation through quantitative research

Abstract

Informing destination recommender systems design and evaluation through quantitative research AbstractPurpose -Destination recommender systems need to become truly human-centric in their design and functionality. This requires a profound understanding of human interactions with technology as well as human behavior related to information search and decision-making in the context of travel and tourism. This paper seeks to review relevant theories that can support the development and evaluation of destination recommender systems and to discuss how quantitative research can inform such theory building and testing. Design/methodology/approach -Based on a review of information search and decision-making literatures, a framework for the development of destination recommender systems is proposed and the implications for the design and evaluation of human-centric recommender systems are discussed. Findings -A variety of factors that influence the information search and processing strategies that influence interactions with a destination recommender system are identified. This reveals a great need for data-driven models to inform recommender system processes. Originality/value -The proposed framework provides a basis for future research and development in the area of destination recommender systems. The paper concludes that the success of a specific destination recommender system will depend largely on its ability to anticipate and respond creatively to transformations in the personal and situational needs of its users. Such system intelligence needs to be based on empirical data analyzed with sophisticated quantitative methods. The importance of recommender systems in tourism marketing is also discussed. Approach: Based upon a review of information search and decision-making literatures, a framework for the development of destination recommender systems is proposed and the implications for the design and evaluation of human-centric recommender systems are discussed.Findings: A variety of factors that influence the information search and processing strategies that influence interactions with a destination recommender system are identified. This reveals a great need for data-driven models to inform recommender system processes.Originality/Value: The proposed framework provides a basis for future research and development in the area of destination recommender systems. The paper concludes that the success of a specific destination recommender system will depend largely on its ability to anticipate and creatively respond to transformations in the personal and situational needs of its users. Such system intelligence needs to be based on empirical data analyzed with sophisticated quantitative methods. The importance of recommender systems in tourism marketing is also discussed.

Spatiotemporal Contingencies in Tourists’ Intradiurnal Mobility Patterns

“…This contribution, beyond adding to the theoretical knowledge, also holds practical implications for design and marketing efforts. For example, it answers the need for a better understanding of the behavioral basis of tourism, as identified within the literature discussing the application of information technologies to assist and guide tourists during their visit (Gretzel 2011; Gretzel, Hwang, and Fesenmaier 2012). This discussion stresses the decision-making context as a critical factor in the design of mobile environments for tourists (Lamsfus et al 2011, 2012).…”

A New Measure of the Quality of Tourism Product

“…Access to activities is key. There are many activities that are quite attractive, but the difficulties associated with travel are so many that they make tourists give up (Gretzel, Hwang & Fesenmaier, 2012;Pearce & Schänzel, 2013).…”

Assessing language discrepancies between travelers and online travel recommendation systems: Application of the Jaccard distance score to web data mining

“…For example, the consumer styles inventory has been applied to comprehend travel decision making styles in a way to envisage different information sources and contents travelers searched as well as attributes of the destinations they preferred (Zin et al, 2003). Gretzel et al, (2012) proposed a theoretical framework of destination recommender systems, suggesting the design components should be responsive to travelers' needs in terms of personal characteristics of the travelers (e.g., demographics and personality), situational needs and constraints (e.g., travel party and lengths of stay) and aspects of the decision-making process (e.g., the specificity of the choice task and decision frames). The focus on the traveler as the user of the system is highlighted by anticipating user needs and offering recommended alternatives according to specific consumption contexts (Buhalis and Amaranggana, 2015).…”

“…At present, the continuous evolution of information technology allows CVB websites to adopt recommender systems that can simplify the decision-making process for travelers (Fesenmaier, Wöber, and Werthner, 2006). This system enables travelers to lessen search costs and cognitive efforts by identifying alternatives that meet the specific needs of online users and by offering information in a personalized way (Gretzel, Hwang, and Fesenmaier, 2012;Kabassi, 2010; Wind and Rangaswamy, 2001). Accordingly, the recommender systems should be humancentric in their design and functionality.…”

“…This requires system-user interactions by understanding cognitive styles of online information seekers and adjusting the recommender system to address the needs/desires (Bauernfeind, 2003;Zins, Frew, Hitz, and O'Connor, 2003). Particularly, this research focuses on linguistic interactions between users and the system in the context of tourism (see Dann, 1996;Gretzel et al 2012). Based upon the definition of linguistic interactions referring to the way in which language appears interactions in everyday to represent cognitive process (Couper-Kuhlen and Selting, 2001), providing destination information that online travelers actually required with proper language is a cornerstone of recommendation, which facilitates smart tourism.…”