Analyzing the Influence of Visitor Types on Location Choices and Revisit Intentions in Urban Heritage Destinations

Sevim Sezi Karayazı (Corresponding author), Gamze Z. Dane, Theo A. Arentze

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Abstract

Understanding visitors’ spatial choice behavior is important in developing effective policies to counteract overcrowdedness in attractive urban heritage areas. This research presents a comprehensive analysis of visitor location choice behavior, aiming to address two primary objectives. First, this paper investigates the relationship between visitor segments and the choice of particular Points of Interest (POIs). Second, this paper explores the impacts of visitors’ experiences and visitor segments on their revisit intentions. We used a sample of 320 visitors who had been to Amsterdam within the last five years to collect data about their location choice behavior and intention to revisit after a recent visit to the city. Combining the revealed choices and intentions of pre-defined visitor segments obtained from a stated choice experiment, association rules are extracted to reveal differences in the patterns of behaviors related to the segment. The findings identify associations between various POIs, including museums such as the Rijksmuseum and Madame Tussauds, and visitor classes, which include “cultural attraction seekers”, “selective sightseers”, and “city-life lovers”. Furthermore, binary logistic regression analysis reveals that affective experiences, such as feelings of comfort, happiness, and annoyance, have a significant influence on visitors’ intentions to revisit the destination in the future. This research found that “cultural attraction seekers” and “selective sightseers” display a higher likelihood of considering a return visit to the city.
Original languageEnglish
Article number115
Number of pages23
JournalISPRS International Journal of Geo-Information
Volume13
Issue number4
Early online date28 Mar 2024
DOIs
Publication statusPublished - Apr 2024

Funding

This research was funded by The Republic of Turkiye, Ministry of National Education, Directorate General for Higher and Overseas Education.

Keywords

  • Apriori algorithm
  • association rule mining
  • density map
  • location choice behavior
  • revisit intention
  • urban heritage tourism
  • visitor segmentation

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