Value-Based Profiles of Visitors to a World Heritage Site: The Case of Suwon Hwaseong Fortress (in South Korea)

Abstract

The aim of this study is to evaluate the place value of Suwon Hwaseong Fortress in Korea, a mountain fortress located in natural resources with UNESCO World Heritage Site status, in order to classify visitors according to place value and to establish marketing strategies based on the characteristics of each profile. In particular, for sustainable cultural heritage development, visitors were asked to evaluate the place value of the site from various perspectives, through a presentation of government policies and business based on both the world heritage value and the inherent attractiveness of the site. Utilizing a person-centered approach, a latent profile analysis (LPA) was applied to a sample of visitors to Hwaseong Fortress (N = 656), with visitors classified by place value into four profiles: Outing Seekers (OS), Tourism Seekers (TS), Heritage Seekers (HS), and Serious Travel Seekers (SS). These profiles differed in relation to distance from the study setting from travelers’ residence, recognition of the fortress as a World Heritage site, and the degree to which the World Heritage site status influenced the decision to visit. The profiles also showed differences in visit satisfaction and intent to revisit. This study contributes a better understanding of visitors’ evaluated value of heritage sites and corresponding behaviors, in order to provide sustainable management for the heritage tourism market.

Latent Profiles of Anxious Children and Their Differences in Aggressive Behavior

“…In this sense, the model with the lowest BIC and AIC values was considered to have the greatest explanatory power. In addition, entropy values closer to 1 report a greater precision of the latent profile classification [39]. Once the optimal model was identified according to statistical data (i.e., BIC, AIC, entropy, and the p-value), the profiles of that model were examined in comparison with the remaining solutions obtained.…”

School anxiety profiles in Spanish adolescents and their differences in psychopathological symptoms

“…These z scores were interpreted according to the following criteria: z scores below -.5 indicated low levels of school anxiety, z scores between -.5 and .5 showed moderate levels of school anxiety, and z scores over .5 indicated high levels of school anxiety [30]. The optimal profile solution that best fitted to data was determined considering several fit indices [31]: the lowest values of the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC); entropy values close to 1; and p-values below to .05 for the Vuong-Lo-Mendell-Rubin Likelihood-Ratio Test (LRT) and the Bootstrap Likelihood Ratio Test (BLRT). In addition, the size of the profiles was also considered to choose the best model, since each profile should be represented by at least 1% of the sample [32].…”

Understanding school refusal behavior in adolescence: Risk profiles and attributional style for academic results

“…The standardized z scores were interpreted as follows: z scores below -.5 suggested low levels of SRB, between -.5 and .5 indicated moderate levels of SRB, and over .5 showed high levels of SRB (Sanmartín et al, 2018). The best profile solution was selected examining the theoretical interpretability of each model and considering the following fit indeces (Song & Kim, 2019): the lowest values of the Bayesian Information Criteria (BIC) and the Akaike Information Criteria (AIC); the Vuong-Lo-Mendell-Rubin Likelihood-Ratio Test (LRT) and the Bootstrap Likelihood Ratio Test (BLRT) p-values below to .05; and entropy scores close to 1. Moreover, each subgroup of participants should contain at least 1% of the sample (Tein et al, 2013).…”