The impact of climate change on visitor destination selection: A case study of the Central Drakensberg Region in KwaZulu-Natal

Many variables influence visitors’ destination choices, for example, affordability, attractions, health and safety, and expectancies. Amongst the indirect influences in destination choice by tourists, climate change is perhaps the greatest factor because of its negative impact on the ecological landscape of tourist destinations. Using the Central Drakensberg Region (CDR) as a case study, this article seeks to investigate the influence of climate change on visitors’ destination choices. A quantitative descriptive survey was conducted on a sample of n347 participants who were selected using purposive and convenience sampling procedures under the auspices of non-probability. The statistical analyses were performed using the latest edition of the Statistical Package for the Social Sciences (Version 25.0). Based on the study’s results, climate change was found to be a key influence on tourists’ decision-making, behaviour and spending habits at tourist destination like the Central Drakensberg Area. The most significant climatic parameter for tourists was determined to be pleasant and warm temperatures, as well as the summer season. Furthermore, owing to the current climate change circumstances, visitors were found to be less likely to return or recommend future visits to the region. To that end, tourism officials in the CDR should swiftly implement adaptation measures to counter the effects, and explore alternatives such as soft tourism and non-climate-dependent activities to accommodate visitors year-around. Further research is recommended to establish the extent to which socio-demographic characteristics influence destination choice in the area, as well as to ascertain the current state of climate change impacts.

SUSTAINABILITY FACTORS INFLUENCING TOURISTS’ DESTINATION CHOICE DURING THE COVID-19 PANDEMIC

As recent studies show, tourists increasingly favour hotels and other tourism businesses that adopt more sustainable practices. This trend has arguably been intensified during the COVID-19 pandemic. Indeed, due to the restrictions regarding crowded places and closed spaces, a lot of tourists have (re)discovered nature. In this context, the present study aims to analyse tourists’ evaluation of sustainability criteria and willingness to pay for items when choosing a destination during the COVID-19 pandemic. To this end, previously validated scales for sustainability criteria and willingness to pay (for a sustainable destination) were tested, through a confirmatory approach, in the context of the COVID-19 pandemic. In this context, data was collected through a survey questionnaire (n=567) with Portuguese tourists and subjected to a Confirmatory Factor Analysis (CFA). The findings show that the factors hold their dimensionality, convergent validity, and reliability in the context of Portuguese tourists travelling during the COVID-19 pandemic. Moreover, a newly proposed item, related to the importance given to the inclusion of local producers in the tourism industry’s supply chain, was validated. The findings also show that, especially when it comes to willingness to pay, factors with a direct effect on tourists’ experience are significantly more valued. Additionally, the results point to a slightly different outlook on sustainability criteria by Portuguese tourists, which is likely related to the context of the pandemic. Finally, the findings provide useful insights for destination managers aiming to attract tourists with a more sustainable behaviour.

Investigating Tourists’ Willingness to Walk (WTW) to Attractions within Scenic Areas: A Case Study of Tongli Ancient Town, China

This paper aims to quantify tourists’ willingness to walk (WTW) in the intra-destination choice in pedestrian scenic areas. The case study presented is the Tongli Ancient Town (Jiangsu Province, China), which has a significant number of heritage sites, but tourism management has been weak. The main objective was achieved by surveying sequential destination choices in the site, with a total of 272 interviewed tourists. A Multi-Stop Behavior Model (MBM) was constructed to identify the factors that influence tourists’ intra-destination choice and willingness to walk (WTW). On the whole, the evidence showed that tourists prefer core-area attractions to peripheral attractions. Walking distance is the most important variable in tourists’ attraction choice. Moreover, WTWs of tourist segments showed both similarities and disparities, inspiring more pertinent strategies in line with tourists’ preferences. Policy and management implications are drawn based on the empirical findings and their effects are predicted using Monte Carlo (MC) simulation.

Exploring Destination Choice Intention by Using the Tourism Photographic: From the Perspectives of Visual Esthetic Processing

This study aims to deepen the understanding of tourism photography by developing and testing a theoretical model that accounts for the relationships between visual esthetics and destination choice intention of tourists. Thus, we sought to use a stimulus-organism-response (S-O-R) paradigm to predict destination choice intention, which includes three variables related to visual esthetics: first impression, visual appeal, and esthetic emotion. We used the combination of self-reported and eye movement data to examine the cognitive processes of tourists that visual esthetic formation. We found that compared to the built environment and amateur esthetic images, natural environment and professional esthetic images can get (1) higher visual appeal, (2) better first impression, and (3) higher visual processing fluency (or less cognitive effort) and positive esthetic emotions. Furthermore, visual appeal, first impression, and esthetic emotion deriving from environment esthetics and photograph esthetics have a positive impact on destination choice intention. This study has practical implications for destination planning and management.

What Drives the Eco-Friendly Tourist Destination Choice? The Indian Perspective

Although eco-friendly (pro-environmental) behaviour in tourism has attracted interest among practitioners and scholars, little is known about the influence of these attitudes on the choice of eco-friendly destinations, especially in the context of emerging tourist markets such as India. Thus, this article aims to verify a model of the relationships between attitudes towards the environment and eco-friendly tourism, social and personal norms regarding environmentally responsible behaviour, perceived behavioural control, behavioural intentions regarding eco-friendly destinations and the willingness to pay for such trips using the theory of planned behaviour. The study used an online survey conducted with 598 Indians. The relationships between the variables were analysed using PLS-PM. The most important results indicated that (1) there are significant relationships between the attitude towards the environment, the attitude towards an eco-friendly destination, social and personal norms and behavioural control and intentions regarding travelling to eco-destinations and (2) well-educated young Indian consumers expressed a positive attitude towards eco-friendly destinations; however, there was only a very weak relationship between this attitude and willingness to pay more for trips to them. These findings are valuable for pro-environmental planning and the growing green market/economy, as well as for the discussion on the future of pro-environmental tourism development.

Forecasting Passenger Flow Distribution on Holidays for Urban Rail Transit Based on Destination Choice Behavior Analysis

Passenger travel flows of urban rail transit during holidays usually show distinct characteristics different from normal days. To ensure efficient operation management, it is essential to accurately predict the distribution of holiday passenger flow. Based on Automatic Fare Collection (AFC) data, this paper explores the passengers’ destination choice differences between normal days and holidays, as well as one-way tickets and public transportation cards, which provides support for variable selection in modeling. Then, a forecasting model of holiday travel distribution is proposed, in which the destination choice model is established for representing local and nonlocal passengers. Meanwhile, explanatory variables such as land matching degree, scenic spot dummy, and level of service variables are introduced to deal with the particularity of holiday passengers’ travel behavior. The parameters calibrated by the improved weighted exogenous sampling maximum likelihood (WESML) method are applied to predict passenger flow distribution in different holiday cases with annual changes in the metro network, using the data collected from Guangzhou Metro, China. The results show that the proposed model is valid and performs better than the other comparable models in terms of forecasting accuracy. The proposed model has the capability to provide a more universal and accurate passenger flow distribution prediction method for urban rail transit in different holiday scenarios with network changes.

Trends in Destination Choice in Tourism Research: A 25-year Bibliometric Review

Evolution of family leisure time have increased the demand for attractive destinations. In tourism, destination choice (DC) is considered a critical, complex and contextual decision. This, first of its kind, comprehensive, mix method bibliometric analysis of 627 papers from Scopus database spanning 25 years, is aimed to identify and review the most influential DC literature. It shows that DC is an interdisciplinary and evolving subject. Five themes, namely DC conceptualization, DC decision-making, DC modelling, DC internal and external factors are prevalent. DC conceptualization is explained by modified TPB and other models. DC decision-making process is hierarchical, sequential, multistage and varies across psychological, demographic and social profiles. Multiple choice, econometric and utility maximization models along with push–pull internal and external motivational factors have been extensively published. Growing academic interest in DC is evident from a threefold jump in average number of articles post-2007, 2500+ citations in 2019 out of 21,664 across 25 years, a growing trend of cross-country collaboration, rising number of publications in mainstream journals and 9 out of top 10 authors getting published in the short period of 2008–2016. Future research themes include empirical investigations of models, non-linear multifaceted decision-making and the pandemic’s impact on motivational factors.