Electronic word-of-mouth (eWOM) is regarded as crucial in business development. Given the intangible nature of tourism and hospitality products, potential customers find it hard to assess them before making purchase. Accordingly, online customer reviews and management responses have influential roles in their decision-making process. While a plethora of previous research focused on customer reviews, scholarly attention on how luxury hotels respond to the reviews was scant. Using content analysis, this study examines the management response characteristics of 35 luxury hotels and response style of 7 luxury chain hotels in Hong Kong. Their response characteristics including response frequency, responder’s job position, and timeliness of response were generally similar. The response style and tone (professional and conversational tones) vary with hotels even they are in the same hotel group. Implications on practice of management responses are offered for luxury hotel operators.
Climbing is a popular sport for active tourists and recreational sportsmen. Alpine climbing areas, such as the Alps, can attract tourists from all over the world. Various websites, mobile applications, and books are used by climbers to obtain information on important aspects of the available climbing routes, including their properties, location, and especially their difficulty. Considering this large amount of information and options, it is in reality difficult for climbers to properly select which routes to climb. Hence, we propose recommendation technologies aimed at supporting climbers in this decision task. The developed system prototype constructs a climber’s profile with preferences derived from climber’s logbook data collected by a mobile app. Then, the system can recommend suitable crags and climbing routes within the selected crags. The designed interface and the basic computational models for such a system prototype are presented. The proposed technology aims at complementing existing electronic climbing guidebooks and providing decision support to climbers.
The use of robotics and artificial intelligence have created a shift in the ways the service-based hospitality and tourism industry can fulfill the needs and wants of consumers that were earlier fulfilled only by humans. Robots have added the automation and self-service experience that play a vital role in the improvements of efficiency, speed, and the overall experience for the guests using technology. While there are many benefits of using robots in the industry, there are also risks associated with the excessive usage of robots on guest experience. As a result of the pros and cons on the topic, it is very important to gather data and analyze the results to further investigate and understand what the outcomes will be for the industry, its employees, and its customers. The purpose of this study is to examine the perceptions of the use of robots in the hotels as perceived by hotel guests who used a service robot and who did not. A self-administered survey was developed, and 939 usable responses were collected from hotel guests. Factor analysis showed that five factors emerged in the study: Advantages, Attitudes, Disadvantages, Pandemic Related, and Fear. Guests recognize the opportunities that service robots are bringing to their experience while voicing their concerns and fears about the use of them. Findings also showed that there are significant differences between users and non-users.
This short paper summarizes the first research stage for applying deep learning techniques to capture human-wildlife interactions in national parks from crowd-sourced data. The results from objection detection, image captioning, and distance calculation are reported. We were able to categorize animal types, summarize visitor behaviors in the pictures, and calculate distances between visitors and animals with different levels of accuracy. Future development will focus on getting more training data and field experiments to collect ground truth on animal types and distances to animals. More in-depth manual coding is needed to categorize visitor behavior into acceptable and unacceptable ones.
The central government and local governments of the South Korea execute a project to build smart tourism city for tourism and urban development. However, little study has shed light on the details of smart tourism city project. To approach the concept of smart tourism city and understand the phenomenon of smart tourism city construction, this study conducts a case study. Incheon is the first city in which implementing the smart tourism city creation project. We apply the metaverse concept to check how Incheon implements a smart tourism city. Specifically, the metaverse concept applied tourism service operated by Incheon is divided into real based and virtual based (AR Incheon and Incheoncraft). Along with an introduction to the case, how the concept of metaverse supports the creation of a smart tourism city is discussed. This is an early-stage study that explores the phenomenon by considering the relationship between the smart tourism and metaverse.
