Many people reserve and purchase travel products via internet. Travelers refer to them to gain more accurate information about specific places, the amount of time they will spend there, and so on. This paper focuses on such worldwide travel site, “A,” and selects 16 hotels, which span two approaches: one from luxurious to modest, and the other, on the basis of geography, from Central Tokyo to local areas. These hotels are classified into four quadrants, and data from site A is collected on the basis of 19,224 reviews. Each data point is composed of each contributor’s review text, assessment scores, and the date on which the review was published. Data points are used to analyze three things: (1) Words extracted from reviews, which are grouped according to a topic model to extract characteristics about a hotel; (2) Hotel rankings, topics, and appearance words per region; and (3) the relationships between topics and evaluations, which are quantified to consider future guidelines and services. Through these analyses, we discuss the relationship between the evaluation of a hotel and its reviews on the basis of regions and hotel rankings.
The number of bike-sharing services has rapidly increased in many cities worldwide. One of the main challenges of the bike-sharing system operation costs is allocating enough bikes and parking space. This paper presents a model for solving the bike-sharing relocation problem. The artificial bee colony (ABC) algorithm is an efficient approach, but it is still insufficient for the selection strategy. ABC has been adopted in various problems to improve the performance of various systems. This research proposed a modified ABC algorithm in a neighbor solution to enhance the solution performance, namely guided local search (GLS), to apply to the design route for transportation while truck relocation bikes each station in the bike-sharing system. Computational experiments were performed to find out the best modeling solution in the case. The implementations were experimental for the same data instances, which made it possible to compare the performance algorithms so as to solve the bike-sharing relocation problem of the pickup and drop off. The results showed that the GLS-ABC method can be a better solution than the original one. The statistically significant p-value of the mean objective value of the different algorithms was smaller than 0.05. Thus, the impact of minimizing the route tour cost in solving the bike-sharing relocation problem.
With support from MPI Japan, we have collected survey responses from active meeting planners in Japan, which revealed their profiles and their perception on priorities regarding meeting site selection criteria. Meeting Professionals International (MPI) is one of the largest meeting planner and event planner industry association worldwide. MPI Japan Chapter was established in 1995. In the results of the questionnaire survey, majority of members are between ages of 35 and 64, and surprisingly overwhelming majority are male. Soft areas such as service and management quality of the venue are deemed more important in their selection of meeting venues, besides ease of access of the venue. The result of our analyses highlights importance of decomposition of MICE into sub-categories to cater to the different needs and perceptions of relative importance of the same issues by meeting planners in Japan.
This study uses “Mobile Kukan Toukei™” (MOBILE SPATIAL STATISTICS) to analyze the impact of the novel coronavirus (COVID-19) infection on people's movements in tourist destinations in Kansai region (mainly Kyoto). Mobile Kukan Toukei is statistical population data created by the operational data of mobile phone networks. Comparison of the data before and after the spread of the disease showed that the impact was remarkable in many areas in April 2020. Urban areas such as Kyoto Station and Osaka Station showed relatively more robust recovery. However, several tourist areas could not bounce back despite the “GoTo” campaign by the Japanese government.
As the outbreak of the novel coronavirus disease caused great damage on inbound tourism in Japan, developing an effective promotion way to revitalize the inbound tourism is an important issue. Since many inbound tourists to Japan have expected healing and relaxing for their travels, motivating prospective tourists who look for these comforts is a key to increase the number of inbound tourists for the future. In this study, the authors conducted an experiment to examine whether photos (still image) or videos (moving image) of scenery are more effective to stimulate tourist’s interests to visit Japan with an approach utilizing neuromarketing. In the experiment we recorded the brain activity of subjects, which is monitored as the amount of cerebral blood flow change by using near-infrared spectroscopy (NIRS) and obtained their impression evaluation for each scenery image by using Semantic Differential (SD) method. The result of the experiment showed that the amount of cerebral blood flow change for both still images and moving images was similar. Moreover, the result of SD measurement for both still and moving images was also similar. Additionally, it illustrated that the mean values of SD adjectives related to healing were higher than other adjectives. These results suggest that the effectiveness of using photos or videos of scenery for promoting tourism on SNS or website does not have a big difference. In addition, the photos or videos which often give relaxing feelings can be effective to motivate prospective tourists who seek a relaxing time in Japan.
The population of elderly people aged 70 and over is expected to continue increasing until around the year 2048 in Japan, and this population group is considered to be important for the domestic travel market. However, the number of overnight trips of the elderly is lower than the average. The main reasons for not going on overnight trips for the entire population are economic limitations and time constraints. However, health reasons are statistically significantly higher in people aged 70 years and older. The authors are carrying out research on travel promotion by deriving tourism activity ability. We define it as the ability to enjoy sightseeing without feeling fatigue from the previous day. In this study, monthly activities of 21 Japanese people aged 65 to 81 years old were monitored. Then, the relationship between the number of steps and the walking ability was analysed. As a result, four male subjects and one female subject reached the recommended target value of daily number of steps specified by Health Japan 21 (second term). There was a statistically significant negative correlation between age and step length. However, no statistically significant correlation was observed between average daily number of steps and walking ability.
Small island destinations with populations of less than one million, typically rely on tourism for economic development and employment generation. Monitoring resident attitudes toward tourism is critical to ensure that government, private sector, and other stakeholders are aware of the perceptions held by residents about the tourism industry and its effects on their quality of life. This paper is a case study of the most recent survey of resident attitudes towards tourism on the Micronesian island of Guam and the use of both quantitative and qualitative methods to measure these perceptions. Results of the survey will be discussed as well as recommendations for destination stakeholders in small islands and rural destinations to prepare for future resident attitude surveys. Special considerations for these less-populated destinations in the post-COVID world will also be examined to ensure that resident perceptions are monitored as a key to maintaining a well-managed tourism destination.
Nowadays, it is thought important to make a decision based on data to use limited resources effectively. Strollers, one of the main targets of sightseeing places for children, are believed to be important for such places, but ticket sales or technology recently utilized are not suitable to grasp the movements of the strollers, therefore, this research focused on strollers through the use of a camera and artificial intelligence. We, first, recorded an entrance, and fine-tuned prepared models to create original object detection artificial intelligence. Then, we counted the number of entering strollers, and analyzed the entering patterns. We discovered several patterns, and suggest that there is a difference between strollers in the weekdays and weekends. Lastly, for future prospects, we mention two things, a real-time counting system with GPU installed small computers, and simultaneous counting of strollers’ companions.
Long hours of work, including night shifts, for taxi drivers are one of the primal risk factors for health and well-being. Many studies indicate that long working hours are associated with the development and exacerbation of cerebrovascular and cardiovascular diseases, and taxi drivers work longer hours than drivers of other transport services. Taxi companies have been emphasizing measures to promote napping as a way to reduce fatigue associated with adverse effects on bodily functions. This paper aimed to examine the influence of naps on fatigue recovery through a questionnaire survey of 126 taxi drivers engaged in night work regarding: (1) the frequency of reported complaints of drowsiness and fatigue while driving, (2) the status and effects of napping in the vehicle during night work, and (3) physical fatigue related to the musculo-skeletal system from a constrained driving posture. The results revealed that it is difficult to take a nap due to the high demand to pick up passengers. The time series variation of drowsiness and fatigue during driving, and the localized physical fatigue to parts of the body related to driving were also discussed. Improvement of resting schedules, including a nap time to reduce task conflicts physically and mentally, was emphasized.