Travel Purpose Research Articles

Catchment-Area Delineation Approach Considering Travel Purposes for Station-Level Ridership Prediction Task

Station-catchment-area delineation is a key component of direct ridership models for urban rail-transport systems as it can determine the relationship between the urban-rail-transit station-level ridership and the variables within the station catchment area. The neglect of differences in the passenger-flow distribution for different travel purposes in previous studies has led to low accuracy of the obtained walk-to-station distances. Therefore, this paper proposes a station-catchment-area delineation method which is based on web map data to obtain accurate walk-to-station distances and considers differences in the distance thresholds and the ridership attraction intensity (RAI) for six travel purposes (corresponding to commercial, medical, residential, educational, administrative, and recreational land uses). In the case study, the ridership data of Xi’an Metro, the 2015 Xi’an Residential Travel Survey data, and the corresponding Gaode Map data are employed to extract passengers’ walking-distance distribution for several travel purposes to delineate the station catchment areas and build direct ridership models. Several geographically weighted regression (GWR) models are constructed to evaluate and examine the effects of the various station-catchment-area delineation methods on the model findings. The obtained results show that the proposed station-catchment-area delineation method significantly improves the ridership prediction performance compared with the traditional circular-buffer method, with the entry and exit ridership prediction accuracy improving by 3.57% and 6.65% on average, respectively. Finally, this study will guide transportation planners on how to delineate station catchment areas when constructing direct-demand models for urban rail stations.

Evaluation of potential rabies exposure among Japanese international travelers: A retrospective descriptive study.

Although Japan has been a rabies-free country for >50 years, a few cases have been reported among people traveling abroad. This study aimed to investigate animal exposure among Japanese travelers using the Japanese Registry for Infectious Diseases from Abroad (J-RIDA). In this retrospective analysis, we examined Japanese overseas travelers with animal exposure, as included the J-RIDA database, reported from October 1, 2017, to October 31, 2019, with a focus on pre-exposure prophylaxis (PrEP) administration and the animals to which the patients were exposed. Among the 322 cases included in the analysis, 19 (5.9%) patients received PrEP and 303 did not. The most common purpose of travel was a non-package tour (n = 175, 54.3%). Most trips (n = 213, 66.1%) were to a single country for <2 weeks. Most patients (n = 286, 87.9%) traveled to countries with a rabies risk. The majority of patients with and without PrEP were injured in rabies-risk countries [n = 270 (89.1%) for non-PrEP and n = 16 (84.2%) for PrEP]. Animals associated with injuries included dogs (55.0%), cats (25.5%), and monkeys (15.5%). Most patients were classified as World Health Organization Category II/III for contact with suspected rabid animals (39.5% and 44.1% for categories II and III, respectively) and had exposure within 5 days of travel. Southeast Asia (n = 180, 55.9%) was the most common region in which travelers were exposed to animals. Japanese overseas travelers had contact with animals that could possibly transmit the rabies virus, even on short trips. Promoting pre-travel consultation and increasing awareness of the potential for rabies exposure are important for prevention of rabies among Japanese international travelers.

Examining the effect of moderating variables on autonomous public van acceptance model (APVAM).

Autonomous vehicles (AVs) will soon become the primary means of transportation for millions of people. However, the introduction of these vehicles may lead to increased traffic and changes in people's travel patterns. To address this issue, one solution is to promote the use of AVs in a shared and public manner. However, the success of this approach depends on public acceptance of public AVs. If the promoters of public AVs are unaware of how people perceive this technology, it is possible that these vehicles will face failure in the market. Therefore, this paper aims to identify the factors that influence the willingness to use public AVs. To achieve this, an autonomous public van acceptance model (APVAM) was developed by adapting the unified theory of acceptance and use of technology (UTAUT2) through structural equations modeling. In this study, 824 citizens of Tehran participated in a field study and completed an online questionnaire. The research results indicated that the variable of effort expectancy indirectly affects the use of autonomous public vans (APVs), while the variables of performance expectancy, facilitating condition, hedonic motivation, and perceived PUnTrust directly affect their use. The research also found that various factors such as gender, level of education, individualism/collectivism, travel purpose, the dominant travel mode, marital status, occupation, age, household wealth, number of vehicles owned, and the price of the current vehicle of the household have a moderating effect on the APVAM. Furthermore, it was revealed that individuals who primarily use personal or public transport for their daily trips are more influenced by the perceived enjoyment of APVs in increasing their willingness to use these vehicles, compared to those whose predominant mode of travel is walking or cycling.

Estimating Cultural Tourism Flows in Romania: Empirical Approaches Based on Existing Data at Municipality Level

Abstract The purpose of this paper is to present two empirical approaches of estimating/approximating the size of cultural tourism in Romania based on existing data at municipality level. These approaches have been labelled ‘the potential supply approach’ (based on municipalities with man-made tourism resources as dominant resource) and ‘the demand approach’ (based on municipalities that register visitors in museums). Number of tourists (arrivals) in accommodation establishments was considered the benchmark statistical indicator. The analysis of Pearson correlation between number of tourists and number of visitors in museums was also included, and municipalities where this correlation is positive and statistically significant were grouped in eight clusters. The results revealed a strong concentration of tourism in big cities that are both cultural and tourism destinations as well as a correlation between tourism and culture data for 67 municipalities (out of 284). However, the precise size of cultural tourism is difficult to be quantified in the lack of any specific demand-side survey regarding travel purposes and/or activities undertaken during tourism trips and within such purposes/activities, cultural tourism to be separately identified. But, in these circumstances, the two approaches presented in this paper can outline only a maximum size of cultural tourism in the country.

ASSESSING THE IMPACT OF TRANSIT-ORIENTED DEVELOPMENT ON RESIDENTS’ QUALITY OF LIFE IN NORTHERN MALAYSIA

Transit-Oriented Development (TOD) is gaining wide acceptance by many state’s governments in Malaysia due to its potential to create a liveable neighbourhood with enhanced mobility. Therefore, this study aims to assess the impact of TOD on the residents’ quality of life in Malaysia northern states. The data for this study were gathered from a survey on 360 residents who used the Northern KTM commuter train service. Descriptive and inferential statistics including chi-square test and PLS-SEM technique was performed to analyse the data and produce the findings. The findings of this study shown that there were significant differences in travel behaviour patterns (companions, frequencies, and walking durations) with respect to respondents’ travel purposes. Moreover, it was revealed that land-use diversity and walkable design as important TOD principles that contribute to their quality of life. The findings of this research would serve as a base but critical information to direct future National Estate Development Plan.

Optimization Path of Metro Commercial Passageway Based on Computational Analysis

In this study, three key factors affecting the planning of metro commercial passageways are selected: the built environment of metro station, travel purposes of passenger flow and gate position of the station hall. The Pearson model, Logistic model and software simulation are combined to analyze passage passenger flow. In the study of metro passageways, most studies focus on the optimization of evacuation and transfer functions, with little research on metro commercial passageways. The purpose of this study is to improve the attractiveness of metro commercial passageways to passenger flow by improving the three key factors mentioned above, thereby improving the current situation of underground commerce. The analysis results show that in the built environment analysis, the four selected construction factors are highly correlated with the passenger flow, and the correlation degree is in the following order (from high to low): length of the passage, operation of the escalators, the distance from the passage exit to the bus stop and the passage width. In the passenger flow travel purpose analysis, based on the structure of passengers and the function of the surrounding land use, it can be divided into shopping, work and living purposes, and the result of model parameter comparison shows that “shopping trips” is the most significant purpose. According to the analysis of the location of the exit gates at the station concourse level, the passageway with a closer distance or linear pattern to the gate location is more attractive to the passenger flow.

From tourist motivations to buying decisions: A multilevel engagement perspective

This paper offers theoretical and practical implications regarding digital media content generated on social media networks (SMNs). However, limited research has been conducted on this topic, resulting in important knowledge gaps. To narrow this gap, this paper proposes a theoretical framework that explored an important tourist-based antecedent (involvement) and its first- (engagement levels), second- (brand love), third-tier (buying decision) consequences, respectively. Data were gathered from a sample of 722 US tourists who used SMNs for leisure travel purposes. Our findings reported that affective involvement had a strong positive relationship with the three levels of engagement. Additionally, cognitive involvement was significantly related to two engagement levels: consumption and creation. Our findings verified the positive link between the three levels of engagement and brand love. Interestingly, brand love exerted a significant positive impact on both impulse buying and cross-buying decisions. Finally, gender moderated the link between brand love and the cross-buying decision.

Impact of the COVID-19 Pandemic on Travel Behavior and Travel Mode Preferences: The Example of Bosnia and Herzegovina

This study aims to analyze the perception of travel, especially in the context of the pandemic, when the measures are alleviated, as well as the citizens’ intentions and preferences for travel methods during the COVID-19 pandemic. The purpose of the study is to investigate the impact of the COVID-19 pandemic on travel behavior and travel mode preferences in the example of the residents of Bosnia and Herzegovina. Five research questions were defined. A quantitative research approach was applied in this study. The data were collected through a questionnaire (online survey) distributed to respondents via e-mail and the social network Facebook. The convenience sample included 265 respondents. In the study, a descriptive and quantitative comparative analysis was conducted. The results show that the COVID-19 pandemic has influenced a change in travel behavior. The primary purpose of travel during and before the pandemic was social activities. The most significant change in the primary purpose of travel during and before the pandemic is reflected in a decrease in social activities and an increase in recreational sports activities. In contrast, other activities remained proportionally the same before and during the COVID-19 pandemic. The average distance traveled for primary outdoor trips before the pandemic is greater than that for primary outdoor trips during the COVID-19 pandemic. The results of this study could be useful in traffic planning and making various policies during various pandemics based on people’s travel needs. In particular, government bodies could use such knowledge to plan partial and smarter lockdowns. Tourism and transport companies could use this information to better plan their services and operations.

Joint prediction of travel mode choice and purpose from travel surveys: A multitask deep learning approach

The prediction and behavioural analysis of travel mode choice and purpose are critical for transport planning and have attracted increasing interest in research. Traditionally, the prediction of travel mode choice and trip purpose has been tackled separately, which fail to fully leverage the shared information between travel mode and purpose. This study addresses this gap by proposing a multitask learning deep neural network framework (MTLDNN) to jointly predict mode choice and purpose. We empirically evaluate and validate this framework using the household travel survey data in Greater London, UK. The results show that this framework has significantly lower cross-entropy loss than multinomial logit models (MNL) and single-task-learning deep neural network models (STLDNN). On the other hand, the predictive accuracy of MTLDNN is similar to STLDNN and is significantly higher than MNL. Moreover, in terms of behaviour analysis, the substitution pattern and choice probability of MTLDNN regarding input variables largely agree with MNL and STLDNN. This work demonstrates that MTLDNN is efficient in utilising the information shared by travel mode choice and purpose, and is capable of producing behaviourally reasonable substitution patterns across travel modes. Future research would develop more advanced MTLDNN frameworks for travel behaviour analysis and generalise MTLDNN to other travel behaviour topics.

Рrospects for the development of religious and excursion tourism in Ukraine

For religious and excursion tourism, sacral buildings that have a special architecture and history are of particular interest, and are often architectural monuments of national significance or represent UNESCO heritage. The subject of the study is the development of religious excursion tourism in Ukraine. The purpose of the article is to determine the state of development and prospects of religious excursion tourism in Ukraine. The goal: to carry out an analysis of the resource base of religious excursion tourism in Ukraine, to determine the state of development of religious excursion tourism in Ukraine; to analyze the foreign experience of the development of religious excursion tourism; to determine the problems and prospects of the development of religious excursion tourism in Ukraine. Research methods used during the writing of the work: statistical, graphic, cartographic, analytical, comparative methods, experimental method, method of scoring. The following results were obtained: the work determined the number of religious buildings of the most common denominations on the territory of Ukraine, architectural monuments of national significance of Ukraine and sacred buildings included in the list of UNESCO World Heritage Sites. The epochs of the construction of sacred buildings and the inherent styles of building religious architecture are given. The peculiarities of the architecture of religious affiliation in the regions of Ukraine are determined. Existing tours and sight-seeing excursions from the leading domestic tour operators of Ukraine were also analyzed. The current trends in the development of cultural and religious tourism in the Kharkiv region were investigated. Conclusions: the significant destruction of church architecture as a result of the war in Ukraine, insufficient supervision of architecture and lack of funds for its restoration, legal problems, low awareness of the country's tourist representatives about the possibilities of using religious objects for the needs of tourism are identified as problems of the organization of this type of tourism. Among the available prospects, the authors indicate: 3D tours of temples and cathedrals, VR reality, interactive installations, 3D mapping, setting up museums inside churches, camping tourism, etc. Therefore, the sacred architecture of Ukraine is an important factor in the formation of new excursion routes that can interest various groups of tourists whose purpose of travel is religious excursion tourism.

THE IMPACT OF THE SOCIO-DEMOGRAPHIC FACTORS ON TOURISM ENTERPRISE MANAGEMENT

The purpose of the paper is to reveal the impact of some socio-demographic factors on tourism enterprise management. A brief overview is presented of several important socio-demographic factors and their influence on tourism enterprise management. As a result, appropriate indicators are selected. On this basis, analysis is carried out of some important socio-demographic factors that tourism enterprise managers should consider when making managerial decisions in connection with the selection, attraction, and retention of target markets of tourists. Specifically, the factors include the purpose of travel of international tourists by countries of origin worldwide and in Bulgaria for the last years. As a result of the analysis, relevant conclusions are drawn.

Determinants of passengers' ticketing channel choice in rail transit systems: New evidence of e-payment behaviors from Xi'an, China

With the rapid emergence of e-payment methods, such as WeChat and Alipay, in China, more passengers choose mobile payment instead of traditional methods such as ticket counters at the station or travel cards when taking public rail transit systems. However, the mechanisms and key drivers of passengers' payment choices when purchasing tickets with new e-payment ticketing channels are significantly underdeveloped. In this paper, a combination of field and online surveys on the city metro system and its passengers was conducted in Xi'an, China, to collect socioeconomic characteristics, residence locations, travel frequency, mobile phone usage information, and payment choices. The Random Forest (RF) model and SHapley Additive exPlanations (SHAP) were used to explore the relationship between payment choices and those passenger-related attributes. The results reveal that travel card ownership, occupation, residence location, travel purpose, education level, and gender are important and influential factors that can effectively affect passengers' preferences regarding how they would like to pay. Subsequent discussions and implications concerning e-payment ticketing channels in rail transit systems were also put forward. This study offers new insights and evidence for a better understanding of the underlying mechanism of passengers' ticketing choice behaviors in this increasingly digitalized era.

Can A Woman Travel As A Woman? Perceptions of Travel Barriers to Women by Personality Trait

The aim of this study is to examine differences in women’s perceptions of travel constraints by personality trait, according to age, educational level, personal income, travelled destination, the purpose of travelling, the time spent travelling, the region travelled to and the factors that affect the choice of destination. The survey data collected from a sample of 304 women travellers were analyzed by performing one-way analysis of variance (ANOVA). The results showed that there are significant differences between women’s perceptions of travel constraints and personal income, the region they travelled to and the purpose of travelling. Significant differences between women’s personality traits and age, education level, duration of travel, destination and destination choice were also found.

User-station attention inference using smart card data: a knowledge graph assisted matrix decomposition model

Understanding human mobility in urban areas is important for transportation, from planning to operations and online control. This paper proposes the concept of user-station attention, which describes the user’s (or user group’s) interest in or dependency on specific stations. The concept contributes to a better understanding of human mobility (e.g., travel purposes) and facilitates downstream applications, such as individual mobility prediction and location recommendation. However, intrinsic unsupervised learning characteristics and untrustworthy observation data make it challenging to estimate the real user-station attention. We introduce the user-station attention inference problem using station visit counts data in public transport and develop a matrix decomposition method capturing simultaneously user similarity and station-station relationships using knowledge graphs. Specifically, it captures the user similarity information from the user-station visit counts matrix. It extracts the stations’ latent representation and hidden relations (activities) between stations to construct the mobility knowledge graph (MKG) from smart card data. We develop a neural network (NN)-based nonlinear decomposition approach to extract the MKG relations capturing the latent spatiotemporal travel dependencies. The case study uses both synthetic and real-world data to validate the proposed approach by comparing it with benchmark models. The results illustrate the significant value of the knowledge graph in contributing to the user-station attention inference. The model with MKG improves the estimation accuracy by 35% in MAE and 16% in RMSE. Also, the model is not sensitive to sparse data provided only positive observations are used.

Illicit COVID-19 products online: A mixed-method approach for identifying and preventing online health risks.

The COVID-19 pandemic triggered a demand for vaccines, cures, and the need of related documentation for travel, work and other purposes. Our project aimed to identify the illicit availability of such products across the Dark Web Markets (DWMs). A retrospective search for COVID-19 related products was carried out across 118 DWMs since the start of the pandemic (March 2020-October 2021). Data on vendors as well as advertised goods such as asking price, marketplace, listed date were collected and further validated through additional searches on the open web to verify the information relating to specific marketplaces. Both quantitative and qualitative methods were used for data analysis. Forty-two listings of unlicenced COVID-19 cures and vaccination certificates were identified across 8 marketplaces sold by 25 vendors with significant variation in prices. The listings were found to be geographically specific and followed the progression of the pandemic in terms of availability. Correlations between vendor portfolios of COVID-19 products and variety of goods of other illicit nature such as illegal weaponry, medication/drugs of abuse also emerged from our analysis. This study is one of the first attempts to identify the availability of unlicenced COVID-19 products on DWMs. The easy accessibility to vaccines, fake test certificates and hypothetical/illegal cures poses serious health risks to (potential) buyers due to the uncontrolled nature of such products. It also exposes buyers to an unwanted contact with vendors selling a variety of other dangerous illicit goods. Further monitoring and regulatory responses should be implemented to protect the health and safety of citizens especially at times of global crisis.

Tourism 5A, Tourism Satisfaction, and Electronic Word of Mouth in a Small Island Destination

Electronic Word of Mouth (EWOM) has gained popularity in academia due to its expansion in online communications, such as Websites, social media, and Blogs for travel and recreation purposes. These online activities in tourism can create an advantage for tourist destinations, especially for businesses and tourism service providers. Therefore, there is an urgent need to look into variables that could affect positive conduct on Electronic Word of Mouth among tourists. The primary purpose of this study is to determine the relationship between Tourism 5A's, Tourism Satisfaction, and conduct Electronic Word of Mouth among domestic tourists in Siargao Island, Philippines. The respondents of this study are domestic tourists. Instrumentation was utilizing a 5 Point-Likert Scale. This study utilizing SmartPLS-SEM, results revealed that among the Tourism 5A's, only the Amenities and Activities have a significant relationship to Tourist Satisfaction and could affect by 84.8 percent. On the other hand, Tourist Satisfaction affects EWOM by 65.7 percent.

Influence of Dockless Shared E-Scooters on Urban Mobility: WTP and Modal Shift

Land use largely depends on the traffic policy of a city. The appearance of e-scooters can greatly affect the visual distribution of transportation, and thus the occupation of land, primarily in the central areas of cities. E-scooters as a shared micro-mobility service have become widespread worldwide since 2017. The advent of e-scooters has made changes in travel habits, especially in the central parts of big cities. However, many issues are focused on e-scooter shared mobility management policies. One of the important issues is the price of renting an e-scooter, on which the percentage of users who use e-scooters largely depend. In order to determine willingness to pay for e-scooter dockless shared mobility, a survey was conducted in the city of Belgrade (Serbia, Europe) on the willingness of participants to use this mode of transport for commuting and other travel purposes depending on the price of renting an e-scooter. The results showed that price plays an important role in the willingness of participants to use an e-scooter. The paper presents mathematical models, which include the cost of renting an e-scooter and the percentage of participants who would accept this type of transport. These mathematical models can help a decision maker to determine the pricing policy in order to maximize the profit from renting an e-scooter, as well as to influence modal shift in order to reduce car-dependent trips.

Exploring the X-Minute City by Travel Purpose in Montréal, Canada

To achieve the x-minute city, we need to understand which destinations are currently reachable or can be reached by sustainable modes within a defined travel time threshold. We find that concentrating on a set of destinations (Leisure and Shopping) and disregarding work trips from the definition of x-minute city can potentially make this concept a more attainable one for 15- and 30-minute city concepts in the North American context. For shopping trips, near half of the current car trips can be replaced by sustainable modes and still be carried out in less than 15 minutes, whilst around 70% of car trips can be replaced by sustainable modes and conducted in less than 30 minutes. Incorporating public transport as a sustainable mode in the x-minute city definition will make it a more achievable one for a specific set of destinations and encouraging sustainable travel behavior requires attention to the importance of local accessibility.

Who are on the road? A study on vehicle usage characteristics based on one-week vehicle trajectory data

ABSTRACT Understanding the characteristics of passenger vehicle use is the prerequisite for effective urban management. However, it has been challenging in the existing literature due to the lack of continuously observed data on passenger vehicle use. Thanks to the advances in data collection and processing techniques, multi-day vehicle trajectory data generated from volunteered passenger cars provide new opportunities for examining in depth how people travel in regular patterns. In this paper, based on a week's operation data of 6600 passenger cars in Shanghai, we develop a systematic approach for identifying trips and travel purposes, and classify vehicles into four categories using a Gaussian-Mixed-Model. A new method is proposed to identify vehicle travel regularities and we use the Z Test to explore differences in travel time and route choices between four types of vehicles. We find that commercially used vehicles present high travel intensity in temporal and spatial aspects and the use intensity in elevated roads is higher for household-used commuting vehicles than semi-commercially used vehicles. The methodologies and conclusions of this paper may provide not only theoretical support for future urban traffic prediction, but also guidance for employing customized active traffic demand management measures to alleviate traffic congestion.

Can dating app users’ self-disclosure foster travel intentions? An appnography approach

This study investigates the effect of self-disclosure on travel motivations and intentions among users of dating apps. Data were collected through a year of appnography and 22 in-depth interviews. The findings show that dating app users go through three stages of self-disclosure, involving the gradual, reciprocal, and hierarchical sharing of information within the app. This self-disclosure leads to the development of travel motivations and strengthens intentions to travel internationally. The study suggests that dating apps, although not designed for travel purposes, can be beneficial to the tourism industry. This paper presents appnographic insights and argues for the increasing importance of online dating apps in the realm of tourism as a platform for creating travel motivations and intentions through in-app interactions.