Mobile Travel Research Articles

Development of Model for Pedestrian Gap Based on Land Use Pattern at Midblock Location and Estimation of Delay at Intersections

Walking has always been a prime source of human mobility for short distance travel. Traffic congestion has become a major problem for safe pedestrian crossing in most of the metropolitan cities. This has emphasized for providing a sufficient pedestrian gap for safe crossing on urban road. The present works aims in understanding factors that influence pedestrian crossing behaviour. Four locations were chosen for identification of pedestrian crossing behaviour, gap characteristics, waiting time etc., in Hyderabad city. From the study it was observed that pedestrian behaviour and crossing patterns are different and is influenced by land use pattern. A gap acceptance model was developed from the data for improving pedestrian safety at mid-block location; the model was validated using the existing data. Pedestrian delay was estimated at intersection using Highway Capacity Manual (HCM). It was observed that field delays are less when compared to delay arrived from HCM method.

인공지능 기반 모바일 여행 정보 특성에 따른 소비자 만족 및 행동의도에 대한 연구

인공지능 기반 모바일 여행 정보 특성에 따른 소비자 만족 및 행동의도에 대한 연구

Exploring the Effects of University Campus Decentralization to Students’ Mode Choice

Mobility patterns and travel behavior aspects of students traveling to universities, are gaining attention, as the completion of such every day trips are rather complicated. University students form a social group, essentially autonomous in terms of mode choice decision making. Understanding the mode choice decision process, may reveal the most appropriate interventions for achieving sustainable transport goals. The current study aims to examine various aspects of university students’ travel bahaviour such as travel distance, travel time, comfort and safety in the city of Xanthi, Greece. Moving a step forward, the paper provides a better understanding of students’ travel patterns in two different environments due to the University relocation from an urban environment to a more isolated one. For this purpose, a questionnaire survey is conducted where students describe their travel habits before and after the relocation. In addition, students are given a choice set comprised of eight different factors hypothesized to internalize the effect of the relocation on mode choice for the trips to and from the University and they are asked to prioritize them ranking them from the most significant one to the least important. For the analysis two Multinomial Logit models are developed. The results verify initial considerations; distance and time are the most important factors for both cases while the use of public transport instead of walking increases the importance of economy and safety.

Business travellers’ use of mobile travel applications: a generational analysis

Generational differences in the workplace, particularly in the area of technology usage, have become an area of increasing interest, both for academia and industry. Mobile travel applications have found a distinct role in business travel and support the business traveller at any stage of the travel cycle. The dynamic nature of the business environment, business travel and mobile technology requires research to ascertain the nature of the use of mobile travel applications by business travellers, how this usage differs between generations, and how these applications should be developed in future to meet the needs of the changing workforce. An internet based survey was completed by 232 business travellers with the results showing that mobile travel applications are currently more frequently being used by older generations than younger generations, but that younger generations are more likely to use certain applications in the future than older generations. This study answers the call by previous researchers for future research to focus on emergent transaction channels and communication platforms (such as mobile computing) that could affect different generations by providing a generational analysis of business travellers’ use of mobile travel applications. It should also assist managers in better understanding their travellers, especially in terms of their technology usage, enabling them to manage the company’s travel programme more effectively.

Can online transportation support low carbon?

The existence of online transportation is one of the alternative priority modes in transportation. Online transportation has the concept of car sharing, mainly by the uses of vehicles together. The function of car-sharing is expected to reduce the number of vehicles use. Through the concept of car sharing, it can help to realize the concept of a low-carbon city. In previous studies, people prefer to choose private cars than public transportation, because of their easiness in mobility and short travel time. Online Transportation is also efficient same as private vehicles, regarding mobility and travel time. Thus, Online Transportation is expected to reduce the usage of private vehicles and create more environmentally friendly. Based on this phenomenon, researchers want to explore the purpose of the preference for online transportation. The result finds out that the variables could influence the choices of online transportation. This research was conducted using the utility of transportation mode selection model.

Factors of Spatial Mobility in Russia

This article considers the “Comprehensive monitoring of living conditions” of the Russian population to determine the level of mobility of residents in different regions of the country. The subject matter of the study is the tourist mobility of Russians. A system of equations from the binomial logistic regression model revealed that the probability of a Russian citizen taking a travel tour is mostly influenced by personal factors, such as economic status and physical condition. The impact of transport infrastructure characteristics is absorbed by the income characteristics of individuals; i.e., regional differences in standard of living correlate with the density of the transport infrastructure. Spatial mobility for tourism purposes was found to be associated to a greater degree with land transport infrastructure rather than with air service. Differentiation of Russians with respect to the parameters of spatial mobility of travel actually reproduces economic inequality, while the density of the transport infrastructure, which differs from region to region, tends not to mitigate the impact of economic resources on spatial movement.

Investigating Multiple Devices Used in the Hotel Reservation Process

With the growing ownership of multiple technology devices, and the contribution of mobile travel bookings to the overall travel market, it is critical to investigate the hotel searching and booking process for different device users. This research investigates four categories of device users via a survey with 383 respondents, in the context of search behaviour and information sources used. The results reveal that search engines and family and friends are the most frequently used information sources while the personal computer (PC) is the most used device for both searching and booking. However, there is a significant difference in how these device users engage with information sources, specifically online travel agents (OTAs) and search engines. Furthermore, device users favor one device and are unlikely to switch devices during the search process.

Unraveling traveler mobility patterns and predicting user behavior in the Shenzhen metro system

ABSTRACTOver the last few years, cities have made available large volumes of smart card data that shed light on the urban dynamics of transit users. This research uses metro card data from Shenzhen, China, to recognize individual mobility patterns and predict travelers' future movements. Joint entropy is proposed to measure the regularity of spatio-temporal patterns and travelers are divided into three groups, i.e. regular users, variable users and irregular users, based on the entropy value. Revised Markov chain model and hidden Markov model (HMM) are then introduced to predict individuals' future movement. We observe that the models predict with a high level of accuracy of 84.46%, 78.79% and 73.07% for three groups in the HMM. This study shows the potential to predict travel patterns and enriches traditional pattern recognition and prediction methods for modeling urban mobility. It also helps reveal structural properties of human behavior in urban metro systems.

Modeling continuance intention towards Mobile Travel Service System (MTSS): a theoretical perspective of motivation and dependency

This work sets up a research model that elaborates upon the development of continuance intention towards Mobile Travel Service System (MTSS) based on the motivational theory and the dependency theory. In the model, continuance intention is indirectly affected by personal innovativeness and e-interaction quality through the full mediation of e-engagement and perceived enjoyment. At the same time, the relationships between e-engagement and continuance intention and between perceived enjoyment and continuance intention are hypothetically moderated by e-interaction quality. The hypotheses of this work were empirically tested using data from working professionals in a technology industry regarding their use of MTSS for travel information sharing as well as booking for accommodation, airline, cars, etc. This study conducted a two-wave survey to empirically test its theoretical rationales. The findings of this work complement the previous literature by verifying the full mediating mechanism of e-engagement and perceived enjoyment and the moderating mechanism of e-interaction quality. Lastly, managerial implications for e-marketers based on this study’s findings are provided.

The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews

The purpose of this research is to identify the status and role of mobile technology in achieving sustainable and smart tourism, and to suggest future research and strategy directions for academia and managers in practice. This research utilized multiple sources, such as patents, academic articles, and news, and selected methodologies optimized for the purpose of each study. Study 1 used Netminer, a social network analysis program, to analyze the relationships between patent’s International Patent Classification (IPC) codes. Study 2 used the T-LAB program for content analysis to analyze the texts of patents, journal articles, and news. Study 3 used the Leximancer program, which utilizes relative frequency to analyze mobile app consumer reviews. In study 1, we identified various forms of data related technologies and mobile technologies for smart city systems and maps. In study 2, we found the environment, sustainability, business, and market themes to be related to mobile technology. In study 3, we explored consumers’ attitudes and preferences for mobile travel app using their reviews. Advances in mobile technology are expected to create innovative experiences for consumers, foster a sustainable competitive advantage for tourism destinations and tourism-related suppliers, and create sustainable competencies for smart tourism.

TOURIST ADOPTION OF MAPPING APPS: A UTAUT2 PERSPECTIVE OF SMART TRAVELLERS

Purpose – Mapping apps are location based travel apps used for navigation and routing. These apps are gaining worldwide popularity because of its enormous potential. Despite of the growing popularity and utility of the mapping apps, the published literature in this area is scarce, leaving an unexplored area of research. Thus, the current study aims to identify factors affecting tourist’s intentions to use mapping apps while travelling. Design – The Extended Unified theory of acceptance and use of technology (UTAUT2) was applied as the basis of the present study Methodology – The data was collected from 284 travellers in India using a structured questionnaire. The data was analyzed using Partial Least Square approach. Findings – The results indicated that the most significant antecedents of behavioral intentions are habit, facilitating conditions, performance expectancy and hedonic motivation. It was observed that the actual usage behavior was influenced by traveler’s intentions and habit to use the technology (mapping apps). However it was noted that effort expectancy, social influence and price value had no significant effects on the tourist’s intentions to use mapping apps while travelling. Originality of the research – Till date limited empirical studies have explored the adoption of mapping apps by travelers. This study is unique as it explores the adoption intentions using a relevant theoretical framework in the developing economy context wherein the use of mapping apps is still in the nascent stage. This research contributes to the literature of innovation adoption and provides an interesting perspective to companies developing location based travel mobile apps.

Investigating the impact of high-speed rail equipment visualization on mode choice models: Case study in central Texas

High-speed passenger rail (HSR) is seen as an ideal solution for fast, safe, and resource-efficient mobility for intercity travel. For proposed HSR service, stated preference (SP) surveys are necessary to obtain the data needed for ridership forecasting. In SP surveys, it may be helpful to include images of the options being examined to support respondent decision-making. However, it is unclear from the current literature how images of a passenger train included in an SP survey affect mode choice models developed from the resulting survey data. This paper presents a case study examining the impacts of including images of proposed high-speed passenger trains in SP surveys for HSR service planning activities based on a survey of residents in two communities in Central Texas. Three groups were examined − a control group with a “text-only” description of proposed rail service, an image of an average-quality train, and an image of a premium-quality train. Analysis of the survey responses found that the value of time (VOT) for respondents viewing the premium image was nearly twice the VOT for the text-only condition. However, the premium-quality train image had a lower error variance, resulting in a data set that was less “noisy” than the other image or the base condition. This analysis provides a starting point for a broader discussion on how HSR is portrayed in surveys and the potential for eliciting bias based on the images displayed.

Assessing the impact of mobile travel applications on tourism industries

Assessing the impact of mobile travel applications on tourism industries

The Analysis of Competitive Strategy and Suggestions for Didi under the Background of the New Car-hailing Regulation

The emergence of car-hailing service satisfies the need of public travel in Internet era. Didi—the representative of car-hailing service, provides users with cost-effective service and great travel experience and quickly became the leader in the field of mobile travel depending on its price advantage, market segmentation, fast respond and some other competitive strategies. However, the promulgation of the new car-hailing regulation brings many challenges to Didi. After the new regulation, it is hard for Didi to gap away significantly from its competitors in scale and price. Thus the differentiated service is the competitive focus for all platforms. So there is an urgent need for Didi to do something to make difference, such as improving the interface design of the platform and the process of order allocation, establishing exclusive ‘station’, increasing the interaction between drivers and passengers. By doing so, Didi can reduce the information asymmetry and increase the user engagement and loyalty with high quality service.

Network-oriented household activity pattern problem for system optimization

The recently emerging trend of self-driving vehicles and information sharing technologies, made available by private technology vendors, starts creating a revolutionary paradigm shift in the coming years for traveler mobility applications. By considering a deterministic traveler decision making framework at the household level in congested transportation networks, this paper aims to address the challenges of how to optimally schedule individuals’ daily travel patterns under the complex activity constraints and interactions. We reformulate two special cases of household activity pattern problem (HAPP) through a high-dimensional network construct, and offer a systematic comparison with the classical mathematical programming models proposed by Recker (1995). Furthermore, we consider the tight road capacity constraint asanother special case of HAPP to model complex interactions between multiple household activity scheduling decisions, and this attempt offers another household-based framework for linking activity-based model (ABM) and dynamic traffic assignment (DTA) tools. Through embedding temporal and spatial relations among household members, vehicles and mandatory/optional activities in an integrated space-time-state network, we develop two 0–1 integer linear programming models that can seamlessly incorporate constraints for a number of key decisions related to vehicle selection, activity performing and ridesharing patterns under congested networks. The well-structured network models can be directly solved by standard optimization solvers, and further converted to a set of time-dependent state-dependent least cost path-finding problems through Lagrangian relaxation, which permit the use of computationally efficient algorithms on large-scale high-fidelity transportation networks.

A cross-sectional study of travel patterns of older adults in the USA during 2015: implications for mobility and traffic safety

BackgroundWith an ever increasing population of older adults (65+ years) in the USA, a better understanding of this population’s travel patterns is needed to improve travel mobility and transportation safety.ObjectiveIn...

‘Les Soixante-Routards: travel, generation, and 1968’

Philippe Gloaguen and the ‘Routard Generation’ reveal a variety of themes in the cultural history of 1968 and its legacy in France regarding the intersection of travel mobility and generational identification. Mobility was and remains a central motif in the mythology of 1968. The way the cultural phenomenon of French backpacker travel has come to be understood there is bound up with ideas about 1968 and generation. The cultural association of 1968 with French travel and mobility helped create a broad generational cohort able to incorporate those who were not politically involved, or at best, were on the margins of protest activity. The self-proclaimed soixante-routards conflate travel mobility with a generational construct centred on 1968 as a means to render their personal travel with political meaning.

Activity-Based Approach for the Design of Sustainable Area and Cordon Pricing Schemes

Background Vehicle-generated emissions remain a serious threat to public health, and a major contributing factor to climate change. In response to this situation, several cities around the world have successfully reduced vehicle emissions by implementing area and cordon-based pricing (ACP). Despite these successes, designing ACP schemes continues to be a challenging task given the complexities of estimating the multidimensional effects of this type of strategy. Existing transportation network design methodologies focus primarily on congestion-related goals, and employ an aggregate representation of travel demand. However, the assessment of the public health impacts of vehicle emissions requires information on disaggregate travel and activity participation behavior, as well as spatially and temporally varying pollutant concentrations; existing methodologies do not meet the planning needs of agencies interested in determining the optimal design of ACP schemes that explicitly account for both congestion and public health. Methods We propose an optimization model that can be used by transportation planning agencies to determine optimal charging boundary locations and toll levels with the objective of reducing the health impacts of vehicular traffic and improve mobility. The proposed ACP design problem is formulated as a bi-level, simulation-based optimization model. The problem's upper-level is composed of the policy makers’ goals (i.e., health and mobility objectives). The travelers’ responses to the policy maker's decisions, as well as the resulting system-wide impacts, are analyzed in the lower-level. The lower-level model system is composed of five sub-models: (a) a disaggregate activity-based travel behavior model to simulate the agents’ behavioral response to ACP specifications, (b) a traffic assignment model to estimate the distribution of traffic in the network, (c) a traffic emissions model, (d) a pollutant dispersion model, and (e) a health impact assessment model to estimate the changes in public health risks resulting from ACP schemes. The proposed methodology is computationally expensive given the type of models being combined. Therefore, we present a multi-objective, surrogate-based optimization approach that is intended to accelerate the discovery of good solutions to the design problem. Results An illustrative application of the proposed methodology is presented using Chicago as a case study. As expected, preliminary results suggest that there is a tradeoff between improving travel mobility objectives and reducing traffic's public health impacts. Conclusions The proposed methodology can be an important tool for transportation planners. Further research is necessary to refine the different parameters and strategies used in the solution algorithm.

The Use Intention of Mobile Travel Apps by Korea-Visiting Chinese Tourists

The Use Intention of Mobile Travel Apps by Korea-Visiting Chinese Tourists

An adaptive hawkes process formulation for estimating time-of-day zonal trip arrivals with location-based social networking check-in data

Location-Based Social Networking (LBSN) services, such as Foursquare, Facebook check-ins, and Geo-tagged Twitter tweets, have emerged as new secondary data sources for studying individual travel mobility patterns at a fine-grained level. However, the differences between human social behavioral and travel patterns can cause significant sampling bias for travel demand estimation. This paper presents a dynamic model to estimate time-of-day zonal trip arrival patterns. In the proposed model, the state propagation is formulated by the Hawkes process; the observation model implements LBSN sampling. The proposed model is applied to Foursquare check-in data collected from Austin, Texas in 2010 and calibrated with Origin-Destination (OD) data and time of day factor from Capital Area Metropolitan Planning Organization (CAMPO). The proposed model is compared with a simple aggregation model of trip purposes and time of day based on a prior daily OD estimation model using the LBSN data. The results illustrate the promising benefits of applying stochastic point process models and state-space modeling in time-of-day zonal arrival pattern estimation with the LBSN data. The proposed model can significantly reduce the number of parameters to calibrate in order to reduce the sampling bias of LBSN data for trip arrival estimation.