Mobile Travel Research Articles

Exploring Factors Influencing Electric Vehicle Purchase Intentions through an Extended Technology Acceptance Model

Recently, with climate deterioration and environmental pollution, consumers are becoming more and more aware of the use of sustainable energy. In particular, the demand for electric vehicles that use sustainable energy is also increasing. In addition, due to the simple driving principle of pure electric vehicles, many electric vehicles developed by electronics companies are continuously being launched. Electric vehicles not only use renewable energy to protect the environment but also save on various usage expenses, so they are expected to become the main products in the mobile travel equipment market in the future. This study aims to explore the impact of product design dimensions on electric vehicle (EV) purchase intentions, provide a theoretical basis for companies’ differentiation strategies, and reflect the impact of product design on purchase intention. This study uses Davis’s TAM combined with environmental awareness (EA) for analysis; an online survey was conducted on Chinese (n = 468) and Korean (n = 409) consumers, both male and female, aged 20–60 years and above. We found that, for Chinese consumers, the aesthetic and symbolic dimensions do not affect perceived usefulness and perceived ease of use, but they do affect environmental awareness, while the functional dimension affects not only perceived ease of use and usefulness but also environmental awareness. For Korean consumers, the aesthetic, functional, and symbolic dimensions all affect perceived ease of use and environmental awareness, but perceived usefulness is only affected by aesthetics and environmental awareness. Through simulation analysis, the results show that perceived ease of use, usefulness, and environmental awareness all directly affect purchase intentions. Perceived ease of use and environmental awareness are particularly important for Chinese consumers, while Korean consumers pay more attention to the test drive experience and environmental awareness. The results show that electric vehicle manufacturers should develop new technologies for the Chinese market to attract consumers, while in the Korean market, they should improve perceived usefulness through test drives and pay attention to environmental awareness. Specific statistical data show that both Chinese and Korean consumers assign importance to the impact of environmental awareness on purchase intention, proving the importance of environmental awareness. The results of this study will be of great reference value to electric vehicle manufacturers, policymakers, and consumer behavior researchers, helping them to better understand the role of product design in improving the market acceptance of electric vehicles.

Using mobile phone data to capture residential segregation and its association with travel mobility

AbstractThis study measures residential segregation and investigates its association with travel mobility by using mobile phone data from Shenzhen, China. It considers residential segregation in terms of income level and migrant group; and travel mobility in terms of travel frequency, activity space, and travel distance. Unlike previous research on residential segregation and travel mobility, our research uses mobile phone data to produce empirical evidence. The extent of segregation between different migrant and income‐level groups is measured using the location quotient and Getis‐Ord index. This enables us to develop a linear regression model with which to investigate the associations of residential segregation with travel mobility. The study results show that the segregation of middle‐ and low‐income groups and migrants from Southwestern China and Jiangxi is negatively associated with travel mobility among those in the suburbs; meanwhile, for groups segregated in the city center, there is a positive association with travel mobility. These findings suggest that residential segregation is especially adverse for the travel mobility of disadvantaged groups and those living in the suburbs. Accordingly, the paper presents policy recommendations that would enhance travel mobility by alleviating the problems associated with the residential segregation of socially disadvantaged groups living in the suburbs.

Who will board urban air taxis? An analysis of advanced air mobility demand and value of travel time for business, airport access, and regional tourism trips in Iran

Recent advancements in the development of a comprehensive urban air mobility ecosystem promise the opportunity for its implementation in the near future. However, the utility of this emerging mode of transportation in comparison to the existing modes varies for different trip purposes and geographical contexts. It is, therefore, imperative to assess its usage potential for various scenarios before moving forward with implementation efforts. This paper presents the findings of three stated preference surveys aimed at characterizing prospective urban air mobility travel demand for weekly business, airport access, and regional tourism trips in Iran. Hybrid multinomial logit and hybrid nested logit models are estimated for each trip purpose. The results indicate that urban air mobility for weekly business trips represents the most viable market segment. Value-of-time estimates for weekly business trips are more than two and a half times higher than those for airport access trips, and tourism trips are valued even less. There is a trend towards delaying the adoption of air taxis to gain trust, and reducing ticket prices is seen as the most effective incentive for increasing the adoption rate. This study pioneers research on urban air mobility in a developing country context, offering valuable insights into market viability for investors and policymakers.

Motivations for the Demand for Religious Tourism: The Case of the Pilgrimage of the Virgin of Montserrat in Ecuador

Religious tourism is one of the oldest forms of mobility for travel. This study aims at validating the motivational dimensions of demand in religious tourism. The present research was carried out with tourists who had attended the pilgrimage of the Virgin of Montserrat in the city of Montecristi (Ecuador), an important tourist destination that stands out for its culture and intangible heritage. This quantitative study had a sample of 298 valid questionnaires that were analyzed through exploratory and confirmatory factor analysis. The results identified five motivational dimensions: experience belief, experience religion, social exploration, escape, and shopping. The results will serve as a guide for private companies to develop products from religious tourism. Likewise, the research contributes significantly to the academic literature on religious tourism in emerging destinations.

Portraying on-road CO2 concentrations using street view panoramas and ensemble learning

A significant reduction in carbon dioxide (CO2) emissions caused by transportation is essential for attaining sustainable urban development. Carbon concentrations from road traffic in urban areas exhibit complex spatial patterns due to the impact of street configurations, mobile sources, and human activities. However, a comprehensive understanding of these patterns, which involve complex interactions, is still lacking due to the human perspective of road interface characteristics has not been taken into account. In this study, a mobile travel platform was constructed to collect both on-road navigation Street View Panoramas (OSVPs) and the corresponding CO2 concentrations. >100 thousand sample pairs that matched “street view-CO2 concentration” were obtained, covering 675.8 km of roads in Shenzhen, China. In addition, four ensemble learning (EL) models were utilized to establish nonlinear connections between the semantic and object features of streetscapes and CO2 concentrations. After performing EL fusion modeling, the predictive R2 in the test set exceeded 90 %, and the mean absolute error (MAE) was <3.2 ppm. The model was applied to Baidu Street View Panoramas (BSVPs) in Shenzhen to generate a map of average on-road CO2 with a 100 m resolution, and the Local Indicator of Spatial Association (LISA) was then used to identify high CO2 intensity spatial clusters. Additionally, the Light Gradient Boost-SHapley Additive exPlanation (LGB-SHAP) analysis revealed that vertically planted trees can reduce CO2 emissions from on-road sources. Moreover, the factors that affect on-road CO2 exhibit interaction and threshold effects. Street View Panoramas (SVPs) and Artificial Intelligence (AI) were adopted here to enhance the spatial measurement of on-road CO2 concentrations and the understanding of driving factors. Our approach facilitates the assessment and design of low-emission transportation in urban areas, which is critical for promoting sustainable traffic development.

Advantage of foreignness in a digital world: role of long tail users

PurposeThis study aims to explore the advantage of foreignness in a digital world.Design/methodology/approachUsage data for 251 days of 32 travel mobile applications installed on a major mobile phone brand in China are examined. Results support the author’s arguments.FindingsForeign mobile apps enjoy higher daily usage time than local apps. Next, the author consider how foreign apps can maximize their advantage, that is, increase daily usage time. The author argue that a multinational enterprise (MNE) can digitally enter a country that has numerous immigrants from its home country because of the high number of potential long tail users. A high level of diversity of international experience of MNEs increases the ability to understand and satisfy the specific needs of long tail users, thereby increasing daily usage time of foreign mobile apps. To maximize the advantage of foreignness in a digital world, MNEs can also carefully select business models that do not heavily rely on network effect, given the difficulty of generating network effect by long tail users.Originality/valuePrevious studies focus on the liability of foreignness or outsidership that MNEs encounter in the digital world, whereas this study argues that foreignness brings certain benefits, such as the capability to satisfy the specific needs of long tail users.

Testing a modified information system success model in a mobile travel app context

Testing a modified information system success model in a mobile travel app context

Assessment of Sustainable Mobility Patterns of University Students: Case of Cameroon

The transition to sustainable mobility is a recognized socio-economic and environmental challenge, particularly among young adults. In addressing the gap in the literature on young adults’ travel behaviors, especially in Cameroon, this paper investigates the transport mode choices, influencing factors, and barriers to sustainable mobility of students at the National Advanced School of Public Works, Yaoundé (NASPW). Data were collected through online questionnaires with 360 valid responses. Findings revealed that most students used multiple modes of transport for commuting, with moto-taxis being the most common. Accessibility, vehicle speed, and flexibility appeared as the most important reasons for the preferred transport modes, while driver’s license possession, safety perceptions, speed, and proximity were significant predictors for mode choice. Demographic factors were found to influence transport preferences, with distinct clusters prioritizing different aspects. Barriers to public transport were primarily long waiting times and congestion, while active mobility was hindered by distance, infrastructure, and weather. The usage of public transportation was encouraged by its affordability and reduced travel time, whilst active options were preferred due to cost savings and health benefits. To promote sustainable mobility for campus travel, it is crucial to encourage active modes, develop mass transport systems, and raise awareness through symposia and conferences among students and staff.

Mining Multimodal Travel Mobilities with Big Ridership Data: Comparative Analysis of Subways and Taxis

Understanding traveler mobility in cities is significant for urban planning and traffic management. However, most traditional studies have focused on travel mobility in a single traffic mode. Only limited studies have focused on the travel mobility associated with multimodal transportation. Subways are considered a green travel mode with large capacity, while taxis are an energy-consuming travel mode that provides a personalized service. Exploring the relationship between subway mobility and taxi mobility is conducive to building a sustainable multimodal transportation system, such as one with mobility as a service (MaaS). In this study, we propose a framework for comparatively analyzing the travel mobilities associated with subways and taxis. Firstly, we divided taxi trips into three groups: competitive, cooperative, and complementary. Voronoi diagrams based on subway stations were introduced to divide regions. An entropy index was adopted to measure the mix of taxi trips. Secondly, subway and taxi trip networks were constructed based on the divided regions. The framework was tested based on the automatic fare collection (AFC) data and global positioning system (GPS) data of a subway in Beijing, China. The results showed that the proportions of taxi competition, taxi cooperation, and taxi complements were 9.1%, 35.6%, and 55.3%, respectively. The entropy was large in the central city and small in the suburbs. Moreover, it was found that the subway trip network was connected more closely than the taxi network. However, the unbalanced condition of taxis is more serious than that of the subway.

The Influence of Design and Arousal on Impulse Purchase in Mobile Travel Applications

Since consumers’ impulse buying intentions can be easily completed via mobile platforms, impulse buying of travel products has become more common. Hence, this study aimed to understand how mobile tourism applications affect travelers’ impulse purchase behaviors. Utilizing the S-O-R framework and distinguishing environmental stimuli and consumer behaviors, this study proposed a conceptual model and hypotheses to investigate the relationship between usability, information effectiveness, emotional arousal, and impulsive purchase intentions in the context of mobile applications. Based on 63 responses, the experiment applied neuroscience methods and found that information effectiveness positively affected impulsive purchase intentions, while usability and emotional arousal did not have significant effects. Hence, results offer practical insights into the development of travel applications and extend the S-O-R framework with the inclusion of emotional arousal.

Exploring Travel Mobility in Integrated Usage of Dockless Bike-Sharing and the Metro Based on Multisource Data

Dockless bike-sharing (DBS) is a green and flexible travel mode, which has been considered as an effective way to address the first-and-last mile problem. A two-level process is developed to identify the integrated DBS–metro trips. Then, DBS trip data, metro passenger data, socioeconomic data, and built environment data in Shanghai are used to analyze the spatiotemporal characteristics of integrated trips and the correlations between the integrated trips and the explanatory variables. Next, multicollinearity tests and autocorrelation tests are conducted to select the best explanatory variables. Finally, a geographically and temporally weighted regression (GTWR) model is adopted to examine the determinants of integrated trips over space and time. The results show that the integrated trips account for 16.8% of total DBS trips and that departure-transfer trips are greater than arrival-transfer trips. Moreover, the integrated trips are concentrated in the central area of the city. In terms of impact factors, it is found that GDP, government count, and restaurant count are negatively correlated with the number of integrated trips, while house price, entropy of land use, transfer accessibility index, and metro passenger flow show positive relationships. In addition, the results show that the GTWR model outperforms the OLS model and the GWR model.

Empowering Safety-Conscious Women Travelers: Examining the Benefits of Electronic Word of Mouth and Mobile Travel Assistant

Male solo travelers tend to be more frequent and mobile compared to female solo travelers. This difference can be attributed to travel constraints and safety issues. Social media connects like-minded people and serves as an inspirational resource for deciding where to go and what to do. Numerous netizen travelers are actively sharing their journeys and experiences on their social media profiles. Exciting dining options, diverse locations, recommendations for restaurants, accommodations, and personal experiences are all shared on social media platforms. Millennials rely on electronic word of mouth (e-WOM) to form perceptions about a destination. Thus, the study aims to gain insights into the experiences of solo female travelers who are active on social media platforms. Sentiment analysis is performed on Twitter data by analyzing the latest and trending tweets, which helps in gaining valuable insights regarding the safety of women travelers. Furthermore, research is being conducted to analyze the positive aspects of the travel experience using the Experience Economy model, which provides opportunities for self-discovery and personal growth.

A Complete and Comprehensive Semantic Perception of Mobile Traveling for Mobile Communication Services

A Complete and Comprehensive Semantic Perception of Mobile Traveling for Mobile Communication Services

Configuring mobile app update strategy for growth: An empirical analysis of a landscape search model

PurposeThis study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.Design/methodology/approachUsing a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.FindingsThis study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.Originality/valueThis study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers

&lt;p&gt;Metro transit is the core of urban transportation, and the mobility analysis of metro ridership can contribute to enhance the overall service level of the metro transit. Researchers studying metro ridership are focused on the spatiotemporal distribution characteristics of the ridership in the underground system of metro station by metro smart card data. However, limited by lack of travel mobility chain of ridership integrity, their activity patterns cannot be used to identify the heterogeneity of metro ridership's origin and transfer travel mode. In our research, we applied full spatiotemporal coverage of mobile phone data to identify the complete travel mobility of metro ridership in the perspective of ground and underground transit. First, the mobility of the boarding and alighting stations was extracted and the order of the transfer station was then extracted. Second, relying on the ridership flow identification method, the aboveground origin and destination of the ridership outside the metro system were extracted, and their transferred traffic mode was identified. The empirical results have shown that our proposed framework can accurately analyze the mobility patterns of metro ridership in an aboveground area and underground station.&lt;/p&gt;

Adoption intention and usage behaviour of mobile travel apps: integration of trust, and technology acceptance model with social cognitive theory

Adoption intention and usage behaviour of mobile travel apps: integration of trust, and technology acceptance model with social cognitive theory

Enhancing smart tourism and smart city development: evidence from Taoyuan smart aviation city in Taiwan

PurposeThis study aims to investigate tourists’ impressions of the smart destinations model from the socio-technical systems and the technology–organization–environment (TOE) perspectives. Specifically, it aims to explore how information source credibility and cloud infrastructure influence tourists’ use of intelligent technology.Design/methodology/approachThis measurement development is based on prior literature; after being evaluated for face and content validity, the authors used random sampling to collect data and conducted a field survey of tourists through Taoyuan Airport and using the airport MRT between December 2022 and March 2023. After confirming that tourists knew the destination information and had experience using travel-related mobile applications to plan their itinerary, the authors further invited tourists to participate in the survey, and 512 valid questionnaires were analyzed by the structural equation modeling approach.FindingsThe finding pointed out that source credibility and intelligent technology were innovative technologies that benefitted tourists, as were mobile travel planning apps, which created a relational context based on interests and activities from the socio-technical and TOE perspectives.Originality/valueTechnological innovation is closely related to the development of smart cities; tourists who used travel itineraries successfully understood travel-related actions and significantly had more positive affective images of the city.

Envisaging AR travel revolution for visiting heritage sites: A mixed-method approach

Augmented Reality (AR) offers transformative potential for augmenting and replacing realities within a wide range of business and social applications. Within this, this study explores antecedents of behavioral adoption of AR mobile travel apps to visit a heritage site by substituting in-person and corporeal tourism experiences through a visualization technique that overlays 3D simulated architecture in front of a user. This research specifically investigates the collective impact of perceived app attributes of the AR service model, and critical characteristics of users in terms of their underlying psychological predispositions impacting their behavioral intention to use AR travel apps for heritage tourism in an emerging nation. In pursuance of this, we adopt a unique mixed-method research methodology where industry experts and travel enthusiasts are invited to delve into the phenomenon and identify facilitators of AR mobile app adoption for heritage tourism in India. Empirical findings find that experiential authenticity, service quality, and user innovativeness are the significant underlying factors expediting the use of AR mobile apps. Additionally, with a focus on the sustainability aspect of AR tourism, this study considers sustainability within travel. This construct is critical since it discerns how it affects the boundary conditions in the light of consumers' personality characteristics for determining intention to use AR apps, thereby providing insightful inferences for the tourism industry and research.

Co-evolution of Smart Small Vehicles and Human Spatial Experiences: Case Study on Battery-Sharing Electric Two-Wheelers Experiment

Small-format mobility services have been introduced in many cities to promote sustainable urban development. In some cities, these services are primarily seen as entertainment rather than significant transport modes. Research has studied the roles of experiential/hedonic and functional/instrumental motivations in users’ adoption intent for such services. However, there is still a limited understanding of how actual spatial experiences of mobility travels shape travel behaviors. This study explores the role of spatial experience in mobility travels. Specifically, the research question revolves around whether better spatial knowledge leads to better spatial experiences, thereby satisfying users’ functional/instrumental and experiential/hedonic values for mobility trips. Additionally, we examine how spatial knowledge affects travel behaviors regarding trip chaining and vehicle charging. To assess road users’ spatial knowledge, we use sketch maps to examine changes after three months of using battery-sharing two-wheelers. A mixed-methods approach and multiple data sources are employed to provide deeper insights, including sketch maps, questionnaire surveys on attitudes, and a panel data analysis on activity-travel patterns. The results indicate that spatial experience significantly influences perceived values and, consequently, travel behaviors. Improved knowledge leads to greater satisfaction with mobility travel. Furthermore, an interaction effect is found between cognitive distance and cognitive direction concerning users’ satisfaction with the driving range and charging issues of electric vehicles.

Factors Influencing Behavioral Intention Toward Using Travel Mobile Application: Examining the Mediating Role of Reviews and Ratings

The purpose of this study is to identify the major factors that affect tourist intention to use mobile application for the purchase of travel and tourism services. This study integrates the theory of M-S-QUAL with two additional factors, price consciousness and information quality, to develop a conceptual framework. Data was collected from 510 users of travel mobile applications from Delhi/NCR, and analyzed using structural equation modeling. The results indicated that efficiency, privacy, price consciousness, and information quality are the main determinants of m-satisfaction. Additionally, m-satisfaction significantly affects tourists’ behavioral intentions. Reviews and ratings was found to partially mediate the relationship between m-satisfaction and tourists’ behavioral intention. The framework is helpful for decision-makers to identify the factors that can satisfy tourists when using a travel mobile application and will also provide useful insights for the travel service providers dealing in m-applications to device their future strategies.