Association between the built environment and children's independent mobility: A meta-analytic review

Children's independent mobility (CIM) is considered as a determining criterion of child-friendly built environment (BE). Researchers have made a substantial effort to identify the characteristics of the BE that affect CIM and thereby to inform city policy to promote CIM. Although the findings from these studies are useful to inform context specific CIM policy, together they provide inconclusive results. This study made a first attempt to draw a generalised conclusion through a meta-analysis of existing knowledge base. The analysis was conducted using primary studies reporting 13 BE-CIM links and published between 1980 and 2016. Overall effect size (ES), directions, and consistency of each link were calculated, also stratified by contexts, using the reported results from the primary studies and based on a random effect model. The results show that four BE factors (dead-end street, % of residential land, % of commercial land, and residential location type) have a positive association with CIM; traffic volume has a neutral association; and the remaining eight factors (vehicular street width, road density, intersection density, major road proportion, land use mix, availability of recreational facilities, residential density, and distance to destination) have a negative association. Living in a dead end street was found to have the strongest positive ES (0.352), with moderate level of consistency across the primary studies. In contrast, land use mix has the strongest negative ES (− 0.212) but with the highest level of inconsistency. Both ESs and consistencies, however, vary between developing and developed country contexts. Diversity in contexts, research design, and measurement instruments across the primary studies contributed to the heterogeneous results. The findings of this research serve as a guide for practitioners and researcher alike to make an informed decision about the BE factors that consistently foster or hinder CIM in different contexts.     

Built environment effects on leisure travel for children: Trip generation and travel mode

This study empirically analyzed the effects of built environment on leisure travel among children. Students of three elementary schools, namely Yangmingshan, Sanyu and Shilin, all located in the Shilin District of Taipei, were chosen to provide sample data. The negative binomial regression model and multinomial logit model were used to analyze trip generation and travel mode, respectively. This study reached the following empirical findings: (1) mixed land use, employment density, walkway quality, leisure facility supply and leisure travel distance encouraged generation of leisure trips for children; (2) intersection density, building density, employment density and walkway quality encouraged a child to use transit systems or non-motorized travel modes for leisure travel; and (3) vehicle density and leisure travel distance discouraged walking and biking but encouraged the use of transit systems for leisure travel involving children. Local government can use the empirical findings of this study to develop urban planning strategies to encourage children to perform leisure activities outside the home using transit systems or non-motorized travel modes.     

Causes and effects between attitudes,the built environment and car kilometres: A longitudinal analysis

Travel-related attitudes are believed to affect the connections between the built environment and travel behaviour. Previous studies found supporting evidence for the residential self-selection hypothesis which suggests that the impact of the built environment on travel behaviour could be overestimated when attitudes are not accounted for. However, this hypothesis is under scrutiny as the reverse causality hypothesis, which implies a reverse direction of influence from the built environment towards attitudes, is receiving increased attention in recent research. This study tests both directions of influence by means of cross-sectional and longitudinal structural equation models. GPS tracking is used to assess changes in travel behaviour in terms of car kilometres travelled. The outcomes show stronger reverse causality effects than residential self-selection effects and that land-use policies significantly reduce car kilometres travelled. Moreover, the longitudinal models show that the built environment characteristics provide a better explanation for changes in car kilometres travelled than the travel-related attitudes. This contradicts the cross-sectional analysis where associations between car kilometres travelled and travel-related attitudes were stronger. This highlights the need for more longitudinal studies in this field.     

Examining the spatial-temporal relationship between urban built environment and taxi ridership: Results of a semi-parametric GWPR model

With the advance of intelligent transportation systems (ITSs) and data acquisition systems (DASs), it becomes possible in recent to explore the determinants of urban taxi ridership using multi-source heterogeneous data. This paper aims to use floating car data, points-of-interests (POIs) data and housing-price data to assess the influence of the built environment on taxi ridership. Within a scale of 0.5 km grid, critical indicators related to the economic aspect, intermodal connection, and land use factors were obtained using the multi-source data in Shanghai. To capture the spatial and temporal heterogeneity, Semi-parametric Geographically Weighted Poisson Regression (SGWPR) models are built over different time dimensions. It is found that SGWPR models result in higher goodness-of-fit than the generalized linear models. More importantly, the results show the impacts of built environment factors on taxi demand are highly heterogeneous, positive or negative in different city areas, reflected in the significant temporal variations of the effects. Overall, these findings suggest that the built environment factors have significant impacts on urban taxi demand, and the spatial context should not be ignored. Findings in this paper are expected to help better understand the relationship between urban taxi demand and built environment factors, improving the service level of the urban taxi system, and offering valuable insights into future urban and transportation planning.     

Understanding the travel behaviors and activity patterns of the vulnerable population using smart card data: An activity space-based approach

Understanding the travel behaviors and activity patterns of vulnerable people is important for addressing social equity in urban and transportation planning. With the increasing availability of large-scale individual tracking data, new opportunities have emerged for studying people's travel behaviors and activity patterns. However, the data has not been fully exploited to examine the travel characteristics of vulnerable people and their implications for understanding transport-related disadvantage. This study proposes a methodological framework based on the concept of activity space that enables a comprehensive examination of vulnerable people's spatiotemporal travel characteristics and an investigation of the geographies of transport disadvantage. Using the proposed framework, a case study that investigates the bus activities of the vulnerable population using four-month smart card data is carried out in the city of Wuhu, China. The case study suggests that vulnerable people possess distinct travel behaviors that differ considerably from the mainstream population and that the implications of transport disadvantage, as revealed by the participation in bus activities, vary across different demographic groups and across different spatial contexts. Some of the empirical insights obtained from this study also differ from conclusions drawn from previous studies and will enrich our understandings of vulnerable people's activities. Overall, the paper makes two major contributions. Methodologically, the proposed framework can overcome some of the deficiencies of activity space-based approaches for understanding transport disadvantage and contribute broadly to the studies of travel behaviors and activities patterns using individual-level tracking data. Empirically, the study identifies varying spatial and temporal implications of transport disadvantage associated with different vulnerable groups, which could further shed light on public transit planning and service design.     

Differences in travel objectives between first‐time and repeat tourists: An empirical analysis for the Kansai area in Japan

This study investigates the differences in travel objectives between first‐time and repeat tourists. We conduct a questionnaire survey of travel agencies, which asked about specific tour plan for target tourists, their experiences and travel objectives in the Kansai area in Japan. We estimate a logit model for the relationship between travel objectives and visiting experiences. The results indicate that the first‐time tourists' main objective is to enjoy looking around sightseeing spots, while the repeat tourists' objective is simply to enjoy the stay, including the hotel visit and participating in events. Copyright © 2010 John Wiley & Sons, Ltd.     

Determinants of travel mode choice for seeking healthcare: A comparison between elderly and non-elderly patients

People's travel mode choices can vary significantly by age group due to different influencing factors, but relevant research on health-related travel is scarce. In this study, we explored and compared the determinants of travel mode choice for healthcare-seeking non-elderly and elderly patients in Beijing, China. A multinomial logit model was used to analyze data from a recent healthcare-seeking behavior survey. The results show that increased age discourages car use and slightly prompts non-motorized travel in the non-elderly, but has the opposite effect in the elderly group. Household income has a negative effect on non-motorized travel in the non-elderly, but a positive effect in elderly patients. Highly mixed land use, intensive urban development, and difficulty in parking discourage non-elderly patients from traveling by car, but none of these factors have a significant effect on the elderly. Our findings shed light on the unique transportation demands for different age cohorts and inform the creation of age-specific interventions to improve overall access to health.     

Impact of COVID-19 on the number of days working from home and commuting travel: A cross-cultural comparison between Australia,South America and South Africa

The COVID-19 pandemic has changed the way we go about our daily lives in ways that are unlikely to return to the pre-COVID-19 levels. A key feature of the COVID-19 era is likely to be a rethink of the way we work and the implications on commuting activity. Working from home (WFH) has been the ‘new normal’ during the period of lockdown, except for essential services that require commuting. In recognition of the new normal as represented by an increasing amount of WFH, this paper develops a model to identify the incidence of WFH and what impact this could have on the number of weekly commuting trips. Using data collected in eight countries (Argentina, Australia, Brazil, Chile, Colombia, Ecuador, Peru and South Africa), we developed a Poisson regression model for the number of days individuals worked from home during the pandemic. Simulated scenarios quantify the impact of the different variables on the probability of WFH by country. The findings provide a reference point as we continue to undertake similar analysis at different points through time during the pandemic and after when restrictions are effectively removed.     

Dependence between travel distance,individual socioeconomic and health-related characteristics,and the choice of the travel mode: a cross-sectional study for Kaunas,Lithuania

The aim of this study was to analyse the associations between individual socioeconomic and health-related characteristics, travel distance, and the choice of different travel modes in urban population. A cross-sectional study included 932 adults of Kaunas city, Lithuania. The choice of the travel mode and individual characteristics were self-reported by the participants, and their travel routes were calculated using the geographic information system. Multivariate logistic regression was used to assess the most significant factors determining the choice of a car, cycling, walking, or public transport. In total, 529 participants reported using a car, of whom 65.8% had medium or high education levels. These participants were more likely to be younger, male, married, and employed. Among bicycle users, statistically significant differences between the employment status, body mass index, and travel distance were observed. Walkers were significantly more likely to be older, those with lower incomes, unemployed, and travelling the shortest distances. The analysis of the travel distance on the choice of the travel mode revealed that men travelled longer distances with a car compared to women. The employment status was significantly associated with travel distance by car or public transport. Employed individuals travelled longer distances by public transport or by car, compared to unemployed individuals. Among bicycle users, we found that people with higher levels of education and overweight individuals cycled the longest distances. Our study emphasizes the importance of considering different individual characteristics when analysing the choice of transport modes. It provides evidence that is relevant for all urban populations on the choice of the transport mode, particularly considering active versus passive transport.     

Exploring the effects of the rural built environment on household car ownership after controlling for preference and attitude: Evidence from Sichuan,China

With the rapid infrastructure development and economic growth in China, household car ownership in the country's rural areas has changed dramatically in the past 16 years. The total number of cars owned by households in rural areas is currently 12 times higher than it was 16 years ago. The exploration of the effects of the built environment on household car ownership in China's rural areas is worthwhile. However, few studies have investigated this topic. To fill in the research gap, this work collected 374 household data from rural areas in China to examine the effects of the built environment in Sichuan's rural areas on the number of cars in a household. It considered family structure, socioeconomic characteristics, and individual's perceptions of the built environment, preferences towards the built environment and attitudes towards car ownership (shortened to perceptions, preferences and attitudes from now on). Geographic information system (GIS) technology, combined with on-site measurement, was used for data collection. The multinomial logit model was applied for estimation. Household structure and the built environment (including the perceived built environment and the objective built environment) significantly influence the number of cars in a household. By contrast, preference and attitude attributes have less influence on car ownership. Most of the findings are in line with the literature in the context of Chinese cities. Nevertheless, new results are also found. For example, rural hukou, and building density have significant positive impacts on household car ownership in China's rural areas, which is in contrast with their effects on cities. As the first study on rural areas in China, this research provides some insights for rural planners and policymakers to understand better the relationship between built environment and household car ownership.     

The nexus between firm-supply-chain relationships and the potential for tourism development: A case study approach

This exploratory study examines the importance of firm-supply chain relationships for tourism development. Based upon prior observations, two firms seeking to boost their tourism offerings and operating in a popular Vietnamese tourist destination were selected. Semi-structured face-to-face and online interviews were conducted and complemented by on-site visits, and firm information. Various salient dimensions emerged from the data analysis. The ‘performance catalyst’ and ‘detectable value adding’ dimensions underscore the supply chain's benefits, while the ‘discerning relations’ dimension highlights deeper relationships through mutual support, building trust, or demonstrating care. Conceptually, the study proposes a framework with associated theoretical and practical implications.     

Istanbul Airport (IGA) and quest of best competitive strategy for air cargo carriers in new competition environment: A fuzzy multi-criteria approach

Our paper determines the best competitive strategy that can be implemented by existing and potential air cargo carriers in the Turkish Air Cargo Industry with the operationalization of Istanbul Airport (IGA) and reveals the competitiveness level of the industry for four bases. We look at the competitiveness levels by analyzing the competitive environment of the industry nationally and internationally both before and post IGA (estimated). We use fuzzy TOPSIS (FTOPSIS) based on the Fuzzy AHP (FAHP) to handle vagueness, which is inherent in the nature of new competition conditions integrating the framework of Porter's five forces analysis. In our study, we use the five forces as our main criteria (with a total of 19 sub-criteria) and the competitive strategies as our alternatives. Our results reveal that the cost-focused strategy is the best competitive strategy that can be implemented by existing and potential carriers in the industry. Another significant result underscores the fact that IGA increases the competitiveness level of the Turkish Air Cargo Industry both nationally and internationally to a fairly high level. Also, the threat of potential competitors is first among the five forces in the industry's new conditions. Our study fills the gap in the literature on the effects of major structural changes in an air cargo industry on the competition among carriers.