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School commuting is critical for modern societies considering its potential and long-lasting impacts in travel behaviour of younger generations, today and in the future. Besides positive health impacts, it is crucial to expose students to more sustainable modes (e.g., walking, cycling, public transport) to form future adults with more sustainable m...
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... order to model the willingness to shift to PT when commuting to school, the initial model included all variables (hard and soft factors) and the school level the students attended. After running different models, the results from the final Logit model are presented in Table 4, Table 4and a number of factors revealed to be statistically significant: Hard Factors (Number of Transfers, Security, Frequency, Schedule, Bus Suppression); Soft Factors (Users´ProfileUsers´Profile 3 -"Bossy", and Child Age); and Context factors (School1 -Primary school, and School2 -Intermediate school). The selected variables improved the quality of the model and avoided multicollinearity without reducing model-data fit (chi-square=99,346; df =15:p<0,001; McFadden Pseudo R-squared = 0,105). ...Context 2
... such, negative parameters (and respective Odds Ratio (OR) lower than 1), indicate an increase in the probability of shifting to PT, while positive parameters (and respective OR bigger than 1), increase the propensity to keep on commuting by car. Table 4 includes two sets of factors: on the top, we include the factors that favour to remaining with the car; while on the bottom, we include the factors that favour shifting to PT. Each factor is organized according to being "hard", "soft", or "context" factors. ...Similar publications
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Citations
... Additionally, school environments could be considered "hard" or "soft" based on the idea that the hard environment is about physical and tangible characteristics, and the soft environment is about the social and psychological ambiance (Queiroz et al., 2020;Wiyono, 2017). In this study, the school hard environment was teachers' background (educational level, match between major and the subject taught, and years of teaching) and school background (school location and school type), while the school soft environment was the principal's support and teacher's music teaching characteristics. ...
Participants included 15,715 fourth graders, 1,309 music teachers, and 950 primary school principals in China. We used a hierarchical linear model (HLM) to estimate the influence of individual and school-level factors on students’ music academic achievement. Results showed that: (1) students’ background had a significant influence on their music academic achievement and the results remained stable throughout our study, (2) school location, music teacher’s major, and years of teaching positively predicted students’ music academic achievement, while school type and music teachers’ education level didn’t, (3) after controlling for the above, both principal support and music teaching characteristics positively predicted children’s music academic achievement; and soft environments had greater influence on their music academic achievement than hard environments did, and (4) of all the variables, music teachers’ teaching content was the best predictor. This study expanded our knowledge of school effectiveness, and the findings enhanced our understanding of the influence mechanism of students’ music learning.
... Other attitudes need to be examined to understand their impact and significance on the mode choice process for school trips. Several important examples of attitudes that impact travel behavior need to be examined in the case of school trips, such as; parents' personality impact on their kids' mode choice (Queiroz, Celeste, and Moura 2020), parents' perception of school trip's safety (Woldeamanuel 2016), environmental concerns (Alemi et al. 2018 Other important aspects of school trips in the post-pandemic situation to be investigated are the operational conditions to minimize the contagion risk. It is essential to define the optimum occupancy level in the different vehicles, especially largesize vehicles, that would be safe for the student to travel and minimize the transmission risk. ...
... There are many barriers to public transport use that can be categorized as hard, soft and complementary (Blainey et al., 2012). Importantly, the hard barriers are more related to indicators and interventions on the supply side of the transport system such as travel cost, time, or frequency, whereas the soft barriers are more related to the demand side including psychological and behavioral aspects (Queiroz et al., 2020). ...
Saudi Arabia intends to reduce GHG emissions by 278 million tons of CO2eq annually by 2030 through Nationally Determined Contribution (NDC) to UNFCCC. Among many policies, mass transit system and transit-oriented development are being developed with the expectation to reduce energy consumption and GHG emissions in Riyadh. To what extent such initiative can reduce energy consumption and GHG emission is an important question. In this paper, a methodology to systematically measure the impact of mass transit and transit-oriented development in Riyadh city on the energy demand has been developed. For Riyadh, a comprehensive travel demand model considering the impact of mass transit and transit-oriented development is still missing. To this end, this paper aims to fill the gap. This methodology considers the state-of-the-art in travel demand analysis and the local context by combining traditional four-step model and activity-based model for modal-shift. This paper describes the methodology and its application for Riyadh by analyzing modal-shift only between car and metro. The results suggest that metro can reduce energy consumption, but the reduction varies with varying accessibility, car, and metro situations. At high urban density and higher car travel cost, we may achieve as high as 13% reduction in fuel demand.
... One of society's major concerns in Thailand is the school commute, a critical topic for households with students. In many countries worldwide, students frequently drive their own cars to school, for example, see Queiroz, et al. [1]; this increase in the overall number of cars results in school areas being congested with vehicles, a common scenario in Thailand's urban areas. This usually occurs at peak times at the start and end of a school day. ...
... There is evidence that parenting styles affect children's perceptions of the risk of travel. In other words, children tend to imitate the behavior of their parents by following their choices and attitudes [1]. It is therefore expected that if parents are aware of the impact of the perceived risks on the road, this can improve their children's perceptions of risk. ...
... Parents' perceived safety Sustainability 2022, 14, 13005 3 of 20 in transport operations and services affects parents' trust in their children's solo travel on public transportation as well as the latent concerns related to "operation service". For example, frequency and schedule greatly affect the willingness to switch to public transport on school trips [1]. In addition, parents' perceptions of safety in their children's travel to school are influenced by age, income, and social cohesion, as well as the quality of the infrastructure [40]. ...
The risk of accidents is a danger in public transport that could lead to threats to property, the environment, and the lives and health of people. In particular, parents are keenly aware of and concerned about the safety of school trips. Thus, this study aims to examine the factors that influence the perceptions of parents about the safety of the school trips of children. The study recruited 750 respondents from Northeast Thailand. Data were obtained from responses to a self-report questionnaire. The model consisted of six factors, namely, transportation satisfaction, infrastructure, information, the safe behavior of drivers, the safety of the transportation systems, and the safety policy. The results of the confirmatory factor analysis indicated that all six factors were in accordance with the empirical data (model fit statistic: χ2 = 758.098, df = 276, χ2/df = 2.747, CFI = 0.962, TLI = 0.955, SRMR = 0.038, RMSEA = 0.048). The results can serve as a reference for developing guidelines and recommending policies for the management and the implementation of safe school trips for students.
... However, such financial measures are often difficult to implement due to public opposition or high implementation cost. Another strand of literature suggests a combination of financial and non-financial measures, promoting a "carrot and stick" approach (Br€ og et al., 2009;Carroll et al., 2021;Queiroz et al., 2020;Washbrook et al., 2006). Although combinations of measures are likely to be more effective for any private vehicle demand reduction, it is also the most complicated to implement. ...
Leisure travel is often highly car-based. In Switzerland, the research area of our study, more than 60% of all kilometers traveled for leisure purposes are traveled by car, and an increase is predicted. As traveling by car comes with many negative side-effects, a more sustainable transportation system calls for a shift to less car-based forms of (leisure) travel. This paper reports an online choice experiment, testing the effectiveness of two financial and three non-financial treatments to reduce car-based leisure travel, all which are currently being discussed in the research and political domains in Switzerland. Additionally, we control for a wide range of determinants proven to be relevant for mode choice. We asked 737 participants to imagine they are visiting family or friends living a short distance (5 km) and longer-distance (100 km) away and to report their mode choice for such trips. Findings show the tested treatments will likely have a limited effect on reducing car-based leisure travel. Results also show that car use is motivated by different reasons than public transport or bike usage. Car users mainly want to travel fast and see car travel as the only viable option. Public transport and bike users, however, attach more importance to enjoyment. Specifically, the availability of a car, bike or public transport card is significant for the mode choice and habitual use. To unfreeze existing lock-ins, we conclude that research needs to look at reasons for why drivers believe there is no alternative.
... This classification was also adopted by Forsythe et al. (2006), and more recently by Han et al. when analysing the intention to adopt electric vehicles (Han et al., 2017). Thus, functional values are defined as the tangible attributes and utilitarian functions such as the variety, price, convenience, and quality of the product; while non-functional values are related to the intangible characteristics of the product regarding social and emotional needs (Han et al., 2017;Ko et al., 2019;Queiroz et al., 2020;Li et al., 2020). Following the trends set by the most recent and advanced mode choice modelling (Kroesen and Chorus, 2020;Nordfjaern and Rundmo, 2018;Simsekoglu and Klöckner, 2019a;Shirgaokar, 2019), micromobility studies have also started to incorporate sociopsychological factors in their attempt to achieve a more realistic and complete representation of micromobility decision-making. ...
This paper aims to identify the main sociopsychological factors that individuals perceive as affecting their intention to adopt electric (e−)micromobility. Drawing from modal choice theory, the factors are classified into functional (money, time, and other convenience values) and non-functional (emotional, social, and epistemic values). Following a PRISMA systematic literature review of 67 papers, we observed the reported influence of several functional and non-functional factors over the decision on whether to use an e-micromobility mode of transport. Results indicate that non-functional factors such as environmental concern, innovativeness, and belonging can be even more influential for individuals than traditional functional factors such as speed, cost, and time savings. Users seem to perceive these services as socially beneficial, contributing to improved livability, equity of access, and diversity of choice. The present review contributes to our understanding of the complexity of modal choice, and the importance of accounting for the sociopsychological factors influencing user decisions regarding micromobility. Our findings can help improve the strategies and policies supporting e-micromobility adoption.
... que existe una resistencia a su uso por parte de los padres y madres de familia, en función de la edad de los hijos, pero también de la calidad del servicio (Queiroz, 2020). Con lo cual, se podría inferir que el mejoramiento de la calidad del transporte público pudiese coadyuvar a incrementar su uso por parte de los niños y jóvenes. ...
El análisis y comprensión de la incidencia de los factores socioeconómicos, de percepción y de mesoescala urbana sobre los modos de movilidad de los niños y niñas en edad escolar es fundamental para fomentar el uso de modos más sustentables. Este estudio explora la relación entre factores socioeconómicos, de percepción y de mesoescala urbana sobre los modos de movilidad diaria de niños y niñas en edad escolar (6 a 12 años) en la ciudad intermedia de Cuenca (Ecuador, América Latina). Se utilizó la herramienta Random Forest, como método de aprendizaje automático supervisado, para clasificar los modos de movilidad en: “caminar”, “autobús” y “automóvil”, y para identificar la importancia de los factores en cada modo. Los datos se obtuvieron de una encuesta de movilidad realizada en hogares de Cuenca en el 2019. A pesar de que buseta es un modo de movilidad usual para escolares, no pudo ser considerado en este estudio ya que no se contemplaba en la encuesta original utilizada. Los resultados mostraron que el mejor modelo para los modos de movilidad “caminar” y “autobús” fue con todos los grupos de factores (socioeconómicos, de percepción y de mesoescala urbana), mientras que para “automóvil”, como se esperaba, fue el modelo con factores socioeconómicos el más relevante. Si bien los factores más importantes fueron el número de vehículos por familia y nivel socioeconómico, también encontramos que los factores de percepción son relevantes para incentivar el caminar como un modo de movilidad cotidiana . Del mismo modo, para fomentar el uso del autobús, deben tenerse en cuenta los factores urbanos de mesoescala. Este estudio aporta datos y un enfoque metodológico para contribuir a la política pública en materia de movilidad activa en edad escolar. Palabras clave: Modos de movilidad, niños y niñas de 6 a 12 años, factores de mesoescala urbana, Random Forest. AbstractAnalyzing and understanding the incidence of socioeconomic, perception and urban mesoscale factors on mobility modes of school-age children is essential to motivate a more sustainable mobility. This study explores the relationship between socioeconomic, perception and urban mesoscale factors on the daily mobility modes of school-age boys and girls (6 to 12 years old) in the intermediatesized city of Cuenca (Ecuador, Latin America). Random Forest, as a classifcation machine learning method, was used to classify the mobility modes into walk, bus and car, and to identify factor importance in each mode. The data were obtained from a mobility survey carried out on Cuenca households in 2019. Even if school bus is a usual mobility mode for schoolchildren, it could not be accounted in this study because it was not contained in the original survey. The results showed that the best model for walk and bus mobility modes was with all the factor groups, while for Car, as expected, was the socioeconomic model. Even if the most important factors were cars´ number per family and socioeconomic level, we also found that, in order to encourage walking as the mobility mode, the perception factors are relevant. Similarly, in order to encourage bus mobility mode, the urban mesoscale factors should be accounted for. This study contributes with data and a methodological approach that could infuence public policy regarding scholar-aged active mobility. Keywords: Mobility Modes, children 6 to 12 years old, urban mesoscale factors, Random Forest
... In order to model the parents' willingness to send their children to the schools, different parameters such as vehicle type used by the parents, class of child studying, preference before and after lockdown, willingness to send the student, and socio-economic and demographic are necessary (Queiroz, Celeste, and Moura 2020). This can be done with the help of the binary logit model (Agarwal et al. 2019;Vasudevan et al. 2019), probit method (Navandar et al. 2019), etc. ...
The novel Coronavirus (COVID-19) significantly impacts all sectors and brings the whole population to stuck
at home due to a countrywide lockdown in India. Due to the lockdown, the major influence is on students
and education systems all over the world. The present study attempts to study the effect of COVID-19 on
traffic patterns and choice of mode for the students to reach their host institute. The response survey was
carried out, and the pre- and post-travel patterns were investigated for the participants. The interesting
finding is that irrespective of the income level, parents are more serious about the safety of their child
against COVID-19. As the available infrastructure is not adequate to follow the COVID-19 protocol, parents
have insisted on using their personalized mode to send their children to school subject to the utmost social
distancing norms followed by schools. Policymakers and planners may use the outcome of the present study
to see the impact of educational trips
