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Field trips can change students’ attitudes and improve their learning performance, but they have rarely been investigated in logistics education research. The purpose of this paper is to present the findings from field trips that were designed to increase students’ knowledge of sustainable transport as well as to change their attitudes and behavioral intentions.

A total of 104 logistics students participated in this longitudinal panel study. Non-parametric statistical tests were used to test for significant effects.

Field trips build students’ knowledge, improve their attitudes and increase their behavioral intentions to use sustainable transport modes in the short and in the long term. Gains in knowledge exceed the results expected from traditional learning theories. Gender and school type are important moderating variables. Gender did not play an important role for knowledge gains, but for attitude and behavioral intentions.

More research is needed to generalize the findings to other populations and longitudinal panel studies are necessary to investigate a long-term effect of field trips.

Field trips are an effective means for successful knowledge transfer and are suitable to trigger attitudinal and behavioral changes. The involvement of practitioners and the hands-on experience ensure that students combine theoretical with practical knowledge.

This is the first longitudinal panel study that investigates the effects of logistics field trips, which were developed collaboratively by industry, educational and research institutions.

This paper asserts that sustainable tourism education is an issue of extreme importance, especially for young adolescents, ages 10 to 12. Despite little intersection between middle-school education and tourism education, these two fields can become natural allies. Today's preteens not only influence their parent's tourism choices but will shape tomorrow's tourism, both as tourists and as hosts. This study is addressing the following research questions: if transformational school trips with tourism sustainability education proposes improve or enhance students' confidence and initiative, and how middle school individuals can become familiar with responsible and sustainable tourism and act upon it. Thus, the conceptual framework offered in this article is intended to contribute to a more systematic, programmatic, theory-based approach to the study of education for sustainable tourism in middle schools, and that by empowering students through travel. Results suggest that empowering middle-school individuals is halfway to achieve tourism sustainability goals.

This chapter investigates the impacts of households’ residential self-selection, parents’ perceptions and travel patterns on their children’s daily travel mode shares, among single parent households.

To capture the complexity of the relationships between parent and children daily travel mode choices, an integrated model structure is introduced and the model estimated with simultaneous equation modelling.

The results show that, beside the daily activity-travel engagements of the parent, both parent’s perceptions and his/her residential self-selection reasons play significant roles in influencing their children daily travel mode shares. The parent’s perceptions play more significant roles in influencing children’s travel modes shares, whilst the residential self-selection reasons have more significant influence on the parent’s travel mode choice.

The finding of this study reveals a fact that wherever the children live, their travel behaviour tend to be ‘neutral’ and open to influence by their parents throughout their childhood.

This study adds to our understanding of the interactions between parents’ attitudes and behaviours with their children’s travel patterns. This study focuses on single parent households, on which there is very little literature.

While it is recognised that the involvement of children in sustainable tourism change and development is crucial the fact remains that information on their worldviews and sustainable tourism behaviour is scarcely available. One long-term empowerment strategy countries and governments around the world can implement is by promoting children's rights through responsible education. This chapter articulates one tactic of that strategy at the local action level of school excursions, which is seen as an instrument that can be made most effective when it is initiated with the assumption that it is needed to help our younger generation acquire an environmental worldview, is harnessed in coalition with collaborators and, applied around the ‘moral’ obligation of educational institutions to provide agency to students' voice. Of the 17 Goals of Sustainable Development, SDG4 (Quality) Education can make a critically important contribution to progress. A series of activities and initiatives undertaken in informal educational environments such as field trips and school excursions can contribute to educating children, building their awareness about responsible and sustainable tourism practices, and developing an environmental sensitivity. Excursion activities and destinations such as museum exhibits have the opportunity to shape identities—through access to objects, information and knowledge. Visitors can see themselves and their culture reflected in ways that encourage new connections, meaning making and learning. Upon looking into transformational experiences in museums it was found that students were easily able to articulate that ‘aha’ moment, particularly around thinking differently about issues and taking action for environmental and sustainable changes.

This chapter explores how technology availability and costs influence public opinion, vehicle ownership decisions, travel, and location choices. Attitudes towards electric vehicles (EVs) are considered within the broader context of other linked technological trends affecting automobility, with a particular focus on the shift to (electric powertrain) autonomous vehicles (AVs).

This chapter draws upon modelling of quantitative survey data from 1,426 Americans, which employed regression analysis to predict and understand variables linked to the preference for an AV over a human driver, percentage of trips taken by an AV, percentage of trips using dynamic ride-sharing (DRS) inside a shared autonomous vehicle (SAV), and factors affecting EV charging access in home and at work/school.

The findings show that full EV charging times significantly affect decisions for next household vehicle purchase. A lack of charging ability at home appears to be a significantly greater hindrance to respondents’ willingness to purchase full EVs than does a lack of charging ability at work. And home location choice impacts of AVs are not expected to be substantial. Considering future EV/AV ride-sharing (an important component of sustainable future mobility systems), DRS may ease congestion if SAV riders widely adopt DRS for work and school trips; however, sharing with strangers may not be popular in practice.

This chapter is useful to manufacturers and fleet operators for pricing and marketing decisions, and public transit authorities/providers can benefit from understanding evolving travel choices and land use patterns to craft equitable policies, and model future transportation demand to help plan services and infrastructure projects.

The purposes of this study are to explore children’s independent mobility, that is the degree to which children of different ages are allowed to make trips to school, friends, shops, and other destinations unaccompanied by adults within the Arab communities in Israel and to study the influence of the demographic and socio-economic characteristics, built environment, geographical location, cultural context, and risk perceptions on children’s independent mobility.

This study is based on a questionnaire given to children between 9 and 15 years old studying in 4th to 9th grades and to one parent or primary caregiver. The methodology of this study is based on descriptive statistics comparing independent mobility licenses and travel behavior of two school children groups: Arab and Jewish children. In addition logistic regression models were developed to study the influence of different factors on independent mobility such as: car availability, gender, age, social class, and so on. In order to examine whether children with independent mobility do more and have access to a wider range of activities than those who do not, a linear regression analysis was performed with the dependent variable being the number of unaccompanied journeys to the various activities in the weekend.

Results clearly show that boys were granted greater freedom in terms of mobility licenses, as were secondary school children compared with those attending primary school. Walking is still the main commuting mode to school. One of the important findings in this study is that children are not interested in walking. That is, regardless of the built environment and parents driving options, children prefer to be driven.

This study will provide essential information for the development of policies and interventions in urban planning, transport planning, community development, community safety initiatives, and health planning.

This study is among the first to examine levels of independent mobility among the Arab school children in Israel, as well as their participation in active transport (e.g., walking/cycling) during journeys to school and to other local destinations.

Therefore, this study will hopefully provide a baseline for future studies in this area and act as a catalyst for more research into independence and mobility, and how this impacts sustainability.

This case, along with its B case (UVA-QA-0865), is an effective vehicle for introducing students to the use of machine-learning techniques for classification. The specific context is predicting customer retention based on a wide range of customer attributes/features. The specific techniques could include (but are not limited to): regressions (linear and logistic), variable selection (forward/backward and stepwise), regularizations (e.g., LASSO), classification and regression trees (CART), random forests, graduate boosted trees (xgboost), neural networks, and support vector machines (SVM).

The case is suitable for an advanced data analysis (data science, machine learning, and artificial intelligence) class at all levels: upper-level business undergraduate, MBA, EMBA, as well as specialized graduate or undergraduate programs in analytics (e.g., masters of science in business analytics [MSBA] and masters of management analytics [MMA]) and/or in management (e.g., masters of science in management [MScM] and masters in management [MiM, MM]).

The teaching note for the case contains the pedagogy and the analyses, alongside the detailed explanations of the various techniques and their implementations in R (code provided in Exhibits and supplementary files). Python code, as well as the spreadsheet implementation in XLMiner, are available upon request.

Increasing physical activity can reduce obesity risk among adolescents. This study analyses how behaviours, ethnicity and various sociocultural characteristics may influence the likelihood of engaging in active commute and other healthy activities. The authors analyse data from the 2010 National Youth Physical Activity and Nutrition Survey. The sample included US Hispanic high school students from 9th to 12th grade. Quasi-Poisson regression was used to understand the association between 24 possible variables and the number of days physically active at least 60 minutes per day. This study will present findings by race and ethnicity: non-Hispanic whites and blacks, as well as Hispanics. The research findings uncover that walking is the most predominant physical activity among Hispanics, especially from school to home, which indicates engagement in active transportation. This study shows the need for tailoring physical activity and health programmes by race and ethnicity. Interventions that encourage active commute can be effective for adolescents to achieve physical activity guidelines – at least 60 minutes per day.

Active school travel (AST) programmes aim to change commuting behaviour to improve children's physical and mental health. However, very limited health education programmes for children use segmentation to create tailored solutions that understand the specific characteristics of each group of children and their caregivers in order to yield better results. The aim of this study is to use a statistical segmentation analysis (two-step cluster analysis) to gain insights on the examination of specific groups to design future health education interventions and campaigns that can improve children's health.

Guided by the Ecological and Cognitive Active Commuting (ECAC) framework, a market segmentation analysis was performed. An online survey was designed to collect data from caregivers of children between 5 and 12 years attending school and responsible for taking the child to and/or from school in Victoria and Queensland, Australia. Using 3,082 responses collected from Australian caregivers of primary school children, a two-step cluster analysis was performed.

Analysis revealed the most important variables for group formation were previous child walking behaviour, distance from school and caregiver income. Perceived risk of the physical environment was the most important psychographic segmentation variable for group formation, followed by social norms. Four distinct groups with different characteristics were identified from the analysis.

This is the first study that applies the ECAC framework to perform market segmentation in the AST context. Results revealed four market segments that demand different tailored solutions. Findings shed light on how to better design AST interventions and campaigns to promote children's health using segmentation techniques.