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Critical social marketing can play a vital role in countering the consequences of behaviours toxified by commercial marketing. This paper aims to hypothesise that auto sector brand activities may be associated with riskier driving.

In this paper, the authors hypothesised that auto sector brand activities may be associated with riskier driving. UK collision data was examined, focusing on collisions that occurred because of an “injudicious action” (risky or aggressive driving manoeuvres) and analysing this data set by comparing the incidence of vehicle brands involved.

After allowing for other effects, a gradient graph illustrated differing associations between vehicle brands and collision rates.

A discussion was offered, adopting the position that if such a problem exists the solutions cannot be left to the sector itself, and that socially responsible interventions may be required. A number of social marketing strategies are proposed including regulatory support, “Truth Campaign” style exposure of commercial damage, and counter-marketing that promotes safe driver behaviour.

This work provides valuable empirical support to the concerns raised by previous workers about the possible effects of automotive sector advertising on driving behaviour. The paper offers a concise discussion of ways forward, concluding with the novel possibility of regulating individual brands as an alternative to sector-wide regulation.

Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.

The authors co-designed and implemented four arts-integrated data literacy units with 10 teachers of arts and mathematics in middle school classrooms from four different schools in the USA. The data include student-generated artwork and their written rationales, and interviews with teachers and students. Through maximum variation sampling, the authors identified examples from the data to illustrate disciplinary synergies and tensions that appeared to support different IIR processes among students.

Aspects of artistic representation, including embodiment, narrative and visual image; and aspects of the culture of arts, including an emphasis on personal experience, the acknowledgement of subjectivity and considerations for the audience’s perspective, created synergies and tensions that both offered and hindered opportunities for IIR (i.e. going beyond data, using data as evidence and expressing uncertainty).

This study answers calls for humanistic approaches to data literacy education. It contributes an interdisciplinary perspective on data literacy that complements other context-oriented perspectives on data science. This study also offers recommendations for how designers and educators can capitalize on synergies and mitigate tensions between domains to promote successful IIR in arts-integrated data literacy education.

The main purpose of this paper is to outline the antecedents of patient satisfaction in the field of medical tourism (MT) applying extant literature and to develop a conceptual model based on the review.

This paper presents a thorough review of prior studies related to the antecedents of patient satisfaction in the MT sector. Moreover, it provides the theoretical base that helped the researcher to identify significant relationship between the patient satisfaction and its antecedents.

The researchers identified the prominent antecedents of patient satisfaction and present the potential interrelationships between different antecedents of patient satisfaction such as treatment quality, cost attractiveness, destination image and service quality with patient satisfaction based on the review.

The results have momentous practical implications as they will help researchers to better understand the antecedents of patient satisfaction and their potential inter linkages with patient satisfaction in MT sector. The conceptual model derived from the review may guide the actions of researchers as well as practitioners in the MT industry as a whole. The present study provides insights for further research in the MT sector and thereby helps to further enrich the existing theoretical base of the MT.

The study brings together the scattered knowledge from the broad and extensive range of medical or health tourism and cognate literature which indicate ideological differences among various aspects of MT as well as potential factors determining patient satisfaction in MT sector (antecedents of satisfaction). The newly developed model incorporates a new construct called “treatment quality” as different from “service quality,” which is a widely used construct to explain customer satisfaction. The antecedents of patient satisfaction and their inter-linkages with patient satisfaction provide a sound theoretical foundation for the future studies.

This chapter examines the University of Connecticut (UConn) Neag School of Education's efforts to improve the recruitment of students of colour through an Early College Experience (ECE) Programme. During the pandemic, the School of Education and the ECE Programme collaborated to train and certify high school teachers to instruct the UConn's lower level undergraduate courses. The programme exposed many students of colour to teaching as a career.

This culminating chapter reviews the impacts of the pandemic on global systems of education. Drawing on the insights of the preceding chapters, this chapter offers three ideas for the future. First, schools of education should engage in innovative learning experiences including in person, online and hybrid learning opportunities. Second, staff support and development are key areas for future growth. Similarly, the third area for future growth is deeper consideration of student well-being and development. The pandemic placed these ideas at the forefront of conversation, and schools of education are positioned to continue that conversation, taking action to create transformative educational experiences.

This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.

Entrepreneurship education is increasingly attracting attention as a means of fostering entrepreneurial activity and creating a culture of innovation. Developing students' entrepreneurial intentions is critical to promote entrepreneurship. This research is built on a mixed method approach of partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis.

The factors that influence students ‘entrepreneurial intentions are identified: business incubation programmes, non-reimbursable grants for entrepreneurial students, networking events to promote entrepreneurship, mentoring services, innovation labs for business idea validation and entrepreneurship courses. This knowledge can help develop effective entrepreneurship education programmes. The study also provides actionable insights for educational institutions and policymakers. It underscores the need for innovative educational platforms such as entrepreneurial bootcamps. It also highlights the value of advanced learning environments such as decision theatres to foster a culture of entrepreneurship and innovation.

The study contributes to the body of knowledge on entrepreneurship education. It highlights the need for a multidisciplinary approach to understand the factors that shape students’ entrepreneurial intentions.

Online medical repositories provide a platform for users to share information and dynamically access abundant electronic health data. It is important to determine whether case report information can assist the general public in appropriately managing their diseases. Therefore, this paper aims to introduce a novel deep learning-based method that allows non-professionals to make inquiries using ordinary vocabulary, retrieving the most relevant case reports for accurate and effective health information.

The dataset of case reports was collected from both the patient-generated research network and the digital medical journal repository. To enhance the accuracy of obtaining relevant case reports, the authors propose a retrieval approach that combines BERT and BiLSTM methods. The authors identified representative health-related case reports and analyzed the retrieval performance, as well as user judgments.

This study aims to provide the necessary functionalities to deliver relevant health case reports based on input from ordinary terms. The proposed framework includes features for health management, user feedback acquisition and ranking by weights to obtain the most pertinent case reports.

This study contributes to health information systems by analyzing patients' experiences and treatments with the case report retrieval model. The results of this study can provide immense benefit to the general public who intend to find treatment decisions and experiences from relevant case reports.

High turnover rates, delay and dissatisfaction among PhD students about the high efforts and low rewards are common problems in doctoral education. Research shows that many different factors are associated with the mental health crisis in graduate education, but these diverse aspects have not often been studied in relation to talent management and human resource management (HRM) strategies. Based on questionnaires and in-depth interviews, this chapter critically assesses the factors that influence doctoral students’ well-being, using as theoretical framework the self-determination theory, concerned with the social and other conditions that facilitate or hinder human well-being and flourishing, and the job demands–resources model, an occupational stress model that suggests strain is a response to imbalance between demands on the individual and the resources he or she has to deal with those demands. These theoretical frameworks help to explore the perceived job demands and resources, and motivations of a sample of 25 PhD students in the Netherlands, in order to recommend adequate talent management strategies to improve PhD work conditions at universities and reduce the increasing levels of ill-being. The study proposes a collegial model, focussing on the enjoyment of work, instead of the current managerial model, which focusses on strengthening knowledge and skills, and stimulating performance-oriented behaviour. A differentiated approach is needed, offering customized talent development for each PhD student in order to respond to his or her specific qualities, improving general well-being. This radical shift in talent management is needed to counter the mental health crisis in doctoral studies.

Drawing upon a systematic literature review in new technology, innovation transfer and diffusion theories, and from interviews with technology leaders in digital transformation programs in the US Oil & Gas (O&G) industry, the authors explore the relationships among O&G industry dynamics, organization's absorptive capacity and resource commitment for new digital technology adoption-implementation process.

The authors employed the empirical survey method to gather the data (a sample size of 172) in the US O&G industry and used structural equation modeling (SEM) to test the measurement model for validity and reliability and the conceptual model for hypothesized structural relationships.

The results provide support for the study’s causal model of adoption and implementation with positive and direct relationships between the initiation and trial stages, between the trial stages and the evaluation of effective outcomes and between the effective outcomes and the effective implementation stages of digital technologies. The results also reveal partial mediating relationships of industry dynamics, absorptive capacity and resource commitment between respective stages.

Based on the current study's findings, managers are recommended to pay attention to the evolving industry dynamics during the initiation stage of new digital technology adoption, to utilize the organization's knowledge-based absorptive capacity during digital technology trial and selection stages and to support the digital technology implementation project when the adoption decision of a particular digital technology has been made.

The empirical research contributes literature on digital technology adoption and implementation by identifying and demonstrating the importance of industry dynamics, absorptive capacity and resource commitment factors as mediating variables at various stages of the adoption-implementation process and empirically validating a process-based causal model of digital technology adoption and a successful implementation project that has been missing in the current body of literature on digital transformation.