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Creating green design capability readiness has become an emerging necessity toward increasing sustainable performance. However, the understanding of the green design readiness markers for housing delivery is lacking. The purpose of this study is to highlight a green design capability readiness model for affordable housing delivery.

Through the use of the self-determination theory and the Technology–Organization–Environment framework, a comprehensive review of related literature revealed 23 indicators on motivational, technological, organizational and environmental markers for green design practices capability readiness for affordable housing delivery. Adopting a deductive design, a questionnaire was developed from these markers for a survey on practitioners with knowledge and experience in green design, sustainability and housing supply chain through purposive and snowballing sampling. Mean score analysis and fuzzy synthetic evaluation were subsequently used to develop the capability readiness model.

This study affirmed the markers and revealed the top indicators in each of the markers. The markers subsequently accounted for 28%, 29%, 17.7% and 25.3% of green design capability readiness for affordable housing delivery. Accordingly, technological and motivational markers had the greatest contributions to green design readiness for affordable housing followed by environmental marker and organizational being the least.

The findings of this study will contribute to developing the right motivations, technological capability and regulatory factors for green design practices to optimize the capability readiness for affordable housing delivery in Ghana.

The model serves as a valuable resource that could be used to objectively align actions and gauge readiness for green design practices toward sustainability performance improvement in affordable housing delivery. It could also aid in benchmarking the readiness potential of future regulations, policies and motivations for green design practices, concepts and technologies for housing delivery.

The purpose of this study is to investigate the factors that influence customers’ green consumption intention by integrating social cognitive theory (SCT) and the cognitive affective conative (CAC) framework.

Survey questionnaire was employed to collect data. Then, this study adopts artificial neural network (ANN) to check the robustness of partial least squares-structural equation modelling (PLS-SEM) empirical results.

The findings confirm that social media marketing and collectivism are potent external stimuli to promote green consumption intention. Significant variables identified in the PLS-SEM analysis were used for ANN models, demonstrating the robustness of the PLS-SEM findings.

The primary theoretical contribution lies in the application of SCT theory and the CAC framework in the context of green consumption, an area that has been relatively underexplored in previous studies. Additionally, the study provides managerial implications for marketers by emphasising the significance of social media marketing and collectivism in influencing consumers’ cognition and affect.

The present study aims to investigate factors influencing Gen-Z consumers' “green food purchase intention” and “healthy lifestyle”. Guided by the attribution theory, “perceived usefulness of green food”, “food safety concerns” (internal attributes), “perceived threat of environmental problems” and “green peer influence” (external attributes) are considered the predictors of “attitude towards green food”, which eventually lead to a healthy lifestyle and green food purchase intention. Besides, “fear of pandemic recurrence” and “greenwash” are tested as moderators.

The Structural Equation Modelling-Partial Least Squares (PLS-SEM) technique was employed for the model testing. An online questionnaire survey was conducted among Gen-Z Chinese adults, which yielded 556 complete, valid responses.

The findings indicate that “consumers' attitudes towards green food” are positively influenced by “perceived threat of environmental problems”, “perceived usefulness of green food”, “concerns about food safety”, and the influence of “green peers”. In addition, results revealed that “attitude toward green food” exerts a positive effect on “healthy lifestyle” and “green food purchase intention”. The study supports the moderating role of “perceived greenwash” in the relationship between “attitude” and “intention to purchase green food”. However, there was no evidence to support the moderating effect of “fear of pandemic recurrence” in relation to a “healthy lifestyle”.

This study is a pioneer in utilizing the attribution theory to predict the drivers of a “healthy lifestyle” and the “intention to purchase green foods”. Furthermore, this study predicted the moderating influence of “fear of pandemic recurrence” on the relationship between attitude and “healthy lifestyle”, a link that has not been tested in previous research. Furthermore, it introduces a novel examination of the moderating effect of “perceived greenwash” on the relationship between “attitudes” and “purchase intentions”.

This paper aims to identify types of robot service failure stressors and explores its impact on emotional labor and recovery work engagement from the employees’ standpoint.

The research adopted a mixed-method approach in the hospitality industry in China, which included 25 hospitality workers participating in semi-structured interviews and 435 hospitality employees participating in a two-stage questionnaire survey.

Three types of robotic service failure stressors – illegitimate tasks, customer mistreatment and robotic instability – were identified. These stressors significantly influence emotional labor strategies in employee subsequently shaping their recovery work engagement through dual pathways. The sequential mediation effect of deep acting and service empathy serves to enhance recovery work engagement, whereas the sequential mediation effect of surface acting and workplace depersonalization diminishes this engagement. Human–robot collaborative climate moderates these effects in this context.

The findings from this study yield several implications for hospitality managers in managing employees and service robots to perform human–robot collaboration tasks.

Current research has primarily delved into how robot service failures impact customer experiences, leaving the effects on employees less explored. To the best of the authors’ knowledge, this paper is the first empirical study to explore the relationship between robot service failure and employee emotional responses and behaviors, enriching the literature on service robots in the hospitality industry and also proposing new directions and frameworks for future human–robot interaction research.

This paper investigates the integration of middle mile drones (MMD) into logistics operations, addressing two key questions: (1) What are the drivers, financial implications and upcoming innovations associated with integrating drones into MM logistics? and (2) What challenges need to be overcome for successful implementation of drones in MM logistics?

The study combines expertise from an industry professional with over ten years of experience in drone operations and logistics applications, along with insights gained from discussions with 33 industry executives.

The research identifies several unique advantages of integrating drones into MM logistics, including their potential to improve operational efficiency in challenging environments. However, significant challenges related to scalability, evolving airframe designs and operational constraints remain. Early-stage use cases demonstrate the viability of MMD technologies in lower-risk logistics environments, but broader implementation requires overcoming the identified challenges.

As MMD logistics is a nascent field, the study is exploratory and based on early-stage use cases and expert discussions. The limited scope of practical implementations may restrict the generalizability of the findings. Future research should focus on larger-scale operations and empirical studies of MMD integration in diverse logistics contexts.

The findings offer valuable insights for practitioners related to the costs, benefits and challenges of integrating drones into logistics operations and for policymakers related to societal implications, workforce development, privacy and safety concerns, and environmental impact.

This paper contributes to the evolving understanding of drone applications in MM logistics by presenting early use cases and identifying both challenges and opportunities for MMD technology and offers a foundation for future research and practice in this emerging domain.

This final chapter encapsulates the key moments and leadership lessons from Taylor Swift’s career. Throughout the book, we’ve seen Swift’s visionary leadership, creativity, resilience, and authenticity. By exploring her strategic decisions and transformative leadership style, we offer aspiring leaders actionable insights on setting clear goals, motivating others, embracing innovation, and leading with integrity. As we conclude, we shift from reflection to action, encouraging readers to apply these principles in their own leadership journeys.

This paper explores the profound philosophical and conceptual foundations that underpin comparative international education research, particularly concerning the evolving roles of universities and colleges that transcend mere skills training or human capital development in contemporary times. Universities and colleges have predominantly focused on measuring their success through criteria such as research excellence and their ability to adapt to the ever-evolving demands of the job market. It is imperative to recognize that the diversity of postsecondary institutions is not only providers of human capital with curriculum shaped by labor market needs; rather, they should be recognized as institutions dedicated to human development, community anchors, the promotion of the public good, democratic education, the cultivation of civil society, and global citizenship. Relying on an extensive review of selected literature pertaining to the mission, goals, aims, and roles of the postsecondary sector in three regions (East Asia, Germanic Europe, and North America), this paper considers the question, “How do different approaches and traditions in different social contexts contribute to our understanding of the civic roles of postsecondary education institutions in shaping future global citizens, transcending the confines of national boundaries?” Throughout the paper, the unique contexts and traditions of these regions are meticulously examined alongside thematic discussions, culminating in comprehensive analyses on what factors are considered as the civic roles of institutions and what challenges are there for them to realize their goals.

Integrating social comparison and social identity theories, this study aims to examine students’ emotional and behavioral responses to the use of ChatGPT in academic settings, focusing on intrinsic motivation, dissonance, envy, schadenfreude and artificial intelligence (AI) usage intentions.

The research design consisted of two sequential survey-based studies with undergraduate business students. Study 1, analyzed with SmartPLS, measured students’ intrinsic motivation, cognitive engagement, dispositional envy, emotional dissonance and schadenfreude experienced in response to academic dishonesty related to ChatGPT. Study 2 explored the motivations behind students’ future use of AI tools, examining ethical considerations and emotional responses.

Study 1 determined that higher levels of cognitive engagement reduce dissonance and envy among highly motivated students. Nevertheless, driven by cognitive engagement, dissonance and envy, it was established that highly motivated students experience schadenfreude when others are caught misusing ChatGPT. In contrast, low-motivated students only feel schadenfreude as a product of dissonance and envy. The focus of Study 2 was on the adoption of ChatGPT. Results indicate that future usage is driven by ethical considerations for highly motivated students, whereas less dissonance is key for low-motivated students.

The study’s originality lies in its exploration of schadenfreude in the context of AI use among students, highlighting how cognitive engagement and motivation influence emotional responses. Drawing on social comparison and social identity theories, it sheds new light on the dynamics of academic integrity and the emotional landscape surrounding AI tools like ChatGPT, thus filling a research gap in understanding student behavior and perceptions in higher education.