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The deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.

An empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.

Results showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.

Insights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

The current inquiry advances the public relations field and practice in several ways. First, this research addresses a clear gap in research on subjective well-being, specifically among PR professionals across career stages and generations. Second, the findings reveal important generational similarities and differences in how PR practitioners talk about well-being. This provides an empirical basis for developing tailored, multi-generational approaches to supporting well-being in PR workplaces. Lastly, this research provides practical implications for PR professionals to understand generational perspectives and to implement flexible policies to improve well-being.

The current study explored subjective well-being (SWB) across generations of public relations professionals. Using a qualitative approach, semi-structured interviews were conducted with 12 PR practitioners at various career levels – entry, mid-level and senior.

Analysis revealed several similarities but a key disparity among cohorts. Senior-level professionals specifically reported struggling with work–life balance and the perceived ability to be autonomous, while entry-level professionals expressed commitment to setting boundaries on their time. These findings highlight a need for the PR industry to establish flexible workplace standards that enable employees at different career stages to collaborate and support one another’s well-being.

Our findings will appeal to your readers who seek to cultivate employee subjective well-being and understand generational issues via qualitative methods. By conducting a qualitative study in an understudied area, PR industry leaders and managers can support employee well-being across generations and career stages.

Our study is the first to examine generational dispositions as it relates to SWB across the public relations industry.

As a smart service, location-based advertising (LBA) integrates advanced technologies to deliver personalized messages based on a user’s real-time geographic location and needs. However, research has shown that privacy concerns threaten the diffusion of LBA. This research investigates how privacy-related factors (i.e. LBA type, privacy self-efficacy (PSE) and consumer generation) impact consumers’ value-in-use and their intention to use LBA.

This study developed and examined an LBA value-in-use framework that integrates the role of LBA type, consumers’ PSE and consumer generation into the technology acceptance model (TAM). Data were collected through two experiments in the field with a total of 374 consumers. The proposed relationships were tested using PROCESS modeling.

The results reveal that pull (vs push) LBA causes higher value-in-use in terms of perceived usefulness and perceived ease of use, leading to greater usage intention. Further, the differences in the mediated relationship between pull- and push-LBA are larger among consumers of low PSE (vs high PSE) and Generation Z (vs other generations). The findings suggest that the consumer value-in-use brought about by LBA diminishes when using push-LBA for low PSE and Generation Z consumers.

This research is the first to integrate the privacy-related interactions of LBA type and consumer characteristics into TAM to develop a TAM-based LBA value-in-use framework. This study contributes to the literature on service value-in-use, smart services and LBA by clarifying the boundary conditions that determine the effectiveness of LBA in enhancing consumers’ value-in-use.

Applying the Innovation Resistance Theory, this study aims to examine the effects of contextual and trait stressors on consumer engagement and wellbeing in the context of service robots.

Data were collected from 560 users who interacted with a service robot at a library and a museum. The data were analyzed using Smart PLS 4.0.

The findings show the significant negative effects of perceived intrusion on consumer engagement and wellbeing. In addition, technology anxiety exhibited a significant positive effect on consumer engagement and wellbeing, whereas consumer engagement predicted wellbeing. Moreover, the findings highlight the importance of consumer engagement as a key mediator between the stressors and wellbeing.

The findings equip service managers with the necessary information to effectively integrate service robots in an inclusive manner that resonates with consumer engagement and wellbeing.

This research uses field data to empirically validate the effects of contextual and trait stressors on consumer resistance to service robots.

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.

This chapter critically explores the transformative role of Artificial Intelligence (AI) in higher education, highlighting both the opportunities it presents and the challenges it imposes. Focused on pedagogical enhancement, it details how AI-driven adaptive learning systems, tutors, and curriculum adjustments contribute to personalized education. It further examines AI's efficiency in streamlining administrative tasks, like enrollment and support services, while addressing significant ethical concerns, including data privacy and algorithmic bias. Moreover, the impact of AI on research and development is discussed, showcasing its potential to revolutionize scientific discovery through advanced data analysis. A strategic framework is proposed for stakeholders to effectively navigate AI integration and digital transformation, emphasizing a balanced approach that prioritizes innovation, ethical considerations, and quality in the digital era of higher education.

This chapter highlights the key areas for the leadership and innovation research agenda in 2035. This agenda will direct researchers’ focus to the core transversal skills that individuals must have amidst the shift toward a greener and digitalized economy. Such skills include leadership, management, creativity, communication, and adaptability. The role of macro governmental policies and micro organizational policies is of great significance to ensure the implementation (if any) of these changes and of core to the research agenda. This chapter will also guide researchers to the challenges at the higher education level that need to be addressed to ensure the balance between the skills and knowledge acquired by workers through education and the needs of businesses in order to increase productivity and innovation.

This study uses computer-aided design to improve the ecological and environmental sustainability of early-stage landscape designs. Urban expansion on open land and natural habitats has led to a decline in biodiversity and increased climate change impacts, affecting urban inhabitants' quality of life and well-being. While sustainability indicators have been employed to assess the performance of buildings and neighbourhoods, landscape designs' ecological and environmental sustainability has received comparatively less attention, particularly in early-design stages where applying sustainability approaches is impactful.

The authors propose a computation framework for evaluating key landscape sustainability indicators and providing real-time feedback to designers. The method integrates spatial indicators with widely recognized sustainability rating system credits. A specialized tool was developed for measuring biomass optimization, precipitation management and urban heat mitigation, and a proof-of-concept experiment tested the tool's effectiveness on three Mediterranean neighbourhood-level designs.

The results show a clear connection between the applied design strategy to the indicator behaviour. This connection enhances the ability to establish sustainability benchmarks for different types of landscape developments using parametric design.

The study allows non-expert designers to measure and embed landscape sustainability early in the design stages, thus lowering the entry level for incorporating biodiversity enhancement and climate mitigation approaches.

This study expands the parametric vocabulary for measuring landscape sustainability by introducing spatial ecosystem services and architectural sustainability indicators on a unified platform, enabling the integration of critical climate and biodiversity-loss solutions earlier in the development process.