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Drawing on the integrative perspective of the technology acceptance model (TAM) and theory of planned behaviour (TPB) and extending it further by examining the role of organisational facilitators and perceived HR effectiveness in this integrative perspective, we examine HR professionals’ AI-augmented HRM (HRM^(AI)) acceptance in this research.

The data (N=375) were collected from HR professionals working in different organisations in India. Structural equation modelling (SEM) was employed to analyse the data.

The results of the study suggest that along with organisational facilitator antecedents to the relevant components of both TAM and TPB, perceived HR effectiveness also enhanced the HRM^(AI) acceptance levels of HR professionals.

The research findings are expected to contribute to the understanding of the factors that influence the acceptance of AI-augmented HRM in organizations. The results may also help organisations to identify the facilitators that can enhance the adoption and implementation of AI-augmented HRM by HR professionals. Finally, the study provides a composite TAM-TPB theoretical framework that can guide future research on the acceptance of AI-augmented HRM.

To the best of our knowledge, this is one of the first attempts to factor in the effect of contextual factors (i.e. organisational facilitators and perceived HR effectiveness) in the TAM and TPB equations.

This study aims to examine the integration of AI in student engagement and its benefits in the learning environment.

The study employed a quantitative research method, analyzing data from a sample of 720 students. The econometric data analysis used the structural equation modeling (SEM) technique.

The results show that facilitating conditions and performance expectations positively affect students’ attitudes toward AI, whereas the negative impact of perceived risk is statistically weak and only marginally significant at the 90% level. On the other hand, the main findings are that attitudes significantly influence the use of AI, which consequently increases students’ productivity, performance, and self-efficacy.

Through the integration of new variables in the TAM and UTAUT models, steps are suggested for institutions to take to increase the acceptance and efficiency of AI.

This study introduces a novel approach to AI integration within higher education, presenting an innovative model that significantly enhances the discourse on AI’s tangible impacts on educational processes.

The utilization of mobile fitness applications (apps) is on the rise, making user retention and engagement critical factors in the commercial success of these apps. However, research in this area is limited and fragmented. The objective of this study is to conduct a thorough review of the available literature on the effects of digital innovations, gamification, artificial intelligence (AI) and machine learning (ML) on user engagement with fitness mobile apps. The findings reveal the relationships between gamification, the use of AI/ML and technology adoption on user engagement, interaction and intent to use. Additionally, the study highlights the importance of understanding how user experience, customer experience and brand experience impact customer retention and contribute to the overall success of mobile fitness apps. Furthermore, the study also identifies the gaps in the current research and recommends further studies to be conducted in these areas. Future research is encouraged to incorporate elements from the experience domains to provide consumers with engaging interactions and improve retention and commercial success for mobile fitness apps.

Tourism value chain (TVC) analysis has been widely used as an alternative approach for designing sustainable and inclusive programs for tourism development in Africa, Asia, and the Pacific. This chapter looks at the experiences of three sustainable tourism initiatives in the Philippines to assess the strengths and limitations of the value chain as a framework for destination development. Short case studies describe the experiences of stakeholders in two popular destinations in the Philippines: the surfing town of San Juan, La Union, and the resort-island of Panglao, Bohol. The third case study shares the perspective of the Transforming the Tourism Value Chain (TTVC) project, a national campaign for more sustainable hotels, resort as well as meetings, conventions, incentives, and event (MICE) facilities in various destinations around the country. Stakeholders deeply involved in implementing these projects share their insights on the successes, challenges, and limitations of TVC-based approaches to resilient and sustainable destination development. The destinations' experiences suggest that the advocacy for sustainable management and operations may be comparable to a process of technology adoption or acceptance along the TVC. Practical and theoretical recommendations for leveraging the TVC toward more holistic and sustainable visitor economies are given at the end of this chapter.

This study aims to investigate the impact of consumer ethnocentrism on consumers' evaluation of blockchain-based traceability information. It also examined how the use of quick response (QR) codes for traceability affects consumers' evaluation of traceable food products.

An online choice experiment was conducted to determine consumers' evaluation of the blockchain-based traceability of Feta cheese with a quota sample of 715 Greek consumers. Pearson bivariate correlation and mean comparison were used to examine the relationship between consumer ethnocentrism and QR use behaviour. Random parameter logit models were employed to examine consumers’ valuation of the examined attributes and interaction terms.

The results show that ethnocentric consumers are willing to pay more for blockchain-based traceability information. Ethnocentric consumers tend to scan QR codes with traceability information. Spending more time reading traceability information embedded in QR codes does not lead to a higher willingness-to-pay (WTP) for traceable food products.

The findings suggest that patriotic marketing messages can draw consumers' attention to blockchain-based traceability information. The modest WTP for and low familiarity with blockchain-based traceability systems raise the need for educating consumers regarding the benefits of blockchain in traceability systems.

This is the first study to provide timely empirical evidence of a positive WTP for blockchain-based traceability information for a processed dairy product. This study is the first to attempt to distinguish the effects of the intention to scan QR codes and reading information embedded in QR codes on consumers’ valuation of food attributes.

Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.

We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.

Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.

Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.

This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

The technology acceptance model (TAM) is a widely used framework explaining why users accept new technologies. Still, its relevance is questioned because of evolving consumer behavior, demographics and technology. Contrary to a research paper or systematic literature review, the purpose of this critical reflection paper is to discuss TAM's relevance and limitations in hospitality and tourism research.

This paper uses a critical reflective approach, enabling a comprehensive review and synthesis of recent academic literature on TAM. The critical evaluation encompasses its historical trajectory, evolutionary growth, identified limitations and, more specifically, its relevance in the context of hospitality and tourism research.

TAM's limitations within the hospitality and tourism context revolve around its individual-centric perspective, limited scope, static nature, cultural applicability and reliance on self-reported measures.

To optimize TAM's efficacy, the authors propose several strategic recommendations. These include embedding TAM within the specific context of the industry, delving into TAM-driven artificial intelligence adoption, integrating industry-specific factors, acknowledging cultural nuances and using comprehensive research methods, such as mixed methods approach. It is imperative for researchers to critically assess TAM's suitability for their studies and be open to exploring alternative models or methods that can adeptly navigate the distinctive dynamics of the industry.

This critical reflection paper prompts a profound exploration of technology adoption within the dynamic hospitality and tourism sector, makes insightful inquiries into TAM's future potential and presents recommendations.

The purpose of this study is to explore the complex interplay between technology, personal norms and emotional factors in shaping the sustainable housing choices of millennials in emerging economies. It integrates the model of goal-directed behavior, technology acceptance model and norm activation model, incorporating both self-interest and prosocial motivations. Key adaptations involve replacing perceived behavioral control with financial self-efficacy and substituting hedonic motivation for anticipated positive emotions. Moreover, it introduces location as a practical anchor.

A quantitative, cross-sectional and descriptive research design was used in this study. Data were gathered from a sample of 610 millennial residential real estate investors across Indian smart cities. A multistage stratified sampling technique was used to ensure a representative sample. For data analysis, partial least squares structural equation modeling was used. The analysis focused on hypothesis testing to examine the relationships between the constructs of interest. Bootstrap t-values and effect sizes were used to assess the significance and magnitude of these relationships, respectively.

One of the key findings of this study was the establishment of significant positive relationships between awareness of consequences, ascription of responsibility and personal norms with behavioral intentions. This underscored the importance of personal ethical considerations in shaping intentions. Perceived usefulness and ease of use were found to significantly influence attitudes positively, highlighting the relevance of these factors in forming favorable attitudes toward behaviors. Attitude, subjective norms, financial self-efficacy and location played significant positive roles. However, negative anticipated emotions decreased desire. This illustrated the complex role emotions play in motivational processes. The study also revealed that subjective norms did not significantly contribute to shaping personal norms. This indicated a potential decoupling of societal expectations from personal ethical obligations in the decision-making process.

This study offers actionable insights for both policymakers and real estate developers. For policymakers, the findings highlight the need to craft initiatives that go beyond mere awareness, instead fostering a deep sense of personal responsibility and environmental stewardship among potential homebuyers. For real estate developers, the emphasis on financial self-efficacy and location suggests a strategy shift toward designing sustainable homes that not only meet environmental standards but also align with buyers’ financial confidence and geographic preferences. Together, these strategies can drive a more widespread adoption of sustainable housing, making sustainability a tangible and appealing choice for millennials.

To the best of the authors’ knowledge, this empirical research study was one of the first studies that contributed to the literature by integrating the model of goal-directed behavior, technology acceptance model and norm activation model. This study thus offered a nuanced understanding of the interplay between normative influences, usability perceptions, ethical considerations and emotions in the context of behavioral intentions.