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Amazon Explore is a new online experience product from Amazon, which offers live stream sightseeing of destinations around the world. This paper aims to provide a first insight into how exactly Amazon Explore enters the virtual experience (VE) industry, and discuss the possible implications of its business model for the future of virtual and offline travel experiences.

Qualitative and quantitative methods of content analysis methods were employed in this study. The sample of this research consisted of 175 Amazon Explore products. Firstly, the authors analysed the content of each product, and then quantitative method were used to present the data. With this analysis, the authors presented how Amazon Explore is testing the foundations for new business models, and discuss the possible implications for the future of tourism. One year later, those same Amazon Explore products were reviewed again to check development progress. The following were the main questions regarding VE: How interactive are Amazon Explore products? How does Amazon Explore aim to ensure the monetisation of these products in an economically sustainable way in order to go beyond the “freemium” business model, often associated with VE as just another destination marketing tool?

This article presents the discussions of VE and virtual reality (VR). The authors determined the level of interactivity of the diverse VE offered themes with a model of four levels of interactivity. The results show that the analysed products achieve mostly only low levels of interaction. Regarding monetisation, Amazon Explore shows three possible future directions in the development of VE: as a marketing tool, as an extension of the offline experience and as potentially someday replacing real travel as part of the future monetisation scenario.

The article offers the first insights into Amazon's extension into the realm of VE in two time periods in 2020 and 2021, and, based on these preliminary results, discusses four possible scenarios for the future development of VE monetisation.

This study sought to develop an aggregated assessment of the literature on the resource-based view (RBV). The main aim was to map the RBV field based on a systematic literature review (SLR) of 226 academic articles published in refereed journals from 1994 to 2022.

Two bibliometric analysis methods were used: bibliographic coupling and co-citation. These measures are complementary because bibliographic coupling is retrospective in nature and co-citation is forward-looking.

The analysis identified the most influential studies, top-cited articles and journals and six major thematic clusters: RBV, customer orientation and alliance portfolio, resource-based theory, firm performance, entrepreneurial orientation (EO) and dynamic capabilities.

This research was based on a combination of bibliographic coupling and co-citation analysis. The results provide a better understanding of the RBV field’s intellectual structure, which reveals potential new lines of future research.

The purpose of this study is to offer insight into present dynamics and study diversification in the field of organizational psychology. This research study offers an organized and critical examination of the construct of psychological detachment using bibliometric analysis.

This study was done using the Scopus database based on studies published between 2006 and 2024. The significance of the research is evaluated by looking at the distribution volume, the trajectory of the publication, statistics techniques, extremely cited articles, journals, most frequently used keywords, research themes, subthemes clusters and thematic overview of the psychological detachment corpus created based on bibliographic coupling. Furthermore, content analysis of recent publications to identify new developments and potential gaps in the existing literature.

This research first tracked the development of this discipline’s body of literature through time and discovered a continuous rise starting in 2015. The results also highlighted crucial concepts that were studied with psychological detachment, such as work-life balance, employment outcomes, emotional exhaustion and various other demographic variables. Researchers chose to concentrate on those subtopics throughout time.

This research relied solely on Scopus data, which, despite being the largest abstract and citation database covering articles from a wide range of fields, does not include Impact Factor or Social Science Citation Index (SSCI) data, which is one of the limitation.

The findings of this research study will assist organizations and practitioners in comprehending the implications of psychological detachment construct at their workplace and give them direction on how they come out from negative job-related outcomes (employee job stress, turnover intention and burnouts at their respective workplaces).

This study offers a diversity of study topics across the psychological detachment literature by applying a variety of bibliographical mapping techniques, making it the first of its type on the topic of psychological detachment. It also indicates promising avenues for further investigation.

This study generates an aggregated overview of the literature on national culture and entrepreneurship (NC&E). The aim is to map the NC&E field via a systematic literature review of 130 articles published in refereed academic journals up to the end of 2022

Two different citation analysis methods are used: bibliographic coupling and co-citation

The results include the most influential studies, top-cited references and journals, and five major thematic clusters. The latter are (1) cultural models, frameworks and case studies; (2) social entrepreneurship, perceived barriers and entrepreneurial intentions; (3) institutions and sociocultural environments; (4) entrepreneurial orientation, cognition and networks; and (5) economic growth, entrepreneurial activity and firm performance

In contrast to previous NC&E literature reviews, this research employs a combination of bibliographic coupling and co-citation analysis. The findings offer a clearer understanding of the intellectual structure of this field and suggest new avenues for future investigations, including several relationship links with the resource-based view

This paper aims to systematically review the application of artificial intelligence (AI) in the tourism industry. By integrating human–computer interaction, machine learning, big data and other relevant technologies, the study establishes a comprehensive research framework that explores the systematic connections between AI and various facets of tourism.

This paper conducts a keyword co-occurrence analysis of 4,048 articles related to AI in tourism. The analysis identifies and classifies dominant topics, which are further refined through thematic literature review and manual coding for detailed discussion.

The analysis reveals five main topics: AI’s impact on tourist experience, AI in tourism marketing and prediction, AI in destination management, AI’s role in tourism enterprises and AI integration in strategic and regulatory framework. Each topic is reviewed to construct an integrated discussion that maps the current landscape and suggests directions for future research.

This paper transcends the fragmented discourse commonly found in the literature by establishing a unified framework that not only enhances understanding of the existing methodologies, theories and applications of AI in tourism but also identifies critical areas for breakthroughs, aiming to inspire a more humane and sustainable integration of AI in the tourism industry.

本文旨在系统回顾人工智能（AI）在旅游业中的应用。通过整合人机交互、机器学习、大数据和其他相关技术, 本研究建立了一个全面的研究框架, 探索人工智能与旅游业各方面之间的系统联系。

本文对4048篇与旅游业人工智能相关的文章进行了关键词共现分析。分析确定了主要议题并对其进行了分类, 然后通过主题文献梳理和手动编码对其进行了进一步完善, 以便进行详细讨论。

分析揭示了五个主要主题：人工智能与旅游体验、人工智能与旅游营销和预测、人工智能与目的地管理、人工智能与旅游企业, 以及人工智能在战略和监管框架中的整合。每个主题都进行了回顾, 以构建一个综合讨论, 勾勒出当前的研究格局, 并提出了未来的研究方向。

研究力图突破目前关于旅游与人工智能的碎片化讨论, 建立了一个统一的框架, 旨在加强对旅游业中人工智能现有方法、理论和应用的理解, 还点明了需要突破的关键领域, 以助力旅游业与人工智能共同创造更加人性化和可持续发展的前景。

Este artículo pretende revisar sistemáticamente la aplicación de la inteligencia artificial (IA) en el sector turístico. Mediante la integración de la interacción humano-ordenador, el aprendizaje automático, big data y otras tecnologías relevantes, el estudio establece un marco de investigación exhaustivo que explora las conexiones sistemáticas entre la IA y diversas facetas del turismo.

Este trabajo realiza un análisis de co-ocurrencia de palabras clave de 4.048 artículos relacionados con la IA en el turismo. El análisis identifica y clasifica los temas dominantes, sobre los que se profundiza mediante una revisión temática de la literatura y una codificación manual para su discusión detallada.

El análisis presenta cinco temas principales: El impacto de la IA en la experiencia turística, la IA en el marketing y la predicción turística, la IA en la gestión de destinos, el papel de la IA en las empresas turísticas y la integración de la IA en el marco estratégico y normativo. Cada tema se revisa para construir un debate integrado que trace el panorama actual y sugiera direcciones para futuras investigaciones.

Este artículo expande el análisis fragmentado que suele encontrarse en la bibliografía al establecer un marco unificado que no sólo mejora la comprensión de las metodologías, teorías y aplicaciones existentes de la IA en el turismo, sino que también identifica las áreas críticas para los avances, con el objetivo de inspirar una integración más humana y sostenible de la IA en la industria turística.

This study aims to explore the provision of accounting ethics education in Ethiopian accounting programs through structuration theory.

A qualitative case study methodology was used, and data were collected through semistructured interviews with faculty members, practitioners and regulatory bodies. The interview transcripts were analyzed using thematic analysis. Accounting curricula were also analyzed to triangulate and support the findings.

The study revealed a significant gap in the status of accounting ethics education, primarily attributed to a misunderstanding of its importance. While faculty initiatives and student interest have partially mitigated this gap, systemic challenges such as rigid curricula, a lack of awareness and commitment, resource constraints and limited stakeholders’ support persisted. A combined approach to accounting ethics education is required to foster ethical behavior. Hence, the structuration theory highlighted how meanings, power dynamics and norms and values constrained and enabled the provision of accounting ethics education.

The study emphasized the need for stakeholders to influence policymakers’ perceptions regarding the significance of accounting ethics education. The study also provided empirical support for structuration theory. Future research should involve cross-cultural comparisons and explore the ethical behavior of accounting professionals using diverse research designs to highlight the gaps and inform effective educational interventions.

This study contributes to the theoretical application of structuration theory in accounting ethics education. It underscores the critical role of comprehensive curricular reforms, stakeholder engagement and resource allocation.

The global construction industry faces both challenges and opportunities from electronic waste (e-waste). This study aims to present a bibliometric analysis and comprehensive literature assessment on e-waste in concrete construction materials.

This study studies 4,122 Scopus documents to examine garbage generation in different countries and inventive ways to integrate e-waste into construction as a sustainable strategy. This study lists famous researchers and their cooperation networks, demonstrating a robust and dynamic area with a surge in research output, notably from 2018 to 2022. Data is visually represented using VOS Viewer to show trends, patterns and study interests throughout time.

The findings imply that e-waste can improve construction materials’ mechanical characteristics and sustainability. The results are inconsistent and suggest further optimization. e-Waste into construction has garnered scientific interest for its environmental, life cycle, and economic impacts. This field has great potential for improving e-waste material use, developing sophisticated prediction models, studying environmental implications, economic analysis, policy formulation, novel construction methods, global cooperation and public awareness. This study shows that e-waste can be used in sustainable building. It stresses this area’s need for research and innovation. This lays the groundwork for using electronic trash in buildings, which promotes a circular economy and environmental sustainability.

The findings underscore the critical role of ongoing research and innovation in leveraging e-waste for sustainable building practices. This study lays the groundwork for integrating e-waste into construction, contributing to the advancement of a circular economy and environmental sustainability.

The social implications of integrating e-waste into construction are significant. Using e-waste not only addresses environmental concerns but also promotes social sustainability by creating new job opportunities in the recycling and construction sectors. It fosters community awareness and responsibility towards sustainable practices and waste management. Additionally, this approach can reduce construction costs, making building projects more accessible and potentially lowering housing prices.

This research contributes to the field by offering a bibliometric analysis and comprehensive assessment of e-waste in concrete construction materials, highlighting its global significance.

The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems.

Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners.

The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes.

The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process.

E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status.

A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

This study aims to investigate the effects of three dimensions of ChatGPT strategic value – organization support (OS), managerial productivity (IM) and decision aids (DA) – on the business sustainability (BS) of Malaysian public universities.

A quantitative methodology was adopted for this study to examine the relationships between ChatGPT strategic value and the BS of Malaysian public universities.

The study found that two dimensions of ChatGPT strategic value, namely, OS and IM, influence BS, whereas DA do not.

To the best of the author’s knowledge, this study is the first to address the relationship between ChatGPT strategic value and BS in a specific context – Malaysian public universities – providing new contributions to theory by extending the literature on the topic.

The findings are expected to guide universities in Malaysia in leveraging ChatGPT strategic value for enhancing BS.

To the best of the author’s knowledge, this empirical study is the first in the literature to examine the relationships between ChatGPT strategic value and BS in the education sector. Supported by an original conceptual model, the insights provided should extend the literature dedicated to ChatGPT strategic value and BS in the context of a South Asian economy.

This study explores the emergence of discrimination based on observable characteristics. In many instances, agents presume differences arising from traits such as race or gender, even when these parameters are irrelevant to the situation at hand. This paper intends to reveal an emergent behavior and a persistent culture of discrimination caused by miscategorization in strategic interactions.

We assume that agents occasionally engage in conflicts modeled as asymmetric hawk and dove games, where boundedly rational agents may categorize their opponents based on observable traits to make effective decisions. Three categorization strategies are considered: fine-grained, regular, and coarse-grained. Subsequently, an evolutionary agent-based model is employed to examine the performance of these strategies in a dynamic environment.

The results demonstrate that fine-grained categorization provides an advantage when the cost of fighting is low, while coarse-grained categorizers exhibit more peaceful behavior, gaining an advantage when the cost of conflict is high. Our primary finding indicates the emergence of discrimination based on non-relevant traits, manifested through consistent aggressive behavior towards individuals possessing these traits.

This paper is the first to investigate the emergence of discrimination without assuming prior differences between groups. Previous studies have assumed either an initial population difference or a homophily-based approach. In contrast, we demonstrate that discrimination can emerge even in the absence of such assumptions. Discrimination between two groups may arise as long as there are agents who label these categories.