Search Results (73)

This article presents an ontology-driven Digital Twin (DT) for hotel front-desk operations that fuses two real-time data streams: (i) physiological and activity signals from wrist-worn wearables assigned to staff, and (ii) 3D people-positioning and occupancy events captured by reception-area cameras using a proprietary implementation of Optical Camera Communication (OCC). Building on a previously proposed front-desk ontology, the semantic model is extended with positional events, zone semantics, and wearable-derived workload indices to estimate queue state, staff workload, and service demand in real time. A vendor-agnostic, property-based REST API specifies the DT interface in terms of observable properties, including authentication and authorization, idempotent ingestion, timestamp conventions, version negotiation, integrity protection for signed webhooks, rate limiting and backoff, pagination and filtering, and privacy-preserving identifiers, enabling any compliant backend to implement the specification. The proposed layered architecture connects ingestion, spatial reasoning, and decision services to dashboards and key performance indicators (KPIs). This article details the positioning pipeline (calibration, normalized 3D coordinates, zone mapping, and confidence handling), the wearable workload pipeline, and an evaluation protocol covering localization error, zone classification, queue-length estimation, and workload accuracy. The results indicate that a spatially aware, ontology-based DT can support more balanced staff allocation and improved guest experience while remaining technology-agnostic and privacy-conscious. Full article

In the digital tourism marketplace, online reviews have become a decisive source of information for travelers who cannot directly assess the quality of hospitality services before purchase. However, it remains unclear how service-related and sustainability-related cues interact to shape guest perceptions in sustainable hotel contexts. This study investigates how intrinsic and extrinsic cues are reflected in online user reviews of sustainable hotels. Drawing on Cue Utilization Theory, a longitudinal content analysis was conducted on a worldwide online travel platform’s (OTP) reviews of hotels certified for their sustainability practices (2004–2024) by user selection. A coding framework was developed deductively based on prior studies on hotel service quality and sustainability practices, and data were analyzed using MAXQDA, Leximancer, and VADER sentiment analysis. Findings indicated that reviews primarily emphasize service quality attributes—particularly staff efficiency, food quality, and accommodation facilities—while sustainability themes appear less frequently, often in nature-related contexts. Sentiment analysis revealed a predominantly positive emotional tone shaped by service quality experiences. Overall, intrinsic cues play a central role in forming guest perceptions, highlighting the need for emotionally engaging sustainability communication strategies. Full article

This research focuses on the effects of leadership styles on the implementation of Green Human Resource Management (Green HRM) initiatives in hotels in Greece by staff members, and it recognizes the lack of sustainability research in the Mediterranean hospitality sector. Employing the Full-Range Leadership Model, we explore the impact of transformational, transactional, and passive leadership on the implementation of environmental HR practices. The data for this study were obtained from 216 employees in 29 hotels in Greece, who completed the Multifactor Leadership Questionnaire (MLQ-5x) and a Green HRM instrument. Several regression analyses showed that transformational leadership was the most robust positive predictor of Green HRM practices, followed by leadership outcomes and transactional leadership. On the other hand, passive leadership was significantly inversely associated with Green HRM implementation. Demographic variables, such as gender, age, and experience, had a substantial impact on both perceptions of leadership and involvement in Green HRM as well. The results offer significant theoretical implications and practical directions for improving environmental performance in hospitality organizations through the strategic use of leadership development and human resource management intervention. Full article

The rapid integration of artificial intelligence (AI) and smart technologies is transforming hospitality operations, yet guest acceptance remains uneven, shaped by utilitarian, experiential, ethical, and cultural evaluations. This study develops and empirically tests a multicomponent framework to explain how these factors jointly influence two behavioral outcomes: whether AI-enabled features affect hotel choice and whether guests are willing to pay a premium. A cross-sectional survey of 689 hotel guests in Tirana, Albania, an emerging hospitality market and rapidly growing tourist destination in the Western Balkans, was analyzed using cumulative link models, partial proportional-odds models, nonlinear and interaction extensions, and binary robustness checks. Results show that prior experience with smart or AI-enabled hotels, higher awareness, and trust in AI, especially trust in responsible data handling, consistently increase both acceptance and willingness to pay. Perceived value, operationalized through the breadth of identified benefits and desired features, also exhibits robust positive effects. In contrast, privacy concerns selectively suppress strong acceptance, particularly financial willingness, while cultural–linguistic fit and support for human–AI collaboration contribute positively but modestly. Interaction analyses indicate that trust can mitigate concerns about reduced personal touch. Open-ended responses reinforce these patterns, highlighting the importance of privacy, human interaction, and staff–AI coexistence. Overall, findings underscore that successful AI adoption in hospitality requires aligning technological innovation with ethical transparency, experiential familiarity, and cultural adaptation. Full article

Adaptive reuse of heritage buildings is a vital strategy for balancing cultural preservation with modern functionality needs. This study provides a post-adaptive reuse evaluation of Dar Al Saraya in Madaba, Jordan, a significant Ottoman-era landmark, to examine how adaptive reuse strategies influence interior environments and heritage value. The analysis employs Zhang and Zhang’s evaluation framework focusing on existing fabric, special character, and policy and value, operationalized through 15 factors. A qualitative methodology was adopted, integrating site observations, photographic documentation, and semi-structured interviews with heritage experts, municipal representatives, residents, visitors, and site staff. Fieldwork was conducted in two phases (November 2024 and October 2025) to capture evolving conditions and perceptions. Findings indicate that challenges in spatial reconstruction were few and well addressed, but gaps in adaptation and reuse function strategies created significant issues. These included a lack of coordinated policies and the failure of municipal authorities and property owners to sustain the building’s reuse and involve the local community in reuse decisions. Despite various initiatives, from a museum, hotel, cultural center and gallery to its recent adaptation into a café, these efforts lacked sustainability and inclusive strategic planning. Consequently, the café has faced difficulties since opening, leaving its future uncertain. These findings highlight the importance of post-adaptive reuse evaluation and of integrating policy, planning, and community participation into adaptive reuse strategies to promote sustainable, community-centred conservation. Full article

The hospitality sector is undergoing a rapid digital change due to smart technology and artificial intelligence. This presents both possibilities and problems for the development of sustainable innovation. Yet, little is known about how leaders’ technological competencies affect employees’ capacity to engage in environmentally responsible innovation. This study addresses this gap by examining how leaders’ competencies in smart technology, artificial intelligence, robotics, and algorithms (STARA) shape employees’ green innovative behavior in hotels. Anchored in person–job fit theory and cognitive appraisal theory, we propose that when employees perceive a strong alignment between their skills and the technological demands introduced by STARA, they are more likely to appraise such technologies as opportunities (challenge appraisals) rather than threats (hindrance appraisals). These appraisals, in turn, mediate the link between leadership and green innovation. Convenience sampling was used to gather data from staff members at five-star, ecologically certified hotels in Sharm El-Sheikh, Egypt. According to structural equation modeling using SmartPLS, employees’ green innovation behaviors are improved by leaders’ STARA abilities. Crucially, staff members who viewed STARA technologies as challenges (i.e., chances for learning and development) converted leadership skills into more robust green innovation results. Conversely, employees who perceived these technologies as obstacles, such as burdens or threats, diminished this beneficial effect and decreased their desire to participate in green innovation. These findings highlight that the way employees cognitively evaluate technological change determines whether leadership efforts foster or obstruct sustainable innovation in hotels. Full article

The COVID-19 pandemic reshaped travel patterns and customer expectations, generating profound challenges for the hotel industry. This study analyzes 50,000 TripAdvisor reviews of New York hotels to examine how customer satisfaction with hotel selection attributes shifted before and during the pandemic. BERTopic was applied to extract eight key attributes, while VADER, PRCA, and Asymmetric Impact–Performance Analysis (AIPA) were used to capture asymmetric effects and prioritize improvements. Comparative analyses by hotel classification, travel type, and customer residence reveal significant shifts in food and beverage, location, and staff, particularly among lower-tier hotels, business travelers, and international guests. The novelty of this study lies in integrating BERTopic and AIPA to overcome survey-based limitations and provide a robust, data-driven view of COVID-19’s impact on hotel satisfaction. Theoretically, it advances asymmetric satisfaction research by linking text-derived attributes with AIPA. Practically, it offers actionable guidance for hotel managers to strengthen hygiene, expand contactless services, and reallocate resources effectively in preparation for future crises. In addition, this study contributes to sustainability by showing how data-driven analysis can enhance service resilience and support the long-term socio-economic viability of the hotel industry under global crises. Full article

Aim: This study extends existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often overlooked group of stakeholders in the adoption of new technologies within the hotel sector. The objective of this research is to investigate the perceptions of hotel employees in Hong Kong regarding the implementation of Metaverse hotels. This study emphasizes their evaluations of the strengths, weaknesses, opportunities, and threats associated with these establishments through a SWOT analysis. Ultimately, the study aims to provide recommendations for addressing technological challenges, supporting employees during the transition, and facilitating adaptation across the industry. Design/Methodology/Approach: A convenience and purposive sampling method is employed to investigate 20 participants, comprising hotel staff from various departments in the Metaverse hotel in Hong Kong. This study adopts a qualitative research design, utilizing semi-structured interviews to gather in-depth insights into the perceptions of the Metaverse hotel among these employees. Purposive sampling ensures that participants have relevant experience and familiarity with VR/AR technologies. Interviews, each lasting 45–60 min, were conducted in person, with informed consent obtained beforehand. Findings: The exploration of hotel employees’ perceptions of Metaverse hotels in Hong Kong underscores the innovative potential of these establishments to enhance operational efficiency and guest engagement, while also offering new training opportunities and streamlining daily tasks. However, employees express concerns about the potential erosion of personal interactions, which are crucial to the hospitality experience, and foresee significant technical and integration challenges. Despite these drawbacks, Metaverse hotels present distinctive opportunities for market differentiation, appealing to tech-savvy guests and generating new revenue streams that contribute to industry growth. Nonetheless, potential threats such as guest skepticism and challenges in industry adaptation highlight the necessity for cautious implementation and robust privacy measures. Balancing these aspects—strengths, weaknesses, opportunities, and threats—will be pivotal for the successful integration of Metaverse technologies into the hotel industry. Theoretical/Practical Implications: Participants recognized that the Metaverse hotel could offer various potential benefits for both employees and businesses, such as enhanced operational efficiencies and new opportunities for guest engagement. Understanding the perceptions of hotel staff towards the Metaverse carries significant real-world implications for shaping policies, practices, and technologies that facilitate its operational success and market acceptance. Leveraging these insights enables the optimization of Metaverse’s advantages while mitigating associated risks and drawbacks. This study advances existing research by focusing specifically on the perceptions of hotel employees, a crucial yet often neglected group of stakeholders in the adoption of new technologies within the hospitality sector. By understanding the perspectives of hotel employees, this research provides valuable insights into the practical challenges and benefits of implementing Metaverse technologies in the hotel industry. Originality/Value: The Metaverse hotel is still relatively new and evolving, making it crucial to conduct research to understand how hotel staff perceive it. However, there is limited research specifically focusing on the perceptions of hotel employees regarding Metaverse hotels. This gap highlights the need for a comprehensive investigation into how employees perceive the strengths, weaknesses, opportunities, and threats of implementing the Metaverse in hotels. Full article

Workplace toxicity in the tourism sector remains a widespread issue, particularly for hotel staff who are constantly suffering from verbal, emotional, or physical abuse. While previous research has primarily highlighted the negative consequences of abusive behavior, this study examines a different perspective—how abusive supervision may be associated with reduced helping behavior among hotel employees, with emotional contagion and self-esteem serving as key moderating and mediating variables. Based on the Conservation of Resources (COR) theory, the current paper suggests that abusive supervision causes people’s psychological resources to be depleted, which decreases their self-esteem and, in turn, their helpful behavior. Furthermore, it is revealed that emotional contagion can act as a moderator to amplify the detrimental association between abusive supervision and self-esteem. Data were gathered from frontline hotels employees. Employing structural equation modeling with SmartPLS 3, the findings reveal that abusive supervision was negatively related to both self-esteem and helping behaviors. Additionally, the correlation between helpful behavior and abusive supervision was strongly mediated by self-esteem. It is also shown that emotional contagion mitigated the detrimental relationship between abusive supervision and self-esteem, such that people with high emotional contagion experienced a stronger negative relationship. This paper advances our theoretical knowledge of workplace dynamics by expanding COR theory to justify how and why abusive supervision impairs pro-social behavior. From a practical standpoint, the findings underscore the significance of management behavior and emotional intelligence in service-oriented sectors. Employee self-esteem and cooperative workplace behavior may be preserved by interventions that deplete supervisory abuse and boost emotional resilience. Full article

Economic growth, especially in emerging economies, has altered the composition of international tourism. It is therefore essential to possess the skills necessary to understand the influence of culture on human behaviour, thereby enabling an appropriate response to the traveller. This research aims to develop a tool for identifying openness, flexibility, awareness, and intercultural preparedness. It focuses on the metacognitive and cognitive aspects of cultural intelligence that shape the development of empathy in customer service staff in hotels in Quintana Roo. The variables were validated and incorporated into a quantitative study using multivariate analysis and inferential statistics. A sample of 77 questionnaires was analysed using simple random sampling under a proportional design. Multiple Correspondence Analysis (MCA) was employed as a discriminatory technique to identify the most significant independent variables. These were subsequently entered as regressors into ordinal logistic regression (OLR), along with age and work experience, in order to estimate the probabilities associated with each level of the dependent variable. The results indicated that age had minimal influence on the metacognitive and cognitive variables, whereas years of experience among tourism staff exerted a significant effect. Full article

The implementation of Digital Twins (DTs) in hospitality facilities represents a significant opportunity to optimize front-end services, enhancing guest experience and operational efficiency. This paper proposes an ontology-driven approach for DTs in hotel reception areas, focusing on integrating IoT devices, real-time data processing, and service optimization. By modeling interactions between guests, receptionists, and hotel management systems, DTs enhance resource allocation, predictive maintenance, and customer satisfaction. Simulations and historical data analysis enable forecasting demand fluctuations and optimizing check-in/check-out processes. This research provides a structured framework for DT applications in hospitality, validated through scenario-based simulations, showing significant improvements in check-in time and guest satisfaction. Validation was conducted through scenario-based simulations reflecting real-world operational challenges, such as guest surges, room assignment, and staff workload balancing. Metrics including check-in time, guest satisfaction index, task completion rates, and prediction accuracy were used to evaluate performance. Simulations were grounded in historical hotel data and modeled typical peak-period dynamics to ensure realism. Results demonstrated a 25–35% reduction in check-in time, a 20% improvement in staff efficiency, and significant enhancements in guest satisfaction, underscoring the practical value of the proposed framework in real hospitality settings. Full article

This paper aims to compare the perceptions of hotel customers and hotel staff regarding the value of green hotel attributes. By examining both stakeholder groups, the study addresses a gap in sustainable hospitality research, which largely overlooks employee perspectives in favour of customer preferences. An exploratory, cross-sectional survey was conducted using structured questionnaires, administered to hotel guests (n = 307) and hotel staff (n = 89) in Porto, Portugal. Respondents rated 15 green hotel attributes using a five-point Likert scale. Demographic data were also collected to analyse perceptual differences across gender, age, income, and education. The results revealed that both customers and staff exhibited environmental awareness, though their prioritisation of specific green practices differed. Customers tended to value visible environmental measures, such as recycling bins, energy-saving light bulbs, and renewable energy signage, while staff placed greater emphasis on operational sustainability aspects, including low-flow plumbing fixtures, refillable soap dispensers, and durable goods used in service areas. These differences reflect the stakeholders’ distinct roles and experiences within the hotel ecosystem. This study enriches the discourse on sustainable hospitality by providing a dual-stakeholder analysis of green hotel attributes using a shared evaluative framework. The findings offer practical insights for hotel managers aligning sustainability strategies with the expectations of both guests and employees, supporting more effective and inclusive green implementation in the lodging sector. Full article

This study highlights the importance of managing and analyzing customer reviews to gain a competitive advantage and improve customer experience in the hospitality industry. In this context, a deep learning-based sentiment analysis system of hotel customer reviews is developed to evaluate service quality within the scope of sustainable tourism. The study analyzed 15,522 customer reviews of five-star hotels in Antalya using text mining, topic modelling, and deep learning-based sentiment analysis. The reviews were classified as positive, negative, or neutral. The findings show that Hotel HB2 has the highest performance, with an F1 score of 97.9%. Overall customer satisfaction is 91%, while emotional satisfaction stands at 77%. Key factors, such as cleanliness, food quality, and staff professionalism, were found to play a critical role in customer loyalty. Additionally, this study integrates sustainability-orientated themes by identifying customer feedback related to environmentally friendly practices and sustainable hotel operations. The results provide evidence that customer satisfaction is not only influenced by service quality but also by the perceived environmental and social responsibility of the hotel. Machine learning techniques have emerged as effective tools for analyzing large-scale customer reviews, offering valuable insights to rapidly and accurately capture customers’ emotions, expectations, and perceptions. As a comprehensive application of sentiment analysis and text mining, this research offers hotel managers a practical framework to enhance service quality, foster customer loyalty, and develop sustainability-orientated strategies. This study contributes to the literature by linking AI-driven sentiment analysis with sustainability practices in the tourism sector. Full article

Businesses in the hotel and hospitality sectors face significant challenges when they lack originality and creativity. Creativity and innovative behavior are both necessary to increase employee effectiveness. This study aims to investigate how psychological empowerment (PEMP) directly affects employee creativity (EC) and affective commitment (AC) in the Saudi hotel industry. Additionally, this study examines the moderating function of psychological safety (PS) and the mediating role of affective commitment. Data were collected through an online cross-sectional survey of a purposive sample of 536 operational staff at hotels in the Eastern Region of Saudi Arabia. Structural equation modeling was used to test the proposed framework (PLS-SEM). Surprisingly, these findings revealed no significant direct effect of PEMP on EC. However, AC has emerged as a crucial mediating mechanism through which PEMP indirectly fosters creativity. Furthermore, psychological safety (PS) is found to moderate the PEMP–EC relationship, enhancing its impact under favorable conditions. These results highlight the theoretical and practical significance of emotional commitment as a conduit for empowering employees to engage in creative behavior. This study offers new insights into how psychological and organizational factors interact to shape creativity in the hospitality context. Full article

Although integrating smart technologies into service encounters can provide hoteliers with a competitive advantage, managing customer satisfaction in smart hotels remains challenging due to limited knowledge of how to prioritize improvements across smart service and traditional service. Therefore, the study aims to evaluate customer satisfaction with both smart and non-smart technology attributes in smart hotels, identify attributes with high improvement priorities, and uncover factors contributing to customer dissatisfaction. This study proposes a prioritization method for service improvement in smart hotels by analyzing online reviews from 42 smart hotels. The findings reveal that customers’ technological needs are well met in smart hotels, but smart hotels need to promptly address three key issues: long check-in wait times, staff attitude and competence, and breakfast quality. To maximize customer satisfaction, managers should adopt a hybrid service model that strikes the right balance between technology and human interaction. Full article