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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

This study examines digital hospitality as a socio-technical system in which technological adoption and human resource (HR) practices jointly shape guest experiences and workforce dynamics. The research is situated at CitizenM hotels in Paris, a brand recognized for its integration of mobile applications, automated check-in, and the ambassador model of flexible role design. A mixed-methods approach was applied, combining a guest survey (n = 517) with semi-structured interviews with managers. Exploratory and confirmatory factor analyses confirmed a five-factor structure of guest perceptions: Digital Efficiency, Smart Personalization, Service Satisfaction, Trusted Security, and Digital Loyalty. Structural equation modeling showed that efficiency significantly drives satisfaction, while personalization and security strongly predict loyalty. Managerial insights revealed that these outcomes rely on continuous investment in training, mentorship, and flexible role allocation. Overall, the findings suggest that digital transformation enhances value creation not by substituting but by reconfiguring human service, with technology alleviating routine tasks and enabling employees to focus on relational and creative aspects of hospitality. The study concludes that effective digital hospitality requires the alignment of technological innovation with supportive HR practices, ensuring both guest satisfaction and employee motivation. Full article

Non-destructive measurement of leaf size based on leaf length and/or width is a simple, economical, and precise methodology. Leaf morphometric indicators were measured on 55 coffee progenies obtained from intraspecific and interspecific crosses. The estimation of parameters in the models and the testing of hypotheses related to these were performed. The relationships between leaf width and length, the ellipticity index, and leaf size were subsequently analyzed with a partitioning algorithm. The groups were then compared using Hotelling’s T² test. In coffee, the Montgomery model allowed for an adequate estimation of leaf size for each progeny, hybridization type, and grouped data. An α value of 0.67000 for the Montgomery model was consistent. This finding indicates that it is a suitable model for both individual and groups of progenies. The model based on the “principle of similarity” was found to be suitable only on a per-progeny basis. Certain characteristics, such as the leaf width-to-length ratio, ellipticity index, and leaf size, modify the parameter fit to inherent values. Similarly, leaves with a higher width-to-length ratio were the most elliptical for coffee, according to the groupings found. The estimation of coffee leaf size improves if the selected model considers whether they come from specific progenies or groups of progenies. Full article

Despite the recognized importance of digital transformation, there remains a research gap regarding the specific mechanisms through which digital leadership enables organizations to translate digital strategies into sustainable outcomes. This study addresses this gap by examining the role of digital leadership (DL) as a critical driver of digital transformation (DT), while highlighting the mediating effects of artificial intelligence (AI) and digital innovation (DI). Drawing on the Dynamic Capabilities Theory, we conceptualize DL as a sensing and seizing capability that mobilizes organizational resources to foster AI adoption and support DI, thereby achieving transformational resilience. Using a convenience sample of 346 employees from five-star hotels and class-A travel agencies in Greater Cairo, Egypt, data were analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that DL has a strong direct impact on DT and, more importantly, an indirect effect through enhancing AI productivity and enabling DI. This dual pathway advances theoretical understanding of how digital leadership shapes transformation processes and offers practical evidence for tourism and hospitality firms seeking to sustain competitiveness in dynamic market environments. Full article

This study examines how psycholinguistic features of online reviews relate to guest satisfaction in Bali’s spa hotel market. Using LIWC-22 category rates from Google Maps reviews, a corpus of 15,560 quality-filtered reviews from ten leading spa hotels was analyzed. Exploratory factor analysis yielded four interpretable dimensions—Social, Health and Wellness, Emotional Tone, and Lifestyle. In regressions predicting review star ratings (satisfaction), Social (β = 0.028) and Health and Wellness (β = 0.023) showed small but statistically detectable positive associations, whereas Emotional Tone (β = 0.006, t = 0.727) and Lifestyle (β = 0.004, t = 0.476) were not significant. The model’s explained variance is negligible (R² = 0.001; F = 5.283, p < 0.05), reflecting the many influences on ratings beyond review language; findings are interpreted as directional associations rather than predictive effects. Practically, the results point to prioritizing interpersonal service cues and wellness/treatment assurances, with tone monitoring being used for service-recovery signals. The design favors interpretability (validated, word-based categories; full-history snapshot) over black-box complexity, and transferability is Bali-specific and conditional on comparable market features. Future work should add contextual covariates (e.g., price and location), apply explicit temporal segmentation, extend to multilingual corpora, and triangulate text analytics with brief questionnaires and qualitative inquiry to strengthen validity and explanatory power. Full article

This paper examines how 360-degree panoramic tours can enhance heritage promotion, accessibility, and engagement, illustrated through two case studies: the Understory Art and Nature Trail in Northcliffe and the Subiaco Hotel in Perth, Western Australia. The Understory Art Trail was deployed in Google Street View to deliver an interactive, virtual walkthrough of outdoor art installations. This made the site accessible to a geographically diverse global audience, including those unable to visit in person. In contrast, the Subiaco Hotel tour was created with 3DVista. It integrated multimedia features such as historical photographs, architectural drawings, and narrative audio, offering users a layered exploration of built heritage. The two studies were designed so that frameworks like Technology Acceptance Model (TAM) could be applied to them to evaluate visitor experience. However, this paper focuses on the workflow for providing 360-degree panoramic tours, the integration of AR, low-cost digital twins, and the testing of interactive web platforms. Google Street View demonstrates ease of use through familiar navigation, while 3DVista reflects usefulness through its richer interpretive features. By analyzing workflows and digital strategies on both platforms, the study evaluates their effectiveness in increasing online visitor engagement, supporting heritage tourism, and communicating cultural significance. Challenges related to technical limitations, geolocation accuracy, audience targeting, and resource constraints are critically discussed. The findings demonstrate that context-sensitive applications of 360-degree tours are valuable for visibility, education, and long-term preservation. The paper concludes with targeted recommendations to guide future heritage projects in leveraging immersive digital technologies to expand audience engagement and support sustainable heritage management. Full article

Grounded in the Conservation of Resources (COR) theory, this study investigates how negative workplace gossip (NWG) influences counterproductive work behavior (CWB) in the hospitality industry. It further examines the mediating role of self-esteem and the moderating influence of emotional contagion in shaping this relationship. While prior research has predominantly treated NWG as a social stressor or reputational threat, this study extends the COR theory by explicitly modeling the resource depletion mechanism, specifically, the erosion of self-esteem as a key pathway linking NWG to CWB. By doing so, it posits that gossip erodes self-esteem, a fundamental psychological resource that eventually leads to behavioral retreat or revenge. Within the COR framework, the study also presents emotional contagion as a unique moderating variable, emphasizing how individual differences in emotional susceptibility may either accelerate or buffer the process of resource loss. Data was collected from 437 employees working in five-star hotels in Sharm El-Sheikh using a structured questionnaire. Analysis via PLS-SEM revealed that NWG significantly increases CWB, both directly and indirectly, by undermining employees’ self-esteem. Additionally, self-esteem was found to mediate the NWG–CWB link, while emotional contagion moderated the impact of NWG on self-esteem, suggesting that individuals with better emotional regulation can maintain self-worth in the face of workplace gossip. The study offers both theoretical and practical insights, highlighting the value of incorporating emotional contagion within the COR theory to understand and manage gossip-induced stress. It also underscores the importance of emotional intelligence and HR practices such as training and selection in minimizing the harmful effects of gossip at work. Full article

The issue of organizational sustainability is pivotal in the hospitality industry in the face of increasing environmental and societal pressures. This research investigates the mediating roles of green knowledge sharing (GKS) and green employee voice (GEV) on talent management (TM) strategic contribution to strengthen organizational sustainability (OS). Based on the Social Exchange Theory, TM is conceptualized as the consequence of employee engagement in sustainability behaviors in relational processes. the data were collected from 268 employees working at five-star hotels in the Eastern Region, Saudi Arabia. The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to evaluate the hypotheses. The results indicate that TM has direct positive influence on OS, GKS, and GEV, which determines its central position in development of environmentally friendly workforce. GEV and GKS also have direct influences on OS, and therefore marketplace advocacy and knowledge exchange are essential to embedding sustainable practices. Mediation analyses show GKS and GEV can partially mediate the TM and OS relationship, proving that the impact TM has on sustainability is further facilitated by the green sharing of knowledge and proactive voice by the employees. Both theoretical and practical implications for both academics and practitioners have been addressed. Full article

This article solves the anomalies’ operational detection in the network traffic problem for cyber police units by developing an adaptive neural network platform combining a variational autoencoder with continuous stochastic dynamics of the latent space (integration according to the Euler–Maruyama scheme), a continuous–discrete Kalman filter for latent state estimation, and Hotelling’s T² statistical criterion for deviation detection. This paper implements an online learning mechanism (“on the fly”) via the Euler Euclidean gradient step. Verification includes variational autoencoder training and validation, ROC/PR and confusion matrix analysis, latent representation projections (PCA), and latency measurements during streaming processing. The model’s stable convergence and anomalies’ precise detection with the metrics precision is ≈0.83, recall is ≈0.83, the F1-score is ≈0.83, and the end-to-end delay of 1.5–6.5 ms under 100–1000 sessions/s load was demonstrated experimentally. The computational estimate for typical model parameters is ≈5152 operations for a forward pass and ≈38,944 operations, taking into account batch updating. At the same time, the main bottleneck, the O(m³) term in the Kalman step, was identified. The obtained results’ practical significance lies in the possibility of the developed adaptive neural network platform integrating into cyber police units (integration with Kafka, Spark, or Flink; exporting incidents to SIEM or SOAR; monitoring via Prometheus or Grafana) and in proposing applied optimisation paths for embedded and high-load systems. Full article

This study aims to bridge the research gap emerging from the relationships between Visual electronic Word-of-Mouth (VeWOM) and brand factors, and their impact on consumers’ behavior by exploring the causal effects of eWOM attributes on hotel brand factor spreading through Brand Awareness (BA) and Brand Perceived Value (BV) and its consequences on Purchase Decisions (PD) in the hospitality context. Attribution Theory was extended to incorporate brand-mediated effects and crisis-specific factors. The study investigates the impact of VeWOM on consumer Purchase Decisions (PD) in terms of hotel room bookings in the British hospitality market, emphasizing the mediating role of brand-related constructs. Drawing on Attribution Theory, the research proposes a structural model to assess both direct and indirect pathways through which VeWOM influences behavioral outcomes. A stratified, non-probability sampling approach yielded 443 valid responses from hotel bookers who engaged with user-generated visual content prior to booking. The Partial Least Squares Structural Equation Model (PLS-SEM) was employed to test the hypothesized relationships. The findings reveal that VeWOM significantly influences Brand Value (BV), eWOM Credibility, and Information Quality, which in turn shape consumer purchase behavior. Crucially, Brand Value emerges as a key mediating variable, bridging VeWOM and Purchase Decisions, while VeWOM alone does not directly affect booking behavior. Moreover, Brand Awareness showed no significant mediating effect. The study underscores the indirect attribution process in visual review contexts, demonstrating that the influence of VeWOM is channeled primarily through brand perception mechanisms rather than direct persuasion. These insights extend Attribution Theory by highlighting the distinct cognitive pathways activated by visual content compared to text-based reviews. Practically, the research suggests that hoteliers should focus on enhancing Brand Value via bundled offerings and relationship-based marketing rather than relying solely on visual appeal or awareness to drive bookings. The study contributes to the growing body of VeWOM literature by clarifying its nuanced effects on decision-making in digital hospitality environments. Full article

In this article, we study a directed version of Douglas–Rachford splitting method in real Hilbert spaces. By using new, self-contained, and simplified techniques, we prove its weak convergence. The major innovation is that we exploit the firm non-expansiveness of the Douglas–Rachford operator for the first time to derive the best possible upper bounds on direction factors, assuming that the involved factors remain constant. We give a new rare feature selection model equipped with the TripAdvisor hotel-review dataset. Numerical results confirm the user-friendliness and efficiency of directed Douglas–Rachford splitting in solving this model. Full article

The development of information technology allows firms to access consumer purchase records, enabling them to distinguish between new and old consumers. Firms can then provide these groups with respective product pricing and promised delivery time. This paper develops a two-period dynamic model based on game theory to examine the effects of behavior-based pricing and behavior-based promised delivery time strategies on product price, promised delivery time, firm profits, consumer surplus, and social welfare under conditions where consumers exhibit time-sensitive preferences. We find, first, when firms opt to implement behavior-based pricing and promised delivery time strategies, they should offer lower (higher) prices and longer (shorter) delivery times to new (old) consumers. Second, the implementation of behavior-based pricing and promised delivery time strategies may decrease firm profits while enhancing consumer surplus. Third, when consumers exhibit stronger time-sensitive preferences, behavior-based pricing and promised delivery time strategies can enhance social welfare; conversely, they may have a detrimental impact on social welfare. Finally, we extend the model into three aspects—asymmetric strategy selection, firm logistics service costs, and myopic consumer behavior—to enrich our research and test the robustness of the model. The results of this paper supply managerial implications and theoretical references for firms’ strategic implementation and policy-making by relevant government departments. Full article

Cross-category innovation in digital platform ecosystems is increasingly pivotal for competitive reconfiguration, and the value it generates for users primarily stems from the benefits of network effects. By extending the spatial competition framework of the Hotelling model through a four-stage sequential game comprising category competition, we formalize the strategic mechanism for expanding network effects governing benchmark competition and category dynamics. The cross-category innovation strategy proposed in this paper offers valuable insights in three key areas: investment in core technological advantages, reconstruction of user cognitive boundaries, and strengthening ecological dependency within the ecosystem. By transcending the limitations in the explanatory power of traditional management theories for cross-organizational boundary issues, this study integrates digital contexts into its analytical framework, thus providing a novel perspective for understanding the dynamic processes of cross-category innovation in digital platform ecosystems. Full article

This study examines how hotel characteristics and urban spatial context influence tourist satisfaction in Seoul, South Korea, by integrating sentiment analysis of online reviews with regression modeling. Drawing on 4500 TripAdvisor reviews from 75 hotels, sentiment scores were extracted using aspect-based sentiment analysis, and two regression approaches, ordinary least squares (OLS) and spatial autoregressive combined models, were applied to evaluate how hotel specific features, such as the age and scale of the hotels and room rates, and their geographic characteristics, such as the proximity to airports and cultural landmarks, affect both emotional sentiment and formal hotel ratings. The OLS model for sentiment scores identified the scale and rating of the hotels as well as the proximity to the airports as key predictors. Additionally, the spatial autoregressive combined model was also statistically significant, suggesting spatial spillover effects. A separate model for the traditional rating revealed weaker associations, with only the hotel’s opening year reaching significance. These findings highlight a divergence between emotional responses and structured ratings, with sentiment scores more sensitive to spatial context. This study offers practical implications for hotel managers and urban planners, emphasizing the value of incorporating spatial factors into hospitality research to better understand the tourist experience. Full article

In the Mexican Caribbean, the demand for tourism services led to the expansion of the hotel industry from the coast inland. This caused rural and urban communities in the region to become involved in tourism activities, initiating the formulation of an international model of sustainable development with a focus on cultural tourism. Considering the tourism potential that the study area can offer to nearby rural communities, as well as the limited number of studies aimed at estimating tourism carrying capacity (see examples of TCC for environmental management units in communal land areas like Baja California, Mexico and the Huagapo cave in Peru), the present research aims at estimating the tourism carrying capacity in the southern region of the Mexican Caribbean. A mixed methodological approach was adopted for the present study entailing a detailed description of flora and fauna in the study area using natural resource mapping tools, social diagnosis of the communities in the study area using the Participatory Action Research (PAR) technique in the communities of Caobas and San José de la Montaña and the estimation of tourism carrying capacity (TCC), Physical Carrying Capacity (PCC), Real Carrying Capacity (RCC), and Effective Carrying Capacity (ECC) using information gathered through fieldwork and bibliographic review. It was found that the area can support a tourism carrying capacity of 538.33 visits per day. In this initial assessment, it was estimated that the implementation of an ecotourism project in a rural community would not alter its environmental conditions. The estimated indicators provide appropriate tools for designing and planning long-term sustainable tourism proposals. Moreover, they integrate environmental, economic, and social aspects in a balanced manner, generating tangible and lasting benefits. Full article