While some conflict can serve as a more sophisticated stimulus to student achievement, significant or unresolved conflict can delay or even frustrate even the best-planned curriculum. The aim of our study is to get a clear picture of the conflicts with whom and to what extent the international students studying on our campuses have conflicts that affect their performance, and how they can manage them. In our study, based on a questionnaire survey (n = 480), we revealed that the international students at our university have the most conflicts with other foreign students, and the least with Hungarians, including their teachers. On the other hand, we found that according to the Thomas-Kilmann Conflict Instrument, they solve their problems by the Compromising and Accommodating style. The results obtained by detailed socio-demographic aspects show significant differences, mainly between gender, age, and country groups. Knowledge of the revealed facts and connections can offer conscious and careful solutions to understand and reduce tensions, and this can improve the understanding and management of conflict in the classroom, in collaborative projects, and even in non-teaching environments on campuses.

This study explores the integration of data mining, customer relationship management (CRM), and strategic management to enhance the understanding of customer behavior and drive revenue growth. The main goal is the use of application of data mining techniques in customer analytics, focusing on the Extended RFM (Recency, Frequency, Monetary Value and count day) model within the context of online retailing. The Extended RFM model enhances traditional RFM analysis by incorporating customer demographics and psychographics to segment customers more effectively based on their purchasing patterns. The study further investigates the integration of the BCG (Boston Consulting Group) matrix with the Extended RFM model to provide a strategic view of customer purchase behavior in product portfolio management. By analyzing online retail customer data, this research identifies distinct customer segments and their preferences, which can inform targeted marketing strategies and personalized customer experiences. The integration of the BCG matrix allows for a nuanced understanding of which segments are inclined to purchase from different categories such as “stars” or “cash cows,” enabling businesses to align marketing efforts with customer tendencies. The findings suggest that leveraging the Extended RFM model in conjunction with the BCG matrix can lead to increased customer satisfaction, loyalty, and informed decision-making for product development and resource allocation, thereby driving growth in the competitive online retail sector. The findings are expected to contribute to the field of Infrastructure Finance by providing actionable insights for firms to refine their strategic policies in CRM.

This study aims to construct an integrative model for understanding the factors that shape Chinese tourists’ intentions to visit Thailand as a gastronomic tourism destination. In detail, we investigate the relationships among cognitive experiences, emotional experiences, cultural experiences, affective destination image, cognitive destination image, and the intention to visit Thailand for culinary experiences. Utilizing an online survey method to gather 562 Chinese tourists who have experienced Thai gastronomy, this study continues to use structural equation model to process data. The findings reveal that cognitive, emotional, and cultural experiences significantly influence tourists’ affective and cognitive destination images, positively impacting their intention to visit Thailand for its culinary offerings. The affective and cognitive destination images act as crucial mediators, intricately linking these experiences with travel intentions. This approach improves our understanding of the dynamics involved. It also provides practical insights for developing targeted marketing strategies.

Soil salinization is a difficult challenge for agricultural productivity and environmental sustainability, particularly in arid and semi-arid coastal regions. This study investigates the spatial variability of soil electrical conductivity (EC) and its relationship with key cations and anions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, CO₃²⁻, HCO₃⁻, SO₄²⁻) along the southeastern coast of the Caspian Sea in Iran. Using a combination of field-based soil sampling, laboratory analyses, and Landsat 8 spectral data, linear Multiple Linear Regression and Partial Least Squares Regression (MLR, PLSR) and nonlinear Artifician Neural Network and Support Vector Machine (ANN, SVM) modeling approaches were employed to estimate and map soil EC. Results identified Na⁺ and Cl⁻ as the primary contributors to salinity (r = 0.78 and r = 0.88, respectively), with NaCl salts dominating the region’s soil salinity dynamics. Secondary contributions from Potassium Chloride KCl and Magnesium Chloride MgCl₂ were also observed. Coastal landforms such as lagoon relicts and coastal plains exhibited the highest salinity levels, attributed to geomorphic processes and anthropogenic activities. Among the predictive models, the SVM algorithm outperformed others, achieving higher R² values and lower RMSE (RMSE_Test = 27.35 and RMSE_Train = 24.62, respectively), underscoring its effectiveness in capturing complex soil-environment interactions. This study highlights the utility of digital soil mapping (DSM) for assessing soil salinity and provides actionable insights for sustainable land management, particularly in mitigating salinity and enhancing agricultural practices in vulnerable coastal systems.

Night tourism, increasingly recognized as integral to the travel experience, has gained attention for its impact on overall tourist satisfaction. This article offers a comprehensive analysis of night tourism development in Vietnam’s coastal cities, focusing on Nha Trang and Quang Ngai, as representative cases of mature and emerging destinations, respectively. Utilizing the Importance-Performance Analysis (IPA) tool, the study aims to provide practical insights for sustainable night tourism. Surveys with 524 domestic tourists were conducted to evaluate perceptions and satisfaction levels. Nha Trang emphasizes accessibility and vibrant nightlife, with a focus on the night market and outdoor shows. Conversely, Quang Ngai highlights its night landscape, dining options, and shopping areas. Recommendations for both destinations include enhancing entertainment offerings and reassessing priorities based on tourist preferences. The study underscores the need for tailored strategies to foster sustainable night tourism development that aligns with evolving tourist demands in coastal cities like Nha Trang and Quang Ngai.

The Yangjiabu Kite Festival, originating over 2000 years ago in Shandong Province, China, stands as a testament to the enduring cultural heritage and artistic traditions of kite flying. This research explores the historical origins, cultural symbolism, festival format, community engagement, and international exposure of the Yangjiabu Kite Festival, shedding light on its evolution and impact over time. Findings reveal the festival's deep roots in ancient Chinese traditions, its role as a platform for showcasing cultural diversity and craftsmanship, and its significance in promoting tourism, cultural exchange, and soft power projection for Shandong Province. Lessons learned from the Yangjiabu Kite Festival offer valuable insights for cross-cultural application, event management, cultural diplomacy, and community development. Suggestions for future research include comparative studies, longitudinal assessments, audience research, and policy analysis to further explore the dynamics and implications of cultural festivals in a global context. Overall, the research underscores the importance of cultural festivals as vehicles for cultural preservation, tourism promotion, and intercultural dialogue, fostering mutual understanding and appreciation across borders.