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Investigation on Tourism Trends Using K-means Clustering and Regression Analysis
Get PDFPurpose: The purpose of this study was to analyze tourism trends by determining the clusters of tourists based on common factors. Three (3) characteristics were explored using k-means clustering namely tourists’ demographics, travel patterns and travel preferences. These clusters were based on individual’s age, gender, country of origin, frequency of travel, travel destinations and seasons. Regression analysis was also performed to determine the factors that influence the length of stay of tourists in their travel destinations.
Methodology: This research conducted a survey from 150 respondents of different age groups, gender, and nationalities. Frequency of travel in a year, length of stay per travel, seasons, destinations, purpose of travel and preferred booking method were the parameters inquired in the survey. The collected dataset was utilized to characterize the clusters of tourists with common considerations. Additionally, regression analysis was used to forecast predictors influencing tourists’ length of stay.
Findings: Three (3) parameters were considered in performing k-means clustering such as tourists’ demographic profiles, travel patterns and preferences. Regression analysis likewise was employed to predict visitors’ length of stay using age, gender, purpose of travel, travel season, and preferred destination as independent variables. In participants’ demographics, number of clusters generated was k=5. Gender and nationalities were found to be randomly clustered while other parameters were categorized according to various age groups and frequency of travel. Consequently, for tourists’ travel patterns, age, gender, country of origin, frequency of stay, purpose of travel, length of stay and travel seasons were used as parameters. The elbow method knee-point revealed (k=6) as the optimal number of clusters. Moreover, travel preferences parameter was also considered for clustering where predictors like gender, age, country of origin, frequency of travel, purpose of travel, travel season and length of stay were utilized. The optimal number of clusters for this category generated K=5. Regression analysis revealed gender, age and purpose of travel as significant factors influencing tourists’ average length of stay. The combination of these variables generated the lowest value of MSE=0.64.
Research limitations/implications: A limited dataset of 150 respondents mainly from Asia and Middle East were utilized in performing preliminary initiatives in analyzing tourism trends. The predictors used in the analysis were restricted to gender, age, country of origin, travel frequency, length of stay, travel season and travel destinations. Supplementary parameters ca be considered in a big data setting for similar studies in the future. K-means clustering was selected among other algorithms with attributes commonality while regression analysis was employed to determine the factors influencing tourists’ length of stay in their destinations.
Social Implications: Results of this study will greatly support individual tourists in determining trends in various travel destinations. Similarly, business owners gain benefit forecasting travellers’ requirements such as accommodation, food, services, etc. Research findings likewise provide informed decisions for stakeholders
Originality / Value: The dataset used were participants from different countries and nationalities which include Philippines, Saudi Arabia, United Arab Emirates, Oman, USA, Portugal, Germany, Malaysia, Thailand, Qatar, Finland, Denmark, Spain Taiwan, South Korea, Singapore, Australia, Austria, England, UK, India and China. The presented codes were programmed in python where analyses and interpretations were based on formulated objectives. K-means clustering, and regression analysis were both employed to present varied clusters according to tourists’ demographic profiles, travel patterns and preferences. Different factors were identified and used to predict tourists’ length of stay in their preferred destinations
Research on the Construction of CuFeS2/ Bi2O3 Composite Materials and Degradation of Bisphenol A by Activating PMS
Get PDFBisphenol A (BPA) is harmful to human health. Advanced oxidation technologies using peroxymonosulfate (PMS) can effectively remove organic pollutants. Among these technologies, bimetallic sulfides stand out for their excellent activation ability. This study focuses on CuFeS2, and CuFeS2/Bi2O3 catalysts were prepared using a hydrothermal method. The CFSBO-2/PMS system can degrade up to 84.06% of BPA in just 30 seconds. XRD analysis shows that compared to the original CFS, the CFSBO catalyst significantly enhances the intensity of diffraction peaks, indicating improved crystallinity. The system maintains high degradation efficiency as the pH increases from 3.6 to 9.0, suggesting that the catalyst is highly adaptable to different water treatment conditions. The main active species generated are SO4−•, •OH, and 1O2. PMS activation in this system is driven by the redox cycles of Cu+/Cu2+, Fe2+/Fe3+, and Bi3+/Bi5+
Soil Erosion in Important Agricultural Areas of Haidong City, Qinghai Province, China
Get PDFHaidong City is located in the eastern region of the Tibetan Plateau and the upper reaches of the Yellow River, which is an important agricultural area in Qinghai Province. Surface soil erosion in this area not only reduces soil quality, but also leads to the pollution of the Yellow River water and the increase of sand transport.The soil erosion status of Haidong City in 2022 was assessed using the modified soil loss equation (RUSLE model), combined with landsat8 OLI imagery, DEM, rainfall and land use data, and RS and GIS techniques. The results show that soil erosion in Haidong City is dominated by slight and mild erosion, with an area of 7,835 km2 and 2,735 km2 respectively.Among the districts (counties), Ledu District and Mutual aid County have the largest area of strong erosion, with an area of 633 km2 and 144 km2 respectively; Ping'an District and Minhe County have a smaller area of strong erosion, with an area of 11 km2 and 30 km2 respectively.Between the different land-use types. grassland erosion area was the largest, with an area of 7449km2, accounting for 59.83%. The results of the above study can provide a scientific basis for soil degradation management in the region to meet the challenges of fragile ecological environment and increasing land use
Research on the Path of Enterprise Organizational Capability Reconstruction Driven by Digital Intelligence Technology
Get PDFIn the context of the digital economy, digital intelligence technologies such as big data, artificial intelligence, and cloud computing are gradually influencing and changing the operating mechanisms and competitive paradigms of enterprises. In this wave of technological change, the original organizational capabilities of enterprises are facing bottlenecks such as process rigidity, data silos, and lagging talent structure. If the organizational inertia and capability lock-in cannot be broken in time, the enterprise will miss the window of strategic transformation. This article focuses on the dynamic adaptation mechanism between digital intelligence technology and organizational capabilities, systematically analyzes its reconstruction path in terms of organizational structure, process system, talent allocation, and cultural identity, reveals the internal logic and key drivers of the evolution of organizational capabilities in the context of technology embedding, and provides theoretical reference and practical guidance for enterprises to build resilience and sustainable competitive advantages in complex environments
Strategic Integration of Generative AI: Opportunities, Challenges, and Organizational Impacts
Get PDFGenerative Artificial Intelligence (GenAI) is reshaping modern business operations, offering transformative capabilities in automation, content creation, and data-driven decision-making. However, adopting GenAI is not without challenges, particularly regarding governance, cybersecurity, ethical concerns, and workforce adaptation. This paper explores how pilot programs are essential for integrating GenAI into business operations while mitigating associated risks. Drawing on a narrative literature review, this study synthesizes contemporary research, industry best practices, and case studies to analyze adoption strategies, regulatory frameworks, and governance models. The findings emphasize the necessity of structured AI governance, organizational preparedness, and iterative testing to ensure successful GenAI deployment. By contributing to the broader discussion on AI’s role in business strategy, this study provides practical recommendations for organizations aiming to implement GenAI ethically, securely, and efficiently
Applying Semantic Theory Framework to Teaching Vocabulary of English for Medical Purposes at Vietnam Military Medical University
Get PDFThis study explores the application of semantic theory in teaching vocabulary of English for medical purposes (ESP-Med) at Vietnam Military Medical University (VMMU). The objective is to enhance vocabulary acquisition through innovative teaching methodologies. A survey of 297 students and 14 instructors was conducted to assess current teaching practices and their effectiveness. Based on the collected data, the study applies three semantic approaches proposed by Daniël & Panos (2028): Referential Approach, Relational Approach, and Denotational Approach. These approaches are integrated into teaching practices to promote contextual learning, lexical associations, and semantic mapping, thereby improving vocabulary retention and comprehension. The findings reveal that the systematic application of semantic theory significantly enhances students' ability to retain and use medical vocabulary. A comparison between the experimental and control groups demonstrates that these approaches facilitate long-term memory retention and the effective use of specialized terminology. Several challenges are identified, including limited instructional time, inadequate vocabulary learning strategies, and students' reliance on rote memorization rather than active learning. Additionally, the study underscores the importance of adopting teaching methods that align with academic and professional needs. The incorporation of multimodal learning tools such as interactive exercises, real-life scenarios, and visual aids further supports vocabulary acquisition. The research also recommends integrating digital technologies, including artificial intelligence, adaptive learning systems, and virtual simulations, to optimize teaching and learning outcomes. These findings contribute to enhancing ESP-Med instruction, ultimately improving students’ academic and professional competencies in the military and medical fields
A Study of the Multi-Actor Evolutionary Game of Social Auditing: A Blockchain Technology-Enabled Perspective
Get PDFPrivate economy is an intrinsic element of China's economic system, and promoting the development of private economy is an important support for the high-quality development of China's economy. Private enterprises are the key subjects of the private economy, and in recent years, the innovation vitality of China's private enterprises has continued to improve, and innovation achievements have emerged one after another, which is an important driving force for cultivating new quality productivity. However, there are still a series of problems such as insufficient domestic demand, intensified involution, and lack of enhancement, which hinder the sustainable development of private enterprises. Based on the perspective of blockchain technology empowerment, this study focuses on the strategic choice of private enterprises, government regulators and accounting firms in social audit regulation, and applies the evolutionary game theory for model construction to analyze the stability conditions for the game system to evolve to a stable state. In deeply grasping the evolutionary trend of all parties' subjects under different strategy choices, this study aims to provide theoretical support for the optimization of China's social audit regulatory system
Optimization of the Business Environment for Private Enterprises in Baoshan under the 'Delegation-Regulation-Service' Reform
Get PDFThis study investigates the optimization of Baoshan’s business environment for private enterprises under the “Delegation-Regulation-Service” (DRS) reform. Using survey data from 453 firms across manufacturing, service, and retail sectors, it constructs a five-dimensional framework encompassing factor, governmental, market, legal, and innovation environments. Through descriptive statistics, confirmatory factor analysis, structural equation modeling, and OLS robustness tests, the study finds that Baoshan’s overall business environment satisfaction is moderately high (mean=3.61). Governmental and innovation environments exert the most significant positive effects, while the legal environment is not statistically significant. Service-sector and larger firms report higher satisfaction than retail and micro enterprises. The paper concludes with policy recommendations to enhance administrative efficiency, strengthen innovation ecosystems, ensure fair market competition, and support micro enterprises
Identification of Influencing Factors and Path Analysis of the Military Products Supply Chain in the Context of Military-Civilian Integration
Get PDFUnder the civil-military integration initiative, the defense industry is transitioning from traditional closed monopoly models to civil-military collaboration. However, prolonged lack of competition and policy protection has left military supply chains with inadequate risk resilience. In this context, defense enterprises face both market efficiency pressures and complex risk challenges, making supply chain resilience enhancement crucial for national security and industrial upgrading. This study examines a 2025 solid rocket engine supply chain optimization project at a domestic aerospace institution. Through literature review and expert interviews, it identifies critical factors affecting military supply chains, employs DEMATEL (Decision-Making Trial and Evaluation Laboratory) to quantify inter-factor influence matrices, and combines ISM (Interpretive Structural Modeling) to construct a multi-level hierarchical structure, ultimately screening core drivers and revealing tiered dependency relationships and operational mechanisms. Under the civil-military integration context, the risk influencing factors of military-industrial enterprise supply chains mainly comprise four modules with sixteen elements: supplier factors (raw material disruption, supply chain stability, supplier capability), production factors (process stability, raw material quality, production safety, manufacturing complexity), technological environment (technical substitutability, R&D capability, talent pool), and market environment (demand fluctuation, price volatility, industry competition fluctuation). Process stability, raw material quality, and demand fluctuation are identified as core factors, while price volatility (F12), industry competition fluctuation (F13), and policy and regulation fluctuation (F14) exhibit high centrality. By integrating DEMATEL and ISM to analyze factor hierarchies and interaction pathways, this study further distinguishes between causal factors and resultant factors, providing both theoretical and practical guidance for enhancing risk resilience in military supply chains. The study focuses on military-industrial products that have received relatively limited research attention, analyzing the sources of their supply chain risks to provide theoretical insights for understanding the influencing factors and mechanisms of military-industrial supply chains
Research on the Construction of the Principles of Electric Circuits Textbook Based on National First-Class Course Standards
Get PDFThe construction of national first-class undergraduate courses serves as a pivotal initiative to deepen reforms in higher education and fulfill the fundamental mission of "cultivating virtue and nurturing talent." As the core medium for delivering course content and the foundational guide for teaching implementation, the quality of textbooks directly determines the effectiveness of first-class course development and the caliber of talent cultivated. This study takes Principles of Electric Circuits, a foundational engineering course, as its research focus, addressing the challenges faced by traditional textbooks in the new era. It systematically explores advanced principles, implementation pathways, and innovative directions for textbook construction. The paper proposes adhering to a construction philosophy centered on "cultivating virtue and talent, student-centered learning, outcome-oriented education, and interdisciplinary integration." It advocates following a construction approach that emphasizes "restructuring the content system, deeply integrating information technology, strengthening practice-based education, and establishing a robust evaluation and feedback mechanism." Furthermore, it calls for comprehensive innovation in "content modalities, learning pathways, capability empowerment, and evaluation mechanisms," aiming to build a new-generation Principles of Electric Circuits textbook system that supports the cultivation of higher-order thinking skills and meets the demands of the digital and intelligent era