Factor Analysis Method Research Articles

Prospecting potential evaluation based on geological factor analysis-a case study of Jiaojiacheng ore belt

Mineral forecasting is of great significance for social development. As an important aspect of geological exploration, its importance lies not only in its direct contribution to economic growth but also in how it employs precise technical methods for mineral exploration. This study utilizes a geological factor analysis method that combines various complex geological observation factors into a few dominant comprehensive factors, followed by causal research and multivariate statistical analysis for classification. Based on this, the study applies principles and methods of elemental geochemistry to identify the dispersion and concentration patterns of associated elements from the distribution characteristics of ordered accompanying factors, providing a scientific basis for mineralization forecasting. Using geochemical experimental data, geological survey comprehensive profiles, and factor score contour maps, this paper analyzes the southern extension segment of the Jiaojia gold mine mineralization belt through geological factor analysis. It was found that the anomalous distribution of chemical elements F4 (Hg, Au, Pb) exhibits certain regularities, which significantly indicate mineralization information and suggest the presence of two main longitudinal mineralization belts.

Spatio-Temporal Differentiation and Driving Factors of County-Level Food Security in the Yellow River Basin: A Case Study of Ningxia, China

Food security is the primary condition for the development of human society. The Great River Basin is very important to ensure the accessibility and availability of agricultural irrigation, which is vital for food security. The Yellow River Basin plays a significant role in China’s food security, with counties serving as key administrative units for guaranteeing this security. This study uses the Yellow River Basin in China as a case study to construct an evaluation index system for county-level food security. It assesses the food security of 22 counties (districts) in Ningxia from 2013 to 2022, applying spatial correlation theories and driving factor analysis methods to explore the factors influencing county-level food security. The results reveal the following: (1) Overall, the food security index in Ningxia has been on the rise, but there is significant internal variation among counties. (2) Spatially, the food security index is relatively low in administrative centers, while the irrigation areas along the Yellow River play a crucial role in maintaining food security, and the overall food security index in the central arid areas is improving. (3) Food security is driven by multiple factors including economic, social, and climatic influences. To enhance food security in the Yellow River Basin, it is necessary to manage land resources systematically, improve grain production technology, and balance ecological protection with food security.

Development of Cross-Sector Collaboration Indicators for Accelerating the Reduction of Stunting in South Sulawesi, Indonesia

Background: To reduce stunting, the government of Indonesia, which has the fifth-highest prevalence of stunting in toddlers, launched the National Strategy for the Acceleration of Stunting Prevention (StraNas Stunting). Despite involving multiple sectors, stunting rates remain high. This research aimed to develop cross-sector collaboration indicators to assess the effectiveness of cross-sector efforts in reducing stunting. Method: This qualitative study utilized a rapid assessment procedure (RAP) to generate cross-sector collaboration indicators through in-depth interviews with five key informants and four experts. The recurring themes from these interviews were identified as indicators, which were further refined. In the second phase, quantitative analysis was conducted with 50 respondents to test the developed indicators using Confirmatory factor analysis (CFA) methods. Result: A total of 15 indicators and 41 sub-indicators of cross-sector collaboration were developed across five key dimensions: governance, administration, autonomy, mutuality, and norms. Confirmatory Factor Analysis (CFA) was performed to validate the indicators, with the results showing that the Average Variance Extracted (AVE) for each dimension was greater than 0.5, and the Composite Reliability (CR) exceeded 0.7. These findings confirm the validity and reliability of the developed indicators. Conclusion: As recognized by experts, the theory of cross-sector collaboration has been further advanced by the cross-sector collaboration indicators generated in this study. Additionally, these indicators, which were based on five dimensions of collaboration, may be used to assess cross-sector performance for the Stunting Acceleration Program in Indonesia. The framework of this study for defining and assessing collaboration was expected to provide a foundation for further research.

A Method for the Analysis of Data About Dyadic Relationships

Psychological research in many subfields focuses on dyads because they influence individual cognitions, emotions, and behavior. However, the measurement of relationship characteristics has been elusive. Although direct observational methods have been hailed as the gold standard, they have some disadvantages, such as their high cost and external validity. We propose a factor-analytic method, specifically the bifactor model, using self-report data from each individual of a dyad. This method has been applied to many contexts but not yet to dyadic data. We show that the information that can be gleaned from these data is relatively low-cost but rich in terms of the insight it yields about the nature of the dyadic relationship. We demonstrate two different applications of the bifactor model to data from married couples.•The bifactor model can be used to identify the individual-specific and dyadic aspects of data reported by the members of a dyad.•The estimates of the bifactor model of dyadic data can yield information about hierarchical aspects of a relationship, which are not directly assessed.

Exploring facets of student motivation using a Bass Ackward strategy and the conceptual lens of self-determination theory

Motivational constructs have proliferated in educational psychology, reflecting the complexity of what moves people to engage and learn. In this exploratory research, we focused on students’ motivation for higher education. Our goal was to understand how a wide range of motives are empirically and conceptually related. We also examined how this diversity of motivational content relates to the motivational typology postulated by Self-Determination Theory (SDT). In Study 1, we extracted items from a broad collection of measures, formatted them with a common set of instructions, and administered them to multiple samples of current and former U.S. college students. Using Goldberg’s (2006) Bass Ackward factor-analytic method, we distilled twenty-six distinct facets that capture a wide variety of motivational contents. Multidimensional Scaling (MDS) suggested a dimension that resembled SDT’s continuum of relative autonomy, with some facets similar to amotivation and others falling along a range from less to more autonomous or volitional forms of motivation. In Study 2, we administered these provisionally labelled motivational facets alongside SDT’s regulatory styles and a set of external criteria covering multiple outcomes of interest in higher education. MDS analyses replicated the general pattern found in Study 1, recovering a dimension resembling SDT’s continuum of autonomy. Motivational facets were also associated with external criteria in a theoretically coherent manner. We discuss the implications of these exploratory findings for understanding the structure of self-reported motivation and for theory and measurement of student motivation.

ANALYSIS OF THE FACTORS OF SOCIAL MEDIA ADVERTISING AND THEIR INFLUENCE ON CONSUMER’S BUYING INTENTION

In a social media setting, it is critical to explore the constructs that drive consumers’ reactions toward advertisements as the lack of understanding of these factors may lead to misplaced advertising for marketers online. This study creates a multifaceted advertising model that assesses the effect of informativeness, entertainment, irritability, and credibility on the valuableness of social media advertising and how these factors influence consumers’ buying intentions. It adopted a covariance-based structural equation modelling approach where primary data was collected by administering questionnaires to a sample study of 364 selected participants, who were university students, employees, and entrepreneurs. The data gathered were analyzed using confirmatory factor analysis and structural equation modelling method were used to examine the correlation between the identified predictors and purchase intention while validating the model constructed. The results established that a strong correlation exists between the perceived value of informativeness and credibility of social media advertising and customer buying intention. The findings, while frowning that advertisements with overly entertaining content may irritate potential buyers, posited that perceived value is critical in the conversion of advertising engagement into purchase habit. The study significantly highlighted that perceived value is the key mediator in the proposed model with a very strong correlation that impacts consumers’ buying intention; that is, consumers who perceive value in the ads are far more likely to express their buying intention. The study recommended that advertisers should focus on making their social media ads more valuable to positively affect customer perceptions.

Structure Equation Model for Costs and Benefits of Distribution Pipe Rehabilitation in Reactive Maintenance

Some water distribution pipe networks were constructed several decades ago and have been damaged. The old pipe network has experienced many leaks and should be rehabilitated. In old cities like Jakarta, with high leak rates (1.6 leaks/km/year), pipeline network managers must frequently repair leaks or perform reactive maintenance. Far too many pipes need to be rehabilitated compared to the available budget. This research will develop an optimization model for selecting rehabilitated pipes under reactive maintenance conditions, which has never been performed before. The selection of pipe segments to be rehabilitated must be optimal to obtain maximum benefits using minimum costs. The variables that influence rehabilitation costs and benefits and the relationship between these variables need to be known to optimize the selection. The influencing variables and their model structure were obtained from literature reviews and surveys of respondents with sufficient experience in water pipe network management. These influential variables have varying characteristics. Data processing and analysis uses the confirmatory factor analysis (CFA) method with a formative–formative measurement model. In total, 22 variables were found to be valid and significantly influenced the cost and benefits of rehabilitation. The analysis results are a structural model of the relationship between variables that influence the costs and benefits of rehabilitation in reactive maintenance with a limited budget, which can be used to optimize rehabilitation models.

Study on the Level Measurement and Spatial Distribution of Comprehensive Competitiveness of Logistics Industry in Henan Province

This paper takes the 18 cities in Henan Province as the research object, combining their relevant data in 2022, and conducts a comparative study on the comprehensive competitiveness indicators of logistics industry in Henan Province through factor analysis method. Starting from the three dimensions of infrastructure level, economic benefits, and development scale, this paper explores the level of comprehensive competitiveness of logistics industry in Henan Province and explores the spatial distribution characteristics of comprehensive competitiveness through spatial trend analysis and natural breakpoint method. And it puts forward corresponding improvement strategies.

Manure contribution to rural livelihoods at farm and landscape levels: a systemic approach in semi-arid Central Tunisia

ABSTRACT Manure valorization through on-farm use or market transactions is an ancient and widespread practice in the mixed crop-livestock systems of the semi-arid areas of North Africa. While research has long focused on the manure contribution to soil fertility at the plot level, little has been done concerning livelihood conditions. The present paper aims to assess the contribution of manure use and exchange on the livelihoods of rural communities using an original dataset collected in 2021 among 150 farmers in Central Tunisia. This analysis is carried out within the analytical agroecology framework combined with factor analysis methods. Results showed that manure use and valorization differ along the watershed, from a socioeconomic perspective in small farms operating under rainfed tree-pastoral systems, to an environmental and agronomic perspective in the mixed rainfed-irrigated systems downstream. Manure flow analysis confirmed that on-farm manure balance is positively correlated to economic wealth. However, the manure fluxes questioned the environmental sustainability of the vulnerable zones. Its use and management could significantly impact livelihood discrepancies in the future, with the increasing of demand and use of manure in more favorable zones such as irrigated lands at the detriment of the rainfed zones.

Study of Tennis Competition Based on Factor Analysis and Comprehensive Evaluation Methods

Study of Tennis Competition Based on Factor Analysis and Comprehensive Evaluation Methods

Factor structure and validation of the electronic form of the Oxford Happiness Questionnaire in patients with COVID-19

Background and Objectives: Background and Aim: Validity Scale Validation can help identify coronavirus disease patients; therefore, the aim of this study was to evaluate the validation of the electronic form of the Oxford Happiness Questionnaire in patients with COVID-19. Methods: This study is instrumental psychometrics that the statistical population includes all patients in 19 cases in Tehran. The number of samples was determined based on psychometric criteria to be 100 for the predictive validity section and 251 for the convergence validity section. Samples were selected by cluster sampling. Research data were collected electronically through two questionnaires of happiness (Oxford) and happiness of positive psychological characteristics by sending the questionnaire link to the participants' mobile phones. To evaluate the validity of the scale, content validity, convergence, and factor analysis methods were used. The reliability of the scale was assessed by internal consistency methods and class reliability. Results: The results of exploratory factor analysis showed that the researcher-made questionnaire consists of three factors and has good validity and reliability. The second-order confirmatory factor analysis also confirmed the three-factor model. This questionnaire was administered along with the short form of the Oxford Happiness Scale, which had 13 items of good reliability and validity. Conclusion: The Oxford Happiness Scale in COVID-19 patients can be used to assess happiness in COVID-19 patients.

Research on Service Quality Improvement of Franchised End Logistics Outlets Based on SERVQUAL

Abstract: As an effective solution to the "last mile" problem of logistics transportation, express terminal network has shown a rapid development trend in recent years. The franchise production is a main operation mode of the end express outlets. By fully mobilizing the enthusiasm of the franchise outlets, the service scope of express enterprises is effectively expanded. However, the problems of loose management and uneven service quality are prevalent in this kind of franchise outlets, which makes the express terminal service become one of the bottlenecks restricting the healthy development of the industry. Based on this, this paper improved the SERVQUAL model combined with the actual situation of the end express outlets of the franchise system, and designed the questionnaire based on it, sorted out and analyzed the survey data by using factor analysis and entropy weight method, and finally found out the shortcomings in the service process of the end express outlets according to the results, and put forward targeted solutions.

Evaluation of Shanghai's Logistics Level from the Perspective of High-quality Development

The thesis evaluates the logistics level of Shanghai by constructing the evaluation indexes of Shanghai logistics level under the perspective of high-quality development, setting up five first-level indexes and corresponding nine second-level indexes, adopting the data of Shanghai Municipal Bureau of Statistics from 2005 to 2022, and evaluating the logistics level of Shanghai by utilizing the factor analysis method to find out the factors that have the most influence on the high-quality development of the logistics level of Shanghai, i.e., the factor of logistics infrastructure and the factor of logistics innovation ability. factor, focusing on these two factors to make countermeasures and suggestions for Shanghai's logistics industry, pointing out the shortcomings of the thesis and the future outlook.

SEMANTIC SPACE OF YOUTH AS A FACTOR IN THE FORMATION OF LIFE COMPETENCE IN THE CONDITIONS OF WAR

The study aims to define the semantic fields of the "life competence" concept and clarify the nature of the relationship between understanding this concept and the setting of life tasks by young people in war. The goal was achieved by solving the following tasks in turn: clarifying the etymology of the "life competence" concept and its content and structural components as semantic fields of understanding this concept in everyday and scientific contexts; studying the semantic space of understanding life competence by young people in war conditions; determining the impact of the peculiarities of understanding the "life competence" concept by young people on their life tasks. The tasks were solved with the help of theoretical (theoretical and methodological analysis, comparison and generalization of results), empirical (semantic differential method, narrative survey method), and mathematical (factor and correlation analyses) methods. The conducted theoretical and empirical research has shown a sufficient cognitive complexity of the "life competence" concept young people's understanding and concepts closely related to it: "life experience", "life task", "difficult life situation", as well as the closeness of semantics to scientific contexts. It has been found that the semantic fields of these concepts are in close direct relationship, which are logically interpreted in the context of everyday thinking and modern psychological science. Defined positive correlations of the criteria for understanding the "life competence" concept by young people with the life tasks that young people set during the war: development, education, family mutual assistance, helping others, solving problems of material support, preserving psychological health, which allowed us to characterize the features of young people semantic space by their life tasks priorities Keywords: life competence, semantic space, difficult life situation, life experience, life task, war, youth

A factor analysis based automatic optimization method of vibration sensor points for ship acoustic reconstruction

To address the challenge associated with optimizing the number and positioning of accelerometer points in ship acoustic reconstruction, factor analysis is applied to the automatic optimization of accelerometer position in this work according to the source independence of ship’s underwater radiated noise. Based on the numerical simulation method that calculates the vibration noise response under specific operation conditions, the minimum number and the optimal position of the accelerometers can be obtained through the factor analysis and multi-parameter comprehensive evaluation method. The results of acoustic reconfiguration and testing are compared using one test cabin as a validation object to verify the effectiveness of the proposed method. The results show that the automatic optimization algorithm can improve the reconstruction accuracy concerning the uniform distribution method. The error is reduced from 15.46% (1.5 dB) to 8.35% (0.8 dB), and the correlation coefficient is improved from 0.86 to 0.89. The semi-automatic optimization method is slightly lower in terms of errors and correlation coefficients compared to the automatic optimization algorithm. After increasing the number of monitoring positions for automatic optimization, the acoustic reconstruction accuracy is further improved, while the average error is reduced to 7.37% (0.7 dB) and the correlation coefficient is improved from 0.89 to 0.92. The experimental results are proximate to the conclusions of the simulation calculation. Even under the circumstance of multi-factor noise interference, the correlation coefficient of multi-position automatic optimization can still reach 0.8, in comparison with the uniform distribution method, the error is reduced from 32.49% (3.4 dB) to 25.94% (2.6 dB). The proposed method effectively captures the dynamic characteristics of complex structures and their impact on underwater radiated noise, and the integration of factor analysis can prominently enhance the computational efficiency, thereby providing technical support for engineering applications to the ship acoustic reconstruction.

The Synergistic Effect of the Same Climatic Factors on Water Use Efficiency Varies between Daily and Monthly Scales

The coupled processes of ecosystem carbon and water cycles are usually evaluated using the water use efficiency (WUE), and improving WUE is crucial for maintaining the sustainability of ecosystems. However, it remains unclear whether the WUE in different ecosystem responds synchronously to the synergistic effect of the same climate factors at daily and monthly scales. Therefore, we employed a machine learning-driven factor analysis method and a geographic detector model, and we quantitatively evaluated the individual effects and the synergistic effect of climate factors on the daily mean water use efficiency (WUED) and monthly mean water use efficiency (WUEM) in different ecosystems in China. Our results showed that (1) among the 10 carbon flux monitoring sites in China, WUED and WUEM exhibited the highest positive correlations with the near-surface air humidity and the highest negative correlation with solar radiation. The correlation between WUEM and climate factors was generally greater than that between WUED and climate factors. (2) There were significant differences in the order of importance and degree of impact of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the near-surface air humidity imposed the greatest influence on the WUED and WUEM changes, followed by the near-surface water vapor pressure. (3) There were significant differences in the synergistic effects of the same climate factors on WUED and WUEM in the different ecosystems. Among the 10 carbon flux monitoring sites in China, the WUED variability was most sensitive to the synergistic effect of solar radiation and photosynthetically active radiation, while the WUEM variability was most sensitive to the synergistic effect of the near-surface air humidity and soil moisture. The research results indicated that synchronous responses of the WUE in very few ecosystems to the same climate factors and their synergistic effect occurred at daily and monthly scales. This finding enhances the understanding of sustainable water resource use and the impact of climate change on water use efficiency, providing crucial insights for improving climate-adaptive ecosystem management and sustainable water resource utilization across different ecosystems.

Analysis of Influential Factors of House Prices in Shenzhen

The change of house prices in Shenzhen can reflect the trend of house price changes in China, to a certain extent. This text chose the Factor Analysis Method to Specific analyze influential factors. This text put F1 as a variable, which included Total Floor Space of Residential Buildings Sold, Permanent Population, Total Floor Space under Construction of Commodity Housing, Investment in Real Estate Development, Gross Domestic Product, Local Budgetary Revenue and Expenditure. Through analyzing the data, this text deduced that Longgang, Baoan and Nanshan districts had above average values on F1. This text put F2 as a variable, which included Per Capital Disposable Income of Permanent Households and Growth Rate of Real Estate Investment, etc. Through analyzing the data, this text deduced that Nanshan, Luohu, Futian districts had above average values on F2. This text can conclude that Nanshan, Baoan and Futian Districts had a great influence on house prices in Shenzhen.

Motivations of Ecotourists and Their Relationship with Sociodemographic Aspects, Satisfaction, and Loyalty: Puntilla de Santa Elena Marine Fauna Production Reserve, Ecuador

This study aims to investigate the demand for ecotourism in marine protected areas by (a) identifying motivations specific to marine protected areas, (b) establishing the relationship between social and demographic variables and motivations, and (c) determining the relationship between social and demographic characteristics, satisfaction, and loyalty variables. The study was conducted in Santa Elena Province at the reserve called “Puntilla”, which is a coastal marine and fauna production reserve in Ecuador, a country renowned for its biodiversity. The sample comprised 369 on-site surveys. Factor analysis and stepwise multiple regression methods were used for data analysis. The results revealed associations between social and demographic variables and tourist motivations. Specifically, lower-income tourists were most motivated by “escape and ego-defensive function motivation” and reported higher satisfaction levels. Conversely, tourists who visited the destination less frequently displayed stronger motivations related to nature and showed high satisfaction. Furthermore, visitors who spent less at the destination demonstrated a greater intention to return and recommend the area to others. These findings hold significant implications for protected areas management and contribute to the scientific literature on ecotourism in similar protected areas.

Anthropometry and Physical Condition Factors for Determining the Speed of Sickle Kick

This research aims to determine the anatomical and physiological factors of the body that have a correlation and role in the speed of sickle kicks of pencak silat athletes. The basic anatomical (anthropometric) factors studied include body height and leg length. Meanwhile, the physiological factors (physical condition) studied include speed, agility, leg power, anaerobic endurance, balance, and flexibility. This research examines the fighting category in men's class C, which is the fighting category that dominates most adolescent pencak silat matches. This research used a quantitative approach with a confirmatory factor analysis (CFA) method which tested the consistency of indicators that had been grouped based on latent variables. All data obtained, processed, and tested went through several stages then would be eliminated if it did not meet the criteria to pass the test. The research population was adolescent pencak silat athletes aged 14-17 years old in Wonosobo Regency. The research location was conducted at 3 (three) high schools which had pencak silat training units and had trained athletes in the men's class C fighting category. The research samples were 15 people taken by using a purposive sampling technique. The research instruments were observation and documentation. The results of the research show that out of 9 latent factor variables, 8 variables are obtained which are the determining factors for the speed of the sickle kick. These factors with their role values are body weight (0.748), height (0.536), leg length (0.834), anaerobic endurance (0.838), speed (0.817), agility (0.876), leg power (0.856), and flexibility (0.902). Meanwhile, the balance is eliminated during the first analysis.

Prediction of allograft function in pre-transplant kidneys using sound touch elastography (STE): an ex vivo study

BackgroundThe purpose of the study was to evaluate renal quality and predict posttransplant graft function using ex vivo sound touch elastography (STE).MethodsIn this prospective study, 106 donor kidneys underwent ex vivo STE examination and biopsy from March 2022 to August 2023. The mean stiffness of the superficial cortex (STEsc), deep cortex (STEdc), and medulla (STEme) was obtained and synthesized into one index (STE) through the factor analysis method. Additionally, 100 recipients were followed up for 6 months. A random forest algorithm was employed to explore significant predictive factors associated with the Remuzzi score and allograft function. The performance of parameters was evaluated by using the area under the receiver operating characteristic curve (AUC).ResultsSTE had AUC values of 0.803 for diagnosing low Remuzzi and 0.943 for diagnosing high Remuzzi. Meanwhile, STE had an AUC of 0.723 for diagnosing moderate to severe ATI. Random forest algorithm identified STE and Remuzzi score as significant predictors for 6-month renal function. The AUC for STE in predicting postoperative allograft function was 0.717, which was comparable with that of the Remuzzi score (AUC = 0.756). Nevertheless, the specificity of STE was significantly higher than that of Remuzzi (0.913 vs 0.652, p < 0.001). Given these promising results, donor kidneys can be transplanted directly without the need for biopsy when STE ≤ 11.741.ConclusionsThe assessment of kidney quality using ex vivo STE demonstrated significant predictive value for the Remuzzi score and allograft function, which could help avoid unnecessary biopsy.Critical relevance statementPre-transplant kidney quality measured with ex vivo STE can be used to assess donor kidney quality and avoid unnecessary biopsy.Key PointsSTE has significant value for diagnosing low Remuzzi and high Remuzzi scores.STE achieved good performance in predicting posttransplant allograft function.Assessment of kidney quality using ex vivo STE could avoid unnecessary biopsies.Graphical