Correlation Analysis Model Research Articles

The Impact of Airline Continuity Behavior and Corporate Image on Consumers' Purchase Intentions: Brand Loyalty as a Moderating Variable

Nowadays, corporations are moving towards sustainable management, and the social responsibility reports released by corporations show their sustainable behaviors. Aviation is a high-polluting industry with high carbon emissions, which makes it even more important for airlines to have a sustainable management plan. Consumers are also becoming more aware of the need to go green in order to minimize environmental damage and enhance human well-being. The purpose of this study is to examine the impact of corporate sustainability behaviors on airline ridership, the role of corporate image as a mediator, and the moderating effect of brand loyalty on ridership. A total of 412 questionnaires were collected from consumers who have traveled on airplanes. After deducting 50 invalid questionnaires, 362 valid questionnaires were collected, with a usability rate of 87.8%. Empirical factor analysis, reliability analysis, correlation analysis and hierarchical regression model were applied. The results of this study show that corporate sustainability behavior and corporate image have a significant positive effect on purchase intention, corporate image plays a part in mediating the effect of corporate sustainability behavior on purchase intention, and consumers' brand loyalty strengthens the effect of corporate image on purchase intention. Finally, this study proposes some recommendations for airlines to make sustainable behavior decisions.

Guiding post-pancreaticoduodenectomy interventions for pancreatic cancer patients utilizing decision tree models.

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in advanced stages, necessitating pancreaticoduodenectomy (PD) as a primary therapeutic approach. However, PD surgery can engender intricate complications. Thus, understanding the factors influencing postoperative complications documented in electronic medical records and their impact on survival rates is crucial for improving overall patient outcomes. A total of 749 patients were divided into two groups: 598 (79.84%) chose the RPD (Robotic pancreaticoduodenectomy) procedure and 151 (20.16%) chose the LPD (Laparoscopic pancreaticoduodenectomy) procedure. We used correlation analysis, survival analysis, and decision tree models to find the similarities and differences about postoperative complications and prognostic survival. Pancreatic cancer, known for its aggressiveness, often requires pancreaticoduodenectomy as an effective treatment. In predictive models, both BMI and surgery duration weigh heavily. Lower BMI correlates with longer survival, while patients with heart disease and diabetes have lower survival rates. Complications like delayed gastric emptying, pancreatic fistula, and infection are closely linked post-surgery, prompting conjectures about their causal mechanisms. Interestingly, we found no significant correlation between nasogastric tube removal timing and delayed gastric emptying, suggesting its prompt removal post-decompression. This study aimed to explore predictive factors for postoperative complications and survival in PD patients. Effective predictive models enable early identification of high-risk individuals, allowing timely interventions. Higher BMI, heart disease, or diabetes significantly reduce survival rates in pancreatic cancer patients post-PD. Additionally, there's no significant correlation between DGE incidence and postoperative extubation time, necessitating further investigation into its interaction with pancreatic fistula and infection.

A Data-Driven Modeling Study of Factors Influencing Preschool Students’ Intention to Teach

Abstract Willingness to teach is an important condition for improving pre-service teacher literacy to promote the professional development of preschool teachers. In this study, we randomly selected 600 students from six types of preschool education majors, and processed the data using a data-driven model that included an independent sample t-test, correlation analysis, and multiple linear regression model. The data results showed that the overall mean and standard deviation of preschool education students’ willingness to teach was 3.91±0.982, and preschool education students’ willingness to teach was high overall, but there were still students who expressed a lack of significant willingness to teach. Further regression analysis revealed that individual characteristics, family environment, school environment, and teacher career perception had explanatory power of 5.8%, 20.7%, 6%, and 3%, respectively, and the factors influencing preschool education majors’ willingness to teach were diverse. Measures at both the government and university levels are necessary to comprehensively improve the willingness to teach.

Research on the non-use value of rammed earth buildings in Shaxi Ancient Town based on CVM

Architectural cultural heritage not only enriches the cultural landscape but also drives economic activity, although its value is often underestimated by the market. This article uses the rammed earth buildings of Shaxi Ancient Town as a case study, quantifying their non-use value through the contingent valuation method, and explores factors influencing public willingness to pay using correlation analysis and binary logistic regression models. The results show that respondents have a high support rate (72.9%) and willingness to pay (26.23 RMB per person) for the conservation and development of rammed earth buildings. The total non-use value reached approximately 29.79 million RMB, demonstrating the significant economic potential of these structures as architectural heritage. This provides critical insights for the conservation and development of rammed earth architecture in China and calls for enhanced recognition and protection efforts from all sectors of society.

Research on Civic and Political Education and Economic Development in the Age of Digital Economy

Abstract This paper constructs the evaluation index system of Civic and Political Education and Digital Economy Development and uses the entropy value method to calculate the weight value of each index in the evaluation system. A gray correlation analysis model is established to explore the degree of correlation and relevance of indicators in the evaluation system of ideological and political education and economic development. Analyze the synergistic development between the two subsystems of ideological and political education and digital economic development by using the coupling degree and the coupling coordination degree analysis method, and explore the degree of coordination of the coupling development between the two. The analysis of the relationship between civic and political education and economic development in the sample sites found that the integrated gray correlation between the two is 0.610, which is a moderate level of correlation. The coupling degree of the two is increasing year by year, and it will reach 0.525 in 2023. On average, the coupling coordination degree reaches 0.610, which belongs to primary coordination. This paper provides data support for the improvement of the coupling coordination between ideological education and economic development in the era of the digital economy. It lays the foundation for the common development of ideological education and economy.

A Study on the Extension of Chinese Traditional Culture in College Art Education Combined with Gray Correlation Analysis Methods

Abstract This study incorporates gray correlation analysis from gray statistical theory to assess the quality of traditional culture and art education. It establishes an evaluation index system and a gray correlation analysis model, examining the relationship between contemporary art education and traditional culture. The model is applied to identify the correlation, key characteristics, and principal influencing factors of traditional Chinese culture and art education in higher education institutions. Additionally, it examines the advantages of random sequences of factors through specific data processing techniques. The structural model tests the influencing factors on the quality of traditional culture and art education, with an analysis of path coefficients. The results showed that 97.4% of teachers chose traditional culture and art teaching resources, mainly by referring to the network aspect. The results of the weight distribution indicate that the teaching process U3 (0.3613) is the most important in traditional culture and art teaching, and the innovative activities in teaching content (0.8113) hold the largest weight. The top three gray correlation values of the indicators of the second-level factor layer are U43>U22>U32. The direct influence effect of excellent traditional culture permeating the teaching process is 0.232, which has the greatest influence on the quality of teaching. The direct impact of excellent conventional culture permeating teaching content is 0.184, which has the second largest influence on teaching quality. This paper successfully constructs a gray correlation model to analyze the relationship between traditional culture and contemporary art, which has high scientific validity.

Clinical characteristics and surgical outcomes of low-grade epilepsy-associated brain tumors

Background: Low-grade epilepsy-associated brain tumors (LEATs) are found to be the second most common lesion-related epilepsy. Malignant potential of LEATs is very low and the overall survival is good, so the focus of treatment is focused more on seizure outcome rather than oncological prognosis. Objectives: This study was conducted to evaluate the risk factors of seizure outcomes after resection in patients with LEATs. Design: A retrospective study. Methods: A retrospective analysis of patients with LEATs who underwent resective surgery in our three epilepsy centers between October 2010 and April 2023 with a minimum follow-up of 1 year. Demography, clinical characters, neurophysiology, and molecular neuropathology were assessed for association with postoperative seizure outcomes at 1-, 2-, and 5-year follow-up. Synthetic minority oversampling technique (SMOTE) algorithm model was performed to handle the imbalance of data distribution. Gaussian Naïve Bayes (GNB) algorithms were created as a basis for classifying outcomes according to observation indicators. Results: A total of 111 patients were enrolled in the cohort. The most common pathology was ganglioglioma ( n = 37, 33.3%). The percentage of patients with seizure freedom was 91.0% (101/111) at 1-year follow-up, 87.5% (77/88) at 2-year follow-up, and 79.1% (53/67) at 5-year follow-up. Partial resection had a significantly poor seizure outcome compared to total resection and supratotal resection ( p < 0.05). The epileptiform discharge on post-resective intraoperative electrocorticography (ECoG) or postoperative scalp electroencephalography (EEG) were negative factors on postoperative seizure freedom at 1-, 2-, or 5-year follow-ups ( p < 0.05). The area under the receiver-operating characteristic curve value of the GNB-SMOTE model was 0.95 (95% CI, 0.876–1.000), 0.892 (95% CI, 0.656–0.934), and 0.786 (95% CI, 0.491–0.937) at 1-, 2-, and 5-year follow-up, respectively. Conclusion: The partial resection, post-resective intraoperative ECoG, and postoperative scalp EEG were valuable indicators of poor seizure outcomes. The utilization of post-resective intraoperative ECoG is beneficial to improve seizure outcomes. Based on the data diversity and completeness of three medical centers, a multivariate correlation analysis model was established based on GNB algorithm.

Examining the Impact of Dividends on Share Prices: Evidence from Microfinance Companies in Nepal

The objective of this empirical study is to investigate how dividends affect stock prices. The antecedent variables are the price-to-earnings ratio, dividend payout ratio, dividend per share, and earnings per share. The consequent variable is the share price of microfinance companies. Profitability (return on equity) acts as a mediator between the antecedent and consequent variables. Microfinance was chosen on the basis of its performance on the Nepal stock exchange, and information was gathered from companies listed in the NEPSE between 2018 and 2022. Purposive or judgmental sampling was utilized to identify the ten microfinance companies that served as study samples. The research employs descriptive statistics, correlation, and regression path analysis models to investigate the mediating role. The findings revealed that the direct and total effects of the dividend payout ratio and earnings per share have insignificant impacts on the share price. Furthermore, the indirect effect of antecedent variables has an insignificant impact on share price through return on equity. Additionally, this study advises investors to use the information not only as a way to profit but also as a tool for assessing companies from an investment standpoint. Moreover, management must determine the dividend payout ratio to enhance shareholder wealth.

Species dependent correlation analysis and regression models of body weight on linear body measures in indigenous sheep and goats of Zimbabwe

<p>Measurements of live weight in goats and sheep are an important source of information for a range of scientific fields and applications in animal husbandry activities. The study was conducted to investigate the relationship between body weight and body measurements and to predict live body weight from body measurements in indigenous Matabele goats and indigenous Sabi sheep at Matopos Research Station in Zimbabwe. For this purpose, data on body weight (BWT) and linear body measurements (LBM) such as heart girth (HG), body length (BL), wither height (WTH), and rump height (RH) were collected from randomly selected females of each species at the age of 4 years. The corresponding means, standard deviations (SD), and coefficients of variation (CV) were determined for body weight and linear body measurements. Bivariate correlations between bodyweight and linear body measure characteristics were also determined. Simple and multiple regression were used to develop a model to predict BWT using linear body measures. Indigenous Matabele goat females’ CV ranged from 15.77% to 22.68%, while indigenous Sabi sheep females’ CV ranged from 19.16% to 19.37%. The CV was calculated by dividing the mean by the standard deviation. At 4 years of age, the mean BWT of the indigenous Sabi sheep and female Matabele goat were 35.96 ± 0.83 kg and 27.90 ± 0.66 kg, respectively. In indigenous Matabele goat females, the average linear body measures were HW (74.20 ± 0.53 cm), WTH (48.55 ± 0.53 cm), BL (47.53 ± 0.61 cm), and RH (57.50 ± 0.88 cm). The mean values for native Sabi sheep were 63.33 ± 0.70 cm, WTH (52.00 ± 0.80 cm), BL (51.26 ± 0.78 cm), and HW (85.56 ± 1.04 cm). The results showed a strong and positive correlation between BWT and linear body measures in female indigenous Matabele goats. The phenotypic correlation values were HG (<em>r</em> = 0.79), BL (r = 0.70), WTH (<em>r</em> = 0.68), and RH (<em>r</em> = 0.56), in decreasing order. In indigenous Sabi sheep, the phenotypic correlation for BWT and linear body measurement was high and positive for HG (<em>r</em> = 0.73), and positive and moderate to low with WTH (<em>r</em> = 0.41), BL (<em>r =</em> 0.32), and RH (<em>r</em> = 0.36). Again, the results also indicated that HG had a high and positive phenotypic correlation with BL (<em>r</em> = 0.53), while modest correlation was observed with HG and WTH (<em>r</em> = 0.41) and HG and RH (0.32). The optimal regression models for easily measuring body weight using HHG are BWT = −46.711 + 1.006 HG (<em>R</em><sup>2</sup> = 60%) and BWT = −15.209 + 0.586 HG (<em>R</em><sup>2</sup> = 53%) for indigenous Matabele goats and indigenous Sabi sheep, respectively. It is recommended that smallholder farmers use HG measurements to estimate body weight in both indigenous Sabi sheep and indigenous Matabele goat females at the age of 4 years.</p>

Resilience, organizational support, and innovative behavior on nurses' work engagement: a moderated mediation analysis.

To investigate the status of nurses' work engagement and the relationship among resilience, organizational support, and innovative behaviors. In this cross-sectional study, we investigated 496 nurses in Hunan, China, from July 2022 to December 2022. A descriptive statistical approach, Pearson's correlation analysis and Hayes' PROCESS Macro Models 4 and 14 were used to analyze the available data. The level of work engagement among nurses was found to be moderate. Resilience positively predicted work engagement among nurses. Organizational support played a partially mediating role in the association between resilience and work engagement. Furthermore, innovative behavior played a moderating role in the association between adaptive resilience and work engagement. Based on the results, greater attention needs to be paid to nurses' work engagement. A high level of resilience, organizational support, and innovative behavior may increase work engagement among nurses. Nursing leaders can take measures to increase work engagement among nurses by improving nurses' resilience and organizational support, and cultivating innovative behavior.

Pandemic-Induced Occupational Disruption and Association With Health in Japanese Community-Dwelling Older Adults.

The COVID-19 pandemic caused occupational disruption and adverse health outcomes in community-dwelling older adults. This study aimed to investigate the extent of occupational disruption in older adults and its relationship to health-related quality of life (QOL), depression, and frailty. In this cross-sectional study, retention rates in four activity domains and relationships with health outcomes were examined in Japanese older adults aged ≥65 years (n=163) using canonical correlation analysis (CCA) and mixed linear models. More than 25% of activities were restricted compared with the pre-pandemic period. CCA demonstrated correlations between four retention rates and health outcomes (canonical correlation = .42, p = .0003). Retention in instrumental and social activities independently predicted QOL and depression (p < .05). This study highlights that different activities may have different effects on health outcomes and can provide community occupational therapy practitioners with a perspective to assess occupational disruption and identify activities for intervention.

Role of amino acids in flavor profiles and foam characteristics of sparkling wines during aging

As sparkling wine ages, a well-balanced amino acid composition can enrich its flavor profiles and achieve an optimal state for foam characteristics. This study aimed to determine the influence of amino acids on the flavor profiles and foam characteristics of white and rosé sparkling wine. The concentrations of amino acids and aroma compounds were determined via liquid chromatography–mass spectrometry (LC–MS) and gas chromatography-mass spectrometry (GC-MS), respectively. Correlation analysis and multiple linear regression (MLR) models were employed for further analysis. It revealed that the content of amino acids (except for proline) in both sparkling wines decreased with aging (11–23%). Ethyl octanoate had the largest odor activity value (OAV) value in both wines, but its content decreased with aging. The foam parameters of both sparkling wines decreased with increased aging duration, leading to changes in effervescence-related taste traits. Correlation analysis showed that most amino acids positively correlated with ethyl octanoate and foam characteristics, whereas the foam parameters did not increase along with the protein concentrations. Furthermore, the MLR analysis emphasized that amino acids had a greater impact on foam characteristics than volatiles. This study provides guidance for the production of high-quality sparkling wines.

Biodegradable PBAT microplastics adversely affect pakchoi (Brassica chinensis L.) growth and the rhizosphere ecology: Focusing on rhizosphere microbial community composition, element metabolic potential, and root exudates

Biodegradable plastics (BPs) have gained increased attention as a promising solution to plastics pollution problem. However, BPs often exhibited limited in situ biodegradation in the soil environment, so they may also release microplastics (MPs) into soils just like conventional non-degradable plastics. Therefore, it is necessary to evaluate the impacts of biodegradable MPs (BMPs) on soil ecosystem. Here, we explored the effects of biodegradable poly(butylene adipate-co-terephthalate) (PBAT) MPs and conventional polyethylene (PE) MPs on soil-plant (pakchoi) system at three doses (0.02 %, 0.2 %, and 2 %, w/w). Results showed that PBAT MPs reduced plant growth in a dose-dependent pattern, while PE MPs exhibited no significant phytotoxicity. High-dose PBAT MPs negatively affected the rhizosphere soil nutrient availability, e.g., decreased available phosphorus and available potassium. Metagenomics analysis revealed that PBAT MPs caused more serious interference with the rhizosphere microbial community composition and function than PE MPs. In particular, compared with PE MPs, PBAT MPs induced greater changes in functional potential of carbon, nitrogen, phosphorus, and sulfur cycles, which may lead to alterations in soil biogeochemical processes and ecological functions. Moreover, untargeted metabolomics showed that PBAT MPs and PE MPs differentially affect plant root exudates. Mantel tests, correlation analysis, and partial least squares path model analysis showed that changes in plant growth and root exudates were significantly correlated with soil properties and rhizosphere microbiome driven by the MPs-rhizosphere interactions. This work improves our knowledge of how biodegradable and conventional non-degradable MPs affect plant growth and the rhizosphere ecology, highlighting that BMPs might pose greater threat to soil ecosystems than non-degradable MPs.

Interfacial behavior and micro-rheological performance of Pickering emulsions co-stabilized by β-cyclodextrin and xanthan gum

Pickering emulsions have higher physical and energy barriers than typical emulsions, preventing emulsion droplets aggregation more effectively. The poor surface activity of β-cyclodextrin (CD) has limited its application in Pickering emulsions, and in order to improve the emulsifying performance of CD, in this paper, Pickering emulsions for usage in the food pathway were prepared using the xanthan gum (XG)/CD complex with different mass ratios. The CD was mixed with XG at a same concentration to form XG1/CD1 mixture, which possessed the highest absolute value of ζ-potential (54.5 mV), optimal wettability (76.9°) and interfacial behavior (like minimum interfacial tension, highest interfacial pressure, diffusion rate, penetration rate and rearrangement rate), could be firmly adsorbed at the oil-water interface and supply electrostatic repulsion and steric hindrance against the aggregation of emulsion droplets. Subsequently, the micro-rheological analysis indicated that XG1/CD1-stabilized emulsion had the highest MVI value (0.79 nm−2·s at 3600 s), suggesting it may be more dominant during long-term stability. Furthermore, the correlation between interfacial behavior of the XG/CD complex and the emulsion’ long-term stability index was revealed by establishing a Pearson correlation analysis model, and the results demonstrated that the long-term stability of the Pickering emulsions can be predicted by the interfacial behavior of XG/CD complex, which had a significant correlation (p ≤ 0.05). Our findings not only present a novel application for CD and XG in food, but also a new strategy for creating food-grade Pickering emulsion.

대학 태권도 학생선수의 능력믿음, 운동스트레스, 진로미결정 및 중도탈락의도의 관계

The purpose of this study is to verify the relationships among ability belief, exercise stress, career indecision, and dropout intention of the college taekwondo athletes. College taekwondo athletes were subjected to questionnaire and based on convenience sampling, total of 348 out of 407, excluding 57 samples that were not suitable for analysis were used for final data analysis. For statistical methods for data processing, frequency analysis, reliability analysis, exploratory factor analysis, correlation analysis, and structural equation model analysis were implemented utilizing SPSS 20.0 and AMOS 20.0 programs. The ability belief of college taekwondo athletes had significant impact upon dropout intention, and exercise stress, The exercise stress of college taekwondo athletes had significant impact upon career indecision, and dropout intention, The career indecision of college taekwondo athletes had significant impact upon dropout intention. Ultimately, in order to reduce the dropout of athletes, it suggests the importance of psychological management to increase athletes' ability belief, the creation of a light sports culture to reduce sports stress, and the need for career education considering individual aptitudes and interests.

엘리트 태권도 지도자의 변혁적 리더십이 운동지속의사 및 경기력에 미치는 영향

The purpose of this study was to verify the relationship between leadership, intention to continue exercise, and performance of elite taekwondo players. Subjects of this study were elite Takwondo athletes registered in 2022 in Korea Taekwondo as the population, and a total of 215 samples were collected using the non-probability sampling method. A total of 202 data were used for analysis, excluding 12 inconsistent among the surveyed questionnaires. Data processing was based on SPSS 22.0 and AMOS 22.0 and data were analyzed through frequency analysis, confirmation factor analysis, reliability analysis, correlation analysis, and structural equation model. The results of this study are as follows. First, The transformational leadership of elite taekwondo leaders has been shown to have a positive effect on the intention to continue exercise. Second, The transformative leadership of elite taekwondo leaders has been shown to have a negative impact on performance. Third, Elite taekwondo athletes' intention to continue exercise has been shown to have a positive effect on performance.

중년여성 만학도의 학습참여동기와 주관적 안녕감의 관계에서 의미추구와 의미발견의 이중매개효과

Objectives The purpose of this study was to identify the relationship between motivation to participate in learning on subjective well-being among middle-aged female later learners entering a college degree program and to investigate the dual mediating effects of search for meaning and presence of meaning in the relationship.&#x0D; Methods A total of 245 middle-aged female later learners aged 40 to 65 years who were enrolled in colleges in Busan. completed the questionnaires to measure motivation to participate in learning, subjective well-being, search for meaning and presence of meaning. Pearson correlation analysis and Process Macro model 6 were used to analyze the relationship between subjective well-being and motivation to participate and dual mediation effect of search for meaning and presence of meaning in the relationship, respectively. Additionally, bootstrapping was conducted to verify the significance of the mediation effect.&#x0D; Results First, motivation to participate in learning was positively related to search for meaning, presence of meaning and subjective well-being. Second, there was no medication effect of search for meaning in the relationship between motivation to participate in learning and subjective well-being. Third, there was a mediating effect in presence of meaning the relationship between motivation to participate in learning and subjective well-being. Fourth, there was a dual mediation of search for meaning and presence of meaning in the relationship between motivation to participate in learning and subjective well-being.&#x0D; Conclusions This study could provide empirical support for possible specific interventions to enhance subjective well-being in among middle-aged female later learners.

Discovering e-commerce user groups from online comments: An emotional correlation analysis-based clustering method

Platform merchants mine user clusters and their characteristics to assist in precision marketing. In view of the information overload in e-commerce reviews, machine methods are needed to efficiently obtain clustering information from text. This study innovatively integrated the emotional correlation analysis model and Self-organizing Map (SOM) in application, to construct fine-grained user emotion vector based on review text and perform visual cluster analysis, which helped quickly mine user clustering and characteristics from review text. The result of empirical analysis based on real reviews of Amazon books showed that the proposed method had the average precision as 0.71, confirming that the clustering method integrating the emotional correlation analysis model and SOM could efficiently mine user groups and match appropriate marketing strategies, which will help platform merchants carry out precision marketing. The study makes contributions to the application and innovation of researches in the field of user clustering and e-commerce precision marketing.

Determining Factors Effecting the Population Growth Rate of Villages in Turkey: An Econometric Perspective

Assuming core (permanent) population to be vital to the maintenance of the village and rural life, this study investigates the population growth rate (PGR) of villages in Turkey. PGR is used as a dependent variable in the analysis, using a sample of 201 villages. The independent variables are ascertained through face-to-face interviews with village heads (mukhtars). Hypothesis tests, correlation analysis and econometric models are used to examine the development/decline trends of the PGR of the village. The results show that total land property of the village and land property per household are the strongest variables supporting the continuity of population. Agricultural income remains the biggest income item in most villages, and this increases according to land size. Beyond this, opportunities for paid work outside the village while living in it (extra-village employment) positively affect the rate of increase of the village population.

Vegetable Pricing and Replenishment Decision Based on Correlation Analysis and Entropy Weight-TOPSIS Model

This article studies the automatic pricing and replenishment decision-making of vegetable products through statistical analysis and modeling. Firstly, a descriptive statistical analysis of the data was conducted, and it was found that the vegetable categories did not fully conform to the normal distribution relationship. The correlation between each category was also explored. Subsequently, grey correlation analysis was used to explore the correlation between individual products within each category. Then, in the overall modeling process, the entropy weight TOPSIS model is used to select sellable items, and linear regression is used to predict the pricing situation for the next day. Using ant colony algorithm to solve the maximum return portfolio pricing strategy model, a profit of 912.235 yuan and corresponding pricing strategy and replenishment volume were obtained. Finally, five factors that affect the profits of supermarkets were proposed, and relevant suggestions were given to enhance the profits of supermarkets.