Structural Relationships among Customer Delight, Exercise Commitment, and Psychological Happiness

2019 ◽  
Vol 118 (1) ◽  
pp. 8-13
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Statistical Analysis ◽  
Confirmatory Factor Analysis ◽  
Correlation Analysis ◽  
Frequency Analysis ◽  
Structural Correlation ◽  
Structural Relationships ◽  
Confirmatory Factor ◽  
Customer Delight

Background/Objectives: The purpose of this study is to find out the structural relationships among customer delight, exercise commitment, and psychological happiness to contribute developing exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted and 160 college students who are familiar with mobile exercise applications participated. The data analyzed with frequency analysis, exploratory factor analysis, confirmatory factor analysis, correlation analysis, and structural correlation analysis. The validity and the reliability were obtained: customer delight (χ2=26.532, df=14, CFI=.985, TLI=.971, RMSEA=.075), exercise commitment (χ2=113.802, df=49, CFI=.956, TLI=.941, RMSEA=.091), and psychological happiness (χ2=15.338, df=8, CFI=.989, TLI=.980, RMSEA=.076, and Cronbach’s α=.906~.938).

Structural Relationships among Customer Delight, Exercise Commitment, and Psychological Happiness

2019 ◽  
Vol 118 (8) ◽  
pp. 275-280
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Statistical Analysis ◽  
Confirmatory Factor Analysis ◽  
Correlation Analysis ◽  
Frequency Analysis ◽  
Structural Correlation ◽  
Structural Relationships ◽  
Confirmatory Factor ◽  
Customer Delight

Background/Objectives: The purpose of this study is to find out the structural relationships among customer delight, exercise commitment, and psychological happiness to contribute developing exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted and 160 college students who are familiar with mobile exercise applications participated. The data analyzed with frequency analysis, exploratory factor analysis, confirmatory factor analysis, correlation analysis, and structural correlation analysis. The validity and the reliability were obtained: customer delight (χ2=26.532, df=14, CFI=.985, TLI=.971, RMSEA=.075), exercise commitment (χ2=113.802, df=49, CFI=.956, TLI=.941, RMSEA=.091), and psychological happiness (χ2=15.338, df=8, CFI=.989, TLI=.980, RMSEA=.076, and Cronbach’s α=.906~.938).

The Effects of Exercise Commitment Facilitated by Service Quality of Smartphone Exercise Applications on Continued Exercise Intention

2019 ◽  
Vol 118 (1) ◽  
pp. 14-19
Author(s):  
Boo-Gil Seok ◽  
Hyun-Suk Park
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Regression Analysis ◽  
Statistical Analysis ◽  
Correlation Analysis ◽  
Service Quality ◽  
Frequency Analysis ◽  
Primary Data ◽  
Exercise Intention

Background/Objectives: The purpose of this study is to examine the effects of exercise commitment facilitated by service quality of smartphone exercise Apps on continued exercise intention and provide primary data for developing and/or improving smartphone exercise Apps. Methods/Statistical analysis: A questionnaire survey was conducted amongst college students who have experiences in using exercise App(s) and regularly exercise. The questionnaire is composed of four parts asking about service quality, exercise commitment, continued exercise intention, which were measured with a 5-point Likert Scale, and demographics. Frequency analysis, factor analysis, correlation analysis, and regression analysis were carried out to analyze the obtained data with PASW 18.0.

The Development of the Scale of Protective Factors: Resilience in a Violent Trauma Sample

2015 ◽  
Vol 30 (5) ◽  
pp. 735-755 ◽  
Author(s):  
Elisabeth Ponce-Garcia ◽  
Amy N. Madewell ◽  
Shelia M. Kennison
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Protective Factors ◽  
Factor Structure ◽  
Individual Factors ◽  
Clinical Settings ◽  
Clinical Criteria ◽  
Resilience Scale ◽  
Confirmatory Factor

This research developed the Scale of Protective Factors (SPF-24) to measure protective factors contributing to resilience. We investigated the factor structure of 35 items. After exploratory factor analysis, we subjected 25 items representing 2 social-interpersonal and 2 cognitive-individual factors to confirmatory factor analysis. The sample consisted of 942 college students from 3 studies and 2 institutions. To examine the diagnostic function of the SPF, we used clinical criteria to identify a subsample of participants who had experienced violent trauma and scored low, moderate, or high on an established resilience scale. Results showed that the low-resilient group scored significantly lower on all subscales of the SPF with marked differences in prioritizing/planning behavior. Implications for the research and clinical settings are discussed.

scholarly journals Effect of Emotional Intelligence and trust on Bank performance (Evidence SME’s in Indonesia)

2019 ◽  
Vol 12 (3) ◽  
pp. 1848-1855
Author(s):  
Titok Waskito Adi ◽  
Budi Prasetyo ◽  
Erlyna Hidyantari
Keyword(s):  
Factor Analysis ◽  
Emotional Intelligence ◽  
Confirmatory Factor Analysis ◽  
Correlation Analysis ◽  
Financial Performance ◽  
Banking Sector ◽  
Bank Performance ◽  
Confirmatory Factor ◽  
The Relationship ◽  
Practical Implications

This study aims to analyze trust in the relationship between staff and customers in the banking sector, its influence on financial performance in the level of emotional intelligence (EI) and their trust. Respondents were asked to complete EI tests and questions related to trust behavior. Exploratory factor analysis and confirmatory factor analysis and correlation analysis are used to identify relationships. Trust's findings are known to consist of three components: trustworthy; knowledge; and expectations. Furthermore, there is a significant correlation between trust and EI, when compared to the financial performance of relationship managers. Research weaknesses/ implications The method used by banks in collecting performance data limits the analysis that can be held. Practical implications increasing relationship manager awareness of their own emotions, and how they perceive and act on the emotions of others, will positively influence financial performance.

Validation of the Dutch Test of Conflict Handling in Chinese College Students

2019 ◽  
Vol 47 (4) ◽  
pp. 1-7
Author(s):  
Yingshan Bao ◽  
Fangwei Zhu ◽  
Yue Hu ◽  
Ning Cui ◽  
Yuan Gu
Keyword(s):  
College Students ◽  
Factor Analysis ◽  
Problem Solving ◽  
Confirmatory Factor Analysis ◽  
Conflict Management ◽  
Reliability And Validity ◽  
Chinese College Students ◽  
Confirmatory Factor ◽  
Valid Instrument ◽  
Conflict Handling

There are limitations in existing conflict management instruments used in China. Therefore, we translated the Dutch Test of Conflict Handling (DUTCH), and then examined the reliability and validity of this Chinese Revised version (DUTCH-CR). Participants were 2,035 college students at 4 universities in China. We conducted exploratory factor analysis and confirmatory factor analysis on data from questionnaires completed by the participants. Our findings show that the DUTCH-CR is a reliable and valid instrument for measuring the handling of conflicts between Chinese college students. Further, we found that 4 conflict-handling styles are more suitable for Chinese college students. This was achieved by merging the problem-solving and compromising factors into a collaborating one, and retaining the yielding, avoiding, and forcing factors of the original DUTCH instrument.

scholarly journals ANALISIS KORELASI KANONIK PADA HUBUNGAN ANTARA SOFT SKILLS TERHADAP PRESTASI BELAJAR MAHASISWA

2019 ◽  
Vol 8 (4) ◽  
pp. 267
Author(s):  
NI PUTU JULIANINGSIH ◽  
EKA N KENCANA ◽  
KOMANG GDE SUKARSA
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Soft Skills ◽  
Sampling Technique ◽  
Primary Data ◽  
Learning Achievement ◽  
Confirmatory Factor

The purpose of this study is to know the relationship between soft skills and learning achievement using canonical correlation analysis and to find out the dominant dimensions of soft skills and learning achievement using confirmatory factor analysis. The data used are primary data obtained by distributing questionnaires. The sampling technique used was proportional to size sampling with the number of respondents as many as 150 respondents. The results of the study with canonical correlation analysis showed that soft skills with learning achievement had a close relationship with canonical correlation values ??of 0.70397. The results of the study with confirmatory factor analysis showed that the dominant dimensions of soft skills and learning achievement were flexibility with the percentage of the variance of 69.081% and cognitive percentage of the variance of 71.706%.

scholarly journals Formation of Social Capital for Community College Students: A Second-Order Confirmatory Factor Analysis

2018 ◽  
Vol 47 (1) ◽  
pp. 3-30 ◽  
Author(s):  
Yu (April) Chen ◽  
Soko S. Starobin
Keyword(s):  
College Students ◽  
Community College ◽  
Social Capital ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Community College Students ◽  
Latent Variables ◽  
Institutional Agents ◽  
Family Social Capital ◽  
Confirmatory Factor

Objective: This quantitative study constructed a statistical model to measure family social capital and college social capital among community college students. The authors also examined influences of these two types of social capital constructs on degree aspiration. Method: This study utilized the STEM (Science, Technology, Engineering and Mathematics) Student Success Literacy Survey (SSSL) to collect data in all 15 community college districts in Iowa. With more than 5,000 responses, the authors conducted descriptive analysis, exploratory and confirmatory factor analysis, and structural equation modeling (SEM) analysis. Results: College social capital was measured by three latent variables such as interaction with advisors, interaction with faculty members, and transfer capital. The three latent variables were further measured by 14 survey items. Family social capital was measured by six survey items that described parent–child interaction in high school. The SEM results indicated that college social capital had stronger direct influences on degree aspiration compared with family social capital. The impact of family social capital was delivered through the mediation of college social capital. Contributions: Findings contributed to the literature by emphasizing the important role of institutional agents in promoting degree aspiration. Intervention programs should be implemented to encourage interactions between institutional agents and underrepresented and disadvantaged students.

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