IMPLICATIVE STATISTICAL ANALYSIS VS CONFIRMATORY FACTOR ANALYSIS IN EVALUATION OF THE LIFELONG LEARNING IMPACT ON HUMAN RESOURCE DEVELOPMENT

2018 ◽  
Author(s):  
Sofia Anastasiadou ◽  
Stella Giossi
Keyword(s):  
Factor Analysis ◽  
Statistical Analysis ◽  
Confirmatory Factor Analysis ◽  
Lifelong Learning ◽  
Human Resource Development ◽  
Human Resource ◽  
Resource Development ◽  
Confirmatory Factor

Consequences of Not Conducting Measurement Invariance Tests in Cross-Cultural Studies: A Review of Current Research Practices and Recommendations

2019 ◽  
Vol 21 (4) ◽  
pp. 466-483
Author(s):  
Shinhee Jeong ◽  
Yunsoo Lee
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Human Resource Development ◽  
Measurement Invariance ◽  
Human Resource ◽  
Cross Cultural ◽  
Measurement Models ◽  
Cultural Research ◽  
Confirmatory Factor ◽  
Cross Cultural Research

The Problem Cross-cultural research has received substantial attention from both academia and practice as it contributes to expand current theory and implements culturally successful human resource strategies. Although the quantity of this type of research has increased, several researchers have raised methodological concerns that the majority of cross-cultural research has simply assumed or ignored measurement invariance. The Solution In this article, we first provide the meaning for measurement invariance, discuss why it is important, and then explain stepwise confirmatory factor analysis procedures to test measurement invariance. We also diagnose the current research practice in the field of human resource development (HRD) based on a review of cross-cultural, comparative research published in the major HRD journals. Finally, we demonstrate that the group difference test results that have been found without ensuring measurement invariance can, in fact, be false. The Stakeholders This article contributes to the HRD literature and practice in two ways. First, HRD researchers are invited to recognize the importance of sophisticated research methodology, such as measurement invariance, and to examine item bias across different groups so they can make a meaningful and valid comparison. The same attention is advisable to any practitioner who attempts to identify group differences using multinational/cultural data. This article also provides HRD scholars and practitioners with specific multigroup confirmatory factor analysis (MGCFA) procedures to facilitate empirical tests of measurement models across different groups and thus disseminate the methodological advances in the field of HRD. It is our hope that the present article raises awareness, circulates relevant knowledge, and encourages more HRD scholars to think critically about measurement.

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).

Tour Conductor Playfulness: Conceptualizing and Scale Development

2020 ◽  
Vol 60 (1) ◽  
pp. 197-207
Author(s):  
Tien-Ming Cheng ◽  
Mei-Tsun Chen ◽  
Cheng-Ho Wu
Keyword(s):  
Factor Analysis ◽  
Content Analysis ◽  
Confirmatory Factor Analysis ◽  
Human Resource ◽  
Convergent Validity ◽  
Discriminant Validity ◽  
Future Research ◽  
Tourism Research ◽  
Confirmatory Factor ◽  
Depth Interviews

The purpose of this study is to conceptualize a construct of Tour Conductor Playfulness (TCP) and establish a set of reliable and valid measures for TCP. The construct of TCP introduces a new concept in tourism research, while also extending the application of playfulness theory. TCP also can help businesses train employees and serve as a tool for human resource management. Study 1 produced initial items through in-depth interviews and content analysis, and study 2 conducted two sample collections. First, an exploratory factor analysis was performed by investigating 253 tour conductors, and four factors were identified: playful guiding, enthusiastic guiding, creative guiding, and engaged guiding. Second, this scale was validated with a new sample of 396 tour conductors. We verified the reliability of the TCP scale through confirmatory factor analysis, convergent validity, and discriminant validity to finally obtain 23 items. Implications and suggestions for future research are provided.

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).

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