Company includes: Training requirement assessment, training commitment, training methods, training content as well as training evaluation.. Recognizing the importance and impact of train
Building questionnaires and encoding scale
The questionnaire was quantified by the researcher on a 5-level Likert scale (1
- strongly disagree up to 5 - Strongly agree) based on previous studies with the factors proposed in Research model includes: Training Needs Assessment,
The training program emphasizes commitment, content, methods, and evaluation To ensure clarity, questions are designed to be simple and easily understandable, avoiding complexity that could confuse respondents The questionnaire is structured into two main sections, beginning with a screening question to identify the appropriate audience for the survey.
Have you participated in company training programs for employees?
Those who choose answer A please continue to the next survey questions. And for those who have not attended any of the company's training courses, please stop the survey.
24 s* The first part contains questions designed by researcher to collect information about the demographics of survey participants. s* The second part relates to the research model factors including:
Training Needs Assessment, Training Commitment, Training Content, Training Methods, Training Evaluation and Performance Variable employee's work.
Enterprise has reduced waste in the production process
Evaluate Enterprise has classified waste in TEF 2 Arthur & effectiveness | the production process Bennett, after training | Enterprise has effectively used the | TEF_3 2003 energy consumed in the production process
Enterprise has effectively used TEF_4 water consumed in the production process
Enterprise has increased the use of | TEF_5 enviromentally friendly coal materials and rawmaterials Training Do you need to take part in the
Needs training courses of quality Goldstein
Do those training courses of TNA_2 2002 Quality department satisfy your
Do you want to take further training courses led by Quality Department?
Are those training course performed effectively and thoughtfully?
Do the department's training courses provide you with necessary knowlege?
Are those training courses performed timely to apply effectively to your work?
The company facilities have met your training requirement yet?
How would you evaluate the content of the department's quality management training?
Training cintent always updated compared to the current reality?
Is the training duration suitable for delivery of training content?
Is the training time and frequency suitable? TCT_4
How is the trainer's method of conveying training content? TM_1 Did the trainer interact with and receive feedback from the trainees TM_2
26 methods during the training process?
Do you understand the whole training content after the course? TM_3
Are you statisfied with the trainer's training method? TM_4
I usually clean up and turn off electrical appliances (ex: computer, printer ) before finishing work
I pay attention to the types of waste and waste to put in the correct trash as prescribed
I am concious of the use and protection of machines,equipment and materials in the workplace
I use water in the sciencific toilet to save water CBH_4
I advise my colleagues when they are not complying with safety and the workplace enviroment
Training Needs Assessment is essential for identifying the gap between employees' current skills and the desired training outcomes By precisely defining training requirements and the existing skill gaps, organizations can develop effective training programs aligned with their competency framework This rationale will be clearly communicated to survey participants.
Methods of sampling and data collectIon - ôô-sô+ss+++ 28
Methods of collecting primary đafa ôô+ss<++<++ 28
The researcher conducted a primary database collection for the study by surveying quality control employees at Samsung Display Vietnam Data was gathered through an online questionnaire distributed via Google Forms.
Sample S1Z© G1 HH HH ng ng 28
According to Hair et al (2014), a sample expansion requires at least 100 observations, with the sample size needing to be five times the number of observed variables In this study, which includes 22 observed variables, the minimum sample size calculated is 110 (22 x 5) The researcher distributed an online survey to 554 quality control employees, receiving 525 valid responses, thus exceeding the minimum sample size and qualifying for analysis.
Analyzing Data Pẽan .- c5 c1 331 113151335E5EEerrrerre 28
Reliability analysis by Cronbach’s alpha
Reliability is the degree of consistency among items measuring a variable, ensuring internal coherence according to Hair et al (2014) A commonly used metric for assessing reliability is Cronbach's alpha, which ranges from 0 to 1 Values between 0.5 and 0.95 indicate acceptable consistency among items, while higher values may suggest redundancy An alpha below 0.5 signifies poor reliability.
Exploratory Factor Analysis — EEA cccc+scessx 28
Factor analysis is a statistical method that simplifies large sets of variables into fewer, more meaningful groups As noted by Hair et al (2014), exploratory factor analysis is a widely utilized technique that helps identify relationships among variables This approach allows researchers to uncover underlying patterns and structures within data, enhancing the interpretability of complex datasets.
(1998) said that it was used to determine the factors that affected variables and to analyze which variables "came together."
Research on hair and others (2014) The following possible assessments of factor loads were made:
* A range of 0.3 to 0.4 is considered the lowest level of interpretation.
Load factors of 0.5 or higher indicate a significant correlation, while values exceeding 1.7 suggest a well-defined structure The factor load must be adjusted according to the sample size, as different sample sizes necessitate varying factor load values (Hair et al., 2014) The required sample sizes for each element to achieve appropriate load levels are detailed in the accompanying table.
TABLE 2 Guidelines for Identifying Significant Factor
Loadings Based on Sample Size
Sample Size Needed Factor Loading for Significance*
* Significance is based on a 05 significance level (œ), a power level of 80 percent, and standard errors assumed to be twice those of conventional correlation coefficients.
Source: Computations made with SOLO Power Analysis, BMDP Statistical Software, Inc., 1993.
Guidelines for Identifying Significant Factor Loadings
The Kaiser-Meyer-Olkin (KMO) measure, as detailed by Hair et al (2014), evaluates the adequacy of factor analysis, with Kaiser (1974) categorizing a KMO value of 0.9 as excellent.
Bartlett test is a measure that compares the correlation matrix with the identity matrix If Sig Bartlett's test is less than 0.05, the observed variables have correlation.
Regression analySsiS .ceecesccsseceseceseceseceeceseeeseesseesseesseesneesaes 30
Regression analysis is a powerful statistical tool used to identify the relationships between multiple variables By examining how independent variables influence a single dependent variable, researchers can uncover which factors are significant predictors and understand the extent of their impact This method is essential for analyzing data and drawing meaningful conclusions in various fields.
DeCoster and Claypool (2004) proposed the following general form of multiple regression model:
In which: ° Y: dependent variable ¢ Xi: independent variables
The first step of regression analysis is to test multicollinearity, that is, there is some interaction between independent variables Therefore, VIF test is
To prevent multicollinearity in your model, it's essential to ensure that independent variables do not exhibit a linear relationship A key indicator of this is the Variance Inflation Factor (VIF); if the VIF value exceeds 2, the corresponding factor should be eliminated from the model to maintain its integrity.
Multivariate R, often referred to as the decision coefficient, quantifies the strength of the overall linear relationship in multivariate regression This metric indicates the extent to which the dependent variable is explained by the independent variables in a multiple regression analysis.
RESULTS AND DISCUSSION eceeeeeeereeeeeeeeeeeeeeeeees 32 4.1 Overview about Samsung Display Vietnam .- -sô 30
General introduction eee eeeesecsecseeesesecseesseesessesnseeeeeaee 30
¥ Company name: Samsung Display Vietnam Company Limited Short
Name: SDV. v Address: Yen Phong Industrial Park, Yen Trung Commune, Yen Phong
District, Bac Ninh Province. vé Tel.: (0241) 390 5002.
Founded in July 2014, Samsung Display Vietnam Co., Ltd is a subsidiary of Samsung Group from Korea, focusing on the production of LCD and OLED screens for various devices such as phones, watches, tablets, and televisions With a total investment of $5 billion, the company boasts an impressive capacity of 160 million products per year and is recognized as the world's first and only manufacturer of flexible screens.
(OLED) products in Vietnam Number of employees: 45 000 employees
SDV is a subsidiary of Samsung group, so it is always working towards 5 core values of Samsung, which are:
VY People: The company is the environment for human development. ¥Y Excellence: No.1 position in all fields. vY Change: Execute a rapid change of reform. v Integrity: Seeking righteousness in all things.
Y Co-prosperity: For a heart for community coexistence.
SDV specializes in manufacturing high-tech products that are the first flexible screens in the world such as Oled, Flecxible, TV screens (UHD,
UHD / QUHD), watches, tablets SDV currently is the main AMOLED screen supplier for the new Apple iPhone X, Oppo.
In the future, SDV is moving towards the ideas of environmentally friendly QLED screens, as well as the idea of an interactive touch screen
SDV, a global leader in LCD and AMOLED display production, is actively engaged in research and development for display manufacturing and service provision The company fosters a youthful, dynamic, and professional work environment, offering employees numerous opportunities for career advancement and skill enhancement in the rapidly evolving 4.0 era.
Training strategy of Samsung Display Vietnam
Samsung prioritizes its people as the most valuable asset, dedicating significant resources to human resource development and training programs The company aims to ensure that each employee excels not only in their technical skills but also possesses a broad understanding of cultural and social contexts.
Employee training is a key annual priority at Samsung, which allocates a significant budget for internal training programs aimed at enhancing personnel quality This commitment plays a crucial role in addressing the shortage of skilled and highly skilled talent within the organization.
Samsung Display Vietnam faced significant challenges during its initial development phase due to a shortage of skilled technical professionals in the country This issue is not unique to Samsung; it affects various electronics and technology manufacturing companies in Vietnam, including Intel, IBM, and BOSC Consequently, Vietnam has attracted limited foreign direct investment (FDI), primarily in light outsourcing and electronic assembly The ongoing concern over human resource shortages frequently arises in discussions with foreign businesses, highlighting the urgent need for skilled labor in the industry.
Samsung has introduced a new human resource training strategy in the Vietnamese market, focusing on the self-training of high-quality human resources This innovative approach aims to enhance the skills and capabilities of employees, ensuring that they meet the demands of the evolving market.
We provide a variety of human resource training programs tailored for Vietnamese employees to enhance productivity and work efficiency Our training is designed not only for new hires but also for existing staff, ensuring continuous professional development The curriculum emphasizes essential skills and knowledge pertinent to the business, complemented by regular extracurricular activities that foster employee engagement and strengthen their connection with the company.
And so far, Samsung Display Vietnam is the strongest manufacturing subsidiary in the world In Vietnam, Samsung accounts for an average of 33% of the market volume.
Samsung's effective human resource training strategy fosters a highly productive workforce, enhances employee engagement, and provides opportunities for personal and professional development.
Samsung Display Vietnam conducts internal training programs to enhance employees' understanding of the company's culture and operational processes, tailored to align with local business practices in Vietnam.
In Quality Department, a large number of training programs have been conducted in reality, which brought back effective performance for employees in practice.
The list of program can be sum up grouping as below:
1/ Training programs focusing on management and communication skill:
2/ Training programs focusing on directly enhancing technique and knowledge on system and technology analysis
3/ Training programs focusing on safety and security compliance in working and measurement tools
Training high-quality human resources emphasizes the importance of equipping employees with knowledge and skills that align with the company's production and business activities The training programs are continuously updated to incorporate the latest trends in electronics and technology, ensuring that the workforce remains competitive and adept in a rapidly evolving industry.
Samsung facilitates collaborative teaching and training programs for its workforce to enhance professional skills Additionally, the company offers internship training opportunities on-site, allowing employees to apply their acquired knowledge directly in the workplace.
Training support programs such as Samsung Talent Program is one of the training programs to help provide effective human resources for SamsungR&D centers.
Functions and responsibilities of the quality control department
SDV's human resource training strategy prioritizes product quality, focusing on high-quality display production and robust quality control mechanisms This concern is central to the Management Board and is a key strategy for the Quality Control Department To align with the company's goals, the Quality Control Department dedicates significant effort to develop and implement comprehensive training programs for both its members and employees across all departments, emphasizing essential quality functions and responsibilities.
The Quality Control Department plays a crucial role in ensuring product quality before shipment by rigorously evaluating components from vendors to SDV This department acts as a protective barrier, filtering the best parts to ensure a smooth production process All incoming quality inspectors and engineers are dedicated to producing high-quality semi-finished products, guided by comprehensive training and daily inspections This unified approach transforms the production stages into interconnected processes, with SDV serving as a quality conduit that delivers pristine finished goods to customers.
The Quality Control Department plays a vital role in overseeing product quality by constructing and collaboratively safeguarding intricate doors throughout various production stages This robust yet adaptable quality control mechanism ensures that employees across all departments are equipped with a thorough understanding of prioritizing quality at every detailed step of the production process.
The ongoing challenge between maintaining quality control and meeting the demand for timely product shipments necessitates a collaborative spirit among production engineers and inspection experts This dynamic requires the Quality Control Department to continuously enhance oversight of production activities Consequently, every quality control document, including SOPs, manuals, and guidelines, undergoes meticulous review and approval by Quality Control Experts, ensuring their effective implementation across all production lines and inspection processes.
To ensure a long product life in customers' hands, Quality Control plays a crucial role in promptly identifying and addressing production issues This process involves thorough analysis conducted by skilled quality engineers, who bring both theoretical knowledge and practical experience to the table Their expertise is essential for uncovering the root causes of problems and implementing effective solutions Consequently, quality control engineers undergo extensive training in product structure and detailed production processes to enhance their analytical capabilities.
The Quality Control Department plays a crucial role in ensuring the quality of both developed and mass-produced products by participating from the outset of new product development By leveraging accumulated experience from previous products, the department maintains best practices while conducting thorough analyses of past weaknesses to inform future quality control measures This proactive approach includes potential design failure mode and effect analysis (DFMEA), which helps identify and mitigate risks in new product designs.
37 becomes one of the most value training topics of the Quality Control Department yearly.
To enhance product processes, the Quality Control Department is tasked with conducting hourly and daily audits to identify any discrepancies in production scores Gaining a thorough understanding of actual production activities and effectively evaluating the quality of the production process presents a significant challenge for the Quality Control Department.
The Quality Control Department plays a crucial role in ensuring the overall quality of finished products and providing excellent after-sales service To achieve this, a robust customer feedback mechanism is established, allowing for open communication and active listening to customer needs regarding production quality improvements This department acts as a flexible bridge, connecting all teams to address challenges throughout the quality assurance process, from incoming materials to the final delivery of goods, ensuring customer satisfaction both before and after the product reaches their hands.
A survey was conducted among 554 employees in the quality department of Samsung Display Vietnam, resulting in 525 valid responses after data cleaning The analysis provides detailed insights into the sample description.
From 26 — 30 years 265 50.5 old From 31 — 35 years 110 21 old From 36 — 45 years 28 5.3 old
University or higher 55 10.5 Less than 5 years 429 81.7 Seniority in From 5 — 10 years 78 14.9 work Over 10 years 18 3.4
It seems that the text you provided is not coherent and appears to be a mix of letters and symbols rather than a meaningful article If you could provide a clear and coherent article, I would be happy to help you rewrite it while adhering to SEO rules.
4.3.1 Test the reliability of the Training Needs Assessment - TNA scale
Table 4.3 The Outstanding statistics of the Training Needs Assessment scale
Table 4.4 The Item Total statistics of the Training Needs Assessment’s varibales ltem-Total Statistics
Scale Mean if Variance if ltem-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Training Needs Assessment (TNA) scale consists of three observed variables: TNA_1, TNA_2, and TNA_3 With a Cronbach's alpha of 0.726, which exceeds the acceptable threshold of 0.5, the scale demonstrates strong reliability Additionally, the total variable correlations for the observed variables are 0.527, 0.505, and 0.621, all of which are above the minimum requirement of 0.3 This confirms the reliability of the TNA scale.
4.3.2 Test the reliability of the Training commitments- TCM scale
Table 4.5 Statistics reliability of the Training commitments- TCM scale
Alpha Items NM of tems
Table 4.6 Item-Total Statistics reliability of the Training commitment’s variables
Scale Mean if Variance if ltem-Tntal Multiple Alpha ifltem Item Deleted Item Deleted Correlation Correlation Deleted
The analysis of training commitment, comprising four items (TCM_1, TCM_2, TCM_3, TCM_4), demonstrates a Cronbach's alpha of 0.790, indicating good reliability as it exceeds the acceptable threshold of 0.5 Additionally, the correlation coefficients among the observed variables are 0.645, 0.642, 0.555, and 0.559, all of which surpass the minimum value of 0.3 These results confirm that the scale used for measuring training commitment is reliable.
4.3.3 Test the reliability of Training contents - TCT scale
Table 4.7 Training contents - TCT reliability statistics
Table 4.8 Item-Total Statistics reliability of the Training content’s variables
Scale Corrected Squared Cronbach's Scale Mean if Variance if ltem-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Training Contents Scale consists of four observed variables: TCT_1, TCT_2, TCT_3, and TCT_4 With a Cronbach's alpha of 0.654, the scale demonstrates reliability, as it exceeds the acceptable threshold of 0.5 Additionally, the correlation coefficients for the observed variables are 0.503, 0.497, 0.370, and 0.385, all of which are above the 0.3 mark, further confirming the scale's reliability.
4.3.4 Test the reliability of the Training methods - TM scale
Table 4.9 Training methods - TM reliability statistics
Table 4.10 Item-Total Statistics reliability of the Training method’s variables
The Training Methods scale consists of four observed variables: TM_1, TM_2, TM_3, and TM_4 With a Cronbach's alpha of 0.666, which exceeds the acceptable threshold of 0.5, the scale demonstrates reliability Additionally, the total variable correlations for the observed variables are 0.443, 0.432, 0.447, and 0.464, all of which are greater than 0.3, further confirming the scale's robustness.
4.3.5 Test the reliability of the Change Behavior - CBH scale
Table 4.11 Change behavior — CBH reliability statistics
Table 4.12 Item-Total Statistics reliability of the Change behavior’s variables
Scale Mean if Variance if Item-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Change Behavior Scale consists of five observed variables: CBH_1, CBH_2, CBH_3, CBH_4, and CBH_5 With a Cronbach's alpha of 0.662, which exceeds the acceptable threshold of 0.5, the scale demonstrates reliability Additionally, the total variable correlations for the observed variables are 0.326, 0.333, 0.532, 0.478, and 0.420, all of which are above the 0.3 mark, further supporting the scale's reliability.
4.3.6 Test the reliability of the Training Effectiveness Scale - TEF
Table 4.13 Statistics reliability of Training Effectiveness — TEF scale
Table 4.14 Item-Total Statistics reliability of the Training effectiveness’s variables
Scale Mean if Variance if ltam- Tatal Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
(Source: Analysis on SPSS 16.0) The employee performance scale includes 3 observed variables, respectively: TEF_1, TEF_2, TEF_3, TEF_4, TEF_5 Cronbach's alpha for
Reliability Analysis - . ng ng ngư 41
4.3.1 Test the reliability of the Training Needs Assessment - TNA scale
Table 4.3 The Outstanding statistics of the Training Needs Assessment scale
Table 4.4 The Item Total statistics of the Training Needs Assessment’s varibales ltem-Total Statistics
Scale Mean if Variance if ltem-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Training Needs Assessment (TNA) scale comprises three observed variables: TNA_1, TNA_2, and TNA_3 With a Cronbach's alpha of 0.726, which exceeds the acceptable threshold of 0.5, the scale demonstrates strong reliability Additionally, the total variable correlations for the observed variables are 0.527, 0.505, and 0.621, all of which are above the 0.3 benchmark, further confirming the scale's reliability.
4.3.2 Test the reliability of the Training commitments- TCM scale
Table 4.5 Statistics reliability of the Training commitments- TCM scale
Alpha Items NM of tems
Table 4.6 Item-Total Statistics reliability of the Training commitment’s variables
Scale Mean if Variance if ltem-Tntal Multiple Alpha ifltem Item Deleted Item Deleted Correlation Correlation Deleted
The analysis of training commitment, comprising four items (TCM_1, TCM_2, TCM_3, TCM_4), reveals a Cronbach's alpha of 0.790, indicating strong reliability as it exceeds the acceptable threshold of 0.5 Additionally, the correlation coefficients among the observed variables are 0.645, 0.642, 0.555, and 0.559, all surpassing the minimum value of 0.3, further confirming the scale's reliability.
4.3.3 Test the reliability of Training contents - TCT scale
Table 4.7 Training contents - TCT reliability statistics
Table 4.8 Item-Total Statistics reliability of the Training content’s variables
Scale Corrected Squared Cronbach's Scale Mean if Variance if ltem-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Training Contents Scale comprises four observed variables: TCT_1, TCT_2, TCT_3, and TCT_4 With a Cronbach's alpha of 0.654, which exceeds the acceptable threshold of 0.5, the scale demonstrates reliability Additionally, the total variable correlations for the observed variables are 0.503, 0.497, 0.370, and 0.385, all of which are above the minimum requirement of 0.3 Thus, the scale can be deemed reliable for assessing training content.
4.3.4 Test the reliability of the Training methods - TM scale
Table 4.9 Training methods - TM reliability statistics
Table 4.10 Item-Total Statistics reliability of the Training method’s variables
The Training Methods scale consists of four observed variables: TM_1, TM_2, TM_3, and TM_4, with a Cronbach's alpha of 0.666, indicating good reliability since it exceeds the 0.5 threshold The total variable correlations for these observed variables are 0.443, 0.432, 0.447, and 0.464, all of which are above the acceptable level of 0.3 Consequently, the scale is deemed reliable.
4.3.5 Test the reliability of the Change Behavior - CBH scale
Table 4.11 Change behavior — CBH reliability statistics
Table 4.12 Item-Total Statistics reliability of the Change behavior’s variables
Scale Mean if Variance if Item-Total Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
The Change Behavior Scale comprises five observed variables: CBH_1, CBH_2, CBH_3, CBH_4, and CBH_5 With a Cronbach's alpha of 0.662, which exceeds the acceptable threshold of 0.5, the scale demonstrates reliability Furthermore, the total variable correlations for the observed variables are 0.326, 0.333, 0.532, 0.478, and 0.420, all of which are above the 0.3 mark, reinforcing the scale's dependability.
4.3.6 Test the reliability of the Training Effectiveness Scale - TEF
Table 4.13 Statistics reliability of Training Effectiveness — TEF scale
Table 4.14 Item-Total Statistics reliability of the Training effectiveness’s variables
Scale Mean if Variance if ltam- Tatal Multiple Alpha if Item Item Deleted Item Deleted Correlation Correlation Deleted
(Source: Analysis on SPSS 16.0) The employee performance scale includes 3 observed variables, respectively: TEF_1, TEF_2, TEF_3, TEF_4, TEF_5 Cronbach's alpha for
The EP value of 0.756 exceeds the threshold of 0.5, indicating strong reliability The correlation coefficients for the three observed variables are 0.420, 0.511, 0.559, 0.587, and 0.740, all of which are above the acceptable level of 0.3 This supports the conclusion that the scale demonstrates high reliability.
Exploratory Factor AnaèẽYSIS .- cv ru 46
4.4.1 EFA test results of the independent variable
After reliability analysis, all the items are confirmed to be reliable to explain their scales Therefore, 20 items are used to conduct exploratory factor analysis.
Table 4.15 Summary of coefficients' statistical results in EFA discovery factor analysis
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 833 Bartlett's Test of Approx Chi-Square 3729.003
The analysis results indicate a KMO value of 0.833, which exceeds the threshold of 0.5, and a significance coefficient (Sig) of 0.000, which is below the 0.05 requirement These findings confirm that the observed variables in the research model are correlated, validating the appropriateness of applying the Exploratory Factor Analysis (EFA) method in this study.
The total variance explained by the proposed research model is 55.658%, exceeding the 50% threshold and meeting the requirement Additionally, the factor extraction at factor 5 yields a value of 1.197, which is greater than 1, further satisfying the criteria Consequently, five elements from the proposed model are identified.
Table 4.16 The total variance explained of EFA for the independent variable
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
% of Variance | Cumulative % Total % of Variance | Cumulative % Total % of Variance | Cumulative %
22.180 33.378 42.448 49.675 85.858 60.231 64.392 68.135 71.836 75.271 78.595 81.887 84.756 87.830 80.432 92.999 95.313 97.411 99.340 100.000 Extractian Method: Principal Component Analysis.
The rotation matrix results in 5 factors drawn and the factors all have coefficients greater than 0.5 (satisfying the requirements) As follows:
Table 4.17 Rotation matrix of exploratory factor analysis EFA is independent variable
(Source: Analysis on SPSS 16.0) 4.4.2 EFA test results of the dependent variable
Table 4.18 Synthesize the results of EFA for the dependent variable
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Bartlett's Test of Approx Chi-Square
Table 4.11 indicates a KMO value of 0.809, exceeding the threshold of 0.5, and a significance coefficient (Sig.) of 0.000, which is less than 0.05 These results confirm that the observed variables are correlated, validating the suitability of using Exploratory Factor Analysis (EFA) in this study.
In addition, the results of factor analysis also showed that the total variance explained is 50.835% > 50% and the stopping point when extracted is 2.542 >
1, both satisfy the condition One factor is drawn from the analysis
Table 4.19 The total variance explained of EFA for the dependent variable omponent Total % of Variance | Cumulative % Cumulative %
The rotation matrix results of factors drawn and the factors all have
Extraction Method: Principal Component Analysis. coefficients greater than 0.5 (satisfying the requirements) As follows:
Table 4.20 Rotation matrix of EFA for the dependent variable
Before performing regression analysis, the researcher conducted Pearson correlation analysis to assess multicollinearity among the variables The average representation of the elements was generated using the command Transform / Compute / Variable / Mean.
Table 4.21 Coding mean representations of factors
No Factor name Number of Name the observed medium variables representative
6 | Change behavior after training 5 CBH
The Pearson correlation analysis reveals the relationship between Training Effectiveness (TEF) and five independent variables: Training Needs Assessment (TNA), Training Commitment (TCM), Training Content (TCT), Training Method (TM), and Change Behavior after Training (CBH).
TM Correlation is significant atthe 0.01 level (2-tailed).
The correlation matrix indicates that all significant coefficients between the independent and dependent variables are below 0.05, making the data suitable for regression analysis As shown in Table 4.14, the correlation coefficients demonstrate a strong and positive relationship between the independent variables and the dependent variable.
The correlation coefficient of the dependent variable for each independent variable ranges from 0.133 to 0.408 (The average correlation is quite strong).
This shows a linear correlation between the dependent variable DLLV and the independent variables Model studies the factors affecting work motivation of employees in enterprises.
TEF =a,*TNA+a,*TCM + az * TCT + a¿* TM +a, * CBH
4.5.2 Verify multivariate linear regression model
After test the correlation between the variables in the model, the researcher conducted a linear regression analysis The results of the regression analysis are presented below:
Table 4.23 Results of regression analysis a Predictors: (Constant), CBH, TCM, TNA, TM, TCT b Dependent Variable: TEF
The linear regression analysis results indicate that the regression model has an R-squared value of 0.304 and an adjusted R-squared value of 0.297 This suggests that the independent variable accounts for 29.7% of the variation in the dependent variable (Hoang Trong, Mong Ngoc, 2008).
To evaluate the overall suitability of the linear regression model, an F-test was conducted, which assesses the linear correlation between the dependent variable and all independent variables The null hypothesis (H_0) is defined as: aj =@2 = đa =ữứy =ứa 0 The findings from the F-test of this study's linear regression model are presented below.
Table 4.24 Test results of the appropriateness of the regression model
The analysis conducted using SPSS 16.0 revealed a significance value (Sig.) of less than 0.05, leading to the rejection of the null hypothesis (H_O) This indicates a linear relationship between the dependent and independent variables in the research model The study employed the Enter method for linear regression analysis, and the results are detailed in the following findings.
Table 4.25 Results of regression analysis
TNA TCM TCT TM CBH a Dependent Variable: TEF
(Source: Analysis on SPSS 16.0) From the above result we lose the value of Sig all show high reliability, both
The analysis reveals that all VIF coefficients for the Beta coefficients are below 10, with the highest value being 1.439, while the Tolerance coefficient exceeds 0.5, with a minimum of 0.695 Additionally, the significance level of the two-sided test between the independent and dependent variables satisfies the criterion, as indicated by a significance value of less than 0.05.
4.5.3 Multiple regression equations and conclusions about the hypotheses
Research findings indicate that five key training activity factors significantly impact the performance of quality control employees at Samsung Display Vietnam These factors include Training Needs Assessment, Training Commitment, Training Content, Training Method, and Behavioral Change Post-Training The study involved thorough testing of scale reliability, correlation between independent and dependent variables, factor analysis, and model appropriateness to arrive at these conclusions.
The quantitative analysis reveals that five key factors significantly enhance the performance of quality control employees at Samsung Display Vietnam The study identifies these factors, ranked from strongest to weakest influence on employee performance within the quality control department.
Table 4.26 The impact level of factors in the research model
Factor Standardized beta coefficients Training needs assessment 125
Table 4.27 Hypothesis of testing result
Hypothesis Sig Result coefficient H1: Training needs assessment has a 002