2) Proud to work in a bank.
3) Glad to have chosen the bank to work with.
4) Banks are very important.
5) Feel like a member of the bank.
6) Feeling of belonging to the bank.
3.2.3.9. “Maintaining Engagement” Scale: The following factors are taken into consideration:
1) Staying in the bank is now necessary.
2) Leaving the bank is difficult at this time.
3) Life will be greatly affected when leaving the bank.
4) It is difficult to find another job after leaving the bank.
5) Investing a lot in the bank is hard to give up.
3.2.3.10. “Moral Commitment” Scale: The following factors are taken into consideration:
1) Feel responsible towards the bank.
2) Feel responsible for everyone in the bank.
3) Feeling like leaving the bank is not a good idea.
4) Feel guilty if you leave the bank.
5) The bank deserves loyalty.
6) The bank has brought too much, feel indebted to the bank.
3.2.4. Qualitative research results
After designing the preliminary scale, the author conducted a pilot interview with 10 employees of the Military Bank, Gia Dinh branch. This interview was to check the wording and meaning of the questions of the scale, and to record the interviewees' comments to make appropriate adjustments. After interviewing and recording the comments
of the interviewee. The author would like to present the official scale in his research:
Table 3.1. Measurement scale
STT
OBSERVATION VARIABLE | ENCRYPTION | |
Job Characteristics | WORK | |
1 | Does the job allow you to make good use of your personal abilities? | CV1 |
2 | Do you like what you do? | CV2 |
3 | Is your job challenging? | CV3 |
4 | Are your working facilities and equipment good? | CV4 |
Training and Advancement | DIRECTION | |
5 | Does the bank provide you with the training needed for the job? | DT5 |
6 | Are bank training programs effective? | DT6 |
7 | Are you satisfied with the bank's training programs? | DT7 |
8 | Is the bank's promotion policy fair? | DT8 |
9 | Does the bank provide you with many opportunities for personal development? | DT9 |
10 | Are you satisfied with the promotion opportunities in the bank? | DT10 |
Income | THUNHAP | |
11 | Can you live solely on your bank income? | TN11 |
12 | Are salaries and incomes paid fairly in banking? | TN12 |
13 | Is your income commensurate with your work performance? | TN13 |
14 | Are you satisfied with the salary and income in the bank? | TN14 |
Superior | CAPTREN | |
15 | Do bank managers match their words and actions? | CT15 |
16 | Do you trust the bank's management? | CT16 |
17 | Do you receive support from your superiors when needed? | CT17 |
18 | Does your superior ask for your opinion when there is a problem related to your work? | CT18 |
19 | Are you respected and trusted at work? | CT19 |
20 | Are you treated fairly and without discrimination? | CT20 |
Colleague | DNGHIEP | |
21 | Are your coworkers easygoing and pleasant? | DN21 |
22 | Do people work as a team? | DN22 |
23 | Are your colleagues willing to help each other? | DN23 |
24 | Do people have high unity? | DN24 |
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Trademark
THIEU | ||
25 | The development prospects of your bank are very clear? | TH25 |
26 | Are you proud of the bank brand? | TH26 |
27 | Does the bank always produce high quality products/services? | TH27 |
28 | Are customers satisfied and appreciate the bank's products/services? | TH28 |
Benefits | PHUCLOI | |
29 | Are you satisfied with the bank's welfare policy? | PL29 |
30 | Are your bank benefits more attractive than other banks? | PL30 |
31 | Does the bank have many valuable welfare programs such as: social insurance, health insurance, unemployment insurance, retirement care...? | PL31 |
Emotional attachment | GBTC | |
32 | Do you feel like the bank is part of your family? | GBTC32 |
33 | Does banking have an important meaning for you personally? | GBTC33 |
34 | Do you feel like you belong to the bank? | GBTC34 |
35 | Are you proud to tell others that you work at a bank? | GBTC35 |
36 | Are you happy working at this bank until you retire? | GBTC36 |
37 | Are you happy that you chose the bank to work for? | GBTC37 |
Stick to it | GBDT | |
38 | Is staying with the bank now necessary for you? | GBDT38 |
39 | Even though you want to, do you feel that leaving the bank at this time is difficult for you? | GBDT39 |
40 | How much would your life be affected if you left the bank now? | GBDT40 |
41 | If you leave the bank now, will you have few other options? | GBDT41 |
42 | If you didn't invest so much in the bank, would you have left the bank? | GBDT42 |
Moral commitment | GBDD | |
43 | Do you feel a responsibility to stay with the bank? | GBDD43 |
44 | Even though there is a better job elsewhere, do you feel that leaving the bank is not the right decision? | GBDD44 |
45 | Would you feel guilty if you left the bank at this time? | GBDD45 |
46 | Is the bank worthy of your loyalty? | GBDD46 |
47 | You cannot leave the bank at this time because of your sense of responsibility to everyone in the bank? | GBDD47 |
48
The bank has given you so many things, do you feel like you “owe” the bank too much? | GBDD48 |
In this study, a 5-point Likert scale was used to measure the above observed variables, specifically:
Level 1: Completely disagree.
Level 2: Disagree.
Level 3: Normal.
Level 4: Agree.
Level 5: Completely agree.
3.3. QUESTIONNAIRE DESIGN
After completing the scale, the author designed a questionnaire to conduct a survey and collect data for the study. The official questionnaire used to collect information is divided into 2 main parts:
Personal information, including: gender, age, professional qualifications, income, working time, working department... This information is used to classify and group different employees, thereby researching the factors that the research needs.
Information to be collected through survey form. Information collected based on the scale built in the above section. This is the main content of the survey questionnaire. Factors include: Job characteristics; Training and promotion; Income; Superiors; Colleagues; Brand; Benefits; Emotional attachment; Maintenance attachment; Ethical attachment
To measure the above 10 factors, 48 questions in the scale section were included in the survey questionnaire. In this study, a 5-point Likert scale was used to measure the above observed variables, from Level 1: Completely disagree to Level 5: Completely agree . (Please see details of the Questionnaire in Appendix 2)
3.4. QUANTITATIVE RESEARCH
3.4.1. Sampling method
In this study, due to limitations in time, cost and knowledge of the author, the sampling method chosen was convenience sampling, data was collected through direct interviews and group mailings to branches in the region.
3.4.2. Sample size
For exploratory factor analysis (EFA), the minimum sample size is N ≥ 5*x (x: total number of observed variables) (Hair & ctg, 2010). In this study, the total number of observed variables is 48, so the minimum number of samples needed is 240.
3.4.3. Data processing and analysis
Survey data after being collected from the survey questionnaire will be coded and analyzed. The software used by the author to perform data analysis is SPSS version 16.0.
3.4.3.1. Sample information description
The author will use descriptive analysis to statistically analyze the attributes of the research sample such as: gender, age, professional qualifications, income, working time, and working department of the surveyed group.
The data for this descriptive analysis step were collected from the personal information section of the interviewees in the questionnaire presented above.
3.4.3.2. Scale verification and evaluation
To evaluate the scale, we need to check the reliability and validity of the scale. Coefficients such as Cronbach's Alpha reliability and Item-total correlation coefficient will help us eliminate observed variables that do not contribute to describing the concept to be measured. The Cronbach's Alpha if Item Deleted coefficient helps
evaluation in eliminating observed variables to improve the Cronbach's Alpha reliability coefficient for the concept to be measured. Exploratory factor analysis (EFA) method to test the value of the scale of research concepts.
a. Cronbach's Alpha analysis
Cronbach's Alpha analysis aims to test the reliability of the scale through the Cronbach's Alpha coefficient and eliminate variables with small Item-Total correlation.
Cronbach's Alpha coefficient has a value that varies in the range [0,1]. A scale has good reliability when the Cronbach's Alpha coefficient varies in the range [0.7,0.8] (Nguyen Dinh Tho, 2011).
If the Cronbach's Alpha coefficient is greater than or equal to 0.6, the scale is acceptable in terms of reliability (Nunally & Bernstein, 1994, quoted in Nguyen Dinh Tho, 2011).
In theory, the higher the Cronbach's Alpha coefficient, the better (the more reliable the scale). However, this is not really the case. A Cronbach's Alpha coefficient that is too large (α > 0.95) shows that there are many variables in the scale that are not different from each other (meaning they measure the same content of the research concept). This phenomenon is called redundancy (Nguyen Dinh Tho, 2011).
Therefore, when testing each measurement variable, we use the item-total correlation coefficient. According to Nguyen Dinh Tho (2011) quoted from Nunnally & Bernstein (1994), if a measurement variable has a corrected item-total correlation coefficient greater than or equal to 0.3, then that variable meets the requirements.
Thus, in Cronbach's Alpha analysis, we will eliminate scales with small coefficients (α<0.6) and also eliminate observed variables with small adjusted variable-total correlation coefficients (<0.3) from the model because these observed variables are not suitable or have no meaning for the scale.
b. Exploratory Factor Analysis (EFA)
After eliminating variables that do not ensure reliability through Cronbach's Alpha analysis, exploratory factor analysis (EFA) is used to determine convergent validity, discriminant validity, and simultaneously reduce estimated parameters according to each group of variables.
In research practice, for a scale to achieve convergent validity, the simple correlation coefficient between variables and factors (factor loading) must be greater than or equal to 0.5 in a factor (0.4 ≤ factor loading < 0.5 is considered important; factor loading > 5 is considered to have practical significance). To achieve discriminant validity, the difference between factors must be greater than or equal to 0.3 (λiA – λiB ≥ 0.3). However, we need to consider its content value before deciding whether or not to eliminate a measurement variable (Nguyen Dinh Tho, 2011).
The number of factors is determined based on the Eigenvalue index - representing the variation explained by each factor. The number of factors is determined at the factor (stopping at the factor) with a minimum Eigenvalue of 1 (≥1) and factors with Eigenvalue less than 1 will be eliminated from the model (Nguyen Dinh Tho, 2011). Variance explained criteria: the total variance extracted must be 50% or more, meaning that the common part must be larger than the specific part and error (60% or more is considered good) (Nguyen Dinh Tho, 2011).
To determine the suitability when using EFA, people often conduct Bartlett and KMO tests:
o Bartlett's test: used to examine whether the correlation matrix is an identity matrix (I) or not. Bartlett's test is statistically significant when Sig < 0.05. This proves that the observed variables are correlated with each other in the population.
o KMO test: KMO is an index used to compare the magnitude of the correlation coefficient between measured variables with the magnitude of their partial correlation coefficients (Norusis, 1994, quoted in Nguyen Dinh Tho, 2011). The larger the KMO coefficient, the better because the common part between the variables is larger (Nguyen Dinh Tho, 2011). The KMO coefficient must be
A value of 0.5 or higher (KMO ≥ 0.5) shows that the analysis is appropriate. The KMO coefficient <
0.5 is unacceptable (Kaiser, 1974, quoted in Nguyen Dinh Tho, 2011).
However, according to Nguyen Dinh Tho (2011, page 397), in reality, with the support of SPSS statistical processing software and we can look at the results of factor weights and variance extraction that meet the requirements, the Bartlett and KMO tests are no longer meaningful because they always meet the requirements.
In this study, the author will use the Principal components factor extraction method with Varimax rotation and stopping point when extracting factors with Eigenvalues greater than or equal to 1 to analyze exploratory factors for 07 independent variables as well as 03 dependent variables.
3.4.3.3 Regression analysis and hypothesis testing
After completing the analysis of scale reliability assessment and EFA exploratory factor analysis, observed variables that do not ensure convergent validity continue to be eliminated from the model until the parameters are grouped into groups of variables that meet the requirements.
Regression analysis will then be used to analyze the research model of the topic.
However, before conducting regression analysis, an important analysis that needs to be performed first is correlation analysis to test the linear correlation between variables in the model.
a. Correlation analysis
This analysis aims to test the linear correlation between variables in the model: between the dependent variable and the independent variables and between the independent variables with each other. Using the Pearson correlation coefficient to quantify the degree of linear relationship between two quantitative variables. The absolute value of the Pearson coefficient is closer to the positive correlation.