specializing in bank credit and economic restructuring to give opinions on observed variables in 6 factors: "Criteria for evaluating the bank's expanded operational capacity for CD CCKT", "Criteria for evaluating the capacity of bank loan customers for CD CCKT", "Criteria for evaluating the bank's expanded state policy for CD CCKT", "Criteria for evaluating the bank's borrowing process for CD CCKT", "Bank's credit information for CD CCKT" and "Criteria for evaluating the bank's lending method for CD CCKT" impact of bank credit on economic restructuring. List of experts ( Appendix 1 ). Including the following 2 steps:
Step 1: Develop a rough questionnaire ( Appendix 2 ) based on the information to be collected in theory, evaluation criteria and collected data along with relevant studies on the impact of bank credit.
Step 2: Select and edit based on expert feedback.
The discussion and interview group of 10 experts aimed to assess the clarity of the questionnaire, thereby recording their initial opinions and wishes regarding the impact of bank credit on economic restructuring.
The questionnaire is designed with two main parts: Part 1: Personal information of the interviewee; Part 2: Measuring 6 factors affecting the expansion of bank credit for CD CCKT TP. HCM according to the survey questions [2], [9].
3.4.2.2. Results of preliminary qualitative research and scale adjustment
After consulting with experts, the questionnaire to survey factors affecting the expansion of credit institutions with CD CCKT TP. HCM was adjusted and coded as follows:
Each group of factors is a component measuring the impact on the expansion of TDNH with CD CCKT TP. HCM, represented by independent variables. Dependent variables.
Table 3.17: Scale of factors affecting TDNH with CD CCKT TP. HCM
STT
Questions of observed variables | Symbol | |
1. Criteria for assessing the operational capacity of credit institutions | NLTD | |
1 | Executive management | NLTD1 |
2 | Capital | NLTD2 |
3 | TD Products | NLTD3 |
4 | Technology level | NLTD4 |
2. Criteria for evaluating loan customer capacity | NLKH | |
5 | Equity | NLKH1 |
6 | Executive Manager | NLKH2 |
7 | Business production scale | NLKH3 |
8 | Collateral | NLKH4 |
3. Criteria for evaluating State policies | CSNH | |
9 | DCCCKT transfer policy | CSNN1 |
10 | Preferential credit policy | CSNN2 |
11 | Preferential credit policy | CSNN3 |
12 | State preferential policies | CSNN4 |
4. Criteria for evaluating credit loan process | QTCV | |
14 | Procedure file | QTCV1 |
15 | Loan term | QTCV2 |
16 | Loan approval time | QTCV3 |
16 | Transaction time | QTCV4 |
5. Credit information assessment criteria | TTTD | |
17 | Ineffective communication channels | TTTD1 |
18 | Misuse of credit capital | TTTD2 |
19 | False information | TTTD3 |
20 | Not fully understood SPTD | TTTD4 |
6. Criteria for evaluating lending methods | PTCV | |
21 | Direct lending | PTCV1 |
22 | Group lending | PTCV2 |
23 | Guaranteed Loan | PHTC3 |
7. Credit expansion with CCKT shift (Dependent variable) TDCCKT | ||
24 | The system of credit institutions is qualified to provide capital for the transition. CCKT | TDCCKT1 |
25 | The operations of credit institutions are developing safely and strongly. | TDCCKT2 |
26 | The activities of credit institutions focus on ensuring capital for transformation. economic structure | TDCCKT3 |
Maybe you are interested!
-
Factors affecting job satisfaction of bank credit officers in Ho Chi Minh City - 13 -
Building a Scale and Research Model of Factors Affecting Customers' Decision to Choose a Bank to Deposit Savings at -
Factors affecting customers' bank switching behavior in Hanoi city - 14 -
Factors affecting job satisfaction of employees of Joint Stock Commercial Bank for Foreign Trade of Vietnam in Ho Chi Minh City - 17 -
Factors affecting the decision to choose an international payment bank of enterprises in Ho Chi Minh City - 16
27
Believe that the operations of the credit institution will develop better in the future. hybrid | TDCCKT4 |
Source: author synthesis
The table above shows that the scale of factors affecting the expansion of credit institutions with CD CCKT TP. HCM, includes 6 groups of independent factors, with 23 observed variables.
3.4.2.3. Scale of impact on TDNH
During group discussions with experts, the scale of bank credit level with CCKT transition was also modified to suit the actual situation of Ho Chi Minh City.
The scale of measuring the impact of bank credit on the transition of economic structure and dependent variable with 4 observed variables and coded as in the following table:
Table 3.18: Bank credit rating scale with coded CCKT transition
STT
Questions of observed variables | Symbol | |
Credit expansion with economic transformation (Dependent variable) TDCCKT | ||
1 | The expanded system of credit institutions is qualified to provide capital for transfer. CCKT translation | TDCCKT1 |
2 | The operations of credit institutions are developing safely and strongly. | TDCCKT2 |
3 | The activities of credit institutions focus on ensuring capital for structural transformation. economic structure | TDCCKT3 |
4 | Believe that the operations of the credit institution will develop better in the future | TDCCKT4 |
Source: author synthesis
3.4.3. Quantitative research
3.4.3.1. Description of research sample
According to Cooper and Schindler (1998), the important reason for using the method is the cost and time savings. In this respect, the non-probability sampling method is superior to the probability sampling method. Professor Dr. Nguyen Thi Canh (2007) said that non-probability sampling is easy to design and implement but it can give misleading results regardless of the researcher's judgment, due to randomness, they may not represent the whole population [9].
From the advantages and disadvantages of this non-probability sampling method, to achieve the research objectives as well as the effectiveness in terms of cost, time, ... The thesis has
Conducting the selection of non-probability sampling method, the convenience is experts and customers who are working and transacting at Ho Chi Minh City Commercial Bank to conduct research on this topic. The reason for choosing this sampling method is because respondents are easy to approach, they are willing to answer the research questionnaire as well as less costly in terms of time and cost to collect the information needed for research and suitable for the author's conditions.
Sample size:
Sample size often depends on the estimation methods used in the study and there are many different opinions.
The sample size depends on the estimation method used in the study, the number of parameters and the normal distribution of the responses. The more complex the research problem, the larger the research sample, another general principle is that the larger the sample, the higher the accuracy of the research results. However, in practice, the choice of sample size also depends on a very important factor as mentioned above, which is the financial capacity and time that the researcher can have, determining how much sample size is appropriate is still controversial and has many different views. Maccallum and co-authors (1999) summarized the views of previous researchers on the absolute minimum sample size required for factor analysis {1}. In which, Gorsuch (1983) and Khlin (1979) suggested that the number is 100 while (Guilford in 1954) suggested that the number is 200 {3}. Comrey and Lee (1992) did not give a fixed number but gave different numbers with corresponding comments: 100 is bad {2}, 200 is fair, 300 is good, 500 is very good, 1000 or more is excellent {4}. Some other researchers did not give a specific number for the required sample size but gave a ratio between the required sample size and the number of parameters to be estimated. According to Hoang Trong & Chu Nguyen Mong Ngoc (2005), for factor analysis, the sample size will depend on the number of variables included in the factor analysis and should be 4 or 5 times the number of observed variables.
Synthesizing the above viewpoints, to simplify sample allocation and ensure minimum sample size conditions, as well as time and cost issues, the sample size of the Thesis is 360 respondents.
The sample in the official study was selected by the convenience sampling method. The questionnaire was sent to those who are working in managing banks, and transacting with management partners of credit institutions in the field of credit activities with CD CCKT and to those who manage small and medium enterprises in need of bank credit capital and are transacting at the bank.
3.4.3.2. Design of survey questionnaire
Design the Questionnaire to:
- Find out the expectations of TCTD expansion for CD CCKT TP. HCM;
- Measure the impact level of factors on the expansion of credit institutions with CD CCKT;
- Testing factors affecting the expansion of credit institutions with CD CCKT;
The questionnaire is considered as a tool used to collect data; including a set of 23 questions on the scale measuring factors affecting the expansion of TDNH with CD CCKT TP. HCM and 4 scales determining the level of TDNH expansion with CD CCKT TP. HCM.
The questions and answers are arranged in a certain logical order.
- Introduction: Has the effect of creating sympathy to create the cooperation of the respondent at the beginning of the interview.
- Qualitative questions: Have the effect of clearly identifying the interviewee;
- Warm-up question: Has the effect of reminding to focus on the topic that the Questionnaire is aiming at;
- Specific questions: Help clarify the content to be researched;
- Sub-questions: Used to collect additional information about the characteristics of the research sample (gender, age, occupation, etc.)
- Design of Questionnaire presentation: The questionnaire is designed with the above structure and is sent conveniently for asking, storing and statistics.
- Pilot survey to test the Questionnaire: After designing the Questionnaire, it is sent to a number of respondents in advance, to conduct a preliminary survey and ask for their opinions again and also to make final adjustments to the Questionnaire before fully implementing it.
The formal quantitative research questionnaire was formed (Appendix 2.)
3.4.3.3. Data processing and analysis methods
Primary data collection was conducted by approaching experts working and customers managing small and medium enterprises transacting with credit institutions and interviewing them on issues related to factors affecting the expansion of credit institutions with CD CCKT TP. HCM and through a pre-prepared questionnaire. Next, data was taken directly from reports, statistics at credit institutions, the State Bank of Ho Chi Minh City and other information channels.
The collected survey questionnaires will be reviewed for validity.
Valid responses will be coded, entered and cleaned on SPSS 20.0 software. Through SPSS 20.0 software, data analysis is performed through descriptive statistics, assessing the reliability of the scale.
3.4.3.4. Descriptive analysis
Create a frequency table to list the characteristics of the collected sample according to gender, age, seniority, income, and education.
After collection, the interview questionnaires were reviewed and those that did not meet the requirements were eliminated. Next, the study coded, entered and cleaned the data. Then, the study used many data analysis tools such as descriptive statistics, exploratory factor analysis (EFA), scale reliability testing (Cronbach's Alpha), Pearson correlation, multiple linear regression analysis, residual scatter plot, Q-Q plot, etc. with SPSS 19.0 software to test the model and research hypotheses.
3.4.3.5. Cronbach Alpha reliability assessment of the scale
Use Cronbach's Alpha coefficient to check the reliability of estimated parameters in the data set according to each group of factors in the model.
- Scale evaluation : test the reliability of the scales through Cronbach Alpha reliability coefficient testing and exploratory factor analysis (EFA).
- Cronbach Alpha coefficient is a statistical test of the degree of consistency with which the items in a scale correlate with each other. With this method, the analyst
can eliminate inappropriate variables and limit junk variables in the research process. Variables with item-total correlation coefficients less than 0.3 will be eliminated and the scale selection criteria when it has Cronbach Alpha reliability of 0.6 or higher (Nunnally & Burnstein 1994).
According to Hoang Trong and Chu Nguyen Mong Ngoc (2008): "Many researchers agree that when Cronbach Alpha is from 0.8 or higher to nearly 1, the measurement scale is good, from nearly 0.7 to nearly 0.8 is usable. Some researchers also suggest that Cronbach Alpha from 0.6 or higher can be used in cases where the concept being measured is new or new to the respondents in the research context". In this study, the author applied Cronbach Alpha from 0.6 or higher to be usable [12], [9].
- Exploratory factor analysis (EFA) is a technique used mainly to reduce and summarize data after assessing the reliability of the scale using Cronbach Alpha coefficient and eliminating variables that do not ensure reliability. This method is useful in determining sets of variables for the research problem as well as used to find relationships between variables.
When analyzing exploratory factors, researchers are often interested in the following criteria:
+ KMO coefficient (Kaiser-Meyer-Olkin) ≥ 0.5 with Barlett significance level ≤ 0.05. KMO is an indicator used to consider the appropriateness of EFA, 0.5 ≤ KMO ≤1 then factor analysis is appropriate. Kaiser (1974) suggested that KMO ≥ 0.90 is very good;
KMO ≥ 0.80: good; KMO ≥ 0.70: acceptable; KMO ≥ 0.60: acceptable; KMO≥ 0.50: bad; KMO < 0.50: unacceptable (Nguyen Dinh Tho, 2011).
+ Factor loading ≥ 0.5. According to Hair & colleagues (2006), factor loading is an indicator to ensure the practical significance of EFA.
Factor loading > 0.3 is considered to have achieved the minimum level; > 0.4 is considered important; ≥ 0.5 is considered to have practical significance. Hair & colleagues (2006) also advise that: if choosing the factor loading standard > 0.3, the sample size must be at least 350, if the sample size is about
If the sample size is 100, the factor loading standard should be > 0.55. If the sample size is about 50, the factor loading must be > 0.75.
+ The scale is accepted when the total extracted variance ≥ 50% and the eigenvalue coefficient
> 1 (Gerbing & Anderson 1988).
+ The difference in factor loading coefficients of an observed variable between factors is ≥ 0.3 to ensure discriminant value between factors (Jabnoun & Al_Tamimi, 2003).
When analyzing EFA, the author uses the Principal Component Analysis extraction method with Varimax rotation to find factors representing variables and stopping points when extracting factors with eigenvalue greater than 1. Varimax allows rotating the entire angle of factors to minimize the number of variables with large coefficients on the same factor, thus enhancing the ability to explain the factors.
3.4.3.7. Multiple linear regression analysis
- Regression analysis: used to find the correlation between independent variables (influencing factors) and dependent variables (factors affecting TDNH with CD CCKT TP. HCM).
Regression analysis to examine the research model. With the model mentioned in chapter 2, multivariate regression analysis method was performed and examined the impact level of factors on TDNH with CD CCKT TP. HCM.
- T-test and ANOVA analysis : to test whether the factors have different impacts or not on the influence of TDNH with CD CCKT TP. HCM13D], [6D].
3.4.4. Survey results
3.4.4.1. Descriptive statistics
The research sample is lecturers, bank leaders, researchers and employees in the field of banking and finance and customers managing small and medium enterprises transacting with credit institutions in Ho Chi Minh City. There are 400 questionnaires sent to the survey subjects according to the research sample. The results received 378 responses; then the responses were checked, and valid responses were determined as follows: