INTRODUCTION:

In VietNam, credit cards are not welcome, when there are still a few quite hesitant with this product, because of concerns about the risk of information theft and credit risk. Like a double-edged sword, a credit card can be a backup financial fund and can also be a debtor that never runs out.

However, the benefits it brings cannot be denied. In recent years, credit cards have gradually become more popular. The bank acts as a pioneer when focusing on upgrading card quality and number of users by approaching from customer's consumption behavior. Realizing its importance has prospects in generating high profits and is the main product of the Bank.

In order to find a sustainable and long-term development direction, to bring credit cards closer to each Vietnamese, this article focuses on deeper research on outstanding features of Credit Cards, especially is to study the factors affecting the intention to use credit cards of customers at Sacombank.

LITERATURE REVIEW:

Consumer Behavior:

Consumer behavior can be defined as the behavior that consumers exhibit when seeking to purchase, use, evaluate, and discard products and services that they expect will meet their needs (Schiffman and Kanuk, 2004)¹. Consumer behavior includes all activities of buyers, former buyers and potential buyers from pre-purchase consideration to post-purchase evaluation and from continued consumption to discontinuation. It extends from the perception of a desire, through the search and evaluation of possible means to satisfy that need and the act of purchase, to the evaluation of the purchased item in use, its effect on directly affect repurchase probability (Alba et al., 1991)².

Purchasing decision:

Customer Relationships and Customer Relationship Management have been at the forefront of business lately and have become prominent in the management profession (Lalitha et al. 2010)^3.Visual merchandising, if implemented in the best possible way by the store, can give the store an edge over existing competitors in the market, while motivating and engaging customers. visit that store to enter and also stimulate their shopping behavior in the store and sometimes lead to customers' even impulsive buying behavior (Pratibha et al. 2016)^4.

Kumar (2015)^5.revealed that there was a significant rise in the use of Nutraceuticals due to the impact caused on health as a result of the newer lifestyle adapted.

Bullappa et al. (2018)⁶shows that the change in five variables that are disposable income, lifestyle, new technology and features, functional conditions and physical damage have significant influence on switching behavior of smartphone user except one variable that is promotions & discounts that has no significant influence on the switching behavior of smartphones users.

Keshav et al. (2022)⁷promoted to help and understand the linkages between irrigation development and poverty reduction, with a view to propose recommendations on how to increase the impact of irrigation development projects on poverty alleviation. Through a review of irrigation project, it aims to provide a framework for analyzing the impacts of irrigation on poverty and to review some effect of these impacts. It is hoped that its findings and recommendations can help to structure future investment strategies in the field rural irrigation and all of irrigation projects.

Ridwana et al. (2022)⁸identified the reason of the consumer behaviour, while purchasing the smart phone.Thevarious factor, the customer see or search in any particular smart phone before purchasingit. Total 21 factors or features of smart phone was identified the customer prefer, whilehe/she purchases the smart phone. The most important and least important factor have beenfigure out in the study.

Suresh et al. (2018)⁹tried to find out the impact of promotional tools on the consumer purchase intention while purchasing packaged food products. The study has been conducted through multivariate analysis. The study is expected to contribute to the marketing policy makers of packaged food product companies while developing promotional studies.

Ashish et al. (2011)¹⁰revealed three factors responsible for switching intention namely intention to switch in future, reasons formulating intention to switch, intention to switch due to offer and improper response.

Every consumer is emotionally attached to their culture and attributes of the culture plays a significant role in developing the motives of the consumer; which is reflected in their buying behaviour. The novelty of doing this research is to develop a robust model; which could predict and justify the buying intention and buying behaviour for culturally rich, tribal handicrafts product. The idea has been proposed after the gap analysis. To the end of this academic endeavour, a conceptual model has been proposed and the validity of the proposed model may be subject to empirical study (Ashok et al., 2016)¹¹

Debasis et al. (2017)¹²reviewed 30 research papers and our findings show that service quality, customer loyalty, customer satisfaction and brand image are the major factors that affect the customer online repurchase behaviour. The paper also discusses the limitations, suggestions for future research and conclusion drawn based on the methodology and themes.

Nitin et al. (2018)¹³state that various factors influence investor’s behaviour. Investment decisions depend on motivational factors and efforts that the investor is making to exercise. The reason for the investor to invest is known as investment intention. Investment intentions are related to personal investment and portfolio management. Investment intentions are generally divided as short term and long term investment intentions.

Sashikala et al. (2018)¹⁴perceived usefulness is not significant in influencing repurchase intention. Research results can help online retailers to make strategies to target technology-savvy online consumers, especially in small cities.

RESEARCH MODEL AND HYPOTHESES:

Based on the researches of a conceptual model was developed which consisted ofthe factors affecting customers' intention to use credit card at Sacombank, the hypotheses are proposed:

Hypothesis H1: Perceptions of behavioral controlhave a positive impact on customers' intention to use credit card at Sacombank.

Hypothesis H2: Convenience in behavior have a positive impact on customers' intention to use credit card at Sacombank.

Hypothesis H3: Cost to using have a positive impact on customers' intention to use credit card at Sacombank.

Hypothesis H4: Attitude towards usage have a positive impact on customers' intention to use credit card at Sacombank.

Figure 1: The study’s Proposed Theoretical Framework

RESEARCH METHODOLOGY:

The research was carried out through 2 phases: Preliminary research and formal research. The preliminary research was carried out by group discussion with 20 customers of Sacombank.Based on combining with observed variables in previous studies on customers' intention to use credit card that the author has synthesized, proceed to build a draft scale,based on a draft scale, the author conducts a discussion with a group of staff to discover additional new variables and remove the ones that do not agree, and unify the composition of the preliminary scale. In the quantitative research phase, the survey questionnaire method is used with a valid number of observations of 200. The quantitative analysis methods that will be used for the data analysis part include:

Testing the reliability of the scale by Cronbach's Alpha: This test reflects the degree of correlation between the observed variables in the same factor. The standard to test the reliability of the scale is that the measurement variables have the total correlation coefficient of Corrected Item - Total Correlation ≥ 0.3, then the variable meets the requirements.

Exploratory Factor Analysis (EFA): This method helps to evaluate two important types of values of the scale: convergent value and discriminant value. The condition for exploratory factor analysis is to satisfy the following requirements: Factor loading > 0,5; KMO (Kaiser-Meyer-Olkin) in the range 0,5 ≤ KMO ≤ 1, Bartlett test has statistical significance (Sig. < 0,05).

Confirmatory factor analysis (CFA): is one of the techniques that allow testing how well the measured variables represent the factors. The CFA method is used to confirm the univariate, multivariate, convergent, and discriminant validity of the factor scale.

Multiple Regression Analysis: Multiple regression analysis is a statistical technique that used to analyze the relationship between the dependent variable and multiple independent variables, in which more than one independent variable is assumed to affect the dependent variable. In this multiple regression analysis, multiple independent variables of the study will be entered into the same types of regressions equation. A separate regression of each variable will calculated to define the relationship with the dependent variable. The relationship that occurs between each dependent variable and independent variable is linear. All the variables of the questionnaire are measured by likert scales. Multiple regressions will be calculated using the proposed formula to study the relationship between the independent variables and dependent variables.

RESULTS:

Testing The Reliability of Scale by Cronbach's Alpha:

After testing Cronbach's Alpha for 6 independent variables, 1 intermediate variable, and 1 dependent variable in the research model (Table 1), all factors have Cronbach's Alpha coefficients that meet the requirements (>0.5) and no observed variables were excluded. The results of testing the reliability of the scale are summarized in Table 1. After testing the reliability coefficient of Cronbach's Alpha, all observed variables meet the requirements for EFA analysis.

Table 1: Cronbach's Alpha test results

Concept	Factor	Number of observed variables	Reliability
	Perceptions of behavioral control	3	0.954
	Convenience in behavior	5	0.935
	Cost to using	4	0.958
	Attitude towards usage	6	0.965

Source: Processing results from survey data, 2022

Exploratory factor analysis (EFA):

The results of EFA analysis are shown in Table 2 with the KMO coefficient = 0.902; the Bartlett test value is significant (Sig < 0.05), all observed variables have factor loading coefficients greater than 0.5 so no variables are excluded.

Table 2: EFA results of the scale

Items	Factors
Items	1	2	3	4	5
PB3	0.864
PB4	0.830
PB1	0.809
PB5	0.758
PB2	0.744
CB3		0.876
CB4		0.870
CB2		0.843
CB1		0.818
CU3			0.845
CU2			0.839
CU4			0.794
CU1			0.794
AT2				0.855
AT3				0.841
AT1				0.832
CY2					0.824
CY1					0.805
CT3					0.797

Source: Processing results from survey data, 2022

Testing the correlation coefficient (R value):

The Multiple Regression Analysis is used to determine the significant relationships between independent variables and dependent variable.

Table 3: Model Summary

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Durbin- Watson
1	0,720	0.518	0,508	0,79347	1,677

Source: Processing results from survey data, 2022

Based on the Model Summary Table 3, the correlation coefficient (R value) for this research is 0,719. This means that the dependent variable strong positively affects independent variable because R value is positive value and 0,719 is fall under coefficient range _±0,71 to ±1.

Testing the Anova:

Table 4: Anova

Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	131,939	4	32,985	52,390	0,000^b
	Residual	122,772	195	0,630
	Total	254,711	199

Source: Processing results from survey data, 2022

In the Anova table 4, it shows that the F value of 52,390 greater than 5 and the p-value is 0.00 which is less than 0.05 (p< 0.05) so significant at the 0.05 level. The significance value was-is less than 0.05, an indication that the model was-is significant. In overall the regression model with those five independent variables is suitable for explaining the variation in Itention to use credit card.

Develop regression equation with standardized coefficients:

The standardized coefficients predict the influence level of independent variables on Itention to use credit card. We can be determined by the following regression equation with standardized coefficients as below:

Y = 0,335*X1 + 0,217*X2 + 0,192*X3 + 0,176X4

Or:

Customers' intention to use credit card = 0,335*Perceptions of behavioral control + 0,217*Convenience in behavior + 0,192*Cost to using + 0,176Attitude towards usage.

DISCUSSION:

The purpose of this study is to measure the factors affecting the intention to use credit cards of customers at Sacombank - Song Han branch. On the basis of the theory of customer's intention to use and the practical basis of previous studies, the author has established a research model and adopted qualitative and quantitative research methods to make result. The research results show that 4 factors affect customers' intention to use credit cards at Sacombank - Song Han branch, including: Perceptions of behavioral control, Convenience in behavior, Cost to using, Attitude towards usage

Perception of card usage control behavior is a very important factor. It is inevitable that customers lose control in the process of using credit cards. Banks need to pay attention in conveying information to customers in the most specific and accurate way before signing the card opening documents. It is necessary to have a customer care department to take care of and assist in notifying customers when payment is due, avoiding debt group jumps, affecting customers' credit reputation.

The usefulness and convenience of using credit cards in payment are many, besides safety, customers can easily manage spending and receive many incentives from credit cards. bring. Banks can link more closely with e-commerce trading floors to ensure maximum safety in the process of customers performing transactions, better ensure the interests of customers.

The cost of using the card is an issue that almost every customer is concerned about. Banks need to have plans as well as plans to optimize the cost of using cards to suit each time, each customer segment so that when customers use credit card services, they do not have to worry about the cost of service benefits will bring more value than that..

Attitude towards card usage is the most important factor affecting customers' intention to use credit cards. Therefore, the bank should invest in the promotion of credit card products, as well as in approaching and advising customers. So that customers can understand the advantages of credit cards and the benefits when customers use it.

REFERENCES:

1. Schiffman, Leon. G. and Kanuk. Consumer Behavior, Leslie Lazar Pearson Education Pvt Ltd., New York. 2004

2. Alba, J. W., Hutchinson, J. W. and Lynch, J. G. Memory and decision making and Robertson, T. S. and Kassarjian, H. H. (eds) Handbook of Consumer Behavior. Englewood Cliffs, NJ: Prentice-Hall. 1991. 1–49.

3. Lindquist, J. D. Meaning of image: Survey of empirical and hypothetical evidence. Journal of Retailing. 1974; 50(4).

4. Sunil Kumar Pradhan, Suman Kalyan Chaudhury. Attitude of Customers towards the Mobile Service Providers: A Study on Kolkata City. Asian J. Management. 2012; 3(2): 80-85.

5. N. Srinivas Kumar. An empirical study on the influence of independent marketing variables on the purchasing decision of selected personal care products. Asian J. Management. 2015; 6(2): 128-134.

6. Haralu Bullappa, Katera Shivkuma. The Impact of Irrigation on Poverty with Special Reference to-Asian Countries. Asian Journal of Management. 2018; 9(3):1109-1116.

7. Keshav Shivhare, Tarun Kumar, Rohit Rajwanshi. A Study on Switching behavior of Smartphone users in India. Asian Journal of Management. 2022;13(2):139-4.

8. Ridwana Hasan, Priya Verma. A Study of Factors Influencing Consumer’s Behaviour Towards Purchasing a Smart Phone in Raipur City. Int. J. Ad. Social Sciences. 2020; 8(3):87-95.

9. A. S. Suresh, Bhavna Pawar. A Study of Factors of Lifestyle and its impact on Nutraceutical Consumption: India Perspective. Asian Journal of Management. 2018; 9(1): 203-211.

10. Ashish Kumar Srivastava, Saket Ranjan Praveer, Charu Yadav . Decision Variables of Purchase Intention: A Multivariate Analysis of Promotional Tools. Asian J. Management. 2011; 2(2): 51-56.

11. Ashok Kumar Jha, G. K. Deshmukh, Sanskrity Joseph. Customers Intention to Switch towards Mobile Number Portability in Chhattisgarh – A Study. Asian J. Management. 2016; 7(3): 213-218.

12. Debasis Pani, Sunil Kumar Pradhan. Integrating effect of Consumer Perception on buying Intention: A Conceptual Model of buying behaviour for Tribal Handicrafts Products. Asian J. Management; 2017; 8(4):1149-1158.

13. Nitin Rohilla, Ruchi Dwivedi, Richa Tewari, Smita Mehendale. Online Repurchase Intention: A Methodological and Thematic Review. Asian Journal of Management. 2018; 9(1):841-846.

14. Sashikala V., P. Chitramani. The Impact of Behavioural Factors on Investment Intention of Equity Investors. Asian Journal of Management. 2018; 9(1):183-188.

Received on 20.07.2023 Modified on 07.09.2023

Asian Journal of Management. 2024;15(1):29-33.

DOI: 10.52711/2321-5763.2024.00005