ISSN: 0974-438X
Imapct factor(SJIF): 5.889

Home | About Us| Invitation For Manuscript| Review Process| Indexing| Subscription | Disclaimer

 

 

PBRI is now indexed in ESCI by THOMSON REUTERS. Pacific Business Review International is included in the UGC List of Recommended Journals (D.O. No. F. 1-1/2016 (PS) Amendment dated 10th January 2017) (S.No. 36785).

 
Editorial Board A Refereed Monthly International Journal of Management
Prof. B. P. Sharma
(Editor in Chief)
Prof. Mahima Birla
(Group Editor)
Dr. Khushbu Agarwal
(Editor)
Ms. Asha Galundia
(Circulation Manager)

 Editorial Team

Dr. Devendra Shrimali
Dr. Dharmesh Motwani
Mr. Jinendra Vyas
 

Factors Influencing Consumer’s Perception Towards the Acceptance of Credit Cards

 

Arti Kundan*, Dr. Amisha Gupta**, Minakshi Kapoor***, Brinder Kumar****

* Research Scholar, The Business School, University of Jammu

House no. 615, Sector 3, Bhagwatinagar, Near Shiv Mandir, Jammu (J&k), India

artikundan@gmail.com,Ph: +91-9419984812

 

**Asst. Prof., The Business School, University of Jammu (J&k), India amishagupta2531@gmail.com, Ph: +91-9419110199

 

***Research Scholar, The Business School, University of Jammu

House no. 98, Sector 6, Trikutanagar, Jammu (J&K), India

mina364@gmail.com,Ph: +91-9419370281

 

**** Asst. Prof, Govt.Women College Udhampur (J&K), India

bkgorka14@gmail.com, Ph: +91-9419214554

 

 

 

 

 

 

 

 

 

 

Abstract

Purpose – Credit cards are a popular medium of payment for consumers today. A large number of past studies have been conducted in the area of credit cards in India and abroad that emphasis on various dimensions likes attitude, awareness and acceptance. However, very few studies have been conducted on the demographic and the socio-economic factors affecting the consumer’s perception towards the acceptance of credit cards, particularly in the state of Jammu and Kashmir. Therefore, the present study aims to explore a set of factors affecting the acceptance of Credit cards among customers in Jammu region.

Design/Methodology/Approach – The study on the empirical findings of a customer survey through the use of a structured questionnaire was administered on a sample of 250 respondents based on convenience sampling technique.

Findings – This study explored different dimensions such as bank policies, payment policies,  flexibility, perceived risk, and so on that affects the acceptance of credit cards usage particularly for the banking sector in Jammu region.

Practical Implications – This research paper provides an in-depth understanding on the factors affecting the usage of Credit cards which could be used by banking sectors of Jammu region where the credit card usage is widespread phenomenon.The study could also help the banking industry to understand their target customers, their preferences and the effect of their policies on credit card application and use.

Originality/Value – This study throws light on the credit card usage, particularly in Jammu region in context of banking industry. Therefore, it would work as a roadmap for banking executives, marketing managers and policy makers to craft appealing marketing strategies to better promote the utilization of Credit cards.

 

Keywords:  Credit cards; Acceptance; Usage; Banking; Demographics; Socio-Economic.

 

Introduction

In this present scenario, credit cards are a popular medium of payment for consumers and also serve as an indispensable credit and payment mechanism throughout the world. Carrying a lot of cash can be bulky, risky and sometimes, one may run short of it, just when it is needed most. A credit card is the smart solution to these problems and is safe and suitable alternative to cash. Greater status was enjoyed by those who possessed a number of credit cards. Most people associate a credit card with prestige and the customers  take  the  accountability  of  being  responsible  to  be  extended  credit. Lee and Kwon (2002) describe that credit cards are used as a financing mechanism instead of a medium of convenience. It allows us to obtain goods and services with the concept of buy now and pay later.

 

Credit card is a new concept in developing country like India and is treated as astatus symbol.Demographics also seem to play a vital role in making a choice and the use of credit cards as a convenience user or resolver. Age and income level have been studied previously and suggest some indication for correlation between demographic and use of credit card.Occupation and income are generally accepted as one of the most popularindicator that explained and significantly correlates with the usage of credit card In fact, income also acts as a factor in determining of how much the purchasing power of consumers will be spent on goods or services (Bowers, 1979). The credit card is extremely useful to those people who use it properly and have knowledge about such card. High credit limits, low interest rates and pre-approval, these have become familiar terms to many customers, who are increasingly bombarded with unsolicited credit card. However, this explosion has brought in a lot of obstacles among the card holders that directly impact the consumers towards the credit card acceptance(Anneke& Nederlandsche, 2010). Similarly, the acceptance of credit card has become an area of economic concern in J&K.

 

In J&K the use of credit cards is in its initial stages and is not so widespread and such its economic and social concern is not significant. The defaults are occurring at an individual level and so people in general are not aware and even those who are suffering from the credit card driven debt are themselves unaware of their real cause of problem. Very few researches have been done regards the credit card in J&K and it is limited up to kissan credit card. So, this study is being conducted in Jammu region and shall be analysis on the basis of demographic and socio-economic of users’ perception towards credit cards.

 

Literature Review

The term credit cardreferred to a card for spending a citizen's dividend from the government, rather than borrowing Bellamy (1887). It is observed that carrying a lot of cash can be bulky,risky and sometimes, one may run short of it, just when it is needed most. A credit card is the smart solution to these problems and is safe and suitable alternative to cash.

Credit cards have become a fact of life for most consumers and are a part of the consumer valuesrevealedby Deviranjitham (2014). The most popular form of plastic money is theCredit card. It provides purchasing power, ease of purchase, a credit facility for a few weeks, the convenience of payment along with protection of purchases and discounts & bonusesChakravorti, S. (2003). The acceptance and the attitude of the customer’s towards the use and acceptability of credit cards differ for psychographic reasons (Yang, James and Lester 2005).

Vora and Gidwani (1993) have come up with the conclusion that the credit card is extremely useful to those people who use it properly and have knowledge about plastic card. Different cards provide the different packages to attract the customers like telemarketing, discounts, insurance coverage and provide reward points, etc. According to researcher, if all tax paying citizens are taken into account the card holders market has a potential to grow to 7 million. But these manful efforts at upgrading services can only have a limited impact as long as the Indian customer remains credit shy. For this, they have to change their spending habits and keep their card active, so that a piece of plastic becomes a premium card in an effective way.

Natarajan and Manohar (1993) have tried to know, to what extent the credit cards are utilized by the cardholders and what factors influencing the utilization of credit cards. The research is confined to cards issued by a particular bank (Canada Bank). Ten components, i.e. numbers of purchases, shops, percentage of purchases, place, frequency, type of product, type of services, cash withdrawal facilities, add on facility, insurance schemes are identified and used for the measurement were collected by random sampling technique. Various statistical techniques like Chi square test has been conducted to know the level of utilization and Chi square test reveals that sex, age, educational qualification of card holders has no relationship with utilization of creditcard. While occupation, income, employment status of spouse, mode of getting card has a relationship with utilization of creditcard.

Almeida (1995) predicted that the credit cards show that businessofcredit cardwill boom in India and numbers are expected to grow at an even faster pace as issuing banks get aggressive. Studies show that more than 4000 business establishments in the country accept credit cards. The country now provides all the components for a healthy credit card industry: a rapidly expanding, increasingly acquisitive middle class, a growing urge for travel and entertainment sophisticated merchant establishment and greater transparency in the financial system.Acquiring banks for business from the merchant establishment has brought the commission down and if the issuing bank happens to be also the acquiring bank, it gets the entire merchant discount. Finally, no payment system can ever replace cash in India on a widespread basis.For this credit card issuers are meeting this challenge by offering to cardholder’s different benefits and incentives and by urging merchants to promotecredit at the point of sale.

Azhagaiah (2002) reveals the recent development, evaluate the present status and assesses the future of the consumer gratitude by credit card debt.Azhagaiahalso discusses the financial position of the banking sector in India and also the strategies used by the banks to meet competition in credit/debit cards.In creating bank’s credit and money supply the credit to individuals and households have a vital role to play.The researcher points out that the role of credit cards in the money market will be very bright in comingyears.There is no doubt, the banks, which concentrates more on credit cards will get more benefits by means of credit creation.

Chakravorti and Emmons (2003) focused that over the last 20 years credit card provide benefits to customers and merchants not provided by other payment instruments as evidenced by their explosive growth in the number and value of transactions. Recently, regulators and antitrust authorities around the world took credit card networks under inspection. The cost and benefit analysis has been done regarding the advantages and disadvantages of credit cards.Several theoretical models have been constructed to study the implications of several business practices of credit cardnetworkson interrelated bilateral transactions.Gupta and Lehmmann (2003) studied Legal and regulatory framework of credit cards asserts that the regulations of credit card business in India are diffused and need to be smooth.There is a need to explore that various legislative premises of the inferior and unclear Indian version for protection of interest of cardholders and healthy growth of the industry.Whereas in developing countries the law on credit card business in comprehensive and straightforward, its Indian version requires a structural change.

Bowers (1979) studied that low income users of credit cards tend to use the cards for the installment feature rather than for service features such as convenience, safety, or identification. It has been suggested that the installment feature of credit is needed by the low income consumer to permit purchases such as automobiles, furnishings, and other consumer durables. Demographics also seem to play a vital role in making a choice and the use of credit cards as a convenience user. Age, income level has been studied previously and suggest some

indication for correlation between demographic and use of credit card. According to the study conducted by Kinsey (1981) the probability of having credit cards and the number held was correlated highly with age and occupation. However these two characteristics were less important than the place of residence, use of checking and savings accounts, and attitude towards credit.

Kaynak (1995) conducted an empirical research in urban Turkey which indicates that there is a relationship between socio-economic and demographic characteristics of Turkish consumers and their credit card holding and usage behaviors. It was observed that the age of the family head and family life–cycle stage are the determinants of credit card usage. Generally, middle and upper age, having a large flexible income level are more likely to use credit cards. This may be termed a social class effect of credit card usage and acceptance. Urban dwellers, more educated with professional type of jobs, and high income earners are using credit card mostly. For this credit card issuers are meeting this challenge by offering to card holder’s different benefits and incentives and by urging merchants to promotescredit at the point of sale.

 

Gambir (1998) studied that the regular user of cards needs to be well-informed and also made aware about credit cards usage. Till recently as it did not go along very well with the spirit of people because they do not have much money to spend because of bad economic conditions. But with increasing economic and financial liberalization and growing prosperity of the urban middle class banks feels that it is desirable to enter into this line of business. Credit cards and money transfers with the latest technological changes would definitely reduce the burden on cash in our system. Therefore, RBI has to give an impetus to the popularity of plastic money, which is consistent with present policy of economic and monetary liberalization.

The study revealed by Bhat and Maurya (2013) that the use of kissan credit card for the uplifting of the poor and to meet their socio-economics conditions and service provided by the J&K bank in the form of artecian credit card (Nazi,2013). Khaki and Sangmi (2012) studied that kissan credit card taken up by banker initiatives in Jammu and Kashmir. The use of credit cards is in its initial stages and is not so widespread and such its economic and social concern are not significant (Hassan & Harris, 2009).

From the review of studies mentioned above, it can be found that most of the studies are related with determinant of usage pattern of credit cards, credit cards fraud and their prevention, economics of card usage, customer acceptance and usage patterns, attitude towards credit cards etc. However, very few studies have been done on thedemographic and the socio-economic factors affecting the use of credit cards,particularly in the state of Jammu and Kashmir. Also, studies pertaining to credit cards on banking customers are very few in numbers and hence, the present study on the demographic and socio-economic analysis of users’ perception towards credit cards has been undertaken in Jammu region.

Research Methodology

Data was collected by using questionnaire, which was distributed amongst the sample of 250 from Jammu in J&K state. The sample was chosen by purposive convenience sampling method of sampling which is one of the non- probability techniques. Out of total nos. of 250 distributed questionnaires, 200 filled questionnaires were collected.

Generation of Scale Items

Theitems of different dimensions of Socio-economic (Bank Policies, Willingness to pay and Payment Policies) and Perception (Flexibility, Related benefits and Perceived Risk) were generated from review of relevant literature. The original scale consisted of 36 items rated on 5-point Likert-type scale with anchors of 1 as strongly disagree and 5 as strongly agree. Out of 36 items 20 items pertaining to Socio-Economic were extracted from the study that include Teoh, Chong and Yong, (2013) and the remaining 16 items pertaining to Perception were generated from  Pudaruth, Juwaheer and Madoo (2013).

Data Analysis

Demographical Profile

Table 1: depicts the demographic profile of the respondents as shown below:

Table1: Demographic Profile

 

Respondent’s Gender

 

Gender

Frequency

Percentage

Male

153

76.5

Female

47

23.5

Total

200

 

 

Respondent’s Occupation

 

Class

Frequency

Percentage

Business

46

23

Service

121

60.5

Professional

31

15.5

Student

2

1

Total

200

 

 

 

Respondent’s Age

 

Age

Frequency

Percentage

18-30

79

39.5

31-45

111

55.5

46-60

10

5

60+

0

0

Total

200

 

 

Respondent’s Income Group

 

Income

Frequency

Percentage

Up to ₹ 20,000

38

19

₹20,001 to ₹ 40,000

65

32.5

₹ 40,001 to ₹ 60,000

41

20.5

₹60,001 to ₹ 80,000

20

10

₹80,001 to ₹1,00,000

15

7.5

More than ₹ 1,00,000

21

10.5

Total

200

 

 

 

Number of Credit Cards Hold

 

Credit Card Number

Frequency

Percentage

Single

134

67

Multiple

66

33

Total

200

 

 

Respondent’s Usage Frequency

 

Usage

Frequency

Percentage

Daily

18

9

Weekly

92

46

Fortnightly

53

26.5

Monthly

23

11.5

Less Frequently

13

6.5

Never

1

0.5

Total

200

 

Source: Primary Data

The table above reveals gender of respondents which shows that out of 200 respondents surveyed; about (76.5%) of the participants were male and rest of (23.5%) were female. The variable occupation revealed that more than half of the participants (60.5%) were service personal and the least (1%) were students. In the case of age, the highest number of respondents was between the age group of 31-45 (55.5%) and lowest respondents were from the age group of 46-60 (5%).In the case of income variable, the income group between 20,001-40,000 (32.5%) was the most prominent. It has been shown from the table that maximum numbers of participants (67%) were single credit card users. The last variable that was taken for the purpose of the study was usage frequency of credit card users which revealed that (46%) of respondents used credit cards weekly and only (0.5%) of the respondents never used it.

 Factor Analysis

The exploratory factor analysis resulted into six factors containing25 items as shown in (Table 2). The variables with factor loading less than 0.5 and Eigen value less than 1.0 were ignored for the subsequent analysis (Hair et al. 2007). The Socio-Economic construct consisted of 20 statements, which reduce to 12 statements under three factors namely Bank Policies (BP), Willingness to pay (WP) and Payment Policies. The high KMO value and x2 value in Bartlett’s test of spherecity (0.767 & 1575.22) revealed the sampling adequacy of data for exploratory factor analysis. The total variance explained by these factors was arrived at 70.97%. Similarly, another construct named as Perception contained 16 statements which were reduced to 13 statements under three factors such as Flexibility (F), Related Benefits (RB) and Perceived Risk (PR). The KMOvalue, x2 value in Bartlett’s test of spherecity and the total variance explained by these factors were arrived at (0.769, 1123.48 and 60.28%), thus, suggested for factor analysis.

Table 2: Factor Analysis Results

Constructs

Factors

Mean

SD

FL

Cronbach’s alpha

 

 

Socio-Economic

 

 

 

 

 

 

 

(F1) Bank Policies

 

 

 

.875

BP2: I spend using credit card to earn points and exchange for gifts.

3.07

1.167

.851

 

BP1: I apply for credit cards to get free gifts.

3.28

1.165

.816

 

BP3: I was attracted by the cash rebate system, thus I always spend using credit card.

3.20

1.275

.752

 

BP4: I do not need to provide previous bills of credit cards when I am applying for another credit card.

3.425

1.113

.630

 

(F2) Willingness to Pay

 

 

 

.871

Wp5: I will make sure, I do make payment of credit card bills every month.

4.190

.6603

.785

 

Wp2: I know exactly the remaining debt that I due from previous transaction.

4.095

.7804

.778

 

Wp4: It is easy to find statement which was not made by me.

4.205

.6894

.762

 

Wp3: I will check on my bills to confirm all the transactions made by me are correct.

4.095

.7339

.684

 

Wp1: I know exactly how much I spent through credit card every month.

4.075

.8383

.683

 

(F3) Payment Policies

 

 

 

.777

PP4: I will make sure I did make payment of credit card bills every month

4.005

.740

.834

 

PP5: I will make sure I reserve my money to pay for the credit card bills

4.005

.753

.721

 

PP3: I will call the bank if I did not receive the monthly statement before the payment due date

3.875

.832

.617

 

 

 

 

 

Perception

(F4) Flexibility

 

 

 

.846

F2: Credit cards make transactions easy

4.245

.746

.850

 

F1: Credit cards allow easy transfer of money

4.210

.705

.831

 

F4: I choose credit cards as a medium for speedy transactions

4.240

.738

.770

 

F3: I use credit cards since withdrawal process is simple

4.050

.794

.750

 

F5: Buying airlines/railways tickets by using credit card at special counter saves times

4.205

.803

.674

 

(F5) Related Benefits

 

 

 

.811

Rb1: Credit card creations influence the acceptance of credit cards

3.710

.780

.797

 

Rb2: Technology facilities encourage me to use credit cards

4.000

.868

.794

 

Rb4: Credit cards are opted mostly for security reasons

3.785

.861

.719

 

Rb3:  Incentive offered on card are not much satisfying

3.690

.829

.692

 

Rb5: Credit cards secure international presence

3.890

.748

.685

 

(F6) Perceived Risk

 

 

 

.668

PR1: Credit cards are not always reliable due to technical problems

3.375

.958

.845

 

PR2: Financial awareness of credit cards is not well communicated to customers.

3.460

1.083

.819

 

PR3:Credit cards are complex to use

3.350

1.055

.602

 

Source: Primary Data

Discussion

The in depth analysis of the above six factors are discussed as:

Factor One: Banking Policies

The factor banking policies explained variance of 28.176 % and composite of 4 items namely i) BP2(0.851), ii) BP1 (0.816) iii) BP3 (0.752) iv) BP4 (0.630). This factor expresses a Cronbach's alpha of 0.875 (87.5%) which is statistically acceptable. The factor banking policies refer to the benefits issuing banks and non-banks provide to credit card holders. These institutions offer benefits in the form of different incentives in order to attract consumers to apply for credit cards. These incentives include no annual fees (which has been packaged as an annual fees waiver), cash rebate, point rewards, airline miles, installment payment plan, and/or discounts for identified purchases. From the relationship marketing perspective, expenditure on credit cards are enhanced in terms of its ability to offer substantial income stream due to the availability of credit card insurance policy. Also , banks and non- banks provide the coverage in case of losing the credit card, accidents while on trips, and the card holders becoming unemployed or ill. Another possible benefit provided by these institutions could be the wide acceptance of the major card association banks which makes purchases through credit cards highly convenient. Therefore, the services provided by the banking institutions are comfortable, user friendly and easily accessible, affect the acceptability of credit cards.

 

Factor Two: Willingness to Pay

This factor explained variance of 24.697%. The composition of this factor also included five items i.e. i) WP5 (0.785), ii) WP2 (0.778), iii) WP4 (0.762), iv) WP3 (0.684) and v) WP1 (0.683). Cronbach's alpha of this factor was 0.871 which is acceptable. This factor refers the consumers’ understanding of cost and implications of using credit cards. It has been assumed that credit card users are aware of their credit balance, credit limit, and annual percentage rates. Hence the factor, “willingness to pay” aware the consumers about the transactions made by them and help them in hassle free deciding and finalizing of plans to make their purchases through credit cards.

 

Factor Three: Payment Policies

The factor namely payment policies explored a variance of 18.098% and composite of 3 items namely i) PP4 (0.834), ii) PP4 (0.721) and iii) PP5 (0.617). This factor expresses a Cronbach's alpha reliability of 0.777 (77.7 %) which was statistically acceptable. The factor payment policies introduced a facility for credit card users since the birth of credit cards. This facility provides grace period for credit card users to settle their debts, usually at the beginning of every month. Some credit card issuers also fixed certain dates of a month as deadline, for example, 10th or 12th day of the following month. This is done in light of the receipt of the credit card statements at the end of every month. If the card holders settle their debts within the grace period, no interest will be charged, otherwise, a fixed rate of interest will be charged on the total outstanding balance.

 

Factor Four: Flexibility

Flexibility is the fourth factor revealed by the study with the rotation sums of squared loading variance of 23.45%. This factor is composed with five items: i) F2 (0.850), ii) F1 (0.831), iii) F4 (0.770), iv) F3 (0.750) and v) F5 (0.674). This factor expresses a Cronbach's alpha reliability of 0.846 (84.6%). The factor flexibility suggested that customers could enjoy greater payment facilities through credit cards since credit cards are more rapid and convenient compared to cash and cheques payments. Moreover, ease-of-use, usage convenience, reliability, dispute resolution capability, record of transaction, and transaction speed contribute significantly towards the acceptance of credit cards. Also, the consumers could reported greater preference for speed, security, convenience, since they no longer have the burden to carry cash.

 

Factor Five: Related Benefits

Related Benefits is the fifth driver revealed by the study with the rotation sums of squared loading variance of 22.64%. This driver is composed with five items: i) RB1 (0.797), ii) RB2 (0.794), iii) RB4 (0.719), iv) RB3 (0.692) and v)RB5 (0.685).This factor expresses a Cronbach's alpha reliability of 0.811 (81.1%) which is statistically acceptable. This factor suggested that the advancement in technology also has an effect on the increase of acceptance of credit cards as it is a convenient channel to shop for goods and services. This practice inspires service innovations and enhances service delivery options.

 

Factor Six: Perceived Risk

Perceived Risk is the sixth factor revealed by the study with the rotation sums of squared loading variance of 14.20%. This driver is composed with three items: i) PR2 (0.845), ii) PR1 (0.819) and iii) PR3 (0.602). This factor expresses a Cronbach's alpha reliability of 0.668 (66.8%) which is statistically acceptable. The factor Perceived risk can influence the attitude and behaviour of consumers towards the credit cards payment services. The variables such as loss of cards and technical problems like machine break down may discourage customers to adopt credit cards in case of emergency. As such banks do not educate their cardholders on financial awareness and thus credit cards becomes complex to use. Also, customers possessing low financial knowledge have higher levels of debts and greater risk of bankruptcy and the perception of risks negatively affect the acceptance of credit cards as a payment mode.

 

  1. Limitations and Future Implications

Like other empirical studies, this study is not without its limitations. Our sample consisted of a very small area which limits the generalizability of the results. The sample size itself is relatively small. The study can be strengthened by increasing the sample size and including participants in other geographical areas. With an increased sample size, a more detailed empirical analysis can be performed. This research can serve as a starting point for the acceptance of credit cards, while encouraging further exploration and integration addition adoption constructs. Future research needs to focus on a larger cross section and more diversified samples to verify the findings of the current study. In this respect, research should extend to non-users, banking executives in order to allow a comparative analysis on the factors impacting on acceptance of credit cards among customers in Jammu region. Likewise, an integrated conceptual model relating to the various factors impacting on credit card adoption among customers can be proposed and tested in order to overcome the conceptual limitations of the present study and the research can be extended to other states of India as well as outside the country.

 

  1. Conclusion

The purpose of this study is to investigate factors affecting acceptability of credit cards in India; therefore, it was concentrated on the primary data only. The study revealed total six factors namely Bank Policies, Willingness to pay, Payment Policies, Flexibility, Related Benefits and Perceived Risk. The present study has emphasized on how customers are involved in the acceptance of credit cards in India. Customers are putting more importance on benefits of credit cards such as speed, convenience, environmental friendly and international presence. Customers are also very much interested about issues such as risks and security issues, new features and innovation when adopting credit cards. Hence, it is highly recommended that the banks develop a deep understanding of the factors influencing the acceptance of credit cards in order to adapt their marketing strategies to the potential customers. In fact, the research results can be useful and form practical tools for the policy makers and financial executives who are responsible for designing and marketing credit cards features and innovation at various point of sale in India.

 

References

  1. Almeida, M. (1995). The Future’s in Cards. Business India February 13(26),(113-116).
  2. Anneke, K.& Nederlandsche, B. (2010). Credit cards Acceptance and surchargingby retailers.
  3. Armstrong, C. J. & Craven, M. J. (1993).Credit card use and payment practices among a sample of college students.Proceedings of the Association for Financial Counseling and Planning Education, 148-159.
  4. Azhagaiah (2002).Credit creation through plastic money.Yojana 46 (12), (33- 34).
  5. Bellamy, E. (1887). Looking Backward.The Utopian Novel.
  6. Bowers, J. (1979). Consumer credit use by low income consumers who have had a consumer education course: An exploratory study. The journal of consumer affairs,13 (2): 340-341.
  7. Chakravorti, S. (2003). Theory of Credit Card Network: A Survey of The Literature, Review of Network Economics 2(2), 50-68.
  8. Deviranjitha, S.&Thamilarasan, S. (2014). A Study on usage and satisfaction of credit cards by customers in Krishnagiri district. International Journal of Business and Administration Research Review, 2(4),
  9. Hair, J. J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2007). Multivariate Data Analysis, (6th ed.) New Jersey: Pearson Prentice Hall.
  10. Hasan, M., & Harris, E. (2009). Entrepreneurship and Innovation in e-commerce. Journal of Achievements in Materials and Manufacturing Engineering, 32(1), 92-97.
  11. Kinsey, J. (1981). Determinants of credit card accounts: An application of Tobit analysis Journal of consumer Research, (8): 179-180.
  12. Lee, J.& K. (2002). Consumers use of credit cards: Store credit card usage as an alternative payment and financing medium. The journal of Consumer Affairs, 36(2): 248.
  13. Natarajan and Manohar (1993). Credit Cards–An Analysis, Financial Express, 14 April.
  14. Pudaruth, S., Juwahur, T.D &Madoo,V.(2013).Mapping the Hidden Construct Towardsthe Adoption of Plastic cards inMauritus,International Journal of Advanced Research, 1(4), 340-355.
  15. Teoh, W.M.C., Chong, S.C. & Yong, S.M. (2013). Exploring the factors influencing Credit card spending behaviour among Malaysians. International Journal of Bank Marketing,31 (6), 481-500.

indication for correlation between demographic and use of credit card. According to the study conducted by Kinsey (1981) the probability of having credit cards and the number held was correlated highly with age and occupation. However these two characteristics were less important than the place of residence, use of checking and savings accounts, and attitude towards credit.

Kaynak (1995) conducted an empirical research in urban Turkey which indicates that there is a relationship between socio-economic and demographic characteristics of Turkish consumers and their credit card holding and usage behaviors. It was observed that the age of the family head and family life–cycle stage are the determinants of credit card usage. Generally, middle and upper age, having a large flexible income level are more likely to use credit cards. This may be termed a social class effect of credit card usage and acceptance. Urban dwellers, more educated with professional type of jobs, and high income earners are using credit card mostly. For this credit card issuers are meeting this challenge by offering to card holder’s different benefits and incentives and by urging merchants to promotescredit at the point of sale.

 

Gambir (1998) studied that the regular user of cards needs to be well-informed and also made aware about credit cards usage. Till recently as it did not go along very well with the spirit of people because they do not have much money to spend because of bad economic conditions. But with increasing economic and financial liberalization and growing prosperity of the urban middle class banks feels that it is desirable to enter into this line of business. Credit cards and money transfers with the latest technological changes would definitely reduce the burden on cash in our system. Therefore, RBI has to give an impetus to the popularity of plastic money, which is consistent with present policy of economic and monetary liberalization.

The study revealed by Bhat and Maurya (2013) that the use of kissan credit card for the uplifting of the poor and to meet their socio-economics conditions and service provided by the J&K bank in the form of artecian credit card (Nazi,2013). Khaki and Sangmi (2012) studied that kissan credit card taken up by banker initiatives in Jammu and Kashmir. The use of credit cards is in its initial stages and is not so widespread and such its economic and social concern are not significant (Hassan & Harris, 2009).

From the review of studies mentioned above, it can be found that most of the studies are related with determinant of usage pattern of credit cards, credit cards fraud and their prevention, economics of card usage, customer acceptance and usage patterns, attitude towards credit cards etc. However, very few studies have been done on thedemographic and the socio-economic factors affecting the use of credit cards,particularly in the state of Jammu and Kashmir. Also, studies pertaining to credit cards on banking customers are very few in numbers and hence, the present study on the demographic and socio-economic analysis of users’ perception towards credit cards has been undertaken in Jammu region.

Research Methodology

Data was collected by using questionnaire, which was distributed amongst the sample of 250 from Jammu in J&K state. The sample was chosen by purposive convenience sampling method of sampling which is one of the non- probability techniques. Out of total nos. of 250 distributed questionnaires, 200 filled questionnaires were collected.

Generation of Scale Items

Theitems of different dimensions of Socio-economic (Bank Policies, Willingness to pay and Payment Policies) and Perception (Flexibility, Related benefits and Perceived Risk) were generated from review of relevant literature. The original scale consisted of 36 items rated on 5-point Likert-type scale with anchors of 1 as strongly disagree and 5 as strongly agree. Out of 36 items 20 items pertaining to Socio-Economic were extracted from the study that include Teoh, Chong and Yong, (2013) and the remaining 16 items pertaining to Perception were generated from  Pudaruth, Juwaheer and Madoo (2013).

Data Analysis

Demographical Profile

Table 1: depicts the demographic profile of the respondents as shown below:

Table1: Demographic Profile

 

Respondent’s Gender

 

Gender

Frequency

Percentage

Male

153

76.5

Female

47

23.5

Total

200

 

 

Respondent’s Occupation

 

Class

Frequency

Percentage

Business

46

23

Service

121

60.5

Professional

31

15.5

Student

2

1

Total

200

 

 

 

Respondent’s Age

 

Age

Frequency

Percentage

18-30

79

39.5

31-45

111

55.5

46-60

10

5

60+

0

0

Total

200

 

 

Respondent’s Income Group

 

Income

Frequency

Percentage

Up to ₹ 20,000

38

19

₹20,001 to ₹ 40,000

65

32.5

₹ 40,001 to ₹ 60,000

41

20.5

₹60,001 to ₹ 80,000

20

10

₹80,001 to ₹1,00,000

15

7.5

More than ₹ 1,00,000

21

10.5

Total

200

 

 

 

Number of Credit Cards Hold

 

Credit Card Number

Frequency

Percentage

Single

134

67

Multiple

66

33

Total

200

 

 

Respondent’s Usage Frequency

 

Usage

Frequency

Percentage

Daily

18

9

Weekly

92

46

Fortnightly

53

26.5

Monthly

23

11.5

Less Frequently

13

6.5

Never

1

0.5

Total

200

 

Source: Primary Data

The table above reveals gender of respondents which shows that out of 200 respondents surveyed; about (76.5%) of the participants were male and rest of (23.5%) were female. The variable occupation revealed that more than half of the participants (60.5%) were service personal and the least (1%) were students. In the case of age, the highest number of respondents was between the age group of 31-45 (55.5%) and lowest respondents were from the age group of 46-60 (5%).In the case of income variable, the income group between 20,001-40,000 (32.5%) was the most prominent. It has been shown from the table that maximum numbers of participants (67%) were single credit card users. The last variable that was taken for the purpose of the study was usage frequency of credit card users which revealed that (46%) of respondents used credit cards weekly and only (0.5%) of the respondents never used it.

 Factor Analysis

The exploratory factor analysis resulted into six factors containing25 items as shown in (Table 2). The variables with factor loading less than 0.5 and Eigen value less than 1.0 were ignored for the subsequent analysis (Hair et al. 2007). The Socio-Economic construct consisted of 20 statements, which reduce to 12 statements under three factors namely Bank Policies (BP), Willingness to pay (WP) and Payment Policies. The high KMO value and x2 value in Bartlett’s test of spherecity (0.767 & 1575.22) revealed the sampling adequacy of data for exploratory factor analysis. The total variance explained by these factors was arrived at 70.97%. Similarly, another construct named as Perception contained 16 statements which were reduced to 13 statements under three factors such as Flexibility (F), Related Benefits (RB) and Perceived Risk (PR). The KMOvalue, x2 value in Bartlett’s test of spherecity and the total variance explained by these factors were arrived at (0.769, 1123.48 and 60.28%), thus, suggested for factor analysis.

Table 2: Factor Analysis Results

Constructs

Factors

Mean

SD

FL

Cronbach’s alpha

 

 

Socio-Economic

 

 

 

 

 

 

 

(F1) Bank Policies

 

 

 

.875

BP2: I spend using credit card to earn points and exchange for gifts.

3.07

1.167

.851

 

BP1: I apply for credit cards to get free gifts.

3.28

1.165

.816

 

BP3: I was attracted by the cash rebate system, thus I always spend using credit card.

3.20

1.275

.752

 

BP4: I do not need to provide previous bills of credit cards when I am applying for another credit card.

3.425

1.113

.630

 

(F2) Willingness to Pay

 

 

 

.871

Wp5: I will make sure, I do make payment of credit card bills every month.

4.190

.6603

.785

 

Wp2: I know exactly the remaining debt that I due from previous transaction.

4.095

.7804

.778

 

Wp4: It is easy to find statement which was not made by me.

4.205

.6894

.762

 

Wp3: I will check on my bills to confirm all the transactions made by me are correct.

4.095

.7339

.684

 

Wp1: I know exactly how much I spent through credit card every month.

4.075

.8383

.683

 

(F3) Payment Policies

 

 

 

.777

PP4: I will make sure I did make payment of credit card bills every month

4.005

.740

.834

 

PP5: I will make sure I reserve my money to pay for the credit card bills

4.005

.753

.721

 

PP3: I will call the bank if I did not receive the monthly statement before the payment due date

3.875

.832

.617

 

 

 

 

 

Perception

(F4) Flexibility

 

 

 

.846

F2: Credit cards make transactions easy

4.245

.746

.850

 

F1: Credit cards allow easy transfer of money

4.210

.705

.831

 

F4: I choose credit cards as a medium for speedy transactions

4.240

.738

.770

 

F3: I use credit cards since withdrawal process is simple

4.050

.794

.750

 

F5: Buying airlines/railways tickets by using credit card at special counter saves times

4.205

.803

.674

 

(F5) Related Benefits

 

 

 

.811

Rb1: Credit card creations influence the acceptance of credit cards

3.710

.780

.797

 

Rb2: Technology facilities encourage me to use credit cards

4.000

.868

.794

 

Rb4: Credit cards are opted mostly for security reasons

3.785

.861

.719

 

Rb3:  Incentive offered on card are not much satisfying

3.690

.829

.692

 

Rb5: Credit cards secure international presence

3.890

.748

.685

 

(F6) Perceived Risk

 

 

 

.668

PR1: Credit cards are not always reliable due to technical problems

3.375

.958

.845

 

PR2: Financial awareness of credit cards is not well communicated to customers.

3.460

1.083

.819

 

PR3:Credit cards are complex to use

3.350

1.055

.602

 

Source: Primary Data

Discussion

The in depth analysis of the above six factors are discussed as:

Factor One: Banking Policies

The factor banking policies explained variance of 28.176 % and composite of 4 items namely i) BP2(0.851), ii) BP1 (0.816) iii) BP3 (0.752) iv) BP4 (0.630). This factor expresses a Cronbach's alpha of 0.875 (87.5%) which is statistically acceptable. The factor banking policies refer to the benefits issuing banks and non-banks provide to credit card holders. These institutions offer benefits in the form of different incentives in order to attract consumers to apply for credit cards. These incentives include no annual fees (which has been packaged as an annual fees waiver), cash rebate, point rewards, airline miles, installment payment plan, and/or discounts for identified purchases. From the relationship marketing perspective, expenditure on credit cards are enhanced in terms of its ability to offer substantial income stream due to the availability of credit card insurance policy. Also , banks and non- banks provide the coverage in case of losing the credit card, accidents while on trips, and the card holders becoming unemployed or ill. Another possible benefit provided by these institutions could be the wide acceptance of the major card association banks which makes purchases through credit cards highly convenient. Therefore, the services provided by the banking institutions are comfortable, user friendly and easily accessible, affect the acceptability of credit cards.

 

Factor Two: Willingness to Pay

This factor explained variance of 24.697%. The composition of this factor also included five items i.e. i) WP5 (0.785), ii) WP2 (0.778), iii) WP4 (0.762), iv) WP3 (0.684) and v) WP1 (0.683). Cronbach's alpha of this factor was 0.871 which is acceptable. This factor refers the consumers’ understanding of cost and implications of using credit cards. It has been assumed that credit card users are aware of their credit balance, credit limit, and annual percentage rates. Hence the factor, “willingness to pay” aware the consumers about the transactions made by them and help them in hassle free deciding and finalizing of plans to make their purchases through credit cards.

 

Factor Three: Payment Policies

The factor namely payment policies explored a variance of 18.098% and composite of 3 items namely i) PP4 (0.834), ii) PP4 (0.721) and iii) PP5 (0.617). This factor expresses a Cronbach's alpha reliability of 0.777 (77.7 %) which was statistically acceptable. The factor payment policies introduced a facility for credit card users since the birth of credit cards. This facility provides grace period for credit card users to settle their debts, usually at the beginning of every month. Some credit card issuers also fixed certain dates of a month as deadline, for example, 10th or 12th day of the following month. This is done in light of the receipt of the credit card statements at the end of every month. If the card holders settle their debts within the grace period, no interest will be charged, otherwise, a fixed rate of interest will be charged on the total outstanding balance.

 

Factor Four: Flexibility

Flexibility is the fourth factor revealed by the study with the rotation sums of squared loading variance of 23.45%. This factor is composed with five items: i) F2 (0.850), ii) F1 (0.831), iii) F4 (0.770), iv) F3 (0.750) and v) F5 (0.674). This factor expresses a Cronbach's alpha reliability of 0.846 (84.6%). The factor flexibility suggested that customers could enjoy greater payment facilities through credit cards since credit cards are more rapid and convenient compared to cash and cheques payments. Moreover, ease-of-use, usage convenience, reliability, dispute resolution capability, record of transaction, and transaction speed contribute significantly towards the acceptance of credit cards. Also, the consumers could reported greater preference for speed, security, convenience, since they no longer have the burden to carry cash.

 

Factor Five: Related Benefits

Related Benefits is the fifth driver revealed by the study with the rotation sums of squared loading variance of 22.64%. This driver is composed with five items: i) RB1 (0.797), ii) RB2 (0.794), iii) RB4 (0.719), iv) RB3 (0.692) and v)RB5 (0.685).This factor expresses a Cronbach's alpha reliability of 0.811 (81.1%) which is statistically acceptable. This factor suggested that the advancement in technology also has an effect on the increase of acceptance of credit cards as it is a convenient channel to shop for goods and services. This practice inspires service innovations and enhances service delivery options.

 

Factor Six: Perceived Risk

Perceived Risk is the sixth factor revealed by the study with the rotation sums of squared loading variance of 14.20%. This driver is composed with three items: i) PR2 (0.845), ii) PR1 (0.819) and iii) PR3 (0.602). This factor expresses a Cronbach's alpha reliability of 0.668 (66.8%) which is statistically acceptable. The factor Perceived risk can influence the attitude and behaviour of consumers towards the credit cards payment services. The variables such as loss of cards and technical problems like machine break down may discourage customers to adopt credit cards in case of emergency. As such banks do not educate their cardholders on financial awareness and thus credit cards becomes complex to use. Also, customers possessing low financial knowledge have higher levels of debts and greater risk of bankruptcy and the perception of risks negatively affect the acceptance of credit cards as a payment mode.

 

  1. Limitations and Future Implications

Like other empirical studies, this study is not without its limitations. Our sample consisted of a very small area which limits the generalizability of the results. The sample size itself is relatively small. The study can be strengthened by increasing the sample size and including participants in other geographical areas. With an increased sample size, a more detailed empirical analysis can be performed. This research can serve as a starting point for the acceptance of credit cards, while encouraging further exploration and integration addition adoption constructs. Future research needs to focus on a larger cross section and more diversified samples to verify the findings of the current study. In this respect, research should extend to non-users, banking executives in order to allow a comparative analysis on the factors impacting on acceptance of credit cards among customers in Jammu region. Likewise, an integrated conceptual model relating to the various factors impacting on credit card adoption among customers can be proposed and tested in order to overcome the conceptual limitations of the present study and the research can be extended to other states of India as well as outside the country.

 

  1. Conclusion

The purpose of this study is to investigate factors affecting acceptability of credit cards in India; therefore, it was concentrated on the primary data only. The study revealed total six factors namely Bank Policies, Willingness to pay, Payment Policies, Flexibility, Related Benefits and Perceived Risk. The present study has emphasized on how customers are involved in the acceptance of credit cards in India. Customers are putting more importance on benefits of credit cards such as speed, convenience, environmental friendly and international presence. Customers are also very much interested about issues such as risks and security issues, new features and innovation when adopting credit cards. Hence, it is highly recommended that the banks develop a deep understanding of the factors influencing the acceptance of credit cards in order to adapt their marketing strategies to the potential customers. In fact, the research results can be useful and form practical tools for the policy makers and financial executives who are responsible for designing and marketing credit cards features and innovation at various point of sale in India.

 

References

  1. Almeida, M. (1995). The Future’s in Cards. Business India February 13(26),(113-116).
  2. Anneke, K.& Nederlandsche, B. (2010). Credit cards Acceptance and surchargingby retailers.
  3. Armstrong, C. J. & Craven, M. J. (1993).Credit card use and payment practices among a sample of college students.Proceedings of the Association for Financial Counseling and Planning Education, 148-159.
  4. Azhagaiah (2002).Credit creation through plastic money.Yojana 46 (12), (33- 34).
  5. Bellamy, E. (1887). Looking Backward.The Utopian Novel.
  6. Bowers, J. (1979). Consumer credit use by low income consumers who have had a consumer education course: An exploratory study. The journal of consumer affairs,13 (2): 340-341.
  7. Chakravorti, S. (2003). Theory of Credit Card Network: A Survey of The Literature, Review of Network Economics 2(2), 50-68.
  8. Deviranjitha, S.&Thamilarasan, S. (2014). A Study on usage and satisfaction of credit cards by customers in Krishnagiri district. International Journal of Business and Administration Research Review, 2(4),
  9. Hair, J. J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2007). Multivariate Data Analysis, (6th ed.) New Jersey: Pearson Prentice Hall.
  10. Hasan, M., & Harris, E. (2009). Entrepreneurship and Innovation in e-commerce. Journal of Achievements in Materials and Manufacturing Engineering, 32(1), 92-97.
  11. Kinsey, J. (1981). Determinants of credit card accounts: An application of Tobit analysis Journal of consumer Research, (8): 179-180.
  12. Lee, J.& K. (2002). Consumers use of credit cards: Store credit card usage as an alternative payment and financing medium. The journal of Consumer Affairs, 36(2): 248.
  13. Natarajan and Manohar (1993). Credit Cards–An Analysis, Financial Express, 14 April.
  14. Pudaruth, S., Juwahur, T.D &Madoo,V.(2013).Mapping the Hidden Construct Towardsthe Adoption of Plastic cards inMauritus,International Journal of Advanced Research, 1(4), 340-355.
  15. Teoh, W.M.C., Chong, S.C. & Yong, S.M. (2013). Exploring the factors influencing Credit card spending behaviour among Malaysians. International Journal of Bank Marketing,31 (6), 481-500.
 
 

Pacific Institute of Management, Pacific Hills, Airport Road, Udaipur - 313001, E-mail: edit@pbr.co.in
Phone : +91-294-2494506, +91-294-2494507

©Pbr.co.in, All Right Reserved IT Department , Pacific Group