Print this page

Impact of Mobile Banking on Overall Customer Satisfaction: An Empirical Study

London Journal of Research in Management and Business
Volume | Issue | Compilation
Authored by dr. fozia , NA
Classification: JEL Code: G24
Keywords: mobile banking overall customer satisfaction and regression test.
Language: English

The purpose of this paper is to analyze the impact of dimensions of Mobile Banking on Overall Customer Satisfaction separately in Public and Private Banks Across Security & Privacy, Accuracy, Accessibility and Easy to Use. A convenience sampling technique was used to recruit 320 customers through a well-designed questionnaire from three Public Banks i.e. SBI, Punjab National Bank and Bank of Baroda and three Private Banks i.e. ICICI, HDFC and Axis Bank of NCR, India. The questionnaire is representing the desired range of demographic characteristics e.g. Gender, Age, and Occupation. Data has been analyzed by Regression Test. This research showed that dimensions of Mobile Banking i.e. Security & Privacy in public banks, Accessibility and Ease of Use variables have significant impact on Overall Customer Satisfaction. Even though Accuracy and Security & Privacy in private banks variables do not have a significant impact on Overall Customer Satisfaction.

               

Impact of Mobile Banking on Overall Customer Satisfaction: An Empirical Study

Dr. Fozia

____________________________________________ 

  1. ABSTRACT

The purpose of this paper is to analyze the impact of dimensions of Mobile Banking on Overall Customer Satisfaction separately in Public and Private Banks Across Security & Privacy, Accuracy, Accessibility and Easy to Use. A convenience sampling technique was used to recruit 320 customers through a well-designed questionnaire from three Public Banks i.e. SBI, Punjab National Bank and Bank of Baroda and three Private Banks i.e. ICICI, HDFC and Axis Bank of NCR, India. The questionnaire is representing the desired range of demographic characteristics e.g. Gender, Age, and Occupation. Data has been analyzed by Regression Test. This research showed that dimensions of Mobile Banking i.e. Security & Privacy in public banks, Accessibility and Ease of Use variables have significant impact on Overall Customer Satisfaction. Even though Accuracy and Security & Privacy in private banks variables do not have a significant impact on Overall Customer Satisfaction.

Keywords: mobile banking overall customer satisfaction and regression test.

Author: Faculty of Commerce, Aligarh Muslim University, India.

  1. INTRODUCTION

With the implementation of information technology, the banking industry has brought a revolutionary change in the workability of banks. Now banks provide IT based products and services to their customers. Bank customers are becoming highly demanding and curious about the new technology-based banking products and services. Technology has changed the total system of banking operation and enabled banks to satisfy the needs of the customers adequately. IT is not confined only to transaction processing and management information system, but it has created a competitive environment for banks to retain their customers. These information technological changes in Indian banking are called as mobile banking. It is one of the emerging trends in the Indian banking and is playing a unique role in strengthening the banking sector and improving service quality.

Mobile banking means that any enquiry or transaction can be processed online without going to branch concerned. It reduces physical and geographical boundaries and allows customers to make banking transactions anywhere and anytime. New technology has rapidly transformed the traditional ways of doing banking operations. Traditional banking is branch based banking in which banks need to establish a physical presence in geographical area to carry out banking operations. It requires a maximum of interaction with physical services, processes, payments and medium of exchange mainly includes cash, check, bank cards and other such operations. But on the other side, new technological banking creates extraordinary opportunities for the banks in the ways they organize financial product development, delivery and marketing via the internet. It provides number of facilities to the customers such as they can get any information related to their account and online transaction. It also allows customers to make payment, perform electronic recharge, pay bills, access account information and transfer funds from one account of the bank to another.

Siu and Mou (2008) examined the perception of customers regarding the service quality dimensions and impact of e-SERVQUAL dimensions on customer satisfaction in internet banking. Factors like credibility, efficiency, problem handling, and security were used to find the perception of customers towards the service quality dimensions in internet banking. The data from 195 customers of banks were selected using an e-SERVQUAL questionnaire and tools like factor analysis; t-test, one-way ANOVA and multiple regression tests were used to find the perception of customers. Finding suggests that all three dimensions such as credibility, efficiency, problem handling were found to be important in determining overall service quality perceptions of customers except security. From the regression test, finding reveals that credibility, problem handling, and security have significant impact on customer satisfaction.

Kumbhar (2011) examined important factors that have impact on customers’ satisfaction. In this study, fifteen key dimension of service quality such as overall satisfaction, system availability, e-fulfilment, accuracy, efficiency, security/ assurance, responsiveness, easy to use, convenience, cost effectiveness, problem handling, compensation, contact, perceived value and brand perception were use. The data was collected through a questionnaire from 150 customers of public and private banks who are using alternative banking channel. Statistical tools like descriptive statistics, multiple correlation, Kruskal Wallis, Mann Whitney test and principal component analysis were used to analyse the data. Further finding implies there was a significant relationship between all dimensions and overall customer satisfaction.

Ramseook-Munhurrun and Naidoo (2011) examined the potential dimensions of internet banking and its impact on customer satisfaction. Five key dimensions of service quality such as reliability-responsiveness, security, ease of use, accessibility and satisfaction were taken for the study. The data was collected through SERVQUAL model questionnaire from 242 internet banking customers. Tools like factor analysis, paired t-test and regression test were used to analyse the data. Finding implies that reliability-responsiveness and accessibility were found to be important in determining overall customer satisfaction, with accessibility having the most significant impact.

Banerjee and Sah (2012) examined the perception of customers towards services provided by public and private sector banks. The SERVQUAL instrument has been used by the researcher and the variables included in the research were tangibility, reliability, responsiveness, assurance and empathy. The sample size of the study was 230 respondents. The Mann Whitney U test was used to compare the perceptions of customers towards the different attributes of the service dimensions between private and public-sector banks. Findings unveil that customers are satisfied with private banks and expect more services from private banks. To satisfy the customers, the public banks should focus on improving the service in terms of tangibility, reliability, responsiveness and empathy.

Prameela (2013) analyzed the perceptions of the customers on the technology deployment in Andhra Bank & ICICI Bank. The variables included in this research were tangibility, reliability, responsiveness, assurance, empathy, efficiency, accuracy, security, easy and convenient banking. The data was collected through a well-designed questionnaire from 500 customers. Tools like chi-square, ANOVA and t-test have been used to analyse the data. Finding reveals that the perception and experience of the customers on the technology deployment in Andhra Bank and ICICI bank were in favour of up gradation of technology.

  1. METHODS

In the present study data was collected with the help of a well-structured questionnaire from selected cities of National Capital Region (NCR) i.e. Faridabad, Gurgaon, Ghaziabad, Noida and New Delhi. the author has selected top three public banks i.e. State Bank of India, Bank of Baroda, Punjab National Bank and top three private banks i.e. ICICI, HDFC, Axis Bank of NCR. About 500 questionnaires have been distributed out of which 320 filled questionnaires have been received from the public and private banks customers of NCR, India. The sample for this study is selected based on convenience sampling method because it is an easy way to collect data for further analysis. The questionnaire is based on Likert‟s five-point scale ranging from “Highly Satisfied”- (5) to “Highly Dissatisfied”- (1). Customers can select the desired option according to their satisfaction and dissatisfaction level. The questionnaire comprises of two sections: section “A” on respondent’s socio demographic characteristics and section “B” is represents Mobile Banking dimensions. The section “A” depicts the demographic information of the respondents i.e. Name of the Bank, Gender, Education level, Income, Occupation and Internet usage. The section “B” of the questionnaire contains close ended questions which are concerned to elicit information about the perception of the customers that have direct emphasis on the hypothesis of the study. In this study, Regression Test is used to analyses the impact of dimensions of Mobile Banking on Overall Customers Satisfaction separately in Public and Private Banks. Data are computed and analyzed via Statistical Packages for Social Science (SPSS) computer program version 19.0.

  1. RESULTS AND DISCUSSION

Ho1: There is no significant impact of dimensions of Mobile Banking on overall customer satisfaction of the customers of the banks.

Ho1.1: There is no significant impact of Security & Privacy as a dimension of Mobile Banking on overall customer satisfaction of the customers of the public banks.

Ho1.2: There is no significant impact of Security & Privacy as a dimension of Mobile Banking on overall customer satisfaction of the customers of the private banks.

Table 1: Beta (β), T value and significant value of Security & Privacy on overall customer satisfaction

S.No.

Results of Multiple Regression

Security & Privacy vs. Overall Customer Satisfaction

Security & Privacy

Beta(β)

T

Sig.

Results

Ho1.1

Public Banks

.154

3.864

.001

Sig. Impact

Ho1.2

Private Banks

.056

.834

.406

No sig. impact

In the above table 1, results of Multiple Regression Test are shown. This table indicates the Beta (β), T value, significant value and result estimates the impact of Security & Privacy on overall customer satisfaction.

The above table shows the result of multiple regression test used to assess the impact of dimension of mobile banking i.e. Security & Privacy as an independent variable on overall customer satisfaction as a dependent variable. In the public banks, Beta(β) value is .154, which is more than the private banks’ Beta(β) value i.e. .056, which shows that the impact of Security & Privacy on overall customers’ satisfaction is more in the public banks as compare to the private banks. The t-value is 3.864 and sig. value of the public banks is .001, which is less than 0.05, which indicates that there is a significant impact of Security & Privacy on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Security & Privacy as a dimension of mobile banking on overall customer satisfaction of the customers of banks stands rejected and alternative hypothesis is accepted.

Similarly, in the private banks, Beta(β) value is .056, which is less than the public banks’ Beta(β) value i.e. .154, which shows that the impact of Security & Privacy on overall customers’ satisfaction is less in the private banks as compared to the public banks. The t-value is .834 and sig. value of the private banks is .406, which is more than 0.05, which indicates that there is no significant impact of Security & Privacy on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Security & Privacy as a dimension of mobile banking on overall customer satisfaction of the customers of the private banks stands accepted and alternative hypothesis is rejected.

Ho2: There is no significant impact of dimensions of Mobile Banking on overall customer satisfaction of the customers of the banks.

Ho2.1: There is no significant impact of Accessibility as a dimension of Mobile Banking on overall customer satisfaction of the customers of the public banks.

Ho2.2: There is no significant impact of Accessibility as a dimension of Mobile Banking on overall customer satisfaction of the customers of the private banks.

Table 2: Beta (β), T value and significant value of Accessibility on overall customer satisfaction

S.No.

Results of Multiple Regression 

Accessibility vs. Overall Customer Satisfaction

Accessibility

Beta(β)

T

Sig.

Results

Ho2.1

Public Banks

.317

3.869

.000

Sig. Impact

  Ho2.2

Private Banks

.319

4.305

.000

Sig. Impact

In the above table 2, results of Multiple Regression Test are shown. This table indicates the Beta (β), T value, significant value and the result estimates the impact of Accessibility on overall customer satisfaction.

The above table shows the result of multiple regression test take to assess the impact of dimension of mobile banking i.e. Accessibility as an independent variable on overall customer satisfaction as a dependent variable. In the public banks, Beta(β) value is .317, which is less than private banks’ Beta(β) value i.e. .319, which confirms that the impact of Accessibility on overall customers’ satisfaction is less in the public banks as compared to the private banks. The t-value is 3.869 and sig. value of the public banks is .000, which is less than 0.05, thus indicating that there is a significant impact of Accessibility on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Accessibility as a dimension of mobile banking on overall customer satisfaction of the customers of the public banks stands rejected and alternative hypothesis is accepted.

Similarly, in the private banks, Beta(β) value is .319, which is more than the public banks Beta(β) value i.e. .317, which shows that the impact of Accessibility on overall customers’ satisfaction is more in the private banks as compared to the public banks. The t-value is 4.305 and sig. value of the private banks is .000, which is less than 0.05, which is an indication that there is a significant impact of Accessibility on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Accessibility as a dimension of mobile banking on overall customer satisfaction of the customers of the private banks stands rejected and alternative hypothesis is accepted.

Ho3: There is no significant impact of dimensions of Mobile Banking on overall customer satisfaction of the customers of the banks.

Ho3.1: There is no significant impact of Ease of use as a dimension of Mobile Banking on overall customer satisfaction of the customers of the public banks.

Ho3.2: There is no significant impact of Ease of use as a dimension of Mobile Banking on overall customer satisfaction of the customers of the private banks.

Table 3: Beta (β), T value and significant value of Ease of use on overall customer satisfaction

S.No.

Results of Multiple Regression 

Easy to use Vs. Overall Customer Satisfaction

Easy to use

Beta(β)

T

Sig.

Results

Ho3.1

Public Banks

.057

3.685

.000

Sig impact

Ho3.2

Private Banks

.255

4.014

.000

Sig impact

In the above table 3, results of Multiple Regression Test are shown. This table indicates the Beta (β), T value, significant value and the result estimates the impact of Ease of use on overall customer satisfaction.

The above table shows the result of multiple regression test put to estimate the impact of dimension of Mobile banking i.e. Ease of use as an independent variable on overall customer satisfaction as a dependent variable. In the public banks, Beta(β) value is .057, which is less than the private banks’ Beta(β) value i.e. .255, which shows that the impact of Ease of use on overall customers’ satisfaction is less in the public banks as compared to the private banks. The t-value is 3.685 and sig. value of the public banks is .000, which is less than 0.05, which indicates that there is a significant impact of Ease of use on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Ease of use as a dimension of mobile banking on overall customer satisfaction of the customers of the public banks stands rejected and alternative hypothesis is accepted.

Similarly, in the private banks, Beta(β) value is .255, which is more than the public banks Beta(β) value i.e. .057, which shows that the impact of Ease of use on overall customers’ satisfaction is more in the private banks as compared to the public banks. The t-value is 4.014 and sig. value of the private banks is .000, which is less than 0.05, which indicates that there is a significant impact of Easy to use on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Ease of use as a dimension of mobile banking on overall customer satisfaction of the customers of the private banks stands rejected and alternative hypothesis is accepted.

Ho4: There is no significant impact of dimensions of Mobile Banking on overall customer satisfaction of the customers of the banks.

Ho4.1: There is no significant impact of Accuracy as a dimension of Mobile Banking on overall customer satisfaction of the customers of the public banks.

Ho4.2: There is no significant impact of Accuracy as a dimension of Mobile Banking on overall customer satisfaction of the customers of the private banks.

Table 4: Beta (β), T value and significant value of Accuracy on overall customer satisfaction

S.No.

Results of Multiple Regression

Accuracy vs. Overall Customer Satisfaction

Accuracy

Beta(β)

T

Sig.

Results

Ho4.1

Public Banks

.073

.906

.366

No sig. Impact

Ho4.2

Private Banks

.013

.225

.822

No sig. Impact

In the above table 4, results of Multiple Regression Test are shown. This table indicates the Beta (β), T value, significant value and the result estimates the impact of Accuracy on overall customer satisfaction.

The above table shows the result of multiple regression test employed to assess the impact of dimension of mobile banking i.e. Accuracy as an independent variable on overall customer satisfaction as a dependent variable. In the public banks, Beta(β) value is .073, which is more than the private banks Beta(β) value i.e. .013, which shows that the impact of Accuracy on overall customers’ satisfaction is more in the public banks as compared to the private banks. The t-value is .906 and sig. value of the public banks is .366, which is more than 0.05, which indicates that there is no significant impact of Accuracy on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Accuracy as a dimension of mobile banking on overall customer satisfaction of the customers of the public banks stands accepted and alternative hypothesis is rejected.

Similarly, in the private banks, Beta(β) value is .013, which is less than public banks Beta(β) value .073, which shows that the impact of Accuracy on overall customers’ satisfaction is less in the private banks as compared to the public banks. The t-value is .225 and sig. value of the private banks is .822, which is more than 0.05, which indicates that there is no significant impact of Accuracy as a dimension of mobile banking on overall customer satisfaction. Hence, the hypothesis that there is no significant impact of Accuracy as a dimension of mobile banking on overall customer satisfaction of the customers of the private banks stands accepted and alternative hypothesis is rejected.

V.    CONCLUSION

In this research Security & Privacy in public banks, Accessibility and Ease of Use variables have a significant impact on overall customer satisfaction towards mobile banking. Even though Accuracy and Security & Privacy in private banks variables do not have a significant impact on overall customer satisfaction. In this research, the importance of these two variables cannot be ignored by mobile banking providers because prior research had shown that Accuracy and Security & Privacy variables are important in fulfilling Overall Customer Satisfaction toward Mobile Banking. This research can help mobile banking providers to know mobile banking users’ opinion and find the solution through customers’ perspective. It can help mobile banking providers easily achieve customer satisfaction.

There are several recommendations that can help in overcoming this research. The problem of constraints on time can be solved by increasing the range of time in conducting a research in the future. The sample size of the research should be increased because the sample size may affect the reliability of the research. Sample size can help to improve the reliability between independent variables and dependent variable. Increase in sample size can help researchers to choose more working adults who work in different areas in NCR. In addition; this research study is geographically restricted to NCR due to time and financial constraints and restricted to Public & private banks only. Co-operative & foreign banks are not included in the study. These are some of limitations in this research, but they can be solved by applying the recommendations mentioned above. After the limitations are solved an accurate and reliable result can be generated in the future research.

REFERENCES

  1. Dhurup, M., Surujlal, J., & Redda, E. (2014). Customer perceptions of online banking service quality. Mediterranean Journal of Social Sciences, 5(2), 587-594.doi:10.5901/ mjss.2014.v5n2p587, p. 592
  2. Zafar, M., Zafar, S., Asif, A., Hunjra, A. I. & Ahmad, H. M. (2012). Service Quality, Customer Satisfaction and Loyalty: An Empirical Analysis of Banking Sector in Pakistan. Information Management and Business Review, 4(3), 159-167.
  3. Kumbhar, V.M. (2011). Service Quality Perception and Customers’ Satisfaction in Internet Banking Service: A Case Study of Public and Private Sector Banks, Cyber Literature: The International Online Journal, 4 (2), 21-30.
  4. Kumbhar, V.M. (2011). Alternative Banking Channels and Customers’ Satisfaction: An Empirical Study of Public and Private Sector Banks, international journal of business and management tomorrow, 1(1), 1-24.
  5. Geetha, K.T. and Malarvizhi,V. (2008). Acceptance of e-banking among customers (An Empirical Investigation in India), Journal of Management and Science, 2(1), 1-9.
  6. Alam, M., & Soni, A. M. (2012), “Customer Satisfaction of Internet Banking and kTheory of Big Push: An Analytical Study with Special Reference to Selected Customers in Vadodara City”, Ninth AIMS International Conference on Management, 941-947.
  7. Kaur, Jasveen and Kaur, Baljit, (2013), Determining Internet Banking Service Quality & Customer Satisfaction in India, Tenth AIMS International Conference on Management, 2670-2679.
  8. Khalil, Khalil Mohammed (2011), Online Service Quality and Customer Satisfaction: A case study of Bank Islam Malaysia Berhad, https://mpra.ub.uni muenchen.de/30782/ MPRA Paper No. 30782.
  9. Khan, M. S., & Mahapatra, S. S. (2009). Service quality evaluation in internet banking: an empirical study in India. International Journal of Indian Culture and Business Management2(1), 30-46.
  10. Nupur, J. M. (2010). E-banking and customers’ satisfaction in Bangladesh: An analysis. International Review of Business Research Papers6(4), 145-156.
  11. Raza, S. A., Jawaid, S. T., & Hassan, A. (2013). “Internet Banking and Customer Satisfaction in Pakistan”, https://mpra.ub.uni-muenchen. de/48395/MPRA Paper No. 48395,
  12. Ping, C. T., Suki,N.M., & Suki,N.M., (2012). service quality dimension effects on customer satisfaction towards e-banking. interdisciplinary journal of contemporary research in business , 4(4), 741-751.
  13.  Al-hawarry, S.I.S., Alhamali., R. M. & Saad, A. A., (2011). Banking Service Quality Provided by Commercial Banks and Customer Satisfaction. American Journal of Scientific Research, 27, 68-83.
  14.  Zafar et al (2012). Service Quarlity, Customer Satisfaction and Loyalty: An Empirical Analysis of Banking Sector in Pakistan. Information Management and Business Review, 4(3),159-167
  15. Kumbhar,Vijay. M. (2011), Structural Equation Modeling of eBankqual Scale: A Study of E-Banking in India, International Journal of Business Economics Management Research, 2(5), 18-32.
  16. Joshua, A. J. & Koshy, M. P. (2011), “Usage Patterns of Electronic Banking Services by Urban Educated Customers: Glimpses from India”, Journal of Internet Banking and Commerce, 16(1), 1-2.
  17. Ahmad, A. E., & Al-Zu' bi, H. A. (2011). E-banking Functionality and Outcomes of Customer Satisfaction: An Empirical Investigation. International Journal of Marketing Studies, 3(1), 51-59.
  18. Wu et al (2006), core capabilities for exploiting electronic banking, Journal of Electronic Commerce Research, 7 (2), 111-122.
  19. Ahmad, A. M., & Al-Zu’bi, H. A. (2011). E-banking functionality and outcomes of customer satisfaction: An empirical investigation. International Journal of Marketing Studies, 3(1), 50-65, p. 51-52.
  20. Dixit, N., & Datta, S. K. (2010). Acceptance of E-banking among Adult Customers: An Empirical Investigation in India. Journal of Internet Banking and Commerce, 15(2), 4-14.
  21. Munhurrun, PrabhaRamseook., and Naidoo, Perunjodi. (2013). Customers' Perspectives of Service Quality in Internet Banking, Services Marketing Quarterly, 32(4), 247-264.
  22. Chaung, C. C., & Hu, Fu-Ling. (2011). An empirical study of customers’ perception of e-banking service based on time usage. Journal of Internet Banking and Commerce, 16(2), 1-11, p. 4.
  23. Ping,C. T. Y., Suki, N. M., & Suki, N. M. (2014). Service quality dimension effects on customer satisfaction towards e-banking. Interdisciplinary Journal of Contemporary Research in Business, 4(4), 741-751, p. 743.
  24. Vivekanandan, L., & Jayasena, S. (2012). Facilities offered by the banks and expectations of IT savvy banking customers. Procedia - Social and Behavioral Sciences, 40, 576-583. doi: 10.1016/j.sbspro.2012.03. 233.
  25. Ling, et al. (2016). Understanding Customer Satisfaction of Internet Banking: A Case Study in Malacca. Procedia Economics and Finance, 37, 80-85.
  26. Siu, N. Yee-Man., & Mou, J. Chi-Wah. (2008). Measuring service quality in internet banking: The case of Hong Kong. Journal of International Consumer Marketing, 17(4), 99-116. doi:10.1300/J046v17n04_06
  27. Ramseook-Munhurrun, P., &Naidoo, P. (2011). Customers' perspectives of service quality in internet banking. Services Marketing Quarterly, 32(4), 247-264. doi:10.1080/15332969.2011.606753
  28. Banerjee, N., &Sah, S. (2012). A comparative study of customers’ perceptions of service quality dimensions between public and private banks in India. International Journal of Business Administration, 3(5), 33-44. Doi:10. 5430/ijba.v3n5p33
  29. Prameela, A. (2013). Technology in banking – An impact study in the operations of public and private sector banks with reference to Andhra bank and ICICI Bank – Vizagcity (Doctoral Thesis, Andhra University, Visakhapatnam Andhra Pradesh). Retrieved from https://shodhganga.inflibnet.ac.in/ handle/10603/8668



author

For Authors

Author Membership provide access to scientific innovation, next generation tools, access to conferences/seminars
/symposiums/webinars, networking opportunities, and privileged benefits.
Authors may submit research manuscript or paper without being an existing member of LJP. Once a non-member author submits a research paper he/she becomes a part of "Provisional Author Membership".

Know more

institutes

For Institutions

Society flourish when two institutions come together." Organizations, research institutes, and universities can join LJP Subscription membership or privileged "Fellow Membership" membership facilitating researchers to publish their work with us, become peer reviewers and join us on Advisory Board.

Know more

subsribe

For Subscribers

Subscribe to distinguished STM (scientific, technical, and medical) publisher. Subscription membership is available for individuals universities and institutions (print & online). Subscribers can access journals from our libraries, published in different formats like Printed Hardcopy, Interactive PDFs, EPUBs, eBooks, indexable documents and the author managed dynamic live web page articles, LaTeX, PDFs etc.

Know more