Adoption of Internet Banking Services in India: An Empirical Study

Table of contents

1. Introduction

echnology across the globe creating wonders in every sector, from automobile to animation and from medicine to machinery. Internet is one such advancement of technology which has changed the landscape of few industries; banking is one among them. Internet banking brought a breakthrough changes in the operations of banking. Customer is now equipped with faster and simpler ways to perform their banking transactions like funds transfer, bill payments, electronic clearances etc.

According to metrics.com (2013), 72.5 million of the households are utilizing internet banking in the world and are very much loyal to the banks. The number of users of internet banking are increasing exponentially; this is due to the several advantages assigned with the online banking system. According to www.roymorgan.com (2015), 90.2% is the satisfaction level of internet banking and 88.4% is the satisfaction of branch banking. Generation Y are the main users of the new technology in banking.

Though there are many advantages of IB, the increase online fraudulent poses greater risk in using IB. BBC report confirms that online banking fraud is increasing and is up by 48% in the year 2014. This is one of the major concern for the banking customers in using IB.

The present study is aimed at investigating the adoption of IB in India. For the same purpose, the study adapts the widely accepted Technology Acceptance Model (TAM). Since web security is one of the main concern, we also included Perceived Web Security (PWS) as one of the construct in understanding the attitude and behavioral intention of the customers in adopting IB services.

2. II.

3. Review of Literature

The present study would focus on the use of TAM to understand the behavioral intention of the customers to use internet banking services. Though a significant number of studies were conducted in the past related to understanding of customers' adoption of new technology using, relatively less number of studies used the extension of TAM (Cheng, Lam, & Yeung, 2006). Extension of TAM to study the adoption of internet banking services; especially in India are significantly less till date.

Technology Acceptance Model (TAM) by (Davis, 1989), which was based on the Theory of Reasoned Action (TRA) by (Ajzen & Fishbein, 1975), has proposed two important determinants to study the adoption of new technology (Legris, Ingham, & Collerette, 2003). The model has been widely used in various contexts to study the behavioral intention.

According to (Davis, 1989, p. 3), Perceived Usefulness (PU) is "the degree to which a person believes that using a particular system would enhance his or her job performance'' and in contrast, Perceived Ease of Use (PEoU) is defined as "the degree to which a person believes that using a particular system would be free of effort." "An attitude is an individual's selfdescription of his affinities for and aversions to some identifiable aspects of his environment" (Greenwald, Brock, & Ostrom, 2013).

TAM has been extended in various researches to study the effect of other determinants in understanding customer behavior in different context. In the present study context i.e., Internet Banking (IB), apart from the Perceived Usefulness and Perceived Ease of Use, Perceived web security (PWS) is considered as one of the important determinant effecting the adoption. As many a customers expressed their concern towards security as one of the major factor in using online transactions (Salisbury, Pearson, Pearson, & Miller, 2001).

Hence the present study, considers PWS as an important predictor of intention and attitude towards use of internet banking. The study adapts the four items of PWS developed by (Salisbury et al., 2001) earlier in their study.

4. III.

5. Objectives

The main objective of the study is to investigate the behavioral intension of the customers to use Internet banking services in relation with the perceived ease of use of services, usefulness of the internet banking services, attitude and the perceived web security towards the IB services.

? To study the effect of Perceived Usefulness on the attitude towards IB services and the Intension to use the services. ? To study the Perceived Ease of Use of Internet Banking services and its effect on attitude and intension of customers to use IB services. ? To study the Perceived Web Security of the customers towards their intension to use the IB services.

IV.

6. Methodology

The study adapts a descriptive and causal research methodology to test the relationship between the TAM constructs in the adoption of IB services. To test the formulated hypotheses, the data is collected using a structured questionnaire; designed by adapting the developed scales. Perceived Usefulness (PU), Perceived Ease of Use (PEoU) and Attitude towards Use (ATU) were measured by adapting the original items developed by (Davis, 1989). These have also been used by (Bhattacherjee, 2000;Davis, Bagozzi, & Warshaw, 1989;Taylor & Todd, 1995). Intention to Use (INTU) construct items have been adapted from (Bhattacherjee, 2000;Mathieson, 1991).

The items related to Perceived Web Security (PWS) has been adapted from the scale developed by (Sathye, 1999). A five-point Likert scale is used; 1 representing "Strongly Disagree" and 5 representing "Strongly Agree".

The data is collected from students, scholars and employees of a university. A total of 400 questionnaire were distributed, out of which 362 were received and finally 340 responses were considered after eliminating the incomplete questionnaire.

V.

7. Hypothesis

The study is using TAM as the base model for the study. Further based on the theoretical model developed and the objectives of the study, the hypotheses to be tested are:

8. VI.

9. Results

10. Demographics

characteristics of the respondents is analyzed; Of the 340 respondents, 55% are male and 45% are female. 33% are between 20-30 years of age group, 38% are between 31-40 years, 20% are between 41-50 years and 9% are above 50 years of age.

Reliability and validity of the measures have been assessed before the actual testing of the hypotheses is done. All the values are adhering to the prescribed standards; and are shown in Table 1. Cronbach's alpha values for the measures are above 0.7 as per Nunnally (1991). Discriminant and Convergent validity measures of the constructs are also satisfying the standards prescribed by (Fornell & Larcker, 1981). These values for the constructs are presented in Table 1. Confirmatory Factor Analysis (CFA) was done for the sample and the results are very much in accordance with the required standard values. Model fit values for the same are shown in Table 2. The structural model is tested using SPSS AMOS 20.0. The Chi-square value of the model is 426.516 at 144 degrees of freedom and is significant at P < 0.05. Other fit indices like CFI, TLI, NFI and GFI also are well within the minimum acceptance levels i.e. > 0.90. The model fit statistics are presented in Table 3.

The relationship between the constructs is tested using the path model and the results are shown in the Figure 1. All the hypotheses H1a, H1b, H2a, H2b, H3b and H4 are supported, except the hypothesis H3a. According to the results all the hypothesized relations have a direct positive effect, however the Perceived Web Security (PWS) does not have a direct significant effect on Attitude towards Use (ATU). Hypothesis H3a is not significant is very much in line with the results of Cheng et al. (2006). As supported by (Moore & Benbasat, 1991), Attitude towards use of IT can be synthesized from the characteristics perceived of innovation (Cheng et al., 2006;Rogers, 1995). However, the hypothesis H3b is significant i.e., PWS has a positive direct effect on Intention to use, which is a powerful predictor of user behavior (Davis et al., 1989).

11. Figure 1: Structural Model with path coefficients

Note: ** is Significant at 0.01; * is Significant at 0.05; NS is Not Significant at 0.05 Attitude towards Use to Intention of the customer to Use Internet Banking is also supported. Thus, the overall results of the structural model support TAM and are consistent with the findings of (Davis et al., 1989).

12. VII.

13. Conclusion

Finally, we can conclude that Perceived Usefulness (PU) is one of the important determinant of Attitude and Intention towards the use of Internet Banking. Similarly, Perceived Ease of Use (PEoU) also determine the Attitude and Intention to Use Internet Banking Services. However, Perceived Web Security (PWS) is influencing Intention to Use and does not have a direct positive effect on attitude.

The importance of Perceived web Security (PWS) is consistent with the results of (Sathye, 1999). Web Security is one of the important concern expressed by the customers while using internet banking.

14. Perceived Web Security

The usefulness and ease of use of online banking has increased the number of customers. Welldesigned web, its functionality and user friendliness are some of the other important factors in adaptation. On the other hand, increased risk in the use of internet is posing grave challenges to the banks.

No matter how robust the service is designed and safety measures are taken up, security remains one of the major issue in the online banking today. Hence, the bankers should take the web security as the priority concern and assure the customers about the secure use of internet banking.

Figure 1. Table 1 :
1
Cronbach's Alpha CR AVE MSV ASV PWS PEOU ATU PU INTU
PWS 0.932 0.932 0.774 0.024 0.012 0.880
PEOU 0.956 0.958 0.850 0.361 0.110 0.155 0.922
ATU 0.953 0.954 0.838 0.035 0.019 0.049 0.186 0.915
PU 0.947 0.948 0.822 0.023 0.017 0.076 0.145 0.151 0.907
INTU 0.968 0.970 0.915 0.361 0.103 0.123 0.601 0.132 0.138 0.957
Figure 2. Table 2 :
2
Fit Statistic Recommended Obtained
Chi-square 289.984
df 142
CMIN/DF(Wheaton, Muthen, Alwin, & Summers, 1977) <5.0 2.042
Chi-square significance P<=0.05 0.000
GFI(JOreskog & Sorbom, 1988) >0.90 .918
NFI(Bentler & Bonett, 1980) >0.90 .962
TLI(Hu & Bentler, 1999) >0.90 .976
CFI(Bentler, 1990) >0.90 .980
RMSEA(MacCallum, Browne, & Sugawara, 1996) <.05 .055
Figure 3. Table 3 :
3
Perceived Usefulness .10*
.13*
.14** Attitude to Use .11* Intention to Use
Perceived Ease of .17**
Use
.11*
.01 NS
.16*
Fit Statistic Recommended Obtained
Chi-square 426.516
Df 144
CMIN/DF (Wheaton et al., 1977) <5.0 2.962
Chi-square significance P<=0.05 0.000
GFI (JOreskog & Sorbom, 1988) >0.90 .896
NFI (Bentler & Bonett, 1980) >0.90 .984
TLI (Hu & Bentler, 1999) >0.90 .956
CFI (Bentler, 1990) >0.90 .963
RMSEA (MacCallum et al., 1996) <.05 .076
Figure 4. Table 4 :
4
Hypothesis Standardized Regression Estimate C.R. P
H1a ATU <--- PU 0.126 2.27 0.023
H1b INTU <--- PU 0.109 2.021 0.043
H2a ATU <--- PEoU 0.168 3.011 0.003
H2b PU <--- PEoU 0.145 2.65 0.008
H3a ATU <--- PWS 0.013 0.226 0.821
H3b INTU <--- PWS 0.112 2.038 0.042
H4 INTU <--- ATU 0.112 2.046 0.041
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Appendix A

  1. Acceptance of ecommerce services: the case of electronic brokerages. A Bhattacherjee . IEEE Transactions on systems, man, and cybernetics-Part A: Systems and humans, 2000. 30 p. .
  2. Psychological foundations of attitudes, A G Greenwald , T C Brock , T M Ostrom . 2013. Academic Press.
  3. Assessing reliability and stability in panel models. B Wheaton , B Muthen , D F Alwin , G F Summers . Sociological methodology 1977. 8 (1) p. .
  4. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. C Fornell , D F Larcker . Journal of Marketing Research (JMR) 1981. 18 (1) p. .
  5. Diffusion of Innovations, E Rogers . 1995. Sept. 2001. New York: ACM the Free Press. p. . (4th Eds.)
  6. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. F D Davis . 10.2307/249008. MIS Quarterly 1989. 13 (3) p. .
  7. User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. F D Davis , R P Bagozzi , P R Warshaw . 10.2307/2632151. Management Science 1989. 35 (8) p. .
  8. Development of an instrument to measure the perceptions of adopting an information technology innovation. G C Moore , I Benbasat . Information systems research 1991. 2 (3) p. .
  9. Belief, attitude, intention and behavior: An introduction to theory and research, I Ajzen , M Fishbein . 1975. Reading, MA: Addison-Wesley.
  10. Internet banking growth and satisfaction outstrips other channels, http://www.roymorgan.com/findings/6494-internet-banking-growth-and-higher-satisfaction 2015. 10/05/2016. august-2015-201510112259.
  11. Psychometric Theory, J C A B Nunnally , IH . 1991. New York, NY: McGraw.
  12. LISREL 7: A guide to the program and its applications, K G Joreskog , D Sorbom . 1988. Chicago: SPSS Inc.
  13. Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. K Mathieson . Information systems research 1991. 2 (3) p. .
  14. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. L T Hu , P M Bentler . 10.1080/107055199. Structural Equation Modeling: A Multidisciplinary Journal 1999. 6 (1) p. .
  15. Adoption of Internet banking by Australian consumers: an empirical investigation. M Sathye . International Journal of bank marketing 1999. 17 (7) p. .
  16. Why do people use information technology? A critical review of the technology acceptance model. P Legris , J Ingham , P Collerette . Information & Management 2003. 40 (3) p. .
  17. Significance tests and goodness of fit in the analysis of covariance structures. P M Bentler , D G Bonett . Psychological bulletin 1980. 88 (3) p. 588.
  18. Comparative fit indexes in structural models. P M Bentler . Psychological bulletin 1990. 107 (2) p. 238.
  19. Power analysis and determination of sample size for covariance structure modeling. R C Maccallum , M W Browne , H M Sugawara . Psychological Methods 1996. 1 (2) p. 130.
  20. Internet Banking Adoption in an Emerging Economy: Indian Consumer's Perspective. R Safeena , H Date , A Kammani . Int. Arab J. e-Technol 2011. 2 (1) p. .
  21. Understanding Internet banking adoption and user behavior: A Hong Kong perspective, S Chan , M Lu . 2004.
  22. The impact of trust and perceived risk on internet banking adoption in India: An extension of technology acceptance model. S K Roy , A Kesharwani , S Singh Bisht . International Journal of bank marketing 2012. 30 (4) p. .
  23. Assessing IT usage: The role of prior experience. S Taylor , P Todd . MIS Quarterly 1995. p. .
  24. Adoption of internet banking: an empirical study in Hong Kong. T E Cheng , D Y Lam , A C Yeung . Decision support systems 2006. 42 (3) p. .
  25. The Growth of Online Banking, http://wwwmetrics.com/banking.htm 2013. 10/06/2016.
  26. Consumer acceptance of online banking: an extension of the technology acceptance model. T Pikkarainen , K Pikkarainen , H Karjaluoto , S Pahnila . Internet research 2004. 14 (3) p. .
  27. Perceived security and World Wide Web purchase intention. W D Salisbury , R A Pearson , A W Pearson , D W Miller . Industrial Management & Data Systems 2001. 101 (4) p. .
  28. Online banking adoption: an empirical analysis. Yee-Loong Chong , A Ooi , K.-B Lin , B Tan , B.-I . International Journal of bank marketing 2010. 28 (4) p. .
Notes
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Date: 2017-01-15