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\title{Adoption of Internet Banking Services in India: An Empirical Study}
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\begin{document}

             \author[1]{Samala  Nagaraj}

             \author[2]{Dr. Sapna  Singh}

             \affil[1]{  University of Hyderabad}

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\date{\small \em Received: 13 December 2016 Accepted: 2 January 2017 Published: 15 January 2017}

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\begin{abstract}
        


Understanding the adoption of a new technology is an essential process to determine its uses and future advancements. This study aims at investigating the adoption of such similar technology i.e., Internet Banking (IB). The study adapted the Technology Acceptance Model (TAM) and Perceived Web Security (PWS) construct to understand the adoption of IB services in India. Perceived Usefulness (PU) and Perceived Ease of Use (PEoU) are considered as the two main determinants to evaluate the Attitude towards Use (ATU) and Intention to Use (INTU) internet banking services. A well-designed questionnaire is used and 340 responses were collected to empirically test the hypothesized relations of the theoretical model developed. The relationship between the constructs are tested using Structural Equation Modelling. The extended model of TAM once again confirmed the role of PU and PEoU in affecting the attitude and intention to use IB services. All the hypothesis were significant except the effect of PWS on attitude towards use of IB services.

\end{abstract}


\keywords{technology acceptance model, internet banking, perceived web security, structural equation modelling.}

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\let\tabcellsep& 	 	 		 
\section[{Introduction}]{Introduction}\par
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.\par
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.\par
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.\par
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. 
\section[{II.}]{II.} 
\section[{Review of Literature}]{Review of Literature}\par
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 \hyperref[b5]{(Cheng, Lam, \& Yeung, 2006)}. Extension of TAM to study the adoption of internet banking services; especially in India are significantly less till date.\par
Technology Acceptance Model (TAM) by \hyperref[b6]{(Davis, 1989)}, which was based on the Theory of Reasoned Action (TRA) by \hyperref[b0]{(Ajzen \& Fishbein, 1975)}, has proposed two important determinants to study the adoption of new technology \hyperref[b12]{(Legris, Ingham, \& Collerette, 2003)}. The model has been widely used in various contexts to study the behavioral intention.\par
According to  {\ref (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" \hyperref[b9]{(Greenwald, Brock, \& Ostrom, 2013)}.\par
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 \hyperref[b22]{(Salisbury, Pearson, Pearson, \& Miller, 2001)}.\par
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 \hyperref[b22]{(Salisbury et al., 2001)} earlier in their study. 
\section[{III.}]{III.} 
\section[{Objectives}]{Objectives}\par
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.\par
? 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.\par
IV. 
\section[{Methodology}]{Methodology}\par
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 \hyperref[b6]{(Davis, 1989)}. These have also been used by \hyperref[b3]{(Bhattacherjee, 2000;}\hyperref[b7]{Davis, Bagozzi, \& Warshaw, 1989;}\hyperref[b24]{Taylor \& Todd, 1995)}. Intention to Use (INTU) construct items have been adapted from \hyperref[b3]{(Bhattacherjee, 2000;}\hyperref[b14]{Mathieson, 1991)}.\par
The items related to Perceived Web Security (PWS) has been adapted from the scale developed by \hyperref[b23]{(Sathye, 1999)}. A five-point Likert scale is used; 1 representing "Strongly Disagree" and 5 representing "Strongly Agree".\par
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.\par
V. 
\section[{Hypothesis}]{Hypothesis}\par
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:  
\section[{VI.}]{VI.} 
\section[{Results}]{Results} 
\section[{Demographics}]{Demographics}\par
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.\par
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 \hyperref[tab_0]{1}. Cronbach's alpha values for the measures are above 0.7 as per \hyperref[b17]{Nunnally (1991)}. Discriminant and Convergent validity measures of the constructs are also satisfying the standards prescribed by \hyperref[b8]{(Fornell \& Larcker, 1981)}. These values for the constructs are presented in Table \hyperref[tab_0]{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 \hyperref[tab_1]{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 \hyperref[tab_2]{3}.\par
The relationship between the constructs is tested using the path model and the results are shown in the Figure  {\ref 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 \hyperref[b5]{Cheng et al. (2006)}. As supported by \hyperref[b16]{(Moore \& Benbasat, 1991)}, Attitude towards use of IT can be synthesized from the characteristics perceived of innovation \hyperref[b5]{(Cheng et al., 2006;}\hyperref[b19]{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 \hyperref[b7]{(Davis et al., 1989)}. 
\section[{Figure 1: Structural Model with path coefficients}]{Figure 1: Structural Model with path coefficients}\par
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 \hyperref[b7]{(Davis et al., 1989)}. 
\section[{VII.}]{VII.} 
\section[{Conclusion}]{Conclusion}\par
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.\par
The importance of Perceived web Security (PWS) is consistent with the results of \hyperref[b23]{(Sathye, 1999)}. Web Security is one of the important concern expressed by the customers while using internet banking.   
\section[{Perceived Web Security}]{Perceived Web Security}\par
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.\par
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.   \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.05250965250965251\textwidth}P{0.13455598455598455\textwidth}P{0.0886100386100386\textwidth}P{0.0918918918918919\textwidth}P{0.0918918918918919\textwidth}P{0.0918918918918919\textwidth}P{0.0918918918918919\textwidth}P{0.07876447876447876\textwidth}P{0.059073359073359075\textwidth}P{0.03938223938223938\textwidth}P{0.029536679536679537\textwidth}}
\tabcellsep Cronbach's Alpha\tabcellsep CR\tabcellsep AVE\tabcellsep MSV\tabcellsep ASV\tabcellsep PWS\tabcellsep PEOU\tabcellsep ATU\tabcellsep PU\tabcellsep INTU\\
PWS\tabcellsep 0.932\tabcellsep 0.932\tabcellsep 0.774\tabcellsep 0.024\tabcellsep 0.012\tabcellsep 0.880\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
PEOU\tabcellsep 0.956\tabcellsep 0.958\tabcellsep 0.850\tabcellsep 0.361\tabcellsep 0.110\tabcellsep 0.155\tabcellsep 0.922\tabcellsep \tabcellsep \tabcellsep \\
ATU\tabcellsep 0.953\tabcellsep 0.954\tabcellsep 0.838\tabcellsep 0.035\tabcellsep 0.019\tabcellsep 0.049\tabcellsep 0.186\tabcellsep 0.915\tabcellsep \tabcellsep \\
PU\tabcellsep 0.947\tabcellsep 0.948\tabcellsep 0.822\tabcellsep 0.023\tabcellsep 0.017\tabcellsep 0.076\tabcellsep 0.145\tabcellsep 0.151\tabcellsep 0.907\tabcellsep \\
INTU\tabcellsep 0.968\tabcellsep 0.970\tabcellsep 0.915\tabcellsep 0.361\tabcellsep 0.103\tabcellsep 0.123\tabcellsep 0.601\tabcellsep 0.132\tabcellsep 0.138\tabcellsep 0.957\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.6100600600600601\textwidth}P{0.11741741741741742\textwidth}P{0.12252252252252252\textwidth}}
Fit Statistic\tabcellsep Recommended\tabcellsep Obtained\\
Chi-square\tabcellsep \tabcellsep 289.984\\
df\tabcellsep \tabcellsep 142\\
CMIN/DF(Wheaton, Muthen, Alwin, \& Summers, 1977)\tabcellsep <5.0\tabcellsep 2.042\\
Chi-square significance\tabcellsep P<=0.05\tabcellsep 0.000\\
GFI(JOreskog \& Sorbom, 1988)\tabcellsep >0.90\tabcellsep .918\\
NFI(Bentler \& Bonett, 1980)\tabcellsep >0.90\tabcellsep .962\\
TLI(Hu \& Bentler, 1999)\tabcellsep >0.90\tabcellsep .976\\
CFI(Bentler, 1990)\tabcellsep >0.90\tabcellsep .980\\
RMSEA(MacCallum, Browne, \& Sugawara, 1996)\tabcellsep <.05\tabcellsep .055\end{longtable} \par
 
\caption{\label{tab_1}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.5364077669902912\textwidth}P{0.06189320388349514\textwidth}P{0.11140776699029126\textwidth}P{0.10728155339805825\textwidth}P{0.033009708737864074\textwidth}}
Perceived Usefulness\tabcellsep \tabcellsep .10*\tabcellsep \\
\tabcellsep .13*\tabcellsep \tabcellsep \\
.14**\tabcellsep \multicolumn{2}{l}{Attitude to Use}\tabcellsep .11*\tabcellsep Intention to Use\\
Perceived Ease of\tabcellsep .17**\tabcellsep \tabcellsep \\
Use\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep .11*\tabcellsep \\
\tabcellsep .01 NS\tabcellsep \tabcellsep \\
.16*\tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Fit Statistic}\tabcellsep Recommended\tabcellsep Obtained\\
Chi-square\tabcellsep \tabcellsep \tabcellsep 426.516\\
Df\tabcellsep \tabcellsep \tabcellsep 144\\
\multicolumn{2}{l}{CMIN/DF (Wheaton et al., 1977)}\tabcellsep <5.0\tabcellsep 2.962\\
\multicolumn{2}{l}{Chi-square significance}\tabcellsep P<=0.05\tabcellsep 0.000\\
\multicolumn{2}{l}{GFI (JOreskog \& Sorbom, 1988)}\tabcellsep >0.90\tabcellsep .896\\
\multicolumn{2}{l}{NFI (Bentler \& Bonett, 1980)}\tabcellsep >0.90\tabcellsep .984\\
\multicolumn{2}{l}{TLI (Hu \& Bentler, 1999)}\tabcellsep >0.90\tabcellsep .956\\
CFI (Bentler, 1990)\tabcellsep \tabcellsep >0.90\tabcellsep .963\\
\multicolumn{2}{l}{RMSEA (MacCallum et al., 1996)}\tabcellsep <.05\tabcellsep .076\end{longtable} \par
 
\caption{\label{tab_2}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4} \par 
\begin{longtable}{P{0.10537190082644628\textwidth}P{0.08078512396694215\textwidth}P{0.09834710743801653\textwidth}P{0.0737603305785124\textwidth}P{0.2353305785123967\textwidth}P{0.1299586776859504\textwidth}P{0.12644628099173555\textwidth}}
Hypothesis\tabcellsep \tabcellsep \tabcellsep \tabcellsep Standardized Regression Estimate\tabcellsep C.R.\tabcellsep P\\
H1a\tabcellsep ATU\tabcellsep <---\tabcellsep PU\tabcellsep 0.126\tabcellsep 2.27\tabcellsep 0.023\\
H1b\tabcellsep INTU\tabcellsep <---\tabcellsep PU\tabcellsep 0.109\tabcellsep 2.021\tabcellsep 0.043\\
H2a\tabcellsep ATU\tabcellsep <---\tabcellsep PEoU\tabcellsep 0.168\tabcellsep 3.011\tabcellsep 0.003\\
H2b\tabcellsep PU\tabcellsep <---\tabcellsep PEoU\tabcellsep 0.145\tabcellsep 2.65\tabcellsep 0.008\\
H3a\tabcellsep ATU\tabcellsep <---\tabcellsep PWS\tabcellsep 0.013\tabcellsep 0.226\tabcellsep 0.821\\
H3b\tabcellsep INTU\tabcellsep <---\tabcellsep PWS\tabcellsep 0.112\tabcellsep 2.038\tabcellsep 0.042\\
H4\tabcellsep INTU\tabcellsep <---\tabcellsep ATU\tabcellsep 0.112\tabcellsep 2.046\tabcellsep 0.041\end{longtable} \par
 
\caption{\label{tab_3}Table 4 :}\end{figure}
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