CUSTOMER PREFERENCE TOWARDS TECHNOLOGY ENABLED BANKING SELF SERVICES WITH SPECIAL REFERENCE TO COIMBATORE CITY

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1 CUSTOMER PREFERENCE TOWARDS TECHNOLOGY ENABLED BANKING SELF SERVICES WITH SPECIAL REFERENCE TO COIMBATORE CITY K.Gokila Research Scholar, School of Commerce, Rathnavel Subramaniam College of Arts and Science, Sulur, Coimbatore. Dr.P.Rajini Research Head & Associate Professor, School of Commerce, Rathnavel Subramaniam College of Arts and Science, Sulur, Coimbatore. ABSTRACT The banking system is taken into account as a service familiarized business. It renders manifold services to the purchasers through different Self-Service Technology (SST)-enabled between bankers and customers. The purpose of the study is, to customer preferences towards technology enabled banking self services with special reference to Coimbatore city. The Main objective of the study is, to know the customer preference towards technology enabled banking self services. For the purpose five hundred respondents were selected using convenient random sampling. Key Words: ATM, Mobile Banking, Self-Service 1.1. INTRODUCTION Technology-enabled banking services offer value to the customers, providing them with anywhere, anytime and anyway banking. Though these technological changes have been pioneered in India by new private sector and foreign banks, now such a situation has reached where even the traditional banks in the public sector and old private banks are increasingly pursuing technology-enabled services. All banks in India have realized in the post-liberalization era that, in order to remain competitive and provide the best services to their customer s, they need to have the latest technology in place. Irrespective of their ownership status (public sector or private sector), almost all of them have given maximum importance to technological development and deployment. ATMs, plastic money, online collection and payment services, electronic fund transfer and clearing services, mobile ATMs, document management systems, smart cards, core banking solutions, branch networking and internet banking are all outcomes of their initiative of technological up gradation (Upadhyay, 2007). In banking, in the past, the technology strategy was considered as subordinate to business strategy. But now with so much advancement in technology it has become as important as business strategy. Technology has provided an altogether new way of interacting and provides excellent service to bank customers rather than merely replicating activities of the bank employees (Godse, 2005). The focus of this research is on technologies that customers independently use for banking without any interaction with or assistance from employees. They are termed as Self- Service Technologies or SSTs (Meuter, M.L et al., 2000).The modes of banking transactions using technology-enabled selfservices, have great potential to benefit both the customers as well as the banks. The Technology-Enabled Banking Self-Services covered under this study include Automated Teller Machines (ATMs), Internet banking, Telephone banking and Mobile banking. Persuading customers to use new technologies in service encounters is generally more challenging than employees use of new technologies as far as banks are concerned. In the delivery of the services, since technology can replace a firm s employees, the use of technology is immensely beneficial to the service provider that, it can standardize service delivery, reduce labor costs and expand the options for provisioning of services. On the other hand it could be wastage of resources if not widely accepted by customers. Thus, it is essential that we find out best ways to design, manage and promote new technologies in order to have the 63

2 best chance of customers acceptance (Curran and Meuter, 2005). The introduction of technology-enabled banking service delivery probably started off with HSBC bank introducing ATM for the first time in India way back in 1987 (N. Thamaraiselvan and J.Raja, 2007). Internet banking was introduced in India in 1996 by ICICI bank with the launch of infinity (Rajneesh De and Padmanabhan, 2002). Even though these electronic delivery channels were introduced by foreign banks and new private banks in order to surmount their limitation of fewer branches, of late even the public sector banks are aggressively investing in these services. So the action in this field really got heated up during the last 5-6 years. This thrust on computerization and automation has led to massive investments in the banking sector in India. For instance as on March 31st, 2005, public sector banks in India had incurred an expenditure of Rs 9,487 crores on computerization and development of communication network (Manoharan), 1.2. STATEMENT OF THE PROBLEM The present study has been carried out to examine the above enquires and offer solutions. Although banking self services may help banks to reduce costs, Technology-based self-service has greatly changed the way business firms and customers interact with their bankers. Moreover, modern day customers feel that it both time consuming costly and unsafe when dealing with branch banks. So they prefer to utilize more banking services like: internet banking, RTCGs services, core banking, and mobile banking and ATM facilities. Technology based services offered by banks highly facilitate them to solve their banking financial problems without moving from their premises either office or home. But, so far, less literature, survey and empirical research work has been conducted in the past that has analyzed the banking customers perception and utilization pattern of banking services. Banking Industry is facing a challenge in change of service delivery, adding more alternative channel for distributing their services with better and the best service standards compared to other industry OBJECTIVE OF THE STUDY The primary objective of the research is 1. To analysis the level of customer preference towards technology enabled banking self services offered by bank SCOPE OF THE STUDY The study has been undertaken mainly to highlight the customer preferences towards technology enabled banking self services. The study is confined to Coimbatore city. The sample respondents are the customers of various selected banks in Coimbatore city METHODOLOGY & RESEARCH DESIGN Methodology is the backbone of the research programme. It directs the researcher to conduct the research in a systematic process which enables the out coming with accuracy. Hence it is mandatory to adopt a right mode of study to derive the conclusion with result Data collection The study has used only primary data. They data has been collected from various private sector banks in Coimbatore city and very few data was collected from secondary sources like newspapers, magazines, journals, books and websites etc Sample size and techniques The sample size restricted to 500 customers in various private sector banks in Coimbatore city. A convenient random sampling technique has been used for this study Statistical tools used. *Reliability analysis. *Factor analysis LIMITATION OF THE STUDY This is an empirical study on the Value Added facilities provided by the private sector Banks in Coimbatore city. Value-Added services have gained greater importance in modern days. Undoubtedly the results and finding of the study can be applied directly to any other areas. Due to limitations of time and money consideration, the sample size has been restricted to 750 customers. Many respondents have been unable to provide proper answer with insight due to lack of knowledge about the new concept of value Added service. 1.7.ANALYSIS AND INTERPRETATION DIMENSIONALITY OF THE MULTI-SCALE ITEMS Factor Analysis is a set of technique which by analyzing correlations between variables reduces their numbers into fewer factors which explain much of the original data, more economically. Even though a subjective interpretation can result from a factor analysis output, the procedure often provides an insight into relevant psychographic variables, and results in economic use of data collection efforts. The subjective element of factor analysis is reduced by splitting the sample randomly into two and extracting factors separately from both parts. If similar factors result, the analysis is assumed as reliable or stable 1. 1 Nargundkar, Rajendra, Marketing Research- Text and Cases, Tata McGraw Hill, New Delhi, 2nd Ed-2003, 64

3 TABLE -1 KMO AND BARTLETT S TEST FOR PREFERENCE TOWARDS TECNOLOGY ENABLED BANKING SELF SERVICES Kaiser- Meyer- Olkin Measure of Sampling Adequacy Bartlett s Test of Sphericity: Approx. Chi- Square Sig 0.00** S/NS Cronbach's Alpha S S-Significant P<0.05 In the above table, two tests namely, Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) and Bartlett s Test of Sphericity have been applied to test whether the relationship among the variables has been significant or not. The Kaiser-Meyer- Olkin Measure of sampling adequacy shows that the value of test statistics is 0.836, which means the factor analysis for the selected variable is found to be appropriate or good to the data. Bartlett s test of sphericity is used to test whether the data are statistically significant or not with the value of test statistics and the associated significance level. It shows that there exists a high relationship among variables. TABLE 2. EIGEN VALUES AND PROPORTION OF TOTAL VARIANCE OF EACH UNDERLYING PREFERENCE TOWARDS TECNOLOGY ENABLED BANKING SELF SERVICES Initial Eigen values component Total % of Variance Cumulative % Extraction Sums of Squared Loadings Total % of Variance Cumulative % Rotation Sums of Squared loadings Total % of Variance Cumulative % Pp

4 Extraction Method: Principal Component Analysis The results of the factor analysis presented in the table 2 regarding factors related to preference towards technology enabled banking self services, have revealed that there are nineteen factors that had Eigen value exceeding one. Among those four factors, the first factor accounted for per cent of the variance, the second per cent and the third factor per cent of the variance in the data set. The first three factors are the final factors solution and they all together represent per cent of the total variance in the scale items measuring the factors related to preference towards technology enabled banking self services. Hence from the above results, it is certain that there are factors related to preference towards technology enabled banking self services. TABLE ---3 COMMUNALITIES FOR FACTORS RELATED TO CUSTOMERS PREFERENCE TOWARDS TECNOLOGY ENABLED BANKING SELF SERVICES S.NO. ITEMS Initial Extraction (h 2 ) 1 Convenient.759 accessibility 2 Convenient location of.762 ATMs 3 Reputation of the bank More facilities.571 provided by e-channels 5 Online shopping.614 Facilities 6 Security and less risk Low hidden cost Savings in Time Online bill payment Checking balance.548 online 11 E- Ticketing Booking Download bank.596 transaction history 13 Applying for customer.552 loan and others 14 Any where banking.693 facilities 15 Accurate information Efficient services.810 The above table (Communalities) represents the application of the Factor Extraction Process, it was performed by Principal Component Analysis to identify the number of factors to be extracted from the data and by specifying the most commonly used Varimax rotation method. In the principal component analysis, the total variance in the data is considered. The proportion of the variance is explained by the fourteen factors in each variable. The proportion of variance is explained by the common factors called communalities of the variance. Principal Component Analysis works on initial assumption that all the variance are common. Therefore, before extraction the communalities are all. Then the most common approach for determining the number of factors to retain i.e., examining Eigen values was done. 66

5 TABLE 4 ROTATED COMPONENT MATRIX FOR PREFERENCE TOWARDS TECNOLOGY ENABLED BANKING SELF SERVICES Variable Component code I II III X X X X X X X X X X X X X X X X Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation converged in 4 iterations. Table 4 represents the Rotated Component Matrix, which is an important output of principal component analysis. The coefficients are the factor loadings which represents the correlation between the factors and the sixteen variables (X 1 to X 16 ). From the above factor matrix it is found that coefficients for factor-i have high absolute correlations with variable X 2 (Convenient location of ATMs), X 1 ( Convenient accessibility), X 5 (Online shopping), X 8 (Savings in Time), X 4 (more facilities provided by e- channels), X 3 (Reputation of the bank), X 9 (Online bill payment), X 6 (Security/less risk), and X 7 (Low hidden cost) that is, 0.855, 0.843, 0.780, 0.759, 0.752, 0.731, 0.688, and0.669 respectively. Similarly factor-ii has high absolute correlation with variable X 12 (Download bank transaction history), X 13 (Applying for customer loan), X 10 (Checking balance online), X 14 (Any where banking facilities) and X 11 (E- Ticketing), that is, 0.762, 0.736, 0.734, and respectively. Next, factor III has high absolute correlation with variable X 15 (Provides accurate information) and X 16 (Provides efficient services) that is, and respectively. For example in this study, factor one is at least somewhat correlated with all variable out of the sixteen variables with absolute value of factor loading greater than or equal to 0.5. In such a complex matrix it is difficult to interpret the factor. So we proceed to compute the rotated factor matrix. TABLE 5 Component Transformation Matrix Component The above table reveals that if the factor correlation matrix factors are uncorrelated among themselves, then in the factor correlation matrix, the diagonal elements will be 1 s and off diagonal elements will be 0 s. Since matrix was rotated with Varimax, barring some variables all other variables are found to have, even if not zero correlations alteast fairly low correlation. 67

6 Component 2 CHART -1 Component Plot in Rotated Space 1.0 q20.13 q20.12 q q20.14 q20.15 q20.16 q20.11 q20.7 q20.3 q20.6 q20.8 q20.9 q20.5 q20.4 q20.1 q Component Component CONCLUSION The study reveals that there are vast opportunities as well as challenges for technology based self services provided by banks in India. It is found that due to technological innovations and significant change in demographic profile of customers, there is huge market potential lying ahead. The study concluded that Convenient location of ATMs, Convenient accessibility, Online shopping, lot of facilities provided by e-channels, Reputation of the bank, Savings in Time and Online bill payment are the reasons that most customers prefer technology enabled banking self services, Which helps and develops the mutual benefit of both the bank and customer. REFERENCES BOOKS 1. Nargundkar, Rajendra, Marketing Research- Text and Cases, Tata McGraw Hill, New Delhi, 2nd Edition-2003, pp Dr.S.P. Gupta, Statistical Methods, Sultan Chand & Sons Educational Publishers, New Delhi Malhotra, Naresh K., and Marketing Research: An applied Orientation, Addison Wesley Longman (Singapore) P. Ltd., New Delhi, Edition Luck, David J., and Rubin, Ronald S., Marketing Research, Prentice-Hall of India Private Limited, New Delhi, Edition Saveeta Saggar, Commercial Banks in India, Deep & Deep Publications Pvt Ltd, New Delhi C.R. Kothari. Research Methodology Methods and Techniques. New Age International (P) Ltd., publishing New Delhi. Edition Dr.G.P.Kapoor, Commercial Banking, A.P.H. Publishing Corporation, New Delhi-2, Ed.2004, pp Garrett, Henry E. 1973, Statistics in Psychology and Education, Vakils, Feffer and Simsons, Bombay, Edition JOURNALS 1. Banks offer Value added services to their customers, The Journal of Indian Institute of Banking and Finance- 2006, pp