Keywords

Bank Selection Process, Retail Banking, Factor Analysis, Determinants of Banking, Bank Marketing.

Introduction

Indian banking system is comprised of 27 public, 26 private, 46 foreign, 56 regional rural, 1,574 urban cooperatives and 93,913 rural cooperative banks along with cooperative credit institutions. More than 70 per cent of the banking system assets are controlled by Public-sector banks leaving a smaller share for private banks comparatively. Indian banking sector is satisfactorily capitalised and well-regulated as per the Reserve Bank of India (RBI). Indian banks have been considered resilient and have endured the global depression well as suggested by credit, market and liquidity risk studies (Banking sector in India, 2017, IBEF). Financial Products or Instruments are basically documents evidencing transfer of funds from the saving community, where it can be gainfully employed, on certain predetermined terms and conditions such as rate of return, repayment schedule, liquidity and benefits etc. High involvement of the customer during the purchase of the financial products and the existence of complex financial products will generally take a long time to plan the purchase of financial products / services in India. High levels of brand equity also exist in the market. The characteristics of retail banking services are as follows:

High Involvement: Some of the financial services like investment banking or portfolio management of debentures, shares and mutual funds involve high involvement purchases. The customers take the best advice or the best offer and will generally take a long time to buy the product.

Brand Loyalty: Most of the customers tend to stay with financial service providers and use them to satisfy their different needs at various stages in lifecycle. ICICI bank advertises about their services to meet a whole lifetime needs from a first-time mortgage and household insurance for family protection, savings and pensions for old age.

Wireless banking: Bank branches have moved from being primary service-oriented to sales and service outlets with the focus on cross selling. It is necessary that the information be standardized across all branches and other direct channels like ATM, Tele banking, Mobile banking throughout the country.

Database: After any time banking, anywhere banking is popularized. For this facility, first step is to create a data warehouse that would eliminate the time consuming. Now, the bank can know how many products a particular customer avails of, how frequently uses the product, transaction characteristics and his banking behavior.

Consumer as an individual: For products such as deposits, company fixed deposits, UTI units, company shares and debentures, LIC policy, provident fund, consumer durable loan, credit cards, customer can be viewed only as individuals.

Consumer as a Corporate Entity: For long term loan from financial institutions, working capital loan from commercial banks, inter-corporate deposits equity by way of shares/debentures etc. The larger the bank, usually it is more difficult is for them react to individual needs.

Review of Literature

Customer satisfaction is an important theoretically as well as practically for the marketers and consumer researchers. A number of studies are available on service quality and level of satisfaction both in India and abroad. A brief the review of these related studies have been made in this section to identify the necessity of the study. The Government of India appointed a working group on customer service in banks under the Chairmanship of (Talwar, 1977). The committee submitted its final report in 1977 in which 176 recommendations were made to improve the customer service.

Kant & Jaiswal (2016) conducted an empirical study to investigate perceived service quality dimensions and its impact on customer satisfaction in the National Capital Region (NCR) of India. Scholars identified six perceived service quality dimensions named as tangibility, assurance, responsiveness, reliability, empathy, and image. They concluded that the most important predictor of satisfaction was “responsiveness”. Al Khulaifi et al. (2005) found in their study that the satisfaction levels of retail bank customers depend on services and facilities provided in the bank. Rust & Zahorik (1993) suggested that staff behaviour and their attitude is very important for a retail bank in order to provide maximum customer satisfaction.

Rao (1994) made a study of marketing of services in commercial banks with special emphasis on the marketing operations of Andhra Bank and observed that the banks made significant changes in the product, price, place, and promotion strategies to reach the target market more effectively. A similar study was also conducted by Saxena (1992) to review the marketing strategies of State Bank of India and have concluded that the bank is ahead of other public sector banks in adopting new technology to improve their products in order to enhance their satisfaction of their customers.

Kansal & Singh (2007) studied the customers orientations towards banking services in urban areas of Punjab particularly the innovative services to the customers of some private banks viz, HDFC bank, ICICI bank and Bank of Punjab. Khan & Mahapatra (2008) studied the customer's satisfaction in the Indian banking sector and have inferred that the satisfaction of customers with the services of Indian banks is linked with the performance of banks.

Anada & Davesh (2018) in their study identified that reliability, responsiveness and assurance is very important factors the drive the customers towards retail banks and customer satisfaction. Antonella & Nathalie (2016) identified that customer experience and solving customer complaints are the determinants that drive the customers towards retail banks. Madhavi & Sanjai (2018) determined that personal touch that drives the customers towards the retail banking. Mohamed (2019) identified that reputation degree of religiosity, advertising, consumer knowledge and costs that drive customers towards retail bank. Neena et al. (2016) found that consumer trust and commitment loyalty and advocacy are the determinants of retail banking for customer patronage. Anna et al., (2020) explored those proximity and customer experiences that drive the customers towards retail banking. Pratap & Sujoy (2013) found that customer satisfaction and service recovery are the determinants customer patronage for retail banking. Gera (2011) explored that service quality, behavioural Intentions, value and satisfaction are important determinants for customer motivation for retail banking.

Gronroos (1982) suggested that service quality stems from a comparison of customers expectations with seller's actual service performance. Parasuraman et al. (1985) reinforced the idea that service quality is a function of customers' expectations and performance gap. Several authors have also articulated different attributes that the customers use as criteria in evaluating bank outlets as given in the Table 1.

Table 1 Review of Literature on Determinants of Bank Selection
S.No.	Researcher(s)	Determinants of bank outlet selection
1	Johnston (1995)	Flexibility, Friendliness, Functionality, Aesthetics, Cleanliness, Comfort, Communication, Competence, Courtesy, Integrity, Reliability.
2	Zeithaml et al. (1996)	System availability, Privacy, Responsiveness, Efficiency, Fulfillment, , Compensation
3	Joseph et al. (1999)	Efficiency, Queue management, Convenience, Accuracy, Feedback/complaint management.
4	Jun & Cai (2001)	Continuous improvement, ease of use, timeliness, Aesthetics, Reliability, Responsiveness, Competence, Courtesy, Credibility, Access, Communication, Understanding the customer,.
5	Yang et al. (2004)	Product portfolio, Reliability, Responsiveness, Competence, Ease of use, Empathy.
6	Loonam & O‟Loughlin (2008)	Responsiveness, Security, Tangibles, Privacy Perceived usefulness, Ease of use, Reliability.
7	Wu et al. (2008)	Privacy, Compensation, Responsiveness, Efficiency, Reliability, Contact.
8	Khan et al. (2009)	Efficiency, Responsiveness, Reliability, Accessibility, User friendliness, Privacy/security.
9	Sadeghi & Farokhian (2011)	Security, Usefulness, Bank image, Convenience, Accessibility, Accuracy.
Source: Review of Literature

The most common determinants are identified from the review of literature and presented in the Table 2 which are considered as variables to conduct this empirical study.

Table 2 Selected Determinants of Retail Banking Outlet Choice
S.No.	Determinants	Author(s)
1	Friendliness	Johnston (1995)
2	Aesthetics	Johnston (1995)
3	Cleanliness	Johnston (1995)
4	Reliability	Johnston (1995)
5	Queue management	Joseph et al. (1999)
6	Accuracy	Joseph et al. (1999)
7	Feedback/complaint management	Joseph et al. (1999)
8	ease of use	Jun & Cai (2001)
9	Credibility	Jun & Cai (2001)
10	System availability	Zeithaml et al. (2002)
11	Efficiency	Zeithaml et al. (2002)
12	Responsiveness	Zeithaml et al. (2002)
13	Product portfolio	Yang et al. (2004)
14	Competence	Yang et al. (2004)
15	Empathy	Yang et al. (2004)
16	Tangibles	Loonam & O‟Loughlin (2008)
17	Security	Loonam & O‟Loughlin (2008)
18	Privacy	Wu et al. (2008)
19	Compensation	Wu et al. (2008)
20	Contact	Wu et al. (2008)
21	Accessibility	Khan et al. (2009)
22	Usefulness	Sadeghi & Farokhian (2011)
23	Bank image	Sadeghi & Farokhian (2011)
24	Convenience	Sadeghi & Farokhian (2011)
Source: Review of Literature

Research Gap

A good number of studies are available in retail banking domain but those studies are only concentrated either on customer expectations or satisfactions/perceptions of banking customers. But the studies that discuss the determinants which drive the customers towards a particular bank outlet are missing. During customer decision making process, a customer considers a number of retail banks to consume services. But after evaluating various banks basing on certain decision attributes, the customer selects only a bank for banking. This study concentrates on those decision attributes that make customer to choose the retail bank. The study will address the following research questions.

Research Questions

1. What are the determinants of customer patronage towards selection and usage of retail bank outlets?

2. What are the customer expectations towards the retail banking services?

3. How is the behaviour of banking consumers while selecting and performing banking services?

Objectives of the Study

The basic purpose of the study is to identify the determinants of patronage of customers while selecting a retail banking outlet. The study attempts to identify the determinants with respect to the decision making process of selecting a bank. The determinants are evaluated by adopting multivariate analysis tools like factor analysis to determine most influencing determinants of electronic shopping store selection, thereby propose the bankers to concentrate on the most significant determinants identified after performing factor analysis for data reduction. The specific objectives of the study are:

1. To identify the determinants of banking outlet selection by retail customers.

2. To record and analyse customer expectations on the determinants of bank choice.

3. To evaluate the determinants basing on customer expectations, thereby identifying most influencing determinants of customer patronage for bank outlet selection.

4. To recommend the bankers to concentrate on the most influencing determinants for better banking performance.

Research Design

This empirical study used both quantitative and qualitative data to identify most influencing drivers of bank outlet selection. The study is primarily based on primary data. The primary data is collected from 600 retail banking customers after confirming that they performed banking transactions. The study aimed at recording the expectations of the retail banking customers on identified attributes of banking. A structured questionnaire is designed in such a way that it captures the expectations of retail banking customers.

Sampling technique: Purposive Sampling, Sample Size: 600, Study Area: Visakhapatnam, Data Collection Instrument: A structured questionnaire.

Profile of the Study Area: (Source: Aponline.gov.in - Official Government website of Visakhapatnam). Visakhapatnam is one of the North Coastal districts of Andhra Pradesh state of India and it lies between 17o-15' and 18o-32' Northern latitude and 18o-54' and 83o-30' in Eastern longitude. The population of the district is 4.28 millions as per 2011 Census and this constituted 5.0 percent of the population of the state while the Geographical area of the District is 11161 Sq. Kms, which is only 4.1 percent of the area of the State. Out of the total population 2.140 millions are Males and 2.147 millions are Females. The Urban population is 3.53 millions whereas rural population is 1.301 millions. The Sex Ratio is 1003 Females per 1000 Males. The District has Density of population of 384 per Sq.Kms. The literacy rate is 67.7 percent in the District.

The questionnaire was administrated in such a way that it carefully records the customer expectations. The customers were asked to provide their expectations on a five point likert scale (Most-Expected [5], Expected [4], Slightly- Expected [3], Least-Expected [2], Not-at-all Expected [1]) regarding attributes of bank outlets. The Questionnaire also concentrates on socioeconomic profile of banking customers and also attempts to study banking behavior of customers.

Material and Methods

The following statistical methods are used in the analysis.

Tabular Analysis: Simple tabular analysis is used to analyze the socioeconomic profile of the respondents. This method is also used for analyzing associations among any two required variables.

Means, proportions and ranks: Most of the analysis is simple and relied on comparing means (average) and proportion. The determinants of the customer patronage for bank outlet choice are ranked basing on factor loadings for different retail outlets.

Factor Analysis: It is a statistical technique used for determining the underlying factors or forces among a large number of interdependent variables or measures: (Krishnaswami & Ranganatham, 2007). In social sciences and especially in behavioral studies, variables cannot be measured directly. Such variables are usually referred as “latent” variables and can be measured by qualitative propositions to reflect the perceptions of the respondents. The factors generated are used to simplify the interpretation of the observed variables. The factor loadings are the correlation coefficients between the variables and factors. Factor loadings are the basis for imputing a label to different factors. Like Pearson’s correlation coefficient “r”, the squared factor loading is the percentage of variance in the variable, explained by a factor.

Eigen values: The Eigen value for a given factor reflects the variance in all the variables, which is accounted for by that factor. A factor's Eigen value may be computed as the sum of its squared factor loadings for all the variables. The ratio of Eigen values is the ratio of explanatory importance of the factors with respect to the variables. Eigen Value or Latent root is the sum of squared values of factor loadings relating to a factor (Krishnaswami & Ranganatham, 2007).

Chi-Square test: Using the information provided in each grouped factor Chi-square test is used to test the significance of the cumulative explanation of variance. If the Calculated Chi-square value is found to be significant (if it is above the table value) the factor/factors are considered as proper and used the factor scores as Indices for further analysis.

KMO Measure: Kaiser-Meyer-Olkin measure of sampling adequacy is performed in factor analysis to determine whether the factor should be considered for further analysis or not. If KMO measure is greater than threshold value of 0.5, then only the factor should be considered for further analysis: (Hair et al., 1998).

Bartlett's Test of Sphericity: In order to find out the appropriateness of factor analysis for the set of variables Bartlett’s Test is used. It measures the correlation of variables where the probability of less than 0.05 (p < .05) is acceptable: (Anchaliya et al., 2012).

KMO and Bartlett's Test: In order to find out the appropriateness of factor analysis for the set of statements (variables), Kaiser-Meyer-Olkin and Bartlett's Test of Sphericity is used. KMO measures the magnitude of observed correlation coefficients to the magnitude of partial correlation coefficients. A value greater than .5 is desirable. Bartlett's Test measures the correlation of variables. A probability of less than .05 is desirable: (Anchaliya et al., 2012).

Cronbach’s Alpha: The value was calculated for the questionnaire administrated in order to determine the reliability of the data where the alpha value is greater than .70 is the recommended level: (Bernardi, 1994). For this study, Cronbach’s Alpha value is calculated as .777 for 600 sample which indicates that the data have relatively higher internal consistency (77.7%).

Socioeconomic Profile of Retail Banking Customers

In this section an attempt has been made to analyse socioeconomic profile of retail banking customers. This analysis helps the bankers to plan for their product portfolio in terms of savings plans, types and other banking services depending on gender, age group, income, education, occupation and size of family. This analysis also helps in planning their marketing communications, media selection, promotional campaigns etc.

In this section an attempt has been made to analyse the socio-economic profile of retail banking customers as presented in Table 3. Out of total 600 sample respondents, 395 (65.83%) are male and 205 (34.17%) are female.

Table 3 Socioeconomic Profile of Retail Banking Customers
Variable	Categories of variable	Frequency	%
Gender	Male	395	65.83%
	Female	205	34.17%
Age	15 - 20 years	13	2.17%
	20 - 30 years	371	61.83%
	30 - 40 years	178	29.67%
	40 - 50 years	28	4.67%
	above 50 years	10	1.67%
Occupation	Students	49	8.17%
	Unemployed	40	6.67%
	Employed	316	52.67%
	Business people	195	32.50%
Education	Less than or 5th Class	4	0.67%
	5th to 9th Class	16	2.67%
	SSC / 10th Class	59	9.83%
	Higher Secondary / Diploma / ITI	69	11.50%
	Graduation (UG)	269	44.83%
	Post Graduation (PG)	156	26.00%
	Higher than PG	27	4.50%
Income	Less than Rs.5,000/-	25	4.17%
	Between Rs.5,000/- and Rs.10,000/-	156	26.00%
	Between Rs.10,000/- and Rs.20,000/-	249	41.50%
	Between Rs.20,000/- and Rs.50,000/-	112	18.67%
	More than Rs.50,000/-	58	9.67%
Size of Family	Two	95	15.83%
	Three	245	40.83%
	Four	225	37.50%
	Five	23	3.83%
	Six	12	2.00%
Sources: field data

Basing on their age, the respondents are classified into five groups. Out of total sample 600, 13 (2.17%) are from the age group of 15 – 20 years, 371 (61.83%) are from age group of 20 – 30 years, 178 (29.67%) are from early middle age group (31 – 40 years), 28 (4.67%) belong to late middle age group 40 – 50 years and 10 (1.67%) are from old age group (above 50 years).

Based on occupation, the respondents are classified into four groups, students 49 (8.17%), unemployed 40 (6.67%), employed 316 (52.67%) and business people 195 (32.50%). Basing on the education, the respondents are classified into seven groups, 4 (0.67%) respondents completed elementary education, 16 (2.67%) have secondary education, 59 (9.83%) studied 6th class to 9th class, 59 (9.83%) completed secondary education, 69 (11.50%) completed higher secondary education, 269 (44.83%) are graduated, 156 (26%) have post graduation qualification and 27 (4.5%) are higher post graduates.

Basing on the income levels, the respondents are classified into five groups, 25 (4.67%) are having monthly income less than Rs.5,000/-, 156 (26%) have income between Rs.5,000/- and Rs.10,000/-, 249 (41.50%) have income between Rs.10,000/- and Rs.20,000/-, 112 (18.67%) have income between Rs.30,000/- and Rs.50,000/-, another 58 (9.67%) respondents have income more than Rs.50,000/-.

The family size attribute of retail banking consumers is categorised into five groups, 95 (15.83%) have family size two, 245 (40.83%) have size three, 225 (37.50%) are having family size four, 23 (3.83%) have five and 12 (2%) of respondents are having size six.

Banking Behaviour of Retail Banking Customers

The banking behavior of the customers is analysed in this section as displayed in the Table 4. The study of banking behavior enables the bankers to design and implement their marketing strategies so as to promote and sell banking services.

Table 4 Banking Behaviour of Retail Banking Customers
Variable	Categories of variable	Frequency	%
Frequency of banking	Daily	15	2.50%
	Weekly	75	12.50%
	Biweekly	54	9.00%
	Monthly	227	37.83%
	Bimonthly	9	1.50%
	As per requirement	220	36.67%
Most preferred week of banking	First week of month	279	46.50%
	2nd week of month	91	15.17%
	Last week of month	16	2.67%
	As per requirement	214	35.67%
Amount of transactions per month	Less than Rs.10,000/-	250	41.67%
	Between Rs.10,000/- to Rs.50,000/-	200	33.33%
	Between Rs.50,000/- to Rs.1,00,000/-	90	15.00%
	More than Rs.1,00,000/-	60	10.00%
Source of Information about bank	News Papers	200	33.33%
	Television	220	36.67%
	Radio	34	5.67%
	Internet Ads	96	16.00%
	Social Networking Sites	50	8.33%
Type of bank	Public Sector Bank	200	33.33%
	Private Bank	150	25.00%
	Foreign Bank	95	15.83%
	Cooperative Bank	50	8.33%
	Any other Financial Institutions	105	17.50%
Sources: field data

1. The frequency of banking is observed in this section. From the total sample 600, the frequency of banking is observed as daily 15 (2.50%), weekly 75 (12.50%), biweekly 54 (9%), monthly 227 (37.83%), bimonthly 9 (1.50%) and 220 (36.67%) of respondents are performing banking as per requirement.

2. In this segment, the most preferred week of retail banking in a month has been analysed. Out of 600 sample, retail banking customers are doing banking in first week of the month are (46.50%), second week 91 (15.17%), last week of the month 16 (2.67%) and 214 (35.67%) of the respondents perform banking as per requirement.

3. The monthly amount of banking transaction by the customer is analysed in this section, out of the sample 600, 250 (41.67%) are doing transactions less than Rs.10,000/-, 200 (33.33%) of the customers are doing transactions with an amount between Rs.10,000 and Rs.50,000, 90 (15%) are doing with an amount between Rs.50,000/- to Rs.1,00,000/- and 60 (10%) are doing banking transactions with an amount more than Rs.1,00,000/-.

4. The concept of retail branding is also applicable to banks. An attempt has been made to identify the media sources through which the customers are able to know about the bank outlet so that the bankers can plan and promote their brand marketing programs. The source is as Newspaper for 200 (33.33%) customers, TV 225 (36.67%), Radio 34 (5.67%), Internet ads 96 (16%) and Social Networking sites as a source for 50 (8.33%) respondents.

5. The types of bank that is used by the customers are identified in this segment. In the study area, out of 600 respondents, 200 (33.33%) are using public sector banks, private banks by 150 (25%), foreign banks by 95 (15.83%) customers, cooperative banks by 50 (8.33%) customers and remaining 105 (17.50%) are using any available financial institutions for performing banking transactions.

Data Analysis – Determinants of Customer Patronage Towards Selection of Bank Outlet

In this section an attempt has been made to analyse the determinants of customer patronage towards selection of bank outlet by performing multivariate analysis (factor analysis for data reduction). The situation where more than one dependent variable is influencing the decisions then factor analysis is considered to be appropriate tool for data analysis. Factor analysis was performed on the data of customer expectations towards selected determinants that motivate the customer to select a bank (24 determinants presented in Table 1). The customers were asked to provide their expectations on a five point likert scale (Most-Expected [5], Expected [4], Slightly- Expected [3], Least-Expected [2], Not-at-all Expected [1]) regarding twenty four attributes/determinants which were derived from previous studies. To determine the data reliability, Reliability test was performed on the data of customer expectations towards selected determinants. The value of the Cronbach's Alpha is found to be 0.787, which shows the data of pre-purchase-attributes is 787% reliable which ensures to proceed for further analysis.

Reliability of Data: Kaiser Meyer Olkin (KMO) and Bartlett’s Test for Determinants of Customer Patronage

To know about which determinants the customers are most expecting, factor analysis was performed on the data of customer expectations towards determinants of customer patronage towards selection of bank outlet choice. To determine the appropriateness of application of factor analysis, Kaiser Meyer Olkin (KMO) and Bartlett’s Test was performed as shown in Table 5. The KMO measure is observed to be .658 which is higher than the threshold value of 0.5 (Hair et al., 1998). So it can be interpreted that there is no error in 65.8% of the sample and remaining 34.2% there may occur some sort of error. Bartlett's Test of Spherincity (2 =6788.578) is found to be significant (p < 0.001, df 190). Finally it can be concluded that the data collected on pre-purchase attributes is appropriate for factor analysis.

Table 5 KMO and Bartlett's Test  for Determinants
Kaiser-Meyer-Olkin Measure of Sampling Adequacy		0.658
Bartlett's Test of Sphericity	Approx. Chi-Square	6788.578
	Df	190
	Sig.	0.000
Source: Factor Analysis Data Reduction

Factors – Determinants of Customer Patronage

Factor analysis was used to remove the redundant variables from the survey data and to reduce the number of variables into a definite number of dimensions. The application was done in SPSS. The factor analysis was performed using principle component extraction method with varimax rotation. After performing factor analysis, the twenty four determinants were reduced to six factor dimensions, which explained 70.26% of overall variance which is indicating that the variance of original values was well captured by these six factors as shown in Table 6. The six factors are provisionally named Security, Privacy, Ambience, People, Brand and Benefits.

Table 6 Factors - Determinants of Customer Patronage
Factor	Eigen Values	% Total variance	Cumulative %
SECURITY	5.325	28.56	28.56
PRIVACY	2.781	11.78	40.34
AMBIENCE	2.111	11.12	51.46
PEOPLE	1.356	7.01	58.47
BRAND	1.287	6.78	65.25
BENFITS	1.107	5.01	70.26
Source: Factor Analysis Data Reduction

Factor Scores Matrix - Determinants of Customer Patronage

The factor scores matrix of Determinants of Customer Patronage shows the associated variables in all the six factors and their relative factor scores as presented in Table 7. The factors, factor loadings and their associated determinants are as follows.

Table 7 Factor Scores Matrix - Determinants of Customer Patronage
Determinants	Security	Privacy	Ambience	People	Brand	Benefits
Security	0.934
Accuracy	0.875
Efficiency	0.718
Reliability	0.589
Privacy		0.811
Accessibility		0.725
Feedback/complaint management		0.638
Product Portfolio		0.573
Aesthetics			0.810
Tangibles			0.735
Convenience			0.547
Friendliness				0.851
Responsiveness				0.645
Empathy				0.520
Queue Management				0.569
Credibility					0.889
Bank Image					0.715
Competence					0.671
Compensation						0.721
Usefulness						0.632
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.

1. First Factor - Security: The first factor formed is security with an Eigen value of 5.325, variance of 28.56% and four associated variables. The associated variables are security (0.934), accuracy (0.875), efficiency (0.718) and reliability (0.589).

2. Second Factor – Privacy: The second factor formed is privacy with an Eigen value of 2.781, variance of 11.78% and four associated variables. The associated variables are privacy (0.811), accessibility (0.725), feedback (0.638) and product portfolio (0.573).

3. Third Factor - Ambience: The third factor formed is ambience with an Eigen value of 2.111, variance of 11.12% and three associated variables. The associated variables are aesthetics (0.81), tangibles (0.735) and convenience (0.547).

4. Fourth Factor – People: The fourth factor formed is risk with an Eigen value of 1.356, variance of 7.01% and four associated variables. The associated variables are friendliness (0.851), responsiveness (0.645), empathy (0.52) and queue management (0.569).

5. Fifth Factor – Brand: The fifth factor formed is brand with an Eigen value of 1.287, variance of 6.78% and three associated variables. The associated variables are credibility (0.889), bank image (0.715) and competence (0.671).

6. Sixth Factor – Benefits: The sixth factor formed is risk with an Eigen value of 1.107, variance of 5.01% and two associated variables. The associated variables are compensation (0.721) and usefulness (0.632).

Eliminated Factors: While performing factor analysis, four determinants from the total list of twenty four were eliminated. They are cleanliness, ease of use, system availability and contact. The customer may not be considering these four variables as important while choosing a bank outlet to perform banking.

Discussion and Suggestions

Hence it is suggested to the bankers to concentrate on the determinants in the order of factors scores from highest to lowest i.e. security, privacy, ambience, people, brand and benefits. In order to attract new customers and to retain existing customers of the bank, the bankers have to take care of these determinants. The retail bank outlet must offer good security to the customers along with accuracy in transactions, performance efficiency and reliability among bank transactions. The bank must provide privacy to the customers in order to be attracted by them. The bank must provide accessibility to various services in banks, provision of considering customer feedback and customer complaint settlements.

In order to attract customers the retail bank must maintain good ambience so that the customers can have good banking experience in the outlet. The bank outlet must maintain infrastructure facilities like good aesthetics, tangibles and offer convenience to the customers. The people recruited in the bank outlet must have the qualities like friendliness, responsiveness, empathy and have good queue management skills. The people element plays very important role in satisfying and retailing the customers with the bank. The brand image of the outlet should be given mush emphasis as it makes the customers to believe the bank. The credibility of the bank, the image of the bank and its competence play significant role in customer decision making process of selecting a retail bank for banking. Finally the benefits given by the bank other than the regular services will also attract the customers towards a particular bank. The monetary compensatory benefits to the customers and usefulness are also important criterion in evaluating a retail bank.

It can be observed that women are not participating actively when compare to men in performing banking transactions. They are contributing to only about 35%. The bankers have to create awareness and educate the women about the usage and performing banking transactions. It is also identified that most of the customers are belonging to 20 to 40 years of age (about 90%) so that the bankers have to concentrate on the needs of this age group and offer suitable banking services and design product portfolios with which this age group can be more attracted. On the basis of education, majority of the customers are graduates and post graduates. The bank managers also have to concentrate on other education groups i.e. from less than 5th class to higher secondary level, which represent about 25%, certain banking literacy programs and campaigns must be organised.

Conclusion

Even though the other banking channels like online banking, remote banking, ATM banking, payments bank are strongly emerging in the banking sector, the concept retail banking always got its own importance, especially for certain segments like senior citizens, loans and lockers. From this empirical study it can be observed that the retail bank customers are expecting security for their deposits, privacy for their data, ambience in the retail bank, people behaviour in the bank, bank brand and customer benefits. The bankers must provide these attributes first and concentrate on other attributes later in order to motivate the customers to get attracted towards the bank.

Limitations and Scope for Further Research

The study was organized in an Indian city of Visakhapatnam only, the sample size may not be representing the entire study area properly so that the chances of occurring sampling error is moderate to high. Basing on the previous studies, the present study is concentrated only on twenty four determinants of retail banking, but there may be more determinants existing which influence the customer decision making process. The same study can be organized across the world because banking exist every part of the world. The same research can be organized on sectors like retailing, insurance, travel, tourism etc.

References

1. Anchaliya, A., Chitnis, E., Bapna, I., & Shrivastava, G. (2012). Job Satisfaction of bank employees – A comparative study of Public and private sector. ed. Ritu Sinha, R.S.Ghosh, Svetlana Tatuskar & Shweta Maheswari. Ensisage 2020: Emerging Business Practices, 86-102.
2. Anna, M., Levesque, N., Boeck, H. (2020). Proximity marketing in banking: lessons from retail and entertainment industries, International Journal of Technology Marketing, 13(3-4), 401-427.
3. Antonella, M., & Nathalie, F. (2016). Customers experience and problem resolutions in retail banking: Some empirical evidence from Italian banking. International Journal of Financial Innovation in Banking, 1(1-2), 109-126.
4. Al Khulaifi, A., Al Sulaiti, K., & Al Khatib, F. (2005). Banking services and customer’s Satisfaction in Qatar, A statistical analysis. Studies in Business and Economics, 11(5), 23-89.
5. Bernardi, R.A. (1994). Validating research results when Cronbach’s Alpha is below .70: A Methodological procedure. Educational and Psychological Measurement, 54(3), 766-775.
6. Gronroos, C. (1982). Strategic Management and Marketing in the Service Sector. Helsinki, Finland: Swedish School of Economics and Business Administration.
7. Saxena, G. (1992). Marketing in Commercial Banks: A Study of S.B.I. Unpublished Ph.D. Thesis, Manipur University, Manipur.
8. Johnston, R. (1995). The determinants of service quality: satisfiers and dissatisfiers. International Journal of Service Industry Management, 6(5), 53-71.
9. Joseph, M., McClure, C., & Joseph, B. (1999). Service quality in the banking sector: the impact of technology on service delivery. International Journal of Bank Marketing, 17(4), 182-193.
10. Jun, M., & Cai, S. (2001). The key determinants of internet banking service quality: a content analysis. International Journal of Bank Marketing, 19(7), 276-291.
11. Hair, J.F., Anderson, R.E., Tatham, R.L., & Black, W.C. (1998). Multivariate data analysis, 5 ed, New Jersey: Prentice Hall, Inc.
12. Rao, K. (1994). Marketing of Services in Commercial Banks: A Study of Marketing operations of Andhra Bank. Unpublished Ph.D. Thesis, Andhra University, Visakhapatnam.
13. Kansal, R., & Singh, M. (2007). Customers Orientation towards Banking Services in Urban Areas of Punjab. Business Vision, Serial Publication, New Delhi, 103-113.
14. Kant, R., & Jaiswal, D. (2016). The impact of perceived service quality dimensions on customer satisfaction: An empirical study on public sector banks in India. International Journal of Bank Marketing, 35(3), 411-430.
15. Khan, M.S., & Mahapatra, S.S. (2008). Service quality evaluation in internet banking: an empirical study in India. International Journal of Indian Culture and Business Management, 2(1), 30-46.
16. Krishnaswami, O.R., & Ranganatham, M. (2007). Methodology of Research in Social Sciences, Hyderabad: Himalaya Publishing House. 338-339.
17. Loonam, M., & O'loughlin, D. (2008). Exploring e-service quality: a study of Irish online banking. Marketing Intelligence & Planning, 26(7), 759-780.
18. Madhavi, A., & Sanjai, K.P. (2018). Personal touch or convenient tech? An investigation of customer channel preferences in retail banking. International Journal of Financial Services Management, 9(2), 103-118.
19. Neena, S., Baldev, R.S., & Supriya M.K. (2017). Customer engagement in the Indian retail banking sector: an exploratory study, International Journal of Business Innovation and Research, 12(1), 41-61.
20. Parasuraman, A., Zeithaml, V.A., & Berrym L.L. (1985). A Conceptual Model of Service Quality and its Implications for Future Research. Journal of Marketing, Fall, 49, 42-50.
21. Pratap, C.M., & Sujoy, B. (2013). Post-service recovery customer satisfaction in Indian retail banking: a qualitative approach. International Journal of Qualitative Research in Services, 1(2), 97-112.
22. Gera, R. (2011). Investigating the link between service quality, value, satisfaction and behavioural intentions in a public sector bank in India. International Journal of Services, Economics and Management, 3(1), 3-20.
23. Rust, R.T., & Zahorik, A.J. (1993). Customer satisfaction, customer retention, and market share. Journal of Retailing, 69, 193-215.
24. Sadeghi, T., & Farokhian, S. (2011). Services quality model for E-bankingservices by behavioral adoption theories and comparative study. African Journal of Business Management, 5(11), 4490.
25. Wu, Y.L., Chang, M.C., Yang, P.C., & Chen, Y.J. (2008). The Use of E-SQ to establish the internet bank service quality table. In Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on (1446-1450).
26. Yang, Z., Jun, M., & Peterson, R.T. (2004). Measuring customer perceived online service quality: scale development and managerial implications. International Journal of Operations & Production Management, 24(11), 1149-1174.
27. Zeithaml, V.A., Berry, L.L., & Parasuraman, A. (1996). The behavioral consequences of service quality. The Journal of Marketing, 31-46.