Customer Perception of Service Convenience: A Comparison between Public and New Private Sector Banks

Abstract

This study examines the difference between public sector and new private sector banks with reference to service convenience dimensions; decision convenience, access convenience, transaction convenience, benefit convenience and post-benefit convenience. A cross-sectional research on 445 retail banking customers through structured questionnaire is conducted. The population of the study is valued retail urban customers of the public and the new private sector banks in Rajasthan, who frequently visit bank premises for transactions, have accounts in at least two banks and have availed of at least one IT based service. The results reveal that service convenience dimensions differ between public and new private sector banks. New private sector bank customers’ mean score is found more than public sector bank customers. This study has theoretical and practical contribution. From theoretical point of view, service convenience scale is used and validated in retail banking sector in Indian context. For bank professionals, this study explains the difference of service convenience between public and new private sector banks and opens door to improve service convenience.

Keywords

Decision convenience access convenience transaction convenience benefit convenience and post-benefit convenience

Introduction

After the deregulation and liberalization in 1991, the forces of competition have become fairly dominant in the Indian banking system. The banking sector has witnessed increased competition among the three major participants, i.e., Indian public sector banks, Indian private sector banks and foreign banks. Foreign banks are far ahead than public and private sector banks in terms of profitability and services given to customers leaving the competition primarily between public and private sector banks. Private sector banks comprise of old and new private sector banks. These new private sector banks have entered into the retail market with innovation and better technology. Public sector banks have to compete with new private sector banks for survival in the market. It is reported that 90 per cent of bank switching in the Asian banking market occurs due to pricing, service quality and inconvenience (Gerrard and Cunningham, 2004).

As the income of people is rising, there is an inclination towards convenience-related services. Growing demand of laundry services, housekeeping and home delivery grocery outlets are some example of services that reflect convenience orientation of people. Bank customers may expect proximity of automatic teller machine (ATM) or bank branch while withdrawing money or 24X7 hrs facilities for electronic transactions. Banking services delivered via the Internet, mobile phone interface, voice response system, call centres, ATMs and via face-to-face in a branch or visits at a customer’s home not only have various cost implications for banks but also drastically affect the nature of service experience for the customer.

For availing of loan service, customers have to rely on personal channels. Therefore, the convenience of location plays an important role in satisfying customer. Customers with a higher knowledge about a service are more likely to use self-service channels like ATM and internet banking. But convenience is a key driver of channel choice for the majority of consumers (Berry et al., 2002). Milligan (1997) suggests that banks with an extensive branch office system and ATM network would have the opportunity to attract customers who are in the convenience segment.

The competition between the new private and public sector banks has resulted in a greater need for service providers to identify the service convenience gaps in the market in order to improve service provisions to retain customers. New generation private sector banks have been able to create a niche in the retail banking due to technology and innovation.

Today’s Indian banking environment demands of convenience for their customers’ survival. The findings from the study can provide valuable insights regarding service convenience differences between public sector banks and new private sector banks.

Literature Review

Inseparability of production and consumption is the most intriguing characteristic of services. Service provider’s physical connection to the service, the customer’s involvement in the service production process and involvement of other customers in the service production process create challenges for the service provider. Customers have to visit the service provider for availing services, if service hours do not coincide with customers’ available time, they have to arrange their schedule to meet service provider’s schedule. It creates inconvenience for the customer. For example, for opening a bank account or for availing of loan, customers have to visit the bank. If the banking hours or the location of the bank is not convenient for bank customers, it creates inconvenience for them.

The concept of convenience started with products. Copeland (1923) defined convenience goods as ‘intensively distributed products that require minimal time and physical and mental effort to purchase’ (Yale and Venkatesh, 1986; Berry et al., 2002). Other definitions of convenience also focused on resources such as time and effort required in shopping for a product (Brown, 1990).

Service convenience is defined as the ‘consumers’ time and effort perceptions related to buying or using a service’ (Berry et al., 2002). Service convenience can be thought of as a means of adding value to consumers, by decreasing the amount of time and effort a consumer must expend on the service (Colwell et al., 2008).

The service convenience construct has been generally treated as a concept with the easiness. Yale and Venkatesh (1986) have proposed six classes of convenience: time utilization, accessibility, portability, appropriateness, handiness and avoidance of unpleasantness. However, this framework was criticized for the lack of theoretical underpinning and means of measurement (Berry et al., 2002). Brown (1989) proposed five types of convenience: time, place, acquisition, use and execution. Whereas some researchers (Luqmani et al., 1994) have labelled the convenience-related costs of time and effort as dimensions, others have defined distinct types or categories of convenience as dimensions. Berry et al. (2002) have conceptualized five dimensions of service convenience: decision convenience, access convenience, transaction convenience, benefit convenience and post-benefit convenience. This conceptualization is theoretical and not validated. It is validated by Seiders et al. (2007). They developed the SERVCON scale and empirically validated the service convenience construct in the context of retail chain with approximately 100 stores located in all major geographical regions of the United States. Service convenience dimensions as proposed by Berry et al. (2002) were used by Colwell et al. (2008) through SERVCON scale in Canadian cellular and internet services. Aagja et al. (2011) also used SERVCON scale in the Indian organized food and grocery retail context. Following are the dimensions of service convenience as conceptualized by Berry et al. (2002).

Decision Convenience (DC)

Decision convenience was defined as ‘consumers’ perceived time and effort expenditure to make service purchase or use decisions’ (Berry et al., 2002). The availability and quality of information about the service provider and its competitors determine decision convenience; consumers normally have a higher convenience threshold when their purchase decisions involve services that are complex or difficult to evaluate (Zeithaml et al., 1996). According to Aagja et al. (2011) when consumers feel the need for a product or a service, they have to decide the service provider from whom they will buy the service. It depends upon the information provided by service providers in making decision.

Transaction Convenience (TC)

Transaction convenience was defined as ‘consumers’ perceived time and effort expenditures to effect a transaction’ (Berry et al., 2002). Transaction convenience perceptions reflect the time spent in physical or remote queues, which can be problematic for firms because wait times commonly are perceived as longer than they actually are and negatively influence overall service evaluations (Kumar et al., 1997). Colwell et al. (2008) stated that more investment in terms of time and energy is required for consumers to complete the transaction of the service.

Benefit Convenience (BC)

Benefit convenience was defined as ‘consumers’ perceived time and effort expenditures to experience the service’s core benefits’ (Berry et al., 2002). Benefit convenience includes the fundamental service experience, which differs in importance based on the type of service being consumed. Once a consumer has accessed and purchased a service, consumption of the service begins (Peter and Olson, 1999).

Access Convenience (AC)

Access convenience was defined as ‘consumers’ perceived time and effort expenditures to initiate service delivery’ (Berry et al., 2002). Physical location, operating hours and availability in person, on telephone or online determine access convenience (Meuter et al., 2000; Seiders et al., 2000). Inseparability of production and consumption is a characteristic of services. Therefore, location of service outlet is very important. As per Colwell et al. (2008), once the consumer has decided on a service provider and a particular product, he wants access to the service in convenient way.

Post-benefit Convenience (PBC)

Post-benefit convenience was defined as ‘consumers’ perceived time and effort expenditures when reinitiating contact with a firm after the benefit stage of the service (Berry et al., 2002). This type of convenience involves the need to contact the provider after the sale is complete to initiate service complaints or failures, request maintenance or upgrades or for general service support (Zeithaml and Bitner, 2000; Colwell et al., 2008). Factors that determine post-benefit convenience often relate to service recovery efforts, in which exchanges frequently represent responses to defective products or services, transaction errors or a customer’s change of mind (Seiders et al., 2007).

Research Gap

According to Colwell et al. (2008) continuum of convenience need to be investigated further and research on convenience should investigate other contexts outside of the cellular and internet services. Studies on convenience in the Indian context are limited to retail mall sector only. Therefore, it requires conducting study on contexts other than the retail sector in the Indian context. According to Aagja et al. (2011), studies could also be undertaken in other service sectors like banking, telecom, insurance, internet, fast food, etc., to assess validity of the service convenience scale in the Indian context. This study will address this gap by studying the service convenience scale in the Indian Banking sector.

Objectives

Based on the review of literature and gaps identified, the major objectives of the present study are as follows:

To investigate the service convenience scale in Indian banking sector.

To study the difference between public sector and new private sector banks with reference to service convenience dimensions.

Research Methodology

The population chosen for the present study is the urban customers of retail banking in both public and new private sector banks in Rajasthan. These customers fulfil the following criteria.

Frequent visit to bank premises for transactions: Since all bank customers may not possess sufficient knowledge of various banking operations, only those customers who frequently visit banking premises for transactions are considered suitable for study. Present study considers at least two bank visits of customers in a month.

Maintain account in at least two banks: As the objective of the present study is to compare public and new private sector banks in terms of service convenience, therefore, customers who have accounts in at least two banks are considered for the study so as to draw credible conclusions from the comparisons.

Subscribing at least one IT based service (ATM, mobile banking, internet banking): Customers who are subscribing and using at least one information technology based services are considered for the study.

Valued customers: This study considers following criteria for customers to be considered as valued customers.

Those who are customers of banks as part of social responsibility criteria of government (student account/Below Poverty Line (BPL) account/National Rural Employment Guarantee Act[NREGA] account) or beneficiaries of welfare oriented schemes of government have been kept outside the purview of the present study.

According to bank officials, top valued customers do not visit bank premises as they are provided services at their doorstep or their assistants do the banking on their behalf. These customers are high net worth customers of the bank. That is the primary reason of their being kept outside the present study. The way, top valued customers are dropped from the study, bottom layer of valued customers are also dropped from the study.

Customers who maintain a minimum average balance of ₹ one lakh in their accounts in terms of deposit or have availed of a loan of at least ₹ one lakh are part of this study. They have a ‘law abiding spirit’ as well. The customers who have a ‘law abiding spirit’ are not defaulters and follow all the rules and regulations of the bank. The prerequisite of a valued customer is a ‘law abiding spirit’.

This study was conducted in the state of Rajasthan. Bikaner, Sri Ganganagar, Alwar and Udaipur from West, North, East and Southern region of Rajasthan ensured representation of the entire state.

The State Bank of India (SBI) and its associate banks, nationalized banks and new private sector bank were selected for study. For selection of banks, the judgment criteria is number of functioning branches of banks in Rajasthan. The top three banks with reference to a number of functioning branches in Rajasthan are considered for both public and new private sector banks (See Table 1). Industrial Credit and Investment Corporation of India (ICICI) bank, Axis bank and Housing Development Finance Corporation (HDFC) bank were selected among the new private sector banks. In public sector banks, the State Bank of Bikaner and Jaipur (SBBJ), the Bank of Baroda (BOB), the Punjab National Bank (PNB) are considered for the study (See Table 2).

Table 1.

Bank-wise Number of Functioning Branches of New Private Sector Banks in Rajasthan (As on 31.03.2011)

Bank Name	Number of Functioning Branches
New Private Sector Banks
1. ICICI Bank Ltd.	380
2. Axis Bank Ltd.	68
3. HDFC Bank Ltd.	67
4. Indusind Bank Ltd.	17
5. Kotak Mahindra Bank Ltd.	13
6. Yes Bank Ltd.	12
7. Development Credit Bank Ltd	3

Source: Master Office File (Latest updated version) on banks, DSIM, RBI cited in RBI (2010–2011b), Statistical Tables Relating to Banks in India 2010–2011.

Notes: 1. Data is as per information reported by banks.

2. Data on number of offices include administrative offices.

Table 2.

Bank-wise Number of Functioning Branches of Public Sector Banks in Rajasthan (As on 31.03.2011)

Bank Name	Number of Functioning Branches
SBI and its Associates
1. State Bank of Bikaner and Jaipur	817
2. State Bank of India	296
3. State Bank of Patiala	33
4. State Bank of Hyderabad	2
5. State Bank of Mysore	1
6. State Bank of Travancore	1
Nationalized Banks
1. Bank of Baroda	391
2. Punjab National Bank	344
3. UCO Bank	162
4. Central Bank of India	145
5. Oriental Bank of Commerce	130
6. Union Bank of India	80
7. Bank of India	71
8. Canara Bank	63
9. Allahabad Bank	62
10. Indian Overseas Bank	41
11. Syndicate Bank	37
12. IDBI Bank Limited	33
13. Punjab and Sind Bank	31
14. Bank of Maharashtra	28
15. Corporation Bank	27
16. Dena Bank	22
17. Vijaya Bank	21
18. Indian Bank	16
19. United Bank of India	11
20.Andhra Bank	10

Source: Master Office File (latest updated version) on banks, DSIM, RBI cited in ‘RBI Statistical Tables Relating to Banks in India 2010–2011’.

Notes: 1. Data is as per information reported by banks.

2. Data on number of offices include administrative offices.

Survey instruments were administered personally and 486 customers were contacted. Out of these questionnaires, 41 were rejected because of the missing data or a high response bias leaving an overall sample size of 445. Out of the total acceptable sample (445), 234 respondents were from public sector banks and 211 from new private sector banks.

The respondents were selected from public and new private sector banks through quota sampling. Quotas were based on public and new private sector banks. Within the quota, customers were selected on the basis of purposive sampling.

Demographics

Table 3 shows the demographic profile of respondents.

The majority of respondents (42 per cent) were in ‘36–45’ age category followed by ‘46–55’ age category (26.3 per cent) for overall banking sector. For public sector banks, (37.6 per cent) customers were in ‘46–55’ age category followed by ‘36–45’ age category (29.5 per cent). For new private sector banks (46.92 per cent) customers were in ‘36–45’ age category followed by ‘46–55’ age category (22.75 per cent). Age variation is found between public and new private sector banks.

Regarding education, the majority of respondents possessed a master’s degree (52.58 per cent) followed by graduation (17.30 per cent) for the overall banking sector. For public sector banks, (58.55 per cent) customers possessed a Master’s degree followed by intermediate (13.25 per cent). For new private sector banks (45.97 per cent) respondents were possessing Master’s degree followed by graduation (22.75 per cent).

Regarding employment, (36.63 per cent) respondents had private jobs followed by public sector jobs (35.06 per cent) for the overall banking sector. For public sector banks, (50 per cent) customers had public sector jobs followed by private sector jobs (32.05 per cent). For new private sector banks (42.18 per cent) respondents were self-employed followed by private sector job (40.76 per cent). Variation can be seen in employment between public and new private sector banks.

Regarding years of transaction with the bank, 67.64 per cent respondents had more than three years of transaction with banks followed by three or less years of transaction with the bank (32.36 per cent) for overall banking sector. For public sector banks, (81.20 per cent) respondents had more than three years of transaction with the bank followed by three or less years’ transaction with bank (18.80 per cent). For new private sector banks (52.61 per cent) respondents had three or less years of transaction with the bank followed by more than three years of transaction with the bank (47.39 per cent). There is a variation between public and new private sector bank customers regarding years of transaction with the bank.

Table 3.

Demographic Profile of Public Sector, New Private Sector and Overall Banking Sector Customers

		Public Sector Bank		New Private sector Bank		Overall Banking Sector
		Number	%	Number	%	Number	%
Age	25 years or less	9	3.8	28	13.27	37	8.3
	26–35	38	16.3	31	14.69	69	15.5
	36–45	69	29.5	99	46.92	187	42
	46–55	88	37.6	48	22.75	117	26.3
	56 and above	30	12.8	5	2.37	35	7.9
	Total	234	100	211	100	445	100
Education	High school	20	8.55	15	7.11	35	7.88
	Intermediate	31	13.25	23	10.90	54	12.13
	Graduation	29	12.39	48	22.75	77	17.30
	Master’s degree	137	58.55	97	45.97	234	52.58
	Others	17	7.26	28	13.27	45	10.11
	Total	234	100	211	100	445	100
Employment	Public	117	50	36	17.06	156	35.06
	Private	75	32.05	86	40.76	163	36.63
	Self-employed	42	17.95	89	42.18	126	28.31
	Total	234	100	211	100	445	100
Years of transaction with this bank	3 years or less	44	18.80	111	52.61	144	32.36
	More than 3 years	190	81.20	100	47.39	301	67.64
	Total	234	100	211	100	445	100
Income per month	` 20, 000 or less	44	18.80	30	14.22	74	16.63
	21,000–40,000	82	35.05	72	34.12	154	34.61
	More than ` 40,000	108	46.15	109	51.66	217	48.76
	Total	234	100	211	100	445	100
Gender	Male	210	89.74	201	95.26	411	92.36
	Female	24	10.26	10	4.74	34	7.64
	Total	234	100	211	100	445	100

Source: Own processed.

Regarding income, (48.76 per cent) respondents were in the category of ‘More than ₹ 40,000 per month’ followed by ‘21,000–40,000’ category (34.61 per cent) for the overall banking sector. For public sector banks, (46.15 per cent) customers were in the category of ‘More than ₹ 40,000 per month’ followed by ‘21,000–40,000’ category (35.05 per cent). For new private sector banks (51.66 per cent) respondents were in the category of ‘More than ₹ 40,000 per month’ followed by ‘21,000–40,000’ category (34.12 per cent).

Regarding gender, 92.36 per cent of the respondents were male, followed by 7.64 per cent females for the overall banking sector. For public sector banks, 89.74 per cent of the respondents were male followed by 10.26 per cent females. For new private sector banks, 95.26 per cent of the respondents were males followed by 4.74 per cent females.

The data is skewed towards educated males in the ‘36–45’ age category who have more than three years of transaction with the bank, and who earn more than ₹ 40,000 per month.

Measure

Service convenience was measured using a 17 item scale developed by Colwell et al. (2008). The scale has five dimensions: decision convenience, transaction convenience, benefit convenience, access convenience and post-benefit convenience. Description of items is given in Table 4.

Table 4.

Description of Service Convenience Items

	Decision Convenience	Items Retained in Factor Analysis
DC1	The information I receive from this bank makes it easy for me to choose what to buy.	Yes
DC2	Making up my mind about what service I want to buy is easy.	Yes
DC3	The information that I receive from this bank is clear and easy to understand.	Yes
DC4	The service provider let me know the exact interest rate or service charges or special offer.	Yes
Transaction Convenience
TC1	I find it easy to complete my service purchase with this bank.	Yes
TC2	I am able to complete the purchase of my service quickly with this bank.	Yes
TC3	It takes little effort to deal with this bank during purchase.	Yes
	Benefit Convenience
BC1	I am able to get the benefits of this service with little effort.	Yes
BC2	The time required to receive the benefits of service is reasonable.	Yes
BC3	Products of this bank are easy to use.	Yes
Access Convenience
AC1	The service provider is available when I need to talk to him.	Yes
AC2	The service provider is accessible through various ways (online, telephone, in person, ATM).	No
AC3	The hours of operation of the service provider are convenient.	Yes
AC4	Location of this bank’s branches are easy to access.	Yes
Post-benefit Convenience
PBC1	My service provider quickly resolves problem/s I have with the service.	Yes
PBC2	It is easy for me to obtain follow up service from the provider after my purchase.	Yes
PBC3	When I have questions about my service, my service provider is able to resolve my problem.	Yes

Source: Own processed.

Results and Discussion

Objective 1: To Study the Service Convenience Scale in Indian Banking Sector

To achieve this objective factor analysis, correlation analysis and reliability analysis are used. Table 5 shows correlation analysis of service convenience scale. An investigation of the correlation matrix reveals that the correlation of the variables that measure an identical conception is higher than the correlation of the variables that measure a different conception, and confirms convergent and discriminant validity. Park et al. (2006) used correlation matrix to measure convergent and discriminant validity. According to them correlation is generally high among the variables that measure an identical conception and shows a convergent validity, moreover, if the correlation of the variables that measure an identical conception is higher than the correlation of the variables that measure a different conception, then it shows discriminant validity. According to Campbell and Fiske (1959) discriminant validity for each item may be tested by counting the number of times that the item correlates higher with items of other factors than with items of its own theoretical factor. It is suggested that the count should be less than one-half the potential comparisons. These criteria are fulfilled and confirm the construct validity of data.

Table 5.

Correlation Analysis of Service Convenience Scale Items

	DC1	DC2	DC3	DC4	TC1	TC2	TC3	BC1	BC2	BC3	AC1	AC3	AC4	PBC1	PBC2	PBC3
DC1	1
DC2	.711**	1
DC3	.736**	.649**	1
DC4	.463**	.437**	.405**	1
TC1	.229**	.214**	.305**	.175**	1
TC2	.172**	.202**	.267**	.142**	.821**	1
TC3	.260**	.252**	.312**	.205**	.874**	.804**	1
BC1	.263**	.230**	.168**	.328**	.449**	.418**	.490**	1
BC2	.191**	.206**	.122*	.297**	.277**	.273**	.346**	.780**	1
BC3	.286**	.239**	.182**	.357**	.341**	.293**	.409**	.825**	.760**	1
AC1	.319**	.352**	.379**	.299**	.321**	.359**	.393**	.232**	.150**	.256**	1
AC3	.362**	.320**	.322**	.205**	.317**	.328**	.395**	.239**	.198**	.204**	.737**	1
AC4	.338**	.337**	.379**	.343**	.362**	.393**	.401**	.328**	.259**	.285**	.780**	.681**	1
PBC1	.206**	.219**	.112*	.030	.137**	.164**	.229**	.309**	.176**	.266**	.297**	.343**	.233**	1
PBC2	.202**	.143**	.175**	.088	.182**	.183**	.202**	.294**	.255**	.281**	.235**	.281**	.207**	.424**	1
PBC3	.152**	.248**	.064	.108*	.218**	.187**	.257**	.224**	.156**	.231**	.191**	.231**	.227**	.405**	.466**	1

Source: Own processed.

Notes: *Significant at the 0.05 level; ** Significant at the 0.01 level.

In order to check the appropriateness of factor analysis Kaiser Meyer Olkin (KMO) and Bartlett’s test were used. The results are shown in Table 6. The KMO value is greater than 0.5 and the significance level for Bartlett’s test value is 0.000 which shows that the value is significant at 1 per cent level of significance, therefore it is appropriate to apply factor analysis.

Table 6.

KMO and Bartlett’s Test Results for Service Convenience Scale

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.823
Bartlett’s Test of Sphericity	Approx. Chi-Square	4678.244**
	Df	120
	Sig.	.000

Source: Own processed.

Note: ** Significant at the 0.01 level.

Exploratory factor analysis was performed on 17 items scale of service convenience. The principle component method was used to extract factors with an initial setting for Eigen values greater than 1.0 (Field, 2005). Orthogonal rotation (Varimax) was applied to reduce potential multicollinearity among the items.

Table 7 shows results of exploratory factor analysis. It resulted in five orthogonal distinct factors, i.e., decision convenience, transaction convenience, benefit convenience, access convenience and post-benefit convenience. These factors confirmed the original scale and together they explained 78.04 per cent of variance.

The first factor ‘decision convenience’ comprised four items and explained 17.01 per cent of the total variance. This factor had an Eigen value of 2.72. The items, DC1, DC3, DC2 and DC4 loaded on this factor.

The second factor ‘transaction convenience’ comprised three items and explained 16.87 per cent of the total variance. This factor had an Eigen value of 2.70. The items, TC1, TC2 and TC3 loaded on this factor.

The third factor ‘benefit convenience’ comprised three items and explained 16.59 per cent of the total variance. This factor had an Eigen value of 2.65. The items, BC2, BC3 and BC1 loaded on this factor.

The fourth factor ‘access convenience’ comprised three items and explained 15.25 per cent of the total variance. This factor had an Eigen value of 2.44. The items, AC1, AC4 and AC3, loaded on this factor. One item, AC2, ‘The service provider is accessible through various ways (online, telephone, in person, ATM)’ is dropped from study due to low communality value.

The fifth factor ‘post-benefit convenience’ comprised three items and explained 12.31 per cent of the total variance. This factor had an Eigen value of 1.97. The items, PBC3, PBC2 and PBC1 loaded on this factor.

Table 7.

A Summary of Factor Analysis for Service Convenience Scale

Factor 1		Factor 2		Factor 3		Factor 4		Factor 5
DC		TC		BC		AC		PBC
Variable	Loading	Variable	loading	Variable	Loading	Variable	Loading	Variable	Loading
DC1 DC3 DC2 DC4	.874 .841 .834 .587	TC1 TC2 TC3	.919 .890 .873	BC2 BC3 BC1	.892 .877 .859	AC1 AC4 AC3	.879 .837 .823	PBC3 PBC2 PBC1	.776 .761 .736
Eigen Value	2.72		2.70		2.65		2.44		1.97
Percentage of Variance	17.01		16.87		16.59		15.25		12.31
Total Variance					78.03

Source: Own processed.

High loading on same factor and no substantial cross-loading confirms convergent and discriminant validity respectively.

To check reliability of scale, the Cronbach alpha test is used. Table 8 shows the results of reliability analysis.

Cronbach alpha for decision convenience is .83. The values in column labelled ‘Corrected Item-Total Correlation’ are all above .3. Deleting one item ‘DC4’ would increase Cronbach alpha from .83 to .87. However, original Cronbach alpha denotes reasonable degree of reliability. This is the reason that this item is not deleted.

Table 8.

Results of Reliability Analysis of Service Convenience Scale

	Scale Mean if Item Deleted	Scale Variance if Item Deleted	Corrected Item-Total Correlation	Squared Multiple Correlation	Cronbach Alpha if Item Deleted
DC1	9.71	7.497	.781	.648	.747
DC2	9.74	7.159	.719	.551	.772
DC3	9.63	7.701	.716	.576	.775
DC4	9.62	8.629	.487	.241	.872
Cronbach alpha= .838
TC1	6.52	4.921	.892	.803	.891
TC2	6.58	5.014	.839	.706	.933
TC3	6.53	4.889	.879	.786	.902
Cronbach alpha= .937
BC1	6.56	3.621	.855	.736	.864
BC2	6.53	3.908	.806	.651	.904
BC3	6.48	3.768	.841	.715	.876
Cronbach alpha = .918
AC1	6.54	3.614	.827	.688	.810
AC3	6.65	3.484	.751	.572	.876
AC4	6.50	3.525	.781	.633	.846
Cronbach alpha = .890
PBC1	6.16	2.876	.483	.235	.632
PBC2	6.08	3.214	.531	.284	.576
PBC3	5.93	2.871	.512	.269	.591
Cronbach alpha = .691

Source: Own processed.

Cronbach alpha for transaction convenience is .93. The values in column labelled ‘Corrected Item-Total Correlation’ are all above .3 and the values in column labelled ‘Cronbach alpha if Item deleted’ shows that none of the item related to transaction convenience is increasing the reliability if that item is deleted.

The overall Cronbach alpha is .91 for benefit convenience. The value in column labelled ‘Corrected Item-Total Correlation’ are all above .3 and none of the item related to benefit convenience is increasing the reliability if that item is deleted.

Cronbach alpha for access convenience is .89. The values in column labelled ‘Corrected Item-Total Correlation’ are all above .3 and none of the item related to access convenience is increasing the reliability if that item is deleted.

The overall Cronbach alpha is .69 for post-benefit convenience. The values in column labelled ‘Corrected Item-Total Correlation’ are all above .3 and none of the item related to post-benefit convenience is increasing the reliability if that item is deleted. The alpha value below .7 for post benefit convenience can be explained by the heterogeneity of respondents and substantial difference in the scores of the questions that measured the same factor.

Service convenience is comparatively a new construct; therefore, previous studies’ reliability on service convenience construct is also presented to compare results. Table 9 shows reliability test results of service convenience scale in previous researches.

Cronbach alpha value obtained in this study for service convenience scale demonstrates satisfactory results as values are varying from .69 to .93.

Objective 2: To Study the Difference between Public Sector and New Private Sector Banks with Reference to Service Convenience Dimensions (Decision Convenience, Transaction Convenience, benefit Convenience, Access Convenience and Post-benefit Convenience)

To address this objective, independent sample t-test is employed. Two independent samples are public and new private sector bank customers. Number of public sector bank customers and new private sector bank customers was 234 and 211 respectively. Table 10 shows the results of independent sample t-test.

Table 9.

Reliability Test Results of Service Convenience Scale in Previous Researches

Author	Aagja et al. (2011)		Colwell et al. (2008)		Sieders et al. (2007)
Area of Research	Organized Food and Grocery Retail, India		Personal Cellular Telephone, Canada		Retail Chain, United States
Variable	No. of Retained Items	Cronbach Alpha	No. of Retained Items	Cronbach Alpha	No. of Retained Items	Cronbach Alpha
DC	3	0.648	4	0.66 to 0.92	3	0.76
TC	3	0.646	3	0.66 to 0.92	3	0.89
BC	4	0.671	3	0.66 to 0.92	4	0.84
AC	3	0.630	4	0.66 to 0.92	4	0.83
PBC	2	0.733	3	0.66 to 0.92	3	0.95

Source: Own processed.

The results of t-test reveal statistically significant difference between the means of public and new private sector banks with reference to service convenience dimensions.

Decision convenience related perception of customers is found more for new private sector banks than public sector banks. The mean score for new private sector banks (M = 3.39) is significantly greater than the public sector banks (M = 3.07) at 1 per cent significant level (t = –3.768, p < .01). New private sector banks provide more decision convenience to their customers than the public sector banks. When customers come to the bank, employees provide all information required to purchase a service. Whereas, public sector banks have a large number of customers and are not able to give time and attention to their customers in comparison to their new private sector counterparts. ‘Help Desk’ in a new private sector bank helps in transaction convenience as well as decision convenience. Though, Axis bank employees are providing all relevant information to customers, an information brochure—‘Customer Information Booklet on Policies and Commitments of the Bank’—is provided at the ‘Help Desk’ for more clarity. Whenever a customer enters the bank, he or she is greeted by the ‘Help Desk’.

Table 10.

Independent Sample t-test Results Examining Differences between Public and New Private Sector Banks with Reference to Service Convenience Dimensions

Variables	Group	N	Mean	SD	Std. Error Mean	t-test	Sig (2-tailed)
DC	Public	234	3.075	.8936	.0584	–3.768**	.000
	Private	211	3.393	.8870	.0611
TC	Public	234	3.170	1.0164	.0664	–2.102*	.036
	Private	211	3.387	1.1667	.0803
BC	Public	234	3.165	1.0276	.0672	–2.257*	.024
	Private	211	3.368	.8476	.0583
AC	Public	234	3.082	.8598	.0562	–4.752**	.000
	Private	211	3.447	.7459	.0514
PBC	Public	234	2.940	.7947	.0520	–2.453*	.015
	Private	211	3.126	.8053	.0554

Source: Own processed.

Notes: *Significant at the 0.05 level; **Significant at the 0.01 level.

Findings related to transaction convenience reveal that the mean score for new private sector banks (M = 3.38) is significantly greater than the public sector banks (M = 3.17) at 5 per cent significant level (t=-2.102, p < .05). It shows that new private sector banks are perceived by customers as more transaction convenience oriented than public sector banks. Transaction convenience shows that the customer can complete his purchase easily, quickly and with less effort. New private sector banks provide this convenience in a very effective way. Transaction convenience is being given through technology and bank offices. In new private sector banks, a customer is not supposed to go from desk to desk to ask every employee for his purchase, rather employees come forward to help him complete his purchase easily and quickly. When customers visit public sector banks they are often forced to complete a bureaucratic cycle as the task of every employee is fixed and employees are found reluctant in helping customers for those problems which do not come under their jurisdiction. It may be due to both large number of customers and lack of service orientation. Unthinkable for the new private sector banks, some counters in public sector banks remain unattended during the business hours. As a result, customers remain unattended for a longer duration thereby lengthening the queue. Transaction convenience can be given to customers by employees only when the employees feel that completing a task is more important than adhering to red-tape. New private sector bank employees are found to possess this team spirit to help their customers.

It is worthwhile to mention here that in Southwest airlines, all the employees used to work together to complete a task. Sometimes pilots used to assist cabin attendants which was not part of their job.

When a large number of customers throng new private sector banks, the staff immediately increases the number of counters and customers are given prompt services in less time. On the contrary, public sector banks are not able to increase the number of counters on every occasion to reduce the customer rush due to a lack of staff.

New private bank customers are enjoying transaction convenience through technology as well. ATMs are being used for money withdrawal and deposit. Cash deposit machine is being used by new private sector bank customers so that the customers can deposit money on their own. On the one hand they are enjoying transaction convenience; on the other they are reducing the workload of employees. Some public sector bank customers are reluctant to use ATMs to withdraw cash, thereby creating rush in the bank premises. Moreover, retired/aged people are reluctant to use ATMs due to a lack of confidence in using this technology. They prefer going to the bank to interact with people and spend their time. It creates an obstacle for public sector banks in providing transaction convenience to customers.

New private sector banks are advanced in the use of information technology which facilitates transaction convenience. For example, ICICI Bank customers can use mobile phones not only to check account balances and transfer funds but also to apply for a loan (ICICI, Annual Report, 2010–2011).

For money withdrawal, new private sector bank customers have two options; the first one is cheque and the second one is ATM. Using ATMs for cash withdrawal helps in reducing rush in the branch. Public sector bank customers use cash withdrawal slip and tend to lengthen the queue in the branch. Due to an overwhelming number of customers at their branches, public sector banks do not provide transaction convenience to their customers like those being given by new private sector banks.

Customers showed higher perception regarding benefit convenience for new private sector banks (M = 3.36) than public sector banks (M=3.16). This difference is statistically significant at 5 per cent significant level (t = –2.257, p < .05). Benefit convenience considers time and effort taken to receive the benefit of service purchase. Public sector bank employees cannot expedite the service process at their discretion because of a standardized and formal pattern but new private sector banks’ employees are encouraged to expedite the service process to give benefit convenience to their customers. To get a loan sanctioned, it takes more time with public sector banks than with new private sector banks. Branch heads of new private sector banks are empowered to make decisions which ensure benefit convenience for customers. In the Southwest airlines, employees were given the freedom to do whatever was necessary to get a plane turned around in the targeted time of 15 minutes. If this sort of functional freedom is given to employees, it helps in achieving the desired objective.

According to the instructions given by the RBI, every bank should display the time required to complete different types of transactions so that customers can know whether the time required to receive the benefit is reasonable or not. New private sector banks are following it meticulously but public sector banks are not able to follow it due to high work load. New private sector banks have predefined Turnaround Time (TAT) for every transaction. When an employee opens account or prepares loan file of customer or attempts any other transaction, he feeds data in the computer and the exact time is recorded by software. Any delay in the transaction time as per TAT norms get automatically reported to his superior. In this way, new private sector bank customers are bound to complete transaction on time to give benefit convenience to customers. Public sector banks have also begun the same procedure to offer time bound benefit convenience to its customers.

Result for access convenience indicates that the mean score for new private sector banks (M = 3.44) is significantly greater than the public sector banks (M = 3.08) at 1 per cent significant level (t = –4.752, p < .01). Probably the reason can be attributed to the institutionalization of some customer friendly arrangements in the new private sector banks like the post of ‘relationship officer’ and the system of 24-hours banking convenience to customers. In this manner, they are providing better access convenience to their customers. The ATM network of new private sector banks is far wider than public s ector banks.

Post-benefit convenience related perception of customers is found more for new private sector banks than public sector banks. The mean score for new private sector banks (M = 3.12) is significantly greater than the public sector banks (M = 2.94) at 5 per cent significant level ( t = –2.453, p < .05). This result is consistent with RBI Report on Trend and Progress of Banking in India 2010–11 (2010–2011a). According to this report, there was an increase in complaints against public sector banks in 2010–11 over the previous year, whereas the number of complaints against new private sector banks witnessed a decline over the same period. It shows that new private sector banks provide a more post-benefit convenience than public sector banks. For example, HDFC bank has three levels of customer complaint handling process. At the first level, the complaint is filed through phone banking, online, at bank itself or by sending a letter. The problems are generally resolved at this level and if the customer is not satisfied, he can go to the second level and the third level by contacting the grievance redressal officer and the nodal officer respectively. In this manner the new private sector banks take proactive steps to deal with the problems of the customers and provide post-benefit convenience. Generally they try their level best to solve every query before it becomes a complaint. All banks have toll free numbers for their customers to cater to all type of problems. All complaints are registered in software and resolved at the earliest. New private sector banks have incorporated more speedy system than public sector banks. It is worth mentioning that if a customer makes any mistake like entry of wrong amount, wrong date on cheque etc., then ICICI bank has a ‘call taken’ procedure where customers are contacted and asked to rectify mistakes. ICICI phone banking provides an ‘auto-dialler’ facility through which customers can request for a call back (ICICI, Annual Report, 2010–2011). All of these steps place new private sector banks far ahead than public sector banks in terms of post-benefit convenience.

Epilogue

All types of conveniences are being enjoyed more by new private sector banks customers than by public sector bank customers. It is appropriate to review the business environment within which public and new private sector banks are operating to have a better insight about their operations. It will help in knowing the cause of difference between public and new private sector banks.

Public sector banks are suffering on account of huge human capital deficit; therefore, it is really challenging to provide convenience to customers. Public sector banks are important pillars of social responsibility programmes (pensioners account, student account, BPL account, NREGA account) and welfare oriented schemes of Government of India. One of the main functions of public sector banks is financial inclusion. Public sector banks have also been entrusted with the responsibility of giving loans to the priority sector at a relatively lower rate of interest with minimum of 40 per cent of the total loan portfolio. With so many conflicting objectives (profit making, giving service quality to customers, financial inclusion, and penetration in rural areas) public sector banks are neither in a position to satisfy customers nor in a position to make profit. These are the reasons that public sector banks are not able to provide all types of conveniences as compare to new private sector banks.

New private sector banks are burning the mid night oil to make customers happy on each and every aspect of the banking operation. New private sector banks are profit driven organizations and customer service is their top priority. Whereas it takes ₹ 500 to open an account in a public sector bank, it takes ₹ 10,000 to open an account in a private sector bank. New private sector banks are enjoying only valued customers. Though, they have received instructions from the RBI to open a no-frill account, the instruction is being followed more in breach than in practice. Similarly all government sponsored schemes are only being operated through public sector banks, leaving less time for employees to take care of their customers.

Limitations of the Study

First, this study has taken into account valued customers who visit bank premises frequently and have an account in at least two different banks. These customers are availing themselves of at least one IT-based service as well. Thus, it limits generalization of results to other banking population. Second, this study focuses on urban customers of retail banking. Therefore, results cannot be generalized for semi-urban and rural customers of retail banking. Third, this study focuses on the retail banking customers only and agriculture customers and other institutional customers are not considered in this study. Fourth, this study has considered ‘penetration of banks in Rajasthan’ for selection of banks.

Perspectives for Future Research

Regarding selection of banks, this study has considered only one criterion, ‘penetration of banks’. There is, however, scope to consider banks on other criteria. It is noteworthy to mention the role of the ‘CAMEL’ model in selection of banks. This model helps in categorization of banks based on their financial performance. Therefore, above average, average and below average banks on the basis of their financial performance may be selected. To study the difference between public sector and new private sector banks, those customers should be surveyed who have accounts in both public and new private sector banks as these customers will have more insight about the service provided by both public and new private sector banks. This study focuses on urban customers of retail banking. Therefore, further study is needed to know the differences among rural, semi urban and urban customers regarding banking services. Current study focuses on valued customers who visit the bank frequently. A comparative study is required to know the difference between valued customers and occasional customers.

Footnotes

References

Aagja

J.P.

Mammen

Saraswat

(2011). Validating service convenience scale and profiling customers: A study in the Indian retail context. Vikalpa, 36(4), 25–49.

Berry

L.L.

Seiders

Grewal

(2002). Understanding service convenience. Journal of Marketing, 66(3), 1–17.

Brown

L.G.

(1989). The strategic and tactical implications of convenience in consumer product marketing. Journal of Consumer Marketing, 6(3), 13–19.

Brown

L.G.

(1990). Convenience in services marketing. Journal of Service Marketing, 4(1), 53–59.

Campbell

D.T.

Fiske

D.W.

(1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.

Colwell

S.R.

Aung

Kanetkar

Holden

A.L.

(2008). Toward a measure of service convenience: Multiple-item scale development and empirical test. Journal of Services Marketing, 22(2), 160–169.

Copeland

M.T.

(1923). Relation of consumers’ buying habits to marketing methods. Harvard Business Review, 1(3), 282–289.

Field

A.P.

(2005). Discovering Statistics Using SPSS (2nd ed.). London: Sage Publications.

Gerrard

Cunningham

J.B.

(2004). Consumer switching behaviour in the Asia banking market. The Journal of Service Marketing, 18(2–3), 215–223.

10.

Industrial Credit and Investment Corporation of India (ICICI) Bank. (2010–2011). Innovative Solutions to Enhance Customer Experience, Annual Report.

11.

Kumar

Kalwani

M.U.

Dada

(1997). The impact of waiting time guarantees on consumer waiting experiences. Marketing Science, 16(4), 295–314.

12.

Luqmani

Yavas

Quraeshi

Z.A.

(1994). A convenience-oriented approach to country segmentation: Implications for global marketing strategies. Journal of Consumer Marketing, 11(4), 29–40.

13.

Meuter

M.L.

Ostrom

A.L.

Roundtree

R.I.

Bitner

M.J.

(2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters. Journal of Marketing, 64(3), 50–64.

14.

Milligan

J.W.

(1997). What do customers want from you: everything! US Bank, 107(12), 38–45.

15.

Park

Robertson

(2006). Modelling the impact of airline service quality and marketing variables on passengers’ future behavioural intentions. Transportation Planning and Technology, 29(5), 359–381.

16.

Peter

J.P.

Olson

J.C.

(1999). Consumer behavior and marketing strategy. NY: Irwin McGraw-Hill.

17.

Reserve Bank of India. (2010–2011a). Report on trend and progress of banking in India. Retrieved from http:/rbi.org.in

18.

Reserve Bank of India (2010–2011b). Statistical tables relating to banks in India. Retrieved from http:/rbi.org.in

19.

Seiders

Berry

L.L.

Gresham

(2000). Attention retailers: How convenient is your convenience strategy? Sloan Management Review, 49(3), 79–90.

20.

Seiders

Voss

G.B.

Godfrey

A.L.

Grewal

(2007). SERVCON: Developing and validation of a multidimensional service convenience scale. Journal of the Academy of Marketing Science, 35(1), 144–156.

21.

Yale

Venkatesh

(1986). Toward the construct of convenience in consumer research. In Lutz

R. J.

(Eds.), Advances in Consumer Research (pp. 403–408). Provo, UT: Association for Consumer Research.

22.

Zeithaml

V.A.

Bitner

M.J.

(2000). Services marketing: Integrating customers focus across the firm (2nd ed.). Boston: McGraw-Hill.

23.

Zeithaml

V.A.

Berry

L.L.

Parasuraman

(1996). The behavioral consequences of service quality. Journal of Marketing, 60(2), 31–46.