1. INTRODUCTION:

The 21^st century is considered to be technological century, slowly and gradually everything is getting online. Banking sector is one of the most influenced sectors on account of technological advances. So it becomes very important to study this sector in this technological oriented century. The pace of technological evolution is immense, leading to drastic growth and development of this sector. On account of these technologies the effectiveness and efficiency of the service offerings has enhanced (Chowdhury, 2014).

Moreover competition has increased because of the advancement and banks are forced to adapt to these technologies in order to face such tough competition (Nair, 2014). IT has altered the practices carried out in traditional banking (David H. Wong, 2008) and as a result Digital banking is the outcome of this. Thus ‘Digital banking’ is defined as offering of various banking services with the use of electronic machine or technology without time and place constrain. It is also known as non-conventional ways of banking or direct banking channel.

The main aim of banks using this non-conventional ways of banking is to offer faster and better services to customers leading to their satisfaction and retention while customers have started preferring this way of banking since the volume of transactions in global and domestic markets have increased. Thus slowly and gradually this non-conventional way of banking is increasing. According to (Singhal and Padhmanabhan, 2008) the differentiating factor between internet enabled electronic banking system and the traditional banking operation is the quicker transfer of information between the consumer and the service provider.

Many studies have been conducted taking into consideration traditional banking, but lack of research in this area with regard to digital banking motivated the researcher to carry out study in this aspect. It becomes quite interesting to study the service quality aspect of digital banking in this technological era. So the researcher tried to identify the factors that contribute towards the service quality of digital banking. So here the main aim of the researcher is to explore the relation and influence of determined variables with regard to service quality of digital banking.

2. THEORETICAL BACKGROUND:

Customers are the main factor that leads to success or failure of a bank. Customer satisfaction and their retention are crucial aspects (Vijay Kumar T, Velu R 2007); dissatisfied customers leads to customers’ bank switching behaviour (Vyas and Raitani 2014). Core and relational performances has an influence on happiness of bank consumer which is key drivers of customer satisfaction (Jamal, 2002). Further customer satisfaction is influenced by many factors from which service quality plays a vital role.

Here service quality is defined as “the outcome of an evaluation process, where the customers compare their expectations with the service they have received” (Gronroos, 1984). Increased levels of customers’ loyalty towards bank, readiness to pay, commitment and trust can be achieved by concentrating on the service quality (Hazra and Srivastava, 2009). The idea of quality of service drives beyond the technical sides of service delivery. It has more to do with what customers think about the services [N. M. Toosi, R. A. Kohanali, 2011].

Many studies concluded that perceived service quality have direct link with behavioral intentions of customers (Boulding et al., 1993; Parasuraman et al., 1988, 1991; Zeithaml et al., 1996). (Navdeep Aggarwal and Mohit Gupta, 2003) during their study to find out the primary dimensions and sub dimensions of qualities of services offered found out that time of service delivery and quality of personal interactions are very important besides ambience for qualities of services offered. Thus, the role of service quality should not be neglected in service oriented sectors particularly in banking sector.

As explained above Service quality and customer satisfaction both are important elements for success of business entity. Service quality affects the customer satisfaction in linear way. The level of customer satisfaction can be enhanced just by improving quality of their services. Many researchers have examined the association amongst expectation, perceived service quality and customers’ satisfaction so far (Zeithaml, et al, 1988) and they have found very strong association of the service quality with the customer satisfaction (Parasuraman et al, 1985; 1988). According to (Jain and Gupta, 2004), it was found out that the higher level of perceived service quality over expected service quality results in increase of customer satisfaction whereas lower level of perceived service quality over expected service quality results in to dissatisfaction of customers. Further (Nadiri, et al 2009) confirmed that improved service quality of the banks increases the satisfaction and develops loyalty that eventually retains bank’s valued customers.

Effective qualitative services are needed by customers in every aspect and this is applicable with regard to E-Banking services also. Absence of staffs’ interaction with the customers in E-Banking, so service quality is more important than to off-line services. (Ibrahim EE, 2006) tried to find out the dimensions of electronic service quality and found out that Convenient and accurate electronic banking operations, accessibility and reliability, good queue management, service personalization, friendly and responsive customer service and targeted customer service are dimensions of electronic service quality. Thus service quality cannot be neglected with regard to digital banking.

3. MODEL DEVELOPMENT:

Based on the rigorous literature review and study of several model, seven factors have been identified to evaluate service quality. Views of customers using digital banking service on these seven factors and their suggestions were taken to finalize the model. Moreover few bank employees associated to service delivery through branch banking channel or digital banking channel were also approached to understand their views on the same. After the rigorous process the model with seven (7) factors have been derived and discussed below.

3.1 Materiality:

The quality of the contents and information of the Digital Banking Channel is being evaluated in the factor named “Materiality”

3.2 Accessibility:

It is important that Digital Banking services are available and accessible to the customers when they need to avail the services in order to bring more and more customers to the Digital Banking platform.

3.3 Complexity:

In Digital Banking Services customers uses the banking services on their own without any direct interaction with the Bank staff. It is a kind of self – service. Rogers (1995) defined complexity as difficulties faced by persons in using new technologies.

3.4 Competence:

Competences of Digital Banking Services for accessing the bank account and executing transactions determine the service quality and affect the customer satisfaction. Qualities of basic proficiencies are being checked in the factor “Competence”.

3.5 Assistance:

Assistance is the support provided by the banks from the back end on various matters. It includes the support for pre and post operating support as well as support for operating Digital Banking Services.

3.6 Security:

Digital Banking services are basically offered through information technology and internet services. The entire data of banks is now online Security factor checks the level of safety of customers’ data and money.

3.7 Connectivity:

Digital Banking services are based on internet technology where in the devices being used to get the services get connected with the banks servers through internet. It has significant impact over the customers in terms of satisfaction as well as intention to use the Digital Banking services.

4. RESEARCH METHODOLOGY:

4.1. Research Design:

(Aaker et al, 2001) defined research design as the detailed outline of the study which helps in achievement of the research objectives and decisions related to research process and data collection methods used. It is basically the conceptual structure of the research within which the entire research work is to be carried out. Research design shall answer the six Ws and one H (What, Why, When, Where, Who, Which and How) for the research work. Descriptive research design is mainly applied where the researches wants to improve on existing work. So here in this study, the researcher has used descriptive research design.

4.2. Sampling Design:

Sampling Design refers to the methods and techniques used for selection of samples. It shows the detailed plan for selection of samples from the universe

4.2.1. Universe and Target Population:

The research is to identify the factors influencing the service quality of the Service Quality of Digital Banking services; hence the universe of the population is the customers using the Digital Banking services across the world

4.2.2. Sampling Techniques:

In this study, the researcher has used quota sampling in which the population is divided in different segments according geographic location and selected banks

4.2.3. Sample Size:

Sample size has been determined by using the standard model for sample size;

Sample size = z²*(p)*(1-p)/c²

Where,

z = z value (1.96) for 95% confidence level

p = percentage of probability of picking up a choice expressed as decimal c = confidence interval

Hence the total sample size has been decided 900 divided in to 400 customers from public sector, 400 customers from private sector banks and 100 customers from foreign banks as number banks as well as customers are very less in number for foreign banks.

4.3. Data Collection:

Data have been collected through survey method, where structured questionnaire is used as an instrument

4.4. Reliability of scale:

Reliability of the scales was checked by computing cronbach alpha, a measure of reliability which found to be satisfactory. All the variables’ coefficient of alpha was above 0.6 specifying a satisfactory internal consistency (Nunnally, 1978).

Table – 4.1 Sampling Frame

	Public Sector Banks				Private Sector Banks				Foreign Banks
City	SBI	BOB	PNB	BOI	HDFC	AXIS	ICICI	Kotak	Citi Bank	Standard Chartered
Ahmedabad	25	25	25	25	25	25	25	25	20	15
Vadodara	25	25	25	25	25	25	25	25	20	15
Surat	25	25	25	25	25	25	25	25	10	10
Rajkot	25	25	25	25	25	25	25	25	NA	10
Total	100	100	100	100	100	100	100	100	50	50

Table 4.1. Reliability for Factors

Factor	No. of Items (Constructs)	Cronbach’s Alpha (α)
Applicability	6	0.894
Accessibility	8	0.888
Complexity	8	0.899
Competence	6	0.890
Assistance	6	0.886
Security	5	0.853
Connectivity	5	0.926

4.5. Sample Characteristics:

Sample characteristics specifies that majority of the respondents were male (68%) and falls in the age group of 20-30 years (46%). When occupation is considered almost 39% of the respondents were private job. Educational qualification specified that majority had U.G. level education (38%) and income level showed that majority have income up to Rs.25000 (38%). Further majority of respondents have their account SBI bank and use their digital platform and mostly use the digital platform on weekly basis.

Table 2: Sample Characteristics of the study

Variable	Categories	Frequency	Percentage
City	Ahmedabad	578	56.17%
	Vadodara	248	24.10%
	Rajkot	96	9.33%
	Surat	107	10.40%
Age	20-30 years	469	45.58%
	30-40 years	342	33.24%
	40-50 years	143	13.90%
	50years and above	75	7.29%
Gender	Male	696	67.6%
	Female	333	32.4%
Occupation	Govt. job	297	28.86%
	Private Job	400	38.87%
	Business	112	10.88%
	Professional	40	3.89%
	Retired	18	1.75%
	Others	162	15.74%
Education	U.G.	386	37.51%
	Graduate	146	14.19%
	Post graduate	301	29.25%
	Professional	168	16.33%
	Others	28	2.72%
Personal Income(Monthly)	Up to 25000	386	37.51%
	Rs.25001-50000	146	14.19%
	Rs.50001-75000	301	29.25%
	Rs.75001-100000	168	16.33%
	Above 100000	28	2.72%
Banking with (for digital banking platform)	SBI	133	12.93%
	BOB	104	10.11%
	PNB	80	7.77%
	BOI	73	7.09%
	HDFC	116	11.27%
	ICICI	134	13.02%
	AXIS	168	16.33%
	KMBL	91	8.84%
	CITI	57	5.54%
	SCB	73	7.09%
Vintage with the Bank	Less than 1 year	45	4.37%
	1 year to 2 years	482	46.84%
	More than 2 years	502	48.79%
Frequency of usage of digital banking channel	Daily	80	10%
	Twice a week	153	7.77%
	Weekly	617	14.87%
	Fortnightly	152	15%
	Monthly	27	12%

5. DATA ANALYSIS:

Correlation is a statistical relationship between two variables which shows the dependence of dependent variable on the independent variables. Pearson’s correlation coefficient is the most widely used correlation coefficient to indicate linear relationship between two variables. In this study the researcher has applied Pearson’s correlation to check the relationship among the factors affecting the overall satisfaction of the customer related to digital banking services. Summated score of all the constructs for a factor is used as the value of the factor for checking correlation.

Table 5.1. Correlation

		MT	AC	CX	CT	AS	SC	CY	IM
MT	Pearson Correlation	1	.653**	.618**	.582**	.534**	.536**	.461**	.655**
	Sig. (2 tailed)		.000	.000	.000	.000	.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
AC	Pearson Correlation	.653**	1	.676**	.626**	.517**	.541** .	.614**	.725**
	Sig. (2 tailed)	.000		.000	.000	.000	.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
CX	Pearson Correlation	.618**	.676**	1	.557**	.633**	.643**	.567**	.753**
	Sig. (2 tailed)	.000	.000		.000	.000	.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
CT	Pearson Correlation	.582**	.626**	.557**	1	.335**	.464**	.437**	.580**
	Sig. (2 tailed)	.000	.000	.000		.000	.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
AS	Pearson Correlation	.534**	.517**	.633**	.335**	1	.590**	.540**	.793**
	Sig. (2 tailed)	.000	.000	.000	.000		.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
SC	Pearson Correlation	.536**	.541**	.643**	.464**	.590**	1	.477**	.759**
	Sig. (2 tailed)	.000	.000	.000	.000	.000		.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
CY	Pearson Correlation	.461**	.614**	.567**	.437**	.540**	.477**	1	.718**
	Sig. (2 tailed)	.000	.000	.000	.000	.000	.000		.000
	N	1029	1029	1029	1029	1029	1029	1029	1029
IM	Pearson Correlation	.655**	.725**	.753**	.580**	.793**	.759**	.718**	1
	Sig. (2 tailed)	.000	.000	.000	.000	.000	.000	.000
	N	1029	1029	1029	1029	1029	1029	1029	1029

**. Correlation is significant at the 0.01 level (2-tailed).

Table 5.2. Hypotheses Testing

Variable	Null Hypothesis	Correlation Coefficient	Sig. value	Decision
Materiality	H0: There is no significant relationship between overall Materiality and overall impact of service quality of the Digital Banking services.	0.655	0.000	Null hypothesis is rejected.
Accessibility	H0: There is no significant relationship between overall Accessibility and overall impact of service quality of the Digital Banking services	0.725	0.000	Null hypothesis is rejected.
Complexity	H0: There is no significant relationship between overall Complexity and overall impact of service quality of the Digital Banking services.	0.753	0.000	Null hypothesis is rejected.
Competence	H0: There is no significant relationship between overall Competence and overall impact of service quality of the Digital Banking services.	0.580	0.000	Null hypothesis is rejected.
Assistance	H0: There is no significant relationship between overall Assistance and overall impact of service quality of the Digital Banking services.	0.793	0.000	Null hypothesis is rejected.
Security	H0: There is no significant relationship between overall Security and overall impact of service quality of the Digital Banking services.	0.759	0.000	Null hypothesis is rejected.
Connectivity	H0: There is no significant relationship between overall Connectivity and overall impact of service quality of the Digital Banking services.	0.718	0.000	Null hypothesis is rejected.

Correlation coefficient value is positive for all independent variables leading to rejection of null hypothesis. According to the coefficient values Competence has the least effect on the overall impact comparing to the other variables whereas Assistance has the highest effect on the overall impact.

6. FINDINGS:

Findings have been summarized as follows:

Materiality:

With correlation coefficient of 0.655 and sig. 0.000 strong positive linear correlations between Materiality factor and overall service quality has been established. Change of 1 point in the Materiality will affect 0.655 points in overall service quality.

Accessibility:

With correlation coefficient of 0.725 and sig. 0.000 very positive linear correlations between Accessibility factor and overall service quality has been established. Change of 1 point in the Accessibility will affect 0.725 points in overall service quality.

Complexity:

With correlation coefficient of 0.753 and sig. 0.000 very strong positive linear correlations between Complexity factor and overall service quality has been established. Change of 1 point in the Complexity will affect 0.753 points in overall service quality.

Competence:

With correlation coefficient of 0.580 and sig. 0.000 strong positive linear correlations between Competence factor and overall service quality has been established. Change of 1 point in the Competence will affect 0.580 points in overall service quality.

Assistance:

With correlation coefficient of 0.793 and sig. 0.000 very strong positive linear correlations between Assistance factor and overall service quality has been established. Change of 1 point in the Assistance will affect 0.793 points in overall service quality.

Security:

With correlation coefficient of 0.759 and sig. 0.000 very strong positive linear correlations between Security factor and overall service quality has been established. Change of 1 point in the Security will affect 0.759 points in overall service quality.

Connectivity:

With correlation coefficient of 0.718 and sig. 0.000 strong positive linear correlations between Connectivity factor and overall service quality has been established. Change of 1 point in the Connectivity will affect 0.718 points in overall service quality.

All the seven factors have significant impact over the service quality of the Digital Banking Services.

7. LIMITATIONS OF THE STUDY:

· The study was carried out in four cities of Gujarat due to constraint of time and expenses.

· The study has been conducted only for those who are using Digital Banking services for more than six months.

· Customers of selected banks only have been contacted in order to collect data,

· Customers in rural areas have not covered under the study.

8. FUTURE SCOPE OF RESEARCH:

There is further scope of validation of the mentioned model taking into consideration different geographical locations and with different banks. Comparative study of service quality and customer satisfaction with respect to the Digital Banking services can be carried out.

10. IMPLICATION OF THE STUDY:

Understanding with regard to the important aspects of service quality related to digital banking will be enhanced, which will further help the strategy formulators in framing effective strategies. Thus this will help in retaining the customers which will enhance their satisfaction and loyalty.

11. CONCLUSION:

Technology has started altering the traditional forms of businesses and banking sector is one of the most influenced sectors on account of this. In order to sustain in the new technologically challenging and highly competitive market, the banks need to have superior products and best-in-class technologies. Digital Banking services act as a shield for banks. So it is very important that customers adapt and use these services on continuous basis for which effective service quality offering is mandate. Banks should attract the customers to accept Digital Banking services by improving on service quality aspect. In order to get success acceptance of these services by the customers is not just sufficient but complete migration of customers onto Digital Banking platform is required. For this effective service offerings is required focusing on good quality leading to customer retention and their satisfaction. Thus, service quality of the Digital Banking services is very crucial for banking sector.

12. REFERENCES:

1. Benamati S. and Serva K. (2007), “Innovation Characteristics and Innovation Adoption Implementation: A Meta-Analysis of Findings’’, IEEE Transaction of Engineering Management, Vol. 29, pp. 34-52.

2. Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation–-confirmation model. MIS Quaterly, 25(3), 351-370.

3. Bitner, M. B. (2000). Technology infusion in service encounters. Journal of the Academy of Marketing Science, 28(1), 138-149.

4. Black, N, J. Lockett, A. and Ennew, C. (2001), “The adoption of internet financial services: a qualitative study”, International Journal of Retail and Distribution Management, 29(8), pp. 390-398

5. Boulding, W., Kalra, A., Stalein, R. and Zeithaml, V.A. (1993), “A Dynamic Process Model of Service Quality: From Expectations to Behavioural Intentions”, Journal of Marketing Research, Vol. 30, February, pp. 7-27.

6. Chen and Chen, (2009), “Determinants of Satisfaction and Continuance Intention Towards Self-Service Technologies”, Industrial Management & Data Systems Vol. 109 No. 9, 2009 pp. 1248-1263

7. Gronroos, C. (1984), “A service quality model and its marketing implications”, European Journal of Marketing, 18(4), 36-44

8. Hazra, S.G. and Srivastava, K.B.L. (2009), “Impact of Service Quality on Customer Loyalty, Commitment and Trust in The Indian Banking Sector”, ICFAI Journal of Marketing Management, Vol. 3 Nos 3/4, pp. 75-95.

9. Howcroft, M. D. (2003). Relationship marketing in baking sector: the impact of new technology. Marketing Intelligence & Planning, 21(1), 61-71.

10. Ibrahim, E.E. (2006), “Customers’ Perception of Electronic Service Delivery in the UK Retail Banking Sector”, International Journal of Bank Marketing, Vol. 24, No. 7, pp. 475-493

11. Jaspal Singh, Gagandeep Kaur (2011), “Customer Satisfaction and Universal Banks: An Empirical Study”, International Journal of Commerce and Management Vol. 21 No. 4, 2011

12. Nunnally, J. (1978). PsychometricTheory.

13. Parasuraman, A. Z. (1985). “A conceptual model of service quality and its implications for future research”. Journal of Marketing, 49(3), 41-50.

14. Prof.N.M.Nair. (2014, March). Role of Information Technology in Banking Sector in India. IBMRD's Journal of Management and Research, 3(1).

15. Robbins, E. (2006, September). Location, Location, Location: Has Electronic Banking Affected the Importance of Bank Location? FINANCIAL INDUSTRY PERSPECTIVES.

16. Shuiqing Yang, Y. L. (2013). Why do consumers adopt online channel? An empirical investigation of two channel. Decision Support Systems, 54(2), 858-869.

17. Vijay Kumar T and Velu R (2007), “Critical Determinants of Customer Satisfaction in Retail Banking in India”, SONO School of Management Journal, Vol. 2, November 2007, pp 25-30

18. Vyas, V. and Raitani, S. (2014), “Drivers of Customers’ Switching Behaviour in Indian Banking Industry”, International Journal of Bank Marketing, Vol. 32 No. 4, pp. 321-342

Received on 31.10.2018 Modified on 13.11.2018

Int. J. Rev. and Res. Social Sci. 2018; 6(4): 486-491 .

DOI: 10.5958/2454-2687.2018.00047.3