Analyzing the digital divide among the demographics in the State of Telangana with reference to adoption of Digital Banking services.

Abstract

The digitalisation of banking services is certainly a positive note that reduces the fatigue of the customers by operating their transactions through their mobile gadgets and other electronic instruments using the internet. However, the research literature demonstrates that Digital initiatives not only has positive connotation but has created a digital divide among the demographics across the communities (Benda et al, 2011) the studies also show evidence that there exists a huge gap among age groups, gender, income levels and socio-cultural groups in availing digital technologies in financial,especially the banking sector (Upadhyaya, L., et al, 2018).

The present study is an attemptwhich focuses on understanding the changing and existing phenomenon of banking with special reference to Digitalisation and the adoption process of these new technologies by customers. The study mainly takes the constructs from Technology acceptance Models to test whether there exists any digital divide among the demographics in the study.

Introduction

In the last few years, The Banking Industry witnessed a gigantic move towards Digitalization. The Traditional mode of banking activities is experiencing a hyper-personaliseddigital-first approach. The banking industry also focused on boosting return on equity and bringing down the cost-to-income ratio to keep themselves in competition. The banks have been proving to face new entrances in their business space,like google, amazon and other technology companies entering intofinancial service. Banks see it as a new threat to their business with these new entrants in the financial transaction space. The changing environment and other external factors have facilitated the new entrants to boost their businesses. This accelerated environment changed customer behaviour and adaptation of new tools and technologies in the banking sector.

One of the surveys (Deloitte Insights) in the Banking Sector revealed that customers are reluctant to visit branches and they are inclined to opt out of newer tools to make their transactions which impacts the closer of Banks outlets at an unprecedented scale. The city Bank and JP Morgan are some examples in the banking sector that shut their branches to a reduced flow of customers due to changing behaviours of Customers shifting towards Digital Banking Technologies in the US.

Banking Industry needs to replace many of its Traditional methods of existing customers' transactions and interactions with the Bank by augmenting improved use of Technologies. Banks need to strive its channels to ensure seamless and superior services across the Channels. Traditionally, Banks have had systematised channels with customised workflow and support. This mechanism, over a while, leads to inherently inefficient and broken customer and banking staff dissatisfaction and increased costs. The banks need to re-engineer their platforms to build channels through digital Technologies. Customers expect increased dynamism at the front end. The Existing Banking systems are monolithic and lead to potential delays in implementing the changes in the Banking system. The banks should focus on decoupling their existing monolithic approach to compete with Digital only Banks (Newman, Sam-2015).Banks should alter their processes through financial re-engineering through technologies.

The existing Data policies in Banking are rigid and have no access to the third party until now banks did not require any data to share with competitors or other service providers. Some banks used their data to improve their product and services. However, the Digitalisation of the Banking sector requires sharing the database with a third party in providing better Digi banking services to its customers. The same was experienced by the European banks in data sharing with the customer's consent (O’Flaherty, K. W., et al.).

Technology-driven banking sector requires a “one size fits all” approach by cross-selling and recommending products to the customers on a bigger scale, financial penetration and reduced interactions by using data to provide a personalised customer experience in banking services (Allen, F., Gu, X., &Jagtiani, J.). Service providers analyse by integrating different kinds of customer data like demographic, transactions, interaction, behaviour and application usage etc. Banks can provide and create a unique experience for their customers. At the same time customers also expect privacy, security, trust, perceived advantage, perceived use and cared interactions while dealing with digital channels.

Digital infrastructure, the internet of things, digital awareness and a model of digit framework are prerequisites for the Digitalisation of Banking services. The government policy should also facilitate promoting digital services to its customers. The services providers of Digital banking products should address risk management and provide trust and other security-related matters to their customers to adopt Digital Banking Services.

Review Of Literature:

The review of the literature focuses on understandingthe conceptual framework and the research done in a specific area of the study. The following reviews mainly stick to perceptions of the customers and factors influencing consumer Behaviour in adopting Digital Banking services and other related areas of the study concern.

Bailey, A. A et al., (2020) conducted a study focusing on factors influencing the use of tap-and-go payment technology by US millennial consumers. The study found that the use of mobile phones has increased tremendously and found that perceived risk, socio-cultural influence and System risk may be affecting mobile payment adoptions among US millennial customers.

BezaMucheTeka and David McMillan(2020) adopted Structural Equation Model(SEM) to understand the factors influencing the usage of electronic banking in Ethiopia. The results of the study revealed that perceived behavioural control, subjective norms, behavioural intention attitude towards perceived usefulness, perceived ease of use and awareness, and internet connections have a significant positive effect on customers' behaviour in the adoption of e-Banking, while perceived risk has a negative influence.

Vinitha, K et al., (2017) analysed three variables like Perceived Benefits, perceived enjoyment and perceived credibility, where the first variable perceived benefit has a positive impact leading to the other two Variables. The perceived benefit has a greater emphasis on study leading to the biggest contribution in influencing the intention of the customers in adopting Digital Payment.

Barkhordari, M et al., (2017) emphasised the influence of Internet Technology on enhancing the operational performance of Banking Sector capabilities. The major concern of the internet banking system is the perceived risk and trust of Costumers.

Yadav, R et al., (2015) research posits that Subjective Norms, Attitude, Perceived Usefulness and Perceived Behavioural Control have a significant influence on the intention of customers in adopting Internet Banking services among the Youth in India.

Barquin, S., & Hv, V. (2015) in their survey found that most of the customers in Developed Asia are seeking specific features like Loyalty programmes, and discounts offered through mobile devices while selecting their portfolios using Digital Banking Services.

Ansong, A at al., (2011)investigated the perceptions of the customers in Ghana towards the adoption of innovative banking products in their Banks. The study focused on a sample of 288 students for the survey and revealed that convenience, security and Reliability,Flexibility, Ease of Use, and Time-Saving have an impact on customers' perception of adopting Innovative products in Banking. The demographic variable like females dominates males in the usage of Innovative products in Ghana.

Vasanthakumari, H et al., (2011) examined Customer perception by considering 304 respondents to measure service quality in the Banking Sector. The study mainly focused on analysing Five factors namely, "Service", "Tangibles", "Reliability", "Time Duration" and "Growth", considering the demographic variables of customers.

Tat, H. H et al., (2008)analysed data collected from 204 respondents in Malaysia and found that factors like Trust, perceived ease of use and perceived usefulness have a considerable effect in predicting the intentions of Customers in Malaysia in adapting Internet Banking

Chau, P. Y et al., 2003) investigated the factors influencing the acceptance of Internet Banking in Hong Kong. The study considered 167 respondents and analysed Perceived Usefulness and Perceived Ease of Use towards acceptance of Internet Banking.

Tan &Teo,( 2000) have discussed factors Influencing Internet Banking and opined that thererequired Internet connectivity to connect Customers with banks in delivering digital financial services effectively.

Objectives Of The Study:

The main objectives of the present study are

1. To analyse the factors influencing the adoption of Digital Banking services concerning demographic variables.

2. To understand the importance of Digital Banking services in this Technology driven Scenario.

Statement Of The Problem

Research about the Banking sector in adopting Digital Banking services is significant but when focused on the Geographic boundaries of Telangana State the study is very minimal. The literature and the research about Developed and Developing countries have identified Digital Divide among the customers in usage of Digital Technologies. The studies suggest that there should be a systematic and step-by-step approach to adopting Digitisation to implement effectively (Cornford,J et al 1996), especially in remote rural areas. It is also evident that income, social status and digital infrastructure (Flensburg, S., & Lai, S. S.), and policies play a vital role in the implementation of Digital Financial Services from the supply point of view. This study is an attempt to understand different factors influencing digital financial services among customers in the State of Telangana.

Research Methodology

Hypothesis:

H₀₁

There is no significant difference in factors influencing customers’ behaviour in adopting Digital banking based on Gender.

H₀₂

There is no significant difference in factors influencing customers’ adoption of Digital banking based on Age.

H₀₃

There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Education.

H₀₄

There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Employment Status

H₀₅

There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking among the existing users and Non-users of Digital Banking services.

Analysis Of Data

The Table I of the study explains the Demographic variables considered in the study. The Demographic variables include Gender, Age, Education and Employment Status. The Total of 107 responses isreceived by distributing a questionnaire to study the factors influencing the adoption of Digital Banking services.

Based on Gender47.7% are Female and 52.3% are Male respondents given their responses. When comparing data on Age wise composition 53.3% are of 18–27 years, 19.6% are 28–37 years age, 16.8% are 38–47 years age group and 10.3% are above 48 years. Education Qualifications ranging from Degree to PhD are considered under the study. The majority of the respondents are having the educational qualification of a Master with51.4%,26.2% with a PhD, 18.7% with Degree and 4.7% are having diploma degree as an educational qualification.

When Employment status is considered the student group is predominant with 54.2%, salaried is 33.6%, self-employed are 6.7%, Retirees and others comprise 4.7% and 0.9% respectively.

Table.2 indicates the opinion of the respondents when asked about the importance of the essentiality of new digital banking services that are advancing due to rapid changein Technologies and their application in the Banking Sector. The Majority, 58%,said that the new digital technologies are essential and 18% opined that New Technologies in Banking System are Vital while 14% expressed as Desirable. In comparison, 10% of the respondents said they could not say exactly. The overall opinion of the respondents supports that new technologies and innovations resulting in Digital Banking services are essential in the present lifestyle.

The Fig. 1 of the study explains different reasons the respondents are finding it difficult to use digital banking services. The majority, 37%,have digital banking services that are challenging while using the technologies, and 25% of the respondents expressed that there is no accessibility of outlets to avail digital banking services. It is a notable point that there should be enough digital infrastructure facility in both customer’s point as well as the agents of service providers. Only 15% have said safety and security issues using digital financial services.

Usage of Digital banking modes by Respondents like Mobile banking. Online Banking, ATM banking, Agency Banking, Client Contact Centre and Mobile Applications.

The table.4 shows the number of products and digital banking services the respondents are availing of. The wide number of respondents ranging to 58%, are using at least two products,and 37% are using online banking, ATM,s Mobile Banking, and Agency banking 28%,23% and 6% respectively.

Opinion of Respondents seeking to Adopt Digital Banking if the following provisions are made.

Table .5 of the analysis represents the opinion of the respondents seeking provisions to utilise digital-related services. The majority expressed that the cheaper cost of using Digital banking technologies, greater security and safety and free training are the aspects that customers are seeking in adopting Digital Banking services. If provided the above provisions, the customers will have effective utilisation of Digital Banking services to opt for and also can expect growth of Digital services reaching a wide range of customers across the State.

Analysing the factors influencing Digital Banking Services:

Discussion

The analysis of the study from Table 6.1 to Table 6.5 explains different factors influencing customers’ behaviour on the adoption of Digital Banking Services concerning Demographic variables like Gender, Age, Education and Employment status. ANOVA test is conducted to analyse factors like Relative Advantage, Compatibility, Complexity, Triable, Perceived ease of Use, Perceived Usefulness, Social Norms, Security & Trust and Awareness, which are tested with Demographic Variables.

ANOVA test is executed by formulating a null Hypothesis based on the objectives of the study at a 95% level of significance. The rule for accepting the Null Hypothesis is that the “p” value or “Sig” value should be > 0.05 at a 95% level of significance. If the Sig value results in less than 0.05 then Reject H₀: Null Hypothesis. In table 6.1 the factors are tested with Gender and all the factors resulted in > 0.05 except for factor Complexity. This means that there is a significant difference when referring to complexity among males and females in adopting Digital Banking Products and services. The complexity factor explains that there is a mean difference concerning the opinion of the respondents expressing that there is a lot of thinking involved and requires a lot of mental stress in using Digital Banking products and services.

Table .6.2 describes and tests Null Hypothesis H₀₂ assuming thatThere is no significant difference in factors influencing customers in the adoption of Digital banking based on Age. The null hypothesis is accepted for all the variables. The "Sig" value for all the Tested variables is > 0.05 at a 95% level of significance. There is no significant difference in factors influencing when compared between Age groups.

Above table 6.3 tests Null hypothesis H₀₃ that There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Education. The derived “p” value or “Sig” values are > 0.05 except for Compatibility. We accept all other Null Hypothesis factors except for Compatibility. This means that Customers with different Educational qualifications have opined that the existing Digital Banking services’ suitability varies with their lifestyle and customisation is required to fit well to manage their finances.

Table 6.4 explains the ANOVA test with Null Hypothesis H₀₄ that There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Employment Status. The derived “p” value “Sig” values are > 0.05 except forSocial Norms. This means that there is significant variation in mean scores among the Employment Groups, showing the influence of friends, family members and colleagues in adopting Digital Banking Services among the Employment Status categories.

Table 6.5 tests the Null Hypothesis considering the current Users and Non- users of Digital Banking products and Services. This analysis is made to test the overall impact of Factors restricting non-users to restrain from Digital Banking irrespective of the Demographic variables. The Null Hypothesis for all the factors is accepted, where the Statistical Sig Value is > 0.05 except for Complexity with a value of 0.028. This means that overall the respondents expressed that the suitability of the Existing product to their lifestyle and the procedural process is a bit difficult. This may be the main reason that restrains them from opting for Digital services effectively.

Finding Of The Study

Based on the discussion, the following major findings are revealed.

• The study shows that the majority of the factors like Relative Advantage, Compatibility, Triable, Perceived Ese of Use, Perceived Usefulness, Security & Trust and Awareness have a positive influence when compared among the Users and Non-users of Digital Banking Services.

• The study has a difference in mean scores in response to factors influencing Digital Banking when compared with categories based on Demographic Variables

• When analysing respondents, both existing Users and Non-Users of Digital Banking, it is found that the Complex nature of Digital Banking is hindering them from adopting Digital Services. the results of the study, when compared based on Gender, the same kind of results are found. Among the Genders Group males and females, there is a difference in Complexity.

• Compatibility varies concerning demographic Factors and Educational Qualifications. The suitability or fit of digital products and Services differ among the groups of customers based on their qualifications.

• The influence of Social Norms is not the same concerning groups tested based on their Employment Status. The respondents with different professions have different means for the influence of their friends, colleagues and Family members in adopting Digital Banking services.

• The overall Respondents express that Digital Banking Services are essential and they are willing to adopt them when certain provisions are provided.

Conclusion

In general, any innovation in the market has lower penetration in the initial stage of its introduction and requires suitable strategies to implement effectively. Many times customers watch and wait for the suitability of the product or service in adopting. The study revealed that the majority of the factors influencing Digital Banking among Users and Non-Users have no significant differences and have a positiveinfluence on customers’ attitudes toward adopting Digital Banking Services. When compared among the demographic variables, there exist differences in influencing factors on the adoption of Digital Banking.It is also evident from the findings that there exist differences among the respondents in fully augmenting the Digital Banking services for Complexity. Since Digital Innovations in Banking deal with financial matters, customers will have a stringent approach to augmenting Digital Innovations in Banking. Most of the Digital applications designed to ensure security features in banking have complexity in their operational procedure. This results in difficulty for many Banking customers in making digital services as an opt decision. The operators of Digital services should consider the divergence of respondents based on different segments and design customised digital services and ensure product service suitability. The operational complexity can be reduced by reengineering or redesigning digital products to have ease of access and make Transactions without compromising security issues.

Declarations

Conflict of interest statement:

The authors have no conflicts of interest. I agree and declare with the contents of the manuscript and there is no financial interest to report. I certify that the submission is original work and is not under review at any other publication.

References

1. Allen, F., Gu, X., & Jagtiani, J. (2020).A Survey of Fintech Research and Policy Discussion.
2. Ansong, A., Marfo-Yiadom, E., & Ekow-Asmah, E. (2011). The effects of financial innovation on financial savings: evidence from an economy in transition. Journal of African Business, 12(1), 93–113.
3. Arnum, E. (1998). and Sergio Conti. Internet Deployment Worldwide: The New Superhighway Follows the Old Wires, Rails, and Roads. Paper presented at the INET ’98, Geneva, Switzerland, July 21–24. Available from http://www.isoc.org/inet98/proceedings/5c/5c_5.htm
4. Awamleh, R., & Fernandes, C. (2006). Diffusion of internet banking amongst educated consumers in a high-income non-OECD country. Journal of Internet Banking and Commerce, 11(3), 2.
5. Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2020). Exploring factors influencing US millennial consumers’ use of tap-and-go payment technology. The International Review of Retail Distribution and Consumer Research, 30(2), 143–163.
6. Banga, K., &te, & Velde, D. W. (2018). Digitalisation and the Future of Manufacturing in Africa. Overseas Development Institute, London.
7. Banga, R. (2019). Is India Digitally Prepared for International Trade? Economic and Political Weekly, 54(5).
8. Barkhordari, M., Nourollah, Z., Mashayekhi, H., Mashayekhi, Y., & &Ahangar, M. S. (2017). Factors influencing adoption of e-payment systems: an empirical study on Iranian customers. Information systems and e-business management, 15(1), 89–116.
9. Benda, P., Havlicek, Z., Lohr, V., & Havránek, M. (2011). ICT helps to overcome disabilities. AGRIS on-line Papers in Economics and Informatics, 3(665-2016-44817), 63–69.
10. BezaMucheTeka, D. (2020). Factors affecting bank customers usage of electronic banking in Ethiopia: Application of structural equation modelling (SEM). Cogent Economics & Finance, 8(1), 10.1080/23322039.2020.1762285. ).
11. Chau, P. Y., & Lai, V. S. (2003). An empirical investigation of the determinants of user acceptance of internet banking. Journal of organizational computing and electronic commerce, 13(2), 123–145.
12. Chawla, D., & Joshi, H. (2017). Consumer perspectives about mobile banking adoption in India–a cluster analysis. International Journal of Bank Marketing.
13. Chen, M. C., Chen, S. S., Yeh, H. M., & Tsaur, W. G. (2016). The key factors influencing internet finances services satisfaction: An empirical study in Taiwan. American journal of industrial and business management, 6(6), 748–762.
14. Cheng, T. E., Lam, D. Y., & Yeung, A. C. (2006). Adoption of internet banking: an empirical study in Hong Kong. Decision support systems, 42(3), 1558–1572.
15. Chiu, J. L., Bool, N. C., & Chiu, C. L. (2017). Challenges and factors influencing initial trust and behavioural intention to use mobile banking services in the Philippines. Asia Pacific Journal of Innovation and Entrepreneurship.
16. Dash, M., Bhusan, P. B., & Samal, S. (1970). Determinants of Customersâ   Adoption of Mobile Banking: An Empirical Study by Integrating Diffusion of Innovation with Attitude. The Journal of Internet Banking and Commerce, 19(3), 1–21.
17. Demirdogen, O., Yaprakli, S., Yilmaz, M. K., & Husain, J. (2010). Customer risk perceptions of internet bankıng–A study in Turkey.Journal of Applied Business Research (JABR), 26(6).
18. Dermine, J. (2016). Digital banking and market disruption: a sense of déjà vu? (p. 17). FSR FINANCIAL.
19. Divya Singhal, & Padmanabhan, V. (2008). “ A study on customer perception towards internet banking: Identifying major contributing factors”, The Journal of Nepalese Business Studies, Vol. V, No.1, Dec 2008
20. Graham, S., Cornford, J., & Marvin, S. (1996). The socio-economic benefits of a universal telephone network: A demand-side view of universal service. Telecommunications Policy, 20(1), 3–10.
21. Newman, S. (2015). Building microservices: designing fine-grained systems. " O'Reilly Media, Inc.".
22. Nguyen, T., & Phuong Dang, T. (2018). Digital banking in Vietnam's current situation and recommendations. International Journal of Innovation and Research in Educational Sciences, 5(4), 418–420.
23. Nyangosi, R., & Arora, J. S. (2011). Antecedents and obstacles to e-banking adoption: a comparative study of India and Kenya. International Journal of Indian Culture and Business Management, 4(2), 123–137.
24. O'flaherty, K. W., Stellwagen, R. G. Jr., Walter, T. A., Watts, R. M., Ramsey, D. A., Veldhuisen, A. W., & Ozden, R. K. (2001). U.S. Patent No. 6,253,203. Washington, DC: U.S. Patent and Trademark Office.
25. Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, 404–414.
26. Tan, M., & Teo, Thompson, S. H. (2000). "Factors Influencing the Adoption of Internet Banking,"Journal of the Association for Information Systems: Vol. 1:Iss. 1, Article 5.
27. Tat, H. H., Nor, K. M., Yang, E. T., Hney, K. J., Ming, L. Y., & Yong, T. L. (2008). Predictors of intention to continue using internet banking services: An empirical study of current users. International Journal of Business and Information, 3(2), 233–244.
28. Vasanthakumari, H., & Sheela Rani, S. (2011). Customer Perception of Service Quality in the Retail Banking Sector”. European Journal of Business and Management, 3(3), 299–306.
29. Upadhyaya, L., Royburman, R., Sangeetha, V., Lenin, V., Sharma, J. P., & Dash, S. (2018). Factors affecting digital divide in ICT-led agricultural information delivery: A comparative analysis.

Tables

Table:1 Showing Demographic Variables and their Percentages. 

Source: Primary Data

Table .2: Opinion of the Respondents on Digital Banking as a new system of delivering banking services. 

Source: Primary Data

Table.4 Usage of Digital banking modes by Respondents like Mobile banking. Online Banking, ATM banking, Agency Banking, Client Contact Centre and Mobile Applications.

Source: Primary Data

Source: Primary Data

Table.5 Opening of Respondents seeking to Adopt Digital Banking if the following provisions are made.

Source: Primary Data

Table .6.1 H₀₁There is no significant difference in factors influencing customers' behaviour in the adoption of Digital banking based on Gender.

Source: Primary Data

Table .6.2 H₀₂ There is no significant difference in factors influencing customers in the adoption of Digital banking based on Age 

Source: Primary Data

Table .6.3  H₀₃ There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Education

Source: Primary Data

Table .6.4 H₀₄ There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking based on Employment Status

Source: Primary Data

Table .6.5 H₀₅There is no significant difference in factors influencing perceptions of customers in the adoption of Digital banking among the existing users and Non-users of Digital Banking services.  

Source: Primary Data