green banking and profitability: an empirical study of

Analysing the Applicability of Blockchain Accounting and Its Impact on Financial Reporting

Asha Sharma*

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SUMEDHA-Journal of ManagementReferred Journal of CMR College of Engineering & TechnologyApril-June 2020, Volume 9, No. 2, pp 14-27ISSN: 2277-6753 (Print) ISSN: 2322-0449 (Online)http://cmrcetmba.in/sumedha/

DOI: https://doi.org/10.46454/sumedha/9.2.2020.2

Green Banking and Profitability:An Empirical Study of Indian Commercial Banks

Renu Jatana*, Harshila Jain**

* Dean & Faculty Chairman, Faculty of Commerce, University College of Commerce and Management Studies,Mohan Lal Sukhadia University, Udaipur (Rajasthan); ORCID Id: https://orcid.org/0000-0002-7540-9869

** Guest Faculty, University College of Commerce and Management Studies, Mohan Lal Sukhadia University,Udaipur (Rajasthan); ORCID Id: https://orcid.org/0000-0003-2813-2120

Abstract

Green Banking is also called as the ethical banking which aims to protect the

environment and reduce the carbon footprint from banking activities. It

encourages banks to carry out environment-friendly investments by

combining its operational improvements and technology know-how in

banking business activities. Environmental friendly practices include

introduction of Green Products and Services, namely, Online Banking,

Mobile Banking, Banking through ATMs, Green Deposits, Green Mortgages

and Loans, Green Credit Cards, and Green Reward Checking Accounts. A

carbon footprint measures the amount of CO2 released into the environment

by an organisation. Banks can reduce their carbon footprints by adopting

the certain measures like paperless banking, energy consiousness, using mass

transportation system and use of solar and wing energy.

The main objective of the research was to find out the impact of Green Banking

products or services on Profitability of Indian Commercial Banks. Out of

above listed Green Banking Products and Services, the present study has

focused on 4 Green Banking Services namely, Total Card Payments, Total

Retail Electronic Clearing, Real Time Gross Settlement (RTGS) transactions

and Number of ATMs. Annual Reports of RBI were used for data collection

for the recent 3 financial years i.e. 2016-17, 2017-18, and 2018-19, for Indian

Commercial Banks.

The study concluded that Profitability of banks can be increased by providing

more focus on Green Banking Services. Among 4 Green Banking Services

included in this study, only Total Retail Electronic Clearings has shown a

significant impact on Profitability of Indian Commercial Banks.

Keywords: Profitability, Total Card Payments, Total Retail Electronic

Clearing, Real Time Gross Settlement (RTGS) transactions, Number of ATMs

JEL Classification:

C1, C8, B410

PUBLISHING CHRONOLOGY

PAPER SUBMISSION DATE :

DECEMBER 9, 2019;

PAPER SENT BACK FOR REVISION :

JANUARY 9, 2020;

PAPER ACCEPTANCE DATE :

FEBRUARY 10, 2020

Cite this Article as follows as

per APA:

Jatana, R., & Jain, H. (2020).

Green Banking and

Profitability: An Empirical

Study of Indian Commercial

Banks. SUMEDHA JOURNAL

OF MANAGEMENT, 9(2), 14.

doi:10.46454/sumedha/

9.2.2020.2

Green Banking and Profitability: An Empirical Study of Indian Commercial Banks


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INTRODUCTION

In today's society, climate change is a most complicated issue. Nowadays, people are moreconversant with global warming and its inherent consequences on human life (Sharma, 2013).So, change is imminent in present scenario for the survival, and continuous efforts are madeto the environmental management in a sustainable manner (Elkington, 1994). It is the matterof concern for the government and the direct polluters and also for other stakeholders likefinancial institutions. This includes banks, which are playing a fundamental role in thedevelopment of the society. Although banking activities are not physically related to theenvironment, yet it is an external impact of the customers which is substantial for them. Toreduce the carbon footprint from the environment substantially, it is required by banks topromote those products, process and technology which adhere to it. Therefore, banks areadopting green strategies into their buildings, operations, and investments and financingstrategies.

The concept of Green Banking or Ethical Banking or Green initiatives taken by banks aims toprotect the environment by means of promoting environmental-friendly practices andreducing the carbon footprint from banking activities. Environmental friendly practicesinclude introduction of Green Products and Services, namely, Online Banking, MobileBanking, Banking through ATMs, Green Deposits, Green Mortgages and Loans, Green CreditCards, and Green Reward Checking Accounts. A carbon footprint measures the amount ofCO2 released into the environment by an organisation. Banks can reduce their carbonfootprints by adopting the certain measures like paperless banking, energy consiousness,using mass transportation system and use of solar and wing energy. (Dipika, 2015)

The present study is aimed at determining the impact of Green banking Services onProfitability Indian Commercial Banks. In order to achieve this, secondary data is collectedfrom RBI annual reports. Though many Green Banking Services exist in India, study is focusedon 4 Green Banking Services namely, Total Card Payments, Total Retail Electronic Clearing,Real Time Gross Settlement (RTGS) transactions and Number of ATMs. A census study isconducted with Indian Commercial banks, covering, 20 Public Sector Banks, 22 Private SectorBanks, and 4 Foreign Banks. Table 1 shows the data of Profitability and 4 Green Bankingservices of Indian Commercial Banks:



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Table 1: Data for 3 Financial Years

2016-2017 2017-2018 2018-2019

Dependent or Criterion Variable (Y)

Operating Profit (Amount: in Billion Rs.)1 2877.337219 2925.865393 3053.332725

Independent Variables or Predictors

ATMs 2,08,3542 2,05,2013 2,00,3524

Total Card Payments (Volume: in millions) 5450.1 8207.6 10781.2

1. Credit Cards5 1087.1 1405.2 1762.6

2. Debit Cards5 2399.3 3343.4 4414.3

3. Pre-paid Payment Instruments (PPIs)5 1963.7 3459.0 4604.3

Total Retail Electronic Clearing (Volume: in

millions) 5

4222.9 6382.3 12466.7

1. NEFT (National Electronic Funds Transfer)5 1622.1 1946.4 2318.9

2. ECS (Electronic Clearing Service) DR5 8.8 1.5 0.9

3. ECS CR5 10.1 6.1 5.4

4. IMPS (Immediate Payment Service)5 506.7 1009.8 1752.9

5. UPI(Unified Payment Interface)5 17.9 915.2 5353.4

6. NACH (National Automated Clearing

House)5

2057.3 2503.3 3035.2

RTGS (Volume: in millions)5 107.8 124.4 136.6

Source: 1 (CEIC Data, 2019); 2(Branches and ATMs of Scheduled Commercial Banks, March 2017);3 (Branches and ATMs of Scheduled Commercial Banks, June 2018);

4 (Branches and ATMs of Scheduled Commercial Banks, March 2019);5(Reserve Bank of India Annual Report 2018-19, August 2019)

REVIEW OF LITERATURE

(Taslima Julia, 2016), aims to investigate the relation between profitability and green financingbased on the experience of 30 sample banks in Bangladesh. Several profitability ratios, namelyROE, ROA, AU and ROD have been used to find the relation with green financing utilizedfunds for three years 2012, 2013 and 2014. The study finds that there are significantrelationships among different banks of Bangladesh such as conventional commercial banks,Islamic commercial banks, state-owned commercial banks and foreign commercial banks interms of profitability ratios. In particular, the ROA, ROD and AU have significant positiverelationships with green financing of the banks, while the ROE showed no significantrelationship with green financing of the banks.

(M. Ramila, 2015), in their research study "Impact of Green Banking Initiatives Adopted byPublic Sector Banks on Profitability" investigates as to how the green banking initiativessuch as NEFT, RTGS, ECS, ATM, POS and Mobile banking, impact the profitability of thepublic sector banks. To achieve this objective, the hypotheses were framed and it was found



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that ECS and ATM transactions create more impact on the profitability of public sector bankswhen compared to other green banking initiatives.

(Dr Namita Rajput, 2013), finds the association of environmental performance and financialperformance by using data panel regression method, taking financial variables like net income,expenses with profitability and variables of green banking exhibiting environmentalperformance. The results show that relationship between the net income and profitability issignificant but no significant relationship exists between the implementation of green bankingand bank's profitability as is revealed in the study. This exhibits clearly that green bankingand environmental initiatives are still in their infancy stage in Indian banking sector and toreap the fruits, a big push is required in this paradigm.

(Awino, 2014), establishes whether there is a relationship between green banking and financialperformance of commercial banks in Kenya. The researcher uses secondary data from CentralBank of Kenya, Communications Authority of Kenya and Kenya National Bureau of Statisticsfor the period between 1st January 2011 and 31st December 2013. The target populationincludes all the 43 commercial banks in Kenya, making the study a census. In order to conductthe research study, the researcher uses two green banking initiatives: mobile banking andonline banking. The researcher also assesses the capital adequacy and liquidity of allcommercial banks in Kenya to establish whether there was truly a relationship between greenbanking and financial performance.

(Rehman, 2016), examines the impact of e-banking over the profitability of commercial banksof Bangladesh. This paper determines the impact of e-banking over the performance of banksfocusing on the profitability. A field survey has been done among the randomly selectedemployees of commercial banks in Dhaka city. Different statistical tools like mean, standarddeviation, t-test, F-test and so on have been used to justify the case. The result shows thatoffering e-banking services have a positive or upward impact over the profitability of banks.It has supported that the banks will earn profits by providing e-services in spite of facinghigh maintenance costs in the long run.

RESEARCH OBJECTIVES

The main objective of the research is to find out the impact of Green Banking products orservices on Profitability of Indian Commercial Banks. The following objectives are consideredas sub-objectives of the research.

1. To reveal the relationship between Profitability of Scheduled Commercial Banks andTotal Card Payments.

2. To identify the relationship between Profitability of Scheduled Commercial Banks andTotal Retail Electronic Clearing.

3. To analyze the relationship between Profitability of Scheduled Commercial Banks andRTGS transactions.



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4. To study the relationship between Profitability of Scheduled Commercial Banks andNumber of ATMs.

5. To give possible recommendations in order to increase Profitability of IndianCommercial Banks with reference to Green banking Services.

RESEARCH METHODOLOGY

DATA COLLECTION

Secondary data is used in this study. Annual Reports of RBI are used for data collection toanalyze the impact of Green Banking (Total Card Payments, Total Retail Electronic Clearing,RTGS transactions and Number of ATMs) transactions on the profitability of IndianCommercial Banks. Data is collected for the recent 3 financial years i.e. 2016-17, 2017-18, and2018-19, for Indian Commercial Banks.

AREA OF RESEARCH

The scope of study includes Indian Commercial banks, covering, 20 Public Sector Banks, 22Private Sector Banks, and 5 Foreign Banks. (Refer Table 2)

Table 2: Names of Indian Commercial Banks

Public Sector Banks Private Sector Banks Foreign Banks

Allahabad Bank Axis Bank Ltd. Citibank N.A

Andhra Bank Bandhan Bank Ltd. DBS Bank India Limited

Bank of Baroda City Union Bank Ltd. Deutsche Bank AG

Bank of India CSB Bank Ltd. Hongkong and Shanghai

Banking Corpn.Ltd.

Bank of Maharashtra DCB Bank Ltd. Standard Chartered Bank

Canara Bank Dhanlaxmi Bank Ltd.

Central Bank of India Federal Bank Ltd.

Corporation Bank HDFC Bank Ltd.

Dena Bank ICICI Bank Ltd.

Indian Bank IDBI Bank Ltd.

Indian Overseas Bank IDFC First Bank Ltd.

Oriental Bank of Commerce IndusInd Bank Ltd.

Punjab and Sind Bank Jammu & Kashmir Bank Ltd.

Punjab National Bank Karnataka Bank Ltd.

State Bank of India Karur Vysya Bank Ltd.

Syndicate Bank Kotak Mahindra Bank Ltd.

UCO Bank Lakshmi Vilas Bank Ltd.

Union Bank of India Nainital Bank Ltd.

United Bank of India RBL Bank Ltd.

Vijaya Bank South Indian Bank Ltd.

South Indian Bank Ltd.

Yes Bank Ltd.

Source: RBI Report on Trend and Progress of Banking in India 2018-19



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DATA ANALYSIS

In this study, quantitative approach is used for analyzing the collected data.

The quantitative analysis is carried out with the help of 'Statistical Package for Social Science'(SPSS) Version 21. Statistical tool Linear Regression analysis is used in order to test the impactof independent variables on depnedent variable. After applying Regression analysis, resultsof Analysis of variancce (ANOVA) is used to test the null hypothesis, whether it is rejected orfailed to be rejected.

In Regression analysis, following variables are considered:

Dependent Variable or Criterion Variable (Y): Profitability of Scheduled Commercial Banks

Independent Variables or Predictors:

1. Total Card Payments (X1)

2. Total Retail Electronic Clearing (X2)

3. RTGS (X3)

4. ATMs (X4)

HYPOTHESES:

H01: There is no significant relationship between Profitability of Scheduled Commercial Banksand Total Card Payments.

H02: There is no significant relationship between Profitability of Scheduled Commercial Banksand Total Retail Electronic Clearing.

H03: There is no significant relationship between Profitability of Scheduled Commercial Banksand RTGS.

H04: There is no significant relationship between Profitability of Scheduled Commercial Banksand ATMs.

H05: There is no significant relationship between dependent and independent variables jointly.

HYPOTHESIS TESTING: REGRESSION ANALYSIS

RESULTS AND INTERPRETATION

HYPOTHESIS 1:

H01: There is no significant relationship between Profitability of Scheduled Commercial Banksand Total Card Payments.



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Table 3: Model Summary (Hypothesis 1)

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 .963a .927 .854 34.68632

Source: SPSS Version 21a. Predictors: (Constant), Total Card Payments

(Refer Table 3) Coefficient of correlation (R) is .963 which indicates that there is high degreeof positive correlation between Profitability and Total Card Payments.

That is, if the independent variable increases then dependent variable will also increase.

Coefficient of Determination (R2) shows the proportion of the variability in the dependentvariable that can be explained by the estimated multiple regression equation. Here R2 isequal to 0.927 (92.7%) which indicates that 92.7% of the variability in Profitability ofcommercial banks is explained by the independent variable i.e. Total Card payments.

Adjusted R2 is 0.854 which shows the proportion of variability in the dependent variablethat can be explained by multiple regressions. It is found after the analysis that the proportionis 0.854 or 85.4%.

Table 4: ANOVAa for Hypothesis 1

Model Sum of Squares Df Mean Square F Sig.

1

Regression 15322.540 1 15322.540 12.735 .174b

Residual 1203.141 1 1203.141

Total 16525.681 2

Source: SPSS Version 21a. Dependent Variable: Profitability

b. Predictors: (Constant), Total Card Payments

(Refer Table 4) F-test is used to determine whether a significant relationship prevails betweenthe dependent variable and independent variables. It is considered as the test for overallsignificance. As p (=.174) is not lower than level of significance of 5% (?=.05), so it can becertainly derived that the null hypothesis is failed to be rejected. So, the overall relationshipis not significant.

That is, Total Card Payments do not create a significant impact on the Profitability ofCommercial Banks.

Hypothesis 2:

H02: There is no significant relationship between Profitability of Scheduled Commercial Banksand Total Retail Electronic Clearing.



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Table 5: Model Summary for Hypothesis 2

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

1 1.000a 1.000 1.000 1.91113

Source: SPSS Version 21

a. Predictors: (Constant), Total Retail Electronic Clearing

(Refer Table 5) Coefficient of correlation (R) is 1.000 which indicates that there is perfectpositive correlation between Profitability and Total Retail Electronic Clearing. That is, withthe increase in Total Retail Electronic Clearings, the Profitability of Commercial Banks willalso increase.

Coefficient of Determination (R2) is equal to 1.000 (100%) which indicates that 100% of thevariability in Profitability of commercial banks is explained by the independent variable i.e.Total Retail Electronic Clearings.

Adjusted R2 is also 1.00 (100%) which shows the proportion of variability in the Profitabilityof Commercial Banks is completely explained by the independent variable.

Table 6: ANOVA a for Hypothesis 2


1

Regression 16522.029 1 16522.029 4523.605 .009b

Residual 3.652 1 3.652

Total 16525.681 2


b. Predictors: (Constant), Total Retail Electronic Clearing

(Refer Table 6) F-test results show that p (=.009) is lower than level of significance of 5%(=.05), so it can be certainly derived that the null hypothesis is rejected.

There exist a significant relationship between Profitability of Scheduled Commercial Banksand Total Retail Electronic Clearing. It can be concluded that Total Retail Electronic Clearingcreates a significant impact on the Profitability of Commercial Banks.

Hypothesis 3:

H03: There is no significant relationship between Profitability of Scheduled Commercial Banksand RTGS.



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Model R R Square Adjusted R Square Std. Error of the Estimate

1 .942a .888 .776 43.03665


a. Predictors: (Constant), RTGS

(Refer Table 7) Coefficient of correlation (R) is 0.942 which indicates that there is highdegree of positive correlation between Profitability and RTGS. That is, with the increase inRTGS transactions, the Profitability of Commercial Banks will also increase.

Coefficient of Determination (R2) is equal to 0.888 (88.8%) which indicates that 88.8% of thevariability in Profitability of commercial banks is explained by the independent variable i.e. RTGS.

Adjusted R2 is also 0.776 (77.6%) which shows the proportion of variability in the Profitabilityof Commercial Banks is completely explained by the independent variable.



1

Regression 14673.528 1 14673.528 7.922 .217b

Residual 1852.153 1 1852.153

Total 16525.681 2


a. Dependent Variable: Profitabilityb. Predictors: (Constant), RTGS

(Refer Table 8) F-test results show that p (=.217) is not lower than level of significance of 5%(=.05), so it can be certainly derived that the null hypothesis is failed to reject.

There does not exist a significant relationship between Profitability of Scheduled CommercialBanks and RTGS transactions.

Hypothesis 4:

H04: There is no significant relationship between Profitability of Scheduled Commercial Banksand ATMs.


Model R R Square Adjusted R Square Std. Error of the Estimate

1 -.991a .983 .966 16.87254

Source: SPSS Version 21a. Predictors: (Constant), ATMs



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(Refer Table 9) Coefficient of correlation (R) is -0.991 which indicates that there is highdegree of negative correlation between Profitability and ATMs. That is, with the increase inATMs, the Profitability of Commercial Banks will decrease.

Coefficient of Determination (R2) is equal to 0.983 (98.3%) which indicates that 98.3% of thevariability in Profitability of commercial banks is explained by the independent variable i.e.Number of ATMs.

Adjusted R2 is 0.966 (96.6%) which shows the proportion of variability in the Profitability ofCommercial Banks is highly explained by the independent variable.



1

Regression 16240.998 1 16240.998 57.050 .084b

Residual 284.683 1 284.683

Total 16525.681 2


a. Dependent Variable: Profitabilityb. Predictors: (Constant), ATMs

(Refer Table 10) F-test results show that p (=.084) is not lower than level of significance of 5%(=.05), so it can be certainly derived that the null hypothesis is failed to reject.

There is no significant relationship between Profitability of Scheduled Commercial Banksand Number of ATMs.

HYPOTHESIS 5:

H05: There is no significant relationship between dependent and independent variables jointly.


R Square Adjusted R Square Std. Error of the Estimate

.998 .996 5.91043


a. Predictors: (Constant), Total

(Refer Table 11) Coefficient of correlation (R) is 0.999 which indicates that there is high degreeof positive correlation between Profitability and Total independent variables. That is, with theincrease in independent variables, the Profitability of Commercial Banks will also increase.

Coefficient of Determination (R2) is equal to 0.998 (99.8%) which indicates that 99.8% of thevariability in Profitability of commercial banks is explained by the independent variables.



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Adjusted R2 is 0.996 (99.6%) which shows the proportion of variability in the Profitability ofCommercial Banks is highly explained by the independent variables.

Table 12: ANOVAa for Hypothesis 5


1

Regression 16490.748 1 16490.748 472.066 .029b

Residual 34.933 1 34.933

Total 16525.681 2


b. Predictors: (Constant), Total

(Refer Table 12) F-test results show that p (=.029) is lower than level of significance of 5%(=.05), so it can be certainly derived that the null hypothesis is rejected.

There exists a significant relationship between Profitability of Scheduled Commercial Banksand Total independent variables. It can be concluded that Total independent variables createa significant impact on the Profitability of Commercial Banks.

FINDINGS OF THE STUDY

1. There is high degree of positive correlation between Profitability and Total CardPayments, but Total Card Payments do not create a significant impact on the Profitabilityof Commercial Banks.

2. There is perfect positive correlation between Profitability and Total Retail ElectronicClearing. That is, with the increase in Total Retail Electronic Clearings, the Profitabilityof Commercial Banks will also increase.

3. There exist a significant relationship between Profitability of Scheduled CommercialBanks and Total Retail Electronic Clearing. That is, Total Retail Electronic Clearingcreates a significant impact on the Profitability of Commercial Banks.

4. There is high degree of positive correlation between Profitability and RTGS. That is,with the increase in RTGS transactions, the Profitability of Commercial Banks will alsoincrease, but there does not exist a significant relationship between Profitability ofScheduled Commercial Banks and RTGS transactions.

5. There is high degree of negative correlation between Profitability and ATMs. That is,with the increase in ATMs, the Profitability of Commercial Banks will decrease.

6. There does not exist significant relationship between Profitability of ScheduledCommercial Banks and Number of ATMs.



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7. There is high degree of positive correlation between Profitability and Total independentvariables. That is, with the increase in independent variables (Green Banking Services),the Profitability of Commercial Banks will also increase.

8. There exists a significant relationship between Profitability of Scheduled CommercialBanks and Total independent variables. It can be concluded that Total independentvariables, i.e. Green Banking Services, create a significant impact on the Profitability ofCommercial Banks.

CONCLUSION AND RECOMMENDATIONS

This study examined the impact of Green Banking Services on profitability of IndianCommercial Banks and relationship between Green Banking Services and profitability.Regression analysis concludes that, when all Green Banking services are analyzed jointly,there is significant impact of Green Banking Services on profitability of Indian CommercialBanks and also there is significant association between Green Banking services andprofitability. Also, the result of Correlation analysis shows very high degree of positivecorrelation between Green Banking Services and Profitability of Indian Commercial Banks.Therefore, it can be concluded that Profitability of banks can be increased by providing morefocus on Green Banking Services.

Now, when individual impact of Green Banking Services is analyzed on Profitability of IndianCommercial Banks, it is giving following results.

When the impact of Total Card Payments (Debit Cards, Credit Cards and Pre-Paid PaymentInstruments) is analyzed on Profitability of Indian Commercial Banks, the null hypothesis isfailed to be rejected. So, the overall relationship is not significant. That is, Profitability ofIndian Commercial Banks is not dependent on Total Card Payments. Though, result shows avery high degree of positive correlation between Profitability and Total Card Payment. Thatis, if Total Card Payment increases then Profitability of Indian Commercial Banks will alsoincrease.

Second Green Banking Service, i.e. Total Retail Electronic Clearing (NEFT, ECS DR, ECS CR,IMPS, UPI, and NACH) shows a significant impact on Profitability of Indian CommercialBanks, as null hypothesis is rejected in this case. That is, Profitability is greatly affected byTotal Retail Electronic Clearings of Indian Commercial banks. Also, a very high degree ofcorrelation exists between the dependent and independent variable.

Third parameter of Green banking Services, i.e. RTGS transactions also shows a very highdegree of positive association with Profitability of Indian Commercial Banks. Whereas, theresult of ANOVA is failed to reject the null hypothesis, which means, that RTGS transactionsdoes not create a significant impact on Profitability of Indian Commercial Banks.

Now, the last parameter of Green Banking Services, taken for this study, Number of ATMs,shows a very high degree of negative correlation with Profitability. This result can be analyzed



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with the help of original data also, that number of ATMs are decreasing from last 3 financialyears i.e., from 2017-2019; and Profitability of Indian Commercial Banks is increasing. Theresult of F-test is failed to reject null hypothesis, which depicts that number of ATMs do notcreate any significant impact on Profitability of Indian Commercial Banks.

Among all Green Banking Services included in this study, i.e., Total Card Payments, TotalRetail Electronic Clearings, RTGS transactions and Number of ATMs, only Total RetailElectronic Clearings show a significant impact on Profitability of Indian Commercial Banks.For this reason, RBI must pay specific attention on Total Retail Electronic Clearings, whichincludes a major portion of NEFT. As we all know that NEFT is a major part of online banking,therefore, it is highly recommended to promote Online Banking so as to implement the conceptof Paperless Banking or Green Banking, and, thereby, increasing Profitability of Banks.

Banks must organize specific training programmes for customers to promote Online BankingTransactions, which will give a specific focus on Green banking Services.

AUTHOR’S CONTRIBUTION

Prof. Renu Jatana has devised the main conceptual idea and supervised this research study.Prof. Renu Jatana has directed at each stage of the study. Dr. Harshila Jain has gone throughprevious literatures related to the current study in order to get the in depth idea of the topic.Dr. Harshila Jain has performed the analytic calculations and performed the numericalsimulations. Both the authors contributed to the final version of the manuscript.

CONFLICT OF INTEREST

The authors certify that they have no affiliations with or involvement in any organization orentity with any financial interest, or non-financial interest in the subject matter or materialsdiscussed in this manuscript.

FUNDING ACKNOWLEDGEMENT

The authors received no financial support for the research, authorship, and/or for thepublication of this article.

REFERENCES

[1]. 2016-17, R. o. (March 2017). Branches and ATMs of Scheduled Commercial Banks. RBI.

[2]. 2017-18, R. o. (June 2018). Branches and ATMs of Scheduled Commercial Banks. RBI.

[3]. 2018-19, R. o. (March 2019). Branches and ATMs of Scheduled Commercial Banks. RBI.

[4]. Awino, O. B. (2014). The Relationship between Green Banking and Financial Performance ofCommercial Banks in Kenya. Kenya: University of Nairobi.

[5]. CEIC Data. (2019, December 25). Operating Profit: Indian Scheduled Commercial Banks. RetrievedFebruary 28, 2020, from CEIC: https://www.ceicdata.com/en/india/scheduled-commercial-banks-income-statement/scheduled-commercial-banks-operating-profit

[6]. Das, S. (August 2019). Reserve Bank of India Annual Report 2018-19. Reserve Bank of India.



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[7]. Dipika. (2015). Green Banking in India: A Study of Various Strategies Adopt by Banks for SustainableDevelopment. International Journal of Engineering Research & Technology (IJERT) , 3 (10), 1-10.

[8]. Dr Namita Rajput, M. S. (2013). An Empirical Study of Impact of Environmental Performance onFinancial Performance in Indian Banking Sector. International Journal of Business and ManagementInvention , 2 (9), 19-24.

[10]. Elena. (2018, July 2). Top 10 Best Public Sector Banks in India: Trendrr. Retrieved August 8, 2018, fromTrendrr: https://www.trendrr.net/1124/largest-best-public-sector-banks-in-india-famous-top-10/

[11]. Elena. (2018, July 2). Top 10 Largest Private Sector Banks in India: Trendrr. Retrieved August 8, 2018,from Trendrr: https://www.trendrr.net/1148/top-ten-best-largest-private-sector-banks-in-india-famous/

[12]. Elkington, J. (1994). Towards the Sustainable Corporation: Win-Win-Win Business Strategies forSustainable Development. California Management Review , 36 (2), 90-100.

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PROFILE OF AUTHORS

Prof. Renu Jatana is serving as Dean and Faculty Chairman of University College ofCommerce & Management Studies, Mohanlal Sukhadia University, Udaipur (Rajasthan).She has 34 years of teaching experience. She has been Course Director of Post graduateprogramme of Masters of International Business (MIB) from past ten years. She has servedUGC Centre for Women's Studies, MLSU, Udaipur, for four years as Director.

Dr. Harshila Jain is working as Guest Lecturer at University College of Commerce &Management Studies, Mohanlal Sukhadia University, Udaipur (Rajasthan). She is anengineering graduate and MBA post graduate. She has 3 years of banking experience and8 years of teaching experience.

green banking and profitability: an empirical study of

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