BANKERS’ PERSPECTIVE ON GREEN BANKINGIN COMMERCIAL

BANKS OF KATHMANDU VALLEY

by

Heena Tandukar

Symbol Number:17220360

PU Registration Number: 2017-2-22-0286

A Graduate Research Project submitted to Pokhara University as partial fulfillment

of the requirements for the degree of

Master of Business Administration

at the

Quest International College

Pokhara University

Gwarko, Lalitpur

November, 2019

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ACKNOWLEDGEMENTS

This graduate research project work is an end-result of persistent support, monitoring,

guidance and supervision of a number of professionals, academicians, peer learners

and other individuals. Thus, I would like to express my deeper sense of gratitude and

thanks to all of them.

First of all, I would like to express my sincere thanks to Dr. Niranjan Devkota, my

Graduate Research Project Report Supervisor, for his valuable suggestions, advice,

instructions and guidance for preparing this compressive research project.

I am very much thankful to Pokhara University for including this research project in

our academic curriculum and Quest International College for allsupport and providing

better learning environment. It gives me an immense pleasure to recall every support

and professional guidance provided by Mr. Udaya Raj Paudel, Principal, Quest

International College. I am equally thankful toMr. Ram Prasad Poudel, MBA

AssociateDirector, Quest International College for providing me academic resources

and direction for the completion of this research project.

I am grateful to all respondents for their cooperation to provide the required

information and data for this study despite of their busy schedule. Without their

support, this projectreport has not been completed. I would also like to thank my dear

friends for their help and contribution during data collection and support throughout

the completion of this report.

I am very much indebted to all family members and relatives whose guidance have

significant contribution to complete thisproject report.

Heena Tandukar

aneehtandukar21@gmail.com

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TABLE OF CONTENTS

DECLARATION ........................................................................................................ i

LETTER OF RECOMMENDATION ........................ Error! Bookmark not defined.

RECOMMENDATION FOR APPROVAL ............... Error! Bookmark not defined.

VIVA-VOCE SHEET ................................................ Error! Bookmark not defined.

ACKNOWLEDGEMENTS ....................................................................................... v

TABLE OF CONTENTS .......................................................................................... vi

LIST OF FIGURES .................................................................................................. ix

LIST OF TABLES .................................................................................................... x

ABSTRACT ............................................................................................................. xi

CHAPTER I: INTRODUCTION ............................................................................... 1

1.1. Background ................................................................................................. 1

1.2. Statement of the Problem ............................................................................. 3

1.3. Objectives of the Study ................................................................................ 4

1.4. Significance of the Study ............................................................................. 4

1.5. Limitation of the Study ................................................................................ 4

1.6. Organization of the Study ............................................................................ 5

CHAPTER II: LITERATURE REVIEW ................................................................... 6

2.1. Thematic Review ............................................................................................ 6

Concept .............................................................................................................. 6

New Trends in Banking System ........................................................................... 7

Origin of the Concept of Green Banking ............................................................. 9

Green Banking Initiation in Nepal .................................................................... 10

Advantages of Green Banking System ............................................................... 11

2.2. Theoretical Review ....................................................................................... 12

Equator Principles ........................................................................................... 12

Typology of Banking & Sustainable Development ............................................. 13

Theory X and Theory Y Model .......................................................................... 14

2.3. Conceptual Framework ................................................................................. 15

Model Internal and External Liability of the Bank ............................................ 15

Schematic Diagram of Conceptual Framework ................................................. 16

Graphical Model of Adoption of Green Banking ............................................... 16

2.4. Empirical Review .......................................................................................... 18

2.5. Policy Review ............................................................................................... 36

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Sustainable Development Goals (SGDs) - Nepal ............................................... 36

SDGs Estimated Costing - Nepal ...................................................................... 37

Banking Policy ................................................................................................. 38

2.6. Research Gap ................................................................................................ 39

2.7. Chapter Conclusion ....................................................................................... 40

CHAPTER III: RESEARCH METHODOLOGY ..................................................... 42

3.1. Research Design ............................................................................................ 42

3.2. Conceptual Framework ................................................................................. 42

3.3. Basic Model .................................................................................................. 44

3.4. Hypothesis & Variables Used ........................................................................ 46

3.5. Defining Variable .......................................................................................... 48

3.6. Method of Data Collection ............................................................................ 51

Study Area and Population ............................................................................... 51

Sources and Nature of Data .............................................................................. 52

Sample Size Determination ............................................................................... 53

Research Instruments ....................................................................................... 53

3.7. Data Analysis ................................................................................................ 54

Descriptive Analysis ......................................................................................... 54

Calculation of Bankers’ Awareness Index ......................................................... 54

Inferential Statistics .......................................................................................... 55

3.8. Summary of Analytical Methods used for the study ....................................... 55

3.9. Chapter Conclusion ....................................................................................... 56

CHAPTER IV: DATA PRESENTATION AND ANALYSIS .................................. 58

4.1. Descriptive Analysis...................................................................................... 58

4.1.1. Bankers‟ Socio Demographic Characteristics .......................................... 58

4.1.2. Understanding Level of Bankers regarding Green Banking ..................... 62

4.1.3. Factors Determining Green Banking ....................................................... 68

4.1.4. Management Strategy for Greening Bank ................................................ 70

4.2. Awareness Index ........................................................................................... 74

4.3. Inferential Analysis ....................................................................................... 77

CHAPTER V: SUMMARY, CONCLUSION AND RECOMMENDATION ........... 91

5.1. Summary of the study .................................................................................... 91

5.2. Contribution of the study ............................................................................... 94

5.3. Conclusion .................................................................................................... 95

5.4. Recommendations ......................................................................................... 96

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5.5. Areas of Further Research ............................................................................. 97

REFERENCES ........................................................................................................ 98

ANNEX I: Questionnaire ....................................................................................... 105

ANNEX II: Awareness Index ................................................................................ 112

ANNEX III: Regression Results (STATA Output) ................................................. 113

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LIST OF FIGURES

Figure 1: Equator Principles .................................................................................... 13

Figure 2: Typology of Banking & Sustainable Development.................................... 13

Figure 3: Theory X and Theory Y ............................................................................ 14

Figure 4: Model Internal and External Liability of the Bank .................................... 15

Figure 5: Schematic Diagram of Conceptual Framework ......................................... 16

Figure 6: Graphical Model of Adoption of Green Banking ....................................... 17

Figure 7: Conceptual Framework ............................................................................. 43

Figure 8: Study Area................................................................................................ 51

Figure 9: Age of the Respondents ............................................................................ 59

Figure 10: Division of Respondent by Sex ............................................................... 59

Figure 11: Level of Education.................................................................................. 60

Figure 12: Training Received by Bankers ................................................................ 61

Figure 13: Source of Training .................................................................................. 61

Figure 14: Bankers' Understanding on Green Banking ............................................. 62

Figure 15: Bankers‟ View on Green Banking on the basis of gender ........................ 63

Figure 16: Five Most Popular Green Banking Services ............................................ 66

Figure 17: Bankers‟ Perception on Factors Determining Green Banking .................. 69

Figure 18: Bankers‟ Perspective on Benefits of Green Banking ............................... 69

Figure 19: Required New Technology to promote Green Banking ........................... 70

Figure 20: How bankers' are ready for Green Banking ............................................. 71

Figure 21: Reason for not adopting Green Banking .................................................. 72

Figure 22: Suggestions for Improvement of Green Banking Practices ...................... 74

Figure 23: Awareness Level based on Age............................................................... 74

Figure 24: Awareness on Green Banking based on Sex ............................................ 75

Figure 25: Awareness based on Educational Level ................................................... 77

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LIST OF TABLES

Table 1: Emphasis by Sustainable Development Goals on Banking ......................... 37

Table 2: Indicators for Sustainable Development Goals ........................................... 37

Table 3: SDGs Investment Required ........................................................................ 38

Table 4: Average investment requirement for SDG implementation ......................... 38

Table 5: Public sector SDG investment requirement, financing sources and financing

gap .......................................................................................................................... 38

Table 6: Description of Variables ............................................................................ 47

Table 7: Summary of Analytical Methods used for the study ................................... 56

Table 8: Work Experience of Respondents .............................................................. 60

Table 9: Bank‟s Awareness Level on Green Banking ............................................... 64

Table 10: Components of Green Banking adopted by Banks .................................... 65

Table 11: Awareness Level regarding Green Banking Practices ............................... 67

Table 12: Awareness Level on Issues of Green Banking .......................................... 68

Table 13: Awareness Level based on Work Experience ........................................... 76

Table 14: Summary Statistics................................................................................... 77

Table 15: Probit Regression Result .......................................................................... 82

Table 16: Multicollinearity Test of Single Dependent Variable ................................ 84

Table 17: Overall Multicollinearity Test of Dependent Variables ............................. 85

Table 18: Heteroscedasticity Test ............................................................................ 85

Table 19: Final Regression Result ............................................................................ 86

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ABSTRACT

Globally, green banking is becoming a buzzword for both banking and financial

sectors and for the general public in the last few decades. Green banking is the

operation of the banking activities which gives special importance to social,

ecological and environmental factors aiming at the conservation of nature and natural

resources. This paper aims to explore banker‟s perspective on the green banking

practices for environmental sustainability. The purpose of this study is to identify

banker‟s general understanding on green banking practices, identify banker‟s

perspectives on green banking practices in their banks, measuring factors affecting

bankers‟ perspectives on green banking practices and recommend the necessary

management strategy for greening the bank. This study reviews the new trend in

banking system, green banking concepts, its benefits and theories related with green

banking to find the impact of green banking practices. Several studies reveals that the

concept of green banking has been emerged considering environmental issues.This

study used both primary and secondary data based on structured questionnaire.

Descriptive analysis, awareness index and inferential statistics were used to analyze

the collected data of the study. The findings of the study shows general understanding

and awareness of bankers‟ on green banking practices. Similarly, the study also

reveals that there is significant relationship between dependent and independent

variables. Likewise, the study found the correlation and regression between identified

dependent and independent variables. This study is the first to identify the perspective

of bankers‟ on green banking in Nepalese context.

Keywords:Banker‟s Perception, Environmental Sustainability, Green Banking

Initiatives, Green Banking Practices, Awareness, Probit regression.

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CHAPTER I: INTRODUCTION

1.1.Background

Green Banking is a new way of showing the banking business through considering the

clean environmental issue as well as corporate social responsibility (Islam & Das,

2013).Similarly, in the research conducted in Bangladesh by Islam and Das (2013), it

is necessary to practice green banking by banks because of globalization and in order

to face the competition in market.Green banking is comparatively new development

in the financial world and the activities of the banks are associated with

environmental protection and sustainable development services (Trehan, 2015). Green

Banking has a role to safeguard the planet from unusual weather patterns, rising

greenhouse gas, and declining air quality, with the aim of ensuring economic growth

which is sustainable (Islam & Kamruzzaman, 2015). Uddin and Ahmmed (2018)

stated green banking plays caring role for sustainable development in overcoming the

institutional obstacles and market challenges, in the way to allocating the investment

to the green projects. Banks should go green and play a pro-active role to take

environmental and ecological aspects as a part of their lending principle (Sahoo &

Nayak, 2007). Nath, Nayak andGoel (2014) examined green banking practices that

are being followed in Indian banking system.

Masukujjaman and Aktar (2013) have stated that Bangladesh Bank was the first

central bank in the world, initiating the concept of green banking. The green banking

initiatives in Bangladesh involves both the in-house which indicates the management

of energy, prevention of wastage of energy and paper within the banking premises and

other than in-house which is related with green banking financing and making the

customers and stakeholders aware of environmental issues (Afroz, 2017). In context

of India, green banking have various benefits towards customers, environments and

banksthey are: use of green banking practices will result in saving the consumption of

energy, fuel, water as well as paper likewise green banking practices are very easy,

cost effective, convenient and time saving for the bank customers as well as the bank

employees (Deka, 2015).Green banking has many advantages, they are: green

banking avoids paper work and all transactions are done through online banking,

creating awareness to business people about environmental and social responsibility

enabling them to do an environmental friendly business practice and banks follow

environmental standards for lending, which is really a good idea and it will make

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business owners to change their business to environmental friendly which is good for

the future generations (Ragupathi & Sujatha, 2015). Green practices of banks are the

efforts of the banking sector to keep the environment green and to minimize

greenhouse effects through rationalizing their strategies, policy, decisions and

activities pertaining to banking service, business and in-house operational activities

(Deka, 2015). Environmental policy considering green banking has been formulated

by different banks like Royal Bank of Canada, Industrial Development Bank if

Turkey and Société Générale, France for their own institutions (Masukujjaman &

Aktar, 2013).

As far as green banking in India is concerned, the banking and financial institutions

are running behind the schedules compared to global trends. In 1980 comprehensive

environmental Response, Compensation and Liability Act (CERCLA), there was a

huge loss for the bank in 1980‟s in U.S in which the bank was directly blamable for

the environmental pollution of their client‟s activities and made them to pay the

remediation cost, that‟s why banks in U.S are more concern about the environment

while lending the fund to their clients. Islam andDas (2013) have conducted a study

highlighting the mobile banking, online banking, green financing, and guidelines for

green banking is a new term in Bangladesh, it is a mature issue in developed

countries. Jha and Bhome (2013) did the empirical study on the steps that can be

taken for going green in the banking sector and to check the awareness among bank

employees, associates and the general public about green banking concept.Similarly,

green banking can be taken as a multi stakeholder‟s task where banks should work

with government, NGOs, International Financial Institutes (IMFs), central bank,

consumers and business groups to achieve the goals (Masukujjaman & Aktar, 2013).

According to guidelines of Bangladesh Bank, banks should formulate and accept a

broad environmental and green banking policy through in-house performance. In

India, the banks can sustained for longer time by undertaking the corporate

entrepreneurship approach to innovate and adopt green banking strategies and many

banks are initiating those strategies (Bhardwaj & Malhotra, 2013). Jha & Bhome

(2013) explained green banking as means of promoting environmental friendly

practices and reducing carbon footprint in banking activities. Banks also contribute to

ecological footprint directly and indirectly through investment and lending in their

customer enterprises (Rajesh & Dileep, 2014).

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1.2.Statement of the Problem

The concept of green banking is new and emerging concept in context of Nepal. As

far as green banking in Nepal is concerned, the banks in Nepal were not found very

active to promote green banking initiatives but analyzing the recent context, some of

the banks have started providing loans for bicycle and solar energy like Civil Bank,

Nepal Investment Bank and Laxmi Bank (Mehta & Sharma, 2016). According to

survey conducted by Mehta & Sharma (2016), Laxmi bank is the first bank in Nepal

to support green banking concept.

According to CEO of Laxmi Bank, going green has become conscious practice and

belief adopted by every single employee at Laxmi Bank, they are promoting bicycles

as emission-free means of transportation through an array of activities, offering

attractive loan packages for environment-friendly products and saving products that

reward the customers for eco-friendly practices are some of the bank‟s activities to

reinforce our focus on the environment.

As part of the role to be played by the corporate sector, banks and financial

institutions should embrace green banking by adopting process and strategies that

promote environment-friendly practices to help in reducing carbon emission. Risal

and Joshi (2018) stated that green banking helps in reducing internal carbon footprint

as well as external carbon emission. Banks have been using lighting, air conditioning,

electronic equipment, IT, high paper wastage in massive proportion. The resultant

internal carbon footprint can be reduced through the use of renewable energy,

automation and other measures. On the other hand, banks can reduce external carbon

emission by financing projects and companies that are working for pollution reduction

and adopting green technologies. Arumugam and Chirute (2018) stated that providing

loans to firms that have concern for environment would ensure proper utilization of

natural resources.

In context of Nepal, banks should provide preference to green assetslike homes

equipped with solar energy, rain water harvesting facility, and properties with better

environmental surroundings for collaterals and secondary priority should be given to

polluting factories, buildings that emitted harmful waste in the environment.

According to CEO of Nabil Bank, Nabil Bank have taken the initiation of promoting

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green banking and green innovation initiative with the objective to foster and facilitate

innovative ideas of Nepalese youth regarding sustainable business that also can add

value to the environment.

1.3.Objectives of the Study

The general objective of this study is to analyze the banker‟s perspective on green

banking in the commercial bank of Kathmandu valley, Nepal. In the line with this, the

specific objectives are as follows:

1. To identify banker‟s general understanding on green banking practices.

2. To identify banker‟s perspectives on green banking practices in their

banks.

3. To measure factors affecting bankers‟ perspectives on green banking

practices.

4. To recommend the necessary management strategy for greening the bank.

1.4.Significance of the Study

After successful completion of this study, the banker‟s understanding on green

banking will be identified. Similarly, the factors that affects the adoption of green

banking will measure and the study also explore the managerial strategy for green

banking promotion to adopt green banking practices in commercial banks of Nepal.

This study will provide some benefits to the concerned authorities like commercial

banks, bankers, institutions connected with banks and other individual related with

banking services. This study will also provide some advantages to future researcher

who wants to do the research on green banking. This research will be beneficial for

the policy maker to make a policies to improve the practices of green banking.

1.5.Limitation of the Study

Despite lots of opportunities prevailing for conducting this research, there were some

hurdles which restricted the study. The concept of green banking is new in context of

Nepal, very few banks are adopting the green banking strategies so it was difficult to

collect the proper information of green banking for the study. Due to the less

awareness about green banking, bankers were not able to provide the clear view of

what they perceived about green banking. The study surveyed only some of the

commercial banks in Kathmandu valley so the result of the study cannot be generalize

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for overall scenario of bankers‟ understanding about green banking in other places of

Nepal.

1.6.Organization of the Study

This study is presented into five chapters. The first chapter introduces the subject

matter of the study. It describes the problems, objectives, significance and limitations

of the study. The second chapter presents the review of the literature on the green

banking practices in different country around the world including brief presentation of

theoretical foundation on green banking and its practices in the commercial bank of

Nepal. Similarly, the third chapter is related to research methodology. It provides

conceptual framework and defines the methodology to attain the objectives, and

nature and types of variables including hypothesis tested in the study.The study used

bankers‟ awareness index and probit model to identify their understanding on green

banking. The fourth chapter provides detail analysis of the study which includes

descriptive analysis, awareness index and probit regression result that is related to

green banking and green banking awareness. Likewise, chapter five provides the

major findings and its strengths and weakness in Nepalese context along with

summary, conclusion, recommendation and managerial implications for effective

green banking promotion.

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CHAPTER II: LITERATURE REVIEW

Green banking is an emerging issue in the global context (Tara, Singh & Kumar,

2015). Green banking helps in promoting environmentally friendly practices that aid

banks and customers in reducing their carbon footprint (Shaumaya & Arulrajah,

2016). The present study is focused on perception of bankers on green banking.

Therefore, this chapter provides a review of the related literature on green banking

and its practices around the globe and in context of Nepal.The chapter is classified

into five main sections. The first section deals with concept on green banking where

we discussed about application of theories on green banking. The second section deals

with the theoretical framework in which the theories related to green banking has

been reviewed. The third section deals withthe conceptual review; four section deals

with empirical literature in which we reviewed about green banking and its practices

in different international and local banks. The final section deals with the policy

review where the study discussed about sustainable development goals, banking

policy in Nepalese context.

2.1.Thematic Review

The thematic review discussed the literature based on theoretical concepts and new

themes. A thematic literature review of research articles was undertaken in order to

determine the level of awareness about green banking practices (Broadhurst &

Harrington, 2016). This review is mainly concerned with the enhancement and

development of student learning experience. This section involves concepts of green

banking, new trends in banking system, and history of banking system in Nepal,

origin of the concept of green banking, green banking initiation in Nepal and

advantages of green banking system.

Concept

Several definition on green banking has been given by some researchers:

Green banking can be defined as encouraging environmental-friendly

practices and decreasing the carbon footprint from banking operations

(Islam & Das, 2013).

Green banking is any form of banking from which the country and

nation gets environmental advantages (Lalon, 2015).

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Green banking is an effort by the banks to make the industries grow

green and in the process to protect the natural environment (Bhardwaj

& Malhotra, 2013).

Green banking is to make internal bank processes, physical

infrastructure and information technology effective towards

environment reducing its negative impact on the environment to the

minimum level (Cholasseri, 2016).

Green Banking is a process of combining operational improvements,

technology and changing client habits in market place (Biswas, 2011).

Green Banking refers to different financial services and products

provided by financial institutions for sustainable development (Shakil

et al., 2014)

Therefore, from the above definition, it is clear that green banking is an ethical and

social banking which deals with promoting environmental friendly activities by

reducing carbon footprints from the operations of banks and other institutions. Some

of the banks in Nepal such as Laxmi Bank, Nepal Investment Bank and Civil Bank

has started to realize the importance of green banking and they are taking up various

green banking initiatives like promoting e-banking activities, spreading awareness and

educating people to the respective field. The concept of green banking was formally

started in 2003 with the intention to protect the environment. In 2003, Congressman

Chris Van Hollen of USA introduced a Green Bank Act with the aim of establishing a

green bank under the ownership of the US government.

New Trends in Banking System

Recently, the banking sectors are undergoing the process of radical changes because

of excessive competition of global players and changes in tastes, preferences and

habits as well as expectations of customers for new products and services (Yajurvedi,

2017). Banking industry has become highly competitive in today‟s world so in order

to sustain in this competitive market, banks should go for the latest technology and

innovative ideas that also includes the issues like environmental concern so it can also

help in developing more eco-friendly method to cope up with changing market.

According to Kumar & Pavithra (2017), there has been considerable innovation and

diversification in the business of commercial banks and those banks are involved in

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the field of consumer credit, credit cards, merchant banking, internet and mobile

banking, leasing, mutual funds etc. Similarly, some of those banks have already set up

subsidiaries for merchant banking, leasing and mutual funds. The major development

areas happened in banking sector are internet, Society for Worldwide Inter-Bank

Financial Telecommunications (Swift, Automated Teller Machine (ATM), cash

dispensers, electronic clearing service, bank net, chip card, phone banking, tele-

banking, internet banking and mobile banking. In upcoming days, banks are expected

to play a vital role in the economic development and emerging market that will

provide opportunities to harness.

History of Banking System in Nepal

Towards the end of 8th century, Gunkam Dev had borrowed money to rebuild the

Kathmandu valley. This shows that banking service is the oldest service industry in

Nepal involved in lending and borrowing activities and has gone through various

stages of evolution and development since the Vedic times (200 to 1400 B.C). Later

with the growing necessity of the commercial banks in Nepal, Nepal bank Nepal

limited came into being in 1937 A.D as the first commercial bank in Nepal under the

Nepal Bank Act 1936 A.D replacing the older system of banking with the motive to

develop the trade and industry in the country. At the time the authorized capital of

NBL was rupees 10 million divided into 1, 00,000 shares of Rs. 100.00 each. This

took over the responsibility of „Tejarath Adda‟ attracted people from the predominant

shahu‟s transaction and introducing other services as well. Being a commercial bank

it was natural to be a profit driven organization and also had to look after the

neglected sectors and therefore NBL was established with 51% ownership of His

Majesty Government (HMG) and 49% from the equity participation from the private

sector. With the development of the banking sector and to help the government,

formulate monetary policies, Nepal Rastra Bank was set up in 1956 A.D (14th

Baisakh

2013 B.S) the central bank of the country. Since then it has contributed to the growth

of financial sector.

However, as the Central Bank, Nepal Rastra Bank had its own limitations and as a

commercial Bank, it was logical for Nepal Bank Ltd. to go to unprofitable sectors. So

to catch up with these problems, the government established Rastriya Banijya Bank in

2022 B.S (1965 A.D), under Banijya Bank Act 1965 A.D. as a fully state owned

commercial Bank. Then the establishment of Nepal Industrial Development

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Corporation (NIDC), employee Provided Fund, Agriculture Development Bank etc.

followed the formation of financial institutions.

Origin of the Concept of Green Banking

The concept of green banking has been origin from western countries and has

officially launched in March 2003 with a motive to protect the environment. Green

banking is any form of banking from that the society can get the environmentally

benefits (Lalon, 2015).The banking sector can play an intermediate role between

economic development and environment protection by promoting socially responsible

and environmentally sustainable investment.The concept of green banking was

formally started from 2013 with the motive of protecting the environment. Later, the

Equator Principles (EPs) were launched and some of leading global banks like

Citigroup Inc, The Royal Bank of Scotland, Westpac Banking Corporation initiated

and adopted the green banking practices. Congressman Chris Van Hollen of USA

introduced Green Bank Act with the objective of establishing a green bank under US

government ownership.

After introducing green banking, the initial aim is to minimize use of paper in banking

works because to make all kinds of papers need to cut trees as raw materials which

tends to reduce the oxygen and increase carbon-dioxide. According to Chris Van

Hollen, there are two types of green banking practices: one is in-house green banking;

another is practice by the bankers in their organization. In-house green banking

includes creating clean and hygienic banking environment, green building,

reforestation, online banking, waste management, installation of solar panel on the

rooftop of the bank and using high mileage vehicles, reducing sound pollution, using

webcam for video conferencing instead of physical meetings, online statements,

emailing documents. Similarly, another major practices by the bankers in their

business area are financing the green projects like Bio-gas Plant, Solar/Renewable

Energy Plant, Bio-fertilizer Plant, Effluent Treatment Plant (ETP), Projects having

ETP working on specific green projects, voluntary activities of banks. Green banking

use proactive measures to conserve environment and to find climate change

challenges while financing along with efficient use of renewable, non-renewable and

natural resources.

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Green Banking Initiation in Nepal

During the last few decades, the climate change and environmental protection has

been one of the biggest emerging issue around the globe. Many prime concern of

governments, policy makers, business firms and other institutions pay special

attention towards environmentally friendly practices. Few years back, issues relating

to environment were barely relevant to financial sectors as well (Shaumya &

Arulrajah, 2017). However, banks have been viewed as contributing to pollution

through their operations and increasing emission of carbon dioxide via use of air

conditioners, lights, electronic and fuel equipment, financing environment polluting

projects. Hence, the proper implementation of green banking has become a need to

promote environment-friendly practices and reducing carbon footprints establishing

the internal banking processes, physical infrastructure and effective information

technology towards the environment.

In 2009, the first green based bank was established in Mt. Dora, Florida, United States

(Jayabal & Soundarya, 2016). Similarly, in context of Nepal, Laxmi Bank was the

first bank initiating green banking strategies in Nepal (Mehta & Sharma, 2016).

Laxmi Bank mainly focuses on digitization through two core services i.e. mobile

money service and internet banking (Risal & Joshi, 2018). The introduction of such

initiatives helps to avoids customer-counter delay and provides access to easy finance.

Likewise, Samina Bank also seems encouraging hydropower investment, solar energy

development funds to promote green banking activities to protect the environment.

Most of the banks in Nepal like Laxmi Bank, Civil Bank, Nepal Investment Bank etc.

have started providing loans for bicycle and solar energy. Promoting bicycles as

emission-free means of transportation through an array of activities, offering

attractive loan packages for environment-friendly products and savings product that

reward the customer for eco-friendly practices are some of the bank‟s activities to

reinforce their focus on the environmental protection (Mehta & Sharma, 2016). The

bank also offers a “Green Savings Account” that has been planting one tree for every

account a customer opens in their bank. Not only this bank strictly advise their

employees to use less paper as possible and provide online banking products to their

customers. Therefore, these kind of activities by bank will be helpful to implement

green banking policies and practices.

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Advantages of Green Banking System

Green banking means promoting environmental friendly practices and reducing

carbon footprint from banking activities (Bihari, 2010). Green banking is like a

normal bank, which considers all the social and environmental or ecological factors

with an aim to protect the environment and conserve natural resources. Gupta (2015)

states that green banking system has many benefits as the products of green banking

helps to reduce paper consumptions, promotes environmental friendly banking

activities, reduces stationary cost, reduce resources wastages and protect environment.

Furthermore, the major benefits of green banking system are enlisted below:

It helps to avoids use of paper at work and rely on online transactions and less

paperwork means less cutting of trees which prevents environment.

Creating awareness to business people about environmental and social

responsibility enabling them to do an environmental friendly business practice

Green banking system helps to adopt and implement environmental standards

for lending, which is really a proactive idea that would enable eco-friendly

business practices which benefit our future generations.

Green banks gives more importance to environmental friendly factors like

ecological gains thus interest on loan is comparatively less.

Use of online banking instead of branch banking saves time.

Therefore, these above are some of the benefits of green banking system. The proper

implementation of green banking initiatives helps to reduce paper work in banking

transactions and promotes online and internet transaction in banking activities.

After the thematic review, it is observed that there are many issues regarding green

banking initiatives in both national and global context. Many countries are paying

special attention to climate change and environmental protection so the concept of

green banking has been emerged to protect the environment by reducing paper

consumption in banking activities. In context of Nepal, Laxmi Bank was the first

pioneer to initiate the concept of green banking and later many banks are practicing

green banking initiatives. The concept of green banking is very important in present

era because there are many burning issues on environmental protection. Similarly,

there are many advantages of green banking to protect environment for sustainable

development. The main advantages of green banking are helps to avoid the maximum

12

use of paper, promote online and internet banking, gives more importance to

environmental friendly factors. Therefore, it is revealed that green banking is very

important for protecting the environment.

2.2. Theoretical Review

Grant and Osanloo (2014) stated that theoretical framework is a framework which is

based on an existing theory in the field of inquiry that is concerned with the

hypothesis of the study. It helps to provide a general set of ideas within which a study

belongs. This section deals on the theoretical aspect of the study.This part of study

includes different theories concerned with green banking and its initiatives, practices

and policies. Various theories were reviewed in order to find out the relatable

variables and concepts for the research. This section of the study highlighted on

various theories and its model defined by different scholars and researchers.

Equator Principles

Equator Principles (EPs) was developed by International Finance Corporation

Performance Standards on Social and Environmental Sustainability and on the World

Bank Groups Environmental Health and safety Guidelines. It is a set of voluntary

guidelines adopted by private financial institutions to ensure that large scale

development or construction projects appropriately consider the associated potential

impacts on the natural environment and the affected communities (Lawrence &

Thomas, 2004). It is a risk management framework, adopted by financial institutions,

for determining, assessing and managing environmental and social risk in project

finance. It is primarily intended to provide a minimum standard for due diligence to

support responsible risk decision-making.

This principle is significance for the study because it deals with the potential impacts

on the natural environment and green banking also focus on making environment

green and safe. EPs are mostly set up on the basis of International Finance

Corporation (IFC) performance standards on social and environmental sustainability

and on the World Bank Groups Environmental Health and safety guidelines.

13

Figure 1: Equator Principles

Source: Lawrence & Thomas (2004)

Typology of Banking & Sustainable Development

The theory “Typology of Banking and Sustainable Development” was developed by

Jeucken in 2001 A.D. This theory deals with the decision taken by banks in order to

provide products and services to those customers who take into consideration the

environmental and social impacts of their activities. This model include four phase of

banking that focus on the environmental sustainability, they are: defensive banking,

preventative banking, offensive banking and sustainable banking.

Figure 2: Typology of Banking & Sustainable Development

Source: Jeucken(2001)

14

Theory X and Theory Y Model

The Theory X and Theory Y has been developed by eminent psychologist Douglas

McGergor in his theory of motivation in 1960s. This theory deals with the positive

management style and its techniques. According to McGergor, there are two basic

approaches in order to manage the human resource in an organization. Most of the

employees in an organization is influenced by Theory X so they are getting poor

result and some employees were influenced by Theory Y which provides better result

and performance.

Figure 3: Theory X and Theory Y

Source: Bojadziev et al. (2016)

From the theoretical review, it is observed that the “Equator Principles” helps to

ensure socially and environmentally responsible financing of large scale

infrastructure, mining and energy projects. This theory is mostly set up on the basis of

IFC performance standards on social and environmental sustainability. This study

uses various theories to have better overview on concept of green banking and their

policies. The theory “Typology of Banking & Sustainable Development” deals with

the decision taken by banks in order to provide products and services to those

customers who take into consideration the environmental and social impacts of their

activities. Likewise, “Theory X and Theory Y Model”concerned with the positive

management style and its techniques. These theories helps to clear the concept and

understanding of banking activities and green banking concept. Similarly, among

these three theories, Equator Principles Theoryis most important theory for

enhancement of green banking theory in developing context as it focuses on making

environment green and safe and hence promotes practicing green banking products.

15

2.3. Conceptual Framework

Camp (2001) stated that the conceptual framework is a structure which the researcher

believes to explain the natural progression ofthe phenomenon to be studied in the

research. It is based on the concepts which are the main variables in the study. It is

linked with the concepts, empirical research and important theories used in

promoting and systemizing the knowledge adopted by the researcher in their

research (Peshkin, 1993). In this section, various conceptual framework developed by

various scholars and researcher has been reviewed and discussed.

Model Internal and External Liability of the Bank

This model has been highlighted on the basis of internal and external liability of the

bank. This model will not only highlight internal green activities but also demands

excellent environment-friendly green lending policy. According to this model, a bank

can ensure its green banking practices and be free from internal and external liabilities

of environmental pollution. This framework deals with different dimensions that

encourage green banking activities, they are: reduce pollution by its operations,

reduce pollutions of companies those are taken credit facilities from the bank, meet up

internal environmental liability of the bank, meet up external environment liability of

the bank, green lending policy, in-house green decorations, paperless statements,

electronic transactions, solar energy consumptions, net banking and mobile banking

(Mehedi & Kuddus, 2017).

Figure 4: Model Internal and External Liability of the Bank

Source: Mehedi & Kuddus (2017)

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Schematic Diagram of Conceptual Framework

According to schematic diagram of conceptual framework, this model has been

designed to know the influencing factor that affect environmental performance of

bank. There are four dimensions namely employee related practices, daily operation

related practices, customer related practices and bank‟s policy related practices

constituting four independent variables along with their dependent variable bank‟s

environmental performance. Bank‟s environmental performance being the dependent

variable whereas environmental training, energy efficient equipment, green loan,

green project, and green policy being the independent variable.

Figure 5: Schematic Diagram of Conceptual Framework

Source: Risal & Joshi (2018)

Graphical Model of Adoption of Green Banking

This model was designed by Ahmad et al. (2013) in their study in which there are five

factors which influence the dependent variable i.e. adoption of green banking. The

dependent variable is influence by five independent variables, they are: pressure from

stakeholder, potential for the profitability, concern for the environment, risk

minimization and image improvement. They conducted the study on the basis of a

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graphical model which will show the interconnections of green baking among some

variables that were identified through literature review.

Figure 6: Graphical Model of Adoption of Green Banking

Source: Ahmad et al. (2013)

After the conceptual review, it is found that many scholars has developed their own

framework for the study by reviewing and reading different existing models and

frameworks. These above framework has been designed by their respective scholars

for their study in order to meet the objective of their study. The model of internal and

external liability of the bank is concerned with ensuring the green banking practices to

be free from internal and external liability so the banks can easily practice green

banking policies. Various above mentioned model deals with the adoption of green

banking and its influencing factors like pressure from stakeholders, concern for

environment, risk minimization and image improvement that have positive impact on

adopting green banking practices.

Similarly, after reviewing conceptual review of various scholars, the important

dependent and independent variables were identified concerned with green banking.

The dependent variables important for these studies are adoption of green banking,

bank‟s environmental performance and understanding on green banking. Likewise,

the independent variables are in-house green decoration, paperless statements,

electronic transactions, solar energy consumption, internet banking, and mobile

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banking, green lending policy, environmental trainings, energy efficient equipment,

green loan, green project, green policy, pressure from stakeholder, potential for the

profitability, concern for the environment, risk minimization and image improvement.

Hence, it is found that these above dependent and independent variables are important

for green banking study.

2.4. Empirical Review

An empirical review is based on observed and measured phenomena and derives

knowledge from actual experience rather than from theory or belief (Long, 2014). The

research may use quantitative research methods, which generate numerical data and

seek to establish causal relationships between two or more variables. Empirical

research articles may use qualitative research methods, which objectively and

critically analyze behaviors, beliefs, feelings, or values with few or no numerical data

available for analysis. This section includes review of various articles of different

scholars related to green banking and green banking initiatives, practices and

challenges around the globe. Various articles were reviewed to get insight of green

banking in context of Nepal and around the world.

Sathye (1999) has explained the factors that affect customers on adopting the internet

banking. The survey was conducted from individual residents and business firms in

Australia. The respondents for the study are 250 each from individual and business.

There are several factors that influence in adoption of internet banking, they are no

security concern, ease of use, awareness of service and its benefits, reasonable price,

no resistance to change and availability of infrastructure. The study addressed the

major aspects that influence the customer to adopt the internet banking in Australia.

He identified the security concerns and lack of awareness about internet banking

which are the major factor that create difficulties in practicing internet banking in

Australia. The study also observe the issues like lack of awareness about the service

and its advantages, complexities in use, resistance to change which are the matters of

customer education. However, there are some possible solutions that could involve

giving wider publicity under scoring the benefits, demonstration where public can

have an experience of using internet banking. The study concludes that the delivery of

financial services over the internet should be treated as a part of overall customer

service and distribution strategy. The rapid migration of customers to internet banking

help in resulting in considerable in operating costs for banks.

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Polatoglu and Ekin (2001) examines the consumers‟ acceptance of internet banking.

The data for the study has been collected through consumer survey administered

among internet banking customers of Garanti Bank. 114 respondents has been

gathered for the study. The majority of the respondents were male in which 83.3%

were between the age of 20 to 39 and 55% of them are married and over 80% were

university graduates. Structured questionnaire was used to gather the data for the

study. They conducted two factor analyses to analyses the collected data. The first

factor explains the satisfaction of customers from the Garanti Bank‟s internet banking

services. The first factor consists of reliability, security and privacy of internet

banking transaction. The second factor describe the actions that the Garanti Bank‟s

customers are satisfied or dissatisfied from internet banking services. It is found that

early adopters are more satisfied than other groups on reliability, security and privacy.

The another finding of the study was the use of alternative banking channels by

Turkish customers, 90% of them reported that they have been using branches,

followed by ATMs and phone banking. They concludes that most of the customers are

using banking services very frequently and most of them are satisfied with the internet

banking services provided by Garanti Bank.

Sohail and Shanmugham (2003) has explained the recent trends in e-commerce

revolution. The study was conducted in Malaysia in order to know the preferences of

customers for electronic banking. The study also focus on the various factors that

impact on influencing the customers to adopt e-banking. The study is based on the

survey of 300 respondents that indicate the significant difference between the age and

educational qualifications of electronic and conventional banking users. The study

addressed that if there are any demographic variables that influence the usage of e-

banking, demographic variables were compared with the e-banking and non e-

banking users. They study also found the seven factor i.e. accessibility, reluctance,

costs, trust in one‟s bank, security concerns, convenience and ease of use that effect

on adopting electronic banking. The study revealed that there is a significant effect of

those factors on the usage of banking facilities. However, the cost of computer,

internet access and security concerns of e-banking have no significant influence in

adopting of e-banking Malaysia. The study concludes that there are greater

promotional efforts on the part of banks to make greater alertness in the use of e-

banking and its advantages for the success of e-banking services patronage.

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Wang et al. (2003) analyze the factors that regulate the acceptance of internet

banking by the consumers. The study is based on the data collected from taking the

telephone interview from 123 respondents. Out of total 123 respondents, 55% were

male and most of them were between the ages of 20 to 40. This study also explores

the effect of computer self-efficacy on the aim to use internet banking. They used

LISREL 8.3 tool to analyze the collected data for the study. It is found that the study

highly support the relevance of using extended TAM to understand the objective of

people to adopt internet banking facility. The substantial effects of perceived

usefulness, perceived ease of use, and perceived credibility on behavioral intention

were analyzed and it can be seen there are strong influence of perceived ease of use

than perceived credibility and perceived usefulness. They also identified that new

TAM variable i.e. perceived credibility have a great influence on behavioral intention

of user than traditional TAM variable i.e. perceived usefulness. The study concludes

that perceived ease of use, perceived usefulness, and perceived credibility were found

to be an important antecedents of the intention to use an internet banking system.

They suggests that the internet banking authorities should develop the beliefs of

usefulness, ease of use and credibility of the customers concerning internet banking.

Sahoo and Nayak (2007) explores the green banking practices in India. The study is

concentered on achieving the sustainable development by allowing markets to work

within the designed framework. The study concerned on application of green banking

for preventing the quality of assets and also for sustainable development. They further

observed that banks should go green in order to make environmental and ecological

aspects in balance. This study highlights the importance of green banking, sites

international experiences and also explore the important lessons for sustainable

banking and development in India. It is found that if the concept of green banking

would implemented it would impact positively in environmental issues. The study

found that none of the banks are adopting the concept of green banking because of

time issue. They explained that the banking and financial sector should be made to

work for sustainable development. It is found that some banks are introducing green

bank loans and products such as investing in environmental projects i.e. recycling,

farming, technology, waste etc., providing options for customers to invest in

environmentally friendly banking products and investing in resources that combine

ecological concerns and social issue. The study concludes that banks should play a

21

significant role to take environmental and ecological aspects as part of lending

principle.

Polasik (2008) analyze influencing aspects that impact on the decision for the

adoption of internet banking in Poland. The study is based on primary data which has

been collected by taking interview with 3519 internet users taken as a respondents.

Interactive questionnaire was used to collect data for the study. He observed the

different variables that impact on taking the decision to adopt the internet banking

such as internet experience and connection mode, perceived security, exposure to

marketing campaigns, experience with other banking products, and socio-

demographic characteristics. The study found that high level of perceived security in

cyberspace is important to foster the adoption of online banking. Moreover, those

customers who are used to with electronic distribution channels like mobile banking

or payments cards shows high activeness to use an internet account. The study

addressed that Polish customers have a similar kind of preference to those observed in

more developed countries but still certain problems in further advancement in online

banking do exist. The study identifies presence of infrastructural barriers coupled with

lower income per capita and lower saturation with basic banking services has been

taken as a restriction. The study concludes that though customer trust is hard to gain

and easy to lose, the internet banking providers should make an effort to maintain a

good record by maintaining the security threats in effective manner.

Ahmad et al. (2013) analyze the aspects in adoption of green banking in commercial

banks of Bangladesh. This study examine the developing banking strategies which

ensure the sustainable development of economy. The study has been conducted in

branches of the banks in Dhaka city by taking 300 bankers as a respondent who work

as an officer and those who are in upper level position. Structured questionnaire has

been used to collect the data for the survey and likert scaling technique was used to

analyze the collected data. The study has identified the aspects behind adoption of

green banking policy. It is found that 6 out of 18 components are retained on the basis

of eigenvalue and those six components contains 65% of influential power in the

adoption of green banking in commercial banks of Dhaka. The study identified that

most of the commercials banks in Dhaka adopt green banking practices to build their

brand image in the market as the concept of green banking concern with environment

issues. They concludes that commercial banks in Bangladesh are practicing green

22

banking policy to be more responsible corporate citizen. The study addressed that

there are multiple aspects that influence in adopting the green banking in banks. They

also explained the advantage of adopting green banking policy in sustainable

economic development.

Ullah (2013) explore the issues regarding green banking in selected banks such as

State-own Commercial Banks (SCBs), State-own Specialized Development Banks

(SDBs), Public Commercial Banks (PCBs) and Foreign Commercial Banks (FCBs).

The study is based on the collected data from secondary source. The data were

collected from annual reports of Bangladesh Bank, different seminar programs and

other internet websites. The researcher found that almost all type of banks are using

online banking facilities representing 36.3%. However, it is noticed that SCBs and

SDBs were not well aware of green banking policy of Bangladesh Bank. It is found

that PCBs and FCBs are mostly using ATM facilities. The study investigate that in

green financing sector, the investment of PCBs is Tk. 127.6 billion, SCBs Tk. 11.4

billion, FCBs Tk. 20.6 billion and SDBs Tk. 43.8 million respectively. It can be seen

that PCBs investment is higher than other banks. The findings of the study indicates

that most of the PCBs and FCBs adopted green banking policy and other banks like

SCBs and SDBs have not adopted yet. The researcher concludes that in spite of

having lots of opportunity in green banking, most of the banks are not adopting the

system due to the awareness. The study suggest that banks should promote the

awareness regarding the benefits of adopting green banking practices.

Islam and Das (2013) examine the practices of green banking in Bangladesh. The

study focus on the online banking, mobile banking green financing and guidelines for

green banking practices. This study based on secondary data and total ten commercial

banks of Bangladesh has been selected on the basis of CAMEL‟S rating and Risk

Based Capital Adequacy (RBCA) measurement that are representing green banking

practices. Bangladesh bank also highlights on the major environmental issue for

launching new branches. The study found that banks has allocated Tk. 525 crore for

green banking and Tk. 505 crore for green financing from their budget. It is found that

40 out of 47 private and public commercial banks has establishes green banking unit

and 41 commercial banks has formulated the policy of green banking. The study

found that 90.73% of the total branches of private commercial banks have been

practicing online banking. The study observed that 23 commercial banks have a

23

license to provide mobile financial services out of which 14 banks have already

started working their operations. The study concludes that green banking practices in

Bangladesh are not in sufficient level as green banking plays an important role to

protect the environment. They recommends that government should encourage the

public about practicing green banking.

Sharma et al. (2014) identified the customer‟s awareness on green banking initiatives

in selected public and private sector banks in Mumbai. The purpose of this study is to

identify the opinion and level of awareness of bank employees and customers

regarding green banking concept in public and private sector banks. The study is

based on primary data in which the respondents having sound educational background

were targeted. Total 100 respondents were considered for the study. All the bank

considered for the study were top rated banks so these banks are chosen from public

and private banking sector. The findings of the study shows that out of total

respondents, 77 % were using green banking products but were not aware of the

terminology of Green banking and remaining 23 % were quite aware of the green

banking services provided by their bank. Similarly, the study also reveals that green

banking initiatives like communication through press, bank environmental policy,

concession on energy savings, solar ATMs, green CDs etc. are still not introduced by

the respective banks according to the respondents. Furthermore, they identified some

of the obstacles experienced by respondents regarding green banking practices they

are: data security and privacy, lack of education, technical issues, traditional approach

and lack of infrastructure. They concludes that India should take some strict steps to

harness these banks and financial institution to adopt the principle equator guideline

so that they can contribute in the protection of environment in future and practice

green banking initiatives.

Yadav and Pathak (2013) analyzed the role of green banking for environmental

sustainability in the private and public sector banks in India. This study aim to

identify the different green banking approaches adopted by private and public sector

banks in India. The study follow the case study method to analyze the data. The data

for the study were collected from- secondary method such as company official

website, annual reports, sustainability reports and articles. The banks for the study

were selected on the basis of their net earnings per year. This study further attempts to

categorize the phases of green marketing initiatives of the banks on their green

24

banking initiatives. Similarly, the sample includes top performing banks of the public

sector and private sector. The findings of the study shows that Indian banking sector

have understood the importance of environmental protection and also started taking

various initiatives of green banking approach. Likewise, the result of this study

reveals that the public sector banks have taken more green banking initiatives than

private sector banks except ICICI bank. The study concludes that the banking sector is

getting modernized and new services like net banking, mobile banking are being

prioritized. They also recommend some managerial implications that banks should

focus on creating awareness among society and practice more environmentally

friendly services.

Ullah (2014) explained the prospects, progress and difficulties of green banking

practices in Bangladesh. He analyze the policies and strategies of green banking

which is concerned with environmental issues. Bangladesh bank has initiate a

numbers of green banking practices after considering the importance of green

banking. The study aimed to assess the best practices of Bangladesh bank in eco-

friendly banking system. The survey has been conducted in twenty commercial banks.

The data has been collected through face-to-face interview, telephone and some are

also collected from email. Unstructured questionnaire was used and different

descriptive statistical tools, charts, tables have been used to analyze the collected data.

The study found that 47 banks are formulating the environmental policies and it

shows that BB‟s initiatives have an incredible change in understanding and approach

in banking communities. In context to paperless banking, all the branches of FCBs are

delivering online banking facilities. 26 banks out of 44 banks have internet and 24

banks have mobile banking services. The study observed that most of the banks are

taking initiation to introduce internal environment management. He also addressed

that banks are also doing environmental risk rating and it has been rated 4394 and

12088 projects in the year 2011 and 2012 and the finance amount of numbers of rated

projects has been increased by 158.75% and 159.69% respectively. He concludes that

however there are many restriction the overall green banking implementation is quite

satisfactory.

Deka (2015) examine the green banking practices by using environmental strategies

of banks. They analyze that banks are the important stakeholders which can be a

better contribution towards environment in adopting green banking practices. The

25

survey has conducted in Assam with 486 customers of State Bank of India (SBI) as a

respondents. Structured questionnaire was used for the survey. Descriptive analysis

techniques has been applied. The study found that 50% of the respondents are not

aware of the concept of green banking in the banks. It is found that most of the

respondents are practicing green banking but they are using it unknowingly. The

study observed that only 19.5% are using online banking facility and most of the

respondents did not feel secured using online banking facility. After examining the

user of mobile banking in SBI, only 20% from the total respondents are using mobile

banking services. The study also analyze the impacts of different green banking

practices on the environment in which it is found that 80.7% of respondents perceive

that adoption of green banking practices contribute in environment as it saves the

paper and energy. Rest of them does not feel green banking as environment friendly.

The study concludes that adoption of green banking practices has a positive impact on

the environment and it also positively impact on sustainability as the practice of green

banking saves paper, energy, fuel, water, time and cost. They also identified that the

use of green banking helps to reduce the workload of the bankers in the bank.

Hossain et al. (2015) have explained that attitude and perception of consumer toward

green banking in Bangladesh. This shows that green banking includes the

environmental and social responsibility of banks towards ensuring effectiveness of

environment and ecological system, for offering wide range of financial products and

services. Similarly, in Bangladesh impact of environment and climate change is

serious problem and that‟s direct impact in functional areas of the bank. In

Bangladesh Green Banking Policy was developed in 2011. This study shows that

some issues related to green banking policy and to save the environment as well as to

increase financial sustainability is necessary. But this study mainly focuses in the

perception and awareness of people toward the Green Banking in Bangladesh.

However, people perception on the environment, satisfaction and acceptability of the

current range of “green” products and services, attitude towards banks which adopt

the practice on Green Banking. The environmental impact, responsibility as well as

performances in their activities is directly impacts the green banking. This study also

shows that environmental impact is directly affect the external activities of the bank,

where investment in environment and carefully lending is the responsibility of the

banking sectors. Environmental management, use of appropriate technology and

26

management system of bank are the lending principles and which are directly forced

industry sector to mandate investment in environment.

Vijai and Natarajan (2015) have explained that customers‟ awareness about green

banking products in certain commercial banking in India in Cuddalore district.

Sample was taken in two stage, in first stage the choose top five Indian commercial

bank and in second stage they collect they choose semi-urban 18 and urban 7 branch,

out of 5 selected commercial banks green banking is recent concept. In selected

branch they choose 15 saving bank accountholders and 10 current accountholders. In

this way they collect data from 625 customers as a sample. To collect primary data

multi- stage sampling technique was adopted and secondary data were collected

through journals, magazines, government‟s reports, RBI bulletin, books and other

various sources. Similarly, data were analyzed by the help of t-test, one way variance,

coefficient of variance and multiple regressions. The result shows that there is no

significant relationship among the respondent with gender, age, education status,

annual income, occupation and types of accounts about green banking. However, it

also shows that there is significant relationship among awareness level with locations,

banks and types of banks about green banking. The moderate correlation shows that

awareness level and green banking product and selected personal variable has

positively correlated (0.756) and R square indicate that 57.6% variation among

awareness level and other personal variables. It also shows that 42.08% respondent

were not awareness about green banking, where mean awareness level 3.20 about use

of energy and 3.17 about online bill payments.

Masukujjaman et al. (2015) analyze the perception of bankers on green banking.

They examine the concept of green banking, its advantages, difficulties and relation

with Islamic banks. The survey has conducted in 48 Islamic banks in Dhaka,

Bangladesh. They used simple judgmental sampling technique. Structured

questionnaire were used to take face-to-face interview for collecting the data. They

observed that most of the bankers perceived green banking as an environmental

banking and they also believed that it is socially responsible banking and ethical

banking. They study also find out the benefit of green banking as its first benefit is to

protect environment and second is to reduce the resource wastage. Going green also

reduce the stationary cost and increase operating profit. Going green is also concerned

with many social activities like corporate social responsibility. They also identify

27

some of the difficulties in adopting green banking initiatives. The top two difficulties

in adopting green banking are high adoption cost and hampering the privacy of

customers. The study concludes that bankers believed that green banking is related

with environmental banking as it cares about environmental issues. In context to

adopting green banking initiative, the major complexity is identified as high adoption

cost.

Shaumya and Arulrajah (2016) explores the green banking practices in Sri Lanka.

They measure the practices of green banking in the commercial banks in Sri Lanka.

The survey has been conducted in only four private banks of Sri Lanka as only these

banks are currently practicing the concept of green banking. The data for the study

have been collected from the annual reports of selected private banks i.e. Ceylon PLC,

HNB PLC, Sampath Bank PLC and Seylon Bank PLC for the last three year i.e. 2013,

2014 and 2015. The systematic content analysis were used to analyze the collected

data for the study. The study found that in four private commercial banks, 98 green

banking practices has been doing. The similar kind of green banking practices found

in all banks are implementation of social and environmental management system

(SEMS), installation of energy saving tools, e-waste management and use of e-mail

and intranet communication. They also analyze four dimension of green banking. It is

found that each dimension contribute in the practicing the green banking by

motivating employees efforts in creating and sustaining green banking concept in

practice, by making daily operations activities more environmental friendly, by

involving customers in those projects which does not harm the environment and

finally by adopting environmental friendly policies, systems and principle to become

a greener bank. They concludes that this findings will contribute to environmental

protection and management by exploring the practices of green banking in Sri Lanka.

Faruque et al. (2016) analyze the green banking and its practices and potential to

grow in Bangladesh. This study estimate the green banking practices in Bangladesh.

The study aimed to create awareness of green banking among businesses and public

people. The study is based on secondary data collected from different magazines,

newspapers, internet and websites of commercial banks. The data has been analyzed

in the perspective of progress of green banking activities. The study found that most

of the banks focused on mobile and internet banking. Banks are facilitating 3.91% and

1.42% of total number of accounts in mobile banking and internet banking. The study

28

also found that some of the banks are introducing the use of solar energy in their

respective branches in which 99 branches of 18 banks have already installed solar

power panels. They observed that 212 branches and 150 SME units and ATM boots

are powered by solar energy and 3226 branches are facilitating the online coverage.

The study concludes that Bangladesh is one of the most climate changing countries in

the world. From the analysis, it can be found that the use of green banking in

Bangladesh is not in adequate. So, they also recommends government to utilize the

use of green banking for reduce the environmental concerns.

Tu and Dung (2016) observed the factor that affect the green banking practices in

Vietnamese banks. This study focus on identifying those factors which affect the

practices of green banking and role of green banking for sustainable development of

economy of Vietnam. The study used questionnaire method after conducting

preliminary interview with several banks in Hanoi. Those banks were selected which

have large revenues because green loans needs high initial investment costs. The

questionnaire has been distributed to 32 selected banks in Vietnam and 329

respondents were received from those selected banks. The SPSS has been used to

analyze the collected data. The study found that there are five variables including

understanding the definitions of green banking, the current activities of green

banking, the barriers in adopting the green banking practices, benefits of developing

green banking and focused business sectors of green banking which emphasizes the

willingness to adopt green banking in Vietnamese banks. It is found that these five

factor have positive relationships with the willingness to adopt green banking

practices. The researchers concludes their study as the awareness level and actual

implementation of the model in commercial banks of Vietnam are comparatively low.

The researchers suggests commercials banks to promote the awareness green banking

practices in the banks of Vietnam.

Ganesan and Bhuvaneswari (2016) have explained about the customer perception

towards green banking in India. In the term of sample 100 customers were taken

through convenience sampling method. Data were collected through both primary and

secondary method, where primary data were collected through structure questionnaire

method and close ended multiple choice methods was used and 26 multiple choice

question were asked, secondary data were collected through various research journals,

books, research papers and banks websites. Data were analyzed by the help of Chi-

29

square analysis (used to identify association between any two variables), one way

ANOVA (find out each variables and ascertain the association between dependent and

independent variable) and frequency table. This study analyzed that effectively and

efficiently use of IT and physical infrastructure to reduce the impact of environment

and effectively development of environment. It also shows that banking is never a

pollution industry, but now in banking sector increasing the carbon footprint due to

their massive use of energy. Similarly, this study focused that awareness of major

green banking services to its customers and shows the use of green banking facilities

are directly impacted by educational qualification. It shows that the age group 25-35

were used all the facilities which are provided by green banking and shows that

facility of green banking has no problem.

Shampa and Jobaid (2017) have explained about the various factors that influence

customers‟ about green banking practices in Bangladesh. Simple random sampling

technique was used to collect sample and the total sample was 246 respondents were

finalized. Five (5) point Likert scale and 23 dimension are identified and summarized

into five factors to analyzed data and found that customer needs and information.

Multiple interdependence technique was used to analyze the data and principle

component analysis (PCA) was used to determine minimum factors which responsible

with maximum amount of variance. Result shows that customers‟ expectations toward

green banking were already disclosed in quantitative part and other factors will help

critical decision. Similarly, it also shows that customers‟ expectation was influenced

by „level of information and customer needs‟ with maximum variance 16.04%, where

website information affects 0.714 and 24/7 service affect 0.755. The second factor

was „ethics and high yield saving‟, which maintain high degree ethical standard was

0.75, lower maintenance fee was 0.737, better deposit rate was 0.523 and lower

transaction cost was 0.535. The third factors was energy efficiency which galvanizes

banks to utilize available resource and renewable energy in effective ways. The forth

factors was product benefits which concern eco-friendly product, like green

mortgages, green home equity, and various other loans. The last factor was

„integration and personalization‟ which affect green banking approach and customer

marketing.

Koiry et al. (2017) have explained about the customers‟ awareness and practices

about green banking in Sylhet district of Bangladesh. Random sampling and

30

convenience sampling technique were used to collect data and 10 customers were

selected from each bank and total 56 banks were selected. Data were analyzed by the

help of t- calculation, F-test and Cronbach Alpha. The result shows that customers are

important part of banks, where higher respondent were 30-64 age groups, highly

educated, professional people, meal customers and green banking knowledgeable

people. Similarly it also shows that, they used recycled papers, use debit and credit

card to withdraw money, natural gas used vehicle were going to bank, used electronic

system, always used ATM, communication has been occurred by the help of audio

and video conference, SMS banking system and various other terms were used for

green banking. The reliability of using post-hoc test, value of Cronbach‟s Alpha was

0.859 that is higher than minimum desirable limit 0.70, where F-test value was

37.128, which was significant at 1%. This study also shows that green banking can be

treated as a part of banking industry to protect environment and positive views and

good knowledge about the green banking practice is very vital for the customer.

Customers were aware about SMS facility of the banking, which is important part of

the green banking.

Iqbal et al. (2017) have explored about the customers‟ perception about green

banking in Bangladesh. Nowadays, banks have been provides eco-friendly financial

services to adopt the concept of green banking. This is the concept, which minimizes

the impact of environmental in their business activities. Green banking acts as a

competitive advantage for banks to offer customers with the help of new ways to

deliver financial services. Adaptation of these service helps to experiences and quality

of service delivery toward customers‟ perceptions. This study also shows that service

qualities and other underlying factors directly affect the customers‟ behavioral about

green banking. The analyses shows that various factors of green banking like

reliability, responsiveness, empathy, privacy, and information quality has positive

effect on performance expectancy, but other factors like performance expectancy,

effort expectancy and facilitating conditions has also influence customers‟ behavioral

intention. Similarly, this study also shows that electronic quality and use of

technology is helps to builds the quality of green banking service. This study also

shows that customers were very rational in this era and they only want those service

which provide maximum utility and quality has positive effect the customers‟ toward

31

green banking. However, it also shows that improve the service quality that will

improve the customers performance of green banking.

Biswakarma (2017) has examined the green banking practices for understanding

strategy convergence in banking sector in Nepal. This study follows the quantitative

approach toward descriptive and casual research design and as sample 350 employee

were consider as a respondent. This study shows that banking industry is never

consider the pollution industry, but nowadays carbon footprint is increasing day by

days, that‟s direct effect to higher use of energy, high paper wastage, lack in green

building and so on. To reduce the carbon bank should use the green banking

technology and pollution reducing projects. Green banking concept is proactive and

smart way of thinking of effective of spaceship earth. There were various factors

related to green banking; green product/service, risk management, green investment,

green banking strategy and green human resource management. The result shows that

all dimension related to green banking have significant relationship with effectiveness

of banking. Environmentally products that combine the social concern care about the

renewable resource and focused green investment to fulfill annual targets, strategic

plan and budget at relevant activities effectiveness of Nepalese banks. It also shows

that Nepalese banking organization has huge potential of green banking practices. If

these banks focus toward effectiveness, it would be beneficial for risk reduction and

development of the nation.

Sharma (2017) examine the issues and challenges in adopting the green banking.

Green banking aims to promote the environmental friendly practices and focus on

reducing the cost of banking activities. In India, many banks has already started

different green banking initiatives, these initiatives brought convenience to the

customers and also helped banks in minimizing their cost of operations. The study

aims to measure the awareness level of customers regarding green banking and

identify the influencing factors affecting the adoption of green banking in selected

banks of India. The study was conducted in the selected public and private banks of

Jaipur, Rajasthan. There are 207 customers of those selected banks as a respondents.

The study include 68.59% of male respondents and 31.41% of female respondents.

This states that male respondents are actively using banking services that female

respondents. Correlation analysis has been used in the study to measure the

relationship between two different variables. It is found that the correlation between

32

awareness towards green banking and perception towards green banking is 0.433 and

the awareness towards green banking and issues of green banking is 0.557. After

findings the correlation, it is proved that there is significant difference in issues and

challenges related to green faced by private and public banks. Similarly, it is found

that there is significant difference in awareness level among customers related to

green banking in the selected private and public banks in India. The study concludes

that there is a vital role of customers of private and public banks in making the

concept of green banking successful.

Shaumya and Arulrajah (2017) conducted the research to identify the impact of

green banking practices on bank‟s environmental performance. Recently, almost all

the sector of world economy are facing a big challenge to deal with the environmental

problems and their impact in daily operations of the business. Most of the banks are

launching green banking initiatives in Sri Lanka. The study aims to measure the

impact of green banking practices on bank‟s environmental performance. The survey

was conducted by collecting primary data through self-administrated questionnaire.

155 employees were taken as a respondents of selected commercial banks in

Batticaloa Region of Sri Lanka. The collected data were analyzed by using computer

based statistical data analysis package, SPSS. The study found that the correlation

between green banking and bank‟s environmental performance are posit ively strong

which means the level of implementation of green banking has positive effect on the

level of bank‟s environmental performance. It is found that the improvement of

environmental performance of banks depends on the implementation of green banking

practices. The individual dimension which have separately contributed in bank‟s

environmental performance. Among these dimension, 55.2% have impact on bank‟s

policy related practices, 2.3% impact on employee related practices, and 1.6% impact

on bank‟s environmental performance. The study concludes that with the help of

green banking practices, banks can improve their environmental performance.

Shayana et al. (2017) analyze the complexities and prospects of green banking in

coastal region of Karnataka, India. This study mainly focus on encouraging eco-

friendly banking practices and reducing the use of paper from banking operations.

The survey has conducted in coastal region of Karnataka by taking 100 respondents.

The data are also collected from secondary source like books, articles, journals,

newspapers and web browsing. From the study, it is found that consumer perceives

33

green banking as a cashless banking which shows the misconception among

customers. They addressed that 50% of respondents are not using internet banking

facilities which means banks need to promote the internet banking facilities. They

also observed that in analyzing the difficulties on adoption of green banking, 35% of

customers are facing complexities under the limited scope for personal advice, 30%

are facing problem in security and rest of them i.e. 30% and 10% are facing

difficulties in transactions and lack of knowledge. The study identified that thebanker

find inconvenient in adopting the green banking and those problem can be evitable so

it shows the support for green banking practices. They concludes that banks should

made their short and long term objectives to promote green banking practices in

proper way.

Mehedi et al. (2017) identified the perspectives of bankers‟ regarding the indicators

for adopting the green banking in commercial banks of Bangladesh. The study was

conducted to know the perception of middle-level banker‟s towards adoption of

concept of green banking. The respondents for the study has been selected from

Shahjalal Islami Bank Limited for collecting the data. The data for the study have

been collected through semi-structured questionnaire method and selected six

scheduled commercial bank in Bangladesh. For the collection of data, sixty

questionnaire were sent to the respondents through e-mail addresses, in which 36

questionnaire were received including proper answer and for the further analysis, only

30 questionnaire were selected. The 5 point likert scale were used to analyze the

collected data. The researcher also used SPSS in order to analyze the factors. The

researcher found some of the factors that influence in adopting the green banking,

they are: governmental units, environmental pollution control policies, social group

pressure and pressure from international organization. The study also addressed the

most influencing power i.e. organizational pressure, environmental policy and

institutional regulatory framework representing 23.327% out of 57.641% of total

variance. The study concludes that the Bangladesh should take some corrective

actions by adopting the concept of green banking. The bankers‟ efforts of the

adoption tools that the banks are currently practicing regarding adoption of green

banking activities are delineated to credit cards, debit cards and other internet banking

facilities.

34

Risal and Joshi (2018)explore the influence of green banking practices on

environmental performance of banks in Kathmandu, Nepal.They conducted the

survey by collecting the data from 189 commercial bankers from five major banks of

Nepal, they are: Agricultural Development Bank Ltd (ADBL), NIC Asia Bank,

Sanima Bank, Laxmi Bank and Siddhartha Bank. They used convenience sampling

method to collect the data. The study apply cross-sectional qualitative approach with

descriptive model. They used SPSS software to analyze the collected data of the

study. The study found that there is positive relationship between green banking

practices and bank‟s environment performance. They addressed the positive impact of

practicing of green banking on bank‟s environmental performance in Nepal in which

the variation in dependent variable is 6.8% with significance level at 0.016. Similarly,

they also found thatthere is significant relationship between green policies,

environmental trainings, energy efficient equipment‟s and bank‟s performance

whereas there were not significant relationship with customers‟ related practices with

bank‟s performance. After simple regression analysis, it is found that green loan and

green project has not impact on environmental performance of banks. The study

concludes that there is positive influence of green banking practices on bank‟s

environmental performance in context of Nepal.

Uddin and Ahmmed (2018)analyze the evidence from Bangladesh about Islamic

banking and Green banking for the sustainable development. In Bangladesh, Green

banking is an essential part of Islamic banking that focus on protecting the

environmental issues. This study deal with the relationship between Green banking

and Islamic banking which contribute to sustainable development. For this study, the

data were collected from both primary and secondary source based on qualitative

research. The primary data for the study were collected through questionnaire method,

including the respondents like investors, executives and managers of Islamic banks in

Bangladesh. There are altogether eight Islamic banks like Islami Bank Bangladesh

Limited, Al-Arafa Islami Bank Limited, Social Islami Bank Limited, Exim. Bank

Limited, Shahjalal Islami Bank Limited, First Security Islami Bank Limited, ICB

Islami Bank Limited, and Union Bank Limited. There are total sample of 126

respondents selected for interviewing from 42 branches of Islamic banks in

Chittagong and Dhaka. The study found that most of the respondents agreed that they

have connected with online banking and internet banking in their operations. The

35

study also investigated the bankers are reconnoitering with the practice of components

of green banking.Most of the banker‟s believed that green banking is the part of

Islamic banking which promotes the environmental-friendly banking system. The

study concludes that the Islamic banks should promote the awareness of green

banking practices among bankers and customers through seminars, workshops and

training programs.

Deepa and Karpagam (2018) analyze the customer‟s understanding on green

banking in the selected private and public banks in Tirupur, India. This study aims to

examine the nature of green banking practices that perceived by the customers. The

survey has been conducted with the customers of banks in Tirupur city. The data for

the study has been collected from primary and secondary source. Questionnaire has

been used to collect primary data and secondary data has been collected through

websites of different banks, articles and journals related to banking. The sample size

30 has been taken for the study. The study choose general public and sampling units

based on convenience sampling. They used percentage analysis, henry garret ranking

method and weighted average analysis as a statistical tools to analyze the collected

data. The findings of the study shows that majority of the respondents (53%) have

been linked with State Bank of India includes SBI groups and least is axis bank, bank

of India, ICIC bank, Lakshmi Vilas bank. Similarly, the result indicates that most of

the respondents are highly aware about usage of alternative energy whereas they are

less aware about green bankingspecialties.Furthermore, they concludes that Reserve

Bank of India (RBI) and Indian government should play a vital role and formulate a

green policy guidelines and financial incentives for effective green banking practices.

Arymugam and Chirute (2018) have explored the factor determining the adoption of

green banking among commercial banks in Malaysia. Green banking is about making

the world better place without making any damage to the environment. The key

objective of this study was to analyze the recent factors that affect the bankers to

adopt green banking in the commercial banks in Malaysia. The study also aims to

identify about the relationship between green banking and factors affecting its

adoption. The survey was based on explanatory research design. Explanatory research

design has been selected because it tries to determine whether a variable that has been

chosen for the study are viable or not. The data were collected from primary source in

which the sample of 160 employees, customers and stakeholders were taken randomly

36

as a respondents from banks of Kuala Lumpur, Malaysia.Similarly, the tools used for

analyzing the collected data are Cronbach‟s alpha and Pearson chi-square. The

findings of the study shows that there is positive relationship among variables that are

chosen for the study. They conclude that most of the banks take green banking

initiatives to encourage environmental-friendly investment. Furthermore, banks may

apply ethics of sustainability and accountability to their business model, construction

of strategy for products and services, operations, and their financing activities to

become stronger.

Green banking has emerged as an important subject matter of study as it deals with

environmental friendly banking, reduce paper consumption, recycle waste properly,

sponsor tree plantation, advocates cleanliness and promotes social responsibility. Due

to climate change and environmental degradation issues, people are becoming more

conscious about conservation of environment hence the concept of green banking as

being emerged for sustainable development.

Several empirical studies shows that green banking isenvironmental banking that

deals with reduction of paper use in banking operations, reduce stationary cost, launch

green product and services and promote digitization. The study conducted by Sohail

& Shanmugham (2003) revealed that there are seven factors namely accessibility,

reluctance, costs, trust in one‟s bank, security concerns, convenience and ease of use

can affect the adoption green products like electronic banking. The green banking

practices are adopted in commercial banks of Dhaka to build their brand image as

green banking is concern with environment issues (Ahmad et al., 2013).

2.5. Policy Review

Various policies that has been formulated by different national and international

agencies related with internet banking, online banking and green banking were

discussed in this section.Policy review helps in understanding the principles and

regulations related to the study. Major polices adopted by Nepal government on

initiating green banking and its practices has been discussed in this section.

Sustainable Development Goals (SGDs) - Nepal

The study has reviewed SDGs paper. Among these papers, goal number four has

discussed about internet users and use of mobile banking. In this paper, the goals

number eight states, “Promote sustained, inclusive and sustainable economic growth,

37

full and productive employment and decent work for all.” To achieve this, UNDP has

made several indicators 8.10 which states “strengthen the capacity of domestic

financial institution to encourage and expand access to banking insurance and

financial services for all.”

Table 1: Emphasis by Sustainable Development Goals on Banking

SDG Targets and Indicators 2015 2030

4.4.1.3. Internet users (percent of adult population) 46.6 95

8.10.1.a. Number of commercial bank balance per 100000 adults 18 36

8.10.1.b. Automated teller machines per 100000 adult population

(number)

11 33

8.10.2. Proportion of adults (15 years and older) with an account

at a bank or other financial institution or with a mobile-

money-service provider

34 99

9.c.1 Proportion of population covered by a mobile network,

by technology

94.5 100

Source: NPC (2016)

According to SDG no. 4.4, by 2030, there will be increase in the number of youth and

adults who have relevant skills, including technical and vocational skills, for

employment, decent jobs and entrepreneurship.

Table 2: Indicators for Sustainable Development Goals

SDG Target and Indicators 2015 2030

17.7.1 Total amount of approved funding for developing

countries to promote the development, transfer,

dissemination and diffusion of environmentally sound

technologies

N/A N/A

Source: NPC (2016)

Likewise, goal number 17 shows “strengthen the means of implementation and

revitalize the global partnership for sustainable development”. For this goal the 17.7

targets states that” promote the development, transfer, dissemination and diffusion of

environmentally sound technologies to developing countries on favorable terms,

including on concessional and preferential terms, as mutually agreed.”

SDGs Estimated Costing - Nepal

SDG 13 goals focus on take urgent action to combat climate change and its impacts.

The major interventions and annual average investment requirement for climate

38

change adaption and mitigation achieving. The followings are major intervention

investment required in green banking (Rs. in billions)

Table 3: SDGs Investment Required

Units: (NRs. In billion)

Interventions 2016-19 2026-30 Average over 2016-30

Reducing emission through

mitigation

1.2 0.8 09

Climate- proofing technology

for infrastructure (revised)

8.6 24.5 15.7

Source: NPC (2016)

Table 4: Average investment requirement for SDG implementation

SDG Areas 2016-19 2026-30 Average over 2016-30

Energy 69 502.7 260.4

Climate change 20 31.2 24.8

Governance 50 65 58

Source: NPC (2016)

Table 5: Public sector SDG investment requirement, financing sources and financing

gap

SDG Areas Total investment

requirement

Public investment

requirement

Financing gap in

public sectors

Energy 3,906 1,887.5 789.5

Climate change 372.0 330.8 62.7

Governance 870.4 730.5 66.9

Source: NPC (2016)

Banking Policy

Indian Institute of Banking and Finance ([IIBF], 2018) has directed that customer

service has great impact on banking industry. Banks should have the board accepted

policy for general management of the branches which may include providing

adequate and proper infrastructure facilities, proper furniture, and adequate space and

so on. Also, bank should keep reviewing and improving upon existing security system

in branches so as to maintain confidence amongst employees and the public and staffs

should be provided with the trainings with customer orientation.

39

Berger (2003) has stated that banks are important in mobilizing and allocating savings

in an economy and can solve important moral hazard and adverse selection problems

by monitoring and screening borrowers and depositors. Besides, banks are important

in directing funds where they are most needed in an efficient manner and have direct

implications on capital allocation, industrial expansion, and economic growth.

Ameme and Wireko (2016) stated in their research that in today‟s competitive world

where technology plays a very important role and if we talk about banking sector or

industry there is a positive relationship between technology and customer satisfaction.

They also stated that satisfaction of customers is not merely introducing innovative

products and services rather it is much more than that. They also found that if the

bank wants to become the market leader in the competitive environment it must use

the innovation approach in all the aspects like products and services. Also there is a

significant relationship between technological innovation and cost. As the innovation

increase the cost is also increase.

The study reviewed various policies related to the green banking. Recently, many acts

and provisions have been developed for promotion of green banking and decreasing

those activities which is harmful for environment. These several acts and provisions

shows government‟s effort on protection of environment, ethical banking activities.

The sustainable development goals (SDGs) were also reviewed to know any targets

related to green banking. However, there are certain gaps in these acts and provisions.

Even though, these acts has been formulated but it has not redefined and properly

implemented. Similarly, the green banking act and provisions is still missing in

context of Nepal. Hence, for the proper practice of green banking initiatives, the

government should formulate the acts and provision related to green banking

activities so it helps to promote green banking practices and helps in adoption of

green banking in all banking sector.

2.6. Research Gap

From the review of literature, it is observed that very few things have been done in

Nepalese context related to green banking and its practices. Till now, the major

discussion theme covers in adopting the green banking in commercial bank of Nepal.

Green banking has a positive influence on bank‟s environmental performance in

Nepal (Risal & Joshi, 2018). The literature review have also been insightful sources

40

for exploring the green banking practices in various banking sectors. Similarly,

various acts and provisions related with protection of environment and green banking

has been encompassed and discussed in the reviews that has been carried out. The

studies reviewed concerned with the determining factors responsible for adoption of

green banking and bankers‟ perspective on green banking practices in their banks.

Several studies have been conducted in the area of green banking around the world.

However, in Nepalese context very few research has been conducted. Since, the issue

of adaptation in Nepal, even in the world, is a new one and very less explored. In

Nepalese context, issues like adopting green banking and bankers‟ perception on

green banking have not been studied yet. Therefore, this dissertation offers an

improved understanding on importance of adopting green banking in the banks of

Nepal.

2.7. Chapter Conclusion

The literature review carried out on different studies shows various factors that effects

on perspectives of bankers‟ and adoption of green banking. From thematic review, we

are able to know the basic concept and definition of green banking. It is that kind of

banking by which the country gets environmental benefits (Lalon, 2015). It refers as

an encouraging environmental-friendly practices which decreases the carbon

footprints and reduces paper consumption from banking operations (Islam & Das,

2013). The literature shows that green banking is an emerging issue in all over world.

The concept of green bankinghas been emerged considering environmental issues.

From theoretical review, three theories were reviewed and out of them Equators

Principles is most important theory for green banking as this theory deals with

potential impacts on natural environment.

The conceptual review helped to identify the relevant dependent and independent

variables for the study. The dependent variables like adoption of green banking,

bank‟s environmental performance and understanding on green banking are important

for green banking study. Similarly, the independent variables are in-house green

decoration, paperless statements, electronic transactions, solar energy consumption,

internet banking, and mobile banking, green lending policy, environmental trainings,

energy efficient equipment, green loan, green project, green policy, pressure from

stakeholder, potential for the profitability, concern for the environment, risk

41

minimization and image improvement are necessary for these type of study. Similarly,

various empirical articles has been reviewed to identify the research conducted on

green banking and its practices. It is observed that recently many research has been

conducted on green banking. Uddin and Ahmmed (2018) stated that green banking is

an essential part of Islamic banking which focus on protecting the environmental

issues. Similarly, Risal and Joshi (2018) revealed that there is positive impact of

practicing green banking on bank‟s environmental performance in Nepal. Despite the

increasing concern for protecting environment around the globe, there seems to be a

research gap in this area in context of Nepal. Very few study has been done in this

area. Therefore, the green banking related studies need to be discovered.

42

CHAPTER III: RESEARCH METHODOLOGY

Methodology is the organized and theoretical analysis of the methods that applied in

the study (Igwenagu, 2016). The methodology of this research work has unified the

research design, nature of data, collection procedures, models, tools of analysis of

data and method of data analysis. The research methodology consists the type of data

collection, way and method used to analyze and obtained the data for the study. This

chapter deal with research design, conceptual framework, theoretical model,

analytical model, defining the variables used for the study and data analysis methods.

3.1.Research Design

This research is based on explanatory research design. This study is important

because it is conducted in order to identify the extent and nature of cause and effect

relationships. This is the most appropriate research design for those research that are

addressing a subject about which there are high levels of uncertainty and ignorance

about the subject, and when the problem is not very well understood. Explanatory

research design focused on explaining the aspects of your study in a detailed manner

(Yajurvedi, 2015).It is usually characterized by a high degree of flexibility and lacks a

formal structure.This research falls on explanatory research design because the

research is based on survey and trying to find out the relationship between dependent

and independent variables.

3.2. Conceptual Framework

The general understanding on green banking is it helps in decreasing the excessive

use of paper, power and energy. Green banking refers to pollution free banking that

uses those operating instruments or products which won‟t harm the environmental

elements (Mehedi, 2017). In order to adopt green banking concept in banks, it

requires basic understanding of proper environment management, its strategies and

policies (Mehedi, 2017).

The concept of green banking involves promoting the social responsibility. According

to Coalition for Green Capital (2016), green banks are public institutions that fund

energy renewal project, energy efficiency, and clean energy project, partners with

private lenders. Green banks are capitalized through the public fund, thus being used

to lend, lease, credit and financial service to minimize the gap between private capital

markets as an energy renewal project. Similarly, Schub (2015) stated that green banks

43

only invest on those projects that is economical with proven technologies, loaners or

project owners are being able to save money from reducing the carbon emission and

energy savings. The nexuses between green banking with its attributes is developed in

the conceptual framework depicted in figure 7:

Figure 7: Conceptual Framework

Source: Modified from Mehedi & Kuddus (2017)

The above framework explains about the various variables that affect the general

understanding of the bankers. After reviewing various articles and thesis related to

green banking, the researcher has made the above conceptual framework for the study

Understanding on Green Banking

Banker‟s awareness on GB

Bank‟s clear concept on GB

Readiness for GB

Green Development Policy of bank

Regulations from NRB for GB

Determinants

Operational wealth

of bank, green

policy by bank,

related parties

instructions, cost

effectiveness of

green banking.

Benefits

Reduce resource waste,

attract customers, protect

environment, accelerate

service delivery, and reduce

stationary cost.

Data security and

privacy, lack of

education, traditional

approach.

Complexities

Socio-

demographic

Age, Gender,

Education level,

Experience.

Awareness

Trainings

Perception

Promotes social

responsibility, reduces

resource wastage.

44

on the basis of researcher‟s assumptions and calculations. The above conceptual

framework includes the socio-demographic factors like age, gender, work experience

and education level of the respondents that effect on their knowledge on green

banking. Similarly, the study also deals with the awareness and perception of bankers

which further incorporate with sub variables like know about GB, training, GB

practice on bank, existing technology, clear concept on GB, readiness to adopt GB

and Promotes social responsibility, advocate cleanliness, reduces resource wastage,

supported by government law, and upholds ethics in business.

This study also concerned with the determining factor of green banking, they are:

organizational pressure & environmental policy, operational wealth of bank, green

policy by bank, related parties instructions. Likewise, the above framework also

includes the major benefit of green banking practices which are reduce resource

waste, attract customers, covers CSR, protect environment, accelerate service

delivery, reduce stationary cost, and raise profit. However, during the review of

various literature and articles, the researcher found some of the complexities that can

create hurdles in adopting and practicing green banking policies, they are: data

security and privacy, lack of education, technical issues, traditional approach, lack of

infrastructure.

As this study is also related with the concept of reducing harmful resources and make

the banking operations paperless so this framework has been designed to analyze the

different dimension related to the activities involved in adopting and practicing green

banking in the commercial banks.

3.3.Basic Model

Since, green banking options help sustainable livelihood and mitigate the problem of

climate change and environmental degradation, it should be promoted and

popularized through ventilating the proper information to the bankers and customers

on time by various measures. However, the decision on how they perceive and adopt

green banking practices depends upon the general framework of green banking

initiatives. It is assumed that a rational people uses adaptation methods only when the

net benefit from using such a method is significantly greater than in the case without

it (Mendelsohn, 2012).

The basic model can be written as:

45

𝑦𝑖∗ = 𝑥𝑖

′𝛽 + 𝑢𝑖 ………………………… 1

In equation 1 as 𝑦∗is dependent variable i.e. bankers‟ awareness on green banking

and 𝑥𝑖′ is the socio economic characteristics, awareness characteristics, other

explanatory independent variables etc. The general form of an order model (with m-

alternatives) is shown by following equation:

𝑦𝑖 = 𝑗 𝑖𝑓 ∝𝑗−1< 𝑦𝑖∗ ≤∝𝑗 ………………… 2

Where, ∝0= −∞ and ∝𝑚= ∞ then,

Pr 𝑦𝑖 = 𝑗 = Pr[∝𝑗−1< 𝑦𝑖∗ ≤∝𝑗 ]

= Pr ∝𝑗−1< 𝑥𝑖′𝛽 + 𝑢𝑖 ≤∝𝑗

= Pr ∝𝑗−1< 𝑥𝑖′𝛽 < 𝑢𝑖 ≤∝𝑗− 𝑥𝑖

′𝛽

= F( ∝𝑗 − 𝑥𝑖′𝛽) − 𝐹 𝛼𝑗−1 − 𝑥𝑖

′𝛽 ,

Where, 𝐹 is the cumulative distribution function of 𝑢𝑖 . The regression parameter 𝛽

and the 𝑚 − 1 threshold parameters ∝1,… ,∝𝑚−1 are obtained by maximizing the

log-likelihood and can be shown as:

ℒ = 𝑙𝑛𝐿𝑁 = 𝑦𝑖𝑗 𝑙𝑛𝑝𝑖𝑗

𝑁

𝑖=1

𝑦𝑖𝑗 𝑙𝑛𝑝𝑖𝑗

𝑚

𝑗

…………………… . (3)

It is important to realize that there are two models that are classified as ordered

multinomial models; these are ordered logit model and probit model. For ordered logit

model 𝑢 is logistic distribution with 𝐹 𝑍 = 𝑒𝑧(1 + 𝑒𝑧) . For the probit model 𝑢 is

standard normal distribution and 𝐹 ∙ is the standard normal cumulative distribution

function. The sign of 𝛽 is interpreted as as determining whether or the latent variable

𝑦∗ increases with the regressor. This study will use probit model by following

Mudombi &Muchie (2013) and Budathoki (2017).

To measure the binary outcomes on dependent variables, several questionnaire choice

model, such as linear probability, logit and probit models can be estimated (Devkota,

2017). Among these model, logit and probit are the most common models used in the

literature, as such model have desirable statistical properties with probability value

ranging and bound with in 0 and 1 (Gbetibono& Ringler, 2009).

46

Green Banking (Y) = f (socio-demographic factors, awareness, perception,

determinants, benefits, complexities)

Suppose, Y is dichotomous variables (understanding bankers‟ perception), then it can

be written as: Y = {1 if bankers understand about green banking & 0 otherwise}.

The final probit regression equation that is need to ascertain variables influencing

bankers; understanding on green banking practices in bank is:

𝑌 = 𝛽0 + 𝛽1𝑋1 + 𝛽2𝑋2 + ⋯+ 𝛽𝑛𝑋𝑛 ………………………………… . (4)

Where,

𝛽 0 = Constant Coefficient

𝑋1 - 𝑋𝑛 = Independent Variables

𝛽 1- 𝛽n =Coefficient of X

3.4.Hypothesis & Variables Used

This section deals with the variables used and hypothesis set for the study. The

variables used for the study have been identified and defined. The hypotheses are set

based on five latent constructs which are used for the study. These latent constructs

are green banking awareness, bank‟s clear concept on green banking, readiness for

green banking, green development policies in bank and regulations from Nepal Rastra

Bank (NRB) for green banking. After reviewing various articles of scholars, similar

kind of variables are used in this study related to green banking.

The following are the hypothesis used for the study:

H01: There is no significant relationship between green banking awareness and given

explanatory variables.

H02: There is no significant association between bank‟s clear concept on green

banking and given explanatory variables.

H03: There is no significant association between readiness for green banking and

given explanatory variables.

H04: There is no significant relationship between green development policies in bank

and given explanatory variables.

H05: There is no significant association between regulation from Nepal Rastra Bank

(NRB) for green banking and given explanatory variables.

47

Table 6: Description of Variables

Variables Description Value Value Expected

Sign

Socio- Demographic

age Respondent‟s age In years +

gen Respondent‟s gender 1=if yes, 0= otherwise ±

edu Respondent‟s level of education In number +

work_exp Work experience In years +

Awareness

bank_give_any_trainin

g

Received any training 1=if yes, 0= otherwise +

Perception

promotes_sr Bankers‟ think green banking

promotes social responsibility

1=if yes, 0= otherwise ±

reduces_res_wastage Bankers‟ feel GB reduces

resources wastage

1=if yes, 0= otherwise ±

Determinants

operational_wealth_ba

nk

Bankers‟ think GB practices

depends on the available

operational wealth of bank

1=if yes, 0= otherwise ±

green_policy_bank Green policy by bank is

important

1=if yes, 0= otherwise ±

relates_parties_inst Related parties instruction 1=if yes, 0= otherwise ±

cost_effe_gb Bankers‟ think green banking is

cost effective

1=if yes, 0= otherwise ±

Complexities

data_sec_privacy Bankers‟ feel data security and

privacy is a challenge to

implement GB

1=if yes, 0= otherwise ±

lack_edu Bankers think lack of education

can provide problem in adopting

GB

1=if yes, 0= otherwise ±

traditional_app Bankers‟ think they are more

comfortable with traditional

approach

1=if yes, 0= otherwise ±

Benefits

red_resource_waste Bankers‟ think GB helps to

reduces resource wastage

1=if yes, 0= otherwise ±

att_cus Bankers‟ feel GB practices can

attract customers

1=if yes, 0= otherwise ±

protect_envn Bankers‟ think GB helps to

protect environment

1=if yes, 0= otherwise ±

acc_service_delivery Bankers‟ think GB helps in accelerate service delivery

1=if yes, 0= otherwise ±

48

reduce_stat_cost Bankers‟ think GB can reduce

stationary cost of the bank

1=if yes, 0= otherwise ±

Source: Researcher‟s Calculation/ Assumptions

3.5. Defining Variable

In the table 6, different variables are classified into socio-demographic, banker‟s

perception on green banking, benefit, complexitiesand factors affecting adoption of

green banking. Socio-demographic variables includes age, gender, education

andworking experience. Similarly, bankers‟ perception includes promoting social

responsibility and reduces resource wastage. Likewise, factor determining the

adoption of green banking involves operational wealth of the bank, green policy of

bank and cost effectiveness. Also, the benefits of green banking includes reducing

resource waste, attract customers, protect environment, accelerate service delivery and

reduce stationary cost. Each variable are given the expected sign on the basis of

researcher‟s assumption that either the effect of the variable will be high, moderate or

both. Similarly, the suitable values for each variable are defined in table 6 as different

variables holds different value. However, the variables given below may not be the

only variable used in the study and many other variable are used as per the need of the

study. Moreover, the detail description of the variables are given below:

Age: According to Ganesan (2016), age group affect the understanding of the concept

of green banking. Younger employees (between 18-30 years) tends to be interested

more in new and latest innovative ideas and techniques whereas the senior staffs

seems to be comfortable with the existing method used by the bank. Thus, this

variable has been includes in the study to analyze the effect of age on the banker‟s

perspectives on concept of green banking and its practices.

Gender: As mentioned by Narteh & Kuada (2014), gender does not matter in how the

employees understands about the importance of green banking. Both male and female

may show concern and both may not. This variable has been selected to know the

respondents can be male and female and the study can be neutral as there were not

gender biasness.

Education: Narteh & Kuada (2014) argues that there is strong relationship between

how the employees in the bank perceive about new initiatives and techniques with

their educational level. Higher the level of education people will be better conscious

and aware about the advantages of green banking in the banking activities to make the

49

environment healthy. Therefore, educational level helps to understand better in

adopting the green banking in banking activities so this variable has been chosen for

the study.

Working experience: Jamal & Naser (2002) argues experienced employees will have

a better knowledge on the benefit of green banking for both banks and environment.

They will have knowledge on other areas also due to their work exposure which

impacts their overall understanding about green banking and its emerging importance

in the globe. Thus, the study include this variable assuming that this can have certain

effect on the perception of banker‟s on green banking.

Trainings provided by bank:Arshad et al. (2011)argued that the trainings have a

positive effect on adoption of green banking practices. If the bankers are provided

green banking trainings they give more attention to green banking services and

perceive it in positive way. The efficient trainings and exposure helps topractice green

products and services.

Green banking promotes social responsibility:According to Masukujjaman et al.

(2017), green banking promotes social responsibility supported by Islamic values.

Majority of the respondents of their study perceive that green banking helps to uphold

the social responsibility. Hence, it is taken as one of the variable for this study.

Green banking reduces resource wastage:Masukujjaman et al. (2017) stated that

green banking helps to reduce resource wastage of the banks. According to their study

findings, most of the respondents of their study agreed that adoption of green banking

initiatives is beneficial in reduction of resource wastage. Therefore, the variable can

be taken at consideration for the study.

Operational wealth of bank: The practices of green banking depends upon the

available operational wealth of bank. If there is less operational budget in the bank

they tend to minimize the use paper and other stationary items (Sharma, 2013). The

operational wealth of bank has huge impact on adoption of green banking practices in

banks so, it can be use as one of the influencing variable for the study.

Green policy by bank:Arshad et al. (2011) examined that the green banking policies

helps to promote the use of green deposits, green mortgages and loans, green credit

cards, green reward checking accounts.Therefore, this variable can be useful for this

50

study because the green banking policy can have significant role on adoption of green

banking.

Related parties’ instruction:Singh (2015) argued thatthe adoption of green banking

practices can be influence by related parties‟ instruction. As green banking is focused

on environmental-friendly banking hence, the environment protection organization,

government, organization associates may have impact on green banking practices in

banks. So, this variable may be appropriate for the study.

Cost effectiveness of green banking: Green banking avoids paper work to the

optimum level and follows electronic media for various transactions, banks

functioning and customer management such as providing e-statements to the

customers, opening of the accounts through online, making all the internal circulars

within the banks online, etc. Hence, paperless banking helps reduces the transaction

cost and provide cost effectiveness to the banks (Sharifi & Hossein, 2015). Hence,

cost effectiveness can be used as a variable for the study.

Data security privacy: Masukujjaman et al. (2017)argue that data security privacy is

one of the green banking initiatives adoption complexities in any banks. Employees

and customers are conscious about using green product like mobile banking, online

banking, green deposits, green loan etc. due to lack of data security privacy. Thus,

data security privacy can be considered as an influencing variable for the study.

Lack of education:Ahmed (2012) argued that positive green banking performance or

initiatives is also depend upon proper education provided to them. So, lack of

education can create difficulties in adopting green banking practices. Theawareness of

environmental impediments and social responsibilities is important to comply with the

environmental regulations and to undertake resource efficient and environmental

activities. Therefore, this variable can be used in the study.

Traditional approach:Ullah (2013) argued that most of the bankers are

convenientwith traditional approach of banking activities. It can be one of problems to

implement green banking initiatives in banks thus, this variable is important to

analyze so it is taken as one of the variable for the study.

Green banking attract customers: Masukujjaman et al. (2017) stated that the

products of green banking helps to attract customers towards banks. The prior benefit

of green banking practices is it can increase customers by providing attractive

51

products and services. Thus, this variable has a positive effect on perception of

bankers‟ on green banking.

Green banking protect environment: Sharma et al. (2014) stated that green banking

focus on protecting the environment by using green products and services.Protecting

environment has significant positive effect on green banking practices thus, it can be

the variable for the study.

Green banking accelerate service delivery: Online banking raises the banking

service productivity by enhancing paperless banking in a great extent and is one of the

major benefits of green initiatives. Green banking helps to accelerate service delivery

thus, it is taken as one of the variable for the study.

Green banking reduce stationary cost: Green banking initiatives focuses on

reduction of paper use in daily operations of banks hence it helps to reduce the

stationary cost of the bank. It can be considered as one of the variable of the study.

3.6.Method of Data Collection

This section includes sources, nature of data, population and sample chosen for the

study, various instruments are used for conducting the research and the measure used

for analyzing the collected data were discussed.

Study Areaand Population

The study area chosen for the study is Kathmandu valley. The Kathmandu valley

comprised of three districts namely Kathmandu, Lalitpur and Bhaktapur which is

located in province 3 of Nepal. Kathmandu is the largest city in Nepal with the

population of around 1 million people. Kathmandu valley lies between the latitudes

27ο32‟13” and 27

ο49‟10” north and longitudes 85

ο11‟38” and 85

ο31‟38” east. It is

located at a mean elevation of about 1300 meters (4265 feet) above sea level in the

bowl-shaped. Kathmandu valley covers an area of 395 km2.

Kathmandu valley is the center for different major industries such as carpets,

garments, finance, tourism, health, educational services as well as banking services.

Due to the lack of infrastructural development and services in other part of Nepal,

Kathmandu valley is becoming a hub for many business and service activities. In the

present context, the banking industry is growing in Nepal. Banking sector is being

popular for saving purpose among the people of Kathmandu valley. The study

52

selected Kathmandu valley because many business activities occurs in this city area.

Also, all 28 commercial banks have their headquarters in Kathmandu valley.

Figure 8: Study Area

The population for this study are the employees from various selected commercial

banks of Kathmandu. The target populations for the study were the people who works

in the commercial banks in Kathmandu valley. A non-probability sampling was used

for the survey. Under the non-probability sampling, purposive sampling was

comprised to select the employees which involves handpicking subjects based on

specific characteristics. The sampling units for the study was the bank‟s staffs. The

326 sample were a relative modest sample size collected from the banks staff using

non-probability sampling.

Sources and Nature of Data

In order to get reliable and valid data, both primary and secondary data were used.

The primary data were collected through Key Informant Interview (KII)and

questionnaire method using ground survey of the study area with selected commercial

banks in Kathmandu valley. Secondary data has been used for strengthening research

and its findings. The secondary data were gathered from articles, journals, annual

53

reports of banks, publications of National Planning Commission (NPC), and report

from Sustainable Development Goals (SDGs), books, newspapers, banking

associatesdocuments, electronic media as well as published and unpublished

documents of various research institutions.

Sample Size Determination

The following formula was used to work out the sample size.

n= z2pq/l

2 (Panta, 2016)

Where,

n0= sample size required for study,

Standard tabulated value for 5% level of significance (z)= 1.96

p= Prevalence or proportion of an event 50 % = 0.50 (More et al., 2012)

So, p= 0.50

q= 1-p, = 0.50

Allowable error that can be tolerated (e) = 6 %

Total population for the study n0= z2pq/l

2

= (1.96)2×0.50×0.50/ (0.06)

2

= 266.78

Non-response error 5%, i.e. 266.78*5/100

= 13.34

Thus, sample size taken for study was (266.78+13.34) = 280.12 ~280

The intended sample size of the study was 280 at 6% error. The collected sample for

the study is 326 respondents which is sufficient to generalize the population.

Research Instruments

Key Informant Interview (KII) has been conducted for understanding weather the

current research has covered issue related to the field. It is conducted before starting

research methodology. KII has conducted by interviewing with three experts related

with concerned field. Methodology has been developed based on the suggestion of

experts. A questionnaire has been prepared and implemented for the data collection.

Self-administrative questionnaire has been used for collecting the data. The data has

been collected from the employeesof commercial banks of Kathmandu Valley.

54

3.7.Data Analysis

The surveyed data initially inputted into Excel, and then the spread-sheet data set was

exported to STATA software. The preliminary data cleaning was done in STATA. For

the analysis of data, both descriptive and inferential method were used. Frequency

counts and other descriptive statistics were employed to detect any errors that may

have appeared during data entry and tabulation. The copies of the original Excel and

STATA data file were kept untouched. Further activities were done on STATA

working directory. All re-coding, adding, and calculation variables were conducted

using STATA.For this study, descriptive, awareness index and inferential statistics

were used. For the analysis of the study, probit model was selected in order to identify

the significant variables that determine the bankers‟ perception on green banking in

study area. The analysis that has been carried out for the study are as follows:

Descriptive Analysis

Descriptive analysis provide the summaries for meeting the research objective and

shows the general picture of the data (Mudombi et al., 2014).This section deals with

the descriptive statistics of the study. The descriptive statistics are performed using

the STATA 2014. For making the descriptive analysis, the section are divided into

four parts i.e. socio-demographic characteristics of respondents, banker‟s

understanding on green banking, bankers‟ perception on factors determining green

banking and management strategy for greening bank.The analysis conducted will be

presented through table, chart and figures.

Calculation of Bankers’ Awareness Index

Several studies have attempt to made bankers awareness index. Such index helps to

measure awareness level of bankers regarding the initiatives of green banking and

their understanding on practice of green banking polices. Nagenthirarajah &

Thiruchelvam (2008) assess bankers‟ knowledge about green banking initiatives by

separating bankers into three groups i.e. low, moderate and high level of knowledge

based on knowledge scale.

Based on the studies, we develop individual banker‟s awareness index measured by

dummy-based index as Mudombi et al. (2014). This dummy based index includes 1

for each argued answer of an individual and 0 for others. The bankers‟ awareness

index can be calculated by using the formula:

55

𝑌(𝐴𝑤𝑎𝑟𝑒𝑛𝑒𝑠𝑠) =

𝑌 = 1, 𝐼𝑓 𝑆𝑐𝑎𝑙𝑒 𝑆𝑐𝑜𝑟𝑒 < 50%𝑌 = 2, 𝐼𝑓 50% < 𝑆𝑐𝑎𝑙𝑒 𝑆𝑐𝑜𝑟𝑒 < 75%𝑌 = 3, 𝐼𝑓 𝑆𝑐𝑎𝑙𝑒 𝑆𝑐𝑜𝑟𝑒 > 75% 𝑎𝑏𝑜𝑣𝑒

As we get the three different values from the three different groups, we applied probit

model as discussed earlier. Hence, the dependent variable is the green banking

awareness variable (1= low aware; 2= medium aware; 3= high aware) whereas the

independent variables comprised socio-demographic and other explanatory variables.

Since, this study seeks to analyze the perception of bankers on green banking with a

particular focus on the important of information, current practices and knowledge.

Inferential Statistics

Inferential statistics use a random sample of data taken from a population to describe

and make inferences about the population. Inferential statistics are valuable when

examination of each member of an entire population is not convenient or possible.

This section includes summary statistics, correlation among variables, probit

regression result, post estimation result and final regression result of the study. Under

post estimation result, there are multicollinearity and heteroscedasticity test to check

the similarities in data set.

3.8.Summary of Analytical Methods used for the study

This section deals with the concise summary of research questions that has been

raised after reviewing and analyzing various articles related to this study. On the basis

of these four research questions, four research objectives has been formulated and at

the end of this study, the result of those objectives need be obtained. The analytical

method used for the study depend on the objective accordingly. The awareness index

is used in first sub-objective in order to identify banker‟s general understanding on

green banking and their awareness level were measure in three level i.e. highly aware,

moderate and less aware. The second sub-objective applied descriptive analysis and

awareness index to identify bankers‟ perspectives on green banking practices in their

banks. Similarly, probit model and descriptive analysis were used to measure factors

affecting bankers‟ perspectives on green banking. Likewise, the last sub-objective

used descriptive analysis and subjective analysis to provide recommendations about

necessary management strategy for greening bank.

56

Table 7: Summary of Analytical Methods used for the study

Research Questions Research Objectives Analytical Method

Sub- objective 1 How can we identify

the general

understanding of

bankers on green

banking practices?

To identify banker‟s

general understanding

on green banking

practices.

Awareness Index

Sub- objective 2 How can we identify

perspectives of

bankers on green

banking practices?

To identify banker‟s

perspectives on green

banking practices in

their banks?

Descriptive

Analysis

Sub- objective 3 What are the factors

affecting bankers‟

perspectives on

green banking

practices?

To measure factor

affecting bankers‟

perspectives on green

banking practices.

Probit Model

Sub- objective 4 What strategy can be

recommended for

necessary

management for

greening the bank?

To recommend the

necessary

management strategy

for greening the bank.

Subjective Analysis

3.9.Chapter Conclusion

This chapter present various issues related to the methodology and the research

methods that were used in the study. These include research design, conceptual

framework, the basic model,and data collection methods and data analysis. This

chapter explained about the overall strategy of the research design and justifies the

choice of specific research methods in order to fulfill the research objectives. The

major approach used in the study is quantitative research method. Both theoretical

foundations and practical issues have been considered to produce a thorough research

57

practice. The research for the study is based on explanatory research design. The data

for the study is based on both primary and secondary sources of data.The sample

taken for the study is 326 respondents from commercial banks of Kathmandu Valley.

The hypothesis has been set for the study to identify the relationship between

dependent and independent variables. The conceptual framework of the study

includes socio-demographic factors of respondents, awareness level, their perception,

determining factors, benefits of green banking and complexities regarding green

banking practices. The chapter also discussed the key variables in the study and how

the data collection instruments were designed and used. Furthermore, data analyses

approach were discussed, Microsoft Excel is used for entering and tabulating the data

and STATA software is used for analyzing the data for the study. Various analytical

methods like descriptive analysis, awareness level and inferential analysis has been

used to analyze the data of the study and to find out the result of the study.

58

CHAPTER IV: DATA PRESENTATION AND ANALYSIS

This chapter presents the preliminary analysis of the study. This chapter describes the

data used for the study. It is composed of descriptive result of key variables, which

are presented in two main section. The first section deals with the socio demographic

characteristics of the survey respondents. The perception of bankers are presented in

the following order: age, sex, education, working experience, general awareness, and

training received by bankers. The presentation of the results is done concurrently with

the discussion.

4.1. Descriptive Analysis

Descriptive analysis are used to describe the basic features of the data in the study.

They provide simple summaries about the sample and the measures. It helps to

investigate the general awareness level of bankers on green banking and how they are

practicing the concept of green banking in their respective banks. Likewise,

descriptive data analysis is presented with respect to the banks level of green banking

practices that influences on the bankers‟ general perspective. Furthermore, the

analysis is also supported by inferential statistics which investigate the various

statistical techniques, indicators and models.

4.1.1. Bankers’ Socio Demographic Characteristics

This section presents the personal characteristics of the bankers in Kathmandu valley.

Various socio-demographic factors such as sex, age, education level and working

experience were analyzed. About 326 respondents were interviewed in each of three

districts i.e. Kathmandu, Lalitpur and Bhaktapur. This section involves basic

demographic factors of bankers which were presented in tables and figures with the

discussion.

Age

Figure 9 shows that, two third of the respondents are above the age 21. 22% of the

respondents are in between the age 31-40 and 4.9% are in between the age of 41-50.

Similarly, only 2% of the respondents are above 51. Hence, there is no respondents

from age below 20.

59

Figure 9: Age of the Respondents

Source: Survey data

Sex

The sex composition of the respondents was 51% female and 49% male as presented

in Figure 10. This shows that the female respondents are greater than male

respondents in the baker on the basis of gender.

Figure 10: Division of Respondent by Sex

Source: Survey data

Education and Experience

Considering the educational background, all the respondents are educated. Figure 11

shows that 14 respondents have the education level up to higher secondary and 119

0

228

73

16 9

0

50

100

150

200

250

Below 20 21-30 31-40 41-50 Above 50

Male49%

Female51% Male

Female

60

respondents have bachelor degree. The study indicates that the majority of the

respondents have Masters degree. The result of the level of education is represented

in the figure below:

Figure 11: Level of Education

Source: Survey data

Experience

Regarding work experience of the respondents, Table 8 indicates that majority of the

respondents have less than 10 years‟ of work experience. Similarly, male respondents

have greater work experienced than female respondents. And only one female

respondent have a work experience above 31 years.

Table 8: Work Experience of Respondents

Gender

Work Experience

Total

Below 10

years 11-20 years 21-30 years

Above 31

years

Male 113 23 17 7 160

Female 130 24 11 1 166

Total 243 47 28 8 326

Source: Survey data

14

119

192

1

0 50 100 150 200 250

Plus 2

Bachelor

Masters

Above masters

61

Training Received by Bankers

According to figure below, only 10% of the bankers have received the green banking

trainings and 90% bankers haven‟t received any trainings related to green banking.

Only few banks has been providing the trainings to its staffs and many of them have

received the training outside their official zone.

Figure 12: Training Received by Bankers

Source: Survey data

Source of Training

Figure 13 shows how those 10% bankers have received the green banking training.

64.52% of bankers have received from the office that means 64.52% have receive the

trainigs that have been conducted by the banks. 12.90% of the bankers have received

the training from outside, from the 2 or 3 days workshops and 22.58% have received

the trainings from both office and ouside.

Figure 13: Source of Training

Source: Survey data

No90%

Yes10%

No

Yes

Office Outside Both

Series1 20 4 7

0

5

10

15

20

25

62

4.1.2.Understanding Level of Bankers regarding Green Banking

This section of the study deals with understanding of bankers regarding green banking

practices. This part of the study portrayed the level of awareness, general

understanding and trainings received by them on green banking practices.

Bankers’ Understanding on Green Banking

Figure 14 has shown the understandings of green banking by the bankers of different

financial instutions. According to the analysis most of the bankers have understood

the concepts of green banking i.e. 57.06%. 17.18% of bankers have stated that may be

known about the green banking concept and remaining bankers 25.77% of bankers

don‟t know about the green banking. They are unaware about this concept even their

bank has the green banking services like mobile banking, e-banking, etc.

Figure 14: Bankers' Understanding on Green Banking

Source: Survey data

Bankers’ View on Green Banking on the basis of Gender

Figure 15 represent the general view of banker on green banking based on their

gender. Ethical banking, social responsibility banking, sustainable banking,

environmental banking, sharing based banking etc. are given in the option to know the

perspective of respondents on green banking concept. According to the below figure,

majority (34.05%) of female respondents think green banking is environmental

banking and 28.53% male respondents perceive green banking as an environmental

0

20

40

60

80

100

120

140

160

180

200

Yes No May be No Idea

63

banking. 15.95% and 15.64% male and female respondents think, it is social

responsibility banking. 14.72% male respondents take green banking as ethical

banking whereas only 10.74% think green banking is ethical banking. In regards to

sustainable banking, both male and female have almost equal thought. 3 male and 1

female respondents have chosen others in which they perceive green banking as a

paperless banking and internet banking.

Figure 15: Bankers‟ View on Green Banking on the basis of gender

Source: Survey data

Bank’s Awareness Level on Green Banking

Table 9 illustrates the awareness level of banks on green banking. There are altogether

28 commercial banks taken for the study in order to know their perspective on green

banking concept and its practices. The result shows that the highest number of

respondents are from Rastriya Banijya Bank (RBB) i.e. 29 and out of them only 11

respondents are aware about green banking practices in their bank. Similiarly, Sanima

and Prabhu Bank has the equal number of respondents and both bank‟s respondents

are equally aware about green banking practices. Out of total 28 commercial banks,

the highest number of respondents are from Rastriya Banijya Bank (RBB), Prabhu

Bank, Sanima Bank and NIC Asia Bank i.e. 29, 21, 21 and 29 respectively. Similarly,

the lowest respondents are four respondents from Kumari Bank and out of four

respondents three are aware about green banking practices and one is not aware. The

result also revealed that the respondents of Everest Bank are not aware about green

48

52

45

93

18

3

35

51

42

111

17

1

0 20 40 60 80 100 120

Ethical banking

Social responsibility banking

Sustainable banking

Environmental banking

Sharing based banking

Others

Female Male

64

banking as there is 0% awareness level. Likewise, there are two banks in which the

awareness level is 100% i.e. Bank of Kathmandu Lumbini Ltd. (BOK) and Citizen

Bank. The respondents are both banks are seven and six respondents and all of them

are highly awarness about green banking practices. Likewise, the awareness level of

all 28 commercial banks are present in table 9.

Table 9: Bank‟s Awareness Level on Green Banking

S.N. Bank Name

Bankers’ Awareness

Yes No May be No idea Total Percent (%)

1 NBL 10 0 5 0 15 66.67

2 RBB 11 10 4 4 29 37.93

3 NABIL 7 3 2 2 14 50

4 NIBL 3 3 0 0 6 50

5 SCBNL 7 3 3 2 15 46.67

6 HBL 5 0 0 1 6 83.33

7 NSBI 5 3 4 0 12 41.66

8 NBB 11 3 0 0 14 78.57

9 EBL 0 3 2 1 6 0

10 BOK 7 0 0 0 7 100

11 NCC 7 4 1 0 12 58.33

12 NIC 15 6 4 2 27 55.56

13 MBL 6 0 2 0 8 75

14 Kumari 3 0 0 1 4 75

15 Laxmi 7 0 2 0 9 77.77

16 SBL 4 2 1 0 7 57.14

17 ADBL 4 4 2 0 10 40

18 Global 8 1 2 1 12 66.67

19 Citizens 6 0 0 0 6 100

20 Prime 7 5 3 0 15 46.67

21 Sunrise 6 0 1 1 8 75

22 NMB 5 0 1 0 6 83.33

23 PRABHU 11 4 5 1 21 52.38

24 Janata 2 1 1 1 5 40

25 Mega 2 2 1 1 6 33.33

26 Civil 12 1 5 0 18 66.67

27 Century 4 1 2 0 7 57.14

28 Sanima 11 7 3 0 21 52.38

Total 186 66 56 18 326

Source: Survey data

Where, NBL= Nepal Bank Limited, RBB= Rastriya Banjiya Bank Ltd., NABIL = Nabil Bank

Ltd., NIBL = Nepal Investment Bank Ltd., SCBNL = Standard Chartered Bank Nepal Ltd., HBL

= Himalayan Bank Ltd., NSBI = Nepal SBI Bank Ltd., NBB = Nepal Bangladesh Bank Ltd., EBL

= Everest Bank Ltd., BOK = Bank of Kathmandu Lumbini Ltd., NCC = Nepal Credit and

65

Commerce Bank Lrd., NIC = NIC ASIA Bank Ltd., MBL = Machhapuchhre Bank Ltd., Kumari =

Kumari Bank Ltd., Laxmi = Laxmi Bank Ltd., SBL = Siddhartha Bank Ltd., ADBL = Agriculture

Development Bank Ltd., Global = Global IME Bank Ltd., Citizens = Citizens Bank International

Ltd., Prime = Prime Commercial Bank Ltd., Sunrise = Sunrise Bank Ltd., NMB = NMB Bank

Ltd., PRABHU = Prabhu Bank Ltd., Janata = Janata Bank Nepal Ltd., Mega = Mega Bank Nepal

Ltd., Civil = Civil Bank Ltd., Century = Century Commercial Bank Ltd., Sanima = Sanima Bank

Ltd.

Green Banking Components adopted by Banks

According to Table 10, among the 13 green banking services, the mobile banking is

the most common services that is used by all the banks i.e. 218. Then after the top

second used service is online banking i.e. 204. Third preferred/ used services is save

paper (i.e. 156), fourth is ethical banking (i.e. 130), 5th is power supply equipment

(i.e. 89), 6th is remote deposit (i.e. 88), 7

th is use solar energy (i.e. 85), 8

th, 9

th, 10

th,

11th, 12

th, and 13

th are green saving accounts (43), green loan (39), green mortgage

(35), green checking account (30), green credit card (29) and green money market

accounts (26).

Table 10: Components of Green Banking adopted by Banks

Components of Green Banking Adopted by your

bank

Five most popular

practice

Ethical Banking 130 53

Green Mortgage 35 17

Green Loan 39 20

Green Credit Card 29 23

Green Saving Account 43 26

Green Checking Accounts 30 12

Green Money Market Accounts 26 20

Mobile Banking 218 109

Online Banking 204 91

Remote Deposit 88 21

Power Supply Equipment 89 25

Save Paper 156 63

Use Solar Energy 85 23

Others………………….. 14 1

Source: Survey data

Five Most Popular Green Banking Services in Banks

The below diagram shows the top five green banking services that has been in

practices in most of the banks. Among these five mobile banking and online banking

66

services is used by all financial institutions. The most prefered and used service is

mobile banking i.e. 32% and then online banking i.e. 27%. And other services are

used less comparing to this both services. Save paper, ethical banking and green

saving account services are used by 18%, 15% and 8% of banks.

Figure 16: Five Most Popular Green Banking Services

Source: Survey data

Awareness Level regarding Green Banking Practices

Table 11 describe the awareness level of respondents on practices of green banking in

their banks. Out of 326 respondents, 203 respondents are aware about the significant

benefit of green banking among customers. According to them, the practice of green

banking helps to save the time of customers and provide them an easy

transaction.Regarding the cost effectiveness of green banking, 207 i.e. 63.50%

respondents think green banking is cost effective and reduces the operating cost of the

bank and out of 207, 140 respondents are aware about its benefit for the bank. The

below table shows that most of the respondents are not aware about the regulations

from any government agencies for green banking. Similarly, 193 i.e. 59.20%

respondents think green banking initiation helps in contributing sustainable

development and 69.02% (225) respondents think green banking initiatives are

32%

27%

18%

15%

8%

Mobile Banking

Online Banking

Save Paper

Ethical Banking

Green Saving Account

67

necessary for environmental conservation and sustainable growth in future. Out of

them, 134 respondents are aware about its benefits. Likewise, 57.98% (189)

respondents feel that there is importance of green banking in the verge of climate

change and out of them 77 and 133 respondents are highly aware and aware about the

importance of green banking in the verge of climate change.

Table 11: Awareness Level regarding Green Banking Practices

Particulars

Awareness Awareness Level

Yes No May

be

No

Idea

1 2 3 4 5

Do you think there is significant

benefit of green banking among

consumer?

203 18 59 15 44 145 58 5 10

Do you think there is cost

effectiveness of green banking?

207 14 63 13 47 140 80 3 0

Is there are any regulations from any

government agencies for Green

Banking?

38 79 81 103 24 44 34 6 5

Do you think such green banking

initiation contribute towards

sustainable development?

193 21 70 17 45 133 53 4 1

Do you think green banking

initiatives are necessary for

environmental conservation and

sustainable growth in future?

225 20 42 8 74 134 44 2 2

Do you think there is importance of

green banking on the verge of

climate change?

189 33 55 25 77 103 44 6 2

Source: Survey data

Awareness Level on Issues of Green Banking

The below table represents the awareness level on the issues regarding green banking.

Out of 326 respondents, 110 i.e. 33.74% think the existing technology is not sufficient

to promote green banking in their banks. 70 respondents feel the existing technology

in their bank is sufficient for promoting green banking. The result of below table

indicates that most of the bank are confused in the concept of green banking and 76

out of 326 respondents think their banks have clear concept about green banking.

Similarly, regarding readiness for green banking 126 i.e. 38.65% respondents are

ready for green banking but 120 (36.81%) respondents are still confuse in accepting

68

green banking in their bank due to lack of training and knowledge about importance

of green banking.

Furthermore, the results also shows there are some technical and administrative issues

in implementing green banking in bank. 84 out of 326 respondents agreed that there

are technical issues in implementing green banking in their banks and 75 respondents

think there is administrative problem in initiating green banking in their bank.

According to the result shown in Table 12, majority (32.82%) of respondents are not

aware about the any green development policy in their banks. Likewise, it is seen that

most of the respondents (32.51%) are also not aware about the NRB regulations

regarding green banking.

Table 12: Awareness Level on Issues of Green Banking

S.N. Particulars Awareness Level

Yes No May be No idea

1. Do you think, the existing technology are sufficient

to promote green banking?

75 110 70 71

2. Does your bank have clear concept about green

banking?

76 60 117 35

3. Do you think you are ready for green banking? 126 32 120 46

4. Are there any technical problems to initiate green banking?

84 58 99 44

5. Are there any administrative problems to initiate green banking?

75 73 101 46

6. Is there any green banking development policies in your bank?

48 107 67 55

7. Is there any regulations from Nepal Rastra Bank (NRB) for green banking?

53 67 74 106

Source: Survey data

4.1.3.Factors Determining Green Banking

This section provides an insights into various factors that determine the perception of

bankers on green banking and their perceived benefits of green banking in

commercial banks of Kathmandu Valley.

Bankers’ Perception on Factors Determining Green Banking

Figure 17 shows how much organizational pressure, environmental policy,

operational wealth of the bank, green policy by bank and related parties instruction

has affected in bankers perception regarding green banking. Majority of respondents

i.e. 173 has stated that envionment policy can impact the perception of bankers, 146

69

respondents state that green policy by bank can impact the bankers thinking, 127

respondents choosed operational wealth of the bank that can affect the bankers

perceptions. Similary, 116 and 46 respondents stated that organiazational pressure and

related arties intruction can affect the bankers perception regarding the green banking.

Figure 17: Bankers‟ Perception on Factors Determining Green Banking

.

Source: Survey data

Bankers’ Perspective on Benefits of Green Banking

The result of Figure 18 state the benefits of green banking; they are reduce resource

waste, attracts customers, covers CSR, protect environment, accelerate service

delivery, reduce stationary cost and raises profit. According to the analysis, 228

respondents have stated that this concept can reduce waste, 143 respondents state that

it can attracts customers, 134 respodents stated that is can covers CSR, 222 stated that

it protects environment, 114 state it can accelerate service delivery, 158 of

respondents state it can reduce stationery cost and 124 state it can raise profit. The

most common answer that most of the repondents think are that green banking will

reduce the waste material and protects the environment.

Figure 18: Bankers‟ Perspective on Benefits of Green Banking

116

173

127146

46

20

20406080

100120140160180200

Organizational pressure

Environmental policy

Operational wealth of the

bank

Green policy by bank

Related parties instruction

Others

70

Source: Survey data

4.1.4.Management Strategy for Greening Bank

This section deals with the descriptive analysis for objective 4 of the study concerned

with recommending necessary management strategy for green bank. This section is

includes required new technology to promote green banking, how they are ready for

green banking and why they are not ready for green banking, green development

policy adopted by bank and suggestions for improvement of scope of green banking.

Required New Technology to Promote Green Banking

This section includes bankers‟ responses towards the requirement of new technology

in their banks to promote green banking. Out of total 326 respondents, 75 respondents

think the existing technology is sufficient to promote green banking whereas 65

respondents answered may be and 46 respondents have no idea about the requirement

of new technology in their banks. Likewise, total 109 respondents think that there is

need of new technology to promote green banking. The responses of requirement of

new technology to promote green banking are presented in figure below:

Figure 19: Required New Technology to promote Green Banking

0

50

100

150

200

250

71

Source: Survey data

The result shows that 13.75% respondents needs green banking related trainings to

properly use green banking practices. Similarly, majority of respondents (17.50%)

think that there is requirement of technological advancement in their banks to initiate

and promote green banking related policies. Likewise, 11.25% respondents feels that

there should be awareness about the new launch technology related to green banking

to each employees of the bank. Furthermore, some of the respondents (7.50%) think

the banks should improve their online system for effective green banking practice.

Sim ilarly, 50% respondents choose others in which they enlisted the required new

technology for promoting green banking in their bank they are: paperless banking,

green auto loan, use of solar energy etc.

Readiness for Green Banking

This section deals with the responses of bankers‟ on their readiness to accept green

banking practicies in their bank. Out of total 326 respondents, 38.65% respondents are

ready for green banking whereas rest of 64.35% respondents are still not ready to

adopt green banking practices. The analysis of how the bankers‟ are ready for green

banking and why they are not ready for green banking are explained in following

figure:

Figure 20: How bankers' are ready for Green Banking

0

0.1

0.2

0.3

0.4

0.5Training

Technological Advancement

Awarness about New Launch

Technology

Improve Online System

Others

72

Source: Survey data

Figure 20 revealed that how the bankers‟ are ready for green banking practices. There

are main four approach in which they show how they are adopting the existing

method of green banking, they are: paperless work, use of mobile banking, use of

online banking and use of green product. Out of total 126 respondents, majority of

respondents are using paperless work and online banking. Similarly, 7% respondents

are regularly using mobile banking and green products. Likewise, remaining 60%

respondents are using other measure which promote green banking

practicesenvironmental friendly banking, recycle wastage, recycle energy and

plantation.

Figure 21: Reason for not adopting Green Banking

Source: Survey data

13%

7%

13%

7%

60%

Paperless Work

Use of Mobile Banking

Use of Online Banking

Use of Green Product

Others

42.00% 44.00% 46.00% 48.00% 50.00% 52.00% 54.00%

Lack of Awareness

Lack of Training

Lack of Awareness Lack of Training

Series1 53.85% 46.15%

73

Figure 21 shows the reasons why bankers‟ are not ready for green banking in their

banks. The result revealed that there are main two reason for not adopting green

banking i.e. lack of awareness and lack of training. Out of 78 respondents who are not

ready for green banking, 53.85% are not ready due to the lack of awarness about the

concept of green banking and they are not clear about the green banking practices.

Similarly, due to the lack of training, remaining 46.15% are not ready for green

banking in their banks. Therefore, there should be awareness program among bankers

and customers about green banking and new services launch by bank related to green

banking. Likewise, banks should provide training to their employees and customers

about green banking practices for effective implementationof green banking in banks.

The training provided to bankers‟ helps to enhance their knowlegde and concept on

green banking.

Suggestions to Improve the Scope of Green Banking in Commercial Banks

Figure 22 depicted the suggestions provided by respondents for improvement of green

banking practives in their banks. The result shows that majority of respondents think

that there is need of green banking related trainings for empoyees for effective

implementation of green banking polices and services. Similarly, it is found that the

awareness among bankers and customers regarding green banking services are equally

important to improve the scope of green banking in commercial banks. Likewise, out

of 84 respondents who give suggestions to improve the scope of green banking in

commercial banks, 22.61% think that there should be proper implementation of

polices regarding green banking in their banks. Furthermore, the recommendations

like proper education, use of latest technology, provide effective online services,

reduce paper consumption and initiation from NRB are suggested by respondents for

improvement of green banking practices in commercial banks.

74

Figure 22: Suggestions for Improvement of Green Banking Practices

4.2. Awareness Index

This section shows the awareness level of bankers on green banking. The awareness

was measured by taking various independent varibales into consideration. The figures

and table shows the awareness level of bankers based on their sex, age, education and

work experience.

Age and Awareness Level

The classification of age group has been done to analyze the awareness level of green

banking in order to know that age factor can influence their awareness level or not.

The respondents are categorized into various age group as shown in above table and

on that basis the awarness index were acquired. According to the figure 23, majority

of respondents are kess aware about green banking. Out of 326 respondents, 76.38%

were less aware, 18.40% were moderatley aware and 5.21% were highly aware about

green banking in their respective banks. Similarly, the age group in between 21-30

seems to be more aware as compared to other age group of respondents.

Figure 23: Awareness Level based on Age

0

5

10

15

20

25

Provide trainings to

employees

Proper education

Reduce paper

consumption

Provide effective

online services

Awareness

Use latest

technology

Policy

implementation

Initiation from NRB

75

Source: Survey data

Sex and Awareness Level

One the basis of gender, 42.02% female respondents are less aware about green

banking and 34.36% of male respondents are less aware of green banking as presented

in figure 24. Similarly, the above table shoes that moderately aware male respondents

are 10.74% whereas female are 7.67% respectively. The result displayed throught

awareness index shows only 3.99% male and 1.23% female respondents are highly

ware about the green banking and its practices in their banks.

Figure 24: Awareness on Green Banking based on Sex

Source: Survey data

Work Experience and Awareness Level

020406080

100120140160180

21-30 31-40 41-50 Above 51

Less aware 173 54 13 9

Moderate 47 47 2 0

Highly aware 8 8 1 0

Less aware Moderate Highly aware

0 50 100 150 200 250

Less aware

Moderate

Highly aware

Less aware Moderate Highly aware

Male 112 35 13

Female 137 25 4

76

Table 13 shows the awareness of bankers‟ on the basis of their work experience.

Work expereince of the bankers can determine their awareness level about green

banking practices in their banks. Out of 326 respondents, 243 (74.54%) bankers have

below 10 years of work expereince and out of them, only 13 (5.35%) are highly aware

about green banking and 13.12% and 76.13% are moderately aware and less aware

about green banking. From the above table, it is seen that there is no respondents

above 11 years of work expereince which are highly aware about green banking in

their banks.

Table 13: Awareness Level based on Work Experience

Green Banking Awareness

Level

Work Experience

Below 10 11-20 21-30 Above

31

Total

Less Aware 185 36 20 8 249

Moderately Aware 45 7 8 0 60

Highly Aware 13 4 0 0 17

Total 243 47 28 8 326

Source: Survey data

Education Level and Awareness

Bankers‟ educational level can also influences their awareness level about green

banking. From figure 25, it can be seen that majority of respondents who compelted

master level are highly aware about green banking which means the edcuation of an

individual can increase their awareness level as well. However, in contrast to it,

77.08% respondents also holding masters degree are less aware about green banking.

Likewise, 21.85% of respondentss holding bachelors degree are moderately aware

about the practices of green banking in their banks.

The result of awareness level indicates that out of total 326 respondents, 76.38% i.e.

249 respondents are less aware about green banking practices in their banks.

Similarly, 18.40% i.e. 60 respondents are moderately aware about green banking

practices and only 5.21% i.e. 17 respondents are highly aware about green banking

77

practices. Therefore, the result shows that the awareness level of banker‟s is very low

as more than 50% are less aware about green banking practices in their bank.

Figure 25: Awareness based on Educational Level

Source: Survey data

4.3.Inferential Analysis

In this section, inferential analysis is used to analyzed the summary statistics,

correlation among varaibles, probit regression, post estimation test and final

regression result.

Summary Statictics

This segment deals with summary statistics which helps to provide the description of

data in one table. The summary statistics includes number of observations, mean,

standard deviation, minimum and maximum number of collected data. The variable

column indicates which variables is being described. There are altogether 24 variables

including dependent and independent. All the variables except age and work

expereince has been depicted in dummy variable 0 and 1.

Table 14: Summary Statistics

Variable | Obs Mean Std. Dev. Min Max

Dependent Variables

greenbanki~e | 326 .5613497 .4969848 0 1

yourbank_c~b | 318 .2389937 .427141 0 1

020406080

100120140160180200

Plus Two Bachelor Masters Above Masters

Highly aware 0 7 10 0

Moderate 0 26 34 0

Less aware 14 86 148 1

Less aware Moderate Highly aware

78

ready_gb | 321 .3925234 .4890746 0 1

gdp_inyour~k | 277 .1732852 .3791787 0 1

reg_nrb_gb | 300 .1766667 .3820236 0 1

Socio_demographic

gen | 326 .4907975 .5006838 0 1

age | 326 29.8589 6.848584 21 58

work_exp | 326 5.915644 6.34506 .5 38

edu | 326 2.542945 .5893902 1 4

bank_give_~g | 323 .0650155 .2469357 0 1

Preception

promotes_sr | 320 .634375 .4823593 0 1

reduces_re~e | 320 .79375 .4052458 0 1

Determinants

operationa~k | 319 .5297806 .4998965 0 1

green_poli~k | 319 .4576803 .4989885 0 1

relates_pa~t | 319 .1473354 .3549968 0 1

Benefits

red_resour~e | 287 .7909408 .4073471 0 1

att_cus | 287 .4912892 .5007973 0 1

protect_envn | 287 .7735192 .4192849 0 1

acc_servic~y | 287 .3937282 .4894292 0 1

reduce_sta~t | 287 .5470383 .498652 0 1

cost_effe_gb | 297 .6969697 .4603439 0 1

Complexities

data_sec_p~y | 245 .4734694 .5003177 0 1

lack_edu | 245 .6530612 .4769705 0 1

traditiona~p | 245 .4979592 .5010194 0 1

Table 14 show that the total five dependent and ninteen independent variables are

used for the study. These above variables has been categorized into five different

sections i.e. socio-demographics variables, preception, determinants, benefits and

complexities of green banking. Under socoi-demographic variables, age has hightest

79

mean and standard deviation of 29.8589 and 6.848584 respectively along with

minimun value 28 and maximum value 58. Similarly, another section of table deals

with the bankers‟ perception on green banking. During the observation of total 320

respondents, the highest mean of green banking reduces resources wastage is 0.79375

with standard deviation 0.052458 with minimum 0 and maximum 1 respectively.

Likewise, regarding another section of table i.e. determinants of green banking, it is

seen that the operational wealth of bank has the highest mean of 0.5297806 with

standard deviation of 0.4998965 which means the total observed 319 respondents

feels that operational wealth of the bank is most influencing factor that drtermines

green banking. Under benefit section of the table, green banking reduce resource

wastage had the highest mean of 0.7909408 and standard deviation of 0.4073471 and

green banking protect environment has the second highest mean of 0.7735192 with

standard deviation of 0.4192849 which means total 287 respondents think that the

core benefit of green banking is it helps to reduce resource wastage and protect the

environment. The last section of table involves the complexities to implemnt green

banking. The total observed 245 respondents thinks that lack of education is the major

compelxities in implementing green banking in banks with the highest mean of

0.6530612 and standrad deviation of 0.4769705 respectively.

Correlation

According to Thelwall (2016), correlation is a statistical measure that indicates the

extent to which two or more variables fluctuate together. A positive correlation

indicates the extent to which those variables increase or decrease in parallel and a

negative correlation indicates the extent to which one variable increases as the other

decreases. Correlation coefficients are expressed as values between +1 and -1. A

coefficient of +1 indicates a perfect positive correlation: A change in the value of one

variable will predict a change in the same direction in the second variable. A

coefficient of -1 indicates a perfect negative correlation: A change in the value of one

variable predicts a change in the opposite direction in the second variable. Lesser

degrees of correlation are expressed as non-zero decimals. A coefficient of zero

indicates there is no discernable relationship between fluctuations of the variables.

From the correlation analysis, the result shows that there is relationship between

dependent and independent variables taken for this study.

80

Green Banking Awareness

There are various variables, which have positive and negative impact to the green

banking awareness. The result shows that education, green policy of bank, related

parties introduction, reducing wastage resources, protect government, access service

delivery, reduce stationary cost, lack of education and cost effective GB traditional

approach have positive relations, but age and work experience have negative relations

to the green banking awareness.

It shows that education has 15.38% positive relationship with green banking

awareness. It means education is the important factors for green banking. Similarly,

bank given any training has 12.93% positive relationship with green banking

awareness. This means green policy of banking also influence the awareness of green

banking. Likewise, related parties introduction has 18.94% positive relationship with

green banking awareness. Next, Protect government has 12.13% positive relationship

with green banking awareness. Reduce stationary cost has 14.65% positive

relationship with green banking awareness and cost effectiveness of green banking

has 13.92% positive relationship with green banking awareness. It presents that all of

the above factors have lower impact on green banking awareness.

Bank’s Clear Concept on Green Banking

Bank‟s clear concept on green banking is positively affected by gender, trainings

provided by bank, green policy of bank and data security policy. The result shows that

bank‟s clear concept has 14.69% influenced by gender, 26.67% by trainings provided

by bank, 12.59% by green policy of bank and 15.46% influenced by data security

policy. These factors have direct impact in bank‟s clear concept on green banking.

However, there are no factors which negatively influence bank‟s clear concept on

green banking.

Readiness for Green Banking

Readiness for green banking has been impact by trainings provided by bank,

operational wealth of bank and cost effectiveness of green banking. Trainings

provided by bank and cost effectiveness of green banking have positively influenced

81

whereasoperational wealth of bank has negatively affect the readiness for green

banking. Trainings provided by bank has 14.85% influence on readiness for green

banking and cost effectiveness of green banking has 22.74% influence on readiness

for green banking.

Green Development Policy of Bank

Green development policy of bank has influenced by gender, education, trainings

provided by bank, protect environment, lack of education and traditional approach.

The result shows that green development policy of bank has positively influenced by

gender and trainings provided by bank. However, other factors negatively influenced

the green development policy of bank. The result presents that 18.33% green

development policy of bank influenced by gender and 27.77% influenced by trainings

provided by bank.

Regulations from NRB for Green Banking

Regulations from NRB for green banking has been influenced by trainings provided

by bank, operational wealth of bank, related parties‟ instructions, green banking

protect environment, accelerateservice delivery, reduce stationary cost and lack of

education. Regulations from NRB is positively affected by trainings provided by

bank, related parties‟ instruction and cost effectiveness of green banking.

It shows that trainings provided by bank has 18.12% impact for regulations from NRB

for green banking. Similarly, related parties‟ instruction has 24.41% impact on

regulation from NRB for green banking and 16..77% influenced by cost effectiveness

of green banking for regulation from NRB.

Probit Regression Result

A probit model or probit regression is a way to perform regression for binary outcome

variables. Binary outcome variables are dependent variables with two possibilities,

like yes/no, positive test result/negative test result or single/not single. The word

“probit” is a combination of the words probability and unit; the probit model

estimates the probability a value will fall into one of the two possible binary (i.e. unit)

outcomes. In the probit model, the inverse standard normal distribution of the

probability is modeled as a linear combination of the predictors. In this study, the

probit regression is performed to know the bankers‟ perception on green banking and

82

to analyze the determinants, benefits and compelxities of green banking which affect

on their prespectives. The probit regression result table is presented below:

Table 15: Probit Regression Result

VARIABLES

(1) (2) (3) (4) (5)

greenbanking

_

aware

yourbank_

clearconcept

_gb

ready_

gb

gdp_

inyourba

nk

reg_nrb

_gb

gen 0.0763 0.325 -0.151 0.712*** -0.167

(0.190) (0.206) (0.179) (0.251) (0.227)

age -0.0457 0.0110 0.00836 0.0114 0.0233

(0.0323) (0.0345) (0.0302) (0.0449) (0.0362)

work_exp 0.00112 -0.0115 -0.0417 -0.0299 -0.0207

(0.0343) (0.0366) (0.0336) (0.0480) (0.0384)

edu 0.261 -0.0230 0.0417 0.589** -0.106

(0.168) (0.179) (0.159) (0.250) (0.199)

bank_give_any_training

0.733* 1.085*** 0.625* 0.999** -0.113

(0.431) (0.393) (0.379) (0.436) (0.441)

promotes_sr -0.227 -0.183 0.0806 0.223 0.371

(0.206) (0.222) (0.194) (0.276) (0.269)

reduces_res_wastage 0.241 -0.0298 -0.193 -0.222 0.304

(0.245) (0.266) (0.231) (0.325) (0.317)

operational_wealth_b

ank

-0.366* 0.495** -0.281 0.181 -0.649***

(0.207) (0.220) (0.188) (0.253) (0.243)

green_policy_bank -0.520** 0.818*** 0.230 0.584* -0.106

(0.227) (0.255) (0.208) (0.302) (0.260)

relates_parties_inst 0.757** -0.0728 0.136 -0.303 1.031***

(0.297) (0.297) (0.255) (0.324) (0.293)

red_resource_waste -0.448 -0.877*** -0.600** -0.270 -0.214

(0.282) (0.299) (0.258) (0.346) (0.323)

att_cus 0.412** 0.233 -0.262 0.0935 0.234

(0.210) (0.232) (0.199) (0.302) (0.262)

protect_envn 0.719*** 0.527* 0.494** -0.299 -0.583**

(0.258) (0.278) (0.243) (0.298) (0.281)

acc_service_delivery -0.445* -0.116 0.224 0.350 -0.523*

(0.236) (0.264) (0.224) (0.331) (0.306)

reduce_stat_cost 0.388* 0.0326 -0.0855 0.287 -0.693***

(0.221) (0.236) (0.205) (0.295) (0.268)

cost_effe_gb 0.210 0.0290 0.552** 0.300 0.840**

(0.227) (0.261) (0.225) (0.330) (0.341)

data_sec_privacy 0.122 0.478** 0.0691 0.205 0.291

(0.199) (0.215) (0.184) (0.257) (0.241)

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lack_edu -0.231 -0.397* -0.134 -0.695** -0.345

(0.229) (0.236) (0.200) (0.276) (0.259)

traditional_app 0.101 -0.615*** -0.291 -0.739** 0.346

(0.210) (0.238) (0.200) (0.297) (0.258)

Constant 0.788 -1.215 -0.186 -2.992** -1.238

(0.897) (0.977) (0.862) (1.252) (1.119)

Observations 235 233 233 214 233

Standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

The probit regression in Table 15 indicates the significance between dependent

variables like green banking awareness, bank‟s clear concept about green banking,

readiness for green banking, any kind of green development policy by bank and any

regulations from NRB with independent variables like socio-demographics and other given

explanatory variables. The first model of the study highlights there is eight independent

variables which is significant with green banking awareness. The significance of green

banking awareness with trainings provided by bank to their staffs, operational wealth of bank,

green policy by bank, related parties instructions, attracting customers, protect environment,

accelerate service delivery and reduce stationary cost. Likewise, the second model shows the

significance of bank‟s clear concept about green banking with eight independent variables

like trainings provided by bank, operational wealth of bank, green policy by bank, reduce

resource wastage, protect environment, data security privacy, lack of education and traditional

approach. Similarly, the third model highlights the significance of readiness for green banking

with four independent variables such as trainings provided by bank, reduce resource wastage,

protect environment and cost effectiveness. The fourth model shown in table 15 indicates

there is six independent variables that is significant with green development policy of bank.

Those variables are gender of the respondents, educational level of respondents, trainings

provided by bank, green policy by bank, lack of education and traditional approach used by

bank. Likewise, in final model there is significant relationship between regulations from NRB

and operational wealth of bank, related parties instructions, protecting environment,

accelerates service delivery, reduces stationary cost and cost effectiveness of practicing green

banking. In order to check the data set follow the ordinary least square properties, there is

need for post estimation test. Therefore, the further section deals with post estimation result

and final regression result.

Post Estimation Result

Under the post estimation results section, it includes multi-collinerarity and

heterscedasticity test which helps to test whether there is repetition in data sets or not.

Multi collinerarity

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Farrar & Glauber (1967) states that multicollinearity is a statistical phenomenon in

which two or more predictor variables in a multiple regression model are highly

correlated which creates redundant information, skewing the results in a regression

model. Thisstudy used multicollinearity test to find the similarities on variables. Table

16 illustrates the multicollinearity test of one dependent and nineteen independent

variables. The dependent variable of the study are green banking awareness of the

respondents (greenbanking_aware), bank‟s clear concept about green banking

(yourbank_clearconcept_gb), readiness for green banking(ready_gb), any kind of green

development policy by bank (gdp_inyourbank) and any regulations from Nepal Rastra Bank

(reg_nrb_gb). Table 16 shows that all independent variable tolerance is more than 0.1 and the

VIF is less than 10. Similarly, the mean VIF is 1.67 which shows the data set taken for the

analysis has no multicollinearity. Therefore, the data are ready to proceed to further analysis.

Table 16: Multicollinearity Test of Single Dependent Variable

SQRT R-

Variable VIF VIF Tolerance Squared

greenbanking_aware 1.27 1.13 0.7869 0.2131

gen 1.07 1.04 0.9322 0.0678

age 5.05 2.25 0.1980 0.8020

work_exp 5.14 2.27 0.1944 0.8056

edu 1.13 1.06 0.8821 0.1179

bank_give_any_training 1.17 1.08 0.8533 0.1467

promotes_sr 1.16 1.08 0.8647 0.1353

reduces_res_wastage 1.26 1.12 0.7933 0.2067

operational_wealth_bank 1.22 1.11 0.8176 0.1824

green_policy_bank 1.49 1.22 0.6691 0.3309

relates_parties_inst 1.24 1.12 0.8033 0.1967

red_resource_waste 1.39 1.18 0.7206 0.2794

att_cus 1.30 1.14 0.7663 0.2337

protect_envn 1.36 1.17 0.7355 0.2645

acc_service_delivery 1.61 1.27 0.6203 0.3797

reduce_stat_cost 1.43 1.19 0.7005 0.2995

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cost_effe_gb 1.23 1.11 0.8147 0.1853

data_sec_privacy 1.15 1.07 0.8698 0.1302

lack_edu 1.26 1.12 0.7968 0.2032

traditional_app 1.35 1.16 0.7393 0.2607

Mean VIF 1.67

Table 17: Overall Multicollinearity Test of Dependent Variables

Model VIF

1 1.67

2 1.67

3 1.65

4 1.66

5 1.67

Heteroscedasticity

Heteroscedasticity is a systematic change in the spread of the residuals over the range

of measure values. Heteroscedasticity is perhaps most often considered in cases of

linear regression through the origin, although that is by no means the limitation of its

usefulness (Knaub, 2007). Present heteroskedasticity in variables indicates the

problem of outliers in data set. To understand our data set, we perform

heteroscedasticity test. The result has presented in Table 15 shows the

heteroscedasticity test of different five models.

Table 18: Heteroscedasticity Test

H0: Constant Variance

Breusch-Pagan / Cook-Weisberg Test for Heteroscedasticity

Model Chi2 Prob > chi2

1 5.22 0.0223

2 24.94 0.0000

3 1.28 0.2571

4 42.71 0.0000

5 38.33 0.0000

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From the above table, it is observed that there is no heteroscedasticity problem in

model 3 whereas the result also indicates that there is heteroscedasticity problem in

model 1, 2, 4 and 5in the existing data set. Hence, we need to perform robust standard

error test to rectify the mentioned problem in data sets. Therefore, the following final

regression result is performed to correct the problems in data set.

Final Regression Result

Robust standard errors is a technique to obtain unbiased standard errors of Ordinary

Least Square (OLS) coefficients under heteroscedasticity (Croux et al., 2004). Robust

standard errors account for heteroscedasticity in a model‟s unexplained variation.

Theyare useful in social sciences where the structure of variation is unknown, but

usually shunned in physical sciences where the amount of variation is the same for

each observation. Robust standard errors are generally larger than non-robust standard

errors, but are sometimes smaller. The robust final regression result of this study is

presented in table 18.

Table 19: Final Regression Result

VARIABLES

(1) (2) (3) (4) (5)

greenban

king_

aware

yourbank_

clearconcept_

gb

ready_

gb

gdp_

inyourban

k

reg_nrb_

gb

gen 0.0763 0.325 -0.151 0.712*** -0.167

(0.185) (0.200) (0.179) (0.247) (0.234)

age -0.0457 0.0110 0.00836 0.0114 0.0233

(0.0280) (0.0301) (0.0281) (0.0382) (0.0359)

work_exp 0.00112 -0.0115 -0.0417 -0.0299 -0.0207

(0.0305) (0.0316) (0.0290) (0.0426) (0.0372)

edu 0.261* -0.0230 0.0417 0.589*** -0.106

(0.156) (0.166) (0.150) (0.210) (0.202)

bank_give_any_training 0.733* 1.085*** 0.625* 0.999** -0.113

(0.401) (0.387) (0.352) (0.441) (0.380)

promotes_sr -0.227 -0.183 0.0806 0.223 0.371

(0.193) (0.214) (0.195) (0.284) (0.246)

reduces_res_wastage 0.241 -0.0298 -0.193 -0.222 0.304

(0.229) (0.266) (0.227) (0.266) (0.268)

operational_wealth_bank -0.366* 0.495** -0.281 0.181 -0.649***

(0.213) (0.212) (0.187) (0.249) (0.252)

green_policy_bank -0.520** 0.818*** 0.230 0.584** -0.106

(0.237) (0.246) (0.205) (0.269) (0.247)

relates_parties_inst 0.757** -0.0728 0.136 -0.303 1.031***

(0.320) (0.294) (0.243) (0.340) (0.310)

red_resource_waste -0.448 -0.877*** -0.600** -0.270 -0.214

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(0.277) (0.286) (0.254) (0.323) (0.309)

att_cus 0.412** 0.233 -0.262 0.0935 0.234

(0.206) (0.207) (0.197) (0.241) (0.232)

protect_envn 0.719*** 0.527** 0.494** -0.299 -0.583**

(0.245) (0.266) (0.233) (0.295) (0.257)

acc_service_delivery -0.445* -0.116 0.224 0.350 -0.523*

(0.249) (0.225) (0.216) (0.279) (0.279)

reduce_stat_cost 0.388* 0.0326 -0.0855 0.287 -0.693***

(0.209) (0.236) (0.208) (0.261) (0.254)

cost_effe_gb 0.210 0.0290 0.552** 0.300 0.840***

(0.227) (0.234) (0.225) (0.294) (0.312)

data_sec_privacy 0.122 0.478** 0.0691 0.205 0.291

(0.197) (0.203) (0.183) (0.222) (0.228)

lack_edu -0.231 -0.397* -0.134 -0.695*** -0.345

(0.205) (0.224) (0.201) (0.239) (0.228)

traditional_app 0.101 -0.615*** -0.291 -0.739*** 0.346

(0.213) (0.235) (0.197) (0.284) (0.233)

Constant 0.788 -1.215 -0.186 -2.992*** -1.238

(0.866) (0.892) (0.827) (1.158) (1.132)

Observations 235 233 233 214 233

Robust standard errors in parentheses

*** p<0.01, ** p<0.05, * p<0.1

The first model of this study indicates that nine independent variables have a

significant relationship with green banking awareness.Six of the factors had a positive

relationship with green banking awareness. Three of these factors namely, education

level of respondents, trainings provided by bank and green banking reduces stationary

cost were highly significant at 1% level, while green banking attracts customers and

adoption of green banking policy depends on related parties instructions were

significant at 5% level and green banking protects environment were significant at

10% level. However, three factors namely green banking practices depends on

operational wealth of bank, green policy by bank and green banking acclerate service

delivery had a significant negative relationship with green banking awareness among

the respondents.

The second modelof the study observed the relationship between bank‟s clear

concept about green banking and other independent variables. It reveals that trainings

provided by bank, operational wealth of bank, green policy by bank, green banking

reduces resource wastage, green banking protects environment, data security and

privacy, lack of education and traditional approach are significantly related to bank‟s

clear concept about green banking. There are five independent variables that are

positively significant with model 2 and three variables are negatively significant. The

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variables named green banking protects environment, operational wealth of bank and

data security and privacy are significant at 5% level. Likewise, trainings provided by

bank and green policy by bank are significant with bank‟s clear concept about green

banking at 10% level. However, the dependent variables i.e. green banking reduces

resource wastage, lack of education and traditional approach are negatively significant

with bank‟s clear concept about green banking.

The third model explains about the relationship between the readiness for green

banking and other independent variables. There are four variables that are significant

with one dependent variable named readiness for green banking. The table 19

indicates that trainings provided by bank is highly significant with readiness for green

banking at 1% level. Likewise, green banking protects environment and cost

effectiveness are significant with readiness for green banking at 5% level. However,

one independent variable named green banking reduces resources waste is negatively

significant with readiness for green banking at 5% level.

The fourth model of the study illustrates the relationship betweenawareness about

green development policy in bank with other independent variables. The result

presented in table 19 shows that six independent variables namely gender of

respondents, educational level of respondents, trainings provided by bank, green

policy by bank, lack of education and traditional approach are significant with green

development policy by bank. Out of six siginificant independent variables, four of

them are positivley significant and two are negatively significant with dependent

variable i.e. green development policy in bank.Green banking policy by bank and

trainings provided by bank are significant with awareness about green developemnt

policy in bank at 5% level. Likewise, gender of respondents and educational level of

respondents are siginificant with dependent variable at 10% level which means the

gender of the respondents and their educational level are less related on their

undersatnding on green development policy in bank. Similarly, lack of education and

traditional approach are negatively significant with awareness of respondents on green

development policy in bank at 10% level.

In the fifth model, it shows the relationship between regulations by NRB for green

banking and other independent variables. There are six independent variables i.e.

operational wealth of bank, related parties instructions, green banking protects

environment, green banking acclerates service delivery, green banking reduces

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stationary cost and cost effectiveness of green banking are significant with regulations

by NRB for green banking. The result presented in table 19 shows that there are

significant realtionship in which two independent variables are positively significant

and rest four variables are negetively significant. The dependent variable is positively

significant at 10% level with related parties instructions and cost effectiveness

provided by green banking. The operational wealth of bank and green banking

reduces stationary cost are negatively significant with regulations by NRB about

green banking at 10% level. Similarly, green banking acclerates service delivery is

highly negative significant with regulations by NRB about green banking at 1% level.

4.4. Chapter Conclusion

Bankers‟ understanding level on green banking variesaccording to their age and

educational level. The first section of this chapter deals with descriptive analysis in

which socio-demographic characteristics of respondents were analyzed. The result

shows that two third of the respondents are above age 21 and there are 51 percent

female and 49 percent male respondents. Banker‟s understanding level regarding

green banking were emphasized which includes general level of understanding of

bankers‟ on green banking, components of green banking services adopted by bank,

five most popular services in banks and son on. The result indicates that mobile

banking, online banking, save paper, ethical banking and green saving account are

five most popular green banking services in banks. Likewise, bankers‟ perception on

factors determining green banking were analyzed and it is found that most of the

respondents think environmental policy is a factor that determines green banking

practices. Also, the perspective of bankers‟ on benefit of green banking were

examinedand the result shows that most of the bankers‟ think the major benefit of

green banking is it reduce resources wastage and protect environment. Lastly, another

section deals with management strategy for greening bank. The suggestions provided

by respondents to improve green banking practices are provides trainings to

employees, proper education, reduce paper consumption, provide effective online

services, awareness, use latest technology, policy implementation and initiation from

NRB.

Similarly, the bankers‟ awareness level about green banking were analyzed on the

basis of their age group, sex, education level and work experience. The second section

of this chapter represent bankers‟ awareness index that indicates most of the

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respondents (76.38%) are less aware about green banking practices in their bank. The

bankers‟ awareness index was examined where responses having less than 50 percent

knowledge are considered to be less aware, 50-75 percent are considered to be

moderately aware and 75 percent and above are considered to be highly aware about

green banking practices.

The third section of this chapter depicted inferential analysis in which the mean,

standard deviation, minimum and maximum values of the variables considered in

conceptual framework were generated. Similarly, the correlation among different

variables were analyzed to know the positive and negative correlation between

dependent and independent variables. Also, probit regression was performed to make

the explanation more effective. Likewise, the post estimation test like

multicollinearity and heteroscedasticity were performed to find out existing

similarities and repetitions in data set. Further, the data set was found to be free from

multicollinearity so further steps of analysis are taken accordingly. However, the

dataset is free from multicollinearity but the problem of heteroscedasticity was

identified in first, second, fourth and fifth models of the study. Hence, final regression

result has been performed to rectify the problem of heteroscedasticity.

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CHAPTER V: SUMMARY, CONCLUSION AND RECOMMENDATION

This chapter integrates the summary, contribution, conclusion and recommendations

on green banking practices in commercial banks. This chapter further categorized into

five sub-sections. The first section deals with summary of the study, second chapter

entails the contribution of the studyand conclusion of the study is includes in third

section. Likewise, recommendations and areas for further research are incorporated in

fourth and fifth section.

5.1. Summary of the study

This research is about bankers‟ perspective in green banking in commercial banks of

Kathmandu Valley. Green banking is comparatively new development in financial

world and the activities of the banks are linked with environmental protection and

sustainable development services (Vadeale& Katti, 2016). According to Deka (2015),

green practices of banks helps to keep environment green and to reduces greenhouse

effects through rationalizing their strategies, policies and activities pertaining to

banking service, business and in-house operational activities.

The main objectives of this study is to analyze the bankers‟ perspective on green

banking in commercial banks of Kathmandu Valley and specific objectives of this

study are to identify banker‟s general understanding on green banking practices, to

identify banker‟s perception on green banking practices in their banks, to measure

factors affecting bankers‟ perspectives on green banking practices and finally to

recommend the necessary management strategy for greening the bank.

In relation to this, various literatures has been reviewed to understand the general

prospects of green banking all around the globe. The thematic review of this study

observed that recently many countries are paying attention to green banking concept

because of climate change and environmental degradation issues. In Nepalese context,

Laxmi Bank is the first bank to initiate the green banking practices in their bank.

Similarly, the theoretical review shows that out of three theories related to green

banking, Equator Principles is most important theory for green banking study as both

are concerned with protection of environment and focuses on making environment

natural and safe. The conceptual review of the study helped to find out the relevant

dependent and independent variables for green banking study. The important

dependent variables for this kind of study are adoption of green banking, bank‟s

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environmental performance and understanding on green banking whereas the

important independent variables are in-house green decoration, paperless statements,

electronic transactions, solar energy consumption, internet banking, and mobile

banking, green lending policy, environmental trainings, energy efficient equipment,

green loan, green project, green policy, pressure from stakeholder, potential for the

profitability, concern for the environment, risk minimization and image improvement.

Hence, after reviewing various articles of different scholars, the important variables

for the study were identified. Likewise, several empirical reviews have been done

which reveals that green banking is environmental banking that is concerned with

reduction of paper use in banking operations, reduce stationary cost, launch green

product and services and promote digitization in banking sectors and recently many

research has been conducted on green banking after knowing the importance of green

banking for sustainable development. Furthermore, the polices, acts and provisions

regarding green banking has been reviewed which indicates there is target in SDGs

regarding protection of environment but there is no proper act regarding green

banking. However, the acts and provision have been development for the promotion

of green banking in banks.

To achieve the research objectives, a questionnaire has been devised which consist the

questions that could serve the objective of the study. The target sample was 326

respondents of commercial banks from Kathmandu Valley. Both primary and

secondary data has been considered for the study. Similarly, the conceptual

framework of the study comprises of socio-demographic factors of respondents,

awareness level, their perception, determining factors, benefits of green banking and

complexities regarding green banking practices. There are five dependent and

nineteen independent variables that are chosen for the study. The study also discussed

the key variables and how the data collection instruments were designed and used.

The collected data are entered and tabulated in Microsoft Excel and data were

analyzed in STATA software. Likewise, different analytical methods namely

descriptive analysis, awareness index and inferential analysis were used in order to

analyze the data of the study.

First data presentation and analysis is done in three parts; descriptive analysis,

awareness index and inferential analysis. Under descriptive statistics, the socio-

demographic characteristics section of the study presents respondent‟s age, gender,

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education level and work experience. The information given in this section shows that

the selected sample was broadly representative of the population who were banking

staffs in Kathmandu valley. The result reveals two third of the respondents are above

age 21 and there are 51 percent female and 49 percent male respondents. The result

also shows that the maximum numbers of male and female respondents have a work

experience of one to ten years and all the respondents are well educated holding above

bachelor degree. Likewise, there are only 10% bankers‟ has received the green

banking training and they received those training from office, outside office and both.

Through the sub-topic banker‟s understanding level regarding green banking, it is

found that 57.06% respondents have knowledge about green banking and 25.77%

respondents have no knowledge about green banking. The result also illustrates that

there are five most popular green banking services namely mobile banking, online

banking, save paper, ethical banking and green saving account. Majority of

respondents (203) thinks that there is significant benefit of green banking among

customers and 92 respondents think there is no significant benefits of green banking

among customers. In the sub-section of measuring the factors determining green

banking, it is found that around 53.06% of the respondents stated that environmental

policy can impact on green banking practices in banks. Similarly, regarding benefits

of green banking, almost 70% of the respondents think the major benefit of green

banking is reduce resource waste and protect environment. Likewise, in the section of

proper management strategy for green bank, majority of respondents (17.50%) think

there is need of technological advancement in their banks to initiate and promote

green banking policies. It is found that 38.65% of the respondents are ready for green

banking and 64.35% of the respondents are not ready for green banking practices.

Also, some of the managerial suggestions are provided by respondents to improve the

scope of green banking in commercial banks; they are: provide trainings to

employees, proper education, reduce paper consumption, provide effective online

services, awareness, and use of latest technology, policy implementation and initiation

from NRB.

The bankers‟ awareness level about green banking were analyzed on the basis of their

age group, sex, education level and work experience. In awareness index section, it is

found that majority of the respondents (76.38%) are less aware about green banking

practices in their bank, 18.40% of the respondents are moderately aware and only

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5.21% of the respondents are highly aware about green banking practices in their

banks.

The inferential analysis comprises of summary statistics, correlations, probit

regression, post estimation result and final regression result. It is found that age has

hightest mean and standard deviation of 29.8589 and 6.848584 respectively along

with minimun value 28 and maximum value 58. Similarly, the correlation result

indicates that education, green policy of bank, related parties introduction, reducing

wastage resources, protect government, access service delivery, reduce stationary

cost, lack of education and cost effectiveness of green banking, traditional approach

have positive relations, but age and work experience have negative relations to the

green banking awareness.

5.2.Contribution of the study

Green banking is an ethical banking deals with promoting environmental activities by

reducing carbon footprints from banking activities (Lalon, 2015). Ahmad et al. (2013)

identified that most of the commercial banks in Dhaka adopt green banking practices

to build their brand image in the market. Green banking concept is proactive and

smart way of thinking of effective of spaceship earth (Biswakarma, 2017).

The first contribution of this study is this is first study in Nepalese context which

examine the perception of bankers on green banking. As the concept of green banking

is new around the globe, very few research has been conducted in this area. Similarly,

the second contribution is this study reviewed various literature to make the study

more comprehensive. In this study, the empirical review from various time horizons

from different countries were reviewed. The models and conceptual review helped to

make the conceptual framework and basic model for the study. Also, theliterature

review helped to identify the important dependent and independent variables for this

study. With the help of various theories and model, the conceptual framework has

been generated. Likewise, studies conducted by various scholars helped to choose the

relevant model for the study. Furthermore, the researcher choose probit model for

analyzing the data of the study after reviewing various studies related to green

banking.Similarly, the awareness index were made to measure the understanding level

of bankers‟ on green banking practices in their banks.

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5.3. Conclusion

From this study, we came to know the perception of banker‟s on green banking

practices in commercial bank of Kathmandu Valley. Green banking plays caring role

for sustainable development in overcoming the institutional obstacles and market

challenges to allocating investment into various green projects (Uddin & Ahmmed,

2018). The aim of the study was to analyze the bankers‟ perspective on green banking

and specific objectives were to identify banker‟s general understanding on green

banking practices, to identify banker‟s perception on green banking practices in their

banks, to measure factors affecting bankers‟ perspectives on green banking practices

and finally to recommend the necessary management strategy for greening the bank.

Various literature were reviewed which helped to identify important model and

variables for the study. With the help of several literature review, the basic model and

conceptual framework of the study had been generated. Both primary and secondary

data has been used for the study. The analysis part was categorized into three sections

namely descriptive analysis, awareness index and inferential analysis.

Under descriptive analysis, it is found that majority of the respondents have

knowledge about green banking and the top most popular green banking practices in

banks are mobile banking, online banking, save paper, green saving account and

ethical banking. Similarly, the result revealed that only 38.65% of the respondents are

ready for green banking practices in their banks. Likewise, respondents also provide

some of the suggestions to improve the scope of green banking in commercial banks.

The recommendations provided by respondents are provides trainings to employees,

proper education, reduce paper consumption, provide effective online services,

awareness, use of latest technology, policy implementation and initiation from

NRB.The result of awareness index shows that majority of the respondents are less

aware about green banking practices in their banks. The result of inferential statistics

showed that there is positive relationship between green banking awareness and

education level of respondents, green policy by bank, related parties instructions,

reduce wastage resources, protect government, accelerate service delivery,reduce

stationary cost, and cost effectiveness of green banking and traditional approach.

Hence, the awareness level of bankers‟ on green banking can be increased if they are

provided proper education about green banking.

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5.4. Recommendations

This following recommendations are provided to concerned people and banking

sector after analyzing the results of the study.

Provide Trainings to Employees: The study shows that only 10% of bankers have

received trainings on green banking practices inside and outside their office.

Therefore, first of all, banks should initiate green banking products and services in

their banks and they should provide proper trainings to their employees for effective

implementation of green banking practices.

Reduce Paper Consumption: The main focus of green banking is to reduce paper

consumption from banking operations that also helps to decrease the stationary cost of

the banks. The result of the study reveals that 48.46% of the respondents think green

banking helps to reduce stationary cost and 38.04% of the respondents think reduction

of paper consumption helps to raise profits of bank. Hence, all banks should reduce

the maximum use of paper consumption in their daily operations.

Provide Effective Online Services:Nowadays,with the advancement in information

technology, most of the customers used online services like mobile banking, online

banking, internet banking, remote deposits etc. to pay their utility bills, deposits, and

transfers balance.The need of effective online services by banks is increasing. The

result of the study also shows that most of the commercial banks in Kathmandu

Valley are providing top five green banking services like mobile banking, online

banking, save paper, ethical banking and green saving account. Therefore, banks

should provide effective online services to customers for proper implementation and

promotion the green banking.

IncreaseAwareness: The awareness index result indicates that 76.38% i.e. 249 of the

respondents are less aware about green banking practices in their banks. The awarness

level of bankers on green banking practices is very low so the banks should increase

their awareness level by providing them proper information during meetings and

workshop about green banking practices in their banks.

Informed about NRB Regulations: The result shows that only 16.25% of the

respondents are aware about the regulations from NRB for green banking. Majority of

the respondents are unknown about any regulations from NRB for green banking.

Recently, the government agencies are paying special attention to green banking

97

concept as it prevents environment and provide cost effective practice in banking

sector. The regulations formulated by NRB should be implement by all banks and

bankers‟ should be aware about the policies and provisions made for green banking. It

helps to adopt the green banking initiatives and promote green banking practices.

5.5.Areas of Further Research

This study emphases on bankers‟ perspective ongreen banking practices in

commercial banks in Kathmandu Valley. The study also measure the awareness level

of bankers on green banking practices in their banks. However, the further research is

important in this study area as the concept of green banking is very new in Nepalese

context and only few research has been conducted in this field.

This study is limited to only Kathmandu Valley so this study does not generalize the

perspectives of bankers‟ of outside valley banks. This study does not look how

bankers‟ of development banks, finance companies and micro finance institutions

perceives green banking practices in their respective organizations. Similarly, the

conceptual framework was generated on researcher calculations and assumptions, the

variables used for the study might not have properly worked for research objectives,

hence further research can analyze various variables comprehensively and rearranged

the variables as per the requirement of the study. In this study, the cost benefit

analysis of green banking as it helps to reduce the total cost of the banks were not

included and analyzed, the further research can be conducted by considering cost

benefit of green banking. Therefore, further research can be conductedby including

various class of banks and their employees for better analysis of their perception

towards green banking.

98

REFERENCES

Afroz, N. N. (2017). Green banking initiatives of Islamic bank Bangladesh

limited. Global Journal of Management and Business Research, 17(1), 1-8.

Ahmad, F., Zayed, N. M., & Harun, M. (2013). Factors behind the adoption of green

banking by Bangladeshi commercial banks. ASA University Review, 7(2), 241-

255.

Ahmed, S. U. (2012). Green banking: advancement and opportunities. Keiei to

Keizai, 92(2), 1-12.

Arshad, M., Aslam, S., Razi, A., & Ali, S. A. (2011). A comparative analysis of

Bankers‟ perception on Islamic Banking in Pakistan. International Journal of

Economics and Research, 2(4), 1-12.

Arumugam, D., & Chirute, T. (2018). Factors determining the adoption of green

banking amongst commercial banks in Malaysia. Electronic Journal of

Business & Management, 50-62.

Berger, A.N. (2003). The economic effects of technological progress: evidence from

the banking industry. Journal of Money, Credit and Banking, 35, 141-176.

https://doi.org/10.1353/mcb.2003.0009

Bhardwaj, B. R., & Malhotra, A. (2013). Green banking strategies: sustainability

through corporate entrepreneurship. Greener Journal of Business and

Management Studies, 3(4), 180-193.

Bihari, S. C. (2010). Green banking-towards socially responsible banking in

India. International Journal of Business Insights & Transformation, 4(1), 82-

87.

Biswakarma, G. (2017). Sustainability and green banking practices: understanding the

strategic convergence in Nepalese banks- sem approach. European Journal of

Management, 17(2), 251-265.

Biswas, N. (2011). Sustainable green banking approach: the need of the

hour. Business Spectrum, 1(1`), 32-38.

Bojadziev, M., Stefanovska-Petkovska, M., Handziski, V., & Barlakoska, G. (2016).

Age related preferences of leadership style: Testing McGregor‟s theory X and

Y. Journal of Management Research, 8(4), 187-207.

Broadhurst, K., & Harrington, A. (2016). A thematic literature review: the importance

of providing spiritual care for end-of-life patients who have experienced

transcendence phenomena. American Journal of Hospice and Palliative

Medicine®, 33(9), 881-893.

Budhathoki, N. K. (2017). Climate change: perceptions, reality and agricultural

practice: evidence from Nepal. South Asian Network for Development and

Environmental Economics, 85.

99

Camp, W. G. (2001). Formulating and evaluating theoretical frameworks for career

and technical education research. Journal of Vocational Educational

Research, 26 (1), 27-39.

Cholasseri, S. (2016). Green banking –an overview. International Journal of Advance

Research and Innovative Ideas in Education, 1(4), 108-111.

Croux, C., Dhaene, G., & Hoorelbeke, D. (2004). Robust standard errors for robust

estimators. CES-Discussion paper series (DPS), 3(16), 1-20.

Deepa, P., & Karpagam, C. R. (2018). A study on customer‟s awareness on green

banking in selected public and private sector banks with reference to Tirupur.

International Journal of Advanced Research and Development, 3(1), 58-63.

Deka, G. (2015). Green Banking Practices: A Study on environmental strategies of

banks with special reference to State bank of India. Indian Journal of

Commerce and Management Studies, 6(3), 11-19.

Devkota, N., Phuyal, R. K., & Shrestha, D. L. (2018). Perception, determinants and

barriers for the adoption of climate change adaptation options among Nepalese

rice farmers. Agricultural Sciences, 9(3), 272-298.

Farrar, D. E., & Glauber, R. R. (1967). Multicollinearity in regression analysis: the

problem revisited. The Review of Economic and Statistics, 92-107.

Faruque, M. O., Biplob, M. N. K., Al-Amin, M., & Patwary, M. S. H. (2016). Green

banking and its potentiality & practice in Bangladesh. Science Journal of

Business and Management, 4(2), 28-33.

Ganesan, R., & Bhuvaneswari, A. (2016). Customer perception towards green

banking. Journal of Economics and Finance, 7(5), 5-17.

Ganesan, S. (1994). Determinants of long-term orientation in buyer-seller

relationships. Journal of marketing, 58(2), 1-19.

Gbetibouo, G. A., & Ringler, C. (2009). Mapping South African farming sector

vulnerability to climate change and variability: A subnational assessment.

International Food Policy Research Institute (IFPRI) and Center for

Environmental Economics and Policy in Africa (CEEPA), Washington DC.

Government of Nepal Investment Board, Government of Nepal Ministry of Industry.

(2017). Nepal Investment Guide. Retrieved from

https://ibn.gov.np/uploads/files/repository/IBN_Investment%20Guide%20Bo

ok_Final.pdf

Government of Nepal, National Planning Commission. (2016). Sustainable

Development Goals (SDGs)- Nepal. Retrieved from http://sdg.npc.gov.np/

Government of Nepal, National Planning Commission. (2019). Sustainable

Development Goals (SDGs)- Nepal: SDGs Investment Requirement.

Retrieved from http://sdg.npc.gov.np/

100

Grant, C., & Osanloo, A. (2016). Understanding, selecting, and integrating a

theoretical framework in dissertation research: Creating the blueprint for your

“house”. Administrative issues journal: connecting education, practice, and

research, 4(2), 12-26.

Gupta, J. (2015). Role of green banking in environment sustainability-A study of

selected commercial banks in Himachal Pradesh. International Journal of

Multidisciplinary Research and Development, 8(2), 349-353.

Hossain, M. Z., Ahmed, M., & Nisha, N. (2015). Consumer attitudes and perception

towards green banking in Bangladesh. Green Banking in Bangladesh and

Beyond, 48-76.

Igwenagu, Chinelo. (2016). Fundamentals of research methodology and data

collection. LAP Lambert Academic Publishing.

Iqbal, M., Nisha, N., & Raza, S. A. (2017). Customers' perceptions of green banking:

examining service quality dimensions in Bangladesh. In Green Business:

Concepts, Methodologies, Tools, and Applications. 1071-1090.

Islam, A., & Kamruzzaman, M. (2015). Green banking practices in Bangladesh. IOSR

Journal of Business and Management, 14(4), 37-42.

Islam, M. S., & Das, P. C. (2013). Green banking practices in Bangladesh. IOSR

Journal of Business and Management, 8(3), 39-44.

Jamal, A., & Naser, K. (2002). Customer satisfaction and retail banking: an

assessment of some of the key antecedents of customer satisfaction in retail

banking. International Journal of Bank Marketing, 20(4), 146-160.

Jayabal, G., & Soundarya, M. (2016). Green Banking: As banks initiative for

sustainable development. International Journal of Management (IJM), 7(7),

276-280.

Jha, N., & Bhome, S. (2013). A study of green banking trends in India. International

Monthly Referred Journal of Research in Management and Technology, 2,

127-132.

Knaub, J. (2007). Heteroscedasticity and homoscedasticity. In N. Salkind (Ed.),

Encyclopedia of measurement and statistics. (pp. 431-432). Thousand Oaks,

CA: SAGE Publications, Inc. doi:

http://dx.doi.org/10.4135/9781412952644.n201

Koiry, S., Saha, J. K., Farid, M. S., Sultana, M. S., & Haque, M. S. (2017). Awareness

and perception of bank customers towards green banking in Sylhet district of

Bangladesh. Asian Journal of Economics, Business and Accounting, 5(2), 1-

12.

Kumar, S. P., & Pavithra, J. (2017). Recent trends in Indian banking

sector. International Journal of Pure and Applied Mathematics, 116(18), 529-

534.

101

Lalon, R. M. (2015). Green banking: Going green. International Journal of

Economics, Finance and Management Sciences, 3(1), 34-42.

Lawrence, R. F., & Thomas, W. L. (2004). The equator principles and project finance:

sustainability in practice. Natural Resources & Environment, 19(2), 20-26.

Long, H. (2014). An empirical review of research methodologies and methods in

creativity studies (2003–2012). Creativity Research Journal, 26(4), 427-438.

Masukujjaman, M., & Aktar, S. (2013). Green banking in Bangladesh: A commitment

towards the global initiatives. Journal of Business and Technology

(Dhaka), 8(1-2), 17-40.

Masukujjaman, M., Siwar, C., Mahmud, M. R., & Alam, S. S. (2017). Bankers‟

perception of green banking: Learning from the experience of Islamic banks in

Bangladesh. Geografia-Malaysian Journal of Society and Space, 12(2).

Masukujjaman, M., Siwar, C., MAHMUD, M., & Alam, S. S. (2015). Banker's

perception on green banking-an empirical study on Islamic banks in

Bangladesh. Management & Marketing Journal, 13(2), 296-310.

Mehedi, S., & Kuddus, M. A. (2017). Green Banking: a case study on Dutch-Bangla

bank ltd. Academy of Accounting and Financial Studies Journal. 21(2), 1-20.

Mehedi, S., Kuddus, M. A., & Maniruzzaman, M. (2017). The identification of

bankers' perception toward indicators for the adoption of green banking in

Bangladeshi scheduled commercial banks. Journal of Internet Banking and

Commerce, 22(2), 2-18.

Mehta & Sharma (2016). Customers‟ persistence for green banking in Nepal. Asian

Journal of Research in Banking and Finance, 6(10), 30-44.

Mendelsohn, R. (2012). The economics of adaptation to climate change in developing

countries. Climate Change Economics, 3(02), 1-21.

Mohamed, R. K. M. H., & Nor, C. S. M. (2013). The relationship between

McGregor's XY theory management style and fulfillment of psychological

contract: A literature review. International Journal of Academic Research in

Business and Social Sciences, 3(5), 715-720.

Mudombi, S., & Muchie, M. (2013). Perceptions of water access in the context of

climate change by rural households in the Seke and Murewa districts,

Zimbabwe. Jàmbá: Journal of Disaster Risk Studies, 5(1), 1-8.

Mudombi, S., Nhamo, G., & Muchie, M. (2014). Socio-economic determinants of

climate change awareness among communal farmers in two districts of

Zimbabwe. Africa Insight, 44(2), 1-15.

Nagenthirarajah, S., & Thiruchelvam, S. (2008). Knowledge of farmers about pest

management practices in Pambaimadu, Vavuniya District: an ordered probit

model approach. Sabaramuwa University Journal, 8(1), 79-89.

102

Narteh, B., & Kuada, J. (2014). Customer satisfaction with retail banking services in

Ghana. Thunderbird International Business Review, 56(4), 353-371.

Narteh, B., & Kuada, J. (2014). Customer satisfaction with retail banking services in

Ghana. Thunderbird International Business Review, 56(4), 353-371.

Nath, V., Nayak, N., & Goel, A. (2014). Green banking practices–A

review. IMPACT: International Journal of Research in Business Management

(IMPACT: IJRBM), 2(4), 45-62.

Nui Polatoglu, V., & Ekin, S. (2001). An empirical investigation of the Turkish

consumers‟ acceptance of internet banking services. International Journal of

Bank Marketing, 19(4), 156-165.

Pant, B. (2016). Financial inclusion in Nepal: Policy review and prescriptions. NRB

Economic Review, 1-18.

Peshkin, A. (1993). The goodness of qualitative research. Educational

researcher, 22(2), 23-29.

Polasik, M., & Piotr Wisniewski, T. (2009). Empirical analysis of internet banking

adoption in Poland. International Journal of bank marketing, 27(1), 32-52.

Ragupathi, M., & Sujatha, S. (2015). Green banking initiatives of commercial banks

in India. International Research Journal of Business and Management, 8(2),

74-81.

Rajesh, T., & Dileep, A. S. (2014). Role of banks in sustainable economic

development through green banking. International Journal of Current

Research and Academic Review, ISSN, 2347-3215.

Risal, N., & Joshi, S. K. (2018). Measuring green banking practices on bank‟s

environmental performance: Empirical evidence from Kathmandu

valley. Journal of Business and Social Sciences, 2(1), 44-56.

Rousseeuw, P. J., & Leroy, A. M. (2005). Robust regression and outlier detection.

John Wiley & Sons,589, 3-6.

Sahoo, P., & Nayak, B. P. (2007). Green banking in India. The Indian Economic

Journal, 55(3), 82-98.

Sathye, M. (1999). Adoption of internet banking by Australian consumers: an

empirical investigation. International Journal of bank marketing, 17(7), 324-

334.

Schub, J. (2015). Green Banks: Growing clean energy markets by leveraging private

investment with public financing. The Journal of Structured Finance, 21(3),

26-35.

Shakil, M. H., Azam, M. K. G., & Raju, M. S. H. (2014). An evaluation of green

banking practices in Bangladesh. European Journal of Business and

Management, 6(31), 8-16.

103

Shampa, T. S., & Jobaid, M. I. Factors influencing customers‟ expectation towards

green banking practices in Bangladesh. European Journal of Business and

Management, 9(12), 140-152.

Sharifi, O., & Hossein, B. K. (2015). Green banking and environment sustainability

by commercial banks in India. International Journal of Science Technology

and Management, 4(11), 294-304.

Sharma, G. (2017). An empirical study of issues and challenges in green banking in

India. International Journal of Economics, Commerce & Business

Management, 4(2), 419-425.

Sharma, K. (2013). Green banking in India: A roadmap to success. IBMRD's Journal

of Management & Research, 2(1), 229-239.

Sharma, N., Sarika, K., & Gopal, R. (2014). A study on customer‟s awareness on

green banking initiatives in selected public and private sector banks with

special reference to Mumbai. IOSR Journal of economics and finance, 28-35.

Shaumya, K., & Arulrajah, A. (2016). Measuring green banking practices: evidence

from Sri Lanka. University of Sri Jayewardenepura, Sri Lanka, 13th

International Conference on Business Management (ICBM).

Shaumya, K., & Arulrajah, A. (2016). Measuring green banking practices: evidence

from Sri Lanka. Proceeding of Jaffna University International Research

Conference, 68-73.

Shaumya, K., & Arulrajah, A. (2017). The impact of green banking practices on

bank‟s performance: Evidence from Sri Lanka. Journal of Finance and Bank

Management, 5(1), 77-90.

Shayana, A., Raj, A.N., & Rai, S. (2017). A study on problems and prospects of green

banking with reference to coastal regions, Karnataka, India. International

Journal of Research in Finance and Marketing, 7(1), 141-151.

Singh, Y. (2015). Environmental management through green banking: A study of

commercial banks in India. International Journal of Interdisciplinary and

Multidisciplinary Studies, 2(4), 17-26.

Sohail, M. S., & Shanmugham, B. (2003). E-banking and customer preferences in

Malaysia: An empirical investigation. Information Sciences, 150(4), 207-217.

Tara, K., Singh, S., & Kumar, R. (2015). Green banking for environmental

management: a paradigm shift. Current World Environment, 10(3), 1029-

1038.

Thelwall, M. (2016). Interpreting correlations between citation counts and other

indicators. Scientometrics, 108(1), 337-347.

Trehan, R. (2015). Green banking in India. Journal of Poverty, Investment and

Development, 14, 27-32.

104

Tu, T. T. T., & Dung, N. T. P. (2016). Factors affecting green banking practices:

Exploratory factor analysis on Vietnamese banks. Journal of Economic

Development, 24(2), 4-30.

Uddin, M. N., & Ahmmed, M. (2018). Islamic banking and green banking for

sustainable development: Evidence from Bangladesh. Al-Iqtishad Journal of

Islamic Economics, 10(1), 97-114.

Ullah, M. M. (2013). Green Banking in Bangladesh-A comparative analysis. World

Review of Business Research, 3(4), 74-83.

Vadrale, K. S., & Katti, V. P. (2016). Green banking initiatives by Indian public and

private sector banks. In Green Banking for Green Industry and Green

Economy, 1-14.

Vijai, C. (2018). A study on customer‟s awareness on green banking initiatives in

selected public and private sector banks with special reference to Cuddalore

district. International Journal of Innovative Research in Science, Engineering

and Technology, 7(11), 9362-9367.

Wang, Y. S., Wang, Y. M., Lin, H. H., & Tang, T. I. (2003). Determinants of user

acceptance of internet banking: an empirical study. International Journal of

Service Industry Management, 14(5), 501-519.

Yadav, R., & Pathak, G. (2013). Environmental sustainability through green banking:

A study on private and public sector banks in India. OIDA International

Journal of Sustainable Development, 6(08), 37-48.

Yajurvedi, N. (2015). Emerging trends in banking-Increasing role of information

technology. Indian Journal of Applied Research, 5(10), 636-639.

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ANNEX I: Questionnaire

Questionnaire to the Bankers’

Dear Bankers,

This is a voluntary and confidential survey conducted by registered MBA student at Pokhara

University: Ms. Heena Tandukar. The main objective of this study is to understand the

Banker‟s opinion and understanding about green banking in Nepal. Your bank, and you, has

been purposively selected and we would be grateful if you could kindly participate in our

survey. Your participation is completely voluntary and you have the right NOT to participate

in this survey at all or stop participation at any point in time during the survey.

This survey which would take about 10 minutes to administer and it includes information on

your understanding about green banking initiatives from you and your organization. All

finding of the study will be held in confidentiality. All reports made out of this survey would

not mention any names and all analysis would be in general terms. If you orally agree to

participate in this study, then you may sign below.

………………………… ………………………… ……………………

Name of Enumerator Name of Respondent Signature

Date: Start Time: …………

Part A: Personal Information:

Name

Gender a. Male b. Female c. Others

Age ……….. years

Contact no

Address

Marital Status a. Married b. Unmarried

Level of Education a. +2 b. Bachelor c. Masters d. Above masters

Experience a. Below 3 years b. 3-6 years c. 7-9 years

d. 10-12 years e. Above 12 years

Position

Name of Bank

Grade of Bank

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Part B: Banker’s general understanding on green banking practices:

Particulars Yes No

a. Do you know about the concept of green banking?

b. Does your bank have clear concept about green banking?

c. Are you aware about green banking practice by your bank?

d. Does your bank provide green banking training to the staff?

e. Do you think you are ready for green banking?

f. Does all your consumers use green banking?

g. Do you think there is significant benefit of green banking among

customers?

h. Do you think there is cost effectiveness of green banking?

Part C: Banker’s perspectives on green banking practices in their banks:

1. In your opinion, what is green banking?

a. Ethical banking

b. Social responsibility banking

c. Sustainable banking

d. Environmental banking

e. Sharing based banking

f. Others (Specify)………

2. Have you ever received green banking training? (If No, please go to Q. 6)

a. Yes b. No

3. If yes, how many times, have you received such training? ……………. times

4. How long have you received such training? ……..day (or) ……..week (or)

………..month (or) ……..year

5. Where do you receive such training? Office Outside Both

6. Does your bank provide green banking training to the staff?

a. Yes b. No c. May be d. No idea

7. If yes, how frequently do they provide such training?

a. Very frequently b. Often c. Sometimes d. Rarely e.

Very rarely

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8. At what level, you are aware about green banking?

a. Very high b. High c. Moderate d. Low e. Very low

9. What is your opinion about the importance of green banking?

a. Very important b. Important c. Moderate d. Less important

e. Not important

10. Among the given green banking practices, please tick all the strategies adopted by

your bank?

Components of Green Banking Adopted by your Bank Five most Popular Practice

Ethical Banking

Green Mortgage

Green Loan

Green Credit Card

Green Saving Account

Green Checking Account

Green Money Market Account

Mobile Banking

Online Banking

Remote Deposit

Power Supply Equipment

Save Paper

Use of Solar Energy

Others……………......

11. Besides the components mentioned above, are there any further steps that can be

taken, by your bank to promote Green Banking? (If No, go to Q. 13)

a. Yes b. No c. May be d. No idea

12. If yes, please mention the other steps.

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

13. Do you think such strategies are helpful to promote Green Banking? (If other than

Yes, go to Q. 15)

a. Yes b. No c. May be d. No idea

14. If yes, on what respect is it helpful? (Please tick all Possible Options).

a. Reduce paper consumption b. Recycle waste properly

c. Sponsor tree plantation d. Spend in green publicity

e. Lunch green product and services f. Others …………………..

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15. Do you think, the existing technology is sufficient to promote Green Banking? (If yes,

go to Q. 18).

a. Yes b. No

16. If no, what should be done?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

17. Are you ready for green banking? (If yes go to Q 18 and if No go to Q 19)

a. Yes b. No c. May be d. No Idea

18. If yes, how?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

19. If no, why?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

20. What is your perception towards current practice of green banking?

a. Very Effective b. Effective c. Moderate d. Less Effective

e. Not Effective

21. What is your perception towards green banking?

a. Green banking promotes social responsibility

b. Green banking advocate cleanliness

c. Green banking reduces resource wastage

d. Green banking is supported by government law

e. Green banking upholds ethics in business

f. Others (Specify)……………………….

22. What do you think the factor that determines green banking? [Please tick all Possible

Options].

a. Organizational pressure and environmental policy

b. Operational wealth of the bank

c. Green policy by bank

d. Related parties instruction

e. Others …………..

23. Do all consumers use green banking services? [If yes, go to Q 26].

a. Yes b. No c. May be d. No Idea

24. If no, what percent of the consumer, do you think, use green banking? ..……….%

25. In your opinion, why consumer are not using green banking?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

109

26. What are the levels of effectiveness about green banking among consumers?

a. Very effective

b. Effective

c. Moderate

d. Less effective

e. Not effective

27. Do you think promotion of green banking is possible to implement on every branch

outside the valley as well?

a. Yes b. No c. May be d. No Idea

28. Do you think such bank facilities can be used by illiterate person as well?

a. Yes b. No c. May be d. No Idea

29. Do you think there is significant advantage of green banking to the consumer?

a. Yes b. No c. May be d. No Idea

30. If yes, at what level it is significant?

a. Extremely High b. High c. Moderate d. Low

e. Extremely Low

31. What do you think is the benefit of green banking? [Please tick all Possible Options].

a. Reduce resource waste

b. Attract customers

c. Covers CSR

d. Protect environment

e. Accelerate service delivery

f. Reduce stationary cost

g. Raises profit

h. Others (Specify) …………….

Part D: Factor affecting bankers’ perspectives on green banking practices:

1. Do you think there are any problems/challenges to implement green banking? [If

other than Yes, go to Q 34].

a. Yes b. No c. May be d. No Idea

2. If yes, what do you think is the major problems/ challenges to implement green

banking? [Please tick all Possible Options].

a. Data security and Privacy

b. Lack of education

c. Technical issues

d. Traditional approach

e. Lack of infrastructure

110

f. Others ……………..

3. Do you think there are any complexities to implement green banking?

a. Yes b. No c. May be d. No Idea

4. What are the complexities faced by employees to implement green banking?

a. High adaptation cost

b. Switch of prime borrowers

c. Privacy hamper

d. Decreasing market values

e. Others……………….

5. How do you think such problem, challenges and complexities can be reduced to

successfully implement green policy?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

6. Besides challenges and complexities, are there any technical procedure problems to

initiate green banking?

a. Yes b. No c. May be d. No Idea

7. If yes, what are the major technical problems?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

8. Similarly, are there any administrative problems to initiate green banking?

a. Yes b. No c. May be d. No Idea

9. If yes, what are the major administrative problems?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

10. Do you think such green banking initiation contribute towards sustainable

development?

a. Yes b. No c. May be d. No Idea

11. If yes, at what level it contributes?

a. Extremely High b. High c. Moderate d. Low

e. Extremely Low

12. Do you think green banking initiatives are necessary for environmental conservation

and sustainable growth in future?

a. Yes b. No c. May be d. No Idea

13. If yes, at what level it is necessary?

a. Extremely High b. High c. Moderate d. Low

e. Extremely Low

111

14. Do you think there is importance of green banking on the verge of climate change?

a. Yes b. No c. May be d. No Idea

15. If yes, at what level it is important?

a. Extremely High b. High c. Moderate d. Low

e. Extremely Low

Part E: Necessary management strategy for greening bank:

1. Is there any green development policy in your Bank?

a. Yes b. No c. May be d. No Idea

2. If yes, what are the policies?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

3. Is there any regulations from Nepal Rastra Bank (NRB) for Green Banking?

a. Yes b. No c. May be d. No Idea

4. If yes, what are the policies?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

5. Is there are any regulations from any government agencies for Green Banking?

a. Yes b. No c. May be d. No Idea

6. If yes, what are the policies?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

7. If yes, whether such regulations and policies have significant influence in

implementation of green banking?

a. Extremely High b. High c. Moderate d. Low

e. Extremely Low

8. Finally, do you have any suggestions for measure to improve the scope of green

banking of the selected commercial bank? [If other than Yes, End the Survey].

a. Yes b. No c. May be d. No Idea

9. What are the suggestions to improve the scope of green banking of the selected

commercial bank?

1.…………………………………… 2………………………………………

3……………………………………. 4………………………………………

End Time:…………………

“Thank You forYour Valuable Time and Contribution”

112

ANNEX II: Awareness Index

Particulars

Awareness Level

Less aware Moderate

Highly

aware Total

Sex

Male 112 35 13 160

Female 137 25 4 166

Total 249 60 17 326

Age Group

Below 20 0 0 0 0

21-30 173 47 8 228

31-40 54 11 8 73

41-50 13 2 1 16

Above 51 9 0 0 9

Total 249 60 17 326

Working Experience

Below 10 185 45 13 243

11-20 36 7 4 47

21-30 20 8 0 28

Above 31 8 0 0 8

Total 249 60 17 326

Education Level

Plus Two 14 0 0 14

Bachelor 86 26 7 119

Master 148 34 10 192

Above masters 1 0 0 1

Total 249 60 17 326

113

ANNEX III:Regression Results (STATA Output)

Describing Variables:

Command:describe Contains data obs: 326 vars: 24 size: 8,802 storage display value variable name type format label variable label greenbanking_~e byte %8.0g Greenbanking_aware yourbank_clea~b byte %8.0g Yourbank_clearconcept_GB ready_gb byte %8.0g Ready_Gb gdp_inyourbank byte %8.0g GDP_inyourBank reg_nrb_gb byte %8.0g Reg_NRB_GB gen byte %8.0g Gen age byte %8.0g Age work_exp float %8.0g Work_Exp edu byte %8.0g Edu bank_give_any~g byte %8.0g promotes_sr byte %8.0g promotes_SR reduces_res_w~e byte %8.0g operational_w~k byte %8.0g green_policy_~k byte %8.0g relates_parti~t byte %8.0g red_resource_~e byte %8.0g Red_resource_waste att_cus byte %8.0g Att_cus protect_envn byte %8.0g Protect_envn acc_service_d~y byte %8.0g Acc_service_delivery reduce_stat_c~t byte %8.0g Reduce_stat_cost cost_effe_gb byte %8.0g Cost_effe_GB data_sec_priv~y byte %8.0g Data_sec_privacy lack_edu byte %8.0g Lack_edu traditional_app byte %8.0g Traditional_app Sorted by: Note: Dataset has changed since last saved.

Summary Statistics

Command:sum

Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- greenbanki~e | 326 .5613497 .4969848 0 1 yourbank_c~b | 318 .2389937 .427141 0 1 ready_gb | 321 .3925234 .4890746 0 1 gdp_inyour~k | 277 .1732852 .3791787 0 1 reg_nrb_gb | 300 .1766667 .3820236 0 1 -------------+--------------------------------------------------------- gen | 326 .4907975 .5006838 0 1 age | 326 29.8589 6.848584 21 58 work_exp | 326 5.915644 6.34506 .5 38 edu | 326 2.542945 .5893902 1 4 bank_give_~g | 323 .0650155 .2469357 0 1 -------------+--------------------------------------------------------- promotes_sr | 320 .634375 .4823593 0 1 reduces_re~e | 320 .79375 .4052458 0 1 operationa~k | 319 .5297806 .4998965 0 1 green_poli~k | 319 .4576803 .4989885 0 1 relates_pa~t | 319 .1473354 .3549968 0 1 -------------+--------------------------------------------------------- red_resour~e | 287 .7909408 .4073471 0 1 att_cus | 287 .4912892 .5007973 0 1 protect_envn | 287 .7735192 .4192849 0 1 acc_servic~y | 287 .3937282 .4894292 0 1 reduce_sta~t | 287 .5470383 .498652 0 1 -------------+--------------------------------------------------------- cost_effe_gb | 297 .6969697 .4603439 0 1 data_sec_p~y | 245 .4734694 .5003177 0 1 lack_edu | 245 .6530612 .4769705 0 1 traditiona~p | 245 .4979592 .5010194 0 1

114

Correlation Result:

Command:pwcorr greenbanking_aware gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst

red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb

data_sec_privacy lack_edu traditional_app, star(0.05)sig

| greenb~e gen age work_exp edu bank_g~g promot~r -------------+--------------------------------------------------------------- greenbanki~e | 1.0000 | gen | 0.0517 1.0000 | 0.3518 | age | -0.1575* 0.1351* 1.0000 | 0.0044 0.0146 | work_exp | -0.1240* 0.1312* 0.8776* 1.0000 | 0.0252 0.0178 0.0000 | edu | 0.1538* -0.0508 -0.1212* -0.1712* 1.0000 | 0.0054 0.3607 0.0286 0.0019 | bank_give_~g | 0.1293* 0.1406* 0.0642 0.0099 -0.0094 1.0000 | 0.0201 0.0114 0.2502 0.8593 0.8658 | promotes_sr | -0.0025 0.0572 0.0326 -0.0310 0.0398 0.0964 1.0000 | 0.9651 0.3081 0.5610 0.5806 0.4780 0.0852 | reduces_re~e | 0.0331 -0.0405 -0.0401 -0.0762 -0.0407 0.0103 -0.0342 | 0.5554 0.4708 0.4745 0.1738 0.4676 0.8539 0.5424 | operationa~k | -0.0738 -0.0458 -0.0213 -0.0187 -0.0814 -0.0032 -0.0724 | 0.1886 0.4149 0.7042 0.7388 0.1469 0.9549 0.1971 | green_poli~k | -0.0117 0.0328 0.0732 0.0739 0.1260* 0.0352 0.1712* | 0.8348 0.5600 0.1922 0.1882 0.0244 0.5306 0.0021 | relates_pa~t | 0.1894* 0.0357 0.0384 0.0235 0.0826 0.0680 0.1671* | 0.0007 0.5256 0.4938 0.6761 0.1412 0.2260 0.0027 | red_resour~e | 0.0001 -0.0496 -0.0332 -0.0972 0.0171 0.0061 0.0441 | 0.9992 0.4023 0.5753 0.1003 0.7735 0.9181 0.4571 | att_cus | 0.1153 -0.0383 0.0819 0.0795 0.0272 -0.0774 0.1105 | 0.0511 0.5184 0.1664 0.1791 0.6464 0.1913 0.0616 | protect_envn | 0.1213* -0.0897 0.0363 0.0627 -0.0572 -0.0481 0.1158 | 0.0399 0.1296 0.5406 0.2901 0.3344 0.4172 0.0500 | acc_servic~y | -0.0101 -0.0670 -0.0406 -0.0185 -0.0313 -0.1365* 0.0826 | 0.8645 0.2580 0.4931 0.7545 0.5974 0.0207 0.1630 | reduce_sta~t | 0.1465* -0.1228* -0.0548 -0.0776 0.0321 -0.0534 0.0634 | 0.0130 0.0376 0.3548 0.1902 0.5876 0.3678 0.2844 | cost_effe_gb | 0.1392* 0.0226 0.0113 0.0632 0.0048 0.0526 0.0556 | 0.0164 0.6975 0.8462 0.2777 0.9338 0.3662 0.3394 | data_sec_p~y | 0.1058 0.0039 -0.0201 -0.0575 -0.0552 0.1224 0.0081 | 0.0986 0.9519 0.7538 0.3702 0.3898 0.0558 0.8995 | lack_edu | -0.0750 0.0056 0.0509 0.0154 -0.0125 -0.1093 0.0666 | 0.2424 0.9305 0.4280 0.8101 0.8457 0.0879 0.3005 | traditiona~p | 0.0055 -0.0612 0.1284* 0.0816 -0.0309 0.1080 0.1536* | 0.9317 0.3398 0.0447 0.2031 0.6300 0.0916 0.0163 | | reduce~e operat~k green_~k relate~t red_re~e att_cus protec~n -------------+---------------------------------------------------------------

115

reduces_re~e | 1.0000 | | operationa~k | 0.0848 1.0000 | 0.1309 | green_poli~k | 0.1367* -0.3448* 1.0000 | 0.0146 0.0000 | relates_pa~t | 0.1225* -0.0159 0.2217* 1.0000 | 0.0288 0.7767 0.0001 | red_resour~e | 0.2775* -0.1867* 0.2039* -0.0090 1.0000 | 0.0000 0.0015 0.0005 0.8800 | att_cus | 0.0506 -0.1080 0.2055* 0.1786* 0.0767 1.0000 | 0.3933 0.0678 0.0005 0.0024 0.1949 | protect_envn | 0.1665* 0.0435 0.1063 -0.0132 0.2131* 0.0988 1.0000 | 0.0047 0.4628 0.0721 0.8238 0.0003 0.0948 | acc_servic~y | 0.1572* 0.0043 0.2239* 0.1533* 0.2214* 0.4349* 0.2146* | 0.0076 0.9419 0.0001 0.0093 0.0002 0.0000 0.0003 | reduce_sta~t | 0.2287* -0.0388 0.1508* 0.1114 0.3068* 0.2642* 0.2936* | 0.0001 0.5124 0.0105 0.0596 0.0000 0.0000 0.0000 | cost_effe_gb | 0.0286 -0.1310* 0.1808* 0.0275 0.2248* 0.0436 0.0635 | 0.6233 0.0239 0.0018 0.6369 0.0001 0.4654 0.2879 | data_sec_p~y | 0.1557* 0.0845 -0.0614 0.1132 0.1734* 0.0706 0.0214 | 0.0149 0.1882 0.3398 0.0776 0.0072 0.2773 0.7426 | lack_edu | 0.2284* 0.0988 0.2463* 0.0562 0.1303* 0.1143 0.2295* | 0.0003 0.1238 0.0001 0.3822 0.0442 0.0777 0.0003 | traditiona~p | 0.1667* 0.0738 0.2793* 0.0434 0.2062* 0.1048 0.2988* | 0.0091 0.2506 0.0000 0.4996 0.0013 0.1061 0.0000 | | acc_se~y reduce~t cost_e~b data_s~y lack_edu tradit~p -------------+------------------------------------------------------ acc_servic~y | 1.0000 | | reduce_sta~t | 0.3608* 1.0000 | 0.0000 | cost_effe_gb | -0.0460 0.1659* 1.0000 | 0.4417 0.0052 | data_sec_p~y | 0.0883 0.1358* 0.0811 1.0000 | 0.1734 0.0359 0.2115 | lack_edu | 0.1962* 0.1584* -0.0672 -0.0817 1.0000 | 0.0023 0.0142 0.3006 0.2027 | traditiona~p | 0.2868* 0.1796* 0.0020 0.0366 0.2114* 1.0000 | 0.0000 0.0054 0.9756 0.5689 0.0009

1. Bankers’ awareness on Green Banking

Probit Regression Result:

Command:probit greenbanking_aware gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app Iteration 0: log likelihood = -151.99462 Iteration 1: log likelihood = -124.7525 Iteration 2: log likelihood = -124.42195

116

Iteration 3: log likelihood = -124.42121 Iteration 4: log likelihood = -124.42121 Probit regression Number of obs = 235 LR chi2(19) = 55.15 Prob > chi2 = 0.0000 Log likelihood = -124.42121 Pseudo R2 = 0.1814 ----------------------------------------------------------------------------------------- greenbanking_aware | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | .0763016 .1903414 0.40 0.689 -.2967607 .4493638 age | -.0457181 .0322781 -1.42 0.157 -.1089821 .0175458 work_exp | .001123 .0342896 0.03 0.974 -.0660834 .0683293 edu | .2608294 .1677662 1.55 0.120 -.0679863 .5896451 bank_give_any_training | .7329372 .4306913 1.70 0.089 -.1112022 1.577077 promotes_sr | -.2273299 .2056709 -1.11 0.269 -.6304375 .1757777 reduces_res_wastage | .2410353 .2446184 0.99 0.324 -.238408 .7204785 operational_wealth_bank | -.3656068 .2071399 -1.77 0.078 -.7715936 .0403799 green_policy_bank | -.5196561 .2274953 -2.28 0.022 -.9655387 -.0737734 relates_parties_inst | .7567438 .2973106 2.55 0.011 .1740258 1.339462 red_resource_waste | -.4476982 .2824184 -1.59 0.113 -1.001228 .1058317 att_cus | .4123234 .2100985 1.96 0.050 .000538 .8241088 protect_envn | .718753 .2576421 2.79 0.005 .2137836 1.223722 acc_service_delivery | -.4454759 .2359297 -1.89 0.059 -.9078896 .0169378 reduce_stat_cost | .3884939 .2211225 1.76 0.079 -.0448981 .821886 cost_effe_gb | .2103587 .2273782 0.93 0.355 -.2352944 .6560119 data_sec_privacy | .1222348 .1992122 0.61 0.539 -.268214 .5126836 lack_edu | -.2309515 .2289393 -1.01 0.313 -.6796642 .2177613 traditional_app | .1005264 .2096173 0.48 0.632 -.3103159 .5113687 _cons | .7881121 .896791 0.88 0.380 -.9695659 2.54579 -----------------------------------------------------------------------------------------

Multicollinearity Test:

Command:collin greenbanking_aware gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app (obs=235) Collinearity Diagnostics SQRT R- Variable VIF VIF Tolerance Squared ---------------------------------------------------- greenbanking_aware 1.27 1.13 0.7869 0.2131 gen 1.07 1.04 0.9322 0.0678 age 5.05 2.25 0.1980 0.8020 work_exp 5.14 2.27 0.1944 0.8056 edu 1.13 1.06 0.8821 0.1179 bank_give_any_training 1.17 1.08 0.8533 0.1467 promotes_sr 1.16 1.08 0.8647 0.1353 reduces_res_wastage 1.26 1.12 0.7933 0.2067 operational_wealth_bank 1.22 1.11 0.8176 0.1824 green_policy_bank 1.49 1.22 0.6691 0.3309 relates_parties_inst 1.24 1.12 0.8033 0.1967 red_resource_waste 1.39 1.18 0.7206 0.2794 att_cus 1.30 1.14 0.7663 0.2337 protect_envn 1.36 1.17 0.7355 0.2645 acc_service_delivery 1.61 1.27 0.6203 0.3797 reduce_stat_cost 1.43 1.19 0.7005 0.2995 cost_effe_gb 1.23 1.11 0.8147 0.1853 data_sec_privacy 1.15 1.07 0.8698 0.1302 lack_edu 1.26 1.12 0.7968 0.2032 traditional_app 1.35 1.16 0.7393 0.2607 -------------------------------------------------------------------- Mean VIF 1.67 Cond Eigenval Index --------------------------------- 1 13.2837 1.0000

117

2 1.1094 3.4603 3 0.8980 3.8461 4 0.7349 4.2516 5 0.6956 4.3700 6 0.5653 4.8477 7 0.5321 4.9963 8 0.4753 5.2863 9 0.4309 5.5524 10 0.3470 6.1873 11 0.3421 6.2312 12 0.3107 6.5390 13 0.2606 7.1391 14 0.2345 7.5269 15 0.2027 8.0951 16 0.1684 8.8827 17 0.1435 9.6212 18 0.1332 9.9870 19 0.1032 11.3471 20 0.0237 23.6777 21 0.0053 49.8760 --------------------------------- Condition Number 49.8760 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.0176

Heteroscedasticity Test

Command:hettest

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of greenbanking_aware chi2(1) = 3.76 Prob > chi2 = 0.0526

Final Regression Result (Probit Robust)

Command:probit greenbanking_aware gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app,r Iteration 0: log pseudolikelihood = -151.99462 Iteration 1: log pseudolikelihood = -124.7525 Iteration 2: log pseudolikelihood = -124.42195 Iteration 3: log pseudolikelihood = -124.42121 Iteration 4: log pseudolikelihood = -124.42121 Probit regression Number of obs = 235 Wald chi2(19) = 43.21 Prob > chi2 = 0.0012 Log pseudolikelihood = -124.42121 Pseudo R2 = 0.1814 ----------------------------------------------------------------------------------------- | Robust greenbanking_aware | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | .0763016 .1854378 0.41 0.681 -.2871499 .439753 age | -.0457181 .0279592 -1.64 0.102 -.1005171 .0090808 work_exp | .001123 .0304531 0.04 0.971 -.058564 .0608099 edu | .2608294 .1562259 1.67 0.095 -.0453677 .5670265 bank_give_any_training | .7329372 .4013067 1.83 0.068 -.0536095 1.519484 promotes_sr | -.2273299 .1933226 -1.18 0.240 -.6062352 .1515755 reduces_res_wastage | .2410353 .2287329 1.05 0.292 -.207273 .6893436 operational_wealth_bank | -.3656068 .2128386 -1.72 0.086 -.7827628 .0515491 green_policy_bank | -.5196561 .2366704 -2.20 0.028 -.9835216 -.0557905 relates_parties_inst | .7567438 .3202724 2.36 0.018 .1290214 1.384466 red_resource_waste | -.4476982 .2772798 -1.61 0.106 -.9911566 .0957602 att_cus | .4123234 .2057355 2.00 0.045 .0090892 .8155576 protect_envn | .718753 .2449437 2.93 0.003 .238672 1.198834 acc_service_delivery | -.4454759 .2493394 -1.79 0.074 -.934172 .0432203

118

reduce_stat_cost | .3884939 .208888 1.86 0.063 -.020919 .7979068 cost_effe_gb | .2103587 .2273011 0.93 0.355 -.2351432 .6558607 data_sec_privacy | .1222348 .1973484 0.62 0.536 -.264561 .5090306 lack_edu | -.2309515 .2045395 -1.13 0.259 -.6318416 .1699387 traditional_app | .1005264 .2133458 0.47 0.638 -.3176238 .5186765 _cons | .7881121 .8657056 0.91 0.363 -.9086397 2.484864 -----------------------------------------------------------------------------------------

2. Bank’s clear concept on Green Banking

Probit Regression Result:

Command:probit yourbank_clearconcept_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app Iteration 0: log likelihood = -130.74872 Iteration 1: log likelihood = -107.24351 Iteration 2: log likelihood = -106.77496 Iteration 3: log likelihood = -106.77362 Iteration 4: log likelihood = -106.77362 Probit regression Number of obs = 233 LR chi2(19) = 47.95 Prob > chi2 = 0.0003 Log likelihood = -106.77362 Pseudo R2 = 0.1834 ------------------------------------------------------------------------------------------ yourbank_clearconcept_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------------------+---------------------------------------------------------------- gen | .3245606 .2062451 1.57 0.116 -.0796723 .7287935 age | .0110256 .0344751 0.32 0.749 -.0565444 .0785956 work_exp | -.0114697 .0366247 -0.31 0.754 -.0832529 .0603134 edu | -.0230123 .1791103 -0.13 0.898 -.374062 .3280375 bank_give_any_training | 1.085197 .3932705 2.76 0.006 .3144006 1.855993 promotes_sr | -.1831662 .2223958 -0.82 0.410 -.619054 .2527216 reduces_res_wastage | -.0298255 .2664307 -0.11 0.911 -.5520202 .4923691 operational_wealth_bank | .4946987 .2203796 2.24 0.025 .0627625 .9266348 green_policy_bank | .8176352 .2550979 3.21 0.001 .3176525 1.317618 relates_parties_inst | -.0727864 .2968122 -0.25 0.806 -.6545275 .5089547 red_resource_waste | -.877444 .2987545 -2.94 0.003 -1.462992 -.291896 att_cus | .2331396 .2323936 1.00 0.316 -.2223434 .6886226 protect_envn | .5269783 .277655 1.90 0.058 -.0172155 1.071172 acc_service_delivery | -.1164278 .2642816 -0.44 0.660 -.6344101 .4015546 reduce_stat_cost | .0326279 .2362732 0.14 0.890 -.4304592 .4957149 cost_effe_gb | .0289842 .2605922 0.11 0.911 -.4817671 .5397356 data_sec_privacy | .4776204 .214534 2.23 0.026 .0571415 .8980994 lack_edu | -.3966398 .2357174 -1.68 0.092 -.8586375 .0653579 traditional_app | -.615332 .2381376 -2.58 0.010 -1.082073 -.1485908 _cons | -1.214792 .9766947 -1.24 0.214 -3.129078 .6994948 ------------------------------------------------------------------------------------------

Multicollinearity Test:

Command: collin yourbank_clearconcept_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app (obs=233) Collinearity Diagnostics SQRT R- Variable VIF VIF Tolerance Squared ---------------------------------------------------- yourbank_clearconcept_gb 1.24 1.11 0.8072 0.1928 gen 1.08 1.04 0.9226 0.0774 age 5.01 2.24 0.1994 0.8006 work_exp 5.18 2.27 0.1932 0.8068 edu 1.13 1.06 0.8861 0.1139 bank_give_any_training 1.21 1.10 0.8290 0.1710

119

promotes_sr 1.15 1.07 0.8675 0.1325 reduces_res_wastage 1.25 1.12 0.7986 0.2014 operational_wealth_bank 1.23 1.11 0.8108 0.1892 green_policy_bank 1.51 1.23 0.6604 0.3396 relates_parties_inst 1.21 1.10 0.8288 0.1712 red_resource_waste 1.45 1.20 0.6917 0.3083 att_cus 1.28 1.13 0.7797 0.2203 protect_envn 1.34 1.16 0.7457 0.2543 acc_service_delivery 1.58 1.26 0.6349 0.3651 reduce_stat_cost 1.42 1.19 0.7058 0.2942 cost_effe_gb 1.22 1.11 0.8169 0.1831 data_sec_privacy 1.18 1.08 0.8499 0.1501 lack_edu 1.26 1.12 0.7908 0.2092 traditional_app 1.38 1.17 0.7244 0.2756 ------------------------------------------------------------------- Mean VIF 1.67 Cond Eigenval Index --------------------------------- 1 12.9067 1.0000 2 1.2321 3.2366 3 0.9007 3.7855 4 0.7447 4.1631 5 0.7052 4.2781 6 0.6061 4.6146 7 0.5480 4.8530 8 0.5142 5.0102 9 0.4695 5.2433 10 0.3933 5.7282 11 0.3391 6.1697 12 0.3233 6.3187 13 0.2725 6.8826 14 0.2540 7.1281 15 0.2073 7.8896 16 0.1688 8.7451 17 0.1426 9.5131 18 0.1333 9.8409 19 0.1097 10.8469 20 0.0235 23.4203 21 0.0055 48.5007 --------------------------------- Condition Number 48.5007 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.0177

Heteroscedasticity Test:

Command: hettest

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of yourbank_clearconcept_gb chi2(1) = 21.44 Prob > chi2 = 0.0000

Final Regression Result (Probit Robust):

Command:probit yourbank_clearconcept_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app,r

Iteration 0: log pseudolikelihood = -130.74872 Iteration 1: log pseudolikelihood = -107.24351 Iteration 2: log pseudolikelihood = -106.77496 Iteration 3: log pseudolikelihood = -106.77362 Iteration 4: log pseudolikelihood = -106.77362 Probit regression Number of obs = 233 Wald chi2(19) = 47.93

120

Prob > chi2 = 0.0003 Log pseudolikelihood = -106.77362 Pseudo R2 = 0.1834 ------------------------------------------------------------------------------------------ | Robust yourbank_clearconcept_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------------------+---------------------------------------------------------------- gen | .3245606 .1996796 1.63 0.104 -.0668041 .7159253 age | .0110256 .0301363 0.37 0.714 -.0480404 .0700916 work_exp | -.0114697 .0315527 -0.36 0.716 -.0733119 .0503724 edu | -.0230123 .1660203 -0.14 0.890 -.3484061 .3023815 bank_give_any_training | 1.085197 .3873177 2.80 0.005 .3260678 1.844325 promotes_sr | -.1831662 .2138364 -0.86 0.392 -.6022778 .2359454 reduces_res_wastage | -.0298255 .2660215 -0.11 0.911 -.5512181 .491567 operational_wealth_bank | .4946987 .211563 2.34 0.019 .0800428 .9093546 green_policy_bank | .8176352 .2455914 3.33 0.001 .336285 1.298986 relates_parties_inst | -.0727864 .2944317 -0.25 0.805 -.6498619 .5042891 red_resource_waste | -.877444 .2857591 -3.07 0.002 -1.437522 -.3173664 att_cus | .2331396 .206732 1.13 0.259 -.1720478 .638327 protect_envn | .5269783 .2658022 1.98 0.047 .0060156 1.047941 acc_service_delivery | -.1164278 .2250372 -0.52 0.605 -.5574926 .324637 reduce_stat_cost | .0326279 .2362257 0.14 0.890 -.430366 .4956217 cost_effe_gb | .0289842 .2340408 0.12 0.901 -.4297272 .4876957 data_sec_privacy | .4776204 .2025327 2.36 0.018 .0806637 .8745772 lack_edu | -.3966398 .2238887 -1.77 0.076 -.8354535 .0421739 traditional_app | -.615332 .2351937 -2.62 0.009 -1.076303 -.1543608 _cons | -1.214792 .892285 -1.36 0.173 -2.963638 .5340548 ------------------------------------------------------------------------------------------

3. Readiness for Green Banking

Probit Regression Result:

Command:probit ready_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app Iteration 0: log likelihood = -159.69388 Iteration 1: log likelihood = -145.41904 Iteration 2: log likelihood = -145.35888 Iteration 3: log likelihood = -145.35884 Iteration 4: log likelihood = -145.35884 Probit regression Number of obs = 233 LR chi2(19) = 28.67 Prob > chi2 = 0.0714 Log likelihood = -145.35884 Pseudo R2 = 0.0898 ----------------------------------------------------------------------------------------- ready_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | -.1509044 .1785048 -0.85 0.398 -.5007674 .1989586 age | .0083637 .0301862 0.28 0.782 -.0508002 .0675275 work_exp | -.0416904 .0336351 -1.24 0.215 -.107614 .0242332 edu | .0417341 .1591846 0.26 0.793 -.270262 .3537302 bank_give_any_training | .6251841 .3794595 1.65 0.099 -.1185428 1.368911 promotes_sr | .0805812 .1938217 0.42 0.678 -.2993023 .4604647 reduces_res_wastage | -.1933416 .2311658 -0.84 0.403 -.6464181 .259735 operational_wealth_bank | -.2806259 .1879494 -1.49 0.135 -.649 .0877482 green_policy_bank | .2301426 .2084824 1.10 0.270 -.1784754 .6387606 relates_parties_inst | .136049 .2552503 0.53 0.594 -.3642323 .6363303 red_resource_waste | -.599714 .2578863 -2.33 0.020 -1.105162 -.0942661 att_cus | -.2619164 .1985573 -1.32 0.187 -.6510816 .1272488 protect_envn | .4937584 .243118 2.03 0.042 .0172559 .9702608 acc_service_delivery | .2241075 .2244513 1.00 0.318 -.215809 .664024 reduce_stat_cost | -.0854702 .2051487 -0.42 0.677 -.4875543 .3166139 cost_effe_gb | .5521291 .224806 2.46 0.014 .1115175 .9927407 data_sec_privacy | .0691272 .1835411 0.38 0.706 -.2906067 .4288612 lack_edu | -.1337703 .2002861 -0.67 0.504 -.5263238 .2587832 traditional_app | -.2905955 .199975 -1.45 0.146 -.6825392 .1013482 _cons | -.1857453 .8616167 -0.22 0.829 -1.874483 1.502992 -----------------------------------------------------------------------------------------

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Multicollinearity Test:

Command:collin ready_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app

(obs=233) Collinearity Diagnostics SQRT R- Variable VIF VIF Tolerance Squared ---------------------------------------------------- ready_gb 1.13 1.06 0.8867 0.1133 gen 1.08 1.04 0.9281 0.0719 age 4.99 2.23 0.2005 0.7995 work_exp 5.16 2.27 0.1938 0.8062 edu 1.12 1.06 0.8961 0.1039 bank_give_any_training 1.17 1.08 0.8543 0.1457 promotes_sr 1.15 1.07 0.8671 0.1329 reduces_res_wastage 1.26 1.12 0.7961 0.2039 operational_wealth_bank 1.21 1.10 0.8258 0.1742 green_policy_bank 1.46 1.21 0.6835 0.3165 relates_parties_inst 1.21 1.10 0.8284 0.1716 red_resource_waste 1.41 1.19 0.7116 0.2884 att_cus 1.31 1.14 0.7649 0.2351 protect_envn 1.33 1.15 0.7517 0.2483 acc_service_delivery 1.58 1.26 0.6330 0.3670 reduce_stat_cost 1.40 1.18 0.7128 0.2872 cost_effe_gb 1.26 1.12 0.7966 0.2034 data_sec_privacy 1.15 1.07 0.8733 0.1267 lack_edu 1.25 1.12 0.7999 0.2001 traditional_app 1.36 1.17 0.7354 0.2646 ------------------------------------------------------------------- Mean VIF 1.65 Cond Eigenval Index --------------------------------- 1 13.0608 1.0000 2 1.1243 3.4083 3 0.8949 3.8203 4 0.7026 4.3115 5 0.6974 4.3274 6 0.6599 4.4488 7 0.5341 4.9453 8 0.4973 5.1249 9 0.4488 5.3945 10 0.3761 5.8932 11 0.3435 6.1661 12 0.3335 6.2584 13 0.2738 6.9065 14 0.2522 7.1970 15 0.2135 7.8210 16 0.1699 8.7678 17 0.1469 9.4300 18 0.1328 9.9184 19 0.1089 10.9536 20 0.0235 23.5725 21 0.0054 49.0155 --------------------------------- Condition Number 49.0155 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.0200

Heteroscedasticity Test:

Command:hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance

122

Variables: fitted values of ready_gb chi2(1) = 0.17

Prob > chi2 = 0.6826

Final Regression Result (Probit Robust):

Command:probit ready_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app,r Iteration 0: log pseudolikelihood = -159.69388 Iteration 1: log pseudolikelihood = -145.41904 Iteration 2: log pseudolikelihood = -145.35888 Iteration 3: log pseudolikelihood = -145.35884 Iteration 4: log pseudolikelihood = -145.35884 Probit regression Number of obs = 233 Wald chi2(19) = 32.72 Prob > chi2 = 0.0259 Log pseudolikelihood = -145.35884 Pseudo R2 = 0.0898 ----------------------------------------------------------------------------------------- | Robust ready_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | -.1509044 .1787522 -0.84 0.399 -.5012523 .1994435 age | .0083637 .0281394 0.30 0.766 -.0467884 .0635158 work_exp | -.0416904 .0290123 -1.44 0.151 -.0985535 .0151726 edu | .0417341 .1503323 0.28 0.781 -.2529119 .3363801 bank_give_any_training | .6251841 .3516307 1.78 0.075 -.0639995 1.314368 promotes_sr | .0805812 .1946077 0.41 0.679 -.300843 .4620054 reduces_res_wastage | -.1933416 .2273469 -0.85 0.395 -.6389333 .2522502 operational_wealth_bank | -.2806259 .1872457 -1.50 0.134 -.6476208 .0863689 green_policy_bank | .2301426 .2052997 1.12 0.262 -.1722374 .6325227 relates_parties_inst | .136049 .2432318 0.56 0.576 -.3406765 .6127745 red_resource_waste | -.599714 .2536366 -2.36 0.018 -1.096832 -.1025954 att_cus | -.2619164 .1965007 -1.33 0.183 -.6470506 .1232179 protect_envn | .4937584 .2330349 2.12 0.034 .0370183 .9504984 acc_service_delivery | .2241075 .2162259 1.04 0.300 -.1996874 .6479024 reduce_stat_cost | -.0854702 .2083879 -0.41 0.682 -.4939029 .3229626 cost_effe_gb | .5521291 .2252057 2.45 0.014 .110734 .9935242 data_sec_privacy | .0691272 .1831445 0.38 0.706 -.2898294 .4280838 lack_edu | -.1337703 .200859 -0.67 0.505 -.5274467 .259906 traditional_app | -.2905955 .1970293 -1.47 0.140 -.6767658 .0955748 _cons | -.1857453 .8274584 -0.22 0.822 -1.807534 1.436043 -----------------------------------------------------------------------------------------

4. Green Development Policy of Bank

Probit Regression Result:

Command:probit gdp_inyourbank gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app Iteration 0: log likelihood = -100.08541 Iteration 1: log likelihood = -78.785081 Iteration 2: log likelihood = -77.385148 Iteration 3: log likelihood = -77.374462 Iteration 4: log likelihood = -77.374462 Probit regression Number of obs = 214 LR chi2(19) = 45.42 Prob > chi2 = 0.0006 Log likelihood = -77.374462 Pseudo R2 = 0.2269 ----------------------------------------------------------------------------------------- gdp_inyourbank | Coef. Std. Err. z P>|z| [95% Conf. Interval]

123

------------------------+---------------------------------------------------------------- gen | .7120515 .2506801 2.84 0.005 .2207276 1.203375 age | .0114466 .0448707 0.26 0.799 -.0764984 .0993916 work_exp | -.0298687 .048021 -0.62 0.534 -.1239881 .0642507 edu | .5885478 .2498322 2.36 0.018 .0988856 1.07821 bank_give_any_training | .9992499 .4355862 2.29 0.022 .1455167 1.852983 promotes_sr | .2234843 .2759464 0.81 0.418 -.3173607 .7643292 reduces_res_wastage | -.2220992 .3251252 -0.68 0.495 -.8593329 .4151344 operational_wealth_bank | .1806106 .2528225 0.71 0.475 -.3149125 .6761336 green_policy_bank | .5844936 .3016632 1.94 0.053 -.0067555 1.175743 relates_parties_inst | -.3025336 .3240612 -0.93 0.351 -.9376818 .3326147 red_resource_waste | -.2696052 .3459842 -0.78 0.436 -.9477217 .4085112 att_cus | .0934774 .3022213 0.31 0.757 -.4988656 .6858203 protect_envn | -.2985109 .2979851 -1.00 0.316 -.882551 .2855292 acc_service_delivery | .3496883 .3311475 1.06 0.291 -.2993488 .9987254 reduce_stat_cost | .286902 .2948557 0.97 0.331 -.2910046 .8648086 cost_effe_gb | .3003273 .3300656 0.91 0.363 -.3465894 .947244 data_sec_privacy | .2054647 .2573684 0.80 0.425 -.2989681 .7098976 lack_edu | -.6945046 .2755254 -2.52 0.012 -1.234524 -.1544848 traditional_app | -.7388655 .2966254 -2.49 0.013 -1.320241 -.1574903 _cons | -2.992038 1.251769 -2.39 0.017 -5.445459 -.5386169 -----------------------------------------------------------------------------------------

Multicollinearity Test:

Command: collin gdp_inyourbank gen age work_exp edu bank_give_any_training promotes_sr

reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst

red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb

data_sec_privacy lack_edu traditional_app

(obs=214) Collinearity Diagnostics SQRT R- Variable VIF VIF Tolerance Squared ---------------------------------------------------- gdp_inyourbank 1.23 1.11 0.8156 0.1844 gen 1.12 1.06 0.8927 0.1073 age 4.81 2.19 0.2079 0.7921 work_exp 5.05 2.25 0.1981 0.8019 edu 1.22 1.10 0.8191 0.1809 bank_give_any_training 1.22 1.10 0.8217 0.1783 promotes_sr 1.15 1.07 0.8676 0.1324 reduces_res_wastage 1.27 1.13 0.7859 0.2141 operational_wealth_bank 1.22 1.11 0.8177 0.1823 green_policy_bank 1.48 1.22 0.6764 0.3236 relates_parties_inst 1.23 1.11 0.8141 0.1859 red_resource_waste 1.42 1.19 0.7028 0.2972 att_cus 1.30 1.14 0.7695 0.2305 protect_envn 1.36 1.17 0.7326 0.2674 acc_service_delivery 1.57 1.25 0.6362 0.3638 reduce_stat_cost 1.43 1.19 0.7016 0.2984 cost_effe_gb 1.24 1.12 0.8042 0.1958 data_sec_privacy 1.16 1.08 0.8636 0.1364 lack_edu 1.26 1.12 0.7951 0.2049 traditional_app 1.45 1.20 0.6919 0.3081 ------------------------------------------------------------------- Mean VIF 1.66 Cond Eigenval Index --------------------------------- 1 12.8830 1.0000 2 1.2484 3.2125 3 0.8900 3.8047 4 0.7758 4.0751 5 0.6880 4.3272 6 0.6685 4.3898 7 0.5479 4.8489 8 0.4990 5.0811 9 0.4450 5.3803

124

10 0.3923 5.7303 11 0.3378 6.1754 12 0.3307 6.2419 13 0.2601 7.0378 14 0.2442 7.2628 15 0.2092 7.8469 16 0.1653 8.8280 17 0.1427 9.5027 18 0.1328 9.8481 19 0.1118 10.7325 20 0.0217 24.3667 21 0.0056 48.0638 --------------------------------- Condition Number 48.0638 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.0165

Heteroscedasticity Test:

Command:hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of gdp_inyourbank chi2(1) = 39.60 Prob > chi2 = 0.0000

Final Regression Result (Probit Robust):

Command:probit gdp_inyourbank gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app,r Iteration 0: log pseudolikelihood = -100.08541 Iteration 1: log pseudolikelihood = -78.785081 Iteration 2: log pseudolikelihood = -77.385148 Iteration 3: log pseudolikelihood = -77.374462 Iteration 4: log pseudolikelihood = -77.374462 Probit regression Number of obs = 214 Wald chi2(19) = 48.95 Prob > chi2 = 0.0002 Log pseudolikelihood = -77.374462 Pseudo R2 = 0.2269 ----------------------------------------------------------------------------------------- | Robust gdp_inyourbank | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | .7120515 .2471734 2.88 0.004 .2276005 1.196503 age | .0114466 .0381986 0.30 0.764 -.0634213 .0863145 work_exp | -.0298687 .042588 -0.70 0.483 -.1133396 .0536022 edu | .5885478 .2099892 2.80 0.005 .1769765 1.000119 bank_give_any_training | .9992499 .4408563 2.27 0.023 .1351874 1.863312 promotes_sr | .2234843 .2843241 0.79 0.432 -.3337808 .7807494 reduces_res_wastage | -.2220992 .2664776 -0.83 0.405 -.7443857 .3001872 operational_wealth_bank | .1806106 .2485729 0.73 0.467 -.3065833 .6678045 green_policy_bank | .5844936 .2691223 2.17 0.030 .0570236 1.111964 relates_parties_inst | -.3025336 .3395752 -0.89 0.373 -.9680887 .3630215 red_resource_waste | -.2696052 .3228157 -0.84 0.404 -.9023124 .363102 att_cus | .0934774 .2407041 0.39 0.698 -.378294 .5652487 protect_envn | -.2985109 .2951219 -1.01 0.312 -.8769391 .2799173 acc_service_delivery | .3496883 .2790857 1.25 0.210 -.1973096 .8966862 reduce_stat_cost | .286902 .2611934 1.10 0.272 -.2250277 .7988317 cost_effe_gb | .3003273 .2944936 1.02 0.308 -.2768695 .8775242 data_sec_privacy | .2054647 .2222411 0.92 0.355 -.2301198 .6410493 lack_edu | -.6945046 .2392313 -2.90 0.004 -1.163389 -.2256199 traditional_app | -.7388655 .2836645 -2.60 0.009 -1.294838 -.1828933 _cons | -2.992038 1.158194 -2.58 0.010 -5.262058 -.7220187 -----------------------------------------------------------------------------------------

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5. Regulations from NRB for Green Banking

Probit Regression Result:

Command:probit reg_nrb_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app Iteration 0: log likelihood = -112.89743 Iteration 1: log likelihood = -84.072958 Iteration 2: log likelihood = -82.733068 Iteration 3: log likelihood = -82.726902 Iteration 4: log likelihood = -82.726901 Probit regression Number of obs = 233 LR chi2(19) = 60.34 Prob > chi2 = 0.0000 Log likelihood = -82.726901 Pseudo R2 = 0.2672 ----------------------------------------------------------------------------------------- reg_nrb_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | -.1665163 .2268935 -0.73 0.463 -.6112194 .2781868 age | .0232845 .0362061 0.64 0.520 -.0476781 .0942472 work_exp | -.0207364 .0384478 -0.54 0.590 -.0960927 .0546198 edu | -.1058111 .1994451 -0.53 0.596 -.4967164 .2850942 bank_give_any_training | -.1131238 .4407775 -0.26 0.797 -.9770317 .7507842 promotes_sr | .3711273 .2689593 1.38 0.168 -.1560233 .8982779 reduces_res_wastage | .3040063 .3170137 0.96 0.338 -.317329 .9253417 operational_wealth_bank | -.6487069 .2426753 -2.67 0.008 -1.124342 -.1730721 green_policy_bank | -.1058947 .2604533 -0.41 0.684 -.6163738 .4045844 relates_parties_inst | 1.031185 .2932897 3.52 0.000 .4563474 1.606022 red_resource_waste | -.2139078 .3233362 -0.66 0.508 -.847635 .4198194 att_cus | .2338878 .2615333 0.89 0.371 -.2787081 .7464836 protect_envn | -.5832688 .2809209 -2.08 0.038 -1.133864 -.0326739 acc_service_delivery | -.5228718 .3057904 -1.71 0.087 -1.12221 .0764663 reduce_stat_cost | -.6925863 .2675606 -2.59 0.010 -1.216996 -.1681771 cost_effe_gb | .8398081 .3414738 2.46 0.014 .1705318 1.509084 data_sec_privacy | .2905189 .2405932 1.21 0.227 -.1810352 .762073 lack_edu | -.3451133 .2589885 -1.33 0.183 -.8527213 .1624948 traditional_app | .3461514 .2577362 1.34 0.179 -.1590023 .8513051 _cons | -1.237807 1.119049 -1.11 0.269 -3.431103 .9554897 -----------------------------------------------------------------------------------------

Multicollinearity Test:

Command:collin reg_nrb_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app (obs=233) Collinearity Diagnostics SQRT R- Variable VIF VIF Tolerance Squared ---------------------------------------------------- reg_nrb_gb 1.32 1.15 0.7556 0.2444 gen 1.08 1.04 0.9230 0.0770 age 5.00 2.24 0.2001 0.7999 work_exp 5.16 2.27 0.1938 0.8062 edu 1.13 1.06 0.8856 0.1144 bank_give_any_training 1.16 1.08 0.8620 0.1380 promotes_sr 1.16 1.08 0.8635 0.1365 reduces_res_wastage 1.27 1.13 0.7892 0.2108 operational_wealth_bank 1.26 1.12 0.7913 0.2087 green_policy_bank 1.47 1.21 0.6788 0.3212 relates_parties_inst 1.28 1.13 0.7823 0.2177 red_resource_waste 1.37 1.17 0.7320 0.2680 att_cus 1.28 1.13 0.7836 0.2164 protect_envn 1.36 1.16 0.7378 0.2622

126

acc_service_delivery 1.60 1.27 0.6234 0.3766 reduce_stat_cost 1.45 1.20 0.6892 0.3108 cost_effe_gb 1.25 1.12 0.8001 0.1999 data_sec_privacy 1.16 1.08 0.8628 0.1372 lack_edu 1.28 1.13 0.7833 0.2167 traditional_app 1.37 1.17 0.7315 0.2685 ------------------------------------------------------------------- Mean VIF 1.67 Cond Eigenval Index --------------------------------- 1 12.8203 1.0000 2 1.1943 3.2764 3 1.0426 3.5066 4 0.7777 4.0602 5 0.6990 4.2825 6 0.6265 4.5235 7 0.5375 4.8840 8 0.5136 4.9963 9 0.4282 5.4720 10 0.3867 5.7579 11 0.3405 6.1364 12 0.3201 6.3284 13 0.2689 6.9044 14 0.2583 7.0451 15 0.2016 7.9745 16 0.1660 8.7886 17 0.1413 9.5257 18 0.1331 9.8135 19 0.1151 10.5558 20 0.0233 23.4387 21 0.0055 48.4061 --------------------------------- Condition Number 48.4061 Eigenvalues & Cond Index computed from scaled raw sscp (w/ intercept) Det(correlation matrix) 0.0165

Heteroscedasticity Test:

Command:hettest Breusch-Pagan / Cook-Weisberg test for heteroskedasticity Ho: Constant variance Variables: fitted values of reg_nrb_gb chi2(1) = 33.81 Prob > chi2 = 0.0000

Final Regression Result (Probit Robust):

Command:probit reg_nrb_gb gen age work_exp edu bank_give_any_training promotes_sr reduces_res_wastage operational_wealth_bank green_policy_bank relates_parties_inst red_resource_waste att_cus protect_envn acc_service_delivery reduce_stat_cost cost_effe_gb data_sec_privacy lack_edu traditional_app,r Iteration 0: log pseudolikelihood = -112.89743 Iteration 1: log pseudolikelihood = -84.072958 Iteration 2: log pseudolikelihood = -82.733068 Iteration 3: log pseudolikelihood = -82.726902 Iteration 4: log pseudolikelihood = -82.726901 Probit regression Number of obs = 233 Wald chi2(19) = 49.90 Prob > chi2 = 0.0001 Log pseudolikelihood = -82.726901 Pseudo R2 = 0.2672 ----------------------------------------------------------------------------------------- | Robust reg_nrb_gb | Coef. Std. Err. z P>|z| [95% Conf. Interval] ------------------------+---------------------------------------------------------------- gen | -.1665163 .2335218 -0.71 0.476 -.6242105 .291178

127

age | .0232845 .0358534 0.65 0.516 -.0469869 .0935559 work_exp | -.0207364 .0372188 -0.56 0.577 -.093684 .0522112 edu | -.1058111 .2021542 -0.52 0.601 -.502026 .2904038 bank_give_any_training | -.1131238 .3804656 -0.30 0.766 -.8588226 .632575 promotes_sr | .3711273 .2461114 1.51 0.132 -.1112422 .8534968 reduces_res_wastage | .3040063 .2681347 1.13 0.257 -.221528 .8295407 operational_wealth_bank | -.6487069 .2518381 -2.58 0.010 -1.142301 -.1551133 green_policy_bank | -.1058947 .2470096 -0.43 0.668 -.5900246 .3782351 relates_parties_inst | 1.031185 .3095223 3.33 0.001 .4245321 1.637837 red_resource_waste | -.2139078 .3087927 -0.69 0.488 -.8191304 .3913148 att_cus | .2338878 .2315279 1.01 0.312 -.2198986 .6876742 protect_envn | -.5832688 .2574665 -2.27 0.023 -1.087894 -.0786437 acc_service_delivery | -.5228718 .278815 -1.88 0.061 -1.069339 .0235955 reduce_stat_cost | -.6925863 .253592 -2.73 0.006 -1.189618 -.1955551 cost_effe_gb | .8398081 .3119583 2.69 0.007 .228381 1.451235 data_sec_privacy | .2905189 .2275975 1.28 0.202 -.1555641 .7366019 lack_edu | -.3451133 .227722 -1.52 0.130 -.7914401 .1012136 traditional_app | .3461514 .2328664 1.49 0.137 -.1102582 .8025611 _cons | -1.237807 1.13158 -1.09 0.274 -3.455663 .9800493 -----------------------------------------------------------------------------------------