Gadjah Mada International Journal of Business Ae September-December.
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Gadjah Mada International Journal of Business Vol.
No.
3 (September-December 2.
: 237-258 Evaluating the Efficiency of Financial Inclusion (Special reference to Jharkhand.
Indi.
Suman Palit a and Niladri Dasb* Project fellow.
Indian school of Mines.
Dhanbad.
India Assistant professor.
Indian school of Mines.
Dhanbad.
India Abstract: This paper is an attempt to analyze the status of financial inclusion in the state of Jharkhand.
India.
It tries to evaluate the efficiency of the financial institutions in terms of their outreach to clients and overall client satisfaction.
Responses were collected separately from the service providers and customers through two different questionnaires and a convenience sampling method was adopted to select the Hypotheses development and testing was done to analyze data using a regression model.
The first questionnaire examined the relationship between various financial inclusion determinants with AuOutreachAy and the second questionnaire studied the relationship between financial inclusion determinants with AuCustomer satisfaction.
Ay The empirical results of the study exhibit that the financial inclusion determinants have a positive effect on the outreach to clients and overall customer satisfaction levels and improve the customersAo financial as well as their social capital base.
This in turn fosters the financial inclusion activity in the region.
Abstrak: Paper ini merupakan upaya untuk menganalisis status inklusi keuangan di negara bagian Jharkhand.
India, dan mencoba mengevaluasi efisiensi lembaga keuangan dalam hal jangkauan mereka untuk klien dan kepuasan klien secara keseluruhan.
Tanggapan dari kuesioner yang dikumpulkan secara terpisah dari penyedia layanan dan pelanggan melalui dua kuesioner yang berbeda dan metode convenience sampling diadopsi untuk memilih responden.
Pengembangan hipotesis dan pengujian dilakukan untuk menganalisis data menggunakan model regresi.
Kuesioner pertama, meneliti hubungan antara berbagai faktor penentu inklusi keuangan dengan Auoutreach,Ay dan kuesioner kedua mempelajari hubungan antara faktor-faktor penentu inklusi keuangan dengan Aukepuasan pelanggan.
Ay Hasil empiris dari studi ini bahwa penentu inklusi keuangan memiliki efek positif pada penjangkauan kepada klien dan tingkat kepuasan pelanggan secara keseluruhan dan meningkatkan pelanggan keuangan serta basis modal sosial mereka.
Hal ini pada gilirannya mendorong aktivitas inklusi keuangan di wilayah tersebut.
Keywords: customer satisfaction.
financial inclusion.
microfinance institutions.
NGOAos.
JEL classification: G21.
L31 * Corresponding authorAos e-mail: niladri_pnu2003@yahoo.
ISSN: 1141-1128
http://journal.
id/gamaijb Palit and Das Introduction Recently the issue of financial inclusion has received much attention from the researchers and policy makers all over the Financial inclusion is the delivery of financial services at affordable cost to sections of disadvantaged and low-income segments in society.
In the context of the financial institutions, it deals with the spread of their services among various sections of society.
AuMicrocredit, or microfinance, is managing an account for the unbankable, bringing credit, empowering investment funds and making other key money related administrations within the reach of a large number of individuals who are too poor to possibly be served by customary banks, on the grounds that, in the vast majority of cases, they are not able to offer adequate insurance.
When all is said and done, banks are for individuals with cash, not for individuals without cash,Ay (Balkom et al.
AuThe plan of microfinance, is accordingly, essentially the procurement of an extensive variety of monetary administrations, for example, stores, advances, installment administration and protection to poor and low wage family units,Ay (ADB 2.
In the context of the above definition, microfinance is the provision of financial services to those who have been neglected by the mainstream banking system.
Some plausible reasons for this neglect could be that the clients are poor, lacking in education, residing in remote areas, ignorant about banking rules etc.
Microfinance was perceived as one of the most promising and sustainable ways to tackle poverty alone, as it is usually presented as a package of financial services to the poor to improve their living standards.
Microfinance is thought to enhance access to education, health services, water and social In other words, financial inclusion activities are a barometer of economic growth for any country, state, or region in particular.
Background to The Study The failure of commercial banking to provi de financial services to the poor, coupled with the disadvantages of using informal markets, are major rationales for the intervention in the market of financial services at the micro level.
Consequently, microfinance emerged as an economic development approach intended to address the financial needs of the deprived groups in society.
The term microfinance alludes to AuThe procurement of monetary administrations to lowwage customers, including independently employed, low-salary business visionaries in both urban and country rangesAy (Dusuki The emergence of this new paradigm was encouraged by the success stories of microfinance innovations serving the poor throughout the 1970s and 1980s.
The most cited examples are Gram een Bank i n Bangladesh, the Unit Desa arrangement of Bank Rakyat Indonesia.
ACCION International in the United States and Latin America and PRODEM.
BancosolAos ancestor in Bolivia.
The microfinance industry embraces business sector arrangements and endeavors to establish an improvement approach.
It accentuates institutional and program advancements to diminish expenses and hazards and can possibly improve the standard of living for the poor in a suitable way (Ashraf 2.
Microfinance in India started in the early 1980s with small efforts at forming informal Self-Help Groups (SHG) to provide access to much-needed savings and credit From this small beginning, the microfinance sector has grown significantly Gadjah Mada International Journal of Business Ae September-December.
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in the past decades.
National bodies like the Small Industries Development Bank of India (SIDBI) and the National Bank for Agriculture and Rural Development(NABARD) are devoting significant time and financial resources to microfinance initiatives.
This indicates the growing importance of the sector.
The strength of the Microfinance Organizations (MFO.
in India is in the diversity of approaches and forms that have evolved over time.
After 60 years of independence, a large section of the Indian population still remains The stark reality is that most poor people in the world still lack access to sustainable financial services, whether it is savings, credit or insurance.
The great challenge before us is to address the constraints that exclude people from full participation in the financial sector.
India is said to live in its villages and nearly 72 percent of our population lives in villages .
s per a valid statement by the Indian Governmen.
But in spite of this huge population in the rural areas, around 650,000 villages do not have a single bank (Alm ost half the country i s The people in far-flung villages are completely ignorant of financial products, like insurance, which could protect the rural poor in adverse circumstances.
The rural poor suffer from financial impediments, seasonal incomes, irregularity of work and job related Only 55 percent of the population have a deposit account and 9 percent have credit accounts with banks.
India has the highest number of households .
excluded from banking.
There is on average only one bank branch per 14,000 Only a little less than 20 percent of the population has any kind of life insurance 6 percent of the population has non life insurance coverage.
Just 18 percent have debit cards and less than 2 percent possess credit cards.
With this backdrop.
Jharkhand, one of the eastern states in India, poses a unique development conundrum insofar as it remains remarkably poor despite possessing an abundance of natural resources, which should, in theory increase its prospects for growth.
The state boasts 40 percent of IndiaAos mineral reserves including iron ore, coal and copper, as well as the countryAos three largest steel plants.
Still.
Jharkhand has low average income levels, very high incidences of poverty and inequality, and low levels of social development in certain districts.
The financial infrastructure in Jharkhand is, as one might expect, notoriously underdeveloped.
Additionally, rural Jharkhand is characterized by the lack of access to credit.
Therefore, various policy initiatives have been taken by the Reserve Bank of India.
NABARD and Government of India to facilitate adequate institutional credit flows, particularly to the underprivileged class.
NABARD has taken a number of initiatives like identifying the potential for development, the preparation of bankable area development schemes, capacity building of entrepreneurs, facilitating the state government for the speedy implementation of rural infrastructure projects, providing promotional support for the expansion of the SHG-bank linkage program etc.
To conclude, financial inclusion not only affects .
n positive way.
the future economic conditions but also improves the routine life of a person and of an organization.
Further, in the modern economy, the social and economic status, as well as the growth of a person, organization and a nation, depends to a large extent on the level of access to formal financial services.
Palit and Das In light of the above discussion, the current work aims to put forward certain objectives that need to be addressed and fulfilled.
A Identify the key factors responsible for influencing financial inclusion and economic growth in the state of Jharkhand.
A Evaluate the efficiency of financial inclusion in terms of outreach to clients and overall customer satisfaction.
This paper tries to assess the penetration level of financial inclusion in the state of Jharkhand from both the service providersAo .
icrofinance institution.
as well as from the service usersAo .
points of view.
It attempts to evaluate the efficiency of financial institutions taking into account the social aspects of their performance.
The remainder of this paper is organized as follows.
The next section consists of the literature The third section explains the methodology adopted.
The fourth section analyses the results obtained and the last section gives the conclusions.
Literature Review The basic idea of microfinance is to provide credit to the people who otherwise would not have access to credit services.
Microcredit programs extend small loans to poor people for self-employment projects that have the potential to generate income and allow them to take care of themselves and their families.
There are various studies which confirm that microfinance programs have a significant positive impact in increasing employment and reducing poverty.
In order to find out the impact of microfinance programs, impact assessment studies have been done by many authors in different countries like Bangladesh.
India.
Nepal.
Thailand.
Ghana.
Rwanda.
Peru and many other countries in South Asia and Africa.
AuAs per a World Bank overview directed for the mid-term audit of neediness mitigation and micro-finance ventures among 675 microcredit borrowers in Bangladesh there is a positive change in the m onetary and econom ic wellbeing of the studied borrowers.
The overview demonstrated that pay had expanded for 98 percent of the borrowers.
89 percent of the borrowers amassed new resources and 29 percent had bought new land, either for property or for agriculture.
Food intake, lodging and clothing had also been enhanced for 89, 88 and 75 percent of the borrowers respectively.
The changes had for the most part happened because of the expanded level of independent work of the ladies membersAy (Lavoori and Paramani 2.
A study conducted on SAPAP self-help groups in Andhra Pradesh.
India also reported an overall reduction in poverty, including reductions among the extreme poor (Kabeer Sheokand talked about the development of Indians managing an account and the inability to give credit facilities to needy individuals.
NABARD began a self-help group - bank linkage program in 1992, which was viewed as a milestone advancement in banking for poor people.
It was observed that regional rural banksAo concentrated more on providing credit to focused groups.
Government sponsored projects had occupied a large part of the financial space and yet did not accomplish the goal of mitigating neediness.
Selfhelp groups with bank linkage projects had been demonstrated to be exceptionally effective at financially strengthening the bad-tothe-bone poor, giving monetary assistance to them and setting them up to take monetary responsibility for neediness lightening.
In spite of the fact that this project was not a pana- Gadjah Mada International Journal of Business Ae September-December.
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cea for the issues of rural destitution, it had the potential for turning into a changeless arrangement for provincial loaning in the nation with full investment from the formal banking framework and with no impedance from the government.
Ay An investigation into the financial effects of PRADAN microfinance was completed in the state of Jharkhand to figure out the ability of microfinance to meet the customersAo fundamental needs, vocational base, resource position, savings, and obligation 400 SHG individuals were compared with 104 non-individuals in the Godda.
Dumka and Banka regions of Jharkhand.
the extent of meeting their fundamental needs, the individuals had reported a far more ideal general diet, as far as sufficiency and differing qualities of available nourishment, when contrasted with the non-individuals.
SHG individuals had more elevated amounts of investment funds and lower occurrence of (Kabeer and Noponen 2.
AuIn this ever changing world, one has to measure an organizationAos efficiency in order to regulate and make the necessary reforms so as to meet the organizational objectives and speed the expeditions.
Ay (From Pitt and KhandekarAos 1998 study of the impact of microfinance on poverty in Banglades.
Chowdhury et al.
examined empirically the impact of microcredit on poverty in Bangladesh.
The focus was on both subjective and objective poverty and attention was paid to the time period, the clients had access to microcredit.
The execution criteria shifted fundamentally starting with one association then onto the next, since they rely on the methodological methodology, which thus relies on the determination to offer need to the supply side or the interest side of the monetary intermediation.
In such a manner, there are two differentiating schools of thought: AuWelfaristAy and AuInstitutionalist.
Ay The first measures the performance of the MFIs on the premise of welfare studies.
They are keen on the MFIs sway on the living state of the recipients.
Welfare studies were criticized by the AuInstitutionalistsAy in view of their subjectivity, their expense and the methodological troubles they They are keen on business variables, for example, the reimbursement rate, the exchange costs and the levels of money related independence and so on, one way or the other, the issue of measuring the effectiveness of the MFIAos twists at assessing their execution for the effort, maintainability and their social effectAy (Congo 2.
According to CheminingAowa, outreach is the effort of MFIs to provide microfinance services to the people who do not come under the umbrella of formal banking and financial institutions.
In order to measure the social impact of the MFIs, it is mandatory to focus on AuPoverty.
Ay (Montgomery and Weiss 2.
defined poverty as AuA lack of access by poor households to the assets necessary for a higher standard of income or welfare, regardless of whether these assets are thought of as human .
ccess to educatio.
, natural .
ccess to lan.
, physical .
ccess to infrastructur.
, social .
ccess to networks of obligation.
or financial .
ccess to credi.
Ay The evaluation of the social impact of the MFIAos in abating poverty has been put forward by different scholars in many different ways.
For example, according to Meyer.
AuSocial impact is defined as attributing specific effects, impacts or the benefits of specific interventions, in this case, improved access to financial services.
Ay Palit and Das Methods This paper suggests a set of operational indicators designed to measure the different dimensions and elements of the social performance of the MFIs.
AuThe social performance of an organization comprises the relations of the organization with its clients and with other stakeholder groups.
The measurement of social performance involves investigating the structure of an organization and its conduct in the market, and the local and wider community.
In the proposed questionnaire social performance is measured through the principles, the actions and the corrective measures implemented by the MFIsAy (Zeller et al.
The present study analyzes the efficiency of financial inclusion in Jharkhand with the help of two questionnaires.
A The first questionnaire for service providers/facilitators examines the relationship between the social performance of the MFIs .
inancial inclusion determinant.
with their outreach to clients.
A The second questionnaire for the service users tries to establish the relationship between the various determinants of financial inclusion and customer satisfaction for the various MFIs in four districts of Jharkhand i .
Dhanbad.
Ranchi.
Jamshedpur and Bokaro.
Four important performance measurements of financial inclusion in the first questionnaire for service providers are: Geographic focus, types of services offered by the MFI, the participation level of the MFIs and access to information whose validity has been tested on the AuOutreach to clients.
Ay Similarly, in the second questionnaire for service users thirteen indicators have been identified as the financial inclusion variables and their validity has been tested on the depen- dent variable AuCustomer satisfactionAy using a linear regression model.
Data Sources The formulation of the research questions and the hypotheses that are to be tested, the nature of the universe, the sampling frame and the sample that has been selected are all described in detail according to the objectives of the study.
The population for the first questionnaire of this study included the employees of microfinance institutions, public sector banks and NGOs .
ervice provider.
who had their various branches located in Ranchi.
Jamshedpur.
Dhanbad and Bokaro.
The population for the second questionnaire included the customers .
ervice user.
of the above mentioned financial institutions.
The data was collected from the following institutions:
A SKS Microfinance A Bandhan Financial Services A Ujjivan Microfinance A Bank of India
A IDBI Bank
A Bank of Baroda
A Indian Overseas Bank
A Global Health Education Organization Ae
NGO
For the service providers a list comprising of 250 employees had been obtained from the selected institutions in 4 districts of Jharkhand.
A convenience sampling method was adopted to select the service providers.
The sample size for the finite population of 250 service providers/facilitators was computed as 152 at the 5 percent confidence interval and allowing for a 95 percent level of Further, an additional 10 percent Gadjah Mada International Journal of Business Ae September-December.
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Table 1.
Sample Distribution Across 4 Districts for Service Providers Table 2.
Sample Distribution Across 4 Districts for Service Users Regions Sample Respondents Regions Dhanbad Dhanbad Ranchi Ranchi Bokaro Bokaro Jamshedpur Jamshedpur Total Total was added to the sample size to cover for invalid and non-responses.
Thus a sample size of 166 was selected for this study.
However, out of this 166 sample of service providers/ facilitators, 31 did not participated in the survey and six responses were found to be incomplete.
Thus a total of 129 questionnaires containing correctly completed information were used for our data analysis.
Similarly, for the service users a list comprising of 250 customers had been obtained from the above institutions in the above mentioned districts.
A convenience sampling method was adopted to select the customers.
The sample size for the finite population of 250 service users was computed to be 152 at a 5 percent confidence interval and allowing for a 95 percent level of precision.
Further, an additional 10 percent was added to the sample size to cover invalid or non-respondents.
Hence a sample size of 166 was arrived at for this part of the study.
In the case of the service users, out of our 166 sample customers, 43 did not participate in the survey and 11 responses were been found to be Thus a total of 112 questionnaires containing completed information were used for the data analysis.
Sample Respondents Statistical Tools Simple descriptive statistical tools were applied to find out the percentages, means and standard deviations of the demographic profiles of the service providers as well as the service users.
Hypothesis testing was used for analysing the data.
Additionally, the study used advanced statistical tools like a multiple linear regression model calculated in SPSS 0 package to find out the causal effect of various variables on the outreach to clients and customer satisfaction levels separately for the service providers and service users.
The number of sample respondents across the four districts is shown in Table 1 and Table 2.
Survey Instrument Two sets of questionnaires were developed in order to evaluate the efficiency of financial inclusion in the above mentioned Questionnaire 1: It was divided into four sections A General Information A Profile of the Organization A Financial Inclusion Determinants A Outreach to Clients/coverage Palit and Das General Information.
The first section collects information on the employeeAos age, sex, residential address and marital status.
Profile of the Organization.
It contains information on the name and address of the organization and the type of business they are into.
Financial Inclusion Determinants.
This section consist of questions on four important determinants of financial inclusion, the geographic focus, the types of services offered by the MFI, the participation level of the MFI and the access to information.
These four factors were further subdivided into other sub-factors which were measured by related instruments based on a five point rating scale ranging from 1 strongly disagree to 5 strongly agree.
Outreach to Clients/Coverage.
This section determined the outreach of the MFIs in terms of their numbers of clients or accounts that were active for the last three years which was measured on the same five point rating The influence of all the financial inclusion determinants was tested on this variable in order to evaluate the efficiency of the financial inclusion.
Questionnaire 2: It was divided into 3 sections:
A Baseline information A Financial inclusion determinants A Customer satisfaction Baseline Information.
This section collected information on the customers / service userAos age, gender and type of business activity they were associated with.
Financial Inclusion Determinants.
This section contained 13 indicators which measured the customerAos satisfaction on a five point rating scale ranging from 1 strongly disagree to 5 strongly agree.
Customer Satisfaction.
The influence of the other critical indicators was tested on the dependent variable AuCustomer satisfactionAy (Bihari et al.
Result and Discussion This chapter consists of our results and analysis of the data gathered using suitable statistical tools and formulating and testing the hypotheses developed.
The analysis has been done in three stages.
Descriptive statistics of the demographic profiles of the service providers and users Analysis and hypotheses testing for the service providers Analysis and hypothesis testing for the service users Scale analysis.
Once the returned questionnaires had been received and checked for suitability, the scale reliability of the developed variables were analyzed using CronbachAos alpha test on both the samples.
Reliability.
CronbachAos alpha is a reliability coefficiency indicator that shows how well the variables are positively correlated to each The CronbachAos alpha came out to be 779 for the service providers and 0.
801 for the service users samples which was considered to be a good sign of reliability as it was more than 0.
7 (Santos 1.
Validity.
Content validity and face validity tests were also done by employing expert Five questionnaires were distributed to experts in the field of academics and finance.
The experts reviewed the questionnaires and according to their suggestions the questionnaire was redesigned as required.
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Table 3.
Mean and Standard Deviations of the Responses (Service Provider.
Variables Mean Standard Deviation Customers targeted in rural areas Customers targeted in urban/semi-urban areas Customers targeted for socio-economic development of the region Literacy training Market information Social awareness training Legal counsel Participation in government meetings Participation in non-government activities Participation in social/political movements Decision making influence on government organizations Decision making influence in the private/NGO sector Receipt of transaction statements Passbook maintenance for savings Passbook maintenance for loans Client participation in business decisions of the MFIs Satisfaction with the number of clients or accounts that are active in the last 3 years Table 4.
Mean and Standard Deviations of the Responses (Service User.
Variables Mean Standard Deviation Client specific needs Client personal attention Management support to employees Safety of transactions Trust in employees Efficient response to client requests Willingness to help customers Prompt service Sympathetic attitude to clients Accuracy of records maintenance Convenient business hours Client specific loan products Client satisfaction with the interest rates I would prefer to use the services of MFIs and in future I will with confidence Palit and Das Descriptive statistics of demographic Table 3 and Table 4 give the means and standard deviations of the respondents .
ervice providers and service user.
and 20-30 .
86 percen.
, a few were in the age group of 40-50 .
96 percen.
and none in the 50 and above group.
Almost, 87 percent were males and only 13 percent females.
The demographic profile represents the pattern of the respondents in terms of their age, gender, marital status and occupation comprising the service providers and service users/customers in Tables 5 and 6.
In the case of the customers, it was observed that the hi ghest number of microloan seekers were in the age groups of 20-30 and 30-40.
It can be observed from Table 5 that out of the total of 129 respondents from the service providers group, most of them were in the age groups of 30-40 .
18 percen.
Table 5.
Service Providers/MFIs Dimensions Particulars Percentage Age 50 and above Gender Male Female Unmarried Married Marital status Table 6.
Service Users Particulars Percentage Age 50 and above Male Female Salaried Self-employed Type of Analysis and Hypotheses Testing for the Service Providers Four factors were taken into consideration namely, the geographic focus, the types of services, the participation level of the MFIs and the access to information.
Development of Hypotheses Dimensions Gender Around 70 percent of the microfinance users were females, as a result of which most of them experienced an increase in their decision making roles in the areas of family planning, marriage of children, buying and selling property and sending their daughters to school (Ashe and Parrot 2.
This showed that microfinance created a strong impact on the empowerment of women.
could also be observed that the number of self-employed customers .
was much higher than the number of salaried clients.
Hypothesis 1: Geographic focus has a positive impact on the outreach or number of clients served .
Hypothesis 2: Types of services offered by the MFIs affects the outreach to clients.
Hypothesis 3: Participation level of the MFIs affects the outreach/ coverage.
Hypothesis 4: Access to information has a positive impact on the outreach to clients.
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Geographic Focus Three factors have been identified under this dimension namely customers targeted in rural areas, customers targeted in urban/ semi-urban areas and customers targeted for socio-economic development of the region.
Regression analysis was carried out to find out the causal effect of each of these three factors on the outreach to the clients.
The following regression model was used to measure the indicators of geographic focus on the coverage or outreach to the clients:
Outreach= A A 1 customers in rural areas A 2 customers in urban/semiurban areas A 3 customers targeted for socio-economic development of the region Au1 where.
A is the intercept.
A 1.
A 2.
A 3 the regression coefficients and Au1 is the error term.
Table 7 shows the regression values of the independent variables of geographic focus.
It clearly shows that the coefficients of customers targeted in rural areas, customers targeted in urban areas and customers targeted for socio-economic development of the region are significant at the 1 percent significance level.
The adjusted R2 value is 0.
and the higher F-value being significant at the 1 percent level shows the good fit of the regression model.
This suggests that geographic focus had a positive impact on the number of clients/coverage.
Types of Services Offered by the MFIs The four factors identified under this dimension were Ae literacy training, market information, social awareness training and legal counsel.
Regression analysis was done to find out the causal effect of each of these four factors on the outreach to the clients.
Table 7.
Regression Analysis of Geographic Focus Dependent Variable: Outreach (Number of Clients Serve.
Variables Coefficients Customers targeted in rural areas 761 * .
Customers targeted in urban/semi-urban areas 789 * .
Customers targeted for socio-economic development of the region 694 * .
Adjusted R2 Analysis of Variance Model Sum of Squares Mean Square Sig.
Regression Residual Note: * and ** implies 1 and 5 percent significance level respectively, t-values are in the parentheses.
Palit and Das The following regression model had been used to measure the indicators of the types of services offered by the coverage or outreach to the clients:
Outreach = A A 1 literacy training A 2 market information A 3 social awareness training A 4 legal counsel Au1 where.
A is the intercept.
A 1.
A 2.
A 3.
A 4 the regression coefficients and Au1 is the error term.
The result of the regression analysis in Table 8 .
demonstrates that market information is highly significant whereas literacy training and social awareness training are less significant, except for the legal counsel.
Legal counsel showed a negative impact on the outreach to clients and the financial inclusion process as the coefficient was insignificant.
But, overall the types of training services offered by these institutions were really helpful in achieving a strong customer base and fulfilled the objective of financial Participation level of the MFIs There were five factors identified under the participation level of the MFIsAo influence on the outreach to the clients.
Hence, a regression analysis was used to identify the participation level factor that affected the outreach to the clients:
Outreach = A A 1 participation in government meetings A 2 participation in non-governmental activities A 3 participation in social/political movements A 4 decision making influence in government organizations A 5 decision making influence in private/NGO sector Au1 Table 8.
Regression Analysis of Types of Services Offered Dependent Variable: Outreach (Number of Clients Serve.
Variables Coefficients Literacy training 076**.
Market information 709*.
Social awareness training 078**.
Legal counsel 089(-0.
Adjusted R2 Analysis of Variance Model Sum of Squares Mean Square Sig.
Regression Residual Note: * and ** implies 1 and 5 percent significance level respectively, t-values are in the parentheses.
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Table 9.
Regression Analysis for Participation Level of MFIs Dependent Variable: Outreach (Number of Clients Serve.
Variables Coefficients Participation in government meetings 043**.
Participation in non-government activities 091**.
Participation in social/political movements 078**.
Decision making influence in government organizations 203(-1.
Decision making influence in the private/NGO sector 019**.
Adjusted R2 Analysis of Variance Model Sum of Squares Mean Square Regression Residual Sig.
Note: * and ** implies 1 and 5 percent significance level respectively, t-values are in the parentheses.
A is the intercept.
A 1.
A 2.
A 3.
A 4.
A 5 the regression coefficients and Au1 is the error term.
Table 9 shows the regression values of the five independent variables on the outreach.
It clearly shows the significance of the regression coefficients at the 5 percent significance level, except for the decision-making power in government organizations which showed a negative impact on the outreach to The negative relationship may be attributed to the reluctance on the part of the government to have the MFIs participating in their decision making processes.
But the overall impact of the participation level of the MFIs in various government and non-government activities was positive, and they do play a role in reaching out to a significantly large number of clients and providing loans for the betterment of the masses.
Access to Information The four factors identified under this dimension were Ae receipt of financial transaction statements, passbook maintenance for savings, passbook maintenance for loans and clients participation in business decisions.
Regression analysis was done to find the causal effect of each of these four factors on the outreach to the clients.
The following regression model was used:
Outreach = A A 1 receipt of transaction statements A 2 passbook maintenance for savings A3 passbook maintenance for loans A 4 client participation i n busi ness decisions of MFIs Au1 where.
A is the intercept.
A 1.
A 2.
A 3.
A 4 the regression coefficients and Au1 is the error term.
Palit and Das Table 10.
Regression Analysis of Access to Information Dependent Variable: Outreach (Number of Clients Serve.
Variables Coefficients Receipt of transaction statements 861*.
Passbook maintenance for savings 869*.
Passbook maintenance for loans 843*.
Client participation in business decisions of the MFIs 706*.
Adjusted R2 Analysis of Variance Model Sum of Squares Mean Square Sig.
Regression Residual Note: * and ** implies 1 and 5 percent significance level respectively, t-values are in the parentheses It can be clearly ascertained from the table that all four factors were highly significant at the 1 percent significance level.
The adjusted value of R2 was 0.
883, which is on the higher side, and a high value of F at 1 percent shows the good fit of the regression The hypothesis developed tested positive showing the usefulness of information accessibility on financial inclusion.
Analysis and Hypotheses Testing for the Service Users Thirteen indicators had been identified as financial inclusion variables and their validity was tested on the dependent variable AuCustomer satisfactionAy using a linear regression model.
Development of Hypothesis H1: Microfinance operations have a positive impact on customer satisfaction.
The following regression model was used to measure the indicators of financial inclusion on customer satisfaction.
Customer satisfaction = A A 1 client specific needs A 2 client personal attention A 3 management support to employees A 4 safety of transactions A 5 trust on employees A 6 efficient responses to client requests A 7 willingness to help customers A 8 prompt service A 9 sympathetic attitude towards clients A 10 accuracy of records maintenance A 11 convenient business hours A 12 client specific loan products A 13 interest rate affordability Au1 Gadjah Mada International Journal of Business Ae September-December.
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Table 11.
Regression Analysis for Customer Satisfaction Dependent Variable: Customer Satisfaction Variables Coefficients Client specific needs 317**.
Client personal attention 071**.
Management support for employees 049**.
Safety of transactions 871**.
Trust in employees 543**.
Efficient response to client requests 231*.
Willingness to help customers 702*.
Prompt service 630*.
Sympathetic attitude to clients 103**.
Accuracy of records maintenance 836*.
Convenient business hours 101(-0.
Client specific loan products 082**.
Interest rate affordability 008(-1.
Adjusted R2 Analysis of Variance Model Sum of Squares Mean Square Sig.
Regression Residual Note: * and ** implies 1 and 5 percent significance level respectively, t-values are in the parentheses.
A is the intercept.
A 1.
A 2.
A 3.
A 4.
A 5.
A 6.
A 7.
A 8.
A 9.
A 10 .
A 11 .
A 12 .
A 13 are the regression coefficients and Au1 is the error term.
Table 11 shows the regression values of the independent variables.
The adjusted R2 value is 0.
886 and the higher value of F being significant at 1 percent shows the good fit of the regression model used to understand the dependency of the financial inclusion variables on AuCustomer satisfaction.
Ay It clearly shows that the coefficient of efficient responses to client requests, willingness to help customers, prompt service delivery to clients and accuracy in records maintenance are highly significant at the 1 percent significance level.
On the other hand the coefficient of clientsAo specific needs, personal attention to clients, management support to employees, safety of transactions, trust in the MFIsAo employees and clientsAo specific loan products are significant at the 5 percent significance Palit and Das It is quite clear from the analysis that the higher the impact of these factors is, the higher will be the customersAo loyalty towards the MFIs, which in turn will promote financial inclusion in the region.
However, two factors Ae convenient business hours for, and the interest rate affordability of, the clients, are both insignificant.
The negative relationship of business hours on customer satisfaction may be attributed to the bureaucratic working style of the public sector banks.
The negative relationship of interest rates affordability can be attributed to the very high rates charged by the microfinance institutions, which sometimes makes it difficult for the customers to repay on time.
Overall, the financial inclusion determinants had a positive impact on the customer satisfaction as developed in our hypothesis and were very crucial for the financial inclusion initiative in the state of Jharkhand.
Conclusion This study identified the key factors which had a profound influence on the performance of the microfinance institutions and as well as the factors which influenced the customersAo satisfaction level.
Though there is no dearth of li terature rel ated to microfinance, and impact assessment studies have been done by many authors in different countries like Bangladesh.
India.
Pakistan.
Nepal.
Thailand.
Ghana.
Rwanda.
Peru and many other countries in South Asia and Africa, this study added to the available Some research worksAo emphasis were more on the financial performance of the microfinance institutions, while some others on the outreach to the clients.
There were limited studies which analyzed the efficiency of the financial inclusion from the performance as well as from the customersAo satisfaction point of view.
This study contributes to the literature by determining the indicators responsible for effective financial inclusion and economic growth in the state of Jharkhand.
Major Findings of The Study A Geographic focus / frequency and type of customers targeted by the MFIs have a positive impact on the outreach to clients which in turn positively affects the level of financial inclusion activity in any region.
The quality and type of training services offered by these institutions are really helpful in achieving a strong base of customers and fulfilling the objective of financial inclusion.
A The influence of the participation level of the MFIs in government and non-governmental activities has a significant impact on the financial inclusion.
A The financial inclusion determinants have a positive impact on the customer satisfaction levels as developed in our hypothesis and are very crucial for the financial inclusion initiative in Jharkhand.
Limitations of the Study The current study is not free from certain limitations.
The present study was restricted to the list of factors that determine the success of financial inclusion.
Data were collected from only four districts of Jharkhand i.
Dhanbad.
Bokaro.
Jamshedpur and Ranchi, keeping in mind the Gadjah Mada International Journal of Business Ae September-December.
Vol.
No.
3, 2015
convenience and accessibility of the researchers.
Thus, the question of inadequate representation cannot be ruled out.
Finally this being a case study in Jharkhand, its generalization across the country will be rather limited.
References