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The data can be collected by the form of secondary data such as the annual report. In this research paper, the researchers have decided to use secondary data to analyses the data in detail. As per the researcher's point of view, the secondary data proved to be more useful in testing the hypothesis and it becomes more relevant with regard to the technical analysis of the data. Generally, secondary data were mostly used in preparing the other projects related to "microfinance institutions" and hence, it proved to be more efficient in the detailed analysis. The detailed analysis would be covered up in the upcoming sections. This report has been prepared by the collection of data which was usually gathered from the “Department of Development Finance” and which was considered to be more relevant and useful data in analysing the whole report as per the regulatory bodies governing the system of "microfinance" in Srilanka.
The
researchers have taken such wide measures by various analytical tools which
will be discussed below in more detail. From the secondary data, a lot of
online data has been collected from different articles which have been
identified in the "Reference List" section. And also the sample of
the research is conducting through the 5 major micro finance institutions in
srilanka, which data could collected through the department of development
finance such as the annual report from 2013 to 2017. Researcher has conducting
the DEA analysis with help of the using excel, r studio and stata.
Analysis method of The microfinancing industry of Sri Lanka.
Data
envelopment method of The microfinancing industry of Sri Lanka.
This
is a non-parametric technique to design to help you measure and improve the
performance of organisation. This analysis used the powerful technique called
the data envelopment method. This analysis compares the relativity efficiency
of the organization for an example in a company efficiency factor can consider
as input and output, input are such as staffs, assets, branches, operating
expenses and output factors are such as sales volume and revenue those
efficiency factors are taking to the one model and calculating the organization
efficiency also it help to give a ideas for “how well are the units doing? “And
“how much could improve the units?” And
it’s also It is help to develop the in these organisations to perform a number
of tasks including
·
Allocating the resource from
inefficiency to efficient
·
Assessment of best practice
·
Identifying the poor and best
practice
·
Monitoring the efficiency of
factors
·
Do the Target setting
The researchers used the methodology to define a better
understanding of the analysis part for the users in which they decided to take
the process of "data employment analysis." In a broader sense, the
scores of data employment analysis (DEA) analysis will be tested through software
named " rstudio " This "rstudio " is used very efficiently
to access the output by providing valuable input from the collection of data
within a short period of time. Researcher
conducting the DEA model CRS ,VRS and SE ,charnes,cooper and Rhodes (1978) CRS
model which had a input orientation and assumed constant return to scale later
alternative assumption such as banker
,charner and cooper (1984) who proposed the variable return scale model .CRS
model only possible to when all DMU’s are operating at the optimal scale
imperfect of competition constaints on institution it may cause to DMU to be
not operating at optimal scale later banker ,charnes,and cooper suggested the extension
of CRS model that VRS . the use of CRS specification when not all DMU’s are
operating at the optimal scale will result in
measure of TE which are confounded by scale efficiencies. The use of VRS
will permit the calculation of TE.
Technical efficiency of The microfinancing industry of Sri
Lanka.
Technical efficiency in the form of
better results that provides a complete pair of inputs to develop the output
for the users. Any organization is considered more efficient those utilize the minimum
number of input and then produce the maximum number of output as technology,
capital, labour and material. No unemployment of resources also required by
technical efficiency. The rate of technical efficiency also determines by
dividing the real output from the given inputs by the highest potential output
from given inputs*100. So if any factor and worker were underemployed then it’s
potential of output also missing.
Pure efficiency or pure technical
efficiency is the type of efficiency that determines also the inefficiencies of
the system and also the size of operation according to information. The
efficiency measure according to VRS assumptions is also included in the pure
technical efficiency. Due to managerial underperformance, the pure technical
efficiencies also determine and consider all the flows and weak areas according
to the performance of the organization. There are many different situations
occur when the pure technical efficiency is determined and measurement the
organization's performance according to its operations and technical set up
Scale efficiency of
The microfinancing industry of Sri Lanka.
Any production or manufacturing of
units determine the scale efficiency when the operational size if the maximum
and after some modification, the efficiency also minimize. Aggregate capability
divided by the technical efficiency than the value of scale efficiency also
determines. Scale efficiency also explains in terms of its manufacturing and
also explains if the unit mass is differing then its efficiency also effected
due to its actual measurement and any change brings down the overall product
down. Scale efficiency help to explain the different facts related to the
measurement of the units and also help to maximize the results related to
output
Differentiate
chart of DEA models: DEA is a form of methodology that use in the organizations
to assess the efficiency in the number of entities and using a set of in
commensurate inputs to develop the simple set of in commensurate outputs. It
helps to compare the products of different organizations according to their
efficiency. It uses the task of fractional programming but it also uses the
linear programming for the units of different tasks under the system of
evaluation.
References of “Department of Development Finance”
(n.d.). Retrieved from
www.cbsl.gov.lk: https://www.cbsl.gov.lk/
Gunatilaka & Silva. (2010). Microfinance
and women's empowerment : the impact of loan ownership on women's empowerment
in microfinance households in Sri Lanka.
Stevenson & St-Onge. (2005). Support
for Growth-oriented Women Entrepreneurs in Tanzania.
annual report of divineguma. (2017). department
of divineguma development.
Atapattu, A. (2009). State of
Microfinance in Sri Lanka.
Beatriz Armendáriz,Bert D’Espallier
,Marek Hudon . (2011). Subsidy Uncertainty and Microfinance Mission Drift.
Bernstein & Seibel. (2011).
Reparations, Microfinance, and Gender:A Plan, with Strategies for
Implementation. 75-113.
CBS. (2010). Annual Report of the
Monetary Board To the Hon Minister of Finance.
Chandradasa, A. J. (2019). Microfinance
and Shelter: An Impact Assessment of microfinance on improving housing
conditions of rural srilanka.
charitonenko, S. (2002).
Commercialization of micro finance in sri lanka. 3-20.
Chavan, P & Ramakumar, R. (2002). Micro-Credit
and Rural Poverty:An Analysis of Empirical Evidence.
crbbank.lk. (2017). Colombo District
Cooperative Rural Bank Union Limited. Retrieved from
https://www.crbbank.lk/wp-content/uploads/2019/08/CRB-Bank-Annual-Report-2017.pdf
DCS. (2009). Household Income and
Expenditure. colombo.
DDF. (2017). department of finance ,
performance report. department of finance.
Demirguc-Kunt, A., Klapper, L., Singer,
D. and Oudheusden. (2015). The Global Findex Database 2014: Measuring
Financial Inclusion around the World.
divineguma, P. r. (2015). department
of divineguma development.
economicshelp.org. (2019). Technical
Efficiency Definition. Retrieved from
https://www.economicshelp.org/blog/glossary/technical-efficiency/
Fixing Sri Lanka’s labour market:
Comparative lessons.
(n.d.). Retrieved from
http://www.ft.lk/columns/Fixing-Sri-Lanka-s-labour-market--Comparative-lessons/4-658844:
ft.lk
Fletschner, D. (2009). Rural Women's
Access to Credit: Market Imperfections and Intrahousehold Dynamics. world
department, 618-631.
G Tilakaratna,U Wickramasinghe, . (2005).
Microfinance in srilanak: A household level analysis of outreach and
impact on poverty.
Harker, M. M. (2006). The Microfinance
Movement: An Analysis of the Reach and Scope of Microfinance Institutions in
the Developing World.
herath. (2015). Impact of Microfinance on Poverty Reduction:evidance from srilanka.
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