This chapter aims to describe the research methodologies used to collect the data which will apply in this study. The discussion of methodology was structured as follows: research design, data collection methods, sampling design, data analysis method and mostly important is model description. According to Hair, Bush and Ortinau (2006), the research design serves as a master plan of the methods to use to collect and analyze the data. By evaluating and choosing the correct research design, it will enable the researchers to develop relevant research methodologies. In this chapter, the details of models will be discussed on how it will help researchers in answering the research questions on how total loan, loan tenure, education of borrowers, borrower’s age, business experience, type of business, technical training, business course, marital status and gender influence the impacts of microfinance on household income, individual income and business income offered by government agencies and commercial banks. This study utilized surveys intended to assess the relationship between the effects of microfinance facilities that provided by government agencies and commercial banks with income of household, individual and business in Malaysia.
A research can be differentiated in terms of approach, either by using quantitative or qualitative approach (Neuman, 2006). Deriving accurate information is highly dependent upon the survey method. The direct face-to face interview is the most commonly used approach (Ogunlade and Adebayo, 2009) and is employed in this study. The research aims to provide an understanding of what is the different between government and non-government institution on the impacts of microfinance taking place on household income, individual income, and business income was affected by constructs like total loan, loan tenure, education of borrowers, borrowers’ age, business experience, type of business, technical training, business course, marital status and gender. In addition, the descriptive and causal research design was applied in this research and work as the main research design. Meanwhile, causal study method was being used to examine the relationships between income of household, individual and business toward the total loan, loan tenure, education of borrowers, borrowers age, business age, type of business, technical training, business course, marital status and gender in microfinance activities. According to Zikmund (2003) descriptive research is use to describe the characteristics of population or phenomenon meanwhile causal research is conducted to identify cause-effect link between variables when the research problem has already been defined.
Data collection is the systematic gathering of data for a particular purpose. A research can be started by selecting quantitative or qualitative approach (Neuman, 2006). This study uses one types of data collection method which is primary data. Due to the money and time constrain, this study was choosing the survey questionnaire as the primary data source.
Primary data consist of information collected for the specific purpose at hand (Kotler, Brown, Adam and Armstrong 2004, p.219). Primary data collection will be adopted in this research and the main source of primary data collection in this study is obtained from survey questionnaire because survey questionnaire is convenience, cost saving and time saving. In this research, 123 sets of questionnaire were distributed to residents in Klang Valley. It is important to have a clear and well structure of questionnaire to let all the respondents to answer it easily in the shorter time. Although primary data are more expensive compare with secondary data, it can provide the latest information about the opinions from the current respondents.
The purpose of this research as stated as in the earlier chapter is to evaluate impacts of microfinance that provided by government and non-government institution toward household income, individual income, and business income in Klang Valley. The determinants (independent variables) include total loan, loan tenure, education of borrowers, borrower’s age, business age, type of business, technical training and business course. Hair, Bush & Ortinau (2006) defines independent variables as “an attribute or elements of an object, idea or event whose measurement scales values are directly manipulate by the researcher”. In this research, dependent variables are including household income, individual income and business income. Hair et al. (2006) defines dependent variables as a singular attribute or element that is the measured outcome or effect change on specific test subjects that is derived from manipulating the independent variables.
Since, it is difficult to conduct a survey on the whole Malaysia population due to limited resources such as cost and time. As a result, this research will select a specific area which is Klang Valley respondents in the population to draw conclusion about the entire population of Malaysian. The main population for this research is the residents in Klang Valley who have receiving the microfinance facilities from government and non-government institution. The eligible respondents for this research will be adults who are 18 years old and above that getting microloan to run his or her business. The reasons for choosing this area of target population are due to the numbers of entrepreneur who getting microfinance are the highest among other cities in Malaysia. This will directly save the cost and time in order to get the greater accurate results and high speed of data collection. Meanwhile, this study’s respondents came from one of the cities in Malaysia, namely, Klang Valley and the surveys were conducted from 3th April to 8th May 2015.
The respondents that will take part in this research study will be restricted to the current residents of Klang Valley who have getting microfinance facilities for business purpose at least one time from any financial institution. The microfinance facilities are including micro-credit and others. Sampling location for this study is Klang Valley. Residents of Klang Valley which have participated in microfinance facilities at least once are identified as the prospective respondents as they have ability to evaluate the impacts of microfinance on household income, individual income and business income. Respondents were randomly selected to ensure the accuracy of this study. All the respondents were required to answer the questionnaire on the spot.
There are two types of sampling techniques which are probability sampling and non probability sampling (Churchill, Jr. and Iacoucci, 2005). The samples selected of this study are based on the non-probability sampling. In this study, judgment sampling is selected as main sampling procedure which based on research objective. The researcher believes that the respondents represent the population of interest (Malhotra and Peterson, 2006).
Roscoe (1975) proposed the rules of thumb for determine the sample size where it is more than 30 and less than 500 are appropriate for the most research. This study has gathered 123 potential respondents who getting loan from any finance institution as the target respondents in this study. In 123 respondents, there are 58 respondents who getting microfinance facilities from government agency; while 65 respondents are getting credit from non-government institution.
According to Cooper and Schindler (2006), data analysis is defined as the process of editing and reducing accumulated data to a size that is manageable, easy to look for patterns in, developing summaries and applying statistical techniques. Several analyses of the data have been carried out in the core of this study. Simple descriptive statistics such as sums, means, ranges, percentages and frequency distributions are were used to analysis primary data for this study. This study utilized the Statistical Package for Social Science (SPSS) to analyses the data. This study also conducted 3 multiple regression analysis for determining impacts of microfinance on 3 models such as household income, individual income and business income from all respondents, 58 respondents who getting microfinance facilities from government agency; and 65 respondents who getting credit from non-government institution. Hence, there will have three different analyses result that based on three dataset in order to reach to the research objective.
According to Burns and Bush (2003, p. 433), descriptive analysis is used to summarize and describe the sample characteristic of the typical respondent and disclosing the general pattern of response. Parametric statistic such as measures of mean, standard deviation and variance will be used to describe the key features of the interval data.
Multiple regression analysis is used to gain a better understanding about the relationship between several independent variables and a dependent variable. This technique is applicable in this study because the dependent variables in 3 model (household income, individual income and business income) and independent variable (total loan, loan tenure, education of borrowers, borrower’s age, business age, type of business, technical training and business course) are measure using the same scale. The weight of data is measured by the beta value is the indication to measure.
For the analysis of this paper, we suggest that each dependent variable are consist 1 model to evaluate the impacts of microfinance. Hence, the analysis is consisting 3 models where each model (household income, individual income and business income) is accounts for the expected effects of microfinance.
In this model, household income is representing the dependent variables. Household income of a respondent was measured in terms of his or her total monthly earning from business activities in which respondent was involved. This dependent variable was measured by taking into consideration all the existing family members’ (such as respondent, husband, son, daughter, father, mother) income of the respondent households. While, in this model there are 7 independent variables which are total loan, household size, business experience, loan tenure, technical training, borrower’s age and individual income. All independent variables will be further explained below. In brief, the model of impacts of microfinance on household income can be concluded as: Household Income = Total loan + Household size + Business Experience + Loan Tenure + Technical Training + Borrower’s Age + Individual Income
The model is measuring the impact of microfinance toward individual income, thus individual income was taken as the dependent variables in this model. Monthly individual income of a respondent was measured by his or her total monthly earning from business activities in which respondent was involved. The main different between household income and individual income is this variable was measured by respondents earning only and not taking into consideration all the existing family members’ (such as respondent, husband, son, daughter, father, mother) income of the respondent households. In this model there are 8 independent variables which are total loan, business income, loan tenure (monthly), education level, business experience, technical training, business course, marital status, gender and borrower’s age. In addition, all independent variables will be further explained below. In summary, the model of impacts of microfinance on individual income can be concluded as: Individual Income = Total loan + Loan tenure (monthly) + Education Level + Business Experience + Technical Training+ Business Course + Marital Status + Gender + Borrower’s Age
Business income is representing the dependent variables in this model in order to measure the impacts of microfinance. This variable was measured by taking into thesum of allmoney received by business, includingincome from revenue fromsales. It is measured by how much profit and money earned by respondents monthly. In this model there are 7 independent variables which are total loan, loan tenure (monthly), education level, business age, type of business, technical training and business course. All independent variables will be further explained below. In brief, the model of impacts of microfinance on business income can be concluded as: Business income = Total loan +Loan tenure (monthly) +Education Level + Business Experience + Type of Business + Technical Training+ Business Course
For the analysis of this paper, we suggest that there are several independent variables that used in multiple regressions. The independent variables in this research consist of total loan, loan tenure (monthly), education level, borrower age, business experience, type of business, technical training, business course, marital status and gender. All variables are accounts for the expected effects of microfinance. The independent variables are representing the causes that influenced the dependent variables and tested to see whether there are the causes.
The most influential independent variables in this research refer to the total amount loan. This variable are mostly influenced the result of analysis is due to it have a very strong figure in R-square. Furthermore, total amount of loan is the main independent variables that used to test on the effect of microfinance toward household income, individual income and household income. Consequently, others independent variables are consider as control variables. Additionally, this variable is defined as amount of loan received by the SMEs from any microfinance institution such as AIM, TEKUN, MARA, Bank Simpanan Nasional, SME Bank, Bank Rakyat and other institutions. It is measured by how much respondents received in term of ringgit Malaysia.
In order to support the main independent variables, loan tenure considers as another useful control variables in determining the effects of microfinance. Loan tenure was measured in term of how many months that a microfinance institution offered to respondents. Thus, this variable was calculated in term of months rather than years.
Refer back to the research, the education level of respondents was taken care and consider as an independent variables. Education variable was measured in terms of formal education acquired by the respondents. In this research, researcher was assigned respondents into two categories which are tertiary and non-tertiary. For example, if the respondent’s education level was above certificate, diploma or bachelor, they are fall into tertiary group. On the other hand, if the respondents are having an education level under certificate, diploma and bachelor, they are fall into non-tertiary group. In this study, non-tertiary group is recode as 1, while tertiary group as coded as dummy value.
Business experience are believed to have a slightly impact on the effect of microfinance, therefore it represent one of the independent variables. In this analysis, business age refer to experience of a respondents has been in the business. In this variables, we are calculated the experience of respondent’s business into the monthly.
Different type of business are expecting to influence the analysis, hence it is stand for another independent variables. In this research, types of business are grouping into two groups such as retail and non retail. Besides, there is a dummy value for no retail business, while retail will be recoded as 1 in this study.
Technical training refer to the training progamme that prepaid by microfinance institution to some of the business requirement. For example, AIM provides an technical training to an entrepreneur who wish to open a tailor shop. In this section, respondents was been question whether they have been send for a technical training or not. They are giving two option which are ‘Yes’ showing they went for a technical training or ‘No’ showing that they never go for a technical training. In order to run the multiple regressions, ‘Yes’ will be recode as 1, while ‘No’ recoded as 0.
Business course refer to the management progamme that offered by the microfinance institution. Business course are considering having small impact on the dependent variables. Thus, it is treated as independent variables in this analysis. Business course was measured in term of ‘Yes’ or ‘No’. ‘Yes’ are presenting the respondents attended business course that provide by microfinance institution, while No presenting the respondents attended business course. Besides, ‘Yes’ is recoded as 1 and ‘No’ is recoded as 0 in the analysis.
The size of household is used to measure the impacts of microfinance on household income. This variable was measured by taking into thesum of allexisting family members’ such as respondent, husband or wife, son, daughter, father, and mother. Besides, it is measured in term of unit such as 1, 2, and others.
The marital status is used to measure the impacts of microfinance on individual income. This variable was measured by categorized respondents into two groups which are married and single. In order to have an easier comparison between two groups, married was recorded as 1 and single was recorded as 0.
Refer back to the research, gender consider as another influential factors. Therefore, gender of respondents is taken under independent variables to test on individual income model. In addition, in this research male was recorded as 1 while female is recorded as 0.
Age of borrowers is measured in years. Borrowers age is included in the independent variables of household income and individual income. According to Su and Heshmati (2013), age of borrowers is one of factors to determine the level of household income and individual income.
In summary, three hypotheses can be specified as follows: H1: Microfinance has impact toward individual income. H2: Microfinance has impact toward household income. H3: Microfinance has impact toward business income.
Chapter 3 mainly discussed the types of research methodologies used to conduct the research study. Quantitative research is used in order to collect numerical and measurable data. Questionnaire will be conducted as to collect the primary data. Hypothesis regarding the effect of the various independent constructs were tested through analysis of survey data obtained from eligible SMEs respondents. Appropriate data analysis strategies were carried out to ensure accuracy of information gathering and analysis process. This study will include descriptive analysis, multicollinearity test and multiple regression analysis.
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