CHAPTER THREE - RESEARCH METHODOLOGY
3.1 RESEARCH DESIGN
Research design or research methodology is researcher's plan of action about the study. The plan embodies strategies and techniques through which a research on a particular subject matter is conducted. It is the specification of procedures used in collecting and analyzing data necessary to help solve the problem at hand, (Donald 1980). A research is the application of scientific method to the study of a problem. It is a way to acquire dependable and useful information. Its purpose is to discover answers to meaningful questions through the application of scientific approach. The descriptive research design was used. The method enables the researcher to obtain a clear understanding in the behaviour of his object of study due to certain changes in some aspects of the object's environment. This type of design is mostly convenient for the management science studies.
3.2POPULATION OF STUDY
The target population of this study are employees, management and visiting personnel of the bank (Access Bank Plc, Okpara Avenue Enugu). As at September 3, 2011, the total number of staff and visiting personnel in the bank was Eighty (80). Thus the eighty employees and visiting personnel constituted the population for the research.
3.3 SAMPLE AND SAMPLING TECHNIQUES
A portion of element taken from the large population is called sample. Sampling is taking or drawing of any portion or element from the large population or universe (Osuala, 1993: 104). Various sampling techniques were available to the researcher for use in the selection of sub-group that will represent a population. These techniques include simple random sampling, multi-stage sampling, cluster sampling and systematic sampling among others. Since the use any of the sampling techniques depends on the defined population and the representation of the sample in the population, the researcher used the random sampling technique. As a result of limitations of time and money needed to cover the whole population, some forms of sampling became necessary. In determining the sample size, the researcher quoting Mmadu (1997: 50) applied the Yaro Yamani's statistical formula for selecting from a finite population.
The formula is stated as
n = N
1 + N(e) 2
Where
N = The entire population
e = Co-efficient of confident or margin of error
n =Sample size
The researcher is of the view that 5% or 0.05 is an appropriate margin of error for the study.
Given N = 80 and e = 0.05
80
n = 1 + 80(0.05) 2
n = 80
1 + 0.2
41 = 80
1.2 = 67
67 = sample size
Thus, since n is 67, therefore, 67 employees constituted the sample size for the project.
3.4 SOURCES AND METHODS OF DATA COLLECTION
There are various sources of data collection for a research purpose. The widely known sources of data collection are primary and secondary sources though with certain degree of variability. The sources of data collection, are discussed further in the following headings.
1. Primary Data
Primary source of data refers to the statistical materials which the researcher originated for the purpose of the enquiry at hand. In other words, primary data consists of information and data collected personally by the researcher for identifying and solving of the problem at hand; the primary data for this study was collected personally through the following methods.
a) Administering of questionnaires which were structurally and carefully formulated to the staff, management and personnel. The researcher guided the respondents on how the questionnaires should be answered.
b) Through the use of oral interview; the researcher personally interviewed the staff, management and personnel of the bank.
c) Also, through what the researcher observed on her own during the field work.
2. Secondary Data
The secondary sources of data according to (Chinall, 1973:26); "are the existing information which may be of relevance to the specific survey at hand". The secondary sources of data for this study include; relevant journals, internet websites, documented files, written projects, textbooks and other useful publications. These data served as good sources of reliable information to the researcher
3.5 DATA RELIABILITY AND VALIDITY
Reliability has been defined by Pilot and Hungler (1993) as the level of consistency with which an instrument measures the attribute it is intended to measure. The researcher constructed questionnaire to measure the impact of corporate planning on organizational performance. In order to ensure face and content validity of the instrument, it was presented to the supervisor and necessary modifications were made based on his advice. On the other hand, validity according to Nnamani (2008: 42) is the degree to which a test measures what it is supposed to measure. A test is said not to be valid per se; it must be valid for a particular purpose and for a particular group. The question should not be whether a test is valid or not. It should instead be whether at test is valid for what and for whom. In this content, the validation of the work was conducted through direct administration validation. This was done by the researcher to ensure that questionnaires cover the topic as well as topic related to it.
3.6 METHOD OF DATA ANALYSIS
Data analytical techniques are various techniques used in analyzing and interpreting the data collected for research purpose. Most of the techniques used today for data presentation and analysis are statistical. Some of these techniques in use are poison distribution, frequency distribution, simple linear regression, exponential, percentages, correlation and chi-square etc. For the presentation and analysis of this research work, simple percentage would be used but for testing the hypothesis, as well chi-square was used. The formula for the Liker Scale
•fxn
•fx = Weighted sum of frequencies
n =Total response
The mean of point scale = •xn
X =sum of norminal value
n =Number of response categories
the cutoff = mean x e 45
where e = error term = 0.05
Chi-square was used to test hypothesis formulated X = • (oi - ei)
where
oi = observed frequency
ei = expected frequencies
the degree of freedom = (r - 1) (k - 1)
where
r = Numbr of roles
K = Number of columns
X = Chi-square 2
Xe = 0.05 = Critical value of chi-square.