IMPACT OF ELECTRICITY TO BUSINESS AND NATIONAL DEVELOPMENT
Need help with a related project topic or New topic? Send Us Your Topic
DOWNLOAD THE COMPLETE PROJECT MATERIAL
IMPACT OF ELECTRICITY TO BUSINESS AND NATIONAL DEVELOPMENT
3.0 Introduction
This chapter examines how data for the research were acquired, the research method utilised in the study, the data collection techniques used and the target demographic, the sample size and sampling strategy, and the data analysis approach employed. Finally, it discusses the techniques and limits encountered in acquiring this evidence.
3.1 Research Design
Because of the nature of the variables at hand, the study employed a descriptive research design in order to provide data for quantitative analysis and to allow for the simultaneous description of views, perceptions, and beliefs at any given time (White, 2000).
To fulfil the proposed research aims of exposing the specific problems that SMEs face in their drive for growth and expansion in Nsukka, a quantitative research approach was used, which is frequently the most efficient and cost-effective research method (Gerhardt, 2004).
Many studies have examined the problems that SMEs face in their drive for growth in Nigeria. In light of this, a case study method was taken, focusing on SMEs in Nsukka, Enugu state.
3.2 Data Collection Techniques
Data for this study were acquired from both primary and secondary sources.
3.2.1 Primary Data
This study’s principal data sources included the use of a questionnaire. Copies of the structured questionnaire were provided to SMEs and/or owners to gather first-hand information for use in answering the research questions. The questionnaire was organised into three sections. Section A focused on the respondents’ firms, such as: Age of the firm.
Form of ownership Nature of the firm
The average monthly turnover of the firm
These assisted us in determining the type of SME that we were working with, whether they were Micro, Small, or Medium enterprises as defined in (Aryeetey et al., 1994) research work.
Section B of the questionnaire included a variety of questions aimed at determining the study’s objective. These questions investigated the impact of intermittent power supply on SME profitability.
The third portion examined how SMEs intend to tackle the high cost of manufacturing that is making them uncompetitive versus competitors that do not face the irregular power supply, as well as what they are doing to overcome these issues in order to achieve growth and expansion into new markets.
3.2.2 Secondary Data
The secondary data were gathered by reviewing journals and publications related to the topic of this research. Newspaper sources and official policy documents from the Nigerian government on the matter were also consulted. The electronic search portal www.google.com was extensively used to find up-to-date materials on the subject.
The primary data comprised the crux of this study because it provided the opportunity to acquire firsthand and relevant responses.
3.3 Sampling Framework and Techniques
The study’s sampling frame comprised all of Nsukka’s SMEs (2000 in total). The research sample size was 80, which included both SMEs who suffer from unpredictable power supply and those that do not due to backup power.
This allowed the researchers to track the effect of profitability on the expansion of SMEs. We issued 80 surveys to these SMEs and obtained replies from them.
65 responders, accounting for around 81% of the response rate, which we considered to be impressive for this study.
The study employed a simple random sampling methodology, which is a probability sampling method that selects a subset of a population so that each member has an equal chance of being chosen.
In other words, in a random sample, all possible samples of a fixed size have the same chance of being chosen; thus, the basic random sample provides us with a sample that is highly representative of the population under study.
A random sample is impartial in the sense that no member of the population has a higher chance of being chosen than any other. Because the units chosen for inclusion in the sample are picked using probabilistic methods, simple random sampling enables us to generalise (i.e., draw statistical conclusions) from the sample to the population.
Need help with a related project topic or New topic? Send Us Your Topic