CHAPTER THREE Sample – A sample Research methodology Chapter 3

CHAPTER THREE

RESEARCH METHODOLOGY

3.1 Introduction

It is standard practice in research for researchers to specify the methods they used to achieve their study objectives. Thus, this chapter presents the methodology adopted in this study in order to achieve the study objectives and provide answers to the research questions. Specifically, this section explains the research design, the population of the study, the study model, the sources of data, and the method for analyzing the data, among other things.

3.2 Research Design

The general framework or strategy that logically merges the diverse components of a study in a coherent manner and is often adopted by a researcher in order to ensure that the research problems are effectively addressed is known as a research design (Myers et al., 2013). In the view of Marczyk et al. (2010), a research design contains the plan for measurement, collection, and analysis of data. In this study, a quantitative study design was adopted. A quantitative research design stresses objective measurement and the numerical, mathematical, and statistical analysis of data (Apuke, 2017). A quantitative design is considered appropriate for this study because it provides a statistical answer to the research questions.

3.3 Population of Study

A population is the total number of entities that are of interest to a researcher (Crane et al., 2017). The population of this study is made up of listed IT firms in the UK and Europe. According to Nasdaq (2022), there are 3 listed UK-based IT firms and 16 European-based IT firms. This makes the total population of the study 19 IT firms. However, the three IT listed firms in the UK will be considered. This includes Atlassian Corporation Plc Class, Mimecast Limited, and GAN Limited. The selected European IT firms include ASML Holding N.V., Seagate Technology Holding Plc., and Ericsson. The financial statements of the IT firms in the UK from 2018 to 2021 will be analyzed in order to get the financial performance data of the studied firms. Also, the demographic compositions of the selected IT firms will be investigated to determine their gender diversity.

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3.4 Model Specification

The model developed for this study specifies the financial performance of selected IT firms (profitability) as a function of gender diversity. The functional representation of the study model is presented thus:

ROA= F (GD) ………………………………………………. (1)

Where;

ROA = Return on Asset

GD = Gender diversity

However, the functional model presented in equation (1) can be transformed into an econometric model for the estimation of the relationship between the variables. The econometrically transformed model is presented below:

ROAt = β0 + β1GDt + ðt

Where;

β0 = intercept

β1 = Coefficient of Gender Diversity

ðt = Error term

3.5 Variables Measurement and Description

Return on Asset (ROA)

The ROA is a monetary ratio that signals the profitability of a firm in relation to its total assets (Almira et al., 2020). Based on this definition, the ROA, which is also a measure of the financial performance of a firm, is measured by dividing the monetary value of net income by total assets. This is consistent with the study by Polina (2017), who investigated the impact of board diversity on corporate financial performance. The formula is expressed thus:

Gender Diversity

Gender diversity refers to the fair or equal representation of individuals of diverse genders in a group (Reddy and Jadhav, 2019). It is commonly described as an equal ratio of women and men. The gender diversity of boards in this study is measured by dividing the number of females in managerial and administrative positions by the total number of board members. The formula is specified thus,

3.6 Source of Data

This study is exclusively dependent on secondary sources of information. Since the study design adopted in this study is quantitative, secondary sources of quantitative data on the study variable were used in gathering relevant information. Specifically, the major source of data for the study was the annual financial report of the selected IT firms. The financial statements of these firms were gotten from the Nasdaq website, which is one of the sites where listed companies’ financial activities are documented. Each IT firm’s data was analyzed over a period of four years (from 2018 to 2021). Also, some information on the composition of the selected IT firms was obtained from the websites of those firms.

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3.7 Method of Data Analysis

The quantitative method of analysis was adopted in this study. The data analysis begins with descriptive statistics of the study variable. A descriptive method of analysis was also used to analyze the extent to which women are given managerial and administrative roles in IT firms in the UK and to compare the extent of board gender diversity between the UK and Europe. Also, a correlation and regression analysis were used in this study to assess the impact of board gender diversity on the financial performance of the selected listed IT firms in the UK. Specifically, this study adopted a pooled balance panel data regression. This was to ensure completeness of data and simplicity of study analysis. Data analysis was done using the EViews statistical software version

References

Almira, N.P.A.K. and Wiagustini, N.L.P., (2020). Return on asset, return on equity, dan earning per share berpengaruh terhadap return saham. E-Jurnal Manajemen9(3), pp.1069-1088. [Online] Available at: https://pdfs.semanticscholar.org/3066/9c80597a2d8f3125bf97837e6498d44b07b9.pdf [Accessed: 6 March, 2022].

Apuke, O.D., (2017). Quantitative research methods: A synopsis approach. Kuwait Chapter of Arabian Journal of Business and Management Review33(5471), pp.1-8. [Online] Available at: https://www.proquest.com/openview/058c84ecfd436cf965eacb1556000ab0/1?pq-origsite=gscholar&cbl=2042228 [Accessed: 6 March, 2022].

Crane, A., Henriques, I., Husted, B.W. and Matten, D., (2017). Measuring corporate social responsibility and impact: Enhancing quantitative research design and methods in business and society research. Business & Society56(6), pp.787-795. [Online] Available at: https://journals.sagepub.com/doi/full/10.1177/0007650317713267 [Accessed: 6 March, 2022].

Marczyk, G.R., DeMatteo, D. and Festinger, D. (2010) “Essentials of research design and methodology” (Vol. 2). John Wiley & Sons 12 pp.25-39 [Online] Available at: http://dspace.vnbrims.org:13000/xmlui/bitstream/handle/123456789/4650/Essentials%20of%20Research%20Design%20and%20Methodology%202005.pdf?sequence=1&isAllowed=y [Accessed: 6 March, 2022].

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Myers, J.L., Well, A.D. and Lorch Jr, R.F. (2013) “Research design and statistical analysis”. Routledge 53 pp.202-214 [Online] Available at: https://doi.org/10.4324/9780203726631 [Accessed: 7 March, 2022].

Nasdaq (2022) “Stock Screener” [Online] Available at: https://www.nasdaq.com/market-activity/stocks/screener [Accessed: 8 February, 2022].

Polina, T. (2017) “The Impact of Board of Directors Diversity Upon Corporate Financial Performance” Business ethics: A European review, 16(4) pp.344-357 [Online] Available at: https://dspace.spbu.ru/bitstream/11701/9533/7/reviewSV_Tingli_P__mag_rec.pdf [Accessed: 20 February, 2022].

Reddy, S. and Jadhav, A.M., (2019). Gender diversity in boardrooms–A literature review. Cogent Economics & Finance7(1), p.1644703. [Online] Available at: https://www.tandfonline.com/doi/full/10.1080/23322039.2019.1644703[Accessed: 6 March, 2022].



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