The changing impact of the government directive on board diversity to enhance corporate performance – a critical evaluation for the UK corporate sectors
Question
The changing impact of the government directive on board diversity to enhance
corporate performance – a critical evaluation for the UK corporate sectors
Aim : ?
Objectives : ?
RQs : ?
Research Rational: ?
For this topic , in case this is doable ?
Module Learning Outcomes
On successful completion of the module, In relation to the
Subject-Specific Knowledge, Understanding & Application
a) Describe and evaluate the purpose of applied research for strategic
decision-making, in the context of own choice of business and management research
topic.
b) Critically evaluate research project design and implementation, including
organisation/ sector context, research question formulation, ethical and methodological
considerations.
c) Select, evaluate and synthesise sources of information associated with a business or
management topic.
d) Appraise and apply a recognised method of analysis to secondary information.
e) Propose recommendations that demonstrate an entrepreneurial mind-set, and that
consider stakeholder impact, sustainability, and value.
Employability & Changemaker Skills
f) Critically reflect upon preferences and experiences in the context of
personal, professional and career development.
g) Demonstrate self-direction and originality in tackling and solving problems, and act
autonomously in planning and implementing tasks.
h) Structure and communicate a coherent and sustained argument
INDICATIVE CONTENT:
• Theoretical perspectives on applied research for strategic management
• Practical approaches to research design
• Ethical and methodological dimensions of applied research
• Devising research questions/hypotheses
• Sources of secondary information and data; secondary data, research
• literature, grey literature, documents
• Selecting, evaluating, analysing and synthesising information
• Proposing, costing and planning recommendations
• Writing skills for different audiences; the long form feature article
• Creating a video proposal
I need help with stated assignment . The assignment is in two parts
MUST submit an article (4,000 words) and a portfolio (4,500 words) excluding
appendices, footnotes, marking sheet, ethics clearance form, table of contents, and
cover page. See the required format/content for article and portfolio as well as the
marking rubric for the article and portfolio for more details. Students MUST engage with
their groups and supervisors as soon as they assigned to them.
Answers ( 2 )
THE CHANGING IMPACT OF THE GOVERNMENT DIRECTIVE ON THE BOARD DIVERSITY TO ENHANCE
CORPORATE PERFORMANCE – A CRITICAL EVALUATION FOR THE UK CORPORATE SECTORS
ABSTRACT
In the methodology chapter, the deductive approach has been followed. The researchers in this aspect have
used positivism philosophy. The researchers follow secondary quantitative data for the research. Thus, they
have to conduct statistical analysis to evaluate the statistical significance of the research.
In the data analysis, results and discussion chapter, secondary qualitative data has been used to conduct
statistical analysis based on turnover percentage in different sectors and the overall turnover in the financial
year 2015. SPSS has been used to conduct the data analysis for evaluating corporate performance.
Descriptive statistics and regression analysis have been conducted in this aspect.
Table of Contents
Portfolio: Research Methodology, Design, and Methods
Introduction
Research methodology is an essential chapter as it outlines the major methods that have been used for
research work. The expected outcomes of the study can be reached properly by using the right methodology.
The process of data collection and its analysis have been detailed in this section. The important ethics
followed in the research work are also presented in this section.
Research philosophy
The research philosophy enables the researcher to conduct the research in the proper direction. The
philosophies used in the research process include”realism, interpretivism and positivism”. In this research, the
“positivism philosophy” has been used by the researchers for analyzing the major factors quantitatively
(Bairagi and Munot, 2019). The philosophy has been appropriate for the study as it supports the different
dimensions of research, and the outcomes are based on the proper data analysis. In this case, the
researchers collected the dataset relevant to the research process and focused on the quantitative outcomes.
Research approach
Figure 1: Research approach
The research approach is important for the research purpose as it helps the researchers support the data
retrieved for supporting the objective of the research. The used approaches include the “inductive research
approach” and “deductive research approach”. The researchers have considered using the “deductive
approach” as suitable. The deductive approach allows for developing conclusive evidence considering the
aim and objectives. The approach also supports different theories for delivering positive outcomes (Machado
and Davim, 2020). The research aims for determining the changing impact of the government directive on
board diversity for enhancing corporate performance Therefore the quantitative data requires prior analysis
board diversity for enhancing corporate performance. Therefore, the quantitative data requires prior analysis
and theories to support the research work in this context. Thus, the deductive approach has been suitable for
the researchers in terms of supporting the research.
Research design
Figure 2: Research design
The research work needs to be conducted in a systematic method that can help in evaluating the positive
outcomes. In this context, the right protocol needs to be selected for meeting the aims and objectives.
Selection of the right research design in this aspect is crucial. The overall outcomes of the study and its
effectiveness are dependent on the research design. The research designs that are available for research are
“exploratory design, explanatory design and descriptive design”. The researchers have followed a “descriptive
research design” as per the requirement of the study. The descriptive research design is rich and
supportsrting the various factual aspects (Novikov and Novikov, 2019). The analysis of the topic can be done
by considering the various perspectives, and outcomes can be managed accordingly.
Data sources and types
The data sources used for the research include the “primary and the secondary data”. The data types include
the “qualitative” and the “quantitative data”. In this research work, the “secondary quantitative data”. The
“secondary data” consists of the previously published information, and the data is extracted for the research
analysis (Ledford and Gast, 2018). The process is effective for evaluating the existing factors supporting the
research work. “Quantitative data”, including numerical data, are collected for the research work. Statistical
data has been collected for the research purpose from reliable sources that helped meet the research
objectives (gov.uk, 2021). All the collected statistical data are related to the UK sectors and their
performances in the past years.
Population and sampling
The population of the research needs to be selected properly to meet the research requirements. The sample
is included from the selected population. The population in this aspect which is selected, includes a dataset
of the UK corporate sectors. The research has a follower secondary quantitative process, and a “random
sampling technique” has been used in this research. A random dataset has been selected from the identified
segment of datasets for the research work. The sampling technique has been the most effective in
maintaining the quality of research. The sample size of the research includes a dataset of the total turnover of
the UK sectors for FY 2015. The dataset also includes the percentages generated by the individual sectors for
each individual year.
Data collection process
The overall research outcomes have reliability on the data collection procedures. The data collection process
has been evaluated to have a connection with the sampling process. The research includes using the
secondary “quantitative data” that have led to the conduction of the statistical analysis (Bairagi and Munot,
2019). In this case, the appropriate dataset has been selected from the authentication platform to maintain
the research’s integrity. This helped in delivering the quality outcomes meeting the aim of the research. The
dataset which is selected is relevant to the research topic. Furthermore, it has been ensured by the
researchers that the dataset selected includes the right information and is from the latest source.
Data analysis
The data collected for the research purpose requires proper analysis to meet the research questions. Thus, it
is necessary to develop an analysis plan that allows the researchers for proper analysis. The research
includes a data analysis plan relevant to the data sources. In case of the “secondary quantitative data
analysis”, statistical analysis has been performed in the dataset (Machado and Davim, 2020). The data
analysis tool issued for the research is “SPSS”, which has helped perform the calculations. The dataset
samples that have been selected have been imported into the SPSS windows, and analyses have been
conducted. The different SPSS statistical functions have been used in this aspect to evaluate the results’
effectiveness. Descriptive and regression analyses have been performed on the dataset to ensure that
outcomes successfully meet the research aim.
Ethical consideration
The professional followed all the important ethics while conducting the research work. Following the ethics in
research has helped sustain the integrity of the outcomes. In case of “secondary quantitative research”, the
dataset, including the statistics of the UK sectors, have been collected by the researchers. Proper
acknowledgements of the authorities have been given in the research work (Novikovand Novikov, 2019). In
selecting the dataset, it has been ensured that the platforms are authentic. The collected dataset has been
used for the research work only, and it was deleted after research work. The research dataset had limited
accessibility for maintaining the privacy of data. Only the research professionals had access to the dataset.
No values within the dataset have been manipulated and used in research work.
Summary
All the important methods followed in research work are outlined in this section. The approach, philosophy,
design and other research factors have been discussed. The discussions about the selection of data for
research and its relevant analysis have also been done. “Secondary quantitative analysis” has been
performed, including statistical analysis on the dataset. A sample dataset including the data of the turnover
of the different sectors in the UK has been considered for the analysis purpose. The important ethics that are
followed for maintaining data integrity are also provided in this section.
Portfolio: Data Analysis, Results, and Discussion
Introduction
In this chapter, “statistical analysis” has been conducted as “secondary quantitative research”. In the present
scenario, a detailed evaluation of the “corporate performance” of the UK corporate sector will be done. The
researchers conducted “descriptive statistics” and “regression analysis” to evaluate the relationship between
the variables. SPSS is used to conduct the “statistical analysis”.
Analysis of secondary quantitative data
The research is conducted by analyzing the “corporate performance” of different sectors of the UK. In the
present scenario, the overall “turnover” generated by different sectors till 2015 has been evaluated. The
“corporate performance” includes market performance, shareholder performance and financial performance
(Ntim et al. 2015). In this aspect, the “statistical analysis” has been conducted based on the “financial
performance” of the banking sector, manufacturing sector, fund management sector, telecom sector and
utility sector. Based on different variables, “descriptive statistics” and “regression analysis” has been
conducted to evaluate the “statistical significance” of the research. The overall “turnover” of the corporate
sectors can be evaluated in this aspect.
Figure 3: Year wise performance
(Source: Self-developed)
The targeted industry in the current scenario is the banking sector. The graph presents the year wise turnover
for the financial year 2006 to 2015. Before the government directive, the industry performance was not
improving. It can be observed from the graph that the banking industry turnover was 47 on an average. The
industry was lacking a governance structure that can help in making decisions and forming strategies. No
proper implementation of rules and regulations were present that have affected the daily operations.
Implementation of the government directive led to improved turnover during the financial years 2014 and
2015. The turnover in the financial years 2014 and 2015 was 48 and 50. Therefore, an increasing trend in the
turnover has been observed with the implementation of the government directive. The government directive
has brought in new structure and regulations that have helped in improving the business process (Homan et
al. 2020).
Descriptive statistics between “percentage of sector turnover” in 2006 and total turnover
Table 2: Descriptive Statistics
Based on the “descriptive statistics”, it is determined that the “mean value” and “standard deviation” of
“turnover percentage in 2008” are 49.63 and 25.65, respectively. On the other hand, the “mean value” and
“standard deviation” of “overall turnover” is 174.17 and 212.02, respectively. In this aspect, the “variances” of
the variables can be evaluated. The variances are calculated as 658.005 and 44956.429, respectively. The
corporate performance in the broad market of the country can be determined by statistical analysis.
Regression analysis between turnover percentage in 2015 and overall turnover
Table 3: Descriptive Statistics
A detailed estimation of the relationship between “dependent variables” and “independent variables” can be
done by regression analysis. In this research, the “average value” of “turnover percentage” and “overall
turnover” can be determined. The averages are detected as 48.36 and 174.17, respectively. A brief analysis of
“standard deviation” is also done to ensure the research’s “statistical significance”. It indicates that the
monetary performance of the banking sector and retail sector is satisfactory for the country (Kiel and
Nicholson, 2016). The researchers can also make relevant decisions based on the “financial analysis”.
Table 4: Correlation
The “correlation analysis” between the variables has been conducted to identify the relationship between
“turnover percentage” and “overall turnover” in 2015. The researchers can also meet the “objectives” of the
research by conducting “correlation analysis”. In this case, the “turnover percentage” is considered as a
“dependent variable”, and “overall turnover” is considered as an “independent variable”. The analysis identified
“Pearson correlations” between the variables as 1 and 0.07, respectively. It signifies that there is no “statistical
relationship” between the variables. Thus, the corporate sector management has to take the necessary steps
to cope with the changing impact of “government directive on board diversity”.
Table 5: Model Summary
In the “model summary”, it is detected that the “standard error” and “R square change” are 24.45 and 0.005,
respectively. The researchers can identify the “F change” as 0.171. In this aspect, the researchers can
evaluate the overall performance of the corporate sectors. The “statistical analysis” evaluates that the “fund
management sector” and “trust funds” generate less turnover than the other sectors. It reflects on the
“turnover percentage” from the financial year 2006 to 2015. The “model summary” also evaluates the
significance of the statistical method conducted in this research (Cui and Hu, 2018).
Table 6: ANOVA
The researchers conducted the “ANOVA test” to determine the variability in the “data set”. The “mean square”
and “sig value” have been identified in this aspect. The “mean square” of the two variables is 102.41 and
598.06, respectively. As the “sig value” is greater than 0.05, the “null hypothesis” has been rejected in this
“statistical analysis”. It also ensures the “statistical significance” of this research. Based on the analysis, it is
also determined that the organizational management can make relevant decisions regarding “board diversity”
to improve the “corporate performance” of the sectors situated in the UK (Riyadh, Sukoharsono and Alfaiza,
2019).
Coefficientsa
Table 7: Coefficient
It is necessary for the researchers to meet the “research objectives” to ensure the significance of the study.
For this purpose, the researchers can evaluate the steps taken by the government for implementing “board
diversity” in the corporate sectors of the country. “Coefficient analysis” is conducted in this aspect for
determining the “standard error” and “beta”. However, a negative “T-value” is reflected in the statistical
analysis. The “sig value” of 0.682 ensures a “statistical significance” in this study. The government can take
crucial steps to enhance this sector’s overall turnover.
Regression analysis between turnover percentage in 2007 and 2008
Table 8: Descriptive statistics
The “average value” of “turnover percentage” in 2007 and 2008 are 49.34 and 49.63, respectively. In the
“descriptive analysis”, the researchers evaluated the ” standard deviation “. It also measures the “central
tendency” and “viability” in statistical analysis. The researchers can also identify the thoughts of the corporate
sector regarding the diversification of the board. The corporate health of different sectors in the UK can be
evaluated in this aspect. It also improves these sectors’ “shareholder performance” (Crowther, Davies and
Cooper, 2018). It indicates that the monetary performance of the banking sector and retail sector meets the
organizational standard of the country.
Correlations
Table 9: Correlation
The “correlation analysis” between the two variables has been conducted to evaluate the relationship between
“turnover percentage” in 2007 and 2008. The “Pearson correlations” between the variables are identified as 1
and 0.98, respectively. It also detects that there is a “significant relation” between the “dependent variable” and
“independent variable”. The “correlation analysis” also identifies that there is a “statistical significance”
detected in conducting the “statistical analysis”.
THE CHANGING IMPACT OF THE GOVERNMENT DIRECTIVE ON THE BOARD DIVERSITY TO ENHANCE
CORPORATE PERFORMANCE – A CRITICAL EVALUATION FOR THE UK CORPORATE SECTORS
ABSTRACT
In the methodology chapter, the deductive approach has been followed. The researchers in this aspect have
used positivism philosophy. The researchers follow secondary quantitative data for the research. Thus, they
have to conduct statistical analysis to evaluate the statistical significance of the research.
In the data analysis, results and discussion chapter, secondary qualitative data has been used to conduct
statistical analysis based on turnover percentage in different sectors and the overall turnover in the financial
year 2015. SPSS has been used to conduct the data analysis for evaluating corporate performance.
Descriptive statistics and regression analysis have been conducted in this aspect.
Table of Contents
Portfolio: Research Methodology, Design, and Methods
Introduction
Research methodology is an essential chapter as it outlines the major methods that have been used for
research work. The expected outcomes of the study can be reached properly by using the right methodology.
The process of data collection and its analysis have been detailed in this section. The important ethics
followed in the research work are also presented in this section.
Research philosophy
The research philosophy enables the researcher to conduct the research in the proper direction. The
philosophies used in the research process include”realism, interpretivism and positivism”. In this research, the
“positivism philosophy” has been used by the researchers for analyzing the major factors quantitatively
(Bairagi and Munot, 2019). The philosophy has been appropriate for the study as it supports the different
dimensions of research, and the outcomes are based on the proper data analysis. In this case, the
researchers collected the dataset relevant to the research process and focused on the quantitative outcomes.
Research approach
Figure 1: Research approach
The research approach is important for the research purpose as it helps the researchers support the data
retrieved for supporting the objective of the research. The used approaches include the “inductive research
approach” and “deductive research approach”. The researchers have considered using the “deductive
approach” as suitable. The deductive approach allows for developing conclusive evidence considering the
aim and objectives. The approach also supports different theories for delivering positive outcomes (Machado
and Davim, 2020). The research aims for determining the changing impact of the government directive on
board diversity for enhancing corporate performance Therefore the quantitative data requires prior analysis
board diversity for enhancing corporate performance. Therefore, the quantitative data requires prior analysis
and theories to support the research work in this context. Thus, the deductive approach has been suitable for
the researchers in terms of supporting the research.
Research design
Figure 2: Research design
The research work needs to be conducted in a systematic method that can help in evaluating the positive
outcomes. In this context, the right protocol needs to be selected for meeting the aims and objectives.
Selection of the right research design in this aspect is crucial. The overall outcomes of the study and its
effectiveness are dependent on the research design. The research designs that are available for research are
“exploratory design, explanatory design and descriptive design”. The researchers have followed a “descriptive
research design” as per the requirement of the study. The descriptive research design is rich and
supportsrting the various factual aspects (Novikov and Novikov, 2019). The analysis of the topic can be done
by considering the various perspectives, and outcomes can be managed accordingly.
Data sources and types
The data sources used for the research include the “primary and the secondary data”. The data types include
the “qualitative” and the “quantitative data”. In this research work, the “secondary quantitative data”. The
“secondary data” consists of the previously published information, and the data is extracted for the research
analysis (Ledford and Gast, 2018). The process is effective for evaluating the existing factors supporting the
research work. “Quantitative data”, including numerical data, are collected for the research work. Statistical
data has been collected for the research purpose from reliable sources that helped meet the research
objectives (gov.uk, 2021). All the collected statistical data are related to the UK sectors and their
performances in the past years.
Population and sampling
The population of the research needs to be selected properly to meet the research requirements. The sample
is included from the selected population. The population in this aspect which is selected, includes a dataset
of the UK corporate sectors. The research has a follower secondary quantitative process, and a “random
sampling technique” has been used in this research. A random dataset has been selected from the identified
segment of datasets for the research work. The sampling technique has been the most effective in
maintaining the quality of research. The sample size of the research includes a dataset of the total turnover of
the UK sectors for FY 2015. The dataset also includes the percentages generated by the individual sectors for
each individual year.
Data collection process
The overall research outcomes have reliability on the data collection procedures. The data collection process
has been evaluated to have a connection with the sampling process. The research includes using the
secondary “quantitative data” that have led to the conduction of the statistical analysis (Bairagi and Munot,
2019). In this case, the appropriate dataset has been selected from the authentication platform to maintain
the research’s integrity. This helped in delivering the quality outcomes meeting the aim of the research. The
dataset which is selected is relevant to the research topic. Furthermore, it has been ensured by the
researchers that the dataset selected includes the right information and is from the latest source.
Data analysis
The data collected for the research purpose requires proper analysis to meet the research questions. Thus, it
is necessary to develop an analysis plan that allows the researchers for proper analysis. The research
includes a data analysis plan relevant to the data sources. In case of the “secondary quantitative data
analysis”, statistical analysis has been performed in the dataset (Machado and Davim, 2020). The data
analysis tool issued for the research is “SPSS”, which has helped perform the calculations. The dataset
samples that have been selected have been imported into the SPSS windows, and analyses have been
conducted. The different SPSS statistical functions have been used in this aspect to evaluate the results’
effectiveness. Descriptive and regression analyses have been performed on the dataset to ensure that
outcomes successfully meet the research aim.
Ethical consideration
The professional followed all the important ethics while conducting the research work. Following the ethics in
research has helped sustain the integrity of the outcomes. In case of “secondary quantitative research”, the
dataset, including the statistics of the UK sectors, have been collected by the researchers. Proper
acknowledgements of the authorities have been given in the research work (Novikovand Novikov, 2019). In
selecting the dataset, it has been ensured that the platforms are authentic. The collected dataset has been
used for the research work only, and it was deleted after research work. The research dataset had limited
accessibility for maintaining the privacy of data. Only the research professionals had access to the dataset.
No values within the dataset have been manipulated and used in research work.
Summary
All the important methods followed in research work are outlined in this section. The approach, philosophy,
design and other research factors have been discussed. The discussions about the selection of data for
research and its relevant analysis have also been done. “Secondary quantitative analysis” has been
performed, including statistical analysis on the dataset. A sample dataset including the data of the turnover
of the different sectors in the UK has been considered for the analysis purpose. The important ethics that are
followed for maintaining data integrity are also provided in this section.
Portfolio: Data Analysis, Results, and Discussion
Introduction
In this chapter, “statistical analysis” has been conducted as “secondary quantitative research”. In the present
scenario, a detailed evaluation of the “corporate performance” of the UK corporate sector will be done. The
researchers conducted “descriptive statistics” and “regression analysis” to evaluate the relationship between
the variables. SPSS is used to conduct the “statistical analysis”.
Analysis of secondary quantitative data
The research is conducted by analyzing the “corporate performance” of different sectors of the UK. In the
present scenario, the overall “turnover” generated by different sectors till 2015 has been evaluated. The
“corporate performance” includes market performance, shareholder performance and financial performance
(Ntim et al. 2015). In this aspect, the “statistical analysis” has been conducted based on the “financial
performance” of the banking sector, manufacturing sector, fund management sector, telecom sector and
utility sector. Based on different variables, “descriptive statistics” and “regression analysis” has been
conducted to evaluate the “statistical significance” of the research. The overall “turnover” of the corporate
sectors can be evaluated in this aspect.
Figure 3: Year wise performance
(Source: Self-developed)
The targeted industry in the current scenario is the banking sector. The graph presents the year wise turnover
for the financial year 2006 to 2015. Before the government directive, the industry performance was not
improving. It can be observed from the graph that the banking industry turnover was 47 on an average. The
industry was lacking a governance structure that can help in making decisions and forming strategies. No
proper implementation of rules and regulations were present that have affected the daily operations.
Implementation of the government directive led to improved turnover during the financial years 2014 and
2015. The turnover in the financial years 2014 and 2015 was 48 and 50. Therefore, an increasing trend in the
turnover has been observed with the implementation of the government directive. The government directive
has brought in new structure and regulations that have helped in improving the business process (Homan et
al. 2020).
Descriptive statistics between “percentage of sector turnover” in 2006 and total turnover
Table 2: Descriptive Statistics
Based on the “descriptive statistics”, it is determined that the “mean value” and “standard deviation” of
“turnover percentage in 2008” are 49.63 and 25.65, respectively. On the other hand, the “mean value” and
“standard deviation” of “overall turnover” is 174.17 and 212.02, respectively. In this aspect, the “variances” of
the variables can be evaluated. The variances are calculated as 658.005 and 44956.429, respectively. The
corporate performance in the broad market of the country can be determined by statistical analysis.
Regression analysis between turnover percentage in 2015 and overall turnover
Table 3: Descriptive Statistics
A detailed estimation of the relationship between “dependent variables” and “independent variables” can be
done by regression analysis. In this research, the “average value” of “turnover percentage” and “overall
turnover” can be determined. The averages are detected as 48.36 and 174.17, respectively. A brief analysis of
“standard deviation” is also done to ensure the research’s “statistical significance”. It indicates that the
monetary performance of the banking sector and retail sector is satisfactory for the country (Kiel and
Nicholson, 2016). The researchers can also make relevant decisions based on the “financial analysis”.
Table 4: Correlation
The “correlation analysis” between the variables has been conducted to identify the relationship between
“turnover percentage” and “overall turnover” in 2015. The researchers can also meet the “objectives” of the
research by conducting “correlation analysis”. In this case, the “turnover percentage” is considered as a
“dependent variable”, and “overall turnover” is considered as an “independent variable”. The analysis identified
“Pearson correlations” between the variables as 1 and 0.07, respectively. It signifies that there is no “statistical
relationship” between the variables. Thus, the corporate sector management has to take the necessary steps
to cope with the changing impact of “government directive on board diversity”.
Table 5: Model Summary
In the “model summary”, it is detected that the “standard error” and “R square change” are 24.45 and 0.005,
respectively. The researchers can identify the “F change” as 0.171. In this aspect, the researchers can
evaluate the overall performance of the corporate sectors. The “statistical analysis” evaluates that the “fund
management sector” and “trust funds” generate less turnover than the other sectors. It reflects on the
“turnover percentage” from the financial year 2006 to 2015. The “model summary” also evaluates the
significance of the statistical method conducted in this research (Cui and Hu, 2018).
Table 6: ANOVA
The researchers conducted the “ANOVA test” to determine the variability in the “data set”. The “mean square”
and “sig value” have been identified in this aspect. The “mean square” of the two variables is 102.41 and
598.06, respectively. As the “sig value” is greater than 0.05, the “null hypothesis” has been rejected in this
“statistical analysis”. It also ensures the “statistical significance” of this research. Based on the analysis, it is
also determined that the organizational management can make relevant decisions regarding “board diversity”
to improve the “corporate performance” of the sectors situated in the UK (Riyadh, Sukoharsono and Alfaiza,
2019).
Coefficientsa
Table 7: Coefficient
It is necessary for the researchers to meet the “research objectives” to ensure the significance of the study.
For this purpose, the researchers can evaluate the steps taken by the government for implementing “board
diversity” in the corporate sectors of the country. “Coefficient analysis” is conducted in this aspect for
determining the “standard error” and “beta”. However, a negative “T-value” is reflected in the statistical
analysis. The “sig value” of 0.682 ensures a “statistical significance” in this study. The government can take
crucial steps to enhance this sector’s overall turnover.
Regression analysis between turnover percentage in 2007 and 2008
Table 8: Descriptive statistics
The “average value” of “turnover percentage” in 2007 and 2008 are 49.34 and 49.63, respectively. In the
“descriptive analysis”, the researchers evaluated the ” standard deviation “. It also measures the “central
tendency” and “viability” in statistical analysis. The researchers can also identify the thoughts of the corporate
sector regarding the diversification of the board. The corporate health of different sectors in the UK can be
evaluated in this aspect. It also improves these sectors’ “shareholder performance” (Crowther, Davies and
Cooper, 2018). It indicates that the monetary performance of the banking sector and retail sector meets the
organizational standard of the country.
Correlations
Table 9: Correlation
The “correlation analysis” between the two variables has been conducted to evaluate the relationship between
“turnover percentage” in 2007 and 2008. The “Pearson correlations” between the variables are identified as 1
and 0.98, respectively. It also detects that there is a “significant relation” between the “dependent variable” and
“independent variable”. The “correlation analysis” also identifies that there is a “statistical significance”
detected in conducting the “statistical analysis”.