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The Effect of Board and Top Management Diversity on Corporate Performance in the UK Financial and Insurance Industry
Abstract
This research aims at the effect of board diversity in the UK financial and insurance industry covering gender, age and ethnics diversity in boardroom and top management and investigating the effect on innovation performance and economic returns.
This dissertation as a financial research uses positivism philosophy to generate law-like findings and deductive approach. It collects secondary data (190 UK listed financial and insurance company) from database expectedly Orbis database.
This research finds that there is no relationship between diversity in top management as well as board and corporate financial performance and between the diversity and innovation performance in UK financial and insurance industry. Gender diversity, age diversity and nationality diversity cannot affect neither corporate financial performance nor innovation performance. Also, this research finds that there is a very poor relationship between board size and gender diversity. It is significant for further researches to discover the negative mediating factors affecting the relationship between diversity in board & top management and corporate performance.
1.3 Aims, Purposes and Objectives
2.2 Critical Evaluation of Previous Research
4.1 Diversity and Corporate Financial Performance
4.2 Diversity and Intellectual Property (IP)
4.3 Board Size and Board Members
5.4 Diversity and Corporate Performance
6.3 Recommendations for Further Research
1.0 Introduction
1.1 Context
Board diversity has aroused considerably attention from the society, practitioners and scholars, especially in financial industry. Many research evidences prove or suggest that board diversity have strong influences on corporate performance (Abdullah, 2013; Davis, 2012; and Hassan and Marimuthu, 2014). Managing a diversified board contributes to innovation, work performance and decision-making process, thus facilitating corporate performance.
However, gender discrimination is still serious in the UK particularly the financial industry. In the UK, financial and insurance industry has the most serious gender pay gap, having 33.7% pay gap between men and women average hourly earnings as a percentage of male’s average hourly earnings for all workers in the UK, followed by education (25.4%) and the sector of professional, scientific and technical activities (24%) in 2019 (Clark, 2019a). In financial and insurance industry, annual median earnings of full-time male employees reached 50,256 GBP, whereas the figure for female employees only was 34,636 GBP in 2018 (Cherowbrier, 2019). Meanwhile, 79% female and 62% male perceived a gender gap pay (Clark, 2019a). Besides the large gender pay gap, only very few females can hold CEO positions in the FTSE companies in the UK. According to Clark (2019b), only 7 female CEO in FTSE 100 and 5 female CEO in FTSE 250. Furthermore, the older female workers are face more serious gender pay gap: 50 to 59 age group facing 16.2% gender pay gap, followed by 40 to 49 age group (13.7%) and 60 and over (12.9%) (Clark, 2019c).
Furthermore, age discrimination also is serious in financial service industry. According to a CV-library survey, 70.8% participants claimed that they perceived age discrimination in their workplace and about 33% people believed that they were rejected because of their age (Larkin, 2020).
Moreover, another pervasive issue is race discrimination in financial and insurance industry. Due to race stereotype, banks and financial service providers tend to hire fewer ethnic minorities especially African British, whereas in return minorities are likely to avoid mainstream banks for a better deal (Andrews, 2017). Race discrimination has been a deep-rooted issue in British society. Ethical minorities have fewer promotion opportunities (Kimathi, 2019).
Under such context, there are many voices advocating that UK government should build a more aggressive voluntary objective to increase gender diversity in corporate board. According to CIPD (2015), 53% of HR professionals support that UK government should set such objective in a CIPD’s survey conducted in 2015. In this survey, 89% of participants agree that good gender diversity enhances boardroom effectiveness and only 6% disagree with it. Those HR professionals illustrate the following benefits of gender balance in corporate boards: 1) women in board propose different perspective that contributes to decisions and decisions (89% of respondents agree); 2) increasing female board members meet the demands of British society and a company’s female customers (79%); 3) boards with a good degree of gender diversity can enhance business performance (68%); women directors can act a positive model (65%); a board with good gender diversity is more innovative and creative (62%); and gender diversity in board contributes to a company’s reputation (56%).
1.2 Research Significance
This research is significant that helps companies in financial and insurance sector to realise the advantages of managing diversified board members and top managers. The results of the research can demonstrate the positive impacts of board diversity on corporate performance, thus advising them to provide more opportunities to female and monitories. By offering empirical evidences, the research makes efforts to try the existing discrimination issues. Also, the advises are beneficial for companies in the industry, allowing them to find a new approach improving competitive advantages and corporate performance.
The results of the research are prominent for the social and economic challenges caused by COVID-19. Unemployment rate has been climbing in the UK during the outbreak of the new coronavirus. The International Monetary Fund (IMF) estimated that the global economy would turn down 3% but start to normalise in the second half year of 2020 in April (IMF, 2020). This means that the UK’s financial and insurance industry is facing difficulties during economic recession and will have to undertake the task of re-organising human resource. During economic recession, it is prominent for the industry to identify an effective approach to improve competitive advantages and secure economic sustainability.
Moreover, the results help the industry to develop innovation, which is significant in the age of Industry 4.0. 4.0 technologies including blockchain, 5G, machine learning and Internet of Internet (IoT) are changing competition landscape in the industry. Smart contract as well as personalised and highly customised service supported by AI are forcing players in the industry to embrace innovation and change business. In such context, this research can suggest the approach of boosting innovation by changing board members and top managers.
Furthermore, this research is important that can cover a research gap. Most of researches focus on workplace diversity, whereas fewer studies pay attention to board diversity and top management diversity. Even fewer scholars studied the impact of board diversity in financial and insurance industry. Based on research, there is no research focusing on the causal relationship between board diversity in the UK’s financial and insurance industry. Therefore, the results of the research can fulfil the research gap.
The results of previous researches are contesting. In the CIPD’s survey, HR professionals reveal many benefits of gender diversity in corporate board, as mentioned, (CIPD, 2015). Meanwhile, many theories can explain the positive influence of diversity, including agency theory (Jensen and Meckling, 1976), the upper echelons theory (Mason, 1984), resource-based view (Bryant and Davis, 2012), and human capital theory (Pasaribu, 2017). On the other hand, many previously academic studies find a negative impact of gender diversity (Adams and Ferreira, 2009 and Bohern and Staubo, 2014). Meanwhile, some academic studies find that the impact of gender diversity on corporate performance is very limited (e.g. Brammer et al., 2007). Pasaribu (2017) find very limited evidences supporting the impact. More importantly, some scholars suggest that the gender diversity in a corporate board is pushed by equal opportunity regulations and pressure from a company’s external environment rather than drove by female’s real capabilities (Conyon and Mallin, 1997 and Powell, 1999). Therefore, more female directors are non-executive. Therefore, it is significant for this dissertation to clarify these arguments.
1.3 Aims, Purposes and Objectives
This research aims at the effect of board diversity in the UK financial and insurance industry covering gender, age and ethnics diversity in boardroom and top management and investigating the effect on innovation performance and economic returns. The purpose of the research is to identify impacts of director and top manager diversity on financial or insurance companies’ innovation performance and economic return, thus providing recommendations to these companies that contribute to their corporate performance. It studies the causal relationship between diversity in boardroom and top management and corporate performance for make recommendations and also changing discrimination issues.
This research has following tactical targets:
1) To collect reliable literature about board diversity and its effects to build research hypothesis
2) To collect analyse secondary data to study the effects
3) To discuss the findings from secondary data with literature to generate conclusions and make recommendations
In alignment with the research purpose, three research objectives are identified:
1) To identify the impacts of gender, age and ethnics diversity on economic returns in the UK financial and insurance industry
2) To study the impacts on innovation performance in the industry
3) To make recommendations for the industry based on findings
2.0 Literature Review
2.1 Board Diversity
Board diversity has positive influences on corporate performance in various ways. It rises board independence so as to improve the monitoring of managers and top management teams (Carter et al., 2003). Demographic diversity positively influences on corporate performance (Hassan and Marimuthu, 2014). Hassan et al. (2015) find that demographic diversity has a robust relationship with corporate performance. Diversity has positive influences on a company’s competitive advantage (Abdullah, 2013).
Agency theory interprets board functions of measuring and supervising managers. In this theory, conflicts arise when there is a conflict between principal’s goal and the agent’s. Agency relationship acts an essential role in corporate performance and relates with board composition (Jensen and Meckling, 1976). This means that agency theory suggests that board membership is related with agency relationship which fundamentally affects corporate performance. Furthermore, the upper echelons theory explains the organisational results such as corporate performance and strategic achievements by behavioural decision-making theories. It can interpret the effects of demographic and cognitive diversity in term of corporate performance. It means that corporate boards are relevant and can affect organisational results. Hambrick and Mason (1984) uses the upper echelons theory proving that board diversity results on wiser decisions than homogenous board. Moreover, Raver and Schneider (2004) find that developing diversity in top management teams can cultivate diverse talent so as to attract, retain and gain competitive advantage. This study is developed on the basis of upper echelon theory because it examines characteristics of top-level management characteristics and its impacts on corporate performance. The finding of the study suggests that diverse boards contribute to monitoring of managers and top management teams because board diversity rises board independence. Nevertheless, agency theory cannot explain the causal correlation between board diversity and financial performance (Carter et al., 2003). Moreover, Resource-Based Review (RBR) explains that sustainable competitive advantages of an organisation are developed on the basis of resources and capabilities (Yang and Konrad, 2011). Unique or rare resources and capabilities sustain competitive advantage. This means that diversified board members may contain rare knowledge and dynamic capabilities, thus contributing to competitive advantage. However, this is theoretical deduction which lacks empirical evidences. Bryant and Davis (2012) highlight that board diversity improve an organisation’s capability to gain more advantages in gaining resources from the environment than a less diversified board. They further explain that a diversified board improves competencies to gain external knowledge and build networks. This explanation aligns with resource-based view.
Furthermore, human capital theory can be used to explain the relationship between board members and corporate performance (Pasaribu, 2017). This theory advocates that directors’ characteristics that can contribute to companies.
2.2 Critical Evaluation of Previous Research
Pasaribu (2017) study the relationship between female directors and corporation performance. However, this research focuses on all non-financial UK listed companies and studies their performance between 2004 and 2012. The research uses regression analysis and finds a little evidence supporting a positive and strong relationship between female directors and corporate performance. However, they found that female director has a significant and positive relationship with corporate performance in the UK’s listed small companies this because they endure fewer over-monitoring and are flexible to address their board of directors.
Brammer et al. (2007) study the impact of gender and ethnic diversity among UK corporate boards. They adopt a large sample size including UK PLCs and covering a director’s gender, ethnicity and position. However, they find that the level of ethnic and gender diversity among these UK PLCs is low. Another finding is that the diversity is weaker in executive positions. Gender diversity is higher in banking, retailing, utilities, and media industry. However, ethnic diversity is considerably low. They highlight gender diversity in corporate boards is related with a firm’s customers and external environment.
Dastane and Eshegbe (2015) study the impact of gender, age, education ethnicity diversity on employee satisfaction in Malaysian hotel sectors. This research adopts collected primary data by 150 questionnaires with convenience sampling technique. They find that diversity has significant and strong impact on employee satisfaction. However, this research did not consider corporate financial performance.
Carter et al. (2010) find a significant relationship between board diversity and corporate value. They adopt Tobin’s Q to measure corporate value for Fortune 1000 companies. They measure board members’ demographics including African Americans, Asians, Hispanic and female.
Based on analysis of previous researches, this dissertation identifies two research gaps. Hassan et al. (2016) conclude that researches focusing on diversity in board level remain ambiguities. There is no theory that forecasts the essence of the correlation between board diversity and financial performance. Furthermore, as mentioned, no study focuses on younger age diversity and its effects on innovations for Industry 4.0 technologies in the financial industry. Moreover, the findings of the impact of gender diversity on board on corporate performance are inconsistent. Additionally, another research gap is the impact of ethnic diversity on innovation and economic performance in the UK financial and insurance industry.
2.2 Gender diversity
Gender diversity on board contributes to decide-making and creativity thus improving corporate performance. Female board members tend to have greater education background and more knowledge than their male counterparts, thus contributing to board capabilities (Arena et al., 2015). This because they can use their wider knowledge improving decision-making and strategic generation. Marimuthu and Kolandasiamy (2009) highlight that female board members positively affect relationship with corporate performance. Mahadeo et al. (2012) highlight that female directors have positive relationship with corporate performance in emerging markets. Erhardt et al. (2003) also demonstrate positive relationship between female directors and corporate performance in the US. This study explains that core responsibility of board directors is to administrate and monitor management and provide resources so diversity contributes to corporate performance. This study thereby is consistent with agency theory and resource-based review disused above. Two studies further explain the contribution of female diversity to corporate performance by resource-based review. Taljaard et al. (2015) explains that companies gain resources from the environment in order to administrate uncertainties and improve corporate performance. The second study elaborates diverse board capital generates board diversity supporting capability of managing resources, and board diversity relieves uncertainties and increases corporate performance (Hillman and Dalziel, 2003). Ujunwa et al. (2012) find that gender diversity or minorities in the board has positive relationship with corporate value. Nevertheless, this study also finds that the participants of female and monitories increase board size, thus compromising positive influences of female directors.
Many researches find that female directors tend to have higher education degree and academic achievements (Sing et al., 2008; and Sealy et al., 2007). Singh et al. (2008) explain that female directors are likely to have an MBA degree and international experience in FTSE 100. Sealy et al. (2007) illustrate that female directors are likely to have an outstanding identity such as Prof, Dr, civic or political identity or aristocratic identity. However, Terjesen et al. (2009) find that female may have less business experience than their male counterparts. Singh and Vinnicombe (2004) explain that female is less attractive to male because they are short of female networks and experience. Singh and Vinnicombe (2004) further explain that one of motives of a company employing female director is the pressure from external environment. Terjesen et al. (2009) highlight that women directors can increase the effectiveness of a board and corporate performance whereas they cannot directly affect a company’s bottom line, because their impacts can be weakened by many mediating variables.
However, there is a contrasting argument that gender diversity among board members can negatively affect corporate performance (Adams and Ferreira, 2009). Zainal et al. (2013) prove that gender diversity and ethnics diversity on board have no relationship with corporate performance in the context of Malaysia. Meanwhile, Bohern and Staubo (2014) find an adverse relationship between female board member and corporate performance. This means that the findings of the relationship between gender diversity on board and corporate performance is inconsistent and arguable. There is a research gap of the diversity’s effects in the UK financial and insurance industry.
2.3 Age Diversity
Academic researches show less concern to the impact of age diversity on board (Kang et al., 2007). However, from resource-based review, age diversity on board can bring more and rare resources and capabilities thus contributing to organisational performance. Most of board members is above 60 years old (Engele et al., 2012). Nevertheless, younger generations trend to be more sensitive to innovation and new technologies in the age of industry 4.0. Mahadeo et al. (2012) highlight that young female board members can contribute to age diversity and also corporate performance. Taljaard et al. (2015) find that female board members are younger than their male counterparts and that age diversity has positive impacts on corporate performance. Younger board members can improve competitiveness and performance of a company.
Many scholars focus on older board members and their positive impacts on knowledge transferring from older members to youngers (Daveri and Maliranta, 2007, Lauring and Selmer, 2012). Older board members have more experience, knowledge and network, which can enrich corporate resources and capabilities. However, there is no study focusing on younger age diversity and its effects on innovations for Industry 4.0 technologies in the financial industry.
Huse and Rindova (2001) highlight that age diversity on board increases companies’ understanding on customer knowledge and insights. Older and younger board members have in-depth understanding on the customer demands in their age groups. This means that age diversity facilitates product innovations. Their knowledge may make contributions in innovation process.
2.4 Nationality Diversity
Nationality diversity in board is related with ethnic diversity and cultural diversity. An early study proves that ethnic minorities have a positive relationship with corporate performance (Biggins, 1999). The study demonstrates that ethnic diversity in board positively affects corporate performance as ethnic minorities provide deep customer insights and have strong competencies of meeting customers. They allow a company to have the perspective of considering the interests of minorities in the board. Ethnic participation on board fulfils their responsibility in a more effective way (Marimuthu and Kolandaisamy, 2009). Ntim (2015) proves that directors from different culture can offer different viewpoints and thus contribute to decision-making and creativeness in board. Additionally, Dastane and Eshegbe (2015) illustrate that ethnicity diversity has positive impacts on employee satisfaction in Malaysian hotel sectors.
On the other hand, Erhardt et al (2003) find that there is no correlation between national diversity on board and corporate performance in the US. Engelen et al (2012) also have the same finding in the UK. Rondoy et al. (2006) prove no such as correlation in Scandinavian companies. Furthermore, Martin (2014) point out the both negative and positive impacts of cultural diversity in the UK. One of the negative impacts of cultural diversity include increased interpersonal conflicts because people from different culture have different work style and communication style. Also, their leadership and management style are varied. Furthermore, cultural diversity tends to result in the divergence in objectives and goals among workers and top managers (Martin, 2014). To be specific, top managers from different culture tend to have a very different goal and objective. As a result, they are likely to work toward a different objective and goal. On the other hand, there are positive impacts of cultural diversity (Martian, 2014). Firstly, top managers from a different culture have a different perspective that contributes to decision-making. Also, cultural diversity helps a company to understand their customers when it conducts international business. Furthermore, Martina (2014) highlights that cultural diversity helps a company to improve its innovation. It assists a company to accept digitalisation and the latest technologies (Martina, 2014).
Also, some previous studies show there is no connection between ethnic minority and corporate financial performance (Cook and Glass, 2015; Masulis et al., 2012; Rose, 2007; and Zahra and Stanton, 1988). Zahra and Stanton (1998) did not find statistical evidences supporting the positive relationship between ethnic minority directors and corporate financial performance including return on equity. Rose (2007) used Tobin’s Q to study the relationship between foreign directors and corporate financial performance between 1998 and 2001. However, Rose (2007) show no evidence supporting significant relationship between corporate performance and foreign directors. Masulis et al (2012) find both advantages and disadvantages of foreign independent directors in American companies. The advantage is that foreign independent directors make contributions to international acquisitions if these acquisitions are conducted in their home countries. However, these foreign directors have a lower board attendance and is related with a higher possibility of financial misreporting, greater CEO compensation, and a poorer sensitivity of CEO turnover (Masulis et al., 2012).
Therefore, there are two contrasting viewpoints about the impact of nationality diversity, which requires further research.
2.5 Board Size and Diversity
Three researches suggest that board size has a relationship with diversity (Bremmer et al., 2007; Conyon and Mallin, 1997; and Powell, 1999). One of important variables of a company’s board diversity is board size (Bremmer et al., 2007). Bremmer et al. (2007) suggest that companies have a good gender diversity because they are under the pressure of gender equality.
Consumers act an important role in pushing gender diversity in corporate diversity. Gender diversity increases along with the size of a board increases. Conyon and Mallin (1997) highlight that companies deliberately increase the number of female directors in their board and make most of them act non-executive directors. This argument can be explained by Powell (1999)’s argument that equal opportunity policies are not flawless. These policies bring challenges to the selection of senior managers and executives as competent candidates are few and homogenous. Based on the arguments of Conyon and Mallin (1997) and Powell (1999), a larger board with more non-executive position tend to have more gender director. Therefore, this is important to study the correlation between board size and board diversity.
2.6 Theoretical Framework
Based on above discussion, this dissertation designs the following three theoretical frameworks including the independent variables (gender, age and nationality diversity) and the dependent variables (corporate financial performance and intellectual property). Also, the dissertation also studies the relationship between board size and board members.
Theoretical framework 1
Figure 1
Based on above framework, this dissertation designs the following hypothesis.
Hypothesis 1:
H0: there is no relationship between gender diversity in boardroom & top management and corporate performance in the UK financial and insurance industry.
H1: there is a relationship between gender diversity in boardroom & top management and corporate performance in the UK financial and insurance industry.
Hypothesis 2:
H0: there is no relationship between age diversity in boardroom & top management and corporate performance in the UK financial and insurance industry.
H1: there is a relationship between age diversity boardroom & top management and corporate performance in the UK financial and insurance industry.
Hypothesis 3:
H0: there is no relationship between nationality diversity in boardroom & top management and corporate performance in the UK financial and insurance industry.
H1: there is a relationship between nationality diversity in boardroom & top management and corporate performance in the UK financial and insurance industry.
Theoretical framework 2
Figure 2
Hypothesis 4:
H0: there is no relationship between gender diversity in board room & top management and innovation performance in the UK financial and insurance industry.
H1: there is a relationship between ethnic diversity in board room & top management and innovation performance in the UK financial and insurance industry.
Hypothesis 5:
H0: there is no relationship between age diversity in board room & top management and innovation performance in the UK financial and insurance industry.
H1: there is a relationship between age diversity in board room & top management and innovation performance in the UK financial and insurance industry.
Hypothesis 5:
H0: there is no relationship between age diversity in board room & top management and innovation performance in the UK financial and insurance industry.
H1: there is a relationship between age diversity in board room & top management and innovation performance in the UK financial and insurance industry.
Theoretical framework 3
Figure 3
Based on above theoretical framework, the following hypotheses are devised.
Hypothesis 6:
H0: there is a relationship between the size of board & top management and diversity in the UK financial and insurance industry.
H0: there is no relationship between the size of board & top management and diversity in the UK financial and insurance industry.
3.0 Research Methodology
3.1 Research Philosophy
This dissertation as a financial research uses positivism philosophy to generate law-like findings. The philosophy studies observable phenomenon in a scientific manner and avoids the impact of researchers’ subjectivities on their research. It relies on quantifiable observations which supports statistical analysis in accordance with empiricist perspective. Positivism-based studies eliminate human influence so as to generate a non-biased approach to study a phenomenon. They have a rigour framework to remove the influence of researchers. They can create law-like findings and universals (Sunders et al., 2009). Their findings are reliable and less arguable as it provides strong and empirical evidences.
On the other hand, interpretivism philosophy is not suitable for this research. Interpretivists highlight that positivism is improper for social research because not all behaviour and variables can be quantified (Gill and Johnson, 2002). Nevertheless, the results of interpretivism-based studies are controversial and arguable. The philosophy uses qualitative analysis enabling researchers to use their experience and findings to perceive an observable phenomenon. More importantly, this dissertation is a financial paper focusing on quantitative analysis.
Therefore, positivism philosophy is chosen by the dissertation and research hypothesis is justified in section 2.0.
3.2 Research Approach
In accordance with positivism, the dissertation adopts deductive approach. This approach explains a research phenomenon by existing knowledge. Thus, it generates no new theory. The objectives of dissertation are not involved in generating new knowledge. Deductive approach is more direct and time-saving than inductive approach.
On the other hand, inductive approach is not suitable for this dissertation, as it does not necessarily generate reliable findings even though it has reliable data and analysis. Meanwhile, it starts with observations and then designs research questions. However, this dissertation already has specific and significant research questions. More importantly, deductive approach certainly can generate valid findings as long as data collection and analysis are reliable.
By deductive approach, this dissertation has the following processes:
1) to collect existing knowledge and discus it in literature review
2) to design research questions and hypothesis
3) to collect and analyse data
4) to discuss findings from secondary data with literature review to generate conclusions and recommendations
3.3 Data Collection
This dissertation collects secondary data from database expectedly Orbis database. Secondary data can be more reliable than primary data. Based on previous research, Orbis database has 190 companies’ data which can be used in this dissertation. The data include demographics of board members and the number of parents and trademarks and Tobin’s Q. The sample size of this research is 190 companies engaging in the UK financial and insurance industry.
3.5 Data Analysis
Hassan and Marimuthu (2016) study the impact of board diversity (gender, ethnic and age diversity) on corporate performance by using Tobin’s Q as dependent variables. The study adopts these variables to measure financial performance. However, this study focuses on non-financial listed companies in Malaysia. Moreover, Guest (2009) also uses Tobin’s Q to measure the impacts of board size and profitability. Additionally, Carter et al. (2010) find a significant relationship between board diversity and corporate performance by using Tobin’s Q to measure corporate financial performance.
This dissertation collects secondary data from reliable database. It focuses on the UK listed financial and insurance companies which reveal their financial information and innovation performance. The dissertation uses Tobin’s Q to measure these companies’ financial performance and adopts the number of parents to evaluate their innovation capability. The data required by the dissertation can be found in database.
In empirical analysis, this dissertation uses the proportion of younger board members (below 40 years old) and older board members (over 65 years old) to total number of board members and top managers as age diversity. Then, it uses proportion of female board members to total number of board members and top managers as gender diversity. Thirdly, the dissertation uses the portion of foreign directors to the total number of and top managers as ethnical diversity.
This dissertation adopts regression analysis to investigate the research topic. Pasaribu (2017) also adopts regression analysis to study the impact of female directors.
The dissertation adopts the following regression equation:
Firm performance (Tobin’s Q) = β + β Gender Diversity + β Age Diversity + β Nationality diversity
Gender diversity = the number of female board members and top managers / total number of board members and top managers
Age diversity = the number of those director and managers (younger than 40 or older than 65) / total number of board members and top managers
Age diversity = the number of foreign director and managers / total number of board members and top managers
Innovation performance (The number of patent and trademarks) = β + β Gender Diversity + β Age Diversity + β Nationality diversity
The dissertation also uses correlation analysis to achieve its research objective. Bremmer et al. (2007) employ correlation analysis to study the relationship between board size and gender diversity in board.
4.0 Empirical Analysis
4.1 Diversity and Corporate Financial Performance
4.1.1 Descriptive Analysis
Age diversity is not high in the 190 samples (mean = 0.2165). Averagely, 21.65% of board members and top managers are either younger than 40 years old or older than 65 years old in the 190 companies.
National diversity is lower than age diversity (mean = 0.0999). Hence, averagely, 9.99% of board members and top managers are foreigners.
More importantly, gender diversity is considerably low (mean = 0.1874). Averagely, 18.74% of board members and top managers are female. However, in the UK, the male to female ratio is 49.37: 50.63. This means that gender diversity is considerably low.
|
Descriptive Statistics |
|||||
|
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
Age diversity |
190 |
.00 |
1.68 |
.2165 |
.22222 |
|
Nationality diversity |
190 |
.00 |
1.22 |
.0999 |
.17216 |
|
Gender diversity |
190 |
.00 |
1.00 |
.1874 |
.15973 |
|
Valid N (listwise) |
190 |
|
|
|
|
Table 1
4.1.2 Correlation Analysis
The results of correlation analysis are shown in the below. The correlation coefficient of gender diversity is 0.033 (< 0.299), implying no relationship between gender diversity and corporate financial performance. The correlation coefficient of age diversity is -0.040 (<0.299), suggesting no relationship between age diversity and corporate financial performance. Additionally, the correlation coefficient of national diversity is -0.154 (<0.299), implying that there is no relationship between nationality diversity and corporate financial performance.
Meanwhile, the P-value of two independent variables (gender diversity and age diversity) are higher than 0.05, suggesting that their relationship with corporate performance is insignificant. The P-value of nationality diversity is 0.034 (lower than 0.05), whereas its correlation coefficient shows that there is no correlation between nationality diversity and corporate financial performance. Given that there is no correlation, it cannot say the correlation is significant.
|
Correlations |
|||||
|
Tobin |
Gender diversity |
Age diversity |
Nationality diversity |
||
|
Tobin’s Q |
Pearson Correlation |
1 |
0.033 |
-0.040 |
-0.154* |
|
Sig. (2-tailed) |
0.655 |
0.588 |
0.034 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Gender diversity |
Pearson Correlation |
0.033 |
1 |
-0.031 |
-0.004 |
|
Sig. (2-tailed) |
0.655 |
0.669 |
0.961 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Age diversity |
Pearson Correlation |
-0.040 |
-0.031 |
1 |
0.071 |
|
Sig. (2-tailed) |
0.588 |
0.669 |
0.331 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Nationality diversity |
Pearson Correlation |
-0.154* |
-0.004 |
0.071 |
1 |
|
Sig. (2-tailed) |
0.034 |
0.961 |
0.331 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
*. Correlation is significant at the 0.05 level (2-tailed). |
|||||
Table 2
This research further runs another correlation analysis to examine the correlation between Tobin’s Q and gender diversity. The gender diversity covers age, gender and nationality diversity. However, the result shows that there is a no correlation between Tobin’s Q and general diversity.
|
Correlations |
|||
|
Tobin’s Q |
General Diversity |
||
|
Tobin’s Q |
Pearson Correlation |
1 |
-.058 |
|
Sig. (2-tailed) |
.430 |
||
|
N |
190 |
189 |
|
|
General Diversity |
Pearson Correlation |
-.058 |
1 |
|
Sig. (2-tailed) |
.430 |
||
|
N |
189 |
189 |
|
Table 3
4.1.3 Regression Analysis
The R (=0.159) shows that the relationship between the dependent variable (Tobin’s Q) and the independent variables (gender diversity, nationality diversity and age diversity). The R Square is 0.025, implying that 2.5% of variants in Tobin’s Q can be predicted by these independent variables.
|
Model Summary |
||||
|
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
|
0.159a |
0.025 |
0.010 |
0.89267 |
|
|
a. Predictors: (Constant), Gender Diversity, Nationality diversity, Age diversity |
||||
Table 4
In table 5 shows, P-value is 0.190 (>0.05), showing that the correlation is insignificant.
|
ANOVAa |
||||||
|
Model |
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
1 |
Regression |
3.834 |
3 |
1.278 |
1.604 |
0.190b |
|
Residual |
147.418 |
185 |
0.797 |
|||
|
Total |
151.252 |
188 |
||||
|
a. Dependent Variable: Tobin’s Q |
||||||
|
b. Predictors: (Constant), Gender diversity, Nationality diversity, Age diversity |
||||||
Table 5
The P-value of age diversity (0.705) and gender diversity (0.668), larger than 0.05. Therefore, their relationships are insignificant. The p-value of nationality diversity is 0.039, less than 0.05. Therefore, the relationship between nationality diversity and corporate financial performance is 0.039.
|
Coefficientsa |
||||||
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
1 |
(Constant) |
1.001 |
0.125 |
7.980 |
0.000 |
|
|
Age diversity |
-0.112 |
0.294 |
-0.028 |
-0.380 |
0.705 |
|
|
Nationality diversity |
-0.787 |
0.378 |
-0.151 |
-2.080 |
0.039 |
|
|
Gender diversity |
0.176 |
0.408 |
0.031 |
0.430 |
0.668 |
|
|
a. Dependent Variable: Tobin’s Q |
||||||
Table 6
4.2 Diversity and Intellectual Property (IP)
4.2.1 Descriptive Analysis
This research used the number of trademarks and patents as important IP and run the following analysis. As Table 7 shows, the mean is 5.1316. In other words, averagely, one company has 5.1316 patents and trademarks.
|
Descriptive Statistics |
|||||
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
|
|
Intellectual properties |
190 |
0.00 |
395.00 |
5.1316 |
34.75688 |
|
Valid N (listwise) |
190 |
||||
Table 7
4.2.2 Correlation Analysis
As Table 8 shows, correlation coefficient of gender diversity (0.048), age diversity (-0.001), and nationality diversity (0.084) is lower than 0.05, showing that they have no relationship with IPs. Also, the P-value of gender diversity (0.506), age diversity (0.991) and nationality diversity (0.249). These results suggest that their relationship with IP is insignificant.
|
Correlations |
|||||
|
IP |
Gender diversity |
Age diversity |
Nationality diversity |
||
|
Intellectual Properties (IP) |
Pearson Correlation |
1 |
.048 |
-.001 |
.084 |
|
Sig. (2-tailed) |
.506 |
.991 |
.249 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Gender diversity |
Pearson Correlation |
.048 |
1 |
-.031 |
-.004 |
|
Sig. (2-tailed) |
.506 |
.669 |
.961 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Age diversity |
Pearson Correlation |
-.001 |
-.031 |
1 |
.071 |
|
Sig. (2-tailed) |
.991 |
.669 |
.331 |
||
|
N |
190 |
190 |
190 |
190 |
|
|
Nationality diversity |
Pearson Correlation |
.084 |
-.004 |
.071 |
1 |
|
Sig. (2-tailed) |
.249 |
.961 |
.331 |
||
|
N |
190 |
190 |
190 |
190 |
|
Table 8
4.2.3 Regression Analysis
As Table 9 shows, the R is 0.097, showing that there is no relationship between the independent variable and the dependent variable (IPs). The R square is 0.009, implying that 0.9% of variants in IPs can be predicted by these independent variables.
|
Model Summary |
||||
|
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
|
|
0.097a |
0.009 |
-0.007 |
34.96347 |
|
|
a. Predictors: (Constant), Gender Diversity, Nationality diversity, Age diversity |
||||
Table 9
The P-value in the Table 10 is 0.626, showing that the relationship between the independent variable and the dependent variables is insignificant.
|
ANOVAa |
||||||
|
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
|
|
Regression |
2141.080 |
3 |
713.693 |
0.584 |
0.626b |
|
Residual |
226152.158 |
185 |
1222.444 |
|||
|
Total |
228293.238 |
188 |
||||
Table 10
As Table 11 shows, P-value of age diversity (0.940), national diversity (0.251) and gender diversity (0.512) is larger than 0.05. This means that their relationship is insignificant with IPs.
|
Coefficientsa |
||||||
|
|
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
|
(Constant) |
1.651 |
4.912 |
0.336 |
0.737 |
|
|
Age diversity |
-0.863 |
11.508 |
-0.006 |
-0.075 |
0.940 |
|
|
Nationality diversity |
17.063 |
14.820 |
0.084 |
1.151 |
0.251 |
|
|
Gender diversity |
10.516 |
15.992 |
0.048 |
0.658 |
0.512 |
|
|
a. Dependent Variable: intellectual properties |
||||||
Table 11
4.3 Board Size and Board Members
As table 12 shows, correlation co-efficient only reaches 0.104 (< 0.199). This means that the relationship between diversity and the size of board and top management is very poor.
|
Correlations |
|||
|
General Diversity |
The number of board members and top managers |
||
|
General Diversity |
Pearson Correlation |
1 |
0.104 |
|
Sig. (2-tailed) |
0.155 |
||
|
N |
189 |
189 |
|
|
The number of board members and top managers |
Pearson Correlation |
0.104 |
1 |
|
Sig. (2-tailed) |
0.155 |
||
|
N |
189 |
190 |
|
Table 12
In Table 13, the co-efficient of gender diversity only reaches 0.198 (>0.99), showing that the relationship between gender diversity and the size of board and top management is very poor. However, this co-efficient is higher than general diversity’s, which suggests that companies offer more opportunities to female when they have a larger size of board and top management.
|
Correlations |
|||
|
The number of board members and top managers |
Gender diversity |
||
|
The number of board members and top managers |
Pearson Correlation |
1 |
0.198** |
|
Sig. (2-tailed) |
0.006 |
||
|
N |
190 |
190 |
|
|
Gender diversity |
Pearson Correlation |
0.198** |
1 |
|
Sig. (2-tailed) |
0.006 |
||
|
N |
190 |
190 |
|
|
**. Correlation is significant at the 0.01 level (2-tailed). |
|||
Table 13
To test the relationship among the size of board and top management, gender diversity and corporate financial performance, this research runs the following regression analysis. It also finds no significant relationship.
|
Coefficientsa |
||||||
|
|
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
||
|
B |
Std. Error |
Beta |
||||
|
|
(Constant) |
.967 |
.127 |
7.633 |
.000 |
|
|
The size of board and top management |
-.003 |
.003 |
-.068 |
-.914 |
.362 |
|
|
Gender diversity |
.258 |
.417 |
.046 |
.620 |
.536 |
|
|
a. Dependent Variable: Tobin’s Q |
||||||
4.4 Summary of Findings
The results of the empirical analysis are shown in Table 14.
|
|
Correlation |
Regression |
Status |
Hypothesis |
|
Relationship with corporate financial performance |
|
|
|
|
|
Gender diversity |
0.033 |
0.940 |
No relationship |
H0 is accepted H1 is rejected |
|
Age diversity |
-0.40 |
0.251 |
No relationship |
H0 is accepted H1 is rejected |
|
Nationality diversity |
-0.154 |
0.512 |
No relationship |
H0 is accepted H1 is rejected |
|
Relationship with IPs |
|
|
|
|
|
Gender diversity |
0.048 |
-0.380 |
No relationship |
H0 is accepted H1 is rejected |
|
Age diversity |
-0.001 |
-2.080 |
No relationship |
H0 is accepted H1 is rejected |
|
Nationality diversity |
0.084 |
0.430 |
No relationship |
H0 is accepted H1 is rejected |
|
Relationship board size |
|
|
|
|
|
General diversity |
0.104 |
|
No relationship |
H0 is accepted H1 is rejected |
|
Gender diversity |
0.198 |
|
No relationship |
|
Table 14
5.0 Discussion
5.1 Gender Diversity
This research finds that there is no relationship between gender diversity and corporate financial performance in UK financial and insurance industry. Also, gender diversity has no connection with innovation performance in the industry. These findings are supported by many previous studies (Bohern and Staubo, 2014; Pasaribu, 2017; and Zainal et al., 2013). These findings also can be explained by these previous studies. Firstly, Terjesen et al. (2009) illustrate that the impact of women directors can be weakened by many mediating variables. This means that it has to consider other factors mediating the impact of gender diversity in corporate board.
Secondly, the finding can be explained by Singh and Vinnicombe (2004)’s argument that a company employing female director is the pressure from external environment. Meanwhile, CIPD (2015) also has such finding. Meanwhile, the arguments of Conyon and Mallin (1997) and Powell (1999) suggest that female directors are selected because of equal opportunity policy and their gender rather than their capabilities. Also, the arguments imply that female are more likely to act non-executive directors. If they act non- executive directors, their impacts on a corporate performance are very limited. Based on the arguments, Bremmer et al. (2017) find that board size has a relationship with gender diversity because a larger size has more non- executive positions for female. This dissertation did not find strong evidence support the relationship between board size and gender diversity in corporate board. However, the correlation co-efficient of gender diversity is higher than that of gender diversity. This may imply that a company with larger size of top management and board offers female more opportunities.
Thirdly, Terjesen et al. (2009) point out the weakness of female directors: they may have less business experience than their male counterparts. This can explain the findings of this dissertation.
Brammer et al. (2017) illustrate that gender diversity is higher in the UK’s banking industry. This dissertation focusing on the UK’s financial and insurance industry however finds gender diversity is relatively low.
Furthermore, this dissertation finds no relationship between gender diversity and corporate financial performance as well as innovation performance, which be explained by the fact that gender diversity is low in the industry. Averagely, only 18.74% of top managers and directors are female, whereas the male to female ratio is 49.37: 50.63 in the UK (Clark, 2020).
Also, the findings of this dissertation are related with Ujunwa et al. (2012) who argue that the participants of female and monitories increase board size, thus compromising positive influences of female directors. This argument conflicts with Brammer et al. (2017)’s finding. According to Ujunwa et al. (2012), the participant of female directors leads to a larger board size which compromises the impact of female directors. However, Brammer et al. (2017) argue that a large board size offers more female opportunities. This dissertation did not find strong evidences supporting a relationship between board size and gender diversity. Also, it examines the relationship among the size of board and top management, gender diversity and corporate financial performance and finds no significant relationship.
5.2 Age diversity
This research finds no relationship between age diversity and corporate financial performance as well as innovation performance. This finding conflicts with some scholars’ augments (Daveri and Maliranta, 2007; Lauring and Selmer, 2012; and Mahadeo et al., 2012). Meanwhile, the research finds that age diversity is relatively low. Averagely, 9.99% of top managers and directors are younger than 40 or older than 65.
5.3 Nationality Diversity
This research finds no relationship between nationality diversity and corporate financial performance as well as innovation performance. This is supported by some previous studies (Cook and Glass, 2015; Erhardt et al, 2003; Engelen et al., 2012; Masulis et al., 2012; Rose, 2007; Rondoy et al., 2006; and Zahra and Stanton, 1988). All theseresearches did not find correlation between nationality diversity or ethnicity diversity and corporate financial performance in different years, country and industry. This means that the finding that nationality diversity has no impact on corporate financial performance is generalised. To be noticed, Rose (2007) also used Tobin’s Q to measure corporate financial performance.
The finding of this dissertation can be explained by the cross-cultural issues (Martin, 2014). Foreign directors may increase interpersonal conflicts because people from different culture have different work style and communication style. Foreign directors and managers are likely to work toward a different objective and goal. Masulis et al. (2012)’s argument also can explain this research’s finding. Foreign independent directors make contributions to international acquisitions if these acquisitions are conducted in their home countries. However, these foreign directors have a lower board attendance and contributes to possibility of financial misreporting, greater CEO compensation, and a poorer sensitivity of CEO turnover. When they have a lower board attendance, they certainly cannot fully offer their unique perspectives, resources and capabilities.
5.4 Diversity and Corporate Performance
This research finds that there is no relationship between diversity in top management as well as board and corporate financial performance and between the diversity and innovation performance. This finding is contrasting with many theories including agency relationship, behavioural decision-making theories, upper echelons theory, resource-based view and human capital theory.
In agency relationship, behavioural decision-making, and upper echelons theory, the demographics and cognition of board members can affect corporate performance and they can contribute to decision-making process. However, this does not mean that they can directly make decisions or they certainly make such contributions. Even though they can contribute to decision-making, decision-makers may not consider their opinion because their discrimination or other reasons. If companies employ female and minorities as directors and managers because of external pressures such as equal opportunity policies and customer pressure, they may not really value the competence of these female and minorities. As a result, the opinions of female and minorities may be neglected.
Secondly, in resource-based view and human capital theory, female and minorities can offer different perspective and competencies thus contributing to a company’s performance. However, it does not mean that these different perspective and competencies are relevant to the company and the company needs them. Also, it does not mean that different competencies and resources from female and minorities certainly can contribute to a company’s core competencies. For example, Masulis et al (2012) argue that foreign independent directors can contribute to international acquisitions, whereas their competencies tend to be regarded as less relevant when these acquisitions complete.
More importantly, these theories are relevant to human resource management, whereas human resource only is one of factors affecting corporate financial performance and innovation performance. There are many factors affecting these performances. CIPD reveals the benefits of gender diversity, which however are perception of HR professionals who did not offer empirical evidences.
Additionally, Pasaribu (2017) explain that the impact of gender diversity is much more prominent in UK small listed companies because they experience less over-monitoring and have higher flexibility to manage their board. This may suggest that the complicated organisational structure and business operation of large corporation weaken the impact of gender diversity. This also suggests that some internal factors may hinder female leaders to make more contributions. On other hand, a company with high flexibility could use diversity more efficiently and effectively. For example, it can hire foreign directors when it addresses international acquisitions. After these acquisitions, it can dismiss these directors to shrink its board size.
6.0 Conclusions
6.1 Summary of Findings
This research finds that there is no relationship between diversity in top management as well as board and corporate financial performance and between the diversity and innovation performance in UK financial and insurance industry. Gender diversity, age diversity and nationality diversity cannot affect neither corporate financial performance nor innovation performance. Also, this research finds that there is a very poor relationship between board size and gender diversity.
6.2 Recommendations
Given that there is no relationship diversity on board and top management, this research makes the following recommendations. Firstly, it is not advised that the UK government sets more aggressive self-voluntary regulations to increase gender diversity in boardroom and top management positions. Secondly, companies should recruit and develop female leadership and minorities leadership to foster their skills and experience. They may devise programs that especially develop the capabilities of female and minorities. Also, these companies should employ those female and minorities who really are qualified rather than irresponsibly offer them non-executive positions to meet social and customer expectations. Furthermore, UK financial and insurance companies should recruit those female and minorities whose capabilities and resources can support their sustainable advantages in resource-based view. Otherwise, their talents will be wasted.
6.3 Recommendations for Further Research
Even though the findings of this research are consistent with many previous researches (e.g. Bohern and Staubo, 2014; Pasaribu, 2017; Cook and Glass, 2015; Engelen et al., 2012; and Masulis et al., 2012, there are still many puzzles unsolved. To be specific, Pasaribu (2017) finds that the impact of gender diversity in UK small listed company’s board is much more significant than UK large companies because small companies endure fewer over-monitoring and are flexible to address their board of directors. Therefore, further research should examine whether over-monitoring and inflexibility of board and top management hinder positive impacts of diversity. Also, it is significant for further researches to discover the negative mediating factors affecting the relationship between diversity in board & top management and corporate performance. By discovering and solving these factors, the impact of diversity can be improved. More importantly, further research should continuingly focus on empirical evidences to find the direct relationship between financial performance and diversity.
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