Intellectual Capital and Its Effects on The Performance of Firms, Sectors and Nations

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MINISTRY OF EDUCATION AND TRAINING HO CHI MINH CITY OPEN UNIVERSITY

INTELLECTUAL CAPITAL AND ITS EFFECTS ON THE PERFORMANCE OF FIRMS, SECTORS AND NATIONS

DOCTORAL DISSERTATION IN BUSINESS ADMINISTRATION

HO CHI MINH CITY – 2024

MINISTRY OF EDUCATION AND TRAINING HO CHI MINH CITY OPEN UNIVERSITY

TRAN PHU NGOC

TRAN PHU NGOC

INTELLECTUAL CAPITAL AND ITS EFFECTS ON THE PERFORMANCE OF FIRMS, SECTORS AND NATIONS

DOCTORAL DISSERTATION IN BUSINESS ADMINISTRATION

1 Dr Vo Hong Duc

2 Dr Van Thi Hong Loan

HO CHI MINH CITY – 2024

DECLARATION

I, Tran Phu Ngoc, declare that the PhD thesis entitled Intellectual Capital and Its

Effects on The Performance of Firms, Sectors and Nations is entirely original and has

not been submitted for any other degree or diploma at any university or institution To the best of my knowledge, this thesis does not include any material that has been previously submitted, either in full or in part, for any academic degree or diploma Unless otherwise stated, this work is solely my own, conducted under the primary supervision of Dr Vo Hong Duc and Dr Van Thi Hong Loan

Ho Chi Minh city, July , 2024

Tran Phu Ngoc

ACKNOWLEDGEMENTS

This thesis would not have been possible without the support of my principal supervisor, Dr Vo Hong Duc I am profoundly grateful to Dr Duc for his dedication, invaluable guidance, scholarly support, and generous commitment of time throughout this process Without his assistance, this thesis would not have come to fruition

I also wish to express my gratitude to Dr Van Thi Hong Loan for her insightful comments and for inspiring me to complete this work

Special thanks go to my friends at The CBER – Research Centre in Business, Economics & Resources at Ho Chi Minh City Open University, Ho Minh Chi, and Tran Pham Khanh Toan, whose encouragement and support were instrumental in completing this thesis

I could not have completed this journey without the love and encouragement of my family and friends I am deeply appreciative of my late father, who believed in my potential, and my mother, who is always proud of my achievements

Lastly, I extend my heartfelt thanks to my wife, Huyen Co, for her patience and support in making this dream a reality

I dedicate this thesis to my beloved daughter, Kha Han, whose inspiration and courage helped me overcome all hardships throughout this journey

ABSTRACT

In a knowledge-based economy, firms put great effort into remaining competitive Various economic sectors have also adopted strategies to demonstrate resilience in a competitive environment Nations are no exception In the era of economic integration, countries have to utilize all available resources to achieve sustainable national performance and development While tangible assets are limited and their use is at the limit, the role of intangible assets has become important Intellectual capital, considered a critical asset, refers to the intangible assets contributing to value creation for firms, sectors, and nations Intellectual capital includes three distinct components: human, structural, and relational The important role of intellectual capital in driving performance is crucial Accumulating and using intellectual capital efficiently provide significant effects and implications for the success of firms, sectors, and nations

Previous research has focused on understanding the role of intellectual capital at a firm level However, there is no well-established and generally agreed-upon approach for measuring intellectual capital at a sector or national level As such, this dissertation aims to achieve two objectives The first objective is to measure intellectual capital at three levels: firm, sector, and nation The second objective is to examine the impact of intellectual capital on the firm performance, sectors' performance, and the country's growth The findings from this dissertation are crucial for policymakers, practitioners, and executives to consider the roles of intellectual capital to maximize the benefits of this important asset

Specific tasks from the first research objective – measuring intellectual capital – can be summarized as follows First, data are manually collected from the annual reports of 150 firms listed in Vietnam from 2011 to 2018 These firms are classified into two categories: financial firms and non-financial firms This dissertation subsequently uses the modified value-added intellectual coefficient (MVAIC) method to compare the differences regarding the intellectual capital level between financial and non-financial firms in Vietnam Second, a new sectoral intellectual capital index is developed to measure the intellectual capital level across 12 sectors in Vietnam from 2011 to 2018

Third, data from 104 nations from 2000 to 2018 are collected to construct a new index of national intellectual capital (INIC)

In addition, the following tasks are conducted to achieve the second research objective – examining the effects of intellectual capital on a firm's performance (at a firm level) and sector's performance (at the sector's level) and economic performance (at a nation's level) This study employs the generalized method of moments (GMM) estimation technique to investigate how intellectual capital affects financial and non-financial firms' performance The dynamic common correlated effects (DCCE) estimation method is used to examine the effects of intellectual capital on the sector's performance Finally, this dissertation examines the impacts of intellectual capital on economic performance across nations using DCCE method

The main results from this dissertation can be summarized as follows First, a

significant difference in intellectual capital level between financial and non-financial firms in Vietnam The empirical results indicate that intellectual capital positively affects firm performance in Vietnam These findings imply that non-financial firms will need to invest in building their intellectual capital to increase their competitive

advantage Second, intellectual capital at the sector's level has been found to improve

the performance of sectors in Vietnam over the last decade, especially during the COVID-19 pandemic, which has put sectors under severe pressure These findings highlight the need for improving intellectual capital efficiency at the sectoral level to

remain competitive and prepare for future adverse events Third, the intellectual capital

level varies significantly across countries and Vietnam, from the current standing regarding intellectual capital ranking compared with other countries, has a significant task to improve intellectual capital for the nation Finally, the empirical results confirm that intellectual capital at the national level supports GDP per capita – an indicator of a country's economic performance

The contributions of this dissertation to the existing literature on intellectual

capital, its measurement and its effects on performance are threefold First, the study

examines the differences in intellectual capital level between the financial and financial in Vietnam and the impact of intellectual capital on firm performance The findings provide valuable managerial implications for practitioners and firm executives

non-Second, this dissertation pioneers the development of indices for measuring intellectual

capital for sectors and nations These indices can be used to examine the effects of

intellectual capital on different managerial and economic issues Third, to the best of the

author's knowledge, this dissertation is the first to measure intellectual capital for firms, sectors, and nations in Vietnam and consider its effects on performance in the Vietnamese context in the same place

TABLES OF CONTENTS

DECLARATION iii

ACKNOWLEDGEMENTS iv

ABSTRACT v

TABLES OF CONTENTS viii

LIST OF ACRONYMS xii

LIST OF FIGURES xiii

1.6 Research subject and scope 12

1.7 Contributions of the study 12

1.8 Research framework and steps 13

1.9 The outline of the dissertation 17

1.10 Summary 18

CHAPTER 2 LITERATURE REVIEW 19

2.1 Definitions and classifications 19

2.1.1 Saint-Onge’s model 20

2.1.2 Sveiby’s model 22

2.1.3 Skandia intellectual capital value scheme 23

2.3.5 Value Added Intellectual Coefficient™ (VAIC™) 34

2.4 Measuring intellectual capital: extended analysis for sectors and nations 36

2.4.1 Sectoral intellectual capital measurements 37

2.4.2 National intellectual capital measurements 40

2.5 Measuring performance of firm, sector and nation 46

2.5.1 Firm performance 47

2.5.2 Financial performance for sector 47

2.5.3 Performance of the nation 48

2.6 The effects of intellectual capital on performance of firms, sectors and nations 50

2.6.1 Intellectual capital and firm’s performance 50

2.6.2 Intellectual capital and sector performance 55

2.6.3 Intellectual capital and national performance 57

2.7 Summary 60

CHAPTER 3 METHODOLOGY 61

3.1 Data 61

3.2 Research methods 63

3.2.1 Assess the impact of intellectual capital on firm performance 63

3.2.2 Assess the impact of intellectual capital on the performance of sector and nation 66

3.3 Variables: definitions and measurements 72

3.3.1 Measuring intellectual capital at firm level 72

3.3.2 Sectoral intellectual capital index 74

3.3.3 New index of national intellectual capital 74

3.3.4 Other variables 79

3.4 Summary 80

CHAPTER 4 MEASURING INTELLECTUAL CAPITAL: THE ANALYTICAL ANALYSIS 81

4.1 An intellectual capital level for Vietnamese listed firms 81

4.2 An intellectual capital across sectors in Vietnam 83

4.3 Measuring national intellectual capital: a tale of two indices 86

4.4 A national intellectual capital across nations 88

4.4.1 National intellectual capital by region 88

4.4.2 National intellectual capital by income 90

4.5 Summary 96

CHAPTER 5 EMPIRICAL RESULTS ON THE EFFECTS OF INTELLECTUAL CAPITAL ON PERFORMANCE OF FIRM, SECTOR AND NATION 99

5.1 Intellectual capital and firm performance 99

5.1.1 Correlation analysis 99

5.1.2 Autocorrelation and heteroskedasticity tests 102

5.1.3 The effects of intellectual capital on firm’s performance using panel data estimation: generalized method of moments (GMM) 102

5.2 Intellectual capital and financial performance across sectors 105

5.2.1 The descriptive statistics 105

5.2.2 The cross-sectional dependence test 107

5.2.3 The slope homogeneity test 107

5.2.4 The panel unit root test 107

5.2.5 The panel cointegration test 108

5.2.6 The effects of intellectual capital on financial performance across sectors using Dynamic common correlated effects technique 108

5.2.7 The causality relationship flows between sectoral intellectual capital, sector performance and other variables 109

5.3 Intellectual capital and national performance 111

5.3.1 The cross-sectional dependence test 113

5.3.2 The slope homogeneity test 113

5.3.3 The panel unit root test 113

5.3.4 The panel cointegration test 113

5.3.5 The effects of national intellectual capital on national performance using the dynamic common correlated effects 114

5.3.6 The causality relationship flows between national intellectual capital, national performance and other macroeconomic variables 115

5.4 Summary 118

CHAPTER 6 CONCLUSIONS AND IMPLICATIONS 120

6.1 Research findings 120

6.1.1 Measuring intellectual capital 120

6.1.2 The effects of intellectual capital on the performance of firm, sector and nation 122

6.2 Contributions and implications 124

6.2.1 Measuring intellectual capital 124

6.2.2 The effects of intellectual capital on the performance of firm, sector and nation 128

6.3 Limitations and suggestions for future research 131

LIST OF ACRONYMS

ASEAN Association of Southeast Asian Nations

CE Domestic credit to the private sector by banks CEE Capital employed efficiency

DCCE Dynamic common correlated effects

HCE Human capital efficiency

INIC Index of national intellectual capital

LEV The ratio between total debt and total assets of firms MVAIC Modified value-added intellectual coefficient

OLS Ordinary least squares

PCA Principal component analysis

RCE Relational capital efficiency

SCE Structural capital efficiency SICI Sectoral intellectual capital index SIZE The natural logarithm of the total assets

LIST OF FIGURES

Figure 1.1 Real GDP growth trends: Vietnam, ASEAN, and the World 2

Figure 1.2 Infrastructure spending, GDP growth rate, and business environment factors 3

Figure 1.3 Global competitiveness and technological readiness ranking 3

Figure 1.4 Research process 13

Figure 1.5 Research framework 16

Figure 2.1 Saint-Onge’s model 21

Figure 2.2 Sveiby’s model 23

Figure 2.3 Skandia intellectual capital value scheme 24

Figure 2.4 Sullivan’s approach to visualize intellectual capital 25

Figure 2.5 The balanced scorecard 31

Figure 2.6 Brooking’s intellectual capital measurement model 32

Figure 2.7 Intangible assets monitor example 33

Figure 2.8 Skandia navigator 34

Figure 2.9 The DuPont model 47

Figure 3.1 Number of listed firms 62

Figure 4.1 Sectoral intellectual capital index in 2011-2018 period 85

Figure 4.2 An index of national intellectual capital: Lin, Edvinsson, Chen and Beding (2014) index versus the INIC 87

Figure 4.3 National intellectual capital across years by region 89

Figure 4.4 National intellectual capital across years by income 91

Figure 4.5 Accumulation of national intellectual capital across years in some countries 92

Figure 4.6 Accumulation of national intellectual capital across years in Group of Seven 93

Figure 4.7 Accumulation of national intellectual capital across years in Top 10 93

Figure 4.8 The accumulation of national intellectual capital for the Asia-Pacific countries for almost two decades, from 2000 to 2018 95

Figure 4.9 National intellectual capital around the globe 96

Figure 5.1 The causality relationship flows between sectoral intellectual capital, sector performance and other variables 111 Figure 5.2 The causality relationship flows between national intellectual capital, national performance and other macroeconomic variables 117

LIST OF TABLES

Table 2.1 Summary - Sectoral intellectual capital measurements 39

Table 2.2 Summary - National intellectual capital (NIC) measurements 45

Table 2.3 Summary - Intellectual capital and firm performance 54

Table 2.4 Summary - Intellectual capital and sector performance 56

Table 2.5 Summary - Intellectual capital and national performance 59

Table 3.1 Three components, and their proxies, of the new index of national intellectual capital (INIC) 79

Table 4.1 Descriptive statistics of the full sample 82

Table 4.2 Descriptive statistics for financial firms and non-financial firms 83

Table 4.3 National intellectual capital by region 89

Table 4.4 National intellectual capital by income 90

Table 5.1 Regression models 99

Table 5.2 The pairwise correlation coefficients and the variance inflation factor (VIF) among variables 101

Table 5.3 Empirical results using GMM estimations 104

Table 5.4 Regression models 105

Table 5.5 Descriptive statistics 106

Table 5.6 Correlation matrix and the variance inflation factor among variables

Table 5.9 Measurements of variables and data sources 112

Table 5.10 Empirical results - The effects of national intellectual capital on national performance 114

Table 5.11 The causality relationship flows between national intellectual capital, national performance and other macroeconomic variables 116

LIST OF PUBLISHED PAPERS

1 Vo, D H., & Tran, N P (2024) Does national intellectual capital matter for

economic growth in the Asia–Pacific economies? Journal of Intellectual

Capital, 25(2/3), 253-274

2 Vo, D H., & Tran, N P (2024) Sectoral Intellectual Capital and Sector

Performance in an Emerging Market Montenegrin Journal of Economics, 20(2),

209-220

3 Vo, D.H., Van, L.T.-H., Hoang, H.T.-T., & Tran N.P (2023) The interrelationship between intellectual capital, corporate governance and

corporate social responsibility Social Responsibility Journal, 19(6), 1023-1036

4 Vo, D.H., & Tran, N.P (2023) Measuring national intellectual capital and its

effect on country’s competitiveness Competitiveness Review, 33(4), 820-839

5 Tran, N.P., & Vo, D.H (2022) Do banks accumulate a higher level of intellectual

capital? Evidence from an emerging market Journal of Intellectual Capital,

Governance Moderate the Relationship between Intellectual Capital and Firm’s

Performance? Knowledge and Process Management, 29(4), 333-342

8 Vo, D.H., & Tran, N.P (2021) Measuring national intellectual capital: a novel

approach Journal of Intellectual Capital, 23(4), 799-815

9 Vo, D.H., & Tran, N.P (2021) Intellectual capital and bank performance in

Vietnam Managerial Finance, 47(8), 1094-1106

10 Tran, N.P., Van, L.T.-H., & Vo, D.H (2020) The nexus between corporate

governance and intellectual capital in Vietnam Journal of Asia Business Studies,

14(5), 637-650.

CHAPTER 1 INTRODUCTION

This chapter presents and discusses the background and rationales for conducting this study and its novelty concerning intellectual capital measurement and the effects of intellectual capital on the performance of firms, sectors and nations

1.1 Introduction

In the context of the knowledge-based economy, firms enhance their competitive advantage by shifting from tangible assets into intangible assets (Stewart, 1997; Sveiby, 1997) Castro et al (2019) consider that intellectual capital plays a major role in the knowledge-based economy and is the key driver of firm’s sustained competitive advantages Intellectual capital is defined as unique skills, knowledge, and solutions that can be converted into value in the market, leading to an increase in firm’s competitiveness, productivity, and market value (Pulic and Kolakovic, 2003)

The role of intellectual capital in firm’s performance is increasing, so it is necessary to examine the dynamics of this role and the contributions of intellectual capital to firm’s performance Inkinen (2015) demonstrates that firms can benefit from a variety of intellectual capital profiles This means that some businesses require high levels of overall intellectual capital to achieve impressive performance, while others can still achieve positive results with relatively low structural or relational capital In addition, the impact of intellectual capital on a firm performance primarily stems from its combinations, interactions and mediating effects Furthermore, there is substantial proof highlighting the important connection between intellectual capital and a firm's innovation performance (Song, 2022; Inkinen, 2015) Various studies have been conducted to examine the effects of intellectual capital on firm’s performance with a focus on financial firms (Haris et al., 2019; Firer and Williams, 2003) and manufacturing firms (Xu and Wang, 2019) Xu and Li (2019) find a difference in intellectual capital efficiency between high-tech and non-high-tech small and medium-size firms in China The impacts of intellectual capital on firm’s performance in the emerging markets in the Asian region has been examined in previous studies (Indonesia, Soetanto and Liem, 2019; Thailand, Tran and Vo, 2018; Malaysia, Goh, 2005) In particular, Soetanto and

Liem (2019) argue that intellectual capital affects the market-to-book value of the knowledge-based sectors, which have intensively used technology and/or human capital In a study on Thailand’s banking sector, Tran and Vo (2018) conclude that bank profitability is driven mainly by the efficiency of capital employed Goh (2005) asserts that banks have accumulated a lower level of structural capital efficiency than human capital efficiency

Since joining the Association of Southeast Asian Nations (ASEAN), Vietnam has emerged as a country with remarkable national performance and development In recent years, leaders in the miracle of national performance among ASEAN members have been emerging markets, such as Vietnam (OECD, 2018) Figure 1.1 indicates that the pattern of real growth in the gross domestic product (GDP) in Vietnam is stable and higher than that of other emerging countries, such as Indonesia, Malaysia, the Philippines, and Thailand Since 2000, Vietnam's GDP per capita has grown by 6.4 percent annually—one of the fastest rates in the world (Trieu, 2019) In addition, Vietnam has closely integrated into the regional and world economy, with strong trade commitments, such as the European-Vietnam Free Trade Agreement, the Comprehensive and Progressive Agreement for Trans-Pacific Partnership, the Vietnam-Eurasian Economic Union Free Trade Agreement, and the ASEAN–Hong Kong, China Free Trade Agreement, to name a few

Source: IMF (2020)

ASEAN 5: Indonesia, Malaysia, the Philippines, Thailand, and Vietnam

Figure 1.1 Real GDP growth trends: Vietnam, ASEAN, and the World1-2.0%

0.0%2.0%4.0%6.0%8.0%10.0%

In addition, as shown in Figure 1.2, Vietnam has increased its investment in infrastructure to bridge the gap with other ASEAN member countries Vietnam’s spending on infrastructure represents the second fastest among the ASEAN members, 11.5 percent, which is almost doubled the rate of GDP growth for the period 2012-2016 However, the business environment in Vietnam is still maturing The gaps in the institutional quality undermine investors’ confidence Figure 1.2 also indicates that satisfaction with the investment environment is still lower in Vietnam than in other emerging markets in Asia

Source: PwC (2018)

Figure 1.2 Infrastructure spending, GDP growth rate, and business environment factors2

Moreover, based on the 2017-2018 global competitiveness index, Vietnam lagged behind that of other ASEAN members, such as Malaysia, Indonesia, and Thailand Vietnam has a competitive advantage from its relatively low labor costs However, its low technology readiness (in the technology readiness ranking, as presented in Figure 1.3) poses a disadvantage for Vietnam in technological innovation and automation

Source: PwC (2018); Economist Intelligence Unit (2018)

Figure 1.3 Global competitiveness and technological readiness ranking

2 Singapore is not included because of differences in population size, income, infrastructure and technology levels Country

Global Competitiveness Index, institutions pillar ranking,

On the above observations, The Vietnamese firms are facing great opportunities and challenges For example, the ongoing Covid-19 pandemic worldwide puts firms in a new state, a new environment The Vietnamese firms have faced new challenges that have never occurred in the past Therefore, The Vietnamese firms need to be flexible in their production plans, business strategies and images and branding The diversified knowledge-based economy plays an important role in all areas of life and society and gradually replaces the industrial economy, which only focuses on production and consumption In order to meet the important requirements of the knowledge-based economy, firms need to thoroughly utilize the value from intellectual capital – an important intangible asset The development of the knowledge-based economy enhances the role of intellectual capital in businesses and society and pushes it to a new level This practice requires firms to use and implement appropriate and flexible policies to utilize the value of resources, which are considered intangible, from firms including skills, knowledge, innovation, and relationship with customers

1.2 Research problems

Edvinsson and Malone (1997) consider that intellectual capital includes two main categories: human capital and structural capital Pulic (1998) introduces a value-added intellectual coefficient (VAIC) model to measure intellectual capital efficiency This model separates intellectual capital into three components, including (i) human capital, (ii) structural capital and (iii) capital employed Other studies such as Nimtrakoon (2015); Vishnu and Gupta (2014); and Nazari and Herremans (2007) also propose a modified value-added intellectual coefficient (MVAIC) model The MVAIC model has been widely used in measuring intellectual capital efficiency at firms’ level (Bayraktaroglu et al., 2019; Xu and Wang, 2019; Chen et al., 2015)

In addition, the strategy of spreading knowledge of firms is not only for themselves, but also extends to the sector, region and country (Pedro et al., 2018) Medina et al (2007) argue that policymakers can identify solutions to enhance the intangible resources of the sector or region through the analysis of their intellectual capital in order to achieve a sustainable growth Marcin (2013) presents countries around the world are increasingly interested in measuring intellectual capital across sectors As such, it is important and necessary to develop a new sectoral intellectual capital in

accordance with the sectors’ development theories (Pedro et al., 2018) Doing so will promote the management of intangible resources in sectors However, a methodology to measure and evaluate the efficiency of the sectoral intellectual capital has been largely ignored in previous studies

Moreover, at the national level, no widely used or highly recognized methods have been used to measure intellectual capital across nations A limited number of studies (Lin, 2018; Kapyla et al., 2012; Lin and Edvinsson, 2011; Schneider, 2007; Andriessen and Stam, 2005; and Bontis, 2004) with the focus on measuring national intellectual capital have been conducted However, the measurements of national intellectual capital adopted in those studies are very impractical to be widely implemented across nations due to the unavailability of required data and/or an excessive usage of judgements Lin and Edvinsson (2011) paper is a pioneering study in measuring intellectual capital across countries This method is impractical to be implemented for other nations outside the intended samples As such, different approaches in measuring intellectual capital across sectors, particularly across nations, are expected to properly measure intellectual capital across sectors and nations for comparison purposes (Salonius and Lonnqvist, 2012)

In the past three decades, the financial sector has played a crucial role in Vietnam's national performance and development In the context of deepening an integration of the Vietnamese economy into the world economy, the financial sector should effectively utilize both tangible and intangible resources, especially intellectual capital The operations of financial firms are directly related to intellectual capital because they are knowledge-based companies (Buallay et al., 2020) In addition, Firer and Williams (2003) emphasize that financial firms have higher intellectual capital efficiency than other sectors Employees of financial firms exhibit a higher homogeneity of skills and knowledge (Kubo and Saka, 2002) Financial firms operating in a highly regulated environment tend to be more compliant in meeting regulatory expectations while non-financial firms are not As such, these differences result in a different level of intellectual capital across sectors

To the best of my knowledge, contributions of intellectual capital to firm’s performance with a focus on the differences between financial and non-financial firms have largely been ignored in previous studies, particularly in emerging markets such as

Vietnam As such, a study directly targeting an emerging market like Vietnam offers crucial implications for the intellectual capital community including firms’ executives, academics and policymakers This study examines the differences in intellectual capital efficiency between financial and non-financial firms in Vietnam and the contribution of intellectual capital to firm’s performance This dissertation extends the existing literature by developing a new sectoral intellectual capital index (SICI) which can be used to measure a different level of intellectual capital across sectors This study uniquely and strikingly extends the current literature concerning intellectual capital measurement by developing a new index of national intellectual capital (INIC) which is hardly seen in previous studies In addition, the effects of intellectual capital on the performance of firms, sectors and nations are investigated

1.3 Research gap

versus non-financial firms

Various studies have also been conducted to examine the effects and contributions of intellectual capital on the financial performance of non-financial firms Different models are used to calculate the level of intellectual capital, such as the VAIC model (Hoang et al., 2020a; Ghosh and Modal, 2009; Kamath, 2008) and the MVAIC model (Soetanto and Liem, 2019; Sardo and Serrasqueiro, 2017) Previous studies have used different econometric techniques, such as OLS techniques (Chan, 2009; Ghosh and Mondal, 2009; Firer and Williams, 2003) and GMM techniques (Soetanto and Liem, 2019; Sardo and Serrasqueiro, 2017) The findings in previous studies confirm a positive relationship between intellectual capital and firm performance (Soetanto and Liem, 2019; Li and Zhao, 2018; Sardo and Serrasqueiro, 2017; Ghosh and Mondal, 2009) However, other studies confirm a negative relationship between intellectual capital and firm performance (Britto et al., 2014; Morariu, 2014) Chan (2009) and Firer and Williams (2003) also reveal an insignificant relationship between intellectual capital and firm performance Maali et al (2021) explore the links between corporate governance and sustainability performance using the corporate social responsibility of 300 UK firms from 2005 to 2017 They state that corporate governance has a positive impact on sustainability performance In addition, corporate social responsibility plays a fully

mediate role in the relationship between corporate governance and sustainability performance in UK firms Soetanto and Liem (2019) state that capital employed efficiency and structural capital efficiency contribute to firm wealth In this paper, when the sample is divided into industries based on whether they are high-level knowledge-based (those with the intensive use of technology and human capital) and low-level-knowledge based, the results indicate that capital employed has a positive effect on firm performance in those that are high-level-knowledge based

My literature review indicates that the contributions of intellectual capital to firm performance with a focus on the financial and non-financial sectors have largely overlooked in Vietnam The financial sector plays the role of providing financial services to people and businesses This segment includes banks, securities, financial, real estate and insurance firms The main players in Vietnam's financial sector being banks and financial institutions (Zhang et al., 2021) The financial firm plays an important role in national performance in Vietnam by facilitating financial transactions In addition, the value of the assets in the banking system is nearly twice that of its GDP (Trieu, 2019) The banking system in Vietnam plays a leading role in Vietnam's national performance, so the focus on banking becomes important in this study Buallay et al (2020) consider banks knowledge-intensive firms The most important financial firm assets are in the form of intellectual capital A financial firm’s activities are mainly related to intellectual capital, such as brand building and human resources Financial firm employees exhibit greater homogeneity than employees in other sectors (Kubo and Saka, 2002) Moreover, it has been argued that banking has accumulated higher levels of intellectual capital than other sectors (Firer and Williams, 2003) The current literature considers that staff identity is important because intellectual capital is one of the key measures for assessing the competence of employees In addition, financial firms operating in a heavily regulated environment, whereas non-financial firms are not, resulting a different levels of intellectual capital efficiency However, to the best of my knowledge, the impact of intellectual capital on the performance of firm with a focus on the differences between financial and non-financial firms has been overlooked in intellectual capital literature, particularly in emerging markets such as Vietnam

Ali et al (2022) argue that intellectual capital consists of three main components: human capital, structural capital and relational capital Human capital contributes to firm

performance through the competence and creativity of employees, allowing them to identify, create new knowledge and solve problems (Xu and Li, 2019) Structural capital includes procedures and processes, human resource policies and guidelines for labor management practices such as recruitment, task management, patents, intellectual property (Sardo and Serrasqueiro, 2017) Human capital utilizes structural capital to increase firm performance (Soetanto and Liem, 2019) Relational capital encompasses the relationships with stakeholders that allow for certain behaviors and sustainable relationships (Tran and Vo, 2018) Relational capital facilitates accessing, processing, synthesizing, and exchanging knowledge within and across corporate influences on firm performance (Maali et al., 2021)

Liu et al (2021) state that intellectual capital plays the important role of intangible assets, it helps to exploit important knowledge that affects the innovation ability of firms, sectors and regions Marcin (2013) emphasizes that intellectual capital is a fundamental resource for value creation at the sectoral, regional and national levels

In addition, from being one of the poorest countries in the world in the mid-1980s, Vietnam has achieved rapid national performance and sustainable development goals in the last 10 years (Baum, 2020) These achievements of Vietnam are based on broad-based economic reforms and national development strategies, focusing on five main sectors: education, health, roads, water and electricity infrastructure (Baum, 2020) Nguyen and Gregar (2018) emphasize the role of knowledge management in innovation of Vietnamese firms Besides, Nguyen et al (2021) also affirm that intellectual capital has a positive influence on firm’s performance in Vietnam Dutt (1990) asserts that imbalance between sectors can slow down economic development In particular, the coronavirus pandemic affects the economies of countries around the world in a "K-shaped recovery" The characteristic of this type of recovery is that some sectors will improve, while others will continue to decline (Nikkei, 2021) Hence, it is necessary to measure and evaluate the efficiency of intellectual capital across sectors in Vietnam and other emerging markets

Previous studies have measured intellectual capital in the firm level (Phusavat et al., 2011; Hoang et al., 2020b) and national level (Lin and Edvinsson, 2011; Bontis,

2004) In addition, measuring intellectual capital at the regional level has also been considered in previous studies, such as regional level in France (Edvinsson and Bounfour, 2004); 29 provinces and cities of China (Xia and Niu, 2010); 8 Russian federal districts (Markhaichuk and Zhuckovskaya, 2019) Besides, various regional intellectual capital measurements have been introduced, such as intellectual capital dynamic value (Edvinsson and Bounfour, 2004), principal components analysis and cluster analysis (Xia and Niu, 2010); data envelopment analysis (Nitkiewicz et al., 2014); multiple-criteria decision-making (Liu et al., 2021)

However, the issue of measuring intellectual capital at the sector level has been largely ignored in previous studies Based on the modified value-added coefficient (MVAIC) model, this study proposes a sectoral intellectual capital index (SICI) by examining the intellectual capital efficiency of each firm in the sector In addition, the author uses total assets as a weight to construct the intellectual capital index of the sector Moreover, this dissertation examines the impact of intellectual capital on sector performance in Vietnam

The Asia-Pacific region is considered the fastest-growing region globally, contributing two-thirds of the global growth The region includes China and Japan, two of the world's three largest economies (Business Insider, 2020) In addition, the region is also home to some of the fastest-growing countries in the world, such as Vietnam (World Bank, 2020a) The S&P (2020) report stresses that the Covid-19 "shadowed" the economic prospects of the Asia Pacific region, leading to shocks in domestic supply and demand in Japan and South Korea, as well as weakening the demand from external markets such as the US and Europe Based on the report, economies in the region are suffering the double effect of weakening demand and a supply reduction Countries in the Asia Pacific region are gradually changing new production methods and new customer approaches The role of intangible assets, such as automated manufacturing technologies and online sales services, has gradually asserted the importance of creating and maintaining a competitive advantage In particular, Stahle et al (2015) state that conducting more detailed analyzes of the role of national intellectual capital in different economies would also add value to intellectual capital literature

Classifying intellectual capital into three distinct levels — firm, sector, and nation — ensures a comprehensive and multidimensional approach to research (Svarc et al., 2021) Rather than solely focusing on intellectual capital at the enterprise level, this dissertation delves deeper into measuring intellectual capital across all three levels to gain a nuanced understanding of its significance and impact on performance This classification and measurement framework offers flexibility and applicability across various contexts, allowing for tailored research and theoretical methods at each level, ranging from the specific context of individual firm to the broader scope of sector and nation

By examining intellectual capital management strategies and measures at the firm, sector, and nation levels, this dissertation aims to provide specific and practical recommendations for businesses and policymakers This approach enables the identification of trends and challenges in intellectual capital management and development at each level, facilitating a deeper understanding of potential issues and opportunities for businesses and the economy as a whole Ultimately, this dissertation contributes to informed decision-making and policy formulation by shedding light on the dynamics of intellectual capital across different levels of analysis

Understanding the impact of national intellectual capital on national performance is essential for businesses to navigate the complexities of the global business environment effectively (Lin, 2018) Research into national intellectual capital yields valuable insights that can inform strategic management decisions and guide business actions in an increasingly competitive landscape The findings of this dissertation can directly inform business management and development practices, providing actionable intelligence for administrators and governments to formulate policies aimed at optimizing the utilization of intangible assets, particularly intellectual capital

As the knowledge economy continues to evolve, research on national intellectual capital occupies a crucial position within the realm of modern business administration and economics (Svarc et al., 2021) This dissertation not only informs current business practices but also shapes future trends and forecasts in firm strategy development and corporate governance By shedding light on the dynamics of intellectual capital, this dissertation field contributes to a deeper understanding of the factors driving national

performance and innovation, thereby facilitating informed decision-making at both organizational and governmental levels

1.4 Research objectives

This study has the overarching objective of measuring intellectual capital at the firm, sector and nation levels In addition, this dissertation also examines the impacts of intellectual capital on the performance of firms and sectors; and on national performance, which is effectively the economic performance of the countries

The objectives of this study are summarized as follows:

1) To measure intellectual capital for firms, sectors and nations Specifically,

I use the modified value-added intellectual coefficient (MVAIC) model to measure intellectual capital of financial and non-financial firms in Vietnam I also examine the difference in intellectual capital of these two groups of firms: financial versus non-financial firms Furthermore, I develop a new sectoral intellectual capital index (SICI) to measure the intellectual capital of 12 sectors in Vietnam In addition, I extend the existing literature by developing a new index of national intellectual capital (INIC) to measure intellectual capital at the nation’s level I then use this newly developed INIC index to measure a degree of intellectual capital for 104 countries globally

2) To examine the effects of intellectual capital on the performance of firms, and sectors, and nations This dissertation employs a measured level of

intellectual capital at firms, sectors, and nations’ levels to investigate the effects of intellectual capital on the performance of firms, sectors and nations Various econometric methods are utilized to ensure the validity and robustness of the findings when examining these effects Drawing on a comprehensive review of previous research, performance at the firm and sector levels is assessed using return on total assets and return on equity metrics In addition, national performance is measured using GDP per capita By employing these metrics and methodologies, this dissertation aims to provide a thorough

analysis of the relationship between intellectual capital and performance

across multiple levels of analysis 1.5 Research questions

In achieving the research objectives, this dissertation attempts to answer the following research questions:

1) What are the differences in intellectual capital level between financial and financial firms in Vietnam? And what are potential advancements in measuring intellectual capital at the sectors and nations’ levels?

non-2) What are the effects of intellectual capital on the performance of firms and sectors in Vietnam; and on performance of nations?

1.6 Research subject and scope

Measuring intellectual capital and the effects of intellectual capital on the performance of firms, sectors and nations are the subjects of the dissertation

For a research scope for firms and sectors, the research scope covers 150 listed firms on the Vietnam’s stock market in the period 2011-2018 For the nations, the scope of the study covers 104 countries in the 2000-2018 period

1.7 Contributions of the study

This study contributes to the existing literature on intellectual capital in the following respects

- First, this dissertation investigates the differences in intellectual capital

efficiency between the financial and non-financial sectors in Vietnam The effects of intellectual capital on firm’s performance in Vietnam are then examined Vietnam is an emerging market in the Southeast Asia, one of the most dynamic economies in the region and the world Managerial implications are important for the intellectual capital community, including academics, policymakers, and practitioners This dissertation provides the bridge to fill the current gap

- Second, this study extends the current literature by developing a new measure

of intellectual capital at the sector level - a new sectoral intellectual capital

index (SICI) The SICI can now be used to investigate various aspects of the sectors with intellectual capital efficiency in Vietnam

- Third, a new index of the national intellectual capital (INIC), one of the first

of its kind, is developed to measure the different levels of intellectual capital across nations globally This new index includes the following fundamental attributes: (i) simplicity - a new index should be simple to calculate; (ii) quantification – a new index should be easily quantifiable without using judgments; (iii) market relevance – a new index should be able to reflect the prevailing market and economy conditions; and (iv) international comparison – a new index should be practically implemented for comparison purposes across countries regardless of the level of national performance and development

1.8 Research framework and steps

Based on the theoretical foundations and empirical research conducted in relation to the field of study, the analytical framework is proposed Research data will be collected and analysis will be performed The research process is described specifically as follows:

Source: Author's synthetic

Figure 1.4 Research process

Research problems

Review of the theoretical foundation and previous studies

Collect data

Analyze and interpret data

Conclusions and implications

• First, research needs to conduct a rigorous theoretical overview to find (i) the theory of intellectual capital and its measurements; factors affect the performance of firms, sectors and nations (ii) variables commonly used in research models in the world, and (iii) research gaps academic

• After identifying the above factors, the second step of the study is to determine the data set to be used to ensure the feasibility of the project Research to collect annual data on intellectual capital at firm, sector and nation These figures are publicly announced in the annual reports of the firms In addition, the data on the new national intellectual capital index is extracted from the source of the World Bank Development Indicators

• Third, this study uses panel data to conduct the study With the data collected and through the theoretical review, this study intends to use econometric methods suitable for the data set in order to solve potential problems (unit root, autocorrelation…), to obtain the best estimate results

• Fourth, after achieving the experimental results, the research needs to explain, discuss the results

• Last but not least, the study concludes on intellectual capital measurements and the effects on performance of firms, sectors and nation Along with that, the study proposes solutions to promote efficiency in the use of intellectual capital, contributing to increase the efficiency of firm, sectors and countries The core of this research is intellectual capital As shown in Figure 1.4, I consider intellectual capital from two perspectives: measuring intellectual capital and examining the effect of intellectual capital on performance In addition, this dissertation also considers at all 3 levels: firm, sector and nation

• For the measure of intellectual capital: I use the structural model and the MVAIC method to measure intellectual capital at the firm level, and compare the difference in intellectual capital between financial and non-financial firms At the sectoral and national level, I propose new intellectual capital measurement, namely sectoral intellectual capital index (SICI) and index of national intellectual capital (INIC)

• For examining the effects of intellectual capital on performance, this dissertation uses two common measures, return on assets (ROA) and return on equity (ROE), to measure performance at the firm and sector levels As for the country level, I use GDP per capita as a measure of national performance

Source: Author's synthetic

Figure 1.5 Research framework

Intellectual capital

Intellectual capital measurements

The effects of intellectual capital on performance

Firm level

Sector level

National level Modified value-added

intellectual coefficient (MVAIC) model

Sectoral intellectual capital index (SICI)

Index of national intellectual capital (INIC)

- Return on assets (ROA) - Return on equity (ROE)

- Return on assets (ROA) - Return on equity (ROE)

Economic growth

1.9 The outline of the dissertation

This dissertation is structured into six chapters to present a comprehensive summary of relevant literature and empirical evidence in response to the above-mentioned research questions Each of the chapters is as follows

Chapter 5

Empirical results relating to the effects of intellectual capital on the performance of firms, sectors and nations are presented and discussed in this chapter

Chapter 6

Chapter 6 presents a summary of key findings and conclusions of this study This chapter presents the main findings and the contributions of this study The potential areas for further research are also discussed

1.10 Summary

In Chapter 1, the author primarily outlines the overarching research objectives of the study, encompassing the measurement of intellectual capital across enterprise, industry, and national strata Furthermore, this dissertation delves into the analysis of how intellectual capital influences the performance of individual firms and sectors, as well as its impact on overall national performance Chapter 1 also identifies and expounds upon the research gap, which serves as the impetus driving the author's engagement with this dissertation Moreover, this chapter elucidates the research's focal subject and its scope, research inquiries, contributions to the field, and delineates the procedural steps of the study Subsequently, the succeeding Chapter 2 embarks upon an extensive literature review

CHAPTER 2

LITERATURE REVIEW

In this chapter, an exposition is undertaken to provide a comprehensive survey of intellectual capital quantification across the dimensions of individual firms, sectors, and national contexts Moreover, the fundamental theories underpinning the relationship intellectual capital and the performance of firm, sector and nation are comprehensively expounded upon and examined

2.1 Definitions and classifications

The concept of intellectual capital is first mentioned by Senior (1836) Intellectual capital is described as an important resource in creating a firm wealth, but it is not recorded on the balance sheet (Xu and Liu, 2020) Ali et al (2022) argue that intellectual capital is a value not only in terms of monetary returns but also in terms of environmental, social and economic issues Intellectual capital is the sum total of all employee competencies and skills that create company wealth (Shahwan and Habib, 2020) The definition of intellectual capital covers different levels, including firm, sector and nation St-Pierre and Audet (2011) suggest that there is consensus on the significant contribution of intellectual capital to value creation, but there is no generally accepted definition of intellectual capital Stewart (1997) defines intellectual capital as an intangible value created for people Sullivan (2000) states that intellectual capital, which is considered as knowledge of the company, could be converted into tangible profits Bontis and Fitz-enz (2002) note that intellectual capital consists of knowledge, experience, intellectual literature, intellectual property, and information that can be used to create value and to increase competitiveness In addition, Sardo and Serrasqueiro (2017) argue that intellectual capital is about the hidden value of a firm However, currently available definitions of intellectual capital refer to an intangible nature of capital based on implicit knowledge, and its ability to create value (Vishnu and Gupta, 2014; Roos et al., 1997; Stewart, 1997; Brooking, 1996; Edvinsson and Sullivan, 1996) The difference between the market value and the book value of a firm has been considered the most obvious indicator of intellectual capital because this difference

represents the economic value of intangible capital (Maditinos et al., 2011) In the following section, I will present several models of intellectual capital classification

Westberg and Sullivan (1998) point out that Saint-Onge's model explores the tangible and intangible role of knowledge in different types of intellectual capital and how these factors are valued Saint-Onge's contributions, particularly through his work in the late 1990s and early 2000s, have provided a comprehensive approach to identifying and leveraging intellectual capital to enhance organizational performance This model underscores the importance of knowledge and relationships in driving value creation within organizations (Pulic, 1998) Saint-Onge’s model categorizes intellectual capital into three primary components, each highlighting different dimensions of intangible assets Human capital refers to the collective skills, expertise, and competencies of employees This component emphasizes the value that individuals bring through their knowledge, innovation, and ability to solve problems Structural capital encompasses the supportive infrastructure, processes, databases, and intellectual property that facilitate an organization’s operations It includes organizational culture, routines, and procedures that enhance efficiency and productivity Relational capital involves the relationships an organization maintains with external stakeholders, including customers, suppliers, partners, and communities (Bontis, 1998) This component focuses on the value derived from strong, trust-based relationships and the organization’s reputation and brand The integration of these components is a key aspect of Saint-Onge’s model, advocating for a synergistic effect that enhances overall organizational performance By recognizing the interplay between human, structural, and relational capital, organizations can better understand how to leverage these assets for sustained competitive advantage This integrated approach ensures that investments in one area (e.g., training employees) are supported by improvements in other areas (e.g., enhancing IT systems and strengthening customer relationships) Saint-Onge’s model is particularly influential in the field of knowledge management By emphasizing the importance of human and structural capital, the model provides a framework for capturing, sharing, and utilizing organizational knowledge effectively This approach helps organizations to foster a culture of continuous learning and innovation In strategic

leveraged to achieve strategic goals By focusing on the holistic view of intellectual capital, managers can develop strategies that align with the organization’s strengths and address its weaknesses This alignment ensures that resources are allocated efficiently to support long-term growth and sustainability (Gates and Langevin, 2010) Traditional performance measurement systems often overlook the value of intangible assets Saint-Onge’s model addresses this gap by providing a structured approach to evaluate intellectual capital This includes assessing the impact of human skills, organizational processes, and external relationships on overall performance Such comprehensive measurement allows for better decision-making and enhances transparency in reporting organizational value

While Saint-Onge’s model offers a robust framework for understanding intellectual capital, it has faced some criticisms Quantifying intangible assets like human skills and relational capital can be subjective and complex, making it difficult to implement the model effectively Integrating Saint-Onge’s model with traditional financial metrics can be challenging, potentially leading to inconsistencies in reporting Additionally, the rapidly changing business environment means that the components of intellectual capital can evolve quickly, requiring continuous updates and adaptations to the model (Pulic, 1998)

Source: Westberg and Sullivan (1998)

Figure 2.1 Saint-Onge’s model

Human capital

Structural capital

Customer capital

2.1.2 Sveiby’s model

Sveiby (1997) considers that employees are important actors and their actions will create the assets and structure of the business, whether tangible or intangible Introduced in the late 1990s, Sveiby’s model emphasizes the importance of knowledge and competence in driving organizational performance and innovation This model is instrumental in highlighting the critical role of intangible assets, often overlooked in traditional accounting and management practices As presented in Sveiby’s model categorizes intellectual capital into three main components: individual competence, internal structure, and external structure Individual competence refers to the knowledge, skills, and experience possessed by employees It underscores the value that individuals bring to the organization through their expertise and ability to solve problems and innovate Internal structure encompasses the internal capabilities of the organization, including processes, databases, organizational culture, and intellectual property This component represents the systems and infrastructure that support and enhance the productivity of employees External structure involves the relationships and networks an organization maintains with external stakeholders, such as customers, suppliers, partners, and the broader community This aspect of the model highlights the importance of reputation, brand, and customer loyalty in contributing to organizational value ( Li and Zhao, 2018)

One of the key strengths of Sveiby’s model is its emphasis on the dynamic interplay between these components By recognizing that intellectual capital is not static but constantly evolving, Sveiby’s model encourages organizations to continually invest in and develop their intangible assets For example, improving individual competence through training and development can enhance the internal structure by fostering innovation and efficiency Similarly, strong external relationships can lead to increased customer loyalty and better market positioning, which, in turn, supports overall organizational growth (Sardo and Serrasqueiro, 2017)

In practical applications, Sveiby’s model is particularly valuable for strategic management and knowledge management In strategic management, the model helps organizations identify and leverage their intellectual capital to achieve competitive advantages By focusing on the holistic view of intangible assets, managers can develop

strategies that align with the organization’s strengths and address its weaknesses This comprehensive approach ensures that resources are allocated effectively to support long-term growth and sustainability In the realm of knowledge management, Sveiby’s model provides a framework for capturing, sharing, and utilizing knowledge within the organization By emphasizing the importance of individual competence and internal structure, the model facilitates the creation of a culture of continuous learning and improvement (Soetanto and Liem, 2019)

However, despite its many strengths, Sveiby’s model also faces some criticisms and limitations One of the primary challenges is the difficulty in measuring and quantifying intangible assets Unlike tangible assets, intellectual capital is often subjective and complex to evaluate, which can lead to inconsistencies and challenges in implementation Additionally, integrating Sveiby’s model with traditional financial metrics can be challenging, as conventional accounting systems are not designed to capture the value of intangible assets effectively (Li and Zhao, 2018; Ghosh and Mondal, 2009)

Visible Equity

(Book value) Tangible assets minus

structure, manual systems, R&D,

software)

Individual competence

(education, experience)

Source: Sveiby (1997)

Figure 2.2 Sveiby’s model

The Skandia Navigator, introduced by Edvinsson and Malone (1997), is a groundbreaking framework for measuring and managing intellectual capital This model marked a significant advancement in acknowledging the importance of intangible assets within organizations Utilizing a five-dimensional approach, the Skandia Navigator provides a comprehensive perspective on organizational performance (Brennan, 2001) The financial dimension covers traditional financial metrics to evaluate the company's

economic outcomes The customer dimension assesses customer satisfaction, loyalty, and market share The process dimension looks at internal processes, efficiency, and effectiveness The renewal and development dimension reflects innovation, research and development activities, and organizational learning Lastly, the human dimension focuses on metrics related to employee skills, competencies, and satisfaction (Edvinsson and Malone, 1997)

Source: Roos et al (1997); Edvinsson and Malone, (1997)

Figure 2.3 Skandia intellectual capital value scheme

Sullivan (2000) determines that intellectual capital includes 2 main components: human capital and intellectual assets Human capital includes the organization’s employee intellect, which provide know-how and institutional memory to the firm In addition, intellectual assets are defined as firm's tangible or physical description of specific knowledge It includes the source of innovations and competitive edge, which are generated from the various processes undertaken by the organization Moreover, intellectual assets include intellectual property, namely, trademarks, patents, trade secrets, copyrights

Market value

Financial capital Intellectual capital

Human capital Structural capital

Customer capital Organizational capital

Innovation capital Process capital