To the author's knowledge, there has been no previous article researching in the effect of IC on COD with the moderation role of bankruptcy risksand ownership structure in the Vietnamese
Problem statement
Knowledge is essential in today’s society, influencing concepts such as knowledge society, knowledge economy, and knowledge management (Kăpylã et al., 2012) The transition from a tangible to an intangible economy, driven by technological advancements and globalization, necessitates organizational change for competitiveness (Drucker, 1993; Bataineh et al., 2022) Effective management of intangible assets, particularly knowledge assets, is crucial for achieving sustainable competitive advantages (Torres et al., 2018) Organizations must commit to long-term learning and invest in their intellectual potential to harness these advantages (Trajkovic, 2018) Intellectual capital (IC), comprising all intellectual resources both internal and external to the organization, plays a significant role in this context (Nahapiet & Ghoshal, 1998; Youndt et al., 2004) IC can be transformed into tangible and intangible value, making it increasingly attractive to institutions and researchers (Lentjusenkova & Lapina, 2016) However, in Vietnam, there is a lack of IC research due to insufficient awareness among managers regarding its significance in management processes (Trinh & Nguyen, 2023).
Despite extensive research on intellectual capital (IC) and its impact on firm performance, the relationship between IC and the cost of debt (COD) remains underexplored Most studies, including 189 out of 777 reviewed papers, focus on IC's influence on performance, particularly in Vietnam, where limited access to capital hinders enterprise growth Effective management plays a crucial role in resource utilization, impacting firms' access to capital and their ability to invest in IC COD serves as a measure of credit security, with lower COD indicating better credit status for firms While managers may undervalue IC, they recognize the importance of reducing COD to lower expenses and facilitate funding IC reports have been shown to positively influence credit decisions by highlighting competitiveness and effective management Additionally, implementing robust risk management strategies can lead to lower risks, resulting in lenders offering reduced COD This study aims to investigate the impact of IC on COD for listed companies on the Vietnam stock exchange from 2008 to 2022.
It is important to deepen some aspects that may moderate the relationship between
This study investigates the correlation between intellectual capital (IC) and cost of debt (COD), focusing on the moderating role of external factors, specifically bankruptcy risk as measured by Altman’s Z-Score Recognized as a leading indicator of a firm's financial distress, the Altman Z-Score helps assess how varying levels of bankruptcy risk influence the relationship between IC and COD By analyzing this moderating effect, the research aims to determine if the impact of IC on COD differs across firms with varying bankruptcy probabilities.
The ownership structure, encompassing both state-owned and foreign-owned enterprises, significantly influences the relationship between intellectual capital (IC) and cost of debt (COD) Research indicates that state-owned enterprises often enjoy lower financing costs (Sanchez-Ballesta & Garcia-Meca, 2011), while a higher proportion of foreign ownership is associated with a decrease in COD (Tran, 2021) Consequently, this study aims to explore the moderating effects of ownership structure, specifically focusing on state ownership and the percentage of foreign ownership.
Research objectives and research questions
- Research objectives: The research provides empirical evidence on the impact of
This article examines the impact of intellectual capital (IC) on the cost of debt (COD) for companies listed on the Ho Chi Minh City Stock Exchange and the Hanoi Stock Exchange in Vietnam from 2008 to 2022 Additionally, it investigates the moderating effects of bankruptcy risk and ownership structure on the relationship between IC and COD, providing insights into how these factors influence corporate financing.
The study focuses on solving the following research questions:
(1) Does IC impact the COD of Vietnamese listed companies?
(2) Does bankruptcy risk moderate the relationship between ĨC and COD among Vietnamese listed companies?
(3) Does ownership structure (state ownership and foreign ownership) alter the relationship between IC and COD in Vietnamese listed companies?
Research object and research scope
- Research object: The impact of IC on COD in a corporate context.
This research focuses on Vietnamese listed companies, specifically those operating on the Ho Chi Minh City Stock Exchange (HOSE) and the Hanoi Stock Exchange (HNX), while excluding financial firms and insurance institutions.
+ Research scope in terms of time: from 2008 to 2022.
Research methods
The research uses quantitative methods with secondary data to test all the research models (Descriptive statistics, Fixed effect model with cluster) The author uses STATA 15.0 software for this research.
Research contribution
- Theoretical contribution: First research focusing on the impact of IC on COD and the moderating effect of state ownership on this correlation of Vietnamese listed companies from 2008 to 2022.
By researching the impact of IC on COD under the moderating role of bankruptcy risks and ownership structure, this research contributes to practice as follows:
Understanding the impact of Intellectual Capital (IC) on Cost of Debt (COD) enables companies to make informed investment decisions in Human Capital (HC) This research indicates that IC, particularly HC, remains valuable even in challenging financial conditions, leading to optimized financing strategies and lower borrowing costs.
Understanding the impact of intellectual capital (IC) on financing costs can enhance creditor confidence, as creditors tend to prefer firms with higher IC capacity, viewing them as lower-risk investments.
The research offers valuable benchmarks and best practices for companies aiming to enhance their intellectual capital (IC) and financing strategies By studying successful case examples, firms can adopt similar methods to improve their financial results and optimize their overall performance.
Thesis structure
The structure of this thesis is as follows:
This chapter sets the foundation for the research by outlining the problem statement and formulating the research question It highlights the significance of the study and offers a concise overview of the thesis structure, ensuring clarity and coherence throughout the research.
Chapter 2: Literature review and hypothesis development
This chapter delves into existing research on the topic, summarizing key findings, identifying gaps in the literature, and explaining how the current study contributes to the field.
This chapter outlines the data collection process, detailing the sources of data, sampling techniques, and methods of data analysis It emphasizes the selected methodology and its relevance to the research question, ensuring a coherent alignment with the study's objectives.
Chapter 4: Research results and Discussion
This chapter presents the research findings through a detailed analysis and interpretation of the data It discusses the implications of these results, compares them with previous studies, and recognizes any limitations encountered Furthermore, it proposes avenues for future research.
This chapter summarizes the key findings of the study, reiterates the research question, and highlights the significance of the results.
LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT 2.1 Concepts
Intellectual Capital
Intellectual Capital (IC) lacks a universally accepted definition or categorization scheme, as highlighted by Brennan and Connell (2000) Various industries and theories define IC in diverse ways, leading to the use of multiple terms to describe this complex concept, as noted by Marr and Moustaghfir.
In the realm of intellectual capital (IC), terms like assets, resources, and performance drivers are often used interchangeably with descriptors such as "intangible," "knowledge-based," and "non-financial" (Augicr & Tcccc, 2018) According to Giuliani and Marasca (2011), the interpretation of the IC concept varies based on the specific context of its application, highlighting the challenge of establishing a universal definition in academic discourse.
Intellectual Capital (IC) encompasses an organization’s intangible assets, which include its innovative processes, capacity for innovation, patents, and the collective knowledge and skills of its members Additionally, IC reflects the organization's societal recognition and the strength of its collaborative networks, highlighting the importance of these elements in driving organizational success.
Intellectual Capital (IC) is considered an intangible asset that significantly enhances an organization's value and performance It encompasses various components, including human capital, business processes, information and communication technologies, and other intangible assets These elements can be converted into both tangible and intangible value, highlighting the crucial role of IC in organizational success.
Intellectual Capital (IC) is fundamentally linked to human capital (HC), relational capital (RC), and structural capital (SC), encompassing the knowledge, information, intellectual property, and experience of individuals within an organization (Edvinsson, 1997; Carson et al., 2004) The research community widely recognizes these three components—HC, RC, and SC—as essential elements of IC (Edvinsson & Sullivan, 1996) Effective management of these elements can significantly enhance IC's potential to generate wealth, making it an indispensable focus for managers (Brennan & Connell, 2000) The following sections will delve deeper into each of these components.
Human Capital (HC) is a crucial component of Intellectual Capital (IC), significantly influencing innovation, growth, and corporate longevity (Zane, 2022) Defined as the capacity of individuals to perform in specific situations (Brennan & Connell, 2000), HC encompasses training, knowledge, skills, attitudes, intellectual agility, experience, and awareness among both employees and managers (Barney, 1991; Edvinsson & Sullivan, 1996; Jardon, 2015) Essentially, HC reflects the intelligence of employees, with its scope limited to their intrinsic knowledge, which may exist prior to or develop after their recruitment, making HC a personal asset that employees carry with them at all times (Bontis, 1998; Lentjusenkova & Lapina, 2016).
Structural Capital (SC) is a vital component of Intellectual Capital (IC), encompassing a firm's frameworks and processes that persist even when employees leave (Lentjusenkova & Lapina, 2016) Unlike Human Capital (HC), SC can be owned and traded (Bontis, 2001) Key elements contributing to effective SC include administrative systems, internal organizational structures, processes, information systems, and organizational culture (Tseng & Goo, 2005) SC can be categorized into two perspectives: the explicit, which includes manuals, databases, and intellectual property (Bontis, 2001), and the implicit, which relies on subjective characteristics shaped by individuals' experiences, values, and beliefs (Beltramino et al., 2020) Moreover, SC plays a crucial role in minimizing costs and maximizing profits per employee, making it an essential factor for measuring IC at the organizational level (Bontis, 1998).
(HC), but if the organization has poor systems and processes (SC) to manage that employee’s actions, the overall IC will not exploit its full potential.
The final component of intellectual capital (IC) is relational capital (RC), which highlights that businesses function as systems of value generated through relationships with customers, suppliers, shareholders, and various stakeholders, both internal and external (Hormiga et al., 2010) Relational capital represents the value embedded in commercial connections, collaboratively created by the company and its partners (Kale et al., 2000; Miocevic).
2016) Relational capital refers to strong relationships developed over time, and they are linked to a decreased demand for administrative forms of governance (Miocevic,
2016) It can be measured (albeit with difficulty) as a function of firm longevity (i.e
RC becomes more valuable over time) (Bontis, 1998).
Cost of Debt
The cost of debt (COD) is the interest rate applied to external debt, serving as a vital metric for comparing various financing methods (Tanin et al., 2024) It plays a significant role in helping firms evaluate investment opportunities and assess their financial performance (Baule, 2018) The determination of COD can vary based on research context, but it is often calculated as the ratio of interest expenses to total debt, reflecting the enterprise's debt relationship and providing a more precise estimate of debt financing costs (La Rosa et al., 2018; Fonseka et al., 2019).
An alternative method for determining the cost of debt is through the loan spread, as highlighted by Graham et al (2008), Bharath et al (2009), Ertugrul et al (2017), and Amin et al (2023) This approach utilizes the natural logarithm of the all-in-loan spread, which reflects the extra basis points a borrower pays over the London Interbank Offered Rate (LIBOR) or a similar benchmark The all-in-loan spread accounts for all upfront fees prorated over the loan's duration However, since LIBOR is not widely used in Vietnam, this research adopts an alternative method to better align with the realities of the Vietnamese market.
Theoretical literature
Strategically, resources and competencies are crucial for achieving long-term competitive advantage and business success A key subset of these critical resources is intellectual capital (IC), which can be understood through the Resource-Based View (RBV) The RBV framework illustrates how companies acquire and sustain their competitive advantages by focusing on internal resources and capabilities, rather than merely on products This approach emphasizes that such resources are difficult for competitors to imitate or substitute due to isolating mechanisms and efficiency improvements Additionally, the RBV highlights the importance of leveraging knowledge asymmetries and exploiting imperfect information to differentiate firms in the marketplace.
The Knowledge-Based View (KBV) extends the Resource-Based View (RBV) by emphasizing the critical role of knowledge, a socially complex and partially tacit resource, in achieving sustained competitive advantages Building on Barney's original criteria—value, rareness, imitability, and substitutability—KBV integrates the concept of social complexity to deepen the understanding of how organizational resources foster lasting competitive advantage Firms are seen as knowledge integration institutions, focusing on the internal knowledge of employees and the organization as a whole This aligns with the definition of "human capital" in Intellectual Capital (IC), which highlights the knowledge possessed by managers and employees Additionally, KBV underscores the importance of organizational structure in facilitating knowledge integration, with management playing a key role in coordinating these efforts Ultimately, the competencies of individuals are regarded as the primary intangible resource in developing a knowledge-based strategy, as they are capable of transmitting and converting information to create value both internally and externally.
Intellectual Capital (IC) is a compelling area of research, yet studies on IC in Vietnam remain limited The predominant focus of IC research in Vietnam centers on its impact on firm performance across various industries (Tran, 2020; Trinh, 2020; Ngo, 2024) Other research streams explore different aspects of IC, including its mediating role in various relationships (Doan et al., 2023), its effects on other factors (Trinh & Nguyen, 2023), and the influence of factors such as governance, board size, and board diversity on IC (Van et al., 2022; Pham, 2023) However, these alternative streams are relatively minor compared to the primary focus on IC's impact on firm performance.
Numerous studies have explored the impact of intellectual capital (IC) on firm performance, consistently highlighting a positive correlation Research conducted by Ngo (2024) examined the effects of IC on the return on assets (ROA) and return on equity (ROE) of 90 publicly listed Vietnamese firms across nine industries from 2014 onwards, reinforcing the notion that effective management of intellectual capital significantly enhances overall firm performance.
In 2022, a regression analysis revealed that firm operational efficiency is significantly influenced by intellectual capital (IC) The study demonstrated that the components of IC—human capital (HC), structural capital (SC), and employed capital (CE)—positively impact firm performance, although structural capital efficiency (SCE) showed no effect on return on equity (ROE) This research, building on Tran (2020), utilized a sample of 37 consumer goods companies categorized by GICS standards, all of which are listed on the Ho Chi Minh City Stock Exchange.
From 2015 to 2019, research indicated that Intellectual Capital (IC) and its components, including Capital Employed Efficiency (CEE) and Human Capital Efficiency (HCE), positively impacted Return on Assets (ROA) A similar study conducted on 45 listed firms in Vietnam from 2011 to 2017 confirmed that IC, as measured by the Value-Added Intellectual Coefficient (VAIC), also positively influenced ROA, which is a key indicator of firm performance Furthermore, Trinh (2020) extended this research to the banking sector, reinforcing the positive relationship between IC and ROA.
Intellectual Capital (IC) significantly enhances the financial performance of the Vietnamese banking sector, as evidenced by a study analyzing data from 30 banks between 2011 and 2019 Utilizing the VAIC model developed by Pulic (1998) alongside quantitative research methods, the study highlights that both Human Capital Efficiency (HCE) and Structural Capital Efficiency (SCE) are key components of IC Notably, SCE plays a crucial role in boosting profits and interest income for banks, underscoring its importance in the industry.
In another stream of research about the effect of other factors on IC, Van et al
A study conducted in 2022 utilizing the Modified VAIC model (MVA1C) analyzed 120 observations from 2011 to 2018, revealing a positive correlation between corporate governance, social responsibility, and intellectual capital (IC) This indicates the importance of responsible practices in enhancing the development and effective utilization of intellectual capital.
The governance mechanisms of enterprises significantly impact intellectual capital (IC) efficiency Research by Pham (2023), which analyzed annual financial statements from 30 Vietnamese commercial banks between 2010 and 2022 using the FGLS estimation method, revealed that board diversity positively influences IC efficiency (ICE) Specifically, an increased proportion of independent and female board members correlates with enhanced IC efficiency, while larger board sizes are associated with a negative impact on IC.
Some studies use IC as a mediating variable in various relationships For instance,
IC can enhance the positive link between corporate social responsibility (CSR) and the innovation performance of businesses (Doan et al., 2023) By analyzing data from
10 direct respondents and 385 survey samples collected between February and April
In 2024, a study utilizing Structural Equation Modeling (SEM) in AMOS explored the relationship between Corporate Social Responsibility (CSR) and Intellectual Capital (IC) in enhancing the innovation performance of ICT enterprises The findings confirmed that IC positively impacts innovation efficiency, with relational capital (RC) exerting the strongest influence on business innovation.
A recent study by Trinh and Nguyen (2023) investigates the impact of intellectual capital (IC) on investment efficiency (IE) in Vietnamese publicly traded companies, highlighting the mediating role of strategic management accounting (SMA) practices Utilizing both secondary financial data and primary data collected through a questionnaire survey, the research employs the PLS-SEM method for analysis The findings indicate a direct relationship between IC and IE, underscoring the importance of effective SMA practices in enhancing investment outcomes.
This study explores the relationship between intellectual capital (IC) and investment efficiency (IE) in Vietnam, highlighting the mediating role of strategic management accounting (SMA) practices It demonstrates that IC components directly correlate with SMA practices, which in turn enhance investment efficiency The research underscores the significance of corporate governance and social responsibility in improving IC, with board diversity further boosting IC efficiency Additionally, it reveals that IC mediates the relationship between corporate social responsibility and innovation performance, emphasizing its critical role in a developing country's economic landscape.
Intellectual Capital (IC) has been extensively studied in international research, with a significant focus on its impact on firm performance, particularly in Vietnam A systematic literature review revealed that out of 777 papers, 189 specifically examine the relationship between IC and performance (Pedro et al., 2018, p 407) Common metrics for measuring firm performance in these studies include Return on Equity (ROE) and Return on Assets (ROA).
Return on Invested Capital (ROIC), profitability, and asset turnover are commonly utilized metrics in assessing firm performance (Bellucci et al., 2020) Similar findings have emerged from intellectual capital (IC) research in Vietnam, indicating a positive correlation between IC and overall firm performance, as well as within specific industries (Clarke et al., 2011; Bataineh et al., 2022) The study of IC typically encompasses elements such as human capital (HC), structural capital (sc), and relational capital (RC) to further substantiate the positive relationship identified.
Intellectual Capital (IC) plays a vital role in enhancing firm performance across various sectors Clarke et al (2011) highlight a direct positive correlation between IC and the performance of Australian publicly listed companies, with past Human Capital Efficiency (HCE) and Structural Capital Efficiency (SCE) also contributing positively to current performance In the Jordanian service sector, IC is essential for improving both performance and market value Research by Bataineh et al (2022) indicates that HCE significantly boosts key financial metrics, such as Return on Assets (ROA) and earnings per share Furthermore, the impact of IC extends beyond listed firms, positively influencing the performance of new ventures and small-to-medium-sized enterprises, as demonstrated by a study of 130 startups conducted by Hormiga et al.
Hypotheses development
2.4.1 The relationship between IC and COD
According to the Resource-Based View (RBV) proposed by Barney (1991), resources that are valuable, rare, unique, and non-substitutable (VRIN) significantly enhance a firm's competitive advantage The Knowledge-Based View (KBV) further emphasizes the role of knowledge and intellectual assets as essential strategic resources that impact business performance (Grant, 1996) Intellectual Capital (IC), a critical subset of these resources, can account for up to 44% of the variance in competitive advantage, with its three elements serving as strong predictors of this advantage (Kengatharan, 2019; Kamukama).
2013) Empirical evidence supports that stronger core competencies lead to a reduction in COD (Sun et al., 2022) From this point of view, IC may reduce COD by developing its own competency.
Credibility plays a crucial role in the credit decisions made by loan officers, as highlighted by Lipshitz & Shulimovitz (2007) The cost of default (COD) is viewed as a potential loss for banks if a borrower fails, underscoring the significance of the applicant's credibility (Valta, 2012) Additionally, intellectual capital (IC) positively influences credit decisions and enhances firms' cost efficiency (Guimón, 2005; Wang et al., 2014) IC also contributes to long-term financial stability (Cenciarelli et al., 2018) and mitigates risks for both investors and banks (Alwert et al., 2009) Notably, bankruptcy prediction models that include intellectual capital demonstrate superior default predictive power compared to traditional models (Cenciarelli et al., 2018).
Intangible capital (IC) enhances long-term financial stability, reducing a company's credit risk and lowering the cost of debt for creditors and lenders by ensuring timely interest and debt payments (Cenciarelli et al., 2018) In credit assessments, intangible assets like IC are more crucial than collateral in evaluating a business's capacity to meet future debt obligations (Guimón, 2005) The influence of IC on a firm's financial health bolsters its credibility, suggesting a positive relationship between IC and the cost of debt (COD).
Hl There is a negative correlation between Vietnamese listed company’ s IC and its COD in the period from 2008 to 2022
2.4.2 The moderating role of bankruptcy risk on the relationship between IC and COD
Bankruptcy risk serves as a key factor in evaluating the moderating role within the research model, significantly impacting firms' operations and public image (Chui et al., 2016) It acts as a natural proxy for a company's financial distress (Dichev, 1998; Shahdadi et al., 2020) For instance, credit-granting personnel in banks and enterprises must accurately assess clients' financial risks to make informed funding decisions Additionally, shareholders, potential investors, and management must evaluate profitability and long-term funding risks to guide their investment and business strategies (Tamari, 1966).
According to some previous research, IC is proved to have a negative correlation with bankruptcy likelihood (Cenciarelli et al., 2018; Shahdadi el al., 2020; Ahmad,
A study by Cenciarelli et al (2018) analyzed 307,994 American firm-year observations from 1985 to 2015, utilizing VAIC and Allman's Z-Score to assess intellectual capital (IC) and bankruptcy risks The findings indicate a significant connection between strong IC performance and a reduced likelihood of future default Similar results were observed in a separate market analysis involving 147 firms listed between 2010 and 2024, reinforcing the importance of IC in mitigating bankruptcy risks.
In a study conducted by Shahdadi et al (2020) on the Tehran Stock Exchange, it was found that intellectual capital (IC) is inversely correlated with the likelihood of bankruptcy, indicating that higher IC can reduce bankruptcy risks This leads to the hypothesis that IC may affect cost of debt (COD) differently for firms with varying bankruptcy risks Specifically, it is proposed that the moderating effect of bankruptcy risk on the relationship between IC and COD is positive, suggesting that firms with lower bankruptcy risks may experience a stronger correlation between IC and COD.
H2 The effect of IC on COD of Vietnamese listed company is stronger when bankruptcy risks rise in the period from 2008 to 2022
2.4.3 The moderating role of ownership structure on the relationship between
The ownership structure serves as the second variable examined for its moderating effect on the primary relationship of this research This study focuses on two distinct ownership types: foreign ownership and state ownership, leading to the formulation of two hypotheses (H3a and H3b) for analysis in this section.
According to Kamardin et al (2017), information asymmetry between managers and shareholders may be lessened by foreign ownership According to Choi et al
In-depth monitoring by foreign investors can significantly reduce information asymmetry, a challenge they face compared to local investors These foreign investors tend to focus on firms with lower information asymmetry, efficiently processing available public information As their involvement increases, local companies may experience heightened scrutiny, necessitating greater transparency in their operations Consequently, as foreign investment and market openness rise, information asymmetry is expected to diminish Furthermore, information asymmetry is a key contributor to cost of debt (COD), leading to higher anticipated losses for debtholders Companies with greater information asymmetry and positive future profitability projections are more likely to seek private financing Therefore, it can be hypothesized that increased foreign investment and transparency will mitigate information asymmetry in the market.
H3a: Foreign ownership strengthens the correlation between IC on COD of Vietnamese listed companies from 2008 to 2022
From the standpoint of state ownership, intellectual capital (IC) significantly boosts firm productivity, with human capital (HC) being the most influential factor Research indicates that HC plays a crucial role in enhancing the productivity of state-owned enterprises.
Human capital (HC) plays a crucial role in intellectual capital (IC), indicating a potential positive correlation between IC and state ownership Additionally, macroeconomic factors contribute to the subtle influence of state ownership on a firm's debt, making it improbable for a state-owned enterprise to face collapse.
The 2023 Vietnamese government report on the investment and management of state capital in enterprises reveals that state-owned enterprises in Vietnam exhibit a lower reliance on debt for their operations Additionally, prior studies indicate that companies with strong government ties benefit from favorable borrowing conditions with state-owned banks.
As of January 31, 2024, state-owned commercial banks in Vietnam represent approximately 41% of the total assets in the banking and finance sector, with an outstanding loan to total deposit ratio of 81.31% This significant presence allows Vietnamese state-owned enterprises to access lower borrowing rates, as they typically benefit from implicit government guarantees on their debt, as highlighted by Le (2020).
H3b: State ownership strengthens the correlation between IC on COD of Vietnamese listed company from 2008 to 2022.
DATA AND METHODOLOGY 3.1 Research process
Data
This thesis analyzes data from Vietnamese listed firms on the HOSE and HNX stock exchanges from 2008 to 2022, utilizing the FiinPro-X platform The study begins in 2008 due to insufficient data prior to this year and concludes in 2022, as no public data for 2023 was available at the time of data collection in late 2023 Employing a quantitative method, the research emphasizes that a longer time frame enhances the reliability of results through increased data volume To maintain a focused analysis, the study excludes financial and insurance institutions, which are characterized by complex transactions and distinct regulatory frameworks, including Basel I, II, and III By concentrating on non-financial listed companies in Vietnam, the research seeks to establish a more consistent and comparable dataset.
After filtering out incomplete data for calculating the Value Added Intellectual Coefficient (VAIC), the study analyzed a final sample of 561 firms, resulting in 4,944 observations This dataset is robust and consistent across all research tests and encompasses firms from 98 different industries, categorized according to the Industry Classification Benchmark (ICB) on the FiinPro-X platform.
This thesis relies on secondary data for all research models, utilizing financial statements and various financial ratios sourced from the FiinPro-X platform Additionally, certain specific indexes that are not available on this platform require manual calculations for accurate analysis.
Research models
Based on the first hypothesis above, according to the review of previous articles,the author infers the research as below.
CODit = po + PiVAICít + p2CHit + p3 DIVit + p4 GROWTHit + PsLEVit + pôMTBEit + p7ROAit + psSIZEit + pọTANit + TIME FIXED EFFECTS + INDUSTRY FIXED EFFECTS + Eit (1)
In this model, the Cost of Debt (COD) serves as the dependent variable, with the ratio of total interest expenses to total debt utilized for its evaluation, as supported by various studies (La Rosa et al., 2018; Fonseka et al., 2019; Li et al., 2020; Vu et al., 2022; Tang & Geng, 2024).
VAIC is a widely recognized method for evaluating intellectual capital (IC) performance and serves as the sole independent variable in this research model Utilizing Pulic's (2004) methodology, VAIC assesses the new value generated per monetary unit invested in each resource A higher VAIC coefficient indicates that a company's resources, particularly its intellectual capital, are effectively contributing to value creation Detailed calculations of VAIC can be found in the variables' calculation method table (refer to Table 3.1) below.
The variables' calculation method in this main research model is built as follows:
1 COD Interest Expense / Total Debt
2 VAIC HCE + SCE + CEE VA = OUT - IN = Total sales - Cost of bought-in materials, components and services
HC = Total salaries and wages of a firm
CE = Book value of the net assets of company
6 CH Cash and Short-term Investments / Book value of total assets
7 DIV A dummy variable: Common Dividends > 0: 0;
10 MTBE Market value of equity / Book value of equity
11 ROA Return on assets at the beginning of the year
14 OWN Specific percentage of state-ownership or foreign ownership
.012*Working capital+.014*Retained Eamings+.033*EBIT+.999*Sales
Total assets 006*Market value equity
Book value of Total debt
This research incorporates eight control variables to enhance the main models, drawing on the methodologies of Fonseka et al (2019) and Orazalin and Akhmetzhanov (2019) The selected control variables include Cash Holdings (CH), Dividends (DIV), Sales Growth (GROWTH), Leverage (LEV), Market-to-Book Ratio (MTBE), Return on Assets (ROA), Firm Size (SIZE), and Asset Tangibility (TAN) Further details on these variables will be provided in the following discussion.
Cash Holdings (CH) represent the ratio of highly liquid assets, such as cash and short-term investments, to total assets Generally, larger companies with strong credit ratings have lower cash-to-total-non-cash asset ratios, as they have better access to financial markets (Opler et al., 1999) Furthermore, research indicates that a firm's level of cash holdings tends to negatively correlate with its efficiency (Guo et al., 2020) Therefore, this study anticipates a negative correlation between CH and COD.
Dividends (DIV) serve as a dummy variable indicating the annual payments received by stakeholders; a value of 0 signifies that dividends were paid, while a value of 1 indicates non-payment This research anticipates a positive correlation between DIV and Cost of Debt (COD), as larger and more successful companies are more likely to pay dividends, which in turn facilitates easier access to debt financing from creditors (Denis & Osobov, 2008).
Sales growth (GROWTH) refers to the year-over-year change in sales volume, indicating whether sales have increased or decreased An increase in sales typically signifies enhanced profitability and business development It is anticipated that GROWTH and COD are negatively correlated, suggesting that as sales grow, the cost of goods sold may decline.
Leverage (LEV) is defined as the ratio of total debt to total assets Research by Anderson et al (2003) indicates that increased debt utilization is associated with higher debt costs, suggesting that leverage is positively correlated with the cost of debt financing.
The market-to-book ratio (MTBE) measures the relationship between a company's market value and its book value at the beginning of the year This ratio serves as an effective indicator of a firm's growth potential Research by Fonseka et al (2019) demonstrated that companies exhibiting stronger growth prospects tend to have lower cost of debt (COD) and an increased likelihood of successfully repaying their debts.
Return on assets (ROA): According to Fonseka et al (2019), more beneficial businesses can pay off their debt, it is expected that there is a negative correlation between ROA and COD.
Firm size, measured as the logarithm of total assets, plays a significant role in determining equity capital costs Research indicates that larger firms typically experience lower costs due to a reduced perceived risk (Bachoo et al., 2013) Consequently, this study anticipates a negative correlation between firm size and cost of debt (COD).
Asset tangibility (TAN): As tangible assets can be used as collateral whenever financed by debt, TAN is expected to positively be related to COD.
Based on the second hypothesis and the first model above, the second model to test the second hypothesis is as below:
CODit = po + plVAICit + P2ZSCORE + p3 VAICitX ZSCORE + p4CHit + PsDIVit + p6 GROWTHit + p7LEVit + psMTBEit + PyROAit + pioSIZEit + pnTANit + TIME FIXED EFFECTS + INDUSTRY FIXED EFFECTS + £it (2)
This article discusses the application of Altman's Z-Score (ZSCORE) to assess bankruptcy risks, a method widely recognized in academic research (Agarwal & Taffler, 2007) Originally developed for industrial firms, Altman's model has proven effective for various non-financial businesses, demonstrating a prediction accuracy of approximately 0.75 across multiple countries (Altman et al., 2016) According to Altman (1968), firms with a Z-Score above 2.99 are classified as "non-bankrupt," while those below 1.81 are deemed bankrupt, with the range between 1.81 and 2.99 referred to as the "zone of ignorance."
This research selects the Z-Score as a key metric to assess the moderating role of corporate bankruptcy risk, as a higher Z-Score indicates a lower likelihood of bankruptcy The study aims to investigate whether the potential for corporate bankruptcy influences the relationship between Intellectual Capital (IC) and Cost of Debt (COD).
The 3a and 3b models of H2 are designed to test hypotheses 3a and 3b, utilizing foreign ownership percentage (FOWNP) and state ownership percentage (SOWNP) as moderating variables, which represent the percentage of a firm's shares held by foreign and state entities, respectively.
CODit = po + piVAICit + P2FOWNP + p3 VAICit X FOWNP + p4 CHit + psDIVit + p6 GROWTHit + p7LEVit + PsMTBEit + pọROAi, + pioSIZEit+ pnTANit + TIME FIXED EFFECTS + INDUSTRY FIXED EFFECTS + £it (3a)
CODit= po+ piVAICit + P2SOWNP + p3 VAICit X SOWNP + p4CHit + psDIVit + p6 GROWTHit + p7LEVit + psMTBEit + PuROAit + PioSIZEit + pnTANit + TIME FIXED EFFECTS + INDUSTRY FIXED EFFECTS + £i, (3b)
Following the four models mentioned above, the expected significance is almost the same as above and presented in Table 3.2 below:
Table 3.2 Variables and expected signs with sources
(2007), Alwert et al (2009), Cenciarelli el al (2018), Sun et al (2022)
Cenciarelli et al (2018), Shahdadi et al
Jiang & Kim (2004), Choe et al (2005), Choi et al (2013), Demen et al (2016), Kamardin et al (2017)
Sapienza (2004), Ding (2005), Borisova et al (2015), Le (2020)
CH (-) Opler et al (1999), Guo et al (2020)
Methodology
This research employs fixed effects and clustered models for panel data regression, as recommended by Le (2023) for their efficiency The Modified Fixed Effects Model (FEM) is chosen to effectively control individual time-invariant characteristics, such as industry, allowing for accurate estimation of the net effects of explanatory variables on the dependent variable By clustering industries, the study addresses issues of autocorrelation and heteroscedasticity, thereby reducing standard error biases (Christodoulou & Sarafidis, 2017; Moody & Marvell, 2018) The absence of serious multicollinearity in the data confirms the appropriateness of using FEM, particularly given the large dataset that is not randomly withdrawn (Đinh, 2016) Recent international studies have increasingly favored FEM for analyzing panel data; for instance, Hoang (2024) found that companies are more inclined to adopt clawback provisions amid rising cybersecurity threats Moreover, fixed-effect quantile regression analysis revealed that government support positively influences tax payment at higher percentiles, while politically connected SMEs consistently pay lower taxes (Minh et al., 2021) Environmental studies also highlight that while CO2 emissions positively affect crop production, renewable energy consumption, labor force, and arable land size significantly impact both crop and livestock production (Otim et al., 2023) Additionally, fixed-effect panel quantile regression indicates that energy efficiency enhances economic growth across all quantiles, although renewable energy consumption negatively impacts growth at higher quantiles (Akram et al., 2020) Overall, the validity of fixed-effect models in this research context is well-supported by existing literature.
RESEARCH RESULTS AND DISCUSSION 4.1 Descriptive statistics
Regression results and Discussion
4.2.1 The effect of IC and its elements on COD
Table 4.3 below shows the results of the negative correlation between COD and
The findings indicate that Information Communication (IC) has a negative impact on Cash on Delivery (COD), supporting the initial hypothesis To date, no prior research has specifically examined the relationship between IC and COD within the Vietnamese market, making direct comparisons challenging Nevertheless, these results align with existing studies that explore the indirect relationship between IC and COD through various influencing factors.
From the RBV perspective, the negative correlation between intellectual capital (IC) and cost of debt (COD) underscores the importance of IC as a vital resource in fostering competitive advantages As emphasized by scholars such as Barney (1991), Grant (1996), and Kamukama (2013), IC acts as a strategic asset that not only differentiates firms but also strengthens their market positioning.
The thesis revealed that GROWTH, ROA, and TAN are significant control variables impacting COD, consistent with prior research (Qiu & Yu, 2009; Spiceland et al., 2015; Fonseka et al., 2019) Specifically, the negative relationship between GROWTH and ROA with COD suggests that increased sales and profits reduce the reliance on external financing In contrast, the positive relationship between TAN and COD indicates that firms with greater tangible assets can obtain more debt financing, as these assets serve as effective collateral Additionally, five control variables—CH and DIV—were found to have no significant impact.
The findings regarding LEV, MTBE, and SIZE reveal unexpected outcomes concerning five control variables Strong sales growth and profitability often indicate robust financial health, facilitating equity capital acquisition for companies Additionally, the positive correlation between TAN and COD suggests that firms with substantial tangible assets can access greater debt financing These assets, including property, plant, and equipment, act as collateral, mitigating lenders' risks and enhancing their confidence in the borrower's repayment capability.
Table 4.3 Regression result ofthe effect of IC and its components on COD
VARIABLES DEPENDENT VARIABLE: COST OF DEBT (COD)
Source: Author's analysis on STATA
VARIABLES DEPENDENT VARIABLE: COST OF DEBT (COD)
4.2.2 The moderating role of bankruptcy risks in the relationship between
The findings presented in Table 4.4 indicate that ZSCORE has an insignificant moderating effect on the relationship between Cost of Debt (COD) and Intellectual Capital (IC), contradicting the initial hypothesis This suggests that the bankruptcy risks faced by firms do not significantly alter the correlation between IC and COD One key reason is that creditors typically factor in bankruptcy risks during their lending evaluations (Tamari, 1966), which may lessen the additional moderating impact of these risks Furthermore, the dynamic nature of IC investments in relation to bankruptcy risks (Ahmad, F., 2024) adds complexity to this moderating role Both recent and historical investments in IC can influence financial performance and market value, thereby affecting COD, which may reduce the importance of bankruptcy risks in this context Ultimately, while the hypothesis proposed a moderating effect of ZSCORE, the empirical evidence reveals that bankruptcy risks do not significantly impact the relationship between IC and COD.
The correlation between IC and COD can be explained by the integration of bankruptcy risks into creditor evaluations, highlighting the complex relationship between IC investments and the associated bankruptcy risks.
Emerging Market Score (EMS) is a scoring system (EMS Model) that helps investors assess the relative value of Emerging Corporate Bonds (Allman et al.,
The EMS model, developed from the ZSCORE model, initially seemed like a suitable choice for this thesis due to its broader applicability to both public and private companies across various industries (Altman et al., 1998) However, further examination revealed its limitations for the study's specific objectives, as it is not designed to predict bankruptcy but rather to estimate equivalent bond ratings and intrinsic fixed income values (Altman et al., 1998, p [insert page number]).
While EMS offers insights into financial health and creditworthiness, its focus on bond ratings diverges from this thesis's primary aim of exploring the predictive power of IC and COD regarding bankruptcy risk In contrast, ZSCORE is specifically designed to predict bankruptcy, with higher scores indicating lower risks This direct correlation supports the investigation of how bankruptcy risks moderate the relationship between IC and COD Utilizing ZSCORE allows for a robust analysis of the connection between IC, COD, and their roles in predicting bankruptcy.
Table 4.4 Regression result ofthe moderating role of ZSCORE on the correlation between IC and COD
VARIABLES DEPENDENT VARIABLE: COST OF DEBT (COD)
Source: Author’s analysis on STATA
VARIABLES DEPENDENT VARIABLE: COST OF DEBT (COD)
4.2.3 The moderating role of ownership structure in the relationship between IC and COD
The analysis presented in Table 4.5 indicates that foreign ownership does not moderate the relationship between intellectual capital (IC) and cost of debt (COD), contradicting hypothesis H3a This lack of correlation can be attributed to findings by Nguyen et al (2022), which revealed no significant link between institutional ownership and COD in a study of 207 Vietnamese listed firms from 2008 to 2016 The unique characteristics of the Vietnamese financial market contribute to this phenomenon, as local banks and lending institutions prioritize company performance and management effectiveness over ownership structure when evaluating creditworthiness This trend is expected to remain stable, as substantial changes in the Vietnamese financial landscape are unlikely in the near term.
State ownership, represented by SOWNP, positively moderates the relationship between intellectual capital (IC) and cost of debt (COD), with a statistically significant interaction at around 5%, supporting hypothesis H3b This aligns with previous studies that highlight the indirect influence of state ownership on IC and COD through intermediary factors Research by Kong & Kong (2016) indicates that human capital within IC enhances productivity in state-owned enterprises Additionally, the favorable debt pricing that state-owned firms experience (Sapienza, 2004; Dinẹ, 2005; Le, 2020) further contributes to a conducive environment for this positive moderation Overall, state ownership significantly influences the IC and COD relationship, reinforcing the findings of existing research.
HC (in IC) on state-owned enterprise productivity and the advantageous debt pricing associated with these firms.
Table 4.5, Regression result ofthe moderating role of FOWNP and SOWNP on the correlation between IC and COD
VARIABLES DEPENDENT VARIABLE : COST OF DEBT (COD)
Source: Author's analysis on STATA
VARIABLES DEPENDENT VARIABLE: COST OF DEBT (COD)
Robust t-statistics in parentheses: *** pcO.Ol, ** p