(Luận văn thạc sĩ) mediating effect of strategic management accounting practices in the relationship between intellectual capital and corporate performance evidence from vietnam

Background

In today's knowledge-based economy, organizations are increasingly investing in intangible assets, particularly intellectual capital, which has become a crucial value driver (Mehralian et al., 2013) Effective management of intellectual capital is essential due to its direct and indirect benefits, including enhanced knowledge processing, improved learning outcomes, and sustainable competitive advantages derived from strategic assets (Roos et al., 1997; Riahi-Belkaoui, 2003) As Vietnam embraces an open-door policy and integrates into regional trade agreements like AEC and TPP, competition among Vietnamese enterprises is intensifying Consequently, managers must recognize the significance of intangibles and intellectual capital to secure sustainable competitive advantages in the global market, thereby encouraging further research on the impact of intellectual capital within the Vietnamese context.

The concept of intellectual capital has evolved through three distinct stages, beginning in the 1990s with a focus on awareness, definitions, and case studies (Mehralian et al., 2013) The second stage, starting in 2000, emphasized measurement, modeling, and international case studies, revealing a positive correlation between intellectual capital and corporate performance across various research methods The third stage, initiated in 2004, shifts attention to the managerial implications of effectively managing intellectual capital While much of the research has been concentrated in developed Western nations and select Asian countries like Thailand and Malaysia, the findings consistently highlight the importance of intellectual capital in enhancing corporate performance.

Hong Kong, this specific area of intellectual capital has been neglected in the body of Vietnamese literature

Strategic management accounting, as defined by CIMA, focuses on information relevant to key strategic decisions and has a potential role in managing intellectual capital, which is an asset used for strategic purposes Despite existing literature primarily addressing external reporting and valuation of intellectual capital, there is limited discussion on the interplay between intellectual capital and strategic management accounting Organizations with strong intellectual capital can develop strategic management accounting systems to identify, measure, and communicate value drivers effectively Conversely, as strategic management accounting evolves, it must address the identification and communication of intellectual capital to support strategic objectives A tailored system of strategic management accounting practices is essential, aligning with a company's unique attributes and competitive strategies In the context of Vietnam, many enterprises are gradually adopting advanced accounting techniques influenced by foreign-owned companies, yet medium and large enterprises often lack understanding of implementing strategic management accounting This gap has led to increased interest in the subject since the 2010s, highlighting the need to study the correlation between intellectual capital, strategic management accounting practices, and corporate performance in Vietnam The research aims to explore the mediating role of strategic management accounting practices in the relationship between intellectual capital and corporate performance.

Research questions and research objectives

The research gaps identified indicate a need to explore the impact of intellectual capital and strategic management accounting practices on corporate performance in transitional economies like Vietnam, where these issues remain largely unexamined This raises critical questions about the necessity for organizations to develop strategic management accounting systems that support intellectual capital to improve financial performance Furthermore, it is essential to understand how strategic management accounting can effectively manage intellectual capital to enhance an organization's financial outcomes Consequently, three research questions have been formulated to address these concerns.

Research question 1: What is the direct effect of intellectual capital components on corporate performance in Vietnamese enterprises?

Research question 2: What is the effect of intellectual capital components on corporate performance in the presence of strategic management accounting practices?

Research question 3: How do strategic management accounting practices handle each component of intellectual capital to improve corporate performance?

This dissertation aims to empirically explore the relationship between intellectual capital, strategic management accounting practices, and corporate performance It specifically examines how strategic management accounting practices mediate the connection between various components of intellectual capital and key financial aspects of corporate performance Additionally, the research analyzes the role of strategic management accounting practices in effectively managing intellectual capital components.

- RO1: Testing the direct impact of each of intellectual capital components on corporate performance h

- RO2: Examining the direct influence of strategic management accounting practices over corporate performance

- RO3: Investigating an indirect path between intellectual capital components and corporate performance through the mediating role of strategic management accounting practices

- RO4: Empirically analysing which group of strategic management accounting practices (i.e strategic cost management, competitor accounting, strategic accounting and customer accounting) are related to manage which components of intellectual capital

- RO5: Providing additional evidence on the interconnection of intellectual capital components.

Research object and research scope

This dissertation examines the interplay between intellectual capital, strategic management accounting (SMA) practices, and corporate performance, focusing on business organizations as the unit of analysis To explore the SMA practices utilized within these organizations, data is gathered through a questionnaire survey directed at SMA practitioners The informants—managers or top management members—are required to possess knowledge in accounting, planning, or finance, along with a minimum of two years of experience in their current roles Additionally, the study incorporates financial information from annual reports and financial statements to analyze the relationship between intellectual capital and corporate performance.

This study is limited in three key aspects: it focuses on Vietnam, a developing Asian country with a transitional economy and collectivist culture; it examines enterprises listed on the Hochiminh Stock Exchange (HoSE) and Hanoi Stock Exchange (HNX) for easier financial data collection; and it utilizes 2016 financial information on intellectual capital (IC) and financial performance of public companies, rather than panel data from multiple years, to analyze SMA practices Additionally, to calculate variables like organizational capital and innovation capital, financial data from a seven-year period (2010-2016) is required.

Methodology

This study reviews existing literature on intellectual capital, strategic management accounting practices, and corporate performance, leading to the development of two research models with six hypotheses Utilizing a quantitative research approach, the study analyzes empirical survey and financial data from a sample of at least 127 public enterprises in Vietnam for the year 2016 Given the complexity of the research models, which include mediators, and the limited sample size, data analysis is performed using partial least squares structural equation modeling (PLS-SEM) with the assistance of SPSS 24.0 and SmartPLS 3.1 software.

Outline of the dissertation

Besides the parts of introduction and conclusion, this dissertation is organized with 7 chapters, as follows:

Introduction part This part states the background well as the research questions and objectives Then it briefly describes the research methodology and provides the research scope

Chapter 1: Literature Review examines existing research on intellectual capital and strategic management accounting across various countries, including Vietnam This review identifies research gaps that highlight potential directions for further investigation, ultimately shaping the research objectives of this dissertation.

Chapter 2 explores the definitions and components of intellectual capital, alongside the concepts of corporate performance and strategic management accounting practices, to elucidate their interrelationships It also introduces existing theories related to the measurement of intellectual capital, providing a foundational understanding that will be built upon in subsequent chapters.

Chapter 3 outlines the theoretical framework and the development of hypotheses, focusing on the conceptual foundations necessary for formulating testable hypotheses within two research models This chapter addresses key research questions and identifies gaps in existing literature, ultimately presenting the rationale behind six testable hypotheses.

Chapter 4 outlines the research methodology, detailing the operationalization and measurement of constructs within the theoretical model It also addresses the unit of analysis, identifies informants, and specifies the sample size used in the study.

Chapter 5 focuses on the assessment of sample characteristics and measurement scales It begins with a discussion on data collection methods for constructing variables related to Strategic Management Accounting (SMA) practices, followed by a pilot test to evaluate the attributes of these indicators The chapter then details the refinement of measurement scales based on data gathered from Vietnamese public enterprises Finally, it presents descriptive statistics of the research data and assesses collinearity issues within the inner structural models.

Chapter 6 focuses on data analysis and discussion, beginning with an evaluation of the theoretical models' fitness It presents empirical results related to the hypotheses formulated in Chapter 3, detailing outcomes from both direct and mediated path regressions using SmartPLS 3.1 The results are systematically organized from the first to the sixth hypothesis, concluding with the testing of control variables In addition to describing the data analysis, the chapter contextualizes each significant finding within a managerial framework.

Chapter 7: Implications for managing intellectual capital by strategic management accounting practices The managerial implications of this study are outlined in this chapter

This article begins by exploring a three-stage value creation process derived from the testing of six hypotheses It offers valuable recommendations for leaders, policymakers, and the academic community on effectively managing intellectual capital The concluding section outlines strategic management accounting techniques tailored to enhance the management of intellectual capital across different groups.

In conclusion, this article summarizes the key findings, highlighting both the theoretical and managerial contributions of the study It also addresses the research limitations and offers suggestions for future research directions.

LITERATURE REVIEW

Review of international studies of intellectual capital

As economies transition from industrial to knowledge-based frameworks, a firm's value is increasingly assessed not just through financial outcomes but also by the activities that foster knowledge resources (Stewart & Ruckdeschel, 1998) This shift emphasizes the importance of understanding how employees, stakeholders, and various activities contribute to value creation, posing the challenge of effectively identifying, measuring, and reporting intellectual capital (Dumay, Guthrie, & Ricceri, 2012) Consequently, the rise of intellectual capital as a significant topic since the mid-1990s has led to a diverse body of literature across multiple research disciplines Reflecting on this trend, it seems that intellectual capital has gained traction akin to a research fashion, as evidenced by the ongoing development of specialized journals such as the Journal of Intellectual Capital (Alcaniz, Gomez-Bezares, & Roslender, 2011).

The International Journal of Learning and Intellectual Capital, along with the Journal of Human Resource Costing and Accounting, features significant research on the intersection of capital and human resources These studies are also published in various prominent business and management journals, highlighting the importance of accounting, auditing, and accountability in contemporary organizational practices.

Journal, European Accounting Review, the Accounting Organizations and Society Journal especially important in the accounting discipline of intellectual capital measurement and management h

1.1.1 Stages in developing intellectual capital as a research field

Understanding the historical context of intellectual capital (IC) is crucial for recognizing its significance as a key business element today Petty and Guthrie (2000) identified two stages of IC research: the first stage aimed to raise awareness about the importance of IC in creating sustainable competitive advantages, leading to the development of guidelines and standards, although lacking specific empirical research Most studies before the mid-1990s fall into this initial phase The second stage shifted focus to organizational evidence, exploring how IC could generate value in the labor market This progression helped establish a common terminology and identified three main components of IC, which are essential for its management, measurement, and accountability (Dumay et al., 2012) A third stage of IC research is now emerging, characterized by critical examinations of IC in practice and its managerial implications, as highlighted in the 2004 special edition of the Journal of Intellectual Capital Unlike the second stage, which primarily assessed IC's financial impact, the third stage emphasizes the broader value of IC, considering the significance of products and services for customers and stakeholders (Dumay & Garanina, 2013).

Despite looking at three developing stages of IC, Guthrie (2001) provides a timeline of major IC research milestones, as summarized in Table 1.1 h

Table 1.1 Milestones of significant contributions to the identifications, measurement and reporting of intellectual capital

General notion of intangible value (often generically labelled

The “information age” takes hold and the gap between book value and market value widens noticeably for many companies

Early attempts by practitioner consultants to construct statements/ accounts that measure intellectual capital (Sveiby, 1989)

 Initiatives to systematically measure and report on company stocks of intellectual capital to external parties (e.g The Swedish Coalition of Service Industries (SCSI) (1995))

 Kaplan and Norton (1992) introduce the concept of a Balanced Scorecard The Scorecard evolved around the premise that “what you measure is what you get”

Nonaka and Takeuchi's seminal work, "The Knowledge-Creating Company" (1995), explores the concept of knowledge and its significance in organizational success While the book primarily focuses on knowledge, it also draws a subtle distinction between knowledge and Intellectual Capital, making it pertinent for those interested in the latter.

In 1994, Skandia released a supplement to its annual report that evaluated the company's Intellectual Capital, titled "Visualizing Intellectual Capital." This innovative approach garnered significant interest from other companies eager to emulate Skandia's pioneering efforts in measuring and reporting intangible assets (Edvinsson & Sullivan, 1996).

The Intellectual Capital movement has been significantly shaped by bestselling authors such as Kaplan and Norton (1996), Edvinsson and Sullivan (1996), and Sveiby (1997) Notably, Edvinsson and Malone focus on the methodologies and processes involved in effectively measuring intellectual capital.

 Intellectual Capital becomes a popular topic with researchers and academic conferences, working papers, and other publications find an audience

 An increasing number of large scale projects (e.g the MERITUM project; Danish; Stockholm) commence which aim, in part, to introduce some academic rigour into research on Intellectual Capital

 In 1999, the OECD convenes an international symposium in Amsterdam on intellectual capital (Organization for Economic Co-operation and Development (OECD), 2000)

Since the 2000s, IC research has been increasingly shared with the broader accounting research community, as generalist accounting journals and conferences have embraced special editions to feature this work.

IC accounting papers (Dumay et al., 2012)

 There is an increasing trend on knowledge management research besides intellectual capital research (Dumay et al., 2012)

Source: Summarized by the author on the sources of Guthrie (2001) and Dumay et al (2012)

1.1.2 Research trends on intellectual capital in the accounting discipline

Intellectual capital is a crucial knowledge resource that requires effective management and can be analyzed from both microeconomic and macroeconomic perspectives It is examined through four key lenses: economic, strategic, managerial, and accounting (Alcaniz et al., 2011) From an economic standpoint, intellectual capital contributes to the wealth of nations, encompassing elements like advanced technology and a highly educated workforce (Stewart & Ruckdeschel, 1998) Strategically, a company’s success increasingly hinges on its intangible assets rather than tangible ones, with the accumulation of intellectual capital influenced by a reciprocal relationship between resources and strategy (Brooking).

From a managerial perspective, different types of capital—physical, financial, and intellectual—are essential components of an organization’s resources and must be effectively identified and managed, as they underpin the organization's value (Bontis, 1999) This study emphasizes the complexities surrounding the accounting of intellectual capital Research by Dumay et al (2012) analyzed 423 journal articles on intellectual capital from 2000 to 2009, revealing that while management accounting and external reporting dominate the focus of intellectual capital research, there is a notable lack of literature addressing accountability, governance, and auditing in this field.

Table 1.2 Topics of intellectual capital research in the accounting discipline

Table 1.2 presents the focus of research trends on intellectual capital in the accounting discipline, as follows:

External reporting on intellectual capital (IC) can be both voluntary and non-quantitative, and its linkage to firm performance benefits both companies and investors While extensive research has focused on IC disclosure practices in developed countries, there is significantly less information available regarding emerging economies (Wagiciengo & Belal, 2012) The limited studies that do exist primarily concentrate on Asian countries, providing empirical insights into IC disclosure through various media, including annual reports and corporate social responsibility reports Findings indicate that IC disclosure varies by company size and industry sector, with European studies revealing that 49% of disclosures pertain to relational capital, 30% to structural capital, and 21% to human capital (Bozzolan, O'Regan, & Ricceri).

A review of existing literature indicates that the majority of prior studies have concentrated on data from a single year through content analysis, with only a few utilizing longitudinal data Notable researchers, including Bozzolan, Favotto, and Ricceri (2003) as well as Bharathi Kamath (2008), have conducted longitudinal studies to provide a more comprehensive analysis of intellectual capital disclosure practices.

 Accountability and governance: Some papers (Keenan and Aggestam (2001); J

Li, Pike, and Haniffa (2008) investigate how corporate governance factors affect the disclosure of intellectual capital, utilizing multiple disclosure measures Their research posits that there are meaningful connections between intellectual capital disclosure in annual reports and various governance elements, including board structure, role duality, ownership concentration, audit committee size, and the frequency of audit committee meetings, while controlling for factors such as listing age, firm size, and profitability.

Management control is a highly researched area, as evidenced by the 160 articles listed in Table 1.2, which cover a diverse array of management topics Key studies include the application of Balanced Scorecards (Flamholtz, 2003) for managing intellectual capital (IC) (O'Connor & Feng, 2005), as well as the management of IC in various organizational contexts such as service organizations (Namasivayam & Denizci, 2006), the banking industry (Puntillo, 2009), and the not-for-profit sector (Kong, 2009) Additionally, research has focused on mapping IC within organizations (Hellström & Husted, 2004), highlighting the multifaceted nature of management control in different sectors.

Tayles et al (2002, 2007) advocate for the use of management accounting approaches to enhance the control of intellectual capital (IC) in service companies Their research highlights the effectiveness of management accounting techniques over traditional methods, emphasizing a shift from conventional and zero-based budgeting to the beyond budgeting concept for better IC management Additionally, they recommend real options valuation as a superior alternative to capital budgeting for evaluating strategic IC investment opportunities (Neil & Hickey, 2001).

In the early 1990s, various performance measurement frameworks emerged to address the limitations of financial-only metrics, emphasizing the importance of intangible resources such as key customers, internal processes, and learning (Tayles et al., 2007; Amir & Lev, 1996) Notable models include the Intangible Assets Monitor and Skandia Navigator, both designed with a focus on intellectual capital, as well as the Balanced Scorecard (BSC), which offers a broader strategic perspective The BSC notably incorporates relational capital from the customer viewpoint, alongside structural and human capital.

Review of international studies of strategic management accounting

In 1981, Simmonds advocated for the adoption of strategic management accounting (SMA) in the UK magazine Management Accounting, initiating a significant discourse that has continued through numerous professional and academic papers Research on SMA has primarily focused on four key themes: defining strategic management accounting, identifying the SMA techniques utilized across various industries and countries, examining the effects of strategic options on SMA practices, and understanding the SMA process Despite extensive empirical research over the past three decades, largely through questionnaire surveys aimed at assessing the adoption of specific SMA techniques, there remains a notable lack of case studies This gap highlights the limited understanding of how SMA techniques are implemented, who employs them, and for what purposes.

1.2.1 Research on conceptualizing strategic management accounting

Strategic Management Accounting (SMA) lacks a universally accepted definition, but it is generally viewed as an intersection of strategic management and accounting (Roslender & Hart, 2003) Simmonds (1981) defines SMA as a holistic approach that integrates management accounting with a company's strategy and positioning, while Bromwich (1990) narrows it down to financial information focused on competitive performance Conversely, some scholars argue that marketing plays a more crucial role in SMA (Foster & Gupta, 1994; Roslender, 1995; Wilson, 1995) The literature reveals three primary approaches to conceptualizing SMA.

Simmonds (1981) emphasizes a cost management approach to Strategic Management Accounting (SMA), drawing on Porter’s framework This perspective has sparked extensive research focused on maintaining a low-price competitive strategy rather than prioritizing design and innovation for product differentiation Consequently, there is a growing need for financial information regarding competitors to effectively respond to the strategies of core competitors.

Bromwich's (1990) SMA approach utilizes the attribute costing technique, focusing on the costs associated with the benefits a product provides to customers rather than merely identifying the factors driving product costs This shift emphasizes the importance of understanding customer benefits and their role in establishing a sustainable competitive advantage.

Roslender and Hart (2003) emphasize the importance of integrating marketing concepts into Strategic Management Accounting (SMA), advocating for a partnership that balances both fields They highlight the need for "brand management accounting," which should incorporate performance metrics like market share, market growth, brand strength, and customer profitability, particularly focusing on sub-brands and targeted market offerings.

The terminology of Strategic Management Accounting (SMA) has diverse interpretations influenced by researchers' backgrounds and assumptions, leading to ongoing debates about its definition since Simmonds’ initial concept over 30 years ago The term encompasses various perspectives, with some scholars highlighting the connection between accounting and marketing, while others focus on its strategic linkages The 1990s are often referred to as “the glory decade” for SMA, as academics, consultants, and practitioners contributed to its popularity (Langfield-Smith, 2008) Shank and Govindarajan (1993) observed that many SMA techniques were trialed in U.S companies and later presented as teaching case studies or book chapters Additionally, professional journals featured SMA-related articles, and training by professional accounting bodies increasingly emphasized strategic cost management tools and techniques (Langfield-Smith).

In 2008, global consulting firms significantly advanced their practices in Strategic Market Analysis (SMA), leading to a diverse range of definitions for the term These definitions vary from narrow interpretations focused on competitor analysis and performance measurement to broader perspectives that emphasize an external orientation.

1.2.2 Research on strategic management accounting techniques

Strategic Management Accounting (SMA) practices lack a unified conceptual framework, leading to a variety of accounting techniques with a strategic focus Significant overlaps exist among the classifications of SMA techniques, particularly in areas like strategic cost accounting and competitor accounting, while notable differences are found in customer accounting and strategic accounting Despite varying research perspectives, techniques such as strategic cost accounting and competitor accounting are widely recognized as essential components of SMA practices Guilding and McManus (2002) introduced three customer-focused techniques, identifying customer accounting as a crucial fourth dimension, although this aspect has often been overlooked in literature due to its late emergence and challenges in observation.

Table 1.4 Literature review of essential techniques in strategic management accounting toolbox

Strategic cost management Attribute costing      

The valuation of customer group  

Source: The author’s literature review

Recent studies on Strategic Management Accounting (SMA) enhance the existing literature by pinpointing essential SMA techniques for corporations, analyzing their dissemination based on structural characteristics, and conducting cluster analyses to explore performance variances among different corporate groups The adoption of SMA techniques varies significantly across firms; for instance, Lachmann, Knauer, and Trapp (2013) note that many SMA methods initially designed for non-hospital sectors are now utilized in hospitals, although commonly used techniques like the balanced scorecard and activity-based costing see only moderate application in that context Additionally, Cadez (2006) identifies capital budgeting and competitor-focused techniques as the most prevalent, while customer-focused techniques rank among the least utilized.

1.2.3 Research on the relationship between environment, strategy choice and strategic management accounting practices

This article explores strategic management accounting (SMA) within organizational contexts, emphasizing the principles of contingency theory It posits that optimal performance arises from the alignment between management accounting systems and contingent factors, as evidenced by Cadez (2007) Research by Gerdin (2005) and Seaman and Williams (2011) highlights SMA's role in enhancing performance measurement through strategic indicators, aligning with the organization's strategic objectives.

Studies have explored the impact of competitive strategies and strategic management accounting (SMA) techniques on the performance of medium and large businesses For instance, Cinquini and Tenucci (2010) analyzed 328 Italian manufacturing firms with sales exceeding $25 million, finding that both defender and cost leader strategies are more inclined to utilize SMA techniques focused on cost information Similarly, Fowzia (2011) highlighted variations in the application of SMA techniques between cost leadership and differentiation strategies Aykan and Aksoylu (2013) further examined the influence of competitive strategies—cost leadership, differentiation, and focus—on perceived business performance Their findings indicate that differentiation strategies, along with competitor-oriented and customer-oriented SMA techniques, significantly enhance the perceived qualitative performance of businesses.

1.2.4 Research on strategic management accounting process

Despite the extensive research on various aspects of Strategic Management Accounting (SMA), there is surprisingly less focus on the actual process of SMA usage Some scholars view SMA as a process and contend that its techniques can be categorized into distinct stages.

The perceptions of the Strategic Management Accounting (SMA) process vary significantly, as highlighted by different scholars Dixon and Smith (1993) outline a four-stage SMA process consisting of strategic business unit identification, strategic cost analysis, strategic market analysis, and strategy evaluation In contrast, Brouthers and Roozen (1999) propose a three-stage approach that includes monitoring, decision-making and planning, and controlling Additionally, Lord (1996) presents a more comprehensive six-stage SMA process, further illustrating the diversity in understanding and implementing SMA techniques.

(2) Exploitation of cost reduction opportunities

(3) Matching of accounting emphasis with strategic position

(5) Exploitation of cost reduction opportunities

(6) Matching of accounting emphasis with strategic position.” (Lord, 1996, p 352)

Shah et al (2011) outline the strategic management accounting (SMA) process in four key stages: gathering competitor information, utilizing accounting for strategic decisions, reducing costs based on these decisions, and achieving competitive advantage by identifying opportunities and making strategic choices While researchers may have different perspectives on the SMA process, it is primarily influenced by the overarching views on strategic management.

Strategic management accounting (SMA) has been a focal point of study for over 25 years, significantly influencing practice, academia, and the accounting field Despite the growing interest in how SMA relates to intellectual capital and intangibles, empirical exploratory research in this area remains scarce Recent studies indicate a shift towards understanding the management and reporting of intellectual capital, highlighting the critical role of strategic management accounting practices in this process.

1.2.5 Review of studies investigating the relationship between strategic management accounting practices and corporate performance

Review of studies of intellectual capital and strategic management accounting in

Vietnam, a developing nation with a significant population, underwent transformative changes in 1986 when individual entrepreneurs gained the right to participate in light industry, coinciding with the Sixth Party Congress's approval of economic reforms that reduced state control Since these reforms were implemented in the 1980s, Vietnam has seen remarkable economic growth, with an average GDP growth rate of 6.45 percent from 2000 to 2017, peaking at 8.48 percent in Q4 2007 and dipping to 3.12 percent in Q1 2009 (Trading Economics).

Vietnam's transition to a market economy, while characterized by a strong entrepreneurial spirit, faces challenges such as inadequate physical infrastructure, technology deficits, and a lack of marketing and international business skills To enhance the competence of its labor force, Vietnam must improve education quality, with a particular focus on intellectual property protection, as evidenced by the low registration of products and designs For Vietnamese exporters to thrive internationally, they need to acquire knowledge in banking, shipping, insurance, and marketing The success of Vietnam's economy hinges on a blend of structural and human capital, alongside robust international relations and a culture of resilience and adaptability Therefore, prioritizing the development of intellectual capital is crucial for the future of Vietnamese enterprises and the nation as a whole.

Vietnam's emergence as a growing economy is marked by the rise of the private sector, the development of securities markets, and increased participation in international trade Public enterprises play a significant role, contributing 26.8% to the country's GDP in 2015 With Vietnam's deeper integration into the global economy through agreements like the Trans-Pacific Partnership (TPP) and the ASEAN Economic Community (AEC), competition for listed enterprises has intensified The influx of foreign companies has brought valuable knowledge, skills, and infrastructure, fostering innovation across industries Despite significant changes within organizations during this period of international integration, there remains a lack of measurement and valuation of intellectual capital—encompassing human resources, structural, and relational capital—impacted by competitive pressures.

1.3.2 Research on intellectual capital in Vietnam

Most intellectual capital research originates from Western countries, with empirical studies conducted across various nations, including North America, Germany, South Africa, Australia, Bangladesh, and several Asian countries like Malaysia, Taiwan, Singapore, and Thailand Despite the significant growth of emerging Asian economies, there is a scarcity of research on the role of intellectual capital in sustaining this growth In Vietnam, the exploration of intellectual capital remains insufficiently addressed.

Since the 2010s, international interdisciplinary accounting research conferences have provided valuable opportunities for intellectual capital (IC) researchers to share their findings and receive feedback However, while some sessions focus on IC, most papers presented at conferences in Vietnam are authored by international researchers and often overlook the unique context of Vietnam A review of academic databases reveals a scarcity of relevant studies, with only one notable paper by Nga and Thomas (2005) addressing the role of IC in Vietnam's development across national, industrial, and firm levels, along with policy recommendations Another article by Nhon, Thong, and Van Phuong (2018) discusses the influence of IC dimensions on firm performance but lacks empirical research This highlights a pressing need for further investigation into IC within Vietnamese firms, emphasizing the importance of developing this area of research.

Intellectual capital (IC) in Western countries has been extensively analyzed, providing insights into its measurement and management However, the applicability of this knowledge to Vietnam's emerging economy remains uncertain, as international IC practices may not directly translate to the local context Consequently, it is essential to conduct research to explore the understanding and perceptions of Vietnamese managers regarding intellectual capital.

1.3.3 Research on strategic management accounting in Vietnam

Vietnam's economic transformation has significantly driven the development of its economy and businesses, particularly through the integration of international accounting practices Over the past decade, Vietnamese enterprises have increasingly adopted advanced accounting techniques aligned with market mechanisms, following the recognition of management accounting in the Accounting Law of 2003 and Circular 53/2006/TT-BTC Although management accounting has existed globally for a long time, Vietnam's system has evolved through various stages since the early 1990s, with numerous distinct themes emerging in research.

Table 1.5 Research trends on management accounting in Vietnam

1990s  The directions are related how to build the contents and organization approaches of management accounting system in Vietnamese enterprises (Duoc, 1997)

 The author came up with organization solutions of management accounting nested within financial accounting (Dung, 1998)

 The directions are how to build reports system of management accounting in Vietnamese enterprises (Quang, 1999) h

In the 2000s, management accounting has been extensively researched within specific industries, including manufacturing (Le, 2002), mining (Hoi, 2007), construction state-owned enterprises (Giang, 2002), transportation (Dinh, 2003), and the pharmaceutical sector (Thuy, 2007).

2010s  Management accounting has been studied in association with the other research fields such as management of environmental issues (Thien, 2010), sustainable development reporting (Thien & Hung,

2016), corporate social responsibilities (Long, 2015), management control system (Tran, 2010), strategic decision making in market orientation and competition (Nguyen & Doan, 2016)

 Strategic management accounting is directed how to implement in Vietnamese enterprises (Que & Thien, 2014)

 The factors have facilitated the use of strategic management accounting in Vietnam – a transitional economy (Anh, 2010)

 The authors have focused on only one of strategic management accounting techniques (i.e Strategic cost management (Hoa,

2014), Time-driven ABC (Thien, 2014), Lean accounting (Hoa,

2015), Balanced scorecard (Van, 2015)) to analyse the conditions resulting in the successful implementation

Source: The author’s literature review

Vietnam's economic, political, and social landscape is distinct from that of Western and other Asian nations Since implementing an open-door policy, competition among Vietnamese enterprises has surged, with numerous private, joint ventures, and wholly foreign-owned businesses emerging over the past two decades This influx of foreign organizations has introduced valuable insights into strategic management accounting for local practitioners and scholars Consequently, research on strategic management accounting began to gain traction in Vietnam during the 2010s, although there remains a lack of comprehensive documentation and analysis regarding the adoption of these practices.

In Vietnam, research indicates that while small and medium enterprises primarily utilize traditional management accounting, it is the medium-to-large enterprises that focus on strategic management accounting to enhance decision-making Despite its significance, there is a lack of empirical studies exploring the effects of strategic management accounting practices on the performance of Vietnamese enterprises, a topic that has been widely examined in other countries.

Research gaps

This study highlights three significant research gaps: the insufficient examination of the performance implications of intellectual capital in relation to the mediating effects of strategic management accounting practices, the limited empirical research on the relationship between intellectual capital and various strategic management accounting practices, and the scarcity of studies focused on intellectual capital and strategic management accounting practices within the context of Vietnam.

1.4.1 Lack of studies concerning performance implication of intellectual capital in association with the mediating role of SMA practices

In the realm of intellectual capital (IC) accounting research, empirical studies have predominantly concentrated on the direct correlation between IC components and corporate performance, with limited exploration of their indirect relationships Ittner and Larcker (1998) emphasize the necessity for management to identify and communicate the value drivers, such as IC, to enhance information systems and resource allocation This indicates that organizations rich in intellectual capital are likely to have developed strategic management accounting practices However, Tayles et al (2007) highlight a gap in research regarding how firms with high IC levels have tailored their strategic management accounting to address the challenges posed by IC, which could ultimately boost corporate performance While existing models often examine the indirect pathway between strategy and performance through management practices, few studies, like that of Asiaei et al (2018), have systematically analyzed the mediating role of these practices in linking resources to performance As noted by Alcaniz et al (2011), the literature on IC has become somewhat repetitive, primarily focusing on its direct impact on performance This underscores the necessity for future research to investigate both the direct and indirect effects of intellectual capital on corporate performance through the mediation of strategic management accounting practices within organizations.

1.4.2 Lack of empirical research concerning the relationship between intellectual capital and each group of SMA practices

A literature review on intellectual capital highlights the need for professional accountants to adopt a strategic management accounting approach to effectively manage an organization’s valuable intellectual capital (IC), as noted by Roslender and Fincham (2001) However, the specific role of management accounting in IC management within high IC companies remains unclear due to a lack of empirical research There is limited academic literature exploring how management accounting practices evolve as organizations adjust their strategies to emphasize value drivers, particularly strategic intangible assets Addressing how strategic management accounting interacts with intellectual capital represents a critical gap that requires further investigation.

1.4.3 Lack of Vietnamese empirical studies on intellectual capital and SMA practices

Most research on intellectual capital and strategic management accounting (SMA) practices has been primarily conducted in developed Western countries and select Asian nations, such as China, Malaysia, Taiwan, and Hong Kong, rather than in developing Asian countries with transitional economies like Vietnam While Western studies assert that intellectual capital is a crucial driver of superior performance, there is a notable lack of studies in developing countries that validate and operationalize these claims, particularly in unstable business environments.

Vietnam Vietnam may differ from Western countries in terms of culture, economy and political environment that influence the progress of IC development (Nga & Thomas,

2005) as well as the orientations how to implement strategic management accounting (Loi,

The relationship between culture and strategic management accounting reveals a contrast between Vietnam's collectivism and the individualism prevalent in the West This raises the question of whether Vietnamese collectivism uniquely influences the implementation of strategic management accounting compared to Western practices While numerous international studies highlight the advantages of strategic management accounting, there is a notable lack of empirical research exploring its impact on corporate performance within the Vietnamese context Therefore, investigating the effects of strategic management accounting practices on the performance of Vietnamese enterprises could enhance our understanding of how these benefits translate in a transitional economy, potentially paralleling those observed in Western environments.

While existing research has extensively examined the value relevance and market valuation of intellectual capital in various countries, its performance in Vietnam remains largely under-researched This gap can be attributed to two main challenges: firstly, Vietnamese companies often fail to provide a thorough account of their intangible investments, with many expenditures expensed rather than capitalized and insufficient disclosure practices Secondly, a lack of awareness among Vietnamese managers regarding the critical importance of intellectual capital in management has hindered interest in this area, resulting in few local studies addressing its performance implications.

Research on intellectual capital and strategic management accounting within the context of Vietnam's transitional economy can significantly enhance the existing literature.

Chapter 1 reviews the international studies and Vietnamese studies in terms of intellectual capital, strategic management accounting, corporate performances and their mutual relationships to identify research gaps for this research

While most empirical studies have concentrated on the direct link between intellectual capital components and corporate performance, there is limited research exploring the indirect relationship, particularly through the mediating role of strategic management accounting practices Furthermore, the academic literature lacks clarity on the specific role that strategic management accounting plays in relation to intellectual capital.

Intellectual capital is a crucial intangible asset that sustains the competitive advantages of economies and firms While research on intellectual capital has been ongoing since the 1980s, studies in Vietnam remain limited, highlighting a need for comprehensive exploration within the local context This paper emphasizes the importance of systematically investigating the relationship between intellectual capital, strategic management accounting practices, and corporate performance in Vietnam Such research will not only enrich Vietnamese literature but also enhance the theoretical understanding of intellectual capital management through strategic accounting practices.

The upcoming chapter defines intellectual capital and its components while exploring corporate performance and strategic management accounting practices It also presents existing theories that support the measurement of intellectual capital, laying the groundwork for developing IC variables in Chapter 3.

THE CONCEPTS AND INTELLECTUAL CAPITAL

Definition of intellectual capital

The global economy is transitioning from an industrial model reliant on tangible assets to a knowledge-based framework that emphasizes intangible resources such as human capital, technology, core competencies, and innovation Major companies like Microsoft, Amazon, and Google exemplify this shift towards a knowledge-driven economy This transition is further highlighted by the increasing market valuations of companies compared to their book values, revealing a significant gap that indicates traditional financial accounting methods inadequately capture a firm's true economic worth Research by Stewart and Ruckdeschel (1998) underscores that conventional accounting fails to accurately assess the value of intangible assets embedded within an organization's operations, despite the market's clear recognition and reward of these assets.

Since the mid-1990s, intellectual capital has gained prominence as a topic of discussion, particularly regarding the disparity between a firm's market value and book value This difference is often regarded as the source of a firm's value However, the literature reveals a lack of consensus on the definition of intellectual capital, leading to varied interpretations and understandings of the concept.

Before exploring the definitions and elements of intellectual capital, it is essential to differentiate between knowledge capital and intellectual capital Polanyi (1967) identifies two dimensions of knowledge within an organization: tacit and explicit knowledge Tacit knowledge, as described by Nonaka (1994), encompasses both technical and cognitive aspects Cognitive knowledge pertains to an individual’s mental models, including beliefs and paradigms, while technical knowledge involves specific skills and know-how applicable to particular contexts.

(2001) explains that the latter dimension - explicit knowledge such as procedures, routines is documented and structured with a fixed-content which is externalized consciously

Discussing the difference between knowledge capital and intellectual capital, Roos (1998) states that:

Intellectual Capital (IC) encompasses all processes and assets typically absent from the balance sheet, including intangible assets recognized by modern accounting methods, such as trademarks, patents, and brands While knowledge is a component of IC, it extends beyond mere knowledge to include the management of relationships with external parties like trade distributors, allies, customers, and stakeholders These elements collectively contribute to value creation in today’s business landscape.

There is a large part of the initial intellectual capital literature contributing into how to define the notion of IC, summarized by the following table 2.1:

Table 2.1 Definitions of intellectual capital

Researchers (year) Definitions Dimensions of IC

Intellectual capital (IC) is an intangible asset that plays a crucial role in organizations, significantly enhancing financial performance and providing a competitive edge.

Technology, Consumer trust, Brand image, Corporate culture and Management skills

Brooking (1996) IC “is the term given to the combined intangible assets which enable the company to function”

Market assets, Intellectual property assets, Human-centered h assets, Infrastructure assets

IC is defined as knowledge that can be converted into value IC is “the aggregate stocks and flows of its potentially useful skills, knowledge and information”

Human capital, Structural capital and

Sveiby (1997) IC consists of invisible assets which result in the difference between a firm’s market value and its book value

Internal structure, External structure and Employee competence

IC is presented as intangible assets and

“it produces value to enterprises that can be reflected as final income in financial statements, but it cannot be expressed as an accounting title in financial statements.”

Human capital and Structural capital

IC “is a combination of intangible resources and activities that allows an organization to transform a bundle of material, financial and human resources into a system capable of creating stakeholder value.”

Organizational capital and Human capital

IC is “the hidden value of a firm which illustrates firm intangible resources that cannot be measured by financial metrics”

Human, Organizational, Technological, Business relations, and Context

Wang (2011) IC is defined as “an intangible asset, which does not exist in physical form

Human, Customer, Process and Innovation h but holds value and can produce future advantages, including competitive advantage to the organization”

Source: The author’s literature review

Following the above-mentioned literature, there is lack of a consensus IC definition; however, it is clear that most prior authors seem to agree:

 IC is a multi-dimensional concept as a sum of all intangible assets including knowledge

 IC includes knowledge capital that can be put to use to create wealth;

 Accumulating IC is beneficial to creating competitive advantage or business value;

 IC is a source of intangible assets that often do not appear on the statement of financial position;

 IC consists of invisible assets which result in the difference between a firm’s market value and its book value;

 IC consists of main components; those are human capital, structural capital and relational with stakeholders

Intellectual capital (IC) is universally recognized as a strategic intangible resource encompassing information and knowledge, essential for gaining competitive advantages and sustainably creating value for key stakeholders The three primary interrelated components of IC include human capital, structural (internal) capital, and relational (external) capital, which are widely acknowledged in the literature This article focuses on analyzing and measuring these critical components of intellectual capital.

Components of intellectual capital

IC researchers, such as Barney (1991b), Brooking (1996), Edvinsson and Sullivan

(1996), Sveiby (1997), Stewart and Ruckdeschel (1998), Petty and Guthrie (2000); Bontis and Fitz-enz (2002), Wang (2011), all include human capital (HC) as a component of IC h

Human capital encompasses a broader scope than human resources, emphasizing the individual competencies of employees, including their knowledge, skills, innovativeness, and talents (McGregor, Tweed, & Pech, 2004) Barney (1991b) further defines human capital to include aspects such as training, judgment, relationships, and insights, highlighting the importance of tacit knowledge that employees possess (Bontis & Fitz-enz, 2002) This tacit knowledge can be externalized into explicit knowledge, which can be stored in knowledge management systems Edvinsson and Sullivan (1996) describe human capital as comprising skills, attitude, and intellectual agility, where skills generate value through the knowledge and talent of individuals Attitude is influenced by personality traits and is less susceptible to organizational improvement, while intellectual agility refers to the ability to transfer knowledge across different contexts.

Human capital is essential for organizations, serving as a key driver of innovation and strategic renewal to adapt to environmental changes through the development and implementation of effective strategies (Wright, McMahan, & McWilliams, 1994) In today's knowledge-based economy, the value of human capital continues to rise, as experienced employees with refined skills become invaluable assets to firms (Helm Stevens, 2011) A higher level of intellectual capital often leads to increased productivity and higher income levels, making it crucial for human resource managers to attract top talent and cultivate employees' explicit knowledge to achieve a competitive advantage (Bontis & Fitz-enz, 2002).

When analysing the contents that should be reported in IC report, Campbell and Abdul Rahman (2010) illustrate the elements of human capital detailed in Appendix 4

Structural capital, as defined by Bontis (2001), encompasses the hardware, software, databases, organizational structure, patents, and trademarks that employees utilize to enhance business processes It focuses on the knowledge infrastructure embedded within an organization's routines, which includes technological components and architectural competencies (Gold & Malhotra, 2001) This form of capital also represents the learning and knowledge applied in daily operations, highlighting that the knowledge retained in an organization after employees depart constitutes the essence of structural capital (Mouritsen et al., 2004; Nazari, 2010; Wang, 2011) While human capital is crucial for developing structural capital and influences the organizational framework (Nazari, 2010), structural capital can exist independently of human capital, as illustrated by the fact that patents, created by human capital, ultimately belong to the organization (J Chen et al., 2004).

Structural capital is essential for organizations as it encompasses the frameworks and systems that support human capital It includes non-human knowledge repositories such as databases, process manuals, routine procedures, organizational culture, and corporate publications, all of which contribute to the organization's value.

Structural capital is a complex component of intellectual capital that interrelates with other capitals, necessitating a clear definition to avoid overlapping meanings This study adopts definitions from Bontis (2001) and Campbell and Abdul Rahman (2010), focusing on technological and architectural elements Key aspects of structural capital include organizational culture, processes, and management philosophy, which are essential for effective analysis and reporting.

IC report, Campbell and Abdul Rahman (2010) illustrate the elements of structural capital detailed in Appendix 5

Relational capital, a key component of intellectual capital, is often defined ambiguously, with some researchers equating it to customer capital, which emphasizes the strength and loyalty of customer relationships (M'Pherson & Pike, 2001; Saint-Onge, 1996; Wang, 2011) However, focusing solely on customer capital can overlook other vital stakeholders such as shareholders, creditors, and employees (Helm Stevens, 2011) Relational capital encompasses all external relationships of an organization, including suppliers, partners, and networks, thereby broadening the concept beyond just customer interactions (Bontis & Fitz-enz, 2002; Helm Stevens, 2011; Levy, 2009; Mouritsen et al., 2004) It involves managing relationships with various stakeholders to foster brand loyalty, reputation, and overall organizational success, ultimately enhancing wealth creation through improved human and structural capital (Sydler, Haefliger, & Pruksa, 2014; María Viedma Marti, 2001).

Relational capital is crucial for organizations as it fosters innovation and future growth opportunities According to Kong (2009), effective organizational relationships facilitate knowledge exchange with external stakeholders, enhancing the ability to generate creative ideas Organizations that understand the needs of their stakeholders are more likely to develop improved products and services (Helm Stevens, 2011), making them more competitive in the market Building relational capital is essential for sustainable growth, as it directly contributes to current and future revenues through strong customer relationships Youndt and Snell (2004) emphasize that alongside investing in structural capital to improve processes, managers should prioritize social relations to safeguard their organization against unfair competition and maintain competitive advantages.

When analysing the contents that should be reported in IC report, Campbell and Abdul Rahman (2010) illustrate the elements of relational capital detailed in Appendix 6 h

Definition of corporate performance

Corporate performance, as defined by Dorestani (2009), encompasses a range of critical measures essential for an organization's success, incorporating both financial and non-financial indicators For decades, frameworks have been established to guide managers in evaluating their firms' performance Notably, DuPont has employed a pyramid of financial ratios since the early twentieth century, effectively linking various financial metrics to investment returns, thereby serving as valuable tools for assessing shareholder wealth Key ratio-based measures, such as return on assets (ROA), return on equity (ROE), and return on capital employed (ROCE), provide diverse perspectives on a firm's overall financial performance.

Kaplan and Norton (2001) emphasize that traditional financial ratios, such as those in the DuPont pyramid, fail to adequately reflect the evolving competitive landscape and strategies of modern organizations, primarily due to their historical focus which promotes short-term thinking Investors, in the context of a knowledge-based and innovation-driven economy, find financial statements increasingly irrelevant, as they do not account for the economic value of intangible assets, leading to greater information asymmetry and inefficient resource allocation in the stock market (Arvidsson, 2011) The significant disparity between a firm's market value and the book value of its assets has prompted the development of contemporary methods to quantify intangibles, such as economic value added (EVA), Tobin's q, and the market-to-book ratio (Gebhardt, 2002) These approaches aim to provide a tangible perspective on intangibles, with many researchers advocating for the use of EVA, Tobin's q, or the market-to-book ratio as effective indicators of a firm's financial performance.

Numerous researchers, including F Chen, Hope, Li, and Wang (2011) and Ming-Chin et al (2005), suggest that in an efficient market, investors tend to value firms with higher investment efficiency more favorably To optimize shareholder value, firms should continue investing until the marginal benefit of investment aligns with the marginal cost.

Information asymmetry between management and shareholders can lead to suboptimal investment decisions, resulting in underinvestment (investing less than expected) or overinvestment (investing more than expected) (Juan Pedro Sánchez & Gomariz, 2012) In ideal financial markets, all positive net present value (NPV) projects should be financed to increase firm value However, market imperfections, along with information asymmetries and agency costs, can result in negative NPV projects being pursued (overinvestment) and positive NPV projects being rejected (underinvestment) (Healy & Palepu, 2001; Hubbard, 1997) Agency theory suggests that these investment inefficiencies stem from asymmetric information among stakeholders, making investment efficiency a crucial metric for evaluating corporate performance in internal management activities.

In addition to financial metrics like investment efficiency and financial ratios, the evolution of corporate performance measurement has led organizations to adopt non-financial measures that align with their objectives Current trends indicate that financial analysts and investors increasingly rely on non-financial information to assess firm value, moving beyond traditional financial statements Research shows a disparity in how management prioritizes non-financial disclosures, with Vandemaele, Vergauwen, and Smith (2005) noting that companies tend to share more about their external relationships, such as customers and partners, while providing less information on human capital, including employee education and expertise Arvidsson (2011) highlights that corporate social responsibility is often the least emphasized category in corporate disclosures Consequently, non-financial measures are essential for owners and management to evaluate corporate performance effectively However, this study primarily focuses on financial information as a criterion for measuring corporate performance.

The four-stage stock market valuation model by Dorestani (2009) is used to report corporate performance in accounting literature, as follows: h

Figure 2.1 Four-stage model of corporate market valuation

Determinants of strategic management accounting practices

Global competitive pressures, deregulation, and advancements in information and manufacturing technology have fundamentally transformed our economy, leading to significant changes in manufacturing and service industries These shifts are influencing production methods, the use of automated equipment, and flexible technologies, while also reshaping organizational structures, business strategies, and managerial philosophies.

In today's competitive global landscape, companies prioritize customer satisfaction by implementing innovative management strategies, transforming manufacturing processes, and investing in advanced technologies, all of which significantly impact their management accounting systems.

These changes challenged the traditional management accounting system New business strategies have also questioned the conventional role of management accounting

As Ashton, Hopper, and Scapens (1991) note:

The investigation by industrialists, academics, and management consultants has led to a prevailing ideology focused on crisis and transformation within the manufacturing sector, highlighting a growing critique of traditional management accounting practices.

Furthermore, it is claimed that traditional management accounting information had failed to provide the information requirement for organization’s strategic purposes

Traditional management accounting has been criticized for its inability to meet the information needs essential for enhancing organizational competitiveness and long-term performance (Bromwich, 1990; Kaplan, 1984; Kaplan & Norton, 2001) Drury (2013) summarizes these principal criticisms into key categories.

Conventional management accounting is increasingly inadequate for today's competitive and technological landscape, as traditional product costing systems often yield misleading information for decision-making Additionally, management accounting practices tend to prioritize financial accounting requirements, overshadowing their original purpose Furthermore, conventional management accounting primarily concentrates on internal activities, neglecting the critical external environment in which businesses operate (Drury, 2013, p 562).

Strategic Management Accounting (SMA) has emerged as a vital tool for gaining competitive advantage, addressing the shortcomings of traditional management accounting by focusing on customers, competitors, and the long-term effects of strategic decisions (Cadez, 2006) Introduced in literature since 1981, SMA was first coined by Simmonds, who defined it as the provision and analysis of management accounting data related to a business and its competitors for strategic development and monitoring (Simmonds, 1981) This innovative perspective emphasizes the externally-focused role of management accountants (Cadez, 2006) Additionally, Bromwich (1988) expands on this concept by defining SMA as the assessment of an enterprise's comparative advantages and the long-term benefits of its products to customers and the firm.

Management accounting plays a crucial role in strategy development, as highlighted by Simmonds (1981) and Bromwich (1988) Strategic Management Accounting (SMA) focuses on external information relevant to the organization Although SMA is primarily used by accounting scholars and practitioners in the UK, Australia, and New Zealand, its significance in integrating external factors into management accounting is widely recognized.

In the USA, the term strategic cost management (SCM) is prevalent in literature, as defined by Shank and Govindarajan (1993), who describe it as the integration of financial analysis with value analysis, strategic positioning analysis, and cost driver analysis While SCM shares similarities with strategic management accounting (SMA), some experts argue that SMA encompasses a broader scope Key distinctions between strategic and traditional management accounting are highlighted in Table 2.2.

Table 2.2 Some key differences between strategic and traditional management accounting Indicators Strategic management accounting Traditional management accounting

- provide information to make key strategic decisions

- require a stronger external focus regarding the behavior of stakeholders

- aid in the creation of operational strategies

- measure and report both financial and non-financial performance ensure efficient use of resources

Direction Forward looking Feedback looking

Competitor cost structure Competitor product costs Relative market share Relative profitability Competitor price margin

Cost structure Product costs Market share Profitability Price margins Tasks Competitor analysis

Customer analysis Pricing decision Portfolio analysis Corporate decision support

Profitability analysis Performance evaluation Budgeting

Operational and management decision support

In the 1990s, numerous researchers, including Bromwich, Ward, Dixon and Smith, Foster and Gupta, and Guilding et al., contributed significantly to the development of the concept of strategic management accounting Their collective efforts laid the groundwork for understanding how strategic management accounting can enhance decision-making and organizational performance.

2010) Although their definition and description of SMA differ considerably, three typical characteristics of SMA can be drawn from their writings:

- A long-term, forward-looking orientation;

- The provision of both financial and non-financial information for managerial decision making

The first original work of SMA practices was recommended by Guilding et al

In their 2000 study, the authors identified 12 techniques of Strategic Management Accounting (SMA), including attribute costing, brand valuation, and target costing, among others (Cadez, 2006) Cravens and Guilding (2001) expanded this list to 15 techniques by adding activity-based costing, benchmarking, and integrated performance measurement Additionally, Guilding and McManus (2002) introduced three customer-related SMA techniques: customer profitability analysis, lifetime customer analysis, and the valuation of customer groups, bringing the total to 18 techniques categorized into four groups Cravens and Guilding (2001) also identified three main dimensions of strategic management accounting practices: strategic cost management, competitor accounting, and strategic accounting This study enhances their findings by incorporating three customer-focused techniques, establishing a fourth dimension in SMA practices.

“customer accounting” based on the research of Guilding and McManus (2002).

Intellectual capital measurement models

Intellectual capital is often considered immeasurable (Wall, Kirk, & Martin, 2003), but the real challenge lies in the multitude of measurement methods that yield diverse and sometimes contradictory results (Fritzsche, 2012) Sveiby (2005) emphasizes that the first step in any measurement initiative should be to clarify its purpose Luthy (1998) and Mitchell Williams (2001) categorize intellectual capital measurement into at least three models: the quantitative approach, which assigns numerical values, and the qualitative approach, which utilizes scorecards to identify key organizational objectives.

Table 2.3 Summary of measurement approaches that are mainly used in intellectual capital research

- Investor-assigned market value (IAMV TM )

- Value added intellectual capital coefficient (VAIC TM )

- Economic value added (EVA TM )

- Total value creation (TVC TM )

- Inclusive valuation methodology (IMV TM )

Quantitative approach – Market capitalization model

The market capitalization model, as outlined by Sveiby (2005), provides methods to evaluate intellectual capital by analyzing the difference between a company's market capitalization and its book value of shareholders' equity This model is characterized by its reliance on capital market values to estimate intellectual capital worth Key methods within this framework include Tobin's q, Market-to-book value, and Investor-assigned market value (IAMV TM), which are briefly discussed in Appendix 8 The model effectively addresses the challenge of assessing a firm's excess value over its replacement cost-adjusted balance sheet by utilizing market mechanisms.

Quantitative approach – Return on assets model

Many ROA methods focus on creating an indicator to assess the efficiency or potential value of Intellectual Capital (IC) This indicator is calculated using specific formulas that evaluate the performance and effectiveness of IC investments.

To calculate a company's Return on Assets (ROA), average pre-tax earnings over a specific period are divided by the average tangible assets This ROA is then compared to the industry average, and the difference is multiplied by the company's average tangible assets to determine the average annual earnings attributable to intangible assets Finally, by dividing these average earnings by the company's average cost of capital or interest rate, an estimate of the value of its intangible assets or intellectual capital can be derived.

This article explores several applied methods for assessing intellectual capital, including the Value Added Intellectual Capital Coefficient, Calculated Intangible Value, and Economic Value Added, detailed in Appendix 9 These methods primarily utilize indicators from historical financial reports as proxies for intellectual capital value However, a significant limitation of this approach is its inability to provide a definitive measure of intellectual capital.

IC required to start a company because it provides a measure of IC while operating

Quantitative approach – Direct intellectual capital model

The evaluation of intellectual capital (IC) components involves various models that consider multiple variables categorized into distinct groups Each group encompasses specific IC components, which are individually identified and measured before being aggregated to create a comprehensive measure of intellectual capital Assessing these components requires different scales, including counts, dollar values, and ratios Popular methods for this evaluation include Intellectual Asset Valuation, Total Value Creation (TVC TM), and Inclusive Valuation Methodology (IMV TM), which are further discussed in Appendix 10.

The model focuses on identifying components of intangible assets and intellectual capital, generating indicators that are reported in scorecards Unlike direct intellectual capital models, it does not assign a dollar value to these assets The primary aim of qualitative models is to highlight key organizational elements and aid in tracking progress towards defined objectives Popular methods in this category include Intangible Assets Monitor™, Skandia Navigator™, IC Index™, Balanced Scorecard™, and Value Chain Scoreboard, with a detailed discussion of these methods available in Appendix 11, though it is not the focus of this research.

Chapter 2 presents the concepts of intellectual capital, strategic management accounting practices, corporate performance, and reviews some of IC measurement models before developing this study’s research models

This study defines intellectual capital (IC) as the strategic management of intangible resources, such as information and knowledge, to gain competitive advantages It identifies three primary interrelated components of IC: human capital, structural capital, and relational capital, aligning with a broad consensus in existing literature Additionally, IC measurement can be categorized into three models: quantitative approaches, including direct IC, ROA, and market capitalization models, and qualitative approaches like the scorecard model This research also references the foundational work on strategic management accounting (SMA) practices by Guilding et al.

(2000) and the supplementary studies, this study categorizes 18 SMA techniques into 4 groups related to strategic cost management, competitor accounting, strategic accounting and customer accounting

The four-stage stock market valuation model developed by Dorestani (2009) assesses corporate performance across four dimensions: productivity, profitability, non-financial indicators, and marketable value However, this study primarily emphasizes financial dimensions, which may limit its broader applicability.

The following chapter focuses on underlying conceptual frameworks to develop testable hypotheses which answer research questions to bridge research gaps h

THEORETICAL FRAMEWORK AND HYPOTHESES

Mediating effect of strategic management accounting practices in the relationship

The initial research model, illustrated in Figure 3.1, highlights the interrelationship among three dimensions of intellectual capital (IC) and their impact on strategic management accounting practices It further explores how these dimensions of IC influence corporate performance Additionally, the model investigates the potential mediating effect of strategic management accounting practices on the relationship between intellectual capital and corporate performance.

Previous research has primarily focused on the link between intellectual capital (IC) and corporate performance, often overlooking the crucial role of strategic management accounting practices For firms to fully leverage their intellectual capital and enhance performance, the integration of strategic management accounting is essential While numerous empirical studies have explored the direct relationship between IC and performance, there is a notable lack of investigation into the indirect effects of intellectual capital on corporate performance This study aims to address this gap by proposing a novel research model and formulating relevant hypotheses.

Figure 3.1 The first research model

Source: Developed by the author

3.1.1 Human capital, structural capital and relational capital reciprocally affect each other (H 1 )

Managerial activities concerning intellectual capital (IC) must work in harmony, as human, structural, and relational elements mutually influence one another (Edvinsson & Sullivan, 1996; Hsu & Fang, 2009) Their collaborative efforts in generating knowledge value lead to synergy, reinforcing the idea that these dimensions of IC are most effective when they support one another (Stewart & Ruckdeschel, 1998) Research by Bontis and Fitz-enz further emphasizes this interdependence, highlighting the importance of a cohesive approach to managing IC.

Research from 2002 indicates that human capital plays a crucial role in enhancing relational capital across all industries, while it also significantly influences structural capital in non-service sectors Additionally, relational capital impacts structural capital in both service and non-service industries For instance, the skills and capabilities of employees (human capital) directly contribute to a company's operational efficiency (structural capital) Furthermore, having high-quality employees not only boosts process efficiency but also attracts valuable customers and business partners.

Relational capital significantly enhances structural capital, as demonstrated by Hsu and Fang (2009) When a firm cultivates strong relationships with customers and business partners, it empowers its employees to effectively manage daily operations and optimize business processes This interplay between relational and structural capital forms the basis for the hypotheses developed in this study.

Hypothesis 1a: Human capital positively impacts on relational capital

Hypothesis 1b: Human capital positively impacts on structural capital

Hypothesis 1c: Relational capital positively impacts on structural capital

3.1.2 Intellectual capital impacts on SMA practices (H 2 )

In today's competitive landscape, organizations recognize that their sustainable competitive advantage lies in effectively utilizing existing intellectual capital and rapidly acquiring new intellectual resources According to Teece (2000), leveraging intellectual capital is crucial for maintaining a competitive edge.

“the competitive advantage of companies in today’s economy stems not from market position, but from difficult to replicate intellectual capital and the manner in which they are deployed.”

Companies are increasingly striving to become learning organizations, recognizing that those who prioritize intellectual capital will thrive (Carlucci, Marr, & Schiuma, 2004) Intellectual capital enhances knowledge management and refines traditional management accounting systems through strategic management accounting techniques (Wiig, 1994) However, intellectual capital alone does not create value or drive growth; it must be integrated with other management factors to be effective (Lev & Daum, 2004) Efficient support systems are essential, as investments in areas like training yield financial benefits only when paired with improved business processes and suitable information systems Thus, intellectual capital provides a range of resources—human, infrastructural, and knowledge-based—that can transform management systems, including management accounting and information management systems This understanding of intellectual capital's role in strategic management accounting practices is significantly informed by competence-based theory.

The competence-based view emphasizes a company's ability to identify, develop, and enhance its core competencies as a key source of competitive advantage (Carlucci et al., 2004) Competencies are defined as a combination of skills, technologies, and learning capabilities (Mouritsen et al., 2002) As noted by Hamel and Prahalad (2013), these competencies play a crucial role in achieving sustained success in the marketplace.

The company is viewed as a collection of competencies, with its competitiveness rooted in the development and enhancement of these skills It focuses on implementing a strategy that effectively connects its objectives, resources, and competencies.

Competencies are crucial for organizational development and are reflected in a firm's strategic management accounting practices, which are considered a key competency To foster continuous competency development, organizations must have the necessary resources, particularly knowledge assets and processes These elements, including intellectual capital and strategic management accounting practices, are essential for effective business operations Firms with strong intellectual capital can leverage quality personnel to bridge connections with external networks, facilitating the flow of knowledge and enhancing strategic business planning The interplay between relationships and skilled personnel is vital for developing robust strategic management accounting practices, which in turn are essential for effectively utilizing external knowledge Well-designed strategic management accounting systems enable the accumulation, integration, and dissemination of knowledge throughout the organization.

The design of management accounting systems varies according to a firm's strategic approach, such as differentiation or cost leadership Both types of firms leverage human capital as a key strategic resource that shapes their corporate strategy Specifically, human capital significantly influences the chosen firm-level strategy, which in turn affects the management accounting system's design Widener (2004) provides a comprehensive illustration of the interplay between management accounting systems, firm-level strategies, and human capital strategies.

Table 3.1 Integration of firm-level strategy and reliance on human capital

Differentiation-based firms Low-cost-based firms

Lower reliance on human capital

Higher reliance on human capital

Non-traditional management accounting system

Non-traditional management accounting system

According to Widener's (2004) study, firms with a lower reliance on human capital tend to develop management accounting systems that focus on traditional financial controls, while those with a higher reliance on human capital adopt non-traditional, non-financial controls and actively involve employees in strategic decision-making High human capital firms prioritize non-financial indicators such as employee loyalty, turnover rates, and skill development as key metrics for strategic decisions Additionally, these firms emphasize employee participation in budgeting, favoring frequent forecasting and targeted goal-setting, which leads to a shift from conventional budgeting to a rolling budgeting approach in strategic management accounting (SMA) practices.

Hypothesis 2a: Human capital is positively associated with the practices of strategic management accounting

In terms of competence-based theory, strategic management accounting “as the provision of information assisting to managers in their strategic decision making” (Cleary,

Structural capital encompasses a firm's processes, organizational structure, information systems, and corporate culture, which significantly influence its accounting practices (Hsu & Fang, 2009) A firm characterized by role culture often relies on formalized rules and centralized decision-making, leading to traditional management accounting methods such as imposed budgeting and financial controls (CIMA, 2014b) In contrast, a task culture promotes teamwork and flexibility, favoring non-financial measures and participative budgeting that enhance creativity and job satisfaction (CIMA, 2014b) Firms focused on customer orientation aim to develop efficient organizational routines through strategic management accounting, utilizing intellectual capital to meet informational demands For example, prioritizing structural capital to create a customer databank can enhance strategic management accounting practices by improving customer accounting and reducing decision-making costs due to information insufficiencies This leads to the formulation of the following hypothesis:

Hypothesis 2b: Structural capital is positively associated with the practices of strategic management accounting

Organizations with extensive networks tend to excel in information acquisition and resource allocation, as highlighted by Hsu & Fang (2009) Tsai (2001) notes that employees with strong communication skills and external connections have greater access to diverse resources, enhancing strategic management accounting practices These connections facilitate the sharing of information and professional technology among business partners, thereby increasing a firm's capacity for external information development Relational capital fosters a stronger external focus on competitors, customers, and suppliers, which is crucial for understanding the market landscape—a key component of strategic management accounting By comprehending and addressing stakeholder needs, firms can drive innovation and economic success Strategic management accountants leverage raw information from external relationships to generate data that supports effective strategic planning, performance control, and informed decision-making This leads to the formulation of the following hypothesis:

Hypothesis 2c: Relational capital is positively associated with the practices of strategic management accounting

3.1.3 Intellectual capital impacts on corporate performance (H 3 )

The resource-based view (RBV) serves as the foundational theory in knowledge management and intellectual capital, often referred to as knowledge-based theory Initially introduced by Penrose in 1959 and later expanded by Wernerfelt, Rumelt, and Lamb, RBV posits that a firm's sustainable competitive advantage stems from its resources, emphasizing that economic value arises not just from resource possession but from effective and innovative resource management While RBV treats assets and knowledge as generic resources, it fails to adequately address their specific characteristics Identifying which assets or knowledge can generate a firm's core competencies is crucial Wernerfelt further elaborated that firms achieve core competencies and superior performance through the acquisition and strategic use of both tangible and intangible assets Barney later established four criteria for identifying these strategic assets, raising important questions about their recognition and utilization.

 Valuable: They must be able to exploit opportunities or neutralize threats in the firm’s environment;

 Rare: Competitors must not have them too, otherwise they cannot be a source of relative advantage;

 Imperfectly imitable: Competitors must not be able to obtain them;

 Non-substitutability: It must not be possible for a rival to find a substitute for this asset

Associations between intellectual capital components and each group of strategic

of strategic management accounting practices

The second research model, illustrated in Figure 3.3, explores how firms with intellectual capital (IC) have developed their strategic management accounting (SMA) practices to effectively account for IC components It suggests that managers in these firms should implement more strategic SMA practices to ensure the organization's valuable IC is not overlooked The model investigates which SMA practices—namely strategic cost management, competitor accounting, strategic accounting, and customer accounting—are most commonly utilized to manage specific IC components Notably, as highlighted by Roslender and Fincham (2001), there is a scarcity of empirical literature on the intersection of SMA and intellectual capital Consequently, this study presents the second research model accompanied by relevant hypotheses.

Figure 3.3 The second research model

Source: Developed by the author

A resource-based strategy alone may not suffice for sustaining competitive advantage in a turbulent environment, as many firms with valuable assets struggle to leverage them into dynamic capabilities (Nazari, 2010) The dynamic capability theory highlights the importance of aligning resources with environmental changes, with Teece, Pisano, and Shuen (1997) defining dynamic capabilities as the ability to integrate and reconfigure competencies in response to rapid shifts The transformation of resources into functional competencies that align with the environment is a key outcome of dynamic capabilities (Eisenhardt & Martin, 2000) This raises the question of whether strategic management accounting qualifies as a dynamic capability, with contingency theory supporting its alignment with dynamic and uncertain environments (Sanford).

2009) Increased dynamism means that traditional management accounting’s models of

Strategic management accounting is essential for firms to adapt swiftly to changing conditions, as traditional methods become outdated rapidly (CIMA, 2014a) It serves as a dynamic capability that effectively manages a firm's initiatives, which are integral to its intellectual capital In essence, strategic management accounting not only positions a firm's strategy but also plays a crucial role in managing and developing its intellectual capital.

The theory of short-termism highlights that organizations relying solely on financial metrics risk sacrificing long-term goals, especially when these metrics are tied to compensation (Kaplan & Norton, 2001) Research indicates that non-financial performance measures serve as superior indicators of long-term success, guiding managers towards more sustainable decision-making (Horngren et al., 2012a) Investments in intellectual capital align with long-term objectives, making strategic management accounting systems that emphasize non-financial indicators essential for managing intellectual capital effectively These indicators not only track target achievement but also reveal trends over extended periods, offering insights into performance improvements or declines beyond typical financial reporting Key non-financial metrics include research and development outcomes, production cycle times (structural capital), employee skills (human capital), and customer relations (relational capital), all crucial for enhancing a company's long-term performance Consequently, literature suggests that balanced scorecards may be an effective tool for developing and sustaining intellectual capital (Andriessen, 2004; Kaplan, 1984; Mouritsen et al., 2002; Roos, 1998).

Firms with higher intellectual capital are better equipped to develop strategic management accounting (SMA) systems, which serve as essential tools for managing and leveraging intellectual capital throughout the value chain SMA plays a crucial role in enhancing corporate performance by optimizing the management of available intellectual capital Research by Tayles et al (2002) emphasizes that SMA acts as a "vital fulcrum" in leveraging intellectual capital for competitive advantage For instance, strategic cost management analyzes the value chain and cost drivers, helping firms understand how intellectual capital contributes to sustainable development By improving customer value while reducing costs, organizations can achieve greater relational capital and competitive effectiveness Additionally, techniques like balanced scorecards help firms assess how employee skills add value, guiding targeted training to enhance human capital at lower costs Furthermore, Tayles et al (2007) highlight that firms with higher intellectual capital prioritize capital budgeting for long-term investments in intellectual capital, underscoring its importance in strategic financial planning.

This study emphasizes contemporary management accounting with a strategic orientation, focusing on four key groups of Strategic Management Accounting (SMA) techniques: strategic cost management, competitor accounting, strategic accounting, and customer accounting While existing literature extensively addresses the valuation and reporting of intellectual capital (IC) for external purposes, there is a lack of attention to how SMA practices can effectively manage IC components Therefore, this exploratory research aims to identify SMA techniques that can influence IC management, contributing to a theoretical framework of strategic management accounting.

Hypothesis 6a: Which categories of SMA techniques (strategic cost management, competitor accounting, strategic accounting and customer accounting) are strongly associated with human capital

Hypothesis 6b: Which categories of SMA techniques (strategic cost management, competitor accounting, strategic accounting and customer accounting) are strongly associated with structural capital

Hypothesis 6c: Which categories of SMA techniques (strategic cost management, competitor accounting, strategic accounting and customer accounting) are strongly associated with relational capital. h

Summary of the correlations in the two research models

Cleary (2015); Hsu and Fang (2009); Nazari

ATO  HCE + + + Bollen et al (2005); Firer and Mitchell-Williams

ROE  HCE + + + S.-L Chang (2007); Hong Pew et al (2007)

TOBINQ  HCE + + + Ming-Chin et al (2005) h

ATO  SCE + + + Bollen et al (2005); Firer and Mitchell-Williams

ROE  SCE + + + S.-L Chang (2007); Hong Pew et al (2007)

TOBINQ  SCE + + + Ming-Chin et al (2005)

ATO  RCE + + + Bollen et al (2005); Firer and Mitchell-Williams

ROE  RCE + + + S.-L Chang (2007); Hong Pew et al (2007)

TOBINQ  RCE + + + Sharabati, Naji Jawad, and Bontis (2010);

A structural equation model (SEM) was utilized alongside data from a questionnaire survey to validate the positive relationship between Strategic Management Accounting (SMA) and overall corporate performance, without focusing solely on financial indicators This approach, as illustrated by Cadez, emphasizes the broader implications of SMA on organizational success.

Contingency theory, information management theory

H6a 4 HCE  SCM ? The author Dynamic capabilities theory, Shortermism theory

SCE  COM ? SCE  STR ? SCE  CUS ?

Source: Developed by the author

Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Relational Capital Efficiency (RCE) are critical metrics for evaluating organizational performance Implementing Strategic Management Accounting practices (SMA) enhances Asset Turnover (ATO) and Investment Efficiency (INVEFF), ultimately leading to improved Return on Equity (ROE) Additionally, the Tobin q (TOBINQ) serves as a valuable indicator of market valuation relative to asset replacement costs Strategic Cost Management (SCM), alongside Competitor Accounting (COM), Strategic Accounting (STR), and Customer Accounting (CUS), plays a vital role in optimizing resource allocation and driving competitive advantage.

In the rapidly evolving business landscape of Vietnam, it is crucial for organizations to effectively leverage their intellectual capital This study aims to explore the interrelationships among various components of intellectual capital and their collective impact on corporate performance.

Intellectual capital, characterized by its rarity, inimitability, non-substitutability, and unobservability, is recognized as a strategic asset that can drive sustainable competitive advantages and superior financial performance Building on resource-based and competence-based theories, this research proposes a model that explores the indirect relationship between intellectual capital and corporate performance, mediated by strategic management accounting practices—a pathway that has been underexplored in prior studies It is anticipated that firms with higher intellectual capital will prioritize the evolution of their management accounting systems, ultimately leading to improved corporate performance.

This study explores the impact of various Strategic Management Accounting (SMA) techniques on the management of intellectual capital components, aiming to identify which categories are most valuable for enhancing corporate performance By conducting exploratory research, the study seeks to contribute to the theoretical framework of strategic management accounting, highlighting the positive and negative influences of IC components on SMA practices.

In the following chapter, the author will outline the research methodology, detailing the research process, unit of analysis, data collection methods, sample size design, and the measurement of variables across all research models, following the theoretical framework established in the previous chapter.

RESEARCH METHODOLOGY

Selection of an appropriate regression approach

Social science researchers have classified statistical analysis tools into two main categories: first-generation methods, which dominated until the 1980s, including correlations, regressions, and tests like ANOVA and t-tests, and second-generation methods that emerged in the early 1980s, such as structural equation modeling (SEM) (Lowry & Gaskin, 2014) While first-generation methods are effective for simple modeling scenarios, they have limitations in testing complex models involving moderation, mediation, and latent variables In contrast, second-generation techniques, particularly SEM, excel in complex causal modeling, making them ideal for studies with intricate research models that require simultaneous estimation of multiple mediators.

There are two main types of Structural Equation Modeling (SEM): covariance-based SEM and partial least squares SEM (PLS-SEM) Covariance-based SEM is utilized to confirm or reject theoretical relationships by assessing how well a proposed model estimates the covariance matrix of a sample dataset (Hair Jr & Hult, 2016) In contrast, PLS-SEM is primarily employed in exploratory research to develop theories by focusing on explaining the variance in dependent variables Consequently, the author chose to use PLS-SEM to investigate the proposed relationships within the research model, taking into account several considerations based on PLS-SEM’s characteristics.

1 PLS-SEM handles a complex model with many structural model relations Larger number of indicators are helpful in reducing the PLS-SEM bias PLS-SEM converges after a few iterations even in situations with complex models to optimum solution and efficient algorithm (Hair Jr & Hult, 2016)

2 Covariance-based SEM is a large sample technique Barrett (2007) suggests that reviewers of journal submissions routinely reject for publication any covariance- based SEM analysis where the sample size is less than 200 In contrasts, PLS-SEM has no identification issue with small sample size This study is extremely difficult to obtain a large sample because the author has to collect both primary data (by questionnaire survey) and secondary data (i.e financial information in the annual report) for one investigated listed company

3 Normal distributions are usually desirable, especially when working with covariance- based SEM In contrast, PLS-SEM generally makes no assumption about the data distributions (Hair Jr & Hult, 2016) Hence, it is more convenient than for the author to collect the sample without normal distributions which allows analysing the path relationships in the research model

4 PLS-SEM can easily handle reflective and formative measurement models, as well as single-item constructs, with no identification problems (Hair Jr & Hult, 2016) It can therefore be applied in a wide variety of research situations When applying PLS- SEM, the author also benefits from high efficiency in handling constructs measured with single-item measure (i.e Assets turnover, ROE, Tobin q) and multi-item measures (i.e measures of the variables of SMA practices)

After deciding to choose the PLS-SEM approach, the research process is designed following the stages of the PLS-SEM approach.

Research process

The research process initiates with defining structural models and measurement scales, leading to data collection and analysis Subsequently, the author employs the PLS-SEM approach, outlining key considerations for conducting this analysis, as depicted in Figure 4.1.

Evaluate VIF of the formative indicators and the structural models

- Size and significance of path coefficients

- Standardized root mean square residual (SRMR)

Evaluation of the fitness of structural model

Evaluation of the stability of parameter estimates

Measurement scales and pilot study Literature review

Examine its correlation with reflective construct of the same concept

Evaluation of measurement of scales

Source: Summarized by the author h

Model estimation provides empirical insights into the relationships between indicators and constructs through measurement models, as well as between constructs via structural models The initial focus of model assessment is on measurement models, where the PLS-SEM approach allows researchers to evaluate the reliability and validity of construct measures For example, multivariate measurement employs multiple constructs to indirectly assess strategic management accounting practices, with each construct necessitating various measurement scales When assessing measurement models, SEM techniques must differentiate between reflectively and formatively measured constructs, as these two approaches to observed variables are based on distinct concepts and require different evaluation criteria.

4.2.1 Evaluation of reflective measurement scales

Reflective measurement illustrates the expressions of an underlying construct, where all indicator items are influenced by the same construct, leading to high correlations among them (Hair Jr & Hult, 2016) The evaluation of reflective measurement models focuses on internal consistency reliability, indicator reliability, convergent validity, and discriminant validity (Kline, 1998).

Internal consistency reliability is traditionally assessed using Cronbach's alpha; however, due to its limitations related to population and item count sensitivity, composite reliability is a more suitable alternative (Hair Jr & Hult, 2016) Composite reliability scores range from 0 to 1, with higher values indicating greater reliability In exploratory research, a composite reliability value above 0.60 is considered acceptable (Nunnally & Burnstein, 1994), while values exceeding 0.95 are undesirable, as they suggest that all observed variables may be invalid when measuring the same phenomenon (Nunnally & Burnstein, 1994).

Indicator reliability is assessed through outer loadings on a construct, reflecting the shared variance among associated indicators A widely accepted guideline is that outer loadings should exceed 0.708 (Hair Jr & Hult, 2016) Indicators with loadings ranging from 0.40 to 0.70 should only be considered for removal if their deletion enhances composite reliability and average variance extracted beyond the established threshold (Hair Jr & Hult, 2016).

Convergent validity is assessed using the average variance extracted (AVE) criterion, calculated as the sum of squared loadings divided by the number of indicators (Nunnally & Burnstein, 1994) An AVE value greater than 0.50 indicates that the construct accounts for more than half of the variance in its indicators However, for single-item constructs, AVE is not a suitable measure, as the outer loading for such indicators is fixed at 1.00.

Discriminant validity is crucial for ensuring that constructs are distinct from one another One effective method for assessing this validity is the Fornell-Larcker criterion, which states that the square root of the Average Variance Extracted (AVE) for each construct should exceed its highest correlation with any other construct, indicating that a construct shares more variance with its indicators than with others (Fornell & Larcker, 1981) Additionally, discriminant validity is confirmed when an indicator's loading on its designated construct surpasses its loadings on other constructs (Hair Jr & Hult, 2016) A more reliable approach, the Heterotrait-Monotrait ratio of correlations (HTMT), proposed by Henseler, Ringle, and Sarstedt (2015), compares the average correlations of indicators across different constructs to those within the same construct An HTMT value significantly below 1.00 is expected, and a value exceeding 0.85 suggests a lack of discriminant validity (Kline, 2011).

A single-item construct differs from a multi-item measurement model, meaning that the evaluation criteria for multi-item models do not apply to single-item constructs.

4.2.2 Evaluation of formative measurement scales

The formative measurement model indicates that indicators may represent independent causes of a construct, leading to lower correlation among them (Hair Jr & Hult, 2016) Chin (1998b) suggests that evaluating convergent and discriminant validity using criteria for reflective measurement scales is not applicable for formative indicators and their weights This study aims to empirically assess formative measurement models by following the outlined procedures The process involves three key steps: first, evaluating convergent validity by correlating the formatively measured construct with a reflective measure; second, addressing collinearity issues within formative measurement models; and third, examining the statistical significance and relevance of formative indicators.

Convergent validity is assessed by correlating a formatively measured construct with a reflectively measured construct of the same concept, a process referred to as redundancy analysis (Chin, 1998b) The path coefficient connecting the reflective and formative constructs indicates the validity of the formative indicators in capturing the intended construct (Chin, 1998b) Ideally, a correlation of at least 0.70 is expected, signifying that the formative indicators adequately contribute to the construct's content (Chin, 1998b).

Collinearity, particularly multi-collinearity, poses significant challenges when high correlations exist between formative indicators To assess this issue, the variance inflation factor (VIF) is utilized, with a recommended threshold of less than 5.0 for each indicator (Hair Jr & Hult, 2016) If any indicator exceeds this value, it is advisable to either eliminate or consolidate indicators into a single index to effectively address the collinearity problem.

The significance of formative indicators is crucial in assessing the relationship between latent variables and their corresponding indicators A significant outer weight allows for further interpretation of both its absolute and relative size Conversely, when the outer weight is not significant, the focus shifts to the outer loading, which reflects the absolute contribution of the formative indicator to its construct If an indicator exhibits a high outer loading (above 0.50) despite a non-significant outer weight, it is typically retained However, the decision to keep or discard an indicator ultimately depends on its theoretical relevance, as outlined by Hair Jr & Hult (2016).

4.2.3 Evaluation of the fitness of structural model

After ensuring the reliability and validity of measurement scales, the next step involves evaluating the structural model results by analyzing the relationships between constructs, as depicted in Figure 4.1 In the PLS-SEM approach, crucial criteria for assessing structural models include the size and significance of path coefficients, the R² value, and the SRMR value.

Evaluating the size and significance of standardized path coefficients is crucial for determining the validity of hypothesized correlations Researchers emphasize not only the statistical significance but also the absolute size of path relationships in their interpretations A significant relationship may still have a path coefficient that is too small to warrant managerial attention (Nitzl, 2016).

 Coefficient of determination (R 2 value): This coefficient is a measure of the model’s predictive power, which is calculated as the squared correlation between a specific endogenous construct’s actual and predicted value (Rigdon,

2014) The R 2 value ranges from 0 to 1 In general, R 2 values of 0.75; 0.50 or 0.25 for the endogenous construct can be described as substantial, moderate and weak, respectively (Hair Jr & Hult, 2016)

The standardized root mean square residual (SRMR) is a valuable goodness-of-fit statistic for Partial Least Squares Structural Equation Modeling (PLS-SEM), as traditional criteria used in covariance-based SEM are not suitable (Hair Jr & Hult, 2016; Henseler et al., 2015; Nitzl, 2016) SRMR measures the root mean squared discrepancy between observed and model-implied correlations, with a threshold of less than 0.08 indicating a good fit (Hu & Bentler, 1998).

4.2.4 Evaluation of the significance and the stability of path coefficients

Unit of analysis and sample size

4.3.1 Unit of analysis and informants

This study examines the relationship between intellectual capital and corporate performance, focusing on business organizations as the primary unit of analysis It also explores the mediating role of strategic management accounting (SMA) practices implemented in various departments, including accounting, finance, planning, and management accounting The research specifically targets organizations utilizing multiple SMA techniques to enhance their business operations Notably, financial service organizations, such as banks and insurance firms, are excluded from the study due to the complexities and variations in financial calculations pertinent to these entities, as highlighted in previous research by Daske, Hail, Leuz, and Verdi (2008) and Francis and Wang (2008).

This study utilizes both primary and secondary data, focusing on financial information from annual reports and financial statements to analyze the relationship between intellectual capital and corporate performance The research specifically examines publicly traded companies listed on the Hochiminh Stock Exchange (HoSE) and the Hanoi Stock Exchange (HNX) Data is sourced from reputable websites, such as cophieu68.vn, finance.vietstock.vn, and cafef.vn, which are widely used by investors, analysts, and researchers in Vietnam.

This study employs a questionnaire survey to gather primary data on Strategic Management Accounting (SMA) practices in public enterprises The survey targets SMA practitioners, utilizing their financial data to assess intellectual capital and corporate performance Given that organizations serve as the unit of analysis, the research is conducted in two phases: the first phase involves distributing the questionnaire via SurveyMonkey to management, focusing on SMA practices, while the second phase entails collecting 2016 financial information related to intellectual capital and performance from the public companies where the respondents are employed.

To ensure the reliability of informants in strategic management accounting research, key informants are selected from senior managers or top management team members who possess expertise in accounting, planning, or finance, along with a minimum of two years of experience in their current organizations Alavi and Leidner (2001) highlight that it is challenging for employees to gain a comprehensive understanding of an organization's operating processes, structure, and culture within just one year of involvement.

A critical guideline regarding the relationship between sample size and model complexity is the N:q rule, as noted by Jackson (2003), where N represents the ratio of cases to model parameters (q) While some researchers follow the 10:1 rule, which suggests a minimum sample size of ten times the maximum number of arrowheads pointing to a latent variable in the model (Barclay, Higgins, & Thompson, 1995), this approach is not a reliable measure for determining sample size in PLS-SEM (Marcoulides & Chin, 2013) PLS-SEM, based on OLS regressions, does not have a strict minimum sample size requirement Therefore, it is essential for researchers to conduct statistical power analyses for multiple regression models (J Cohen, 1988) to ascertain a more accurate sample size rather than solely relying on the minimum thresholds Additionally, Faul et al (2007) recommend assessing the necessary sample size for effective analysis.

PLS-SEM relies on statistical power, which is influenced by effect size (f²), the number of predictors, and the significance level (α) Researchers can utilize software like G*Power to perform power analysis for determining the optimal sample size In this study, the required sample size was calculated using the free program G*Power 3.1.9.2, available for download at http://www.gpower.hhu.de/ (Faul et al., 2007).

For the analysis, the F-test is utilized as the test family, while the statistical test employed is linear multiple regression with a fixed model, assessing the R² deviation from zero Additionally, an a priori power analysis is conducted to compute the necessary sample sizes based on the specified alpha level, statistical power, and effect size.

In business studies, key input parameters for research include effect size (f²), α error probability, power, and the number of predictors A statistical power of at least 0.80 at an α level of 0.05 is deemed acceptable (J Cohen, 1988) The effect size (f²) values of 0.02, 0.15, and 0.35 indicate small, medium, and large effects, respectively, of an exogenous construct on an endogenous construct (Hair Jr & Hult, 2016) In management accounting research, it is often sufficient to aim for detecting medium effects (f² = 0.15) with a reasonable sample size, rather than small effects, due to the time and cost constraints associated with collecting questionnaire data (Nitzl, 2016) The first research model allows for a maximum of 12 predictors, while the second model is limited to 4 predictors.

Figure 4.2 Calculation of sample size of the first research model

Source: Calculated by the author

Figure 4.3 Calculation of sample size of the second research model

Source: Calculated by the author h

The first research model has a sample size of 127, while the second model has 85 observations, necessitating a minimum of 127 samples for both to achieve an 80% statistical power in detecting R² values of at least 0.25, with a 5% error probability Therefore, the target sample size for this study, conducted in Vietnam, an Asian developing country, is set at a minimum of 127 observations Due to challenges in obtaining a comprehensive sampling frame, a convenience-sampling approach will be utilized to identify listed enterprises and potential informants.

Variables measurement

4.4.1 Measures of each component of intellectual capital

The "Value Added Intellectual Coefficient" model (VAIC TM), developed by Pulic in 2000, serves as the primary method for measuring intellectual capital (IC) using archival data This study utilizes the VAIC model due to its two key advantages highlighted by Firer and Mitchell-Williams (2003): first, it offers a standardized and easily calculable measurement that facilitates effective comparative analysis among firms; second, the data required for VAIC calculations are derived from financial statements, which are typically audited by professional public accountants.

Figure 4.4 The value-added intellectual coefficient model

Source: Summarized by the author

The VAIC model utilizes a series of indicators to assess the value and efficiency of a company's resources As illustrated in Figure 4.4, these indicators provide a comprehensive overview of the variables involved prior to calculating the components of intellectual capital The model outlines specific procedures for measuring various constructs effectively.

4.4.1.1 Operationalization of value added (VA)

The VAIC model emphasizes a company's capacity to generate value added (VA) as a key metric for measuring firm performance Aligning with the stakeholder view proposed by Donaldson & Preston (1995), it argues that a comprehensive assessment of value added by stakeholders surpasses traditional accounting profit, which focuses solely on stockholder returns Consequently, the VAIC model defines firm performance through value added, calculated as the difference between output and input.

Consistent with Riahi-Belkaoui (2003), the calculation of value added can be expressed as equation (4.1):

RE = SALES – B – DEPN – WAGES – INT – T – DD (4.1) Where:

RE: Changes in retained earnings

B: Bought-in materials and services

WAGES: Wages and employee salaries

Equation (4.1) can be re-arranged as equation (4.2):

SALES – B = DEPN + WAGES + INT + T + DD + RE (4.2)

Equation 4.2 is the gross value-added approach The left-hand side of the equation calculates gross value added and the right-hand side of the equation represents the h distribution of the value created by firms to stakeholders including employees, debt- holders, stockholders and governments VA is defined as the gross value created by firm during the years, and because dividends (DD) plus retained earnings (RE) is equal to after- tax income (NI), equation 4.2 can be expressed as follows:

VA = SALES – B = DEPN + WAGES + INT + T + NI (4.3)

VAIC measures the efficiency of intellectual capital components, which include human capital, structural capital, and relational capital, as defined by Edvinsson and Sullivan (1996) The calculation of these components is detailed in the subsequent sections.

4.4.1.2 Operationalization of human capital efficiency (HCE)

According to Pulic (2000), the Value Added Intellectual Coefficient (VAIC) framework does not categorize employee expenditures as INPUT, viewing them instead as an investment rather than a cost This perspective allows for the measurement of human capital efficiency (HCE) by assessing the value added generated by an organization for each dollar invested in its workforce HCE is calculated to reflect the effectiveness of human capital investments in driving organizational value.

HC: Human capital (total salaries and wages of a firm)

Higher wages typically indicate a more skilled workforce, which can contribute greater value to a firm compared to employees earning lower wages with fewer skills When a company has low wages but high value added (VA), it demonstrates efficient utilization of its human capital (HC) Conversely, if a firm experiences low VA relative to wages and salaries, it signifies inefficient use of its HC, resulting in a lower human capital efficiency (HCE).

4.4.1.3 Operationalization of structural capital efficiency (SCE)

Both structural capital and relational capital are calculated as follows:

SRC: Structural capital and relational capital

HC: Human capital (total salaries and wages of a firm)

Nazari and Herremans (2007) argue that structural and relational capital rely heavily on human capital, indicating that enhanced human capital leads to better internal structures and external relationships However, Pulic (2000) highlights a logical inconsistency when using value added (VA) as the numerator for measuring the efficiency of human, structural, and relational capital Specifically, employing VA in the efficiency calculations suggests that any increase in value generated from human capital directly contributes to the improvement of both structural and relational capital Consequently, Pulic (2000) proposes a method for calculating structural and relational capital efficiency (SRCE).

SRCE: Structural capital and relational capital efficiency

SRC: Structural capital and relational capital

Structural capital and relational capital efficiency (SRCE) is the dollar of SRC within a firm, for each dollar of value added, and as HCE increases, SRCE increases Alternatively:

SRCE: Structural capital and relational capital efficiency

SCE: Structural capital efficiency (SC is divided by VA)

RCE: Relational capital efficiency (RC is divided by VA)

Moving to the lower level, structural capital is composed of innovation capital and organizational capital (Nazari, 2010) Structural capital is calculated on the basis of its components as:

Equation of SCE can be re-arranged as equation (4.10), based on equation (4.9):

Research and development expenditure (R&D) has been used extensively in the literature as a proxy for innovation capacity (Bosworth & Rogers, 2001) The efficiency of innovation is calculated in the following manner:

Under Vietnamese accounting standards, firms are not mandated to disclose their R&D investment levels, making it challenging to gather this information from financial statements Consequently, this study employs cash outflows related to the acquisition of tangible and intangible assets, excluding purchases of controlled entities and businesses, as an indirect measure of a firm's R&D investment for the year when direct financial information on R&D is unavailable.

This study evaluates cumulative R&D investment by utilizing the carrying amount of prior years' R&D expenditures, necessitating an amortization rate for accurate measurement over time Building on the frameworks established by Lev and Sougiannis (1996), Gu and Lev (2001), and Shangguan (2005), it is assumed that R&D investments are depreciated straight-line over a three-year economic lifespan The author faces limitations in extending the depreciation period due to insufficient data from the relatively young Vietnam stock exchange, which has been operational since 2010 Consequently, the cumulative R&D investment (RDC) for year t is calculated based on this three-year economic life.

RDCi,t = RDi,t + 2/3 RDi,t-1 + 1/3 RDi,t-2 (4.13) Where:

RDCi,t: Cumulative level of R&D investment in the year t

RDi,t: Level of R&D investment in the year t

RDi,t-1: Level of R&D investment in the year t – 1

RDi,t-2: Level of R&D investment in the year t – 2

Organizational capital represents the accumulated knowledge that integrates human skills and physical resources to create systems for producing and delivering products that satisfy consumer needs (Shangguan, 2005) The efficiency of organizational capital can be determined using the formula outlined in equation 4.10.

Firms often do not disclose their expenditures on organizational capital in financial statements, as this involves capitalizing selling, general administrative (SGA) spending, akin to the capitalization of research and development expenses While Vietnamese accounting standards mandate immediate expensing of SGA spending, it encompasses significant investments in areas such as human resources, IT, workplace practices, and marketing This perspective aligns with the capitalization principles of R&D expenditures Further support for treating SGA spending as a capital investment can be found in the works of Amir and Lev (1996), Lev (2001), and Lev and Radhakrishnan (2003) Notably, when calculating organizational capital, SGA spending excludes employees’ salaries and wages, as these are accounted for under human capital.

Firstly, this study conducts the following firm-level estimation by industry:

Log(Ei,t)= γ0 + γ1Log(PPEi,t-1) + γ2Log(RDCi,t-1)+ δ1Log(SGAi,t)+ δ2Log(SGAi,t-1) + δ3Log(SGAi,t-2) (4.15) Where:

Log(Ei,t): Logarithm of annual earnings before depreciation, R&D, and SGA expenses in year t

Log(PPEi,t-1): Logarithm of book value of plant, property, and equipment in year t-

1, representing the firm’s physical capital

Log(RDCi,t-1): Logarithm of accumulative level of R&D investment in the year t – 1,

RDC is estimated in the model 4.13

Log(SGAi,t): Logarithm of selling, general administrative spending (excluding employees’ wages and salaries) in the year t

Log(SGAi,t-1): Logarithm of selling, general administrative spending (excluding employees’ wages and salaries) in the year t – 1

Log(SGAi,t-2): Logarithm of selling, general administrative spending (excluding employees’ wages and salaries) in the year t – 2

The rationale behind equation (4.15) is that Selling, General, and Administrative (SGA) expenditures encompass a significant portion of organizational capital, which is expected to generate future earnings for the firm Consequently, past SGA expenditures should have an impact on current earnings, with the extent of this effect determined by the rates of organizational capital represented by γ3, γ4, and γ5 in the equation This study utilizes a maximum of three years of past SGA expenditures to influence current earnings, ensuring that the duration of Research and Development (R&D) and SGA contributions to earnings aligns.

On the other hand, the empirical results from the simple correlations and multivariate regressions do not control for the potential endogeneity of SGAi,t and Ei,t (Shangguan,

To address potential simultaneity bias in the analysis of Selling, General, and Administrative (SGA) expenditures, this study employs a two-step regression approach, utilizing instrumental variables that capture the exogenous component of SGA expenditures SGA expenditures are considered joint endogenous variables influenced by underlying exogenous factors such as total assets and profitability It is anticipated that a firm's SGA expenditure aligns with its overall expenditure level, total assets (used as a proxy for firm size), and prior year profitability (measured by Return on Assets, ROA) In the initial stage of the regression, SGA expenditures are regressed against profitability and firm size to derive estimates that inform the broader model examining the relationship between SGA expenditures and log-transformed earnings.

Log(SGAi,t) = ϕ0 + ϕ1TAi,t-1 + ϕ2ROAi,t-1 + εi,t (4.16) Where:

SGAi,t Logarithm of selling, general administrative spending (excluding employees’ wages and salaries) in the year t

TAi,t-1 The natural logarithm of total assets in the year t – 1

ROAi,t-1 Profitability is the ratio of net profit to total assets in the year t – 1

This study estimates the values of δ1, δ2, and δ3 from equations 4.15 and 4.16 through a two-step regression, focusing on industry-specific organizational capital based on SGA amortization rates Unlike the R&D investment measurement in equation 4.13, which treats all current R&D spending as capital investment, this research only capitalizes the unamortized SGA expenditures, while the amortized portion is classified as current operating expenses (Shangguan, 2005) The significant values of δ1, δ2, and δ3 reflect the contribution of SGA expenditures from the current and previous two years to current earnings, with their sum representing the total earnings impacted by these expenditures over the same period Additionally, the ratios ω1, ω2, and ω3 are calculated to represent the amortization rates of SGA expenditures for the respective years Finally, the firm-specific level of organizational capital is determined using equation 4.17.

SGAi,t Selling, general administrative spending (excluding employees’ wages and salaries) divided by net revenue in the year t

SGAi,t-1: Selling, general administrative spending (excluding employees’ wages and salaries) divided by net revenue in the year t – 1 ORGC: Organizational capital

4.4.1.4 Operationalization of relational capital efficiency (RCE)

SAMPLE CHARACTERISTICS AND MEASUREMENT SCALES

Data collection to construct the variables of SMA practices

This study utilizes both primary data, obtained through surveys, and secondary data from financial statements to explore the application of Strategic Management Accounting (SMA) practices within business organizations Data is gathered through a questionnaire survey directed at SMA practitioners, specifically managers or top management members with expertise in accounting, planning, or finance, and a minimum of two years of experience in their current roles This section outlines the methodology for collecting primary data on SMA practices through the questionnaire survey.

The questionnaire, initially crafted in English, consists of three sections: Part A gathers demographic details about respondents, including their job titles, areas of responsibility, and years of experience Part B focuses on the organization's strategic management accounting (SMA) practices, featuring 18 techniques related to strategic cost management, competitor accounting, strategic accounting, and customer accounting.

C, the final part of the questionnaire, contained optional information on the contact of the respondents Measuring the degree of usage is achieved by asking the question “To what extent does your organization use the following techniques?” Immediately, following the questions, the 18 SMA techniques are listed together with five-point Likert scale, ranging from 1 (not at all) to 5 (to a great extent) A response of 1 indicates the lowest amount of usage, while a response of 5 indicates the greatest amount of using such a SMA technique h being questioned Please refer to Appendix 13 and 14 to see the survey forms in English and Vietnamese, respectively

5.1.2 Translating and pilot testing of the questionnaire

The questionnaire was translated into Vietnamese following a meticulous process Initially, the draft English version was reviewed by three experienced professors in management accounting The translation adhered to Brislin's (1970) three-step method, which involved: (1) translating the original questionnaire into Vietnamese, (2) back-translating the Vietnamese version to English, and (3) comparing the back-translated version with the original to ensure consistency in meaning.

The revised Vietnamese questionnaire underwent a thorough review by three managers and two academic staff to improve its clarity, wording, and overall comprehensibility Minor adjustments were made to ensure cultural and linguistic appropriateness for Vietnamese respondents, while preserving the original meaning of the items For comprehensive details on the final Vietnamese questionnaire, please refer to Appendix 14.

The pilot testing of the Vietnamese questionnaire involved students enrolled in CIMA programs at management and strategic levels or ACCA at the professional level, ensuring that respondents had relevant knowledge and experience in strategic management accounting After collecting and analyzing 80 completed responses, the reliability and validity of the measurement scales were assessed using Cronbach Alpha and Explanatory Factor Analysis (EFA) via SPSS 20.0 The Cronbach Alpha coefficients ranged from 0.887 to 0.923, exceeding the acceptable threshold of 0.60 and remaining below 0.95, while all item-total correlation coefficients were above 0.3, confirming the scales' reliability for EFA.

In the context of exploratory factor analysis (EFA), principal component analysis (PCA) is typically utilized for dimension reduction, employing Varimax rotation to enhance interpretability Significant factor loadings were identified, with all values exceeding a threshold of 0.50 The EFA revealed four factors, each with an Eigenvalue greater than 1.5, accounting for a cumulative variance of 77.841% To ensure the appropriateness of the analysis, both Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure were conducted.

The KMO value of 0.930 and a very small significance value confirmed the reliability of the EFA results (χ² = 1,215.546, df = 153, p = 0.000), indicating that the measures were appropriately designed for further analysis, demonstrating accepted validity and reliability in this study During the EFA testing, observed variables were organized and named based on the principle that those with significant factor loadings would be assigned to their respective dimensions, as shown in Appendix 15.

This study employs a quantitative research method, utilizing empirical survey and financial data from a sample of at least 127 publicly traded enterprises in Vietnam for the year 2016 While there were 356 companies listed on HoSE and 387 on HNX in 2016, survey links were sent to only 250 selected informants from firms nominated for the award recognizing the best annual reports Due to the challenges in obtaining contact information for senior managers with expertise in accounting, planning, or finance, the study leveraged support from global professional accounting bodies like ACCA and CIMA, which sponsor the annual awards.

E-mail survey was one of the most suitable data collection techniques for a broad survey of business organizations in Vietnam This technique has been used for its timeliness and cost effectiveness It could aim at potential informants, was inconspicuous, and potential informants could decide to answer or not E-mails with survey links were sent to the email address of 250 potential informants via the SurveyMonkey software Follow-up emails were sent to non-respondents to re-explain the purpose of the research h and to request a response These e-mailing processes were programmed and managed with SurveyMonkey

Six months after the initial emails were sent, 192 complete responses were collected, with "complete" defined as having no missing data Participants were required to answer all mandatory survey questions before advancing to the next section This approach, implemented using SurveyMonkey software, effectively addressed the problem of incomplete survey responses.

Careless responses can significantly bias survey results, particularly when they are completed in a short amount of time In this study, 9 responses with a completion time of less than 10 minutes were eliminated, accounting for 5% of the total 192 responses, aligning with Meade and Craig's (2012) findings that 5% to 15% of participants may answer inadvertently during lengthy surveys All responses were from eligible informants, ensuring that none were excluded due to a lack of financial literacy or insufficient experience Additionally, 4 responses were discarded because the informants indicated that their organizations do not analyze management accounting data for strategic purposes, suggesting a lack of understanding in strategic management accounting Finally, 5 responses were retained despite incomplete financial information, as they were necessary for regression analysis in the research models.

The final sample was comprised of 174 valid responses, as shown in Table 5.1 The

A total of 174 responses underwent an elimination process and were deemed eligible for data analysis The data from these responses were exported from SurveyMonkey to a spreadsheet to incorporate additional financial information for further examination.

Table 5.1 Development of the final sample in the main study

Number of potential informants emailed 250

Less: Invalid responses from informants

- with total response time of less than 10 minutes 9

- with “No” responses to the question of SMA concept 4

- with responses not available the required financial data 5 18

Source: Summarized by the author

Sample characteristics

In section 5.1.3, it was noted that 250 potential informants were contacted via email with a survey link, resulting in 192 completed responses from the listed companies After excluding 18 unsuitable responses, the final sample comprised 174 valid observations The following sections outline the key characteristics of this research sample.

Table 5.2 illustrates the industry composition of 174 firms with available data, revealing that the manufacturing sector dominates the sample at 35.63 percent This is followed by the real estate and construction industries, accounting for 18.39 percent, and the mining and energy sector, which comprises 12.64 percent of the total Overall, these selected firms represent 20 percent of the total sample analyzed.

Vietnam has 743 publicly traded companies listed on the Hochiminh and Hanoi Stock Exchanges Utilizing the sample size formula by Krejcie and Morgan (1970), a representative sample of 750 firms yields a sample size of 154, making the selection of 174 listed firms suitable for generalization Public enterprises play a vital role in the Vietnamese economy, with the market capitalization of listed companies contributing 26.8% to the country's GDP in 2015 As per the General Statistics Office of Vietnam (GSO) in 2016, the economic structure revealed that agriculture, forestry, and fishing accounted for 16.32%, industry and construction for 32.72%, and services for 40.92% This data suggests that findings from the analysis may be more applicable to manufacturing and construction sectors than to services and agriculture.

Table 5.2 The number of respondents by Industry type

5.2.2 Organization size and SMA practices type

Table 5.3 outlines the characteristics of the sample concerning total assets and the level of Strategic Management Accounting (SMA) implementation as reported by respondents According to Decree 39/2018/ND-CP, small enterprises are defined as those with total equity under VND 20,000 million, while medium enterprises fall within the range of VND 20,000 to 100,000 million, and large enterprises exceed VND 100,000 million in total equity The data reveals that 89.66% of the sampled organizations are classified as large enterprises, possessing total equity above VND 100,000 million This composition is deemed suitable for investigating intellectual capital and strategic management accounting, given that the majority of the sample consists of publicly traded large enterprises.

The study investigates 18 Strategic Management Accounting (SMA) techniques, with each assessed on a scale of 1 to 5, yielding a maximum score of 90 A threshold value of 45 is established to categorize organizations into high and low SMA practice groups According to the findings in Table 5.3, 70.11% of the sampled organizations fall into the high SMA practices category, with 92.62% of large enterprises demonstrating elevated levels of SMA implementation To evaluate the appropriateness of organizations regarding SMA practices, the author employed specific questions derived from the SMA definition, such as, “Does your organization analyze management accounting data about your business, competitors, and customers for developing and monitoring business strategy?” Responses indicating “No” were excluded, ensuring the relevance of the sampled organizations for investigating the correlation between SMA practices and intellectual capital.

Table 5.3 The number of respondents by Organization size and SMA practices type

Size in terms of total equity

Lower level (≤ 45) Frequency % Frequency % Frequency % Small companies

The survey respondents, representing various organizations, include executives and individuals who directly interact with finance or accounting departments across sectors such as commercial finance, cost management, budgeting, accounting, planning, and procurement To ensure the appropriateness of the respondents, the author included a qualifying question regarding their current highest position in the company, offering three options: top management, middle management, and non-management staff, before proceeding with the subsequent questions.

The author categorizes the sample into seven groups, revealing that finance managers comprise 27.01% of the respondents, followed by reporting managers at 20.11%, and both department heads and general managers at 14.36% All participants are senior managers or members of the top management team, possessing knowledge in accounting, planning, or finance, and have a minimum of two years of experience in their current organizations.

Table 5.4 Number of Respondents by Positions type and Working Years type in the current organization

Number of working years in the current organization Total

The outcomes of reflective measurement scales assessment

The SMA practices variable is constructed using reflective measurement scales, which are evaluated for internal consistency reliability, indicator reliability, convergent validity, and discriminant validity, as outlined in Part 4.2.1 (Kline, 1998).

 Internal consistency reliability: the criterion for internal consistency evaluation is composite reliability Composite reliability value of higher than 0.60 and not above 0.95 are acceptable in exploratory research (Nunnally & Burnstein,

1994) Appendix 16 shows that the composite reliabilities of these latent h variables range between 0.860 and 0.950 These results indicate a high level of reliability of the measurement scales in the outer models

Indicator reliability is assessed through outer loadings on a construct, reflecting the commonality among associated indicators As shown in Appendix 16, the outer loadings for all observed variables across constructs range from 0.577 to 0.881, exceeding the acceptable threshold of 0.5 (Hair Jr & Hult, 2016) Additionally, the t-bootstrap values are significantly high, ranging from 10.493 to 50.343, well above the statistical significance threshold of 1.96.

Convergent validity is assessed using the average variance extracted (AVE) criterion, calculated by dividing the sum of squared loadings by the number of indicators (Nunnally & Burnstein, 1994) All latent variables exhibit acceptable AVE values, ranging from 0.516 to 0.697, indicating strong convergent validity as they exceed the 0.5 threshold.

Discriminant validity was assessed using the Fornell-Larcker criterion, as detailed in Appendix 18, where the square root of the Average Variance Extracted (AVE) for each construct ranged from 0.746 to 0.835, surpassing the highest correlations with other constructs, thereby confirming discriminant validity Notably, the SMA variable's square root of AVE was lower than its correlations with constructs like COM, CUS, SCM, and STR; however, this is acknowledged due to SMA being a hierarchical component model Additionally, discriminant validity is supported when an indicator's loading on its designated construct exceeds its cross-loadings with other constructs, as shown in Appendix 17 For instance, the indicator COM1 exhibited the highest loading of 0.745 with its construct COM, while its cross-loadings with other constructs were lower, reinforcing the validity of the constructs Furthermore, the study utilized the Heterotrait-Monotrait (HTMT) test, which is more rigorous than the Fornell-Larcker method, with HTMT values ranging from 0.466 to 0.785, all significantly below the threshold of 0.85, further substantiating the discriminant validity of the constructs.

The outcomes of formative measurement scales assessment

The structural capital (SCE) variable is developed using formative measurement scales, specifically focusing on innovation capital efficiency (RDCE) and organizational capital efficiency (ORGCE) This section outlines the calculations for both RDCE and ORGCE, followed by an evaluation of their convergent validity, collinearity concerns, statistical significance, and the relevance of the formative indicators, as detailed in Part 4.2.2.

5.4.1 Calculation of measurement scale of innovation capital efficiency

The efficiency of innovation is determined by dividing cumulative research and development (R&D) investments by the value added, as outlined in section 4.4.1.3 Cumulative R&D investments are calculated based on the total value of prior years' investments, assuming a straight-line depreciation over a 3-year economic lifespan This study adopts a 3-year depreciation period due to the limited availability of data in the relatively young Vietnamese stock exchange, where comprehensive information has only been accessible since 2010 For instance, if a manufacturing firm invests 3,408 million VND in R&D in 2016 and 5,658 million VND in 2015, these figures will be used to assess innovation efficiency.

2014 = 1,307 million VND, the cumulative R&D investment in year 2016 is: RDC1, 2016 3,408 + 0.667 x 5,658 + 0.333 x 1,307 = 7,617.12 Then, the efficiency of innovation of this firm (0.0503) is calculated by the cumulative R&D investment (7,617.12) divided by the value added (151,395)

5.4.2 Calculation of measurement scale of organizational capital efficiency

As demonstrated in the Part 4.4.1.3, the empirical results from the simple correlations and multivariate regressions do not control for the potential endogeneity of SGAi,t and Ei,t

(Shangguan, 2005) In the presence of endogeneity, ordinary-least-squares estimation yields biased and inconsistent coefficient estimate For this reason, the author conducts the h

The two-step regression analysis of Equation 4.15 incorporates firm-specific fixed effects and year-specific random effects categorized by industry In the initial step, a regression is conducted to estimate SGA expenditures based on exogenous variables such as total assets and profitability The second stage employs Ordinary Least Squares (OLS) regression, utilizing the estimates from the first stage to derive consistent parameter estimates that link SGA expenditures to annual earnings For detailed information, please consult Appendix 19 and Appendix 20 Panel.

The article presents coefficient estimates over several years across various industries, revealing that the 2-step regression analysis yields significant δ1 and δ2 values for SGA expenditures and annual earnings in all sectors However, δ3 is not significant in industries like mining, energy, commercial, logistics, transportation equipment, real estate, and construction This indicates that SGA expenditures have a useful life of two to three years, with the most substantial effect on earnings occurring in the concurrent year, followed by rapid depreciation.

To calculate the amortization rates of SGA expenditures, only statistically significant coefficients from Panel A are considered Each coefficient indicates the contribution of specific SGA expenditures to earnings, with the total of significant coefficients reflecting the annual benefits of these expenditures For the Manufacturing sector, the contributions are as follows: δ1 = 1.694 for current SGA expenditures, δ2 = 0.651 for previous-year expenditures, and δ3 = 0.204 for expenditures from two years prior, totaling ∑(δ1, δ2, δ3) = 2.549 in earnings for year t In contrast, the Commercial sector totals δ1 + δ2 = 1.493, as δ3 is not statistically significant Consequently, the amortization rates for the Manufacturing sector are 0.665 for year t, 0.255 for year t-1, and 0.080 for year t-2 Panel B of Appendix 20 provides a detailed illustration of the amortization rates across selected industries.

To assess the firm-specific level of organizational capital, the amortization rates are first determined, followed by the application of equation 4.17 For example, a manufacturing firm that invested SGA1,2016 = 49,854 million VND, SGA1, 2015 = 40,122 million VND, and SGA1, 2014 = 19,158 million VND would calculate its cumulative organizational capital investment for 2016 as ORGC1, 2016 = 49,854 x (1 – 0.665) + 40,122 x (1 – 0.255 – 0.655) + 19,158 x (1 – 0.080 – 0.255 – 0.665) = 19,910.85 million VND Consequently, the efficiency of the organizational capital is determined by dividing the cumulative investment (19,910.85 million VND) by the value added (151,395 million VND), resulting in an efficiency ratio of 0.131516.

5.4.3 Assessment of formative measurement scales related to the structural capital efficiency variable

The RDCE and ORGCE indicators serve as formative measurement scales for the SCE variable As detailed in section 4.2.2, their evaluation includes assessing convergent validity, addressing collinearity issues, and determining the statistical significance and relevance of the formative indicators.

Convergent validity is assessed by correlating a formatively measured construct with a reflectively measured construct of the same nature However, the absence of established reflective measurement instruments can make creating a new scale challenging and time-consuming (Hair Jr & Hult, 2016) A viable alternative is to utilize a general item that encapsulates the essence of what the formative indicators aim to measure (Hair, Ringle, & Sarstedt, 2013) In the context of PLS-SEM for structural capital, an additional question is posed: “Please assess the extent to which your company’s structural capital has performed in the last three years compared to your major competitors,” where respondents indicate their answer on a specified scale.

1 (extremely poor) to 7 (excellent) This question can be used as an endogenous single-item construct to validate the formative measurement of structural capital

Figure 5.1 Assessment of convergent validity of formative indicators relative to structural capital

Source: Calculated by the author in SmartPLS 3.1 h

The redundancy analysis for the SCE construct, represented as SCE_F for the original formative construct and SCE_G for the general assessment of structural capital efficiency, reveals a path coefficient of 0.885 This value exceeds the recommended threshold of 0.70, indicating strong support for the convergent validity of the formative construct.

In formative measurement models, high correlations between items are not anticipated, distinguishing them from reflective indicators, which are interchangeable Table 5.5 illustrates that there is no collinearity issue among the formative indicators, as each indicator's VIF value is 1.203, well below the threshold of 5.0 (Hair Jr & Hult, 2016).

The significance of formative indicators is crucial for evaluating their contribution, particularly through their outer weights, which result from the multi-regression analysis between the latent variable and the formative indicators As indicated in Table 5.5, the outer weights are notably significant and exceed the threshold of 0.50, making them suitable for inclusion in subsequent regressions.

Table 5.5 VIF, Significance and relevance of formative indicators

Models with endogenous construct RDCE ORGCE

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed), t value (shown in brackets)

Source: Calculated by the author in SmartPLS 3.1 h

Calculation of the variable of investment efficiency

The analysis of equation 4.20 utilizes three regression techniques: Pooled Ordinary Least Squares (OLS), Fixed Effects Model (FEM), and Random Effects Model (REM), all based on the Generalized Least Squares (GLS) method These approaches are applied to panel data models to effectively address the problem of heteroskedasticity For additional details, please consult the Appendix.

The Likelihood test results indicate that the Fixed Effects Model (FEM) is more suitable than the Pooled Ordinary Least Squares (OLS) model To determine whether the Fixed or Random Effects Model is more precise, the Hausman test is utilized, which evaluates the null hypothesis that the Random Effects Model is appropriate for the sample compared to the Fixed Effects Model As shown in Table 5.6, the p-value for the cross-section random effect is less than 5 percent, leading to the rejection of the null hypothesis Consequently, the model incorporating firm-specific and year-specific fixed effects is deemed the most appropriate for all estimations Additionally, Durbin-Watson ratios falling within the range of [1.5; 2.5] suggest a satisfactory fit to the data, indicating no autocorrelation Following the regression, the dependent variable for investment efficiency is defined as the absolute value of the standardized residuals multiplied by -1, where a higher value signifies greater efficiency.

Table 5.6 The coefficient of explanatory variables in Equation 4.20

Cross-section None Fixed Fixed Random Random

Period None None Fixed None Random

- Cross-section and period random 61.460310

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed)

Source: Calculated by the author in Eviews 9.0

Descriptive statistics and collinearity assessment

Descriptive statistics offer straightforward summaries of sample data and metrics, forming the foundation for quantitative data analysis To explore the relationship between dependent and independent variables, Pearson correlation analysis is conducted Additionally, potential collinearity issues are assessed to determine if any corresponding indicators should be removed prior to further regression analysis.

Appendix 22 contains descriptive statistics for all the variables used in this study As can be observed from Table 5.2, the valid number of observations for each variable is 174 samples Mean, median, maximum, minimum, standard deviation, Skewness and Kurtosis are reported for each variable used in the current study Skewness and Kurtosis statistics all suggest that the variables are not normally distributed To reduce the heteroskedasticity problem arising out of the non-normal distributions, regressions are estimated by the PLS- SEM as the advantage of this regression method HCE has a significantly greater mean than SCE and RCE

Appendix 22 also presents Pearson’s correlation coefficient analysis for the dependent and independent variables Correlation coefficient summarizes the linear relationship between two variables having ranked and provide sufficient information from this study’s point of view Under the Pearson’s correlation, of particular note is that the correlation coefficients are not of high magnitude between any two of the independent variables to cause concern about multicollinearity problems

The study reveals significant positive relationships between HCE-SMA (0.551), SCE-SMA (0.514), and RCE-SMA (0.829), thereby supporting the second hypothesis that each component of intellectual capital is positively linked to the practices of strategic management accounting.

Correlation analyses reveal that all components of intellectual capital (IC) are positively associated with corporate performance indicators at a significant level Specifically, improvements in value creation efficiency correspond to enhanced market value, profitability, and operational efficiency These findings validate the third hypothesis, confirming significant positive relationships between each IC component and corporate performance indicators.

The relationships between SMA practices and corporate performance are notably positive, with correlations of SMA-ATO at 0.713, SMA-INVEFF at 0.776, SMA-ROE at 0.930, and SMA-TOBINQ at 0.844 These findings provide strong support for the fourth hypothesis, indicating that firms that implement more SMA practices experience a significant enhancement in their overall performance.

Appendix 22 reveals a significantly positive relationship between various groups of SMA practices and most components of intellectual capital (IC), with the exception of customer accounting and structural capital, which shows an insignificant correlation (0.011) This suggests that SMA practices are generally expected to positively influence the majority of IC components, serving as a foundational basis for further regression analysis.

The analysis presented in Appendix 23 shows that all VIF values are consistently below the critical threshold of 2, with the exception of the SMA variable, which has a value just under 5 This indicates that collinearity does not pose a significant concern for any of the constructs, ensuring the reliability of the partial least square path model estimations.

Chapter 5 presents data collection to construct the variables of SMA practices, the assessment of reflective and formative measurement scales, descriptive statistics and collinearity assessment

The study analyzed 174 valid responses, predominantly from the manufacturing sector, revealing that 70.11% of organizations exhibit a high level of Strategic Management Accounting (SMA) practices Notably, 92.62% of large enterprises demonstrate advanced SMA implementation The respondents, primarily senior managers with at least two years of experience in their current roles, included finance managers (27.01%), reporting managers (20.11%), heads of departments (14.36%), and general managers (14.36%) All participants possess expertise in accounting, planning, or finance, underscoring their qualifications in the field.

This chapter presents the assessment outcomes of reflective and formative measurement scales in relation to strategic management accounting (SMA) practices, following the research process outlined in Chapter 4 The dataset supports the reliability, convergent validity, and discriminant validity of the measurement scales associated with SMA practices The final 18 indicators for the four constructs of SMA practices are deemed satisfactory for further analysis Notably, there is no measurement scale for exception, and the issue of collinearity does not reach critical levels in any of the inner constructs.

The upcoming chapter will focus on data analysis and the empirical results derived from measurement and structural models It will examine both direct regression and mediated path regressions to explore the relationship between Intellectual Capital (IC) and corporate performance, specifically through the mediation of Strategic Management Accounting (SMA) practices Additionally, the chapter will assess the influence of SMA practices on the management of IC.

DATA ANALYSIS AND DISCUSSION

Evaluation of the fitness of theoretical models

The classical goodness-of-fit index (GoF) is not suitable for evaluating both inner structural and outer measurement models in PLS-SEM, as noted by Hair Jr & Hult (2016), Henseler et al (2015), and Nitzl (2016) Instead, the standardized root mean square residual (SRMR) serves as a promising alternative for this approach As indicated in Table 6.1, the SRMR values for all five models range from 0.048 to 0.073, all of which are below the acceptable threshold of 0.08, confirming that all proposed models exhibit a good fit to the data.

Table 6.1 Summary of the SRMR results of 5-testing models

SRMR values t value p value Conclusion

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1 h

Empirical results – testing of reciprocal correlations between intellectual capital

The findings in Table 6.2 validate hypotheses H1a – H1c regarding intellectual capital variables in the initial model Specifically, the results indicate a significant link between human capital and relational capital (β = 0.552; p < 0.01), as well as a connection from relational capital to structural capital (β = 0.256 – 260; p < 0.01) These relationships, observed across all regression models with four types of endogenous variables related to corporate performance, exceed the threshold of 0.2, highlighting their relevance for managerial consideration (Chin, 1998a).

Human capital has a significant direct effect on structural capital (β = 0.371 – 0.376, p < 0.001) Additionally, the indirect effect of human capital on structural capital is moderate (approximately 0.141) and statistically significant (p < 0.1) This indicates that relational capital serves as a complementary mediator in the relationship between human capital and structural capital, demonstrating partial mediation as human capital directly correlates with structural capital while relational capital partially mediates this relationship.

To evaluate the predictive power of the structural models, it is essential to consider the adjusted R² values of the endogenous constructs The findings indicate that relational capital ranges from 30.1% to 30.5% across all four tested models, while structural capital shows values between 30.0% and 30.8% An adjusted R² value of approximately 0.3 for both relational and structural capital suggests a moderate level of predictive accuracy (Hair Jr & Hult, 2016).

This study confirms that human, structural, and relational capital are interdependent and influence one another Human capital directly enhances both relational and structural capital, while relational capital also positively impacts structural capital Furthermore, relational capital acts as a complementary mediator in the relationship between human and structural capital Increased efficiency in human capital not only boosts structural capital efficiency directly but also enhances relational capital efficiency, which subsequently contributes to structural capital efficiency These findings align with previous research focused on intellectual capital (IC).

Table 6.2 Summary of the results of the first hypothesis testing

H1b ATO SCE  HCE + 0.371 2.679 *** 0.141 1.992 ** 0.512 6.120 *** Partial Support

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1 h

6.3 Empirical results – testing of the correlations between intellectual capital components and strategic management accounting practices (H 2 )

Table 6.3 summarizes the results examining SMA practices that are expected to be influenced by IC components’ intensity H2a, H2b, H2c are accepted in more details below

The analysis in Table 6.3 reveals that human capital significantly impacts the strategic management accounting (SMA) practices of respondent firms, with all β-path coefficients being positive and statistically validated at the 5 percent level across four corporate performance models: asset turnover (β = 0.081, p = 0.019), investment efficiency (β = 0.085, p = 0.010), return on equity (β = 0.082, p = 0.016), and Tobin q (β = 0.081, p = 0.018) Despite the statistical significance, the small size of the path coefficients may limit their managerial relevance However, the mediating effects of relational and structural capital, with a substantial path coefficient of 0.552, support the hypothesis H2a This mediation analysis indicates that while higher human capital directly enhances SMA practices, it also fosters relational capital, which subsequently promotes structural capital, further elevating SMA practices Consequently, firms that leverage human capital are more inclined to adopt SMA tools like the balanced scorecard and non-financial measures, which provide critical insights for strategic decision-making This trend suggests that robust internal knowledge, stemming from a strong human capital foundation, is essential for transitioning to advanced management accounting systems, enabling management accountants to generate valuable outputs that enhance firm value.

The t-statistics presented in Table 6.3, ranging from 2.369 to 2.456, exceed the threshold of 1.96, indicating that the β-path coefficients are significant at the 5 percent level and confirming a strong correlation between structural capital and strategic management accounting (SMA) practices across the four testing models, thus supporting hypothesis H2b This finding aligns with previous research that suggests the selection of SMA practices is influenced not only by technical or economic factors but also by cultural and political dynamics related to legitimacy, power, and organizational structure (Collier, 2001; M Hussain & Hoque, 2002) Organizations that prioritize strategy orientation tend to develop efficient routines and processes, leveraging structural capital as a foundation for transforming customer-focused and market-driven data into actionable insights for managerial decision-making For instance, firms with robust structural capital, such as comprehensive customer databanks, are better positioned to enhance their SMA practices, particularly in customer accounting As noted by Anderson (2007), a significant portion of the information needed for effective strategic management accounting lies outside the traditional accounting function, necessitating a strong infrastructure for successful SMA implementation.

The research highlights a significantly positive relationship between relational capital and Strategic Management Accounting (SMA) practices, with β-path coefficients ranging from 0.722 to 0.725 across all models This suggests that employees with stronger internal and external connections have enhanced access to resources that improve SMA practices, as much of the information necessary for SMA is sourced outside the accounting function Consequently, hypothesis H2c is supported However, the analysis of the indirect relationship through structural capital reveals that the empirical t values for the RCE → SMA relationship (ranging from 1.519 to 1.558) yield p values exceeding the 10 percent threshold, indicating a lack of mediation This implies that while information from external relations is directly utilized in SMA techniques by individuals, it fails to transform into explicit knowledge that can be shared throughout the organization.

The adjusted R² values for the structural models of SMA practices are significant, with ATO at 0.714, INVEFF at 0.711, ROE at 0.713, and TOBINQ at 0.718, indicating a strong fit This study confirms positive relationships between each component of intellectual capital (IC) and SMA practices, highlighting the need for managerial attention Furthermore, it identifies the mediating role of structural capital in the relationship between human capital and SMA practices The findings suggest that firms with higher values of IC components are better equipped to leverage these resources for implementing advanced management accounting practices like SMA.

Table 6.3 Summary of the results of the second hypothesis testing

H2a ATO SMA  HCE + 0.081 2.350 ** 0.472 8.056 *** 0.552 10.244 *** Partial Support

H2c ATO SMA  RCE + 0.722 18.807 *** 0.037 1.538 No 0.758 21.604 *** No Support

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1 h

Empirical results – testing of the direct correlations between strategic management

The results indicate a strong positive relationship between Strategic Management Accounting (SMA) practices and corporate performance, corroborating previous studies Notably, four β-path coefficients—asset turnover (β = 0.511, p < 0.01), investment efficiency (β = 0.724, p < 0.01), return on equity (β = 0.806, p < 0.01), and Tobin q (β = 0.653, p < 0.01)—are statistically significant across all models tested Vietnamese publicly traded enterprises are increasingly adopting SMA practices for operational and strategic decision-making As these firms grow and evolve, they are implementing more advanced management accounting systems to meet their complex managerial information needs, thereby enhancing productivity, financial performance, and overall firm value.

Recent studies indicate that Strategic Management Accounting (SMA) may be at risk of losing its traditional role as a key information provider for managerial decision-making aimed at enhancing corporate performance This is due to various techniques emerging outside the accounting function and increased demands for stronger internal controls and fraud detection Nevertheless, this study reaffirms the significant impact of SMA practices in Vietnamese public enterprises Vietnam's open-door policy has led to the establishment of numerous wholly foreign-owned enterprises over the past two decades, which have introduced innovative SMA knowledge to local practitioners Consequently, foreign managers are fostering new ideas that significantly enhance corporate performance, surpassing the conventional approaches of management accountants.

Table 6.4 Summary of the results of the forth hypothesis testing

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1

Empirical results – testing of the direct correlations (H 3 ) and indirect correlations

Table 6.5 presents the direct and indirect regression coefficients for all independent variables related to IC components, utilizing various performance measures—Asset Turnover, Investment Efficiency, Return on Equity (ROE), and Tobin's Q—as the dependent variables.

The analysis focuses on the direct influence of human capital on the asset turnover of the sampled firms The findings reveal a positive yet weak β-path coefficient for human capital, measured at β = 0.146, with statistical significance at a low level (p value < 0.05).

The study reveals that the direct relationships between structural capital, relational capital, and asset turnover are not significant at the 10 percent level, supporting only hypothesis H3a while rejecting H3b and H3c Consistent with previous research by Chang (2007) and Hong Pew et al (2007), it is evident that Vietnamese firms aiming to boost productivity prioritize the effective utilization of their human resources This focus on human capital enhances the efficient use of tangible assets, as employees' tacit knowledge plays a crucial role in driving productivity improvements, as noted by Bontis and Fitz-enz (2002) However, it is important to acknowledge that not all studies align with these findings, as highlighted by Firer and Mitchell-Williams.

Research by Shiu (2006) and Hang-Chan (2009) indicates a significant negative relationship between human capital and asset turnover, suggesting that the efficiency of a firm's human resources adversely affects productivity Additionally, this study identifies that SMA practices act as a full mediator in the relationship between human capital, relational capital, and asset turnover The mediation is indirect, demonstrating that SMA practices completely mediate the impact of human and relational capital on productivity The statistical analysis confirms the significance of the indirect effects of SMA practices in these relationships, with a t value of 3.882.

The study reveals that human capital and relational capital significantly influence Strategic Management Accounting (SMA) practices, which subsequently enhance productivity as indicated by asset turnover However, no direct or indirect relationship between structural capital and asset turnover was established, as both paths lacked statistical validation The predictive power of the asset turnover-related model is demonstrated by an adjusted R² of 0.501 for the non-mediated model and 0.574 for the mediated model, indicating that the components of intellectual capital (IC) explain over 50% of the variance in productivity These findings support hypotheses H5a and H5c regarding the connection between human and relational capital and productivity, but do not support H5b concerning asset turnover as an endogenous construct.

Investment efficiency is significantly influenced by structural capital, with a positive association indicated by a β coefficient of 0.162 and a p-value of 0.000 In contrast, the effects of human capital and relational capital on investment efficiency are not statistically significant, as evidenced by p-values of 0.295 and 0.140, respectively These findings highlight the critical role of structural capital in enhancing investment efficiency.

The analysis reveals that structural capital is crucial for efficient capital allocation, while strategic management accounting (SMA) practices play a significant mediating role between intellectual capital (IC) components and investment efficiency Specifically, SMA practices act as a complementary mediator between structural capital and investment efficiency, and serve as a full mediator for human and relational capital This indicates that while human and relational capital may not directly influence investment efficiency, they become valuable through SMA practices, which enhance the management of investment projects Furthermore, managers can leverage SMA techniques along with external information to optimize investment decisions, ultimately leading to sustainable investment efficiency The investment efficiency model demonstrates moderate explanatory power, underscoring the important relationship between IC components and investment efficiency mediated by SMA practices, thereby supporting hypotheses H5a, H5b, and H5c.

This study reaffirms the positive relationship between human capital and return on equity, with a coefficient of β = 0.074 and a p-value of 0.023 However, the strength of this association is too weak to draw broad managerial implications, aligning with findings from previous research, including those by Ming-Chin et al.

The study by Hong Pew et al (2005), Maditinos et al (2011), and others indicates that human capital is the primary component of intellectual capital (IC) that significantly influences a firm's profitability, as evidenced by its strong direct effect on return on equity The findings support the hypothesis that a lack of human capital can lead to decreased profitability due to ineffective employee involvement in business operations While the direct regression results highlight the importance of human capital, they do not affirm the significance of structural and relational capital However, the study confirms that these components positively impact profitability through the mediation of Strategic Management Accounting (SMA) practices, with significant coefficients for human (0.482), structural (0.110), and relational capital (0.619) at the 1% and 5% levels SMA practices partially mediate the relationship between human capital and profitability, while fully mediating structural and relational capital Overall, the implementation of SMA practices enhances the effectiveness of IC, contributing to improved future profitability, as reflected in the high predictive power of the return on equity model (adjusted R² = 0.870).

Appendix 26), and therefore IC components are the most suitable measures in explaining profitability, compared with productivity, investment efficiency or firm value This outcome is consistent with Ming-Chin et al (2005), where the predictive powers in the return on assets and return on equity models increase higher than the other financial performance measures when VAIC is split into IC components for an investigation

Finally, studies using IC components have resulted in a mixture of results related to firm value across different countries, industries and years For instance, Ming-Chin et al

Research indicates that intellectual capital significantly influences firm value (2005) However, Firer and Mitchell-Williams (2003) and Hang-Chan (2009) suggest that firms and investors prioritize physical capital over intellectual capital Additionally, Shiu (2006) and Hang-Chan (2009) find a negative correlation between human capital and market capitalization This conflicting evidence highlights the need for further investigation into the relationship between intellectual capital components and firm value, particularly using Vietnamese data.

The study explores the relationship between intellectual capital (IC) components and firm value, measured by Tobin's q While direct associations show a positive but statistically insignificant correlation for human capital (β = 0.130, p = 0.175), structural capital (β = 0.009, p = 0.881), and relational capital (β = 0.052, p = 0.479), these findings do not support hypotheses H3a, H3b, and H3c In contrast, an indirect model reveals that the β-path coefficients for human (0.394), structural (0.131), and relational capital (0.498) through strategic management accounting (SMA) practices are significantly positive, supporting hypotheses H5a, H5b, and H5c at the 1% and 5% levels This indicates that SMA practices serve as a full mediator in the relationship between IC components and firm value The research provides empirical evidence that firms with enhanced intellectual capital efficiency and effective SMA practices are valued more highly by investors, with an adjusted R² value of 0.751 underscoring the model's predictive power.

Overall, these results show the conclusions as follows:

 The adjusted R 2 defines IC components best in explaining the relationship with profitability presenting by the financial indicator of return on equity

The relationship between intellectual capital (IC) components and corporate performance reveals significant correlations, particularly between structural capital and investment efficiency Structural capital plays a crucial role in enhancing investment efficiency, as well-organized structures enable firms to allocate capital more effectively Additionally, the direct-effect model indicates that public enterprises depend on human capital to boost profitability, as evidenced by improvements in return on equity.

SMA practices serve as a mediator, fully or partially influencing the positive relationship between intellectual capital components and corporate performance, which is assessed through productivity, investment efficiency, profitability, and firm value However, it is important to note that structural capital does not significantly affect productivity, specifically in terms of asset turnover.

Firms convert external knowledge (RCE) into their internal knowledge base (HCE), enabling dissemination across the organization (SCE), which can enhance corporate performance metrics such as ATO, INVEFF, ROE, and TOBINQ when effectively managed through strategic management accounting (SMA) This aligns with Galbreath and Galvin's (2004) research, which emphasizes that no single resource is solely critical for determining corporate performance.

Empirical results – testing of the associations of strategic management accounting

Table 6.6 highlights the relationship between SMA practices—strategic cost management, competitor accounting, strategic accounting, and customer accounting—and the three core components of intellectual capital, outlining the essential concepts associated with each factor.

This study highlights the strong positive correlation between strategic cost management approaches—such as attribute costing, life cycle costing, quality costing, target costing, value chain costing, and activity-based costing—and high levels of structural (β = 0.605, p = 0.000) and relational capital (β = 0.342, p = 0.003), supporting hypotheses H6b and H6c However, there is no significant association between these approaches and the degree of human capital within firms (β = 0.251, p = 0.303) This indicates that strategic cost management effectively utilizes cost data to enhance structural and relational capital, thereby improving operational performance For instance, quality costing helps ensure customer satisfaction, thereby boosting relational capital, while contemporary systems like value chain costing and activity-based costing contribute to the enhancement of structural capital Nonetheless, traditional strategic cost management techniques are not reliable for measuring human capital efficiency, as evidenced by the lack of statistical affirmation in this relationship.

This study reveals that firms with elevated human and structural capital prioritize strategic costing approaches more significantly, indicating that the level of intellectual capital (IC) within organizations is influenced by strategic accounting-based methods.

Strategic accounting, which includes strategic costing, strategic pricing, brand valuation, and capital budgeting, demonstrates a positive correlation with both human capital and structural capital, supporting hypotheses H6a and H6b However, the impact of relational capital is not significant, indicating no support for H6c This suggests that strategic accounting plays a crucial role in managing human and structural capital The study reveals a distinction between conventional accounting and strategy-oriented accounting, with the latter emphasizing cost-effectiveness, quality, employee management, and long-term investment Firms with high human capital tend to utilize regular brand valuation, strategic costing, and strategic pricing Furthermore, strategic accounting practices, such as capital budgeting, are linked to enhanced structural capital, highlighting the effectiveness of modern techniques in knowledge management and supporting the notion that strategic orientation aligns with firms that have high intellectual capital.

The analysis of competitor accounting approaches reveals their positive impact on both structural capital (β = 0.286, p = 0.058) and relational capital (β = 0.237, p = 0.056) within respondent firms, although the significance of these results is relatively weak Additionally, while competitor accounting shows a positive association with human capital (β = 0.199), this relationship is not statistically significant (p = 0.336) These findings support hypotheses H6b and H6c.

Firms that invest significantly in competitor accounting strategies, such as benchmarking and performance appraisal, are better equipped to handle unexpected economic events By effectively managing relational capital, these companies can mitigate risks associated with stock market declines, competitive pressures, and investor overreactions Improved relationships with investors and competitors enable firms to anticipate external reactions in a volatile business environment This aligns with Lev and Zarowin's (1999) findings, suggesting that Malaysian firms with strong investor-board relationships experience reduced stock market volatility and less price overreaction.

Table 6.6 analyzes the relationships between customer accounting approaches—such as customer profitability analysis, lifetime customer analysis, and customer group valuation—and their impact on human, structural, and relational capital The findings indicate a negative but not statistically significant β-path coefficient for human capital (β = -0.067, p = 0.483) In contrast, both structural capital (β = 0.808, p = 0.000) and relational capital (β = 0.302, p = 0.000) show significant positive associations These results align closely with competitor accounting-based findings, supporting hypotheses H6b and H6c The outcomes suggest that customer accounting is a crucial strategic management accounting practice for managing relational and structural capital It enables firms to identify valuable customer groups, guiding marketing decisions related to expenditure on retention strategies, discounts, credit terms, and after-sales service Ultimately, these approaches enhance the financial value of marketing and product development, contributing to the efficiency of the operating management system and strengthening the firm's structural capital.

The study emphasizes that only strategic accounting approaches are employed for managing human capital, while all categories of strategic management accounting practices are confirmed to be effective in managing structural capital Additionally, three other groups of strategic management accounting practices—strategic cost management, competitor accounting, and customer accounting—are identified as the most suitable techniques for managing relational capital in Vietnamese publicly traded enterprises.

Table 6.6 Summary of the results of the sixth hypothesis testing

The importance of the use of

Variables loaded on factors t value (bootstrap)

Attribute costing, Life cycle costing, Quality costing, Target costing, Value chain costing, Activity-based costing

Strategic costing, Strategic pricing, Brand valuation, Capital budgeting

Benchmarking, Competitive position monitoring, Competitor cost assessment, Competitor performance appraisal, Integrated performance measurement

Customer profitability analysis, Life-time customer analysis, The valuation of customer group

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1

Empirical results – testing of control variables

To reduce the influence of other factors affecting corporate performance, four control variables—size, age, growth, and financial leverage—are integrated into the regression models The analysis reveals that neither firm size nor firm age shows a significant relationship with the dependent variables across the four research models, making it impossible to draw conclusions about these control variables.

The interactions between firm growth and dependent variables are significant at 10 percent level under the INVEFF, ROE and TOBINQ model and 5 percent level under h

The ASSTURN model indicates that firm growth positively impacts asset turnover, return on equity, and Tobin's q, suggesting that higher sales growth enhances a firm's wealth This finding aligns with previous research by Ming-Chin et al (2005), Hong Pew et al (2007), Nazari (2010), and Clarke et al (2011) Conversely, the study reveals a negative and statistically significant relationship between firm growth and investment efficiency (β = -0.091, t value = 1.921), echoing the conclusions of Q Li and Wang (2010), F Chen et al (2011), and Juan Pedro Sánchez and Gomariz (2012) This negative correlation suggests that increased firm growth may lead to managerial carelessness in investment decisions, ultimately harming investment efficiency.

The interactions between financial leverage and dependent variables are significant at the 10 percent level for the INVEFF and ROE models, and at the 5 percent level for the Tobin q model Financial leverage positively impacts ROE and Tobin q, suggesting that effective financial strategy planning can enhance return rates by yielding greater returns on borrowed funds compared to their costs Additionally, there is a significant negative correlation between financial leverage and investment efficiency (β = -0.112, t value = 1.837), indicating that firms with higher debt levels are subject to debt covenants that help reduce investment inefficiencies (Juan Pedro Sánchez & Gomariz, 2012).

Table 6.7 Summary of the testing results of control variables

Investment efficiency model ROE model Tobin q model β Result β Result β Result β Result

(SIZE) -0.011 No accepted 0.004 No accepted -0.028 No accepted 0.006 No accepted

(AGE) -0.015 No accepted -0.037 No accepted -0.004 No accepted -0.027 No accepted

Financial leverage (LEV) 0.076 No accepted

Note: Significant at: *10, **5 and ***1 percent levels (2-tailed)

Source: Calculated by the author in SmartPLS 3.1 h

This study successfully addresses all research questions, confirming reciprocal correlations among intellectual capital components The findings support the modified VAIC model's ability to estimate intellectual capital, particularly structural capital through organizational and innovation capital, which positively influences firms' performance, market value, profitability, and productivity Additionally, this research reinforces the resource-based theory, highlighting the importance of various resources, such as physical and intellectual capital, in developing advanced managerial systems like Strategic Management Accounting (SMA) to meet the growing demand for sophisticated managerial information, ultimately adding value to firms.

This study establishes a clear link between firms' financial performance indicators and their strategic management accounting (SMA) practices It reveals that SMA practices serve as a mediator, either fully or partially, enhancing the positive impact of intellectual capital (IC) components on corporate performance In the context of Vietnamese publicly traded companies, there is a prevailing preference for utilizing strategic management accounting to manage intellectual capital This indicates that these firms are increasingly adopting contemporary SMA systems to inform their operational and strategic decision-making processes.

The research underscores the significance of strategic management accounting (SMA) practices in managing intangibles, revealing that only strategic accounting approaches are applied to human capital management Notably, the findings confirm the effectiveness of various SMA practices in managing structural capital In contrast, three other SMA categories—strategic cost management, competitor accounting, and customer accounting—are best utilized for managing relational capital.

The next chapter is going to discussed some of the implications for integrations of strategic management accounting practices into intellectual capital management h

IMPLICATIONS FOR MANAGING INTELLECTUAL CAPITAL

A discovery of three-stage value-creating process

From the testing results of six hypotheses, this study provides undiscovered empirical evidence on a three-stage value production model demonstrating the capability of creating

Increasing a firm's value through intellectual capital (IC) efficiency is crucial for practitioners By applying Strategic Management Accounting (SMA) techniques and utilizing benchmarking, firms can pinpoint the necessary efforts to align with industry leaders This process involves analyzing performance to identify which organizations leverage their IC most effectively The three-stage model offers a significant advantage as it measures the relationship between inputs and outputs while encompassing the entire value-creation process.

The three-stage value-creating process highlights the positive relationships among intellectual capital (IC) components, confirming their impact on IC capability performance (Stage 1) This stage emphasizes a firm's ability to generate and utilize IC through both internal and external resources, which fosters improved managerial systems like strategic management accounting (SMA) The second stage reinforces the importance of SMA practices in managing IC capital to enhance efficiency performance Ultimately, the third stage illustrates how the efficiency of IC contributes to a firm's added value, as evidenced by a higher market-to-book ratio, further supported by the study's H3 and H5 hypotheses.

Figure 7.1 The three-stage value-creating process by IC and SMA practices

Source: Developed by the author

In today's knowledge-based economy, intellectual capital (IC) serves as both a competitive advantage and a means to enhance a firm's value While numerous studies have established a link between IC and corporate performance, there remains a lack of research focused on the processes of IC creation and its efficiency in developing managerial systems that foster value This study presents a comprehensive model illustrating the relationship between resources, practices, and performance from a resource-based perspective Consequently, it is concluded that IC efficiency surpasses IC capability, indicating that even firms with limited IC capabilities can significantly benefit from effective management of their intellectual capital, driving sustained value growth.

IC capability SMA Practices IC efficiency Corporate performance

Implications for the management, policy and research of intellectual capital

While physical and financial assets are important, intellectual capital (IC) elements such as knowledge, strong branding, essential skills, corporate reputation, and stakeholder relationships are vital for achieving sustainable competitive advantages Leading companies like Amazon, Wal-Mart, Microsoft, and Google exemplify the significance of IC in their success (Marr, 2008) Although physical assets like office buildings and warehouses matter, they are less impactful than technology, market insights, and customer knowledge For example, Wal-Mart's success relies on its strategic store placements, consumer understanding for inventory selection, and expertise in stock replenishment Without effective management of intellectual capital, physical assets become mere commodities yielding average returns (Marr, 2008) Therefore, organizations aiming to stay competitive must adopt tools and techniques to effectively manage their intellectual capital.

This study demonstrates that intellectual capital (IC) positively influences the performance of publicly traded companies in Vietnam Additionally, not-for-profit organizations can utilize this research as a foundational method to explore whether they experience similar conditions as the sample firms analyzed Understanding the impact of IC can provide valuable insights for various types of organizations.

Organizations can enhance their intellectual capital to improve corporate performance and strengthen their competitive position Just as muscles weaken without use, intellectual capital diminishes when not actively engaged To thrive in today's market, organizations must excel in international organizational learning.

1990) Strategically managing IC should follow these steps:

To effectively assess intellectual capital (IC), organizations should begin with an IC audit, which may involve designing and administering surveys using Likert scales or calculating the VAIC value to gauge the current level of IC However, given that each firm possesses unique characteristics and operates within distinct industry contexts, it is essential for organizations to develop tailored management metrics that align with their specific strategic objectives.

To enhance individual competency (IC) management, organizations should focus on evaluating each employee by setting specific targets for their development For instance, companies can encourage employees to explore areas of knowledge or skills that are currently unfamiliar to the organization, fostering growth and innovation.

To effectively leverage knowledge within your industry and business, it is essential to formally define its role and gather intellectual resources from diverse sources, including suppliers, customers, government entities, academia, and industry associations.

 Recruit a leader who is responsible for developing your organization's intellectual capital This person must have an integrated background in human resources, strategy and information technology

To enhance your intellectual portfolio, develop a knowledge map of your organization to pinpoint where knowledge is held among individuals and systems For instance, establish a central database to consolidate and provide access to all competitive intelligence.

 Utilize information systems and sharing tools that aid in knowledge exchange and codifying such as groupware technology, video conferencing, Intranets, corporate universities and storytelling amongst employees

Marr (2008) outlines five essential steps for effectively managing intellectual capital, starting with the identification of an organization’s intellectual assets Following this identification, it is crucial for managers to evaluate the value of these assets to ensure successful management.

Not all intellectual capital holds inherent value for an organization; its worth is determined by its ability to support organizational objectives Therefore, managers should assess the relevance of intellectual capital by aligning it with a strategic map that highlights its value drivers Subsequently, meaningful management information can be extracted by measuring the performance of intellectual capital This information is crucial for analyzing performance and generating insights that guide organizational decision-making and learning Finally, external reports can be created to effectively communicate the value of intellectual capital to both internal and external stakeholders.

Figure 7.2 Five-step intellectual capital management model

In conclusion, prioritizing intellectual capital (IC) efficiency over IC capability is essential for enhancing firm value When starting with limited intellectual capital, managers should concentrate on efficient management practices to generate additional intellectual capital This shift in mindset necessitates that managers adopt relevant measurement techniques and strategically manage IC to distinguish their organizations from mediocrity and achieve excellence.

This study highlights the connection between the efficiency of value-added (VA) as measured by a firm's intellectual capital (IC) components and traditional corporate performance metrics Despite efforts to enhance intellectual capital in publicly traded companies, the Vietnamese business landscape continues to prioritize physical capital assets, largely due to the indifference of many small and medium enterprises towards effective IC management Consequently, policymakers are encouraged to implement initiatives that foster a deeper understanding and acceptance of the IC concept among businesses in Vietnam.

SMEs may have negative consequences during the period when Vietnam continues efforts to join in the international community

Policymakers should encourage Vietnamese firms to voluntarily provide intellectual capital (IC) reports to capital and debt holders, aligning with the global trend of external reporting While the primary focus of IC reporting frameworks is internal management, the current accounting systems in Vietnam often neglect to capture the value of intellectual capital To address this gap, it is essential to establish necessary guidelines, as the International Accounting Standards Board and other national standard-setting bodies have adopted a conservative stance on accounting for intangibles.

The primary challenge in establishing standards for measuring intellectual capital (IC) lies in identifying appropriate indicators that enhance comparability among firms To address this issue, it may be beneficial to develop intermediary guidelines for companies, as suggested by Brennan & Connell (2000) Furthermore, Grojer and Johanson (1999) warn that implementing a mandatory standard during a time of rapid change in IC could be detrimental.

A flexible voluntary standard that can be modified or discarded as needed is preferable Policymakers should encourage companies to explore three reporting approaches for intellectual capital (IC) information, drawing on the recommendations from Abhayawansa (2014) and the International Integrated Reporting Council (IIRC, 2013, p 35).

 “Explanation of how IC fits within business strategies and overall corporate objectives;

 Assessment of IC indicators based on their importance in achieving organizational objectives and/ or strategies;

 Disclosure of an inventory of IC indicators without linking these to organizational objectives and/ or strategies.”

When disclosing intellectual capital (IC) information in the capital market, it is crucial to carefully consider the potential loss of competitive advantage The absence of mandatory standards for IC means that voluntarily disclosed information can be easily appropriated or imitated by competitors Therefore, organizations must strike a balance between the necessity of IC disclosure and the risk of enabling competitors to gain an unfair advantage.

Implications for integration of strategic management accounting practices into

To enhance future value, organizations must deepen their understanding of intellectual capital and utilize the latest tools for its identification, measurement, and management The strategic management accounting (SMA) approach equips managers and accountants with essential skills to effectively handle intangibles, thereby boosting organizational performance and future value Additionally, SMA practices focus on innovative tools for internal management, enabling companies to report intellectual capital externally and improve stakeholder communication regarding the organization's value The following sections will outline strategies for managing intellectual capital based on various strategic management accounting techniques.

7.3.1 Orientations to manage intellectual capital by strategic cost management

Strategic cost management positively correlates with structural and relational capital, serving as a vital tool for managing these components to enhance a firm's development By utilizing cost information, organizations can effectively identify and manage these key value drivers, leading to improved operational performance Intellectual capital components are dynamic and interdependent, influencing each other and interacting with both tangible and intangible resources to create core competencies that deliver value propositions The value proposition outlines key stakeholder outputs and core activities essential for differentiation, derived from an analysis of organizational purpose and stakeholder needs Techniques like attribute costing and life cycle costing within strategic cost management help clarify the role of intellectual capital, enabling organizations to align their offerings with customer expectations and define activities linked to their core competencies.

According to Bollen et al (2005), while many organizations have diverse forms of intellectual capital (IC), certain types play a more significant role in enhancing their value proposition The effectiveness of intellectual capital is closely linked to the specific strategy employed by the organization.

The analysis of the value chain within each business unit highlights the significance of intellectual capital as a core competency driving success For instance, technology development, a support activity in the value chain, exemplifies how the processes employees engage in to generate intellectual capital can themselves be considered a form of this capital By understanding the performance and interconnections of value chain activities, businesses can enhance customer satisfaction and value, particularly regarding cost efficiency, quality, delivery, and overall satisfaction Consequently, value chain analysis contributes to the growth of structural and relational capital An illustrative example of the relationship between value chain analysis and intellectual capital components is provided in Table 7.1.

Table 7.1 Example of intellectual capital components in value chain

Types of intellectual capital Human capital Structural capital Relational capital

The ability of materials control

Operations Expertise on management of operations and production

Actions could position company’s reputation into higher level, e.g friendly environment products h

Types of intellectual capital Human capital Structural capital Relational capital

The ability of logistic activities control

Taking care of availability of products

Customers convenience such as shop more appealing, more facilities

Responsibilities and integrity of employees to prepare quotations

Development and maintenance of electronic connections

Relationship with external expert or consultant

Good connection to recruit mature staff

The ability of creative strategies development

Source: Developed by the author

7.3.2 Orientations to manage intellectual capital by competitor accounting

Research findings indicate that competitor accounting approaches significantly influence both structural and relational capital These approaches enable firms to effectively navigate unexpected economic events by fostering better relationships with investors and competitors This understanding allows companies to anticipate external reactions to changes in a turbulent business environment, ultimately aiding managers in developing effective strategies.

To understand the role and strategic importance of intellectual capital in any organization therefore requires a clear understanding of the firm’s strategic direction and objectives

Benchmarking and competitive analysis are essential techniques for identifying operational and strategic gaps within a company To enhance competitiveness, organizations must first understand the reasons behind the competitive gap with industry leaders Research indicates that intellectual capital plays a significant role in this gap, varying by specific business activities Once identified, managers can use this information to benchmark against top competitors, such as using McDonald's intellectual capital as a model in the fast-food sector Viedma-Marti's intellectual capital benchmarking system framework (ICBS) is recommended for analyzing local and global competitors, facilitating comparisons and improvements in intellectual capital The ICBS model focuses on comparing a company's core competencies with those of its leading competitor, while recognizing that variations exist across different business units By applying the value chain mechanism to each unit, organizations can identify the core competencies that drive the success of top competitors, providing insights into the reasons behind competitive gaps.

Competitive analysis involves monitoring competitors' positions, assessing their costs, and appraising their performance through financial data This process includes regularly updating forecasts of competitors' costs per item and evaluating their sales, market share, and unit costs, offering a comprehensive view of their competitive standing Additionally, competitor performance appraisal, as defined by Simmonds, analyzes published financial statements to identify key sources of competitive advantage To effectively assess competitors' intellectual capital (IC) performance, various accessible sources such as direct observations and published accounting data should be utilized A systematic comparison of one's own unit costs with those of competitors requires evaluating structural and relational capital, which can significantly impact corporate and business strategies Addressing cost disadvantages through targeted cost reduction programs can help mitigate the risks of intense competition.

To effectively measure intellectual capital, organizations must first identify and map its value drivers before implementing an integrated performance measurement system that combines both financial and non-financial metrics (Kaplan & Norton, 2001) This system is crucial for understanding current performance levels, assessing improvements or declines in intellectual capital, and evaluating the impact of various initiatives Access to meaningful performance data enables organizations to make informed decisions, refine strategies, and manage associated risks Utilizing tools like the balanced scorecard within the strategic management cycle allows for a comprehensive evaluation of intellectual capital performance across multiple perspectives (Kaplan & Norton, 2001) Additionally, organizations must proactively address any potential risks linked to their intellectual capital.

Organizations often excel in managing financial and disaster risks, yet they frequently neglect the management of intellectual capital risks, particularly those related to human capital The potential loss of employees possessing critical knowledge and expertise poses a significant risk that is commonly overlooked Additionally, knowledge, while essential, is a vulnerable resource that can diminish if not properly nurtured In the current network economy, maintaining strong relationships is crucial for both private and public organizations, as their reputations depend on these connections Consequently, managing risks throughout the supply chain is vital for delivering products and services effectively To navigate these challenges, performance measurement is essential for assessing risks associated with intellectual capital Given its role as a key value driver, organizations should prioritize data accumulation to identify and understand their greatest risk exposures.

7.3.3 Orientations to manage intellectual capital by strategic accounting

This study reveals that firms with elevated levels of human and structural capital place significant emphasis on strategic accounting-based approaches, particularly strategic costing methods.

“Strategic pricing, Strategic costing, Brand valuation and Capital budgeting”, as shown in Table 6.6

Pricing is a complex process that requires companies to allocate resources, establish infrastructure, and develop effective processes to determine the optimal price at any given moment Additionally, the existing intellectual capital significantly influences a company's pricing strategy capabilities.

An effective pricing process demands well-trained personnel who grasp the complexities of the company, including its strategy, product range, customers, suppliers, and competitors While having dedicated individuals for pricing decisions is essential, their effectiveness is hindered without adequate structural capital to support the pricing process Therefore, developing both human and structural capital is crucial for establishing an efficient pricing strategy Additionally, investing in relational capital is vital for enhancing strategic capability, particularly in anticipating and managing customer responses to price changes, which can be a cost-effective aspect of pricing A strategic pricing approach also serves as a tool for managing intellectual capital; for instance, companies pursuing a cost leadership strategy must leverage their structural capital to maintain efficient production processes and achieve cost savings Consequently, managers should focus on continuously improving production methods to sustain their competitive edge in cost leadership while effectively managing human capital through training or hiring professionals with pricing expertise.

Strategic costing is essential for managing a firm's structural and relational capital, utilizing a cost database with strategic information to analyze costs associated with customers, stakeholders, and regulators for a sustainable competitive advantage Customer costs arise from acquiring and servicing clients, while stakeholder costs involve transactions with employees, suppliers, and investors Regulatory costs are imposed by various governmental entities and contribute to relational capital To enhance relational capital, management accountants and financial managers must reallocate funds from elective costs—largely self-imposed and procedural—to under-resourced strategic costs, focusing on optimal spending that promotes new product development and market expansion, ultimately increasing customer retention and driving repeat purchases.

Traditional appraisal techniques are becoming inadequate for evaluating intangible investments due to their associated non-financial benefits and complex costs (Tayles et al., 2007) Mouck (2000) emphasizes that conventional capital budgeting models fail to serve the high-tech, knowledge-based sectors of the economy As companies invest more in intangible assets rather than tangible ones, justifying these investments with traditional capital budgeting tools is increasingly challenging (Irani, Ezingeard, & Grieve).

The growing literature on real options enhances traditional capital budgeting by offering a more suitable evaluation of strategic investments (Tayles et al., 2007) Firms with high intellectual capital (IC) that invest significantly in innovation are better positioned to capitalize on future, unidentified opportunities, including market entry, follow-on product development, and brand extensions Traditional discounted cash flow models fail to account for the value of options inherent in corporate decisions (Tayles et al., 2007) High structural capital firms are more likely to implement capital investment systems that effectively capture the costs and benefits of intangibles, enabling them to adopt a real options approach and pursue projects that may not seem financially viable Evidence from Malaysian high IC firms indicates that those emphasizing managerial creativity, innovation, intellectual property, and stakeholder relationships tend to exhibit substantial strategic flexibility, relying less on conventional capital budgeting methods like net present value, while easily identifying follow-on options.

Summary of research findings

This study explores the relationships between intellectual capital (IC) components and corporate performance, focusing on the role of strategic management accounting practices as a mediator The research identifies three key interrelated non-financial components of IC: human capital, structural capital, and relational capital It examines the impact of these components on four financial performance indicators—asset turnover, investment efficiency, return on equity (ROE), and Tobin's q To test the research hypotheses, the study employs partial least squares structural equation modeling using SmartPLS 3.1.

The findings of my study contribute to the existing literature by demonstrating the interconnectedness of intellectual capital (IC) components Specifically, the empirical evidence indicates a positive and significant relationship between human capital and both structural and relational capital Additionally, relational capital is shown to positively influence structural capital, while also acting as a complementary mediator in the relationship between human capital and structural capital.

There is a significant connection between IC components and SMA practices, indicating that the capacity of intellectual capital enhances the implementation of strategic management accounting A deeper analysis shows that structural capital mediates the relationship between human capital and SMA practices, while it does not influence the link between relational capital and SMA practices This suggests that employees with superior knowledge, combined with a well-organized infrastructure, are more likely to successfully implement SMA techniques Furthermore, information gathered from external sources is utilized directly in SMA methods by individuals, without being converted into explicit knowledge.

There is limited direct correlation between intellectual capital (IC) components and corporate performance, with the exception of structural capital, which enhances investment efficiency through a well-organized framework that aids in capital allocation However, strategic management accounting (SMA) practices play a crucial mediating role, either fully or partially enhancing the positive impact of IC components on corporate performance.

Forthly, with rejections to majority of null hypotheses, this study confirms relationships between firms’ financial performance indicators and their strategic management accounting practices

The study emphasizes that only strategic accounting approaches are utilized for managing human capital Notably, the findings confirm the effectiveness of all categories of strategic management accounting practices in managing structural capital In contrast, the other three groups of strategic management accounting practices—strategic cost management, competitor accounting, and customer accounting—are best suited for managing relational capital.

This study reveals a three-stage value-creating process based on the testing of six hypotheses, highlighting the integration of strategic management accounting (SMA) practices into intellectual capital (IC) management The first stage emphasizes a firm's ability to generate IC through both internal and external resources, alongside effectively utilizing IC components to implement improved managerial systems such as the SMA approach The second stage, focused on IC efficiency performance, illustrates how successful firms continue to enhance their value-creating processes by leveraging strategic management accounting techniques to generate additional intellectual capital Finally, the third stage, known as added-value performance, demonstrates that the efficiency of IC significantly contributes to increasing a firm's added value, as evidenced by a higher market-to-book value.

Theoretical contributions

This dissertation contributes to the literature in several ways:

This study investigates the mediating role of Strategic Management Accounting (SMA) practices in the relationship between intellectual capital (IC) and corporate performance, marking a novel exploration of the indirect pathway linking these elements By bridging the research gap, it enhances the existing literature on resource management, specifically focusing on the interplay between intellectual capital, SMA practices, and financial performance The confirmation of SMA practices as a mediator offers valuable insights into managerial behaviors, highlighting the strategic use of management accounting in organizations with significant levels of intellectual capital.

This dissertation advances the study of accounting for intellectual capital by examining the impact of various Strategic Management Accounting (SMA) techniques on the components of intellectual capital It is the first research to evaluate the appropriateness of SMA techniques for managing these components The significant statistical findings provide managerial insights on which groups of SMA techniques are most effective for managing intellectual capital components.

This study explores the impact of Intellectual Capital (IC) and Strategic Management Accounting (SMA) practices on investment efficiency, a key indicator of corporate productivity and performance It adds to the existing literature by providing empirical evidence on how IC and SMA practices enhance investment efficiency Notably, the research highlights the importance of human capital and well-structured processes in facilitating effective capital allocation Furthermore, it suggests that improved SMA practices enable managers to make more informed investment decisions by accurately identifying optimal projects and providing reliable accounting information for internal stakeholders.

This study enhances intellectual capital (IC) measurement by introducing a novel method for assessing organizational capital efficiency, a key component of structural capital To align with the measurement of other IC elements, organizational capital should focus on cost-based metrics and the capitalization of selling and general administrative expenses Unlike previous studies that primarily utilized market or survey-based approaches, this method offers a distinct perspective on evaluating organizational capital.

This study explores the accounting of intellectual capital (IC) in Vietnam, a transitional economy that has lacked empirical research in this area It contributes to the IC research community by combining primary data from surveys with secondary financial data from statements, offering a new perspective distinct from previous studies that relied solely on case studies or financial data This research aligns with the growing academic interest in the external reporting of intellectual capital's value to businesses.

Practical managerial contributions

The current study enhances the existing literature on intellectual capital (IC) by identifying the key elements that significantly impact a firm's performance This insight will enable organizations to gain a clearer understanding of their organizational capabilities and improve their management strategies Additionally, it will assist firms in pinpointing the most effective indicators for predicting their success.

The findings of this study highlight the urgent need for Vietnamese managers to recognize the significance of intellectual capital in enhancing a company's value Consequently, there is an increasing demand for management accounting practices that effectively capture, measure, and report on the value and performance of intellectual capital.

The interconnection of intellectual capital (IC) components highlights the importance of linking these elements for effective utilization Managers must invest in organizational routines and processes to harness the knowledge held by individuals, ensuring that it translates into practical benefits for the organization.

This study demonstrates that intellectual capital (IC) significantly impacts management accounting practices, particularly through the adoption of strategy-driven approaches that incorporate a blend of financial and non-financial metrics, moving beyond a sole emphasis on profit.

In conclusion, this study recommends that managers utilize various strategic management accounting (SMA) techniques tailored to specific objectives within intellectual capital management.

Strategic cost management utilizes techniques such as attribute costing, life cycle costing, value chain analysis, and activity-based analysis to develop value creation maps These maps illustrate the essential connections between an organization’s intellectual capital, value proposition, and core activities, highlighting the cause-and-effect relationships that drive value creation.

Competitor accounting approaches significantly influence both structural and relational capital by enabling organizations to effectively navigate unexpected economic events By fostering a deeper understanding of investor and competitor dynamics, these approaches help businesses anticipate external reactions to shifts in a turbulent environment, ultimately empowering managers to develop strategic responses.

Strategic-based accounting involves managerial actions aimed at continuous improvement, with some decisions guided by insights from the management accounting system, while others are made independently This approach focuses on process enhancements that identify opportunities for greater efficiency and effectiveness, ultimately boosting intellectual capital Ideally, strategic-based accounting should prioritize value creation, striving not only to reduce costs but also to enhance intellectual capital and increase shareholder value.

Businesses should adopt a customer-centric strategy rather than relying on a traditional product-focused approach This involves utilizing three key customer accounting techniques: identifying customer contributions, measuring customer satisfaction, and assessing customer capital By addressing these elements concurrently, firms can effectively manage their relational capital.

Limitation

This study acknowledges several limitations, primarily that the sample examining the relationship between intellectual capital and corporate performance is restricted to listed companies The difficulty in obtaining annual reports from companies not listed on the Vietnamese stock exchange has resulted in their exclusion from this research.

One limitation of this study is the small sample size, which restricts the ability to analyze the invariance of hypothesized relationships across different industry types To better understand the influence of industry type, future research may need to focus on industry-specific studies or gather data from Vietnamese organizations over an extended period Moreover, since the data is derived from a single East Asian country, the findings may be subject to noise and should be interpreted cautiously to avoid overgeneralization.

The VAIC model, while gaining attention for cross-company comparisons, faces limitations due to data unavailability and its econometric properties In Vietnam, firms are not mandated to disclose R&D investment levels, complicating the collection of relevant financial data Consequently, this study measures innovation capital efficiency by examining cash outflows for purchasing tangible and intangible assets, excluding those related to controlled entities Additionally, the lack of data hinders the investigation of input-output relationships, raising questions about the validity of human capital proxies Although labor markets value skilled employees higher, it remains uncertain whether these higher salaries correlate with increased productivity.

This study highlights the proposed orientations for managing intellectual capital (IC) through strategic management accounting (SMA) practices However, it is important to note that the specific relationships between each SMA technique and the components of IC have not been re-evaluated using quantitative or qualitative statistical models due to limitations in time and scope.

Further research directions

This study has not examined variations in intellectual capital proxies across different industries due to certain limitations Future research should consider exploring these variations and investigating additional indicators of corporate performance.

Intellectual capital (IC) is crucial for gaining competitive advantage, yet the field is still developing and lacks maturity in quantifying and reporting practices One major challenge for the accounting profession is creating comparable IC measures across different firms due to its inherent complexity and diversity While the international accounting community is increasingly focused on understanding IC management and reporting, the evolution of widely accepted practices is still a long way off There is a pressing need for research to evaluate the relevance and usefulness of IC reporting guidelines for various stakeholders, particularly concerning the perceptions of stakeholders in small and medium-sized enterprises (SMEs) and the non-profit sector.

To enhance the credibility of intellectual capital (IC) information and increase user trust, it is essential to implement auditing practices as recommended in section 7.2.3 Unlike tangible assets, IC assets require unique auditing approaches, necessitating the development of new procedures to validate measurement techniques Grojer and Johanson (1999) emphasize that the exploration of innovative auditing methods is a critical area for further research.

To validate the findings of this study over time, future research should replicate the model used in a longitudinal manner Currently, Vietnamese accounting standards do not mandate the disclosure of research and development, advertising, or marketing costs, making such disclosures voluntary and resulting in a limited number of companies reporting all three This lack of mandatory disclosure restricts the potential for time series analysis However, as more companies begin to report these expenditures, the feasibility of conducting longitudinal studies is expected to improve in the future.

This study marks the initial phase of an ongoing investigation into intellectual capital (IC) stocks and flows, emphasizing the management of IC through Strategic Management Accounting (SMA) practices The findings highlight the necessity for future research to develop a more nuanced understanding of IC that incorporates dynamic capabilities and the integration of various SMA techniques Additionally, it calls for an exploration of boundary conditions and moderating variables Future directions should also focus on reassessing the implementation of SMA techniques to enhance the management of IC components, ultimately boosting corporate performance.

This study serves as a benchmark for the modified VAIC model, which estimates the intellectual capital components linked to firms' market value, profitability, and productivity It provides an additional method for assessing organizational capital efficiency, a crucial aspect of structural capital, and offers guidance for managing intellectual capital through strategic management accounting practices.

LIST OF THE AUTHOR’S PUBLICATIONS

Trinh Hiep Thien (2015) “Factors Affecting the Propensity to Create Budgetary Slack – Evidence from Vietnamese Enterprises” Journal of Economic Development (English version), 22(1), 100-124

The study by Trinh Hiep Thien et al (2014) investigates the relationship between corporate social responsibility (CSR) disclosures and firm value in Vietnam It provides empirical evidence indicating that effective CSR communication can enhance a company's market value The findings suggest that firms that actively disclose their CSR efforts may attract more investors and improve their financial performance, highlighting the importance of transparency in corporate practices The research is published in the International Journal of Accounting and Financial Reporting, volume 5, issue 1, pages 212-228.

Papers published in the international conference proceedings

Trinh Hiep Thien (2018) “Do managers cut sticky costs to alleviate financial distress during the global economic crisis – Evidence from Vietnamese public enterprises”

The 5th IBSM International Conference on Business, Management and Accounting Proceedings, Hanoi University of Industry, University of Economics in Bratislava Slovakia and University of Social Sciences Poland, ISBN 976-602-72911-6-4

Trinh Hiep Thien, Doan Ngoc Que, Le Dinh Truc (2017) “Association between intangible investments and cost of equity capital – Evidence from Vietnam” The 3 rd

International Conference on Accounting and Finance 2017 Proceedings, University of Economics, Da Nang, Aston University, YOKOHAMA National University, Institute of Global Finance and ACCA, ISBN 978-604-84-2457-2

Trinh Hiep Thien, Doan Ngoc Que, Le Dinh Truc (2016) “Endogenous association between financial reporting quality and investment in sustainable development” The

2 nd International conference on Accounting and Finance 2016 Proceedings,

University of Economics, Da Nang, Aston University, YOKOHAMA National University and ACCA, ISBN: 978-604-84-1563-1

Trinh Hiep Thien, Tran Anh Hoa, Le Hoang Oanh (2016) “Financial Reporting quality and investment in sustainable development – Evidence from Vietnam” The 3rd

International Conference on Finance and Economics Proceedings, Ton Duc Thang h

University, HCMC and TOMAS BATA University IN ZLIN, ISBN 978-80-7454- 598-6

In their 2015 study, Trinh Hiep Thien, Doan Ngoc Que, and Le Hoang Oanh explore the relationship between corporate governance and accounting conservatism in Vietnamese public enterprises Presented at the International Conference on Accounting, the research provides valuable insights into how effective corporate governance practices influence accounting decisions within this context The findings, documented in the conference proceedings, contribute to the understanding of financial reporting standards in Vietnam.

In the 2015 study by Trinh Hiep Thien, titled “Value Relevance of Nonfinancial Information Disclosed in Annual Reports During the Global Financial Crisis: Evidence from Vietnamese Public Enterprises,” the research highlights the significance of nonfinancial disclosures in annual reports amid economic turmoil The findings presented at the 3rd International Conference on Business, Economics, and Accounting reveal that such nonfinancial information plays a crucial role in enhancing the value relevance for stakeholders, particularly during challenging financial periods This study underscores the importance of transparency and comprehensive reporting in fostering trust and informed decision-making among investors and the public.

Education Organizer Training and Consulting, ISBN 978-602-84-19725-8-8

In the 2018 study by Trinh Hiep Thien, titled “Association between goodwill and cost of equity capital – Evidence from Vietnamese public enterprises,” published in The Economic Scientific Research Proceedings by HUTECH University, the author explores the relationship between trade advantages and the cost of equity capital among publicly listed companies in Vietnam This research provides valuable insights into how goodwill impacts financial performance and capital costs in the Vietnamese market, contributing to the understanding of corporate finance dynamics in emerging economies.

Trinh Hiep Thien and Nguyen Xuan Hung (2017) explore the application of Partial Least Squares Structural Equation Modeling (PLS-SEM) in management accounting research, highlighting its potential as a tool for advancing future studies Their work was presented at the Conference on Accounting and Auditing Issues in Scientific Research and Business Environment, hosted by the University This research emphasizes the importance of PLS-SEM in enhancing analytical approaches within the field of management accounting.

Trinh Hiep Thien and Nguyen Xuan Hung (2016) explore the relationship between sustainable development investments and financial performance, emphasizing the role of financial reporting quality in this association Their research highlights how effective financial reporting can influence the outcomes of sustainable investments, ultimately impacting overall financial success This study underscores the importance of transparent financial information in driving sustainable investment strategies and enhancing financial performance.

Conference on Accounting and Auditing in the context of the International h

Integration and the Newly Commercial Conventions Proceedings, Hanoi University of Industry, ISBN 978-694-65-2831-9

Trinh Hiep Thien (2016) discusses the evolution of management accounting towards strategic management accounting in the context of modern business environments The article emphasizes the need for management accounting to adapt to contemporary challenges, highlighting the integration of strategic decision-making processes It underscores the importance of aligning accounting practices with broader business strategies to enhance organizational performance The findings were presented at The National Conference on Accounting, showcasing the relevance of these changes in today’s competitive landscape.

Auditing in the context of Vietnamese Integration in TPP and AEC, National

Trinh Hiep Thien and Nguyen Xuan Hung (2016) conducted a study exploring the relationship between financial reporting quality and the quality of sustainable development information in Vietnamese public enterprises Their research emphasizes the importance of integrated reporting as a means to enhance transparency and accountability in financial disclosures The findings suggest that improving the quality of both financial and sustainability reports can significantly benefit public enterprises in Vietnam.

Le Hoang Oanh, Trinh Hiep Thien, Nguyen Bao Linh (2016) “The determinants influencing the decisions on learning professional accounting program – Evidence from undergraduate students”, University-level research project, University of

In their 2014 research project conducted at the University of Economics in Ho Chi Minh City, Nguyen Thi Ngoc Bich, Trinh Hiep Thien, Le Viet, Tran Thi Thanh Hai, Nguyen Thi Phuoc, and Le Hoang Oanh explored the effects of corporate social responsibility (CSR) disclosure on firm value in Vietnam Their empirical evidence highlights the significant relationship between CSR practices and the financial performance of companies, emphasizing the importance of transparency in enhancing corporate reputation and stakeholder trust.

Abhayawansa, S (2014) A review of guidelines and frameworks on external reporting of intellectual capital Journal of Intellectual Capital, 15(1), 100-141 doi:http://dx.doi.org/10.1108/JIC-04-2013-0046

Al-Mawali, H., & Al-Shammari, H (2013) Strategic Management Accounting Usage,

Perceived Environmental Uncertainty and Organizational Performance

Alamri, A M (2018) Association between strategic management accounting facets and organizational performance Baltic Journal of Management

Alavi, M., & Leidner, D E (2001) Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues MIS Quarterly,

Alcaniz, L., Gomez-Bezares, F., & Roslender, R (2011) Theoretical perspectives on intellectual capital: A backward look and a proposal for going forward Accounting

Forum, 35(2), 104-117 doi:http://dx.doi.org/10.1016/j.accfor.2011.03.004

Alum, R A., & Drucker, P F (1986) Innovation and Entrepreneurship: Practice and

Alvesson, M., & Deetz, S (2000) Doing critical management research: Sage

Amir, E., & Lev, B (1996) Value-relevance of nonfinancial information: The wireless communications industry Journal of Accounting and Economics, 22(1), 3-30

Amit, R., & Schoemaker, P J (1993) Strategic assets and organizational rent Strategic management journal, 14(1), 33-46

Andersen, R., & McLean, R (2000) Accounting for the Creation of Value Ongoing research project sponsored by the Canadian Institute of Chartered Accountants

Anderson, S W (2007) Managing costs and cost structure throughout the value chain: research on strategic cost management In C S Chapman, A G Hopwood, & M

D Shields (Eds.), Handbook of Management Accounting Research (Vol 1, pp 481-

Anderson, S W., & Lanen, W N (1999) Economic transition, strategy and the evolution of management accounting practices: the case of India Accounting, Organizations and Society, 24(5), 379-412 h

Andriessen, D (2004) IC valuation and measurement: classifying the state of the art

Anh, D N P (2010) Factors affecting the use of consequences of strategic management accounting practices in a transitional economy: The case of Vietnam Journal of

Appuhami, B R (2007) The impact of intellectual capital on investors' capital gains on shares: An empirical investigation of Thai banking, finance & insurance sector

Arvidsson, S (2011) Disclosure of non-financial information in the annual report Journal of Intellectual Capital, 12(2), 277-300

Ashton, D., Hopper, T., & Scapens, R W (1991) Issues in management accounting:

PREVIOUS STUDIES INVESTIGATING THE RELATIONSHIP

Study Sources/ sample Dependent variables Control variables Significant relationships

Bontis et al (2000) Malaysian firms Performance, SC & RC SC + Performance, RC + SC, HC + RC

Bollen et al (2005) 41 German pharmaceuticals companies

SC, HC and RC have at least an indirect impact on performance through intellectual property mediator

20 Russian companies having below 180 employees

HC is the most important IC component for competitive advantage

External environment is less important in determining competitiveness

Firms characterized with high levels of IC and high use of KMP are likely to outperform the firms with low overall levels of IC and KMP h

Study Sources/ sample Dependent variables Control variables Significant relationships

237 respondents from targeted SMEs in Malaysia

HC, customer capital, SC, social capital, technological capital and spiritual capital are crucial components of IC and all link to organisational performance

Combination of questionnaires and financial data

J Cohen et al (2004) 52 Greek SMEs

IC information from questionnaires of CEOs

Hard IC + Profits Functional IC + Sales per employee

ROA, asset turnover, market-to-book value

Size, Financial leverage, ROE and industry type

HCE – asset turnover, market-to-book value

SCE + ROA CEE + Market-to-book value

Market-to-book value, ROA, ROE, revenue growth, productivity

VAIC/ HCE/ CEE + ROA, ROE, market- to-book value, revenue growth, productivity

SCE + ROA, market-to-book value h

Study Sources/ sample Dependent variables Control variables Significant relationships

Appuhami (2007) Thailand (1 year: 2005) Capital gain on shares None VAIC + capital gain on shares

CEE – capital gain on shares

ROE, EPS, Annual stock return

None HCE, SCE, together + ROE, EPS, annual stock return

Economic income, ROA, market-to-book value

VAIC + Economic income, ROA CEE – Economic income

CEE + ROA, market-to-book value

ROE, ROA, revenue growth, market-to-book value

34 Chinese life insurance companies (5 years: 2006 – 2010)

Operating efficiency using dynamic slack- based measure model

Local capital source, age, size, financial leverage

HCE, SCE, CEE 2 + Operating efficiency

Source: The author’s literature review

2 CEE: Capital employed efficiency, HCE: human capital efficiency, SCE: structural capital efficiency, RCE: relational capital efficiency, VAIC: value added intellectual coefficient h

REVIEW OF PRIOR INTERNATIONAL STUDIES OF

Study Sources/ sample Dependent variables Methodology Important findings

Theme: Defining strategic management accounting

SMA is the provision and analysis of management accounting data about a business and its competitors for developing and monitoring the business strategy

SMA is the managerial use of cost information explicitly directed at the stages of the strategic management cycle

Ward (1992) UK Normative method SMA is accounting for strategic management

(1993) USA Normative method Strategic cost management

Langfield-Smith (2008) North American Literature review

A review of the origins of strategic management accounting and an assessment of the extent of adoption

Study Sources/ sample Dependent variables Methodology Important findings

Theme: Strategic management accounting practices

Mailed questionnaire and ANOVA procedure

Capital budgeting and competitor-focused techniques are the most widely used while customer-focused techniques are the least widely used

65 large-sized Croatian companies in

12 SMA techniques Questionnaire survey, ANOVA

The synergistic effect of the different strategic management accounting techniques implementation has a positive impact on cost control and reduction

Mailed questionnaire and regression model

The usage of 16 SMA techniques + organizational performance

Size, legal form, ownership and affiliation to a group

Written questionnaire, Kruskall-Wallis tests, regression model

12 SMA techniques + ownership, affiliation to a group

No correlation between SMA techniques and size, legal form

Study Sources/ sample Dependent variables Methodology Important findings

Theme: Environment, strategy choice and strategic management accounting practices

328 Italian manufacturing firms with sales higher than $25 million

Internet questionnaire survey, ANOVA, regression model

Both defender- and cost leader-type of strategy are found to be more willing to use SMA techniques addressing cost information

Ma and Tayles (2009) Meditech Group SMA practices Case study

The internal and external influences enable the adoption of SMA and the repositioning of management accountants to become more strategic

14 SMA techniques Questionnaire survey, ANOVA

There are differences in using different types of strategic management accounting techniques among sizes of industries, cost leadership and differentiation strategy, build and harvest strategy

116 Singaporean small- to medium-sized

CFO performance with mediator of perceived

Configurations of SMA technique change + CFO performance enhancement under both low h

Study Sources/ sample Dependent variables Methodology Important findings manufacturing firms environmental uncertainties and high levels of perceived environmental uncertainties

Questionnaire survey, empirical approach, cluster analysis

Internally consistent strategy and SMA system configurations are associated with higher performance

Theme: Strategic management accounting process

Dixon and Smith (1993) Normative method Four stages to SMA process

Lord (1996) Commentary method Six stages to SMA process

(1999) Normative method Three stages to SMA process

The interface between management accounting and marketing management affirm SMA’s limited impact on practice in the UK

Source: The author’s literature review h

PREVIOUS STUDIES INVESTIGATING THE RELATIONSHIP

STRATEGIC MANAGEMENT ACCOUNTING AND CORPORATE PERFORMANCE

Study Sources/ sample Dependent variables Independent/ Moderating variables

Performance Product differentiation, low price strategies, SMA practices

(+) associations between performance and a range of SMA practices, under various strategic orientations

Ma and Tayles (2009) Case study research in a UK pharmaceutical company

Performance SMA practices An increasing strategic role for management accountants in informing strategic decision-making leads to performance enhancement

Hassan et al (2011) 107 Malaysian companies

SMA usage The usage of technology in SMA can improve organizational performance Ramljak and Rogošić

The largest 400 companies in Croatia

SMA techniques The effect of the different strategic management accounting techniques implementation has a positive impact on cost control and reduction

Study Sources/ sample Dependent variables Independent/ Moderating variables

Performance Prospector/ defender business strategy, Market orientation, SMA usage, Accountant’s participation in strategic decision making

High SMA levels and greater involvement of accountants in strategy processes are more congruent with a dynamic prospector-strategy, leading higher organizational performance

486 medium and large-size businesses of the Directorate of the Kayseri Organized Industrial Region

Perceived (qualitative and quantitative) performance of businesses

Competitive strategies and use of SMA techniques (cost, competitor, customer, strategic decision and control-oriented)

Differentiation strategies (+) perceived qualitative-quantitative performance of businesses

Te competitor- oriented, customer- oriented techniques (+) qualitative performance of the businesses

Independent variable: SMA Moderator: Perceived environmental uncertainty

The level of SMA usage (+) organizational performance, via the moderator of perceived environmental uncertainty

Turner, Way, Hodari, and Witteman (2017)

Mediator: SMA usage Market orientation strategy is the key determinant of hotel SMA uasge and h

Study Sources/ sample Dependent variables Independent/ Moderating variables

Market orientation strategy Leadership strategy

Hotel size illuminate the mediating role of SMA uage to enhance financial performance

Alamri (2018) 103 listed companies in Malaysia

Organizational learning Mediator: SMA usage

SMA usage is not associated with firm performance, indicating that the mediation role of SMA usage on the relationship between organizational capabilities and firm performance is not supported

Source: The author’s literature review h

ELEMENTS OF HUMAN CAPITAL IN INTELLECTUAL

Employees Basic attributes of employees Employee profile

Employee equity Equal opportunities Employee safety Employee relationship Employee featured Employee representation Employee welfare

Employee recognition Compensation plan, bonus Loyal and retention

Duties and responsibilities Employee good attitude Employee morale

Training The act or process taken by company directly or indirectly to imparting skills to employees

Vocational development Career development Induction programme

In house training Recruitment Employee assistance program Continuing education

Any state of being trained

Education Education level possessed by any company’s members

Bachelor, Master, Ph.D Professional qualification h

Work related Knowledge Work related Competencies Work related Experience Know how

Innovation Innovation is holistic and covers the entire range of activities in business which creates value to customers and satisfactorily returns to business

Innovation appears in product and services, human resources management, procedure, organization structure and many things

Development new product Research and development Modern technology

Creative marketing strategy Add new product line

Source: Campbell and Abdul Rahman (2010) h

ELEMENTS OF STRUCTURAL CAPITAL IN INTELLECTUAL

A patent is a government-granted exclusive right that allows an inventor to exclusively make, use, and sell their invention for a specified period In contrast, copyright protects creative and artistic works, including literature, drama, music, art, and recordings, ensuring the creator's rights are upheld.

Trademark – A distinctive characteristic by which a person or things become to be known

Patent Trademark Copyright Internet domain name Design

The pattern of arrangement, material or behavioral which has been adopted by a corporation, group or team as the accepted way of solving problem

Vision Mission Code of ethic Code of conduct Code of practice Principles of operation

How organization thinks about its employees, customers, environmental and community (referring to company’s general belief not to activities)

Create value to shareholders Sustain growth

Listen to customer Protect environment and Caring society

System, procedure and technologies practiced or used by companies

Control stock Quality control Performance appraisal h

System consisting of the network of all communication channels used within organization

Software, hardware Network, intranet, server, etc

Infrastructure Development of tangible long-term assets Portfolio of properties

Source: Campbell and Abdul Rahman (2010) h

ELEMENTS OF RELATIONAL CAPITAL IN INTELLECTUAL

Favorable monetary relationship with suppliers

Relationship with shareholders, bankers and other fund suppliers

Brands By identifying and authenticating a product or services, it delivers a pledge of satisfaction and quality

Brand Sub-brand Range of product and services name

Market shares Product awards Customers Attributes to customers Customers named

Customer loyalty Customers trust Customers feedback Customer satisfaction Number of customers Customers segment Customers convenience such as shop more appealing, more facilities

The commercial process involves promoting, selling and distributing product and services into market

Supply chain Business network Development new stores across regions

Marketing and advertising Carry out market research Online selling

Catalogue Promotion activities/ strategies Liaison office

A relationship between company and individual or groups that is characterized by mutual cooperation and responsibilities in terms of business or social/ environmental objectives

Franchising Licensing Collaboration Outsourcing Suppliers External expert/ consultant Local authorities

Actions and activities would position company’s reputation into higher level

Company name Community involvement Environmental protection measures

Social responsibilities Any activity that could raise company name and favorable contract

Source: Campbell and Abdul Rahman (2010) h

DESCRIPTIONS OF SMA TECHNIQUES

Attribute costing refers to the process of evaluating the costs associated with specific features of a product or service that attract customers Key attributes that can be assessed include operational performance, warranty agreements, supply reliability, quality of finish and trim, and post-sale service (Cadez, 2006).

Life-cycle costing is a systematic approach that monitors and aggregates the costs associated with each stage of a product's value chain, starting from the initial research and development phase and extending through to customer service and support (Horngren et al., 2012).

Quality costing This technique classifies and monitors costs deriving from conformance costs and non-conformance costs

In a strategic perspective, this technique support the pursuit of quality to ensure that goods are produced and services supplied of the highest quality (Cinquini

Target costing refers to the estimated long-run cost per unit of a product or service, allowing a company to reach its desired operating income per unit at a specified target price This target cost per unit is calculated by deducting the target operating income per unit from the target price, ensuring effective pricing strategies and profitability (Horngren et al., 2012d).

An activity-based approach allocates costs to value-creating activities, beginning with raw material sources or component suppliers and extending to the final product or service delivered to the customer (Cadez, 2006).

Activity-based costing (ABC) is a method that prioritizes individual activities as the primary cost drivers This approach utilizes the costs associated with these activities to allocate expenses to various cost objects, including products and services, ensuring a more accurate representation of costs (Horngren et al., 2012b).

Benchmarking is an ongoing process that involves comparing the performance of producing goods and services, as well as executing activities, against the highest performance standards of competing companies or those with similar processes This practice helps organizations identify areas for improvement and adopt best practices to enhance their overall efficiency and effectiveness.

Analyzing competitors' positions in the industry involves evaluating trends in their sales, market share, and return on sales By comparing this data with its main competitors, a company can effectively assess its own market standing and adjust its strategies accordingly (Cinquini & Tenucci, 2010).

Competitor cost assessment involves analyzing the cost structures of rivals to estimate their unit costs, as noted by Simmonds (1981) Ward (1992) recommends utilizing indirect sources for this analysis, including physical observation, insights from common suppliers, information from ex-employees, and external reports about competitors.

Analyzing competitors' public statements, including annual and financial reports, is essential for evaluating their core competencies that provide a stable competitive advantage This quantitative and qualitative assessment helps businesses understand the strengths and strategies of their rivals, enabling them to enhance their own market positioning.

An integrated performance measurement system incorporates both financial and non-financial metrics to enhance performance insights The balanced scorecard exemplifies this approach, playing a crucial role in the strategic management cycle by utilizing four perspectives to formulate strategies and assess organizational performance (Kaplan & Norton, 2001).

Strategic costing refers to cost management that emphasizes strategic considerations, enabling managers to leverage cost data alongside strategic and marketing insights This approach aids in the development and identification of superior strategies that foster sustainable competitive advantage.

Strategic pricing involves analyzing key factors that influence pricing decisions, including the five competitive forces within an industry, competitor price reactions, demand elasticity, economies of scale, and market growth (Cadez, 2006).

Brand valuation It is financial valuation of a brand name through the assessment of a brand’s strengths such as leadership, market share, stability, internationality, trend, historical brand profitability (Cadez, 2006) h

Capital budgeting is a crucial process for planning substantial investments in long-term projects, utilizing various techniques such as net present value, internal rate of return, and discounted payback period to assess their financial viability (Noreen, Brewer, & Garrison, 2011).

“Customer profitability analysis involves calculating profit earned from a specific customer The profit calculation is based on costs and sales that can be traced to a particular customer.” (Guilding & McManus, 2002)

Lifetime customer analysis expands the timeframe for evaluating customer profitability by considering future years This approach emphasizes all expected revenue streams and associated costs related to servicing a specific customer.

The valuation of customer groups

Valuing customers or customer groups as assets involves determining their financial worth to a company This process often includes calculating the present value of expected future profit streams linked to specific customers or customer segments.

Source: Summarized by the author h

CATEGORIZATION OF THE IC MEASUREMENT METHODS

Tobin q Market-to-book value

Investor-assigned market value (IAMV TM )

Originator and year of first publication

Description Tobin q is the ratio of the stock market value of the firm divided by the replacement cost of its assets (Tobin, 1969)

Changes in Tobin q provide a proxy to measure whether or not intellectual capital performs effectively (Stewart &

The value of intellectual capital is assessed by the disparity between a firm's stock market value and its book value (Stewart, 1997) Some researchers suggest that utilizing the ratio of market value to book value provides a more effective measurement (Luthy, 1998).

According to Standfield (1998), a firm's actual market value is determined by its book value, realized intellectual capital, the erosion of intellectual capital, and its sustainable competitive advantage The disparity between book value and market value reflects the investor-assigned market value.

IAMV) may be defined as “realized IC” (Rodov

Inefficiency existing within every organizational structure prevent the firm performing the optimum h

Tobin q Market-to-book value

Investor-assigned market value (IAMV TM ) level, defined that intellectual capital erosion

Characteristics If q > 1 and/or q is greater than another company’s q, than that company has a higher intellectual capital

A greater disparity between market value and book value indicates a higher level of intellectual capital within a firm To improve the reliability of this ratio, it is beneficial to compare companies operating within the same industry.

“A firm’s market value is its tangible capital value (book value) plus its intellectual capital value, which falls short of its attainable market value by intellectual capital erosion.” (Rodov & Leliaert, 2002)

Advantages - It is easy and understandable because Tobin q has been widely used in the literature (Nazari,

- It counterbalances the effects of using different depreciation policies (Bontis, 1998)

- Market-to-book ratio has a long history financial literature (Nazari, 2010)

- It is understandable and can be quickly calculated (Nazari,

This method provides a direct link between the attainable market value and investor-assigned market value via intellectual capital erosion (Rodov & Leliaert, 2002)

Disadvantages - It is difficult to estimate the replacement costs of a firm’s assets for the

- This ratio uses market values which are affected by many factors outside the control of the company

- It is difficult to estimate intellectual capital erosion IC audit are designed to identify h

Tobin q Market-to-book value

Investor-assigned market value (IAMV TM ) denominator of this ratio (Nazari, 2010)

- Tobin q ratio can only be used to compare the company with peers in the industry with similar types of physical assets (Bontis,

1998) than just intellectual capital (Luthy, 1998)

- It may encourage the depreciation of the assets using a faster rate than what they actually wear out Thus, the book value of the assets may be reported understatedly

- Market value and book value are numbers that an investor already knows and thus, the metric provides no additional information (Gu & Lev, 2001) activities and processes that erode IC value

- The primary issue with this model is that it requires a subjective valuation in order to assign the weights to the components of intellectual capital

Source: Summarized by the author h

CATEGORIZATION OF THE INTELLECTUAL CAPITAL

UNDER RETURN ON ASSETS MODEL

Value added intellectual capital coefficient (VAIC TM )

Economic value added (EVA TM )

Originator and year of first publication

Pulic (2000) Stewart (1997) Stern, Stewart, and

This model evaluates both the size and efficiency of intellectual capital (IC) by analyzing three key components: capital employed, human capital, and structural capital The formula for Value Added Intellectual Coefficient (VAIC) is represented as VAIC = CEE + HCE + SCE, according to Pulic.

Calculate the excess return on hard assets then use this figure as a basis for determining the proportion of return attributable to intangible assets (Bhartesh &

Calculated by adjusting the firm’s disclosed profit with charges related to intangibles (Sveiby, 2005)

Characteristics CEE and HCE can be viewed as the value added by a dollar input of physical assets and human capital, respectively (Riahi-

SCE represents the proportion of total value added accounted

This approach posits that intangible assets, despite lacking physical form, have the potential to produce future cash flows that are equal to or even exceed those generated by tangible assets.

Changes in EVA provide an indication of whether a firm’s intellectual capital is productive or not (Bhartesh & Bandyopadhyay, 2005) h

Value added intellectual capital coefficient (VAIC TM )

Economic value added (EVA TM ) for by structural capital (Riahi-Belkaoui, 2003) from physical assets (Stewart, 1997)

Advantages - Easy to calculate, standardized and consistent basis of measurement (Firer &

- Data used in calculation of VAIC are usually audited by professional public accountants (Firer &

- Easy to perform because all of information is readily available in annual reports (Bhartesh &

- Unlike some other performance indicators such as EPS or EBITDA, EVA gauges both operating and financing activities (Nazari, 2010)

- EVA ties financial calculation and risk with investment indicators (Nazari,

Disadvantages The VAIC model could be improved further by the addition of more intellectual capital constructs (Nazari,

- It may be inaccurate due to its dependence on historical data (Bhartesh &

- It may have limited relevance to the value of a firm’s IC in the future (Bhartesh &

- EVA might outperform some traditional financial performance in measuring wealth (Andriessen, 2004)

- It does not separate wealth creation into tangible and intangible sources (Andriessen,

Source: Summarized by the author h

CATEGORIZATION OF THE IC MEASUREMENT METHODS

Intellectual asset valuation (IAV) Total value creation (TVC TM ) Inclusive valuation methodology

Originator and year of first publication

Sullivan (2000) Andersen and McLean (2000) M'Pherson and Pike (2001)

Description Methodology for assessing the value of intellectual property IAV consists of three dimensions: context, a non- accounting view of the firm, and IC activities (Sullivan, 2000)

A project initiated by the Canadian Institute of Chartered Accountants

TVC TM utilizes a model to assess value creation by discounting the future potential of value streams generated from the firm's key activities (Andersen & McLean, 2000).

IVM TM can be summarized in the following formula:

CVA 3 = MVA combined with IVA (M'Pherson & Pike, 2001)

3 CVA: combined value added, MVA: monetary value added, IVA: Intangible value added h

Intellectual asset valuation (IAV) Total value creation (TVC TM ) Inclusive valuation methodology

Characteristics - The context of IC is the long-term strategy and vision and the roles that have been allocated to IC (Sullivan,

- A non-accounting view of the firm is about information that is essential for knowledge companies in transforming innovations into value (Sullivan,

- IC activities involve activities, procedures, software tools and policies that are utilized to convert ideas into value for the firm (Sullivan, 2000)

TVC TM uses discounted projected cash-slows to re-assess how events affect planned activities (Andersen &

The formula's components will be represented in a three-dimensional diagram, encompassing intrinsic value, which reflects internal management and operational effectiveness; instrumental value, indicating delivery effectiveness; and extrinsic value, showcasing the impact and recognition in areas like stakeholder relations and brand influence (M'Pherson & Pike, 2001).

Advantages IAV support to know what activities should be managed to extract value from IC activities, that is more important than knowing the type of

As opposed to the traditional accounting system, that measures value realization by past transactions,

A multidimensional valuation system that tries to link the company value,

IC, and monetary measurement in an h

Intellectual asset valuation (IAV) Total value creation (TVC TM ) Inclusive valuation methodology

(IMV TM ) value that should be extracted (Sullivan, 2000)

TVC TM measures the value that has been created (Nazari, 2010) inclusive business value system (Nazari, 2010)

Despite Sullivan (2000) proposing that a firm's value includes its tangible assets and the net present value of earnings from both intellectual and generic structural capital, Andriessen (2004) points out that the methodology for calculating these various types of earnings remains unclear.

- TVC TM is an ongoing research project that has not yet been examined and discussed extensively in the intellectual capital literature (Nazari, 2010)

- There is a high level of uncertainty involved in determining the cash flows of future events (Nazari, 2010)

IVM TM is fairly complex and requires computer programs to calculate the value of intangible assets (Andriessen, 2004)

Source: Summarized by the author h

CATEGORIZATION OF THE INTELLECTUAL CAPITAL

Originator and year of first publication

Sveiby (1989) emphasizes that management should choose indicators aligned with the firm's strategic objectives to assess four key aspects of value creation from intangible assets: external structure, internal structure, and competence These aspects are measured through four primary dimensions: growth, innovation, efficiency, and stability.

The balanced scorecard is an essential tool for translating an organization's mission, objectives, and strategies into measurable performance indicators It encompasses various perspectives, including financial, customer, internal processes, employee engagement, and community impact, allowing leaders to pinpoint areas of excellence and identify shortcomings According to Kaplan and Norton (2001), this framework effectively links both tangible and intangible assets, illustrating how their integration can generate value and enhance overall performance.

IC is measured through the analysis of up to 164 metric measures (91 intellectually based and 73 traditional metrics) that cover five components: (1) h

Originator and year of first publication

Description of measure financial; (2) customers; (3) process; (4) renewal and development and (5) human (Bhartesh & Bandyopadhyay, 2005)

IC index TM Roos, Edvinsson, et al (1997)

Consolidates all individual indicators representing intellectual properties and components into a single index Changes in index are then related to changes in the firm’s market valuation (Levy, 2009)

According to Lev (2001), intellectual properties, including trademarks, patents, and copyrights, are considered intellectual assets that receive legal protection Lev categorizes intangible assets into three main types: innovation-related intangibles, human resource intangibles, and organizational intangibles He presents a matrix of non-financial indicators organized into three development phases: Discovery, Implementation, and Commercialization.

Source: Summarized by the author h

INDICATORS FOR REFLECTIVE MEASUREMENT OF SMA

Indicators for reflective measurement of SMA constructs

To what extent does your organization use the following techniques? Scales range from

1 (not at all) to 5 (to a great extent)

(Explain: The costing of a product or service’s attributes that appeal to customers.)

The cost appraisal of a product or service is determined by analyzing the various stages of its life cycle, which include design, introduction, growth, maturity, and decline This analysis is essential for developing effective business strategies tailored to each phase of the product or service's life cycle.

Quality costs are categorized into four main types: prevention costs, appraisal costs, internal failure costs, and external failure costs The purpose of cost of quality reports is to guide management in focusing on and prioritizing quality issues effectively.

The target cost per unit is calculated by deducting the target operating profit per unit from the target price This approach is utilized to establish the desired cost of a product or service during the research and development phase, rather than attempting to cut costs during manufacturing.

(Explain: An activity-based approach where costs are allocated to activities required to design, procure, produce, market, distribute and service a product or service.)

(Explain: This technique uses the costs of individual activities as the basis of assigning costs to other cost objects to allocate indirect cost in more accuracy.)

(Explain: The process of searching, comparing, applying of an ideal standard to internal processes to achieve higher competitive advantages.)

Analyzing competitor positions in the industry involves evaluating trends in sales, market share, volume, unit costs, and return on sales by gathering data from external reports This information serves as a foundation for assessing a competitor's market strategy effectively.

(Explain: This technique is to regularly analyse competitors’ cost structures.)

(Explain: The numeric analysis of a competitor’s published statements as a part of an assessment of a competitor’s key resources of competitive advantage.)

(Explain: A measurement system focuses typically on acquiring performance knowledge based on customer requirements, the capability to adapt with the h competitors’ changes and may encompass non-financial measures.)

(Explain: The usage of cost database with strategic and marketing information to develop and identify superior strategies that will bring a sustainable competitive advantage.)

(Explain: The analysis of strategic elements in the pricing decision process.)

(Explain: A brand is valuated in financial terms through the assessment of brand strength factors.)

(Explain: This technique analyses the strategic benefits of long-term assets and projects.)

(Explain: This involves calculating profit earned from a specific customer.)

(Explain: The practice focuses on all forecasted revenue streams and costs involved in servicing a particular customer.)

The valuation of customer group:

(Explain: The technique refers to the calculation of the value of customers list to the company.)

Source: Modified from Cravens and Guilding (2001) and Guilding and McManus (2002) h

SURVEY FORM IN ENGLISH

PART A: DEMOGRAPHIC DETAILS OF THE INFORMANTS

1 Is your company publicly listed in the Vietnamese Stock Exchange?

Yes, please provide Stock Code  Continue question 2

2 Please provide your company name:

3 Do you use information obtained from the finance or accounting department and interact with finance or accounting department?

4 What is your current highest position in your company? (Please tick one box only)

Top manager (e.g CEO, CFO, managing director, member of the BOM)

Mid-level manager (e.g Head or vice-head of departments)

 Continue question 5 Non-management employee

5 Your title/ position in your company is:

6 What is the number of years you have been working in your current highest position?

7 What is the number of years you have been working for your company?

8 What is the area you are in-charge of? (Please tick one or many boxes as applied)

Research and Development Information Technology

Risk and compliance management Legal

9 With what accounting/ finance functions do you interact with the most? (Please tick one box only)

10 Does your organization analyse of management accounting data about a business and your competitors and your customers for use in developing and monitoring the business strategy?

Over the past three years, evaluate your company's structural capital performance compared to major competitors Structural capital encompasses the hardware, software, databases, organizational structure, patents, trademarks, and all resources utilized by employees to enhance business processes Rate your assessment on a scale from 1 (extremely poor) to 7 (excellent).

PART B: STRATEGIC MANAGEMENT ACCOUNTING PRACTICES

Please select a number that reflects your opinion on the strategic management accounting technique in question, where 1 represents the lowest usage and 5 signifies the highest You may also choose any number in between to indicate your level of agreement There are no right or wrong answers; we simply seek a number that accurately represents your perceptions regarding the discussed issues.

To what extent does your organization use the following techniques? Scales range from 1 (not ay all) to 5 (to a great extent) (Circle number corresponding to your response)

Does your organization implement the managerial technique of:

(Explain: The costing of a product or service’s attributes that appeal to customers.)

The evaluation of costs is determined by the various stages of a product or service's life cycle, which includes design, introduction, growth, maturity, and decline This assessment is crucial for formulating effective business strategies tailored to each phase of the product or service's development.

Quality costs are divided into four main categories: prevention costs, appraisal costs, internal failure costs, and external failure costs These classifications help organizations identify and address quality issues effectively Cost of quality reports are generated to guide management in prioritizing quality problems, ensuring a focus on improving overall performance and reducing inefficiencies.

The target cost unit is calculated by deducting the target operating profit per unit from the target price This approach focuses on establishing the desired cost for a product or service during the research and development phase, rather than attempting to cut costs during manufacturing.

Does your organization implement the managerial technique of:

(Explain: An activity-based approach where costs are allocated to activities required to design, procure, produce, market, distribute and service a product or service.)

(Explain: This technique uses the costs of individual activities as the basis of assigning costs to other cost objects to allocate indirect cost in more accuracy.)

(Explain: The process of searching, comparing, applying of an ideal standard to internal processes to achieve higher competitive advantages.)

Analyzing competitor positions within the industry involves assessing trends in sales, market share, volume, unit costs, and return on sales by gathering data from external reports This information serves as a foundation for evaluating a competitor's market strategy.

(Explain: This technique is to regularly analyse competitors’ cost structures.)

Does your organization implement the managerial technique of:

(Explain: The numeric analysis of a competitor’s published statements as a part of an assessment of a competitor’s key resources of competitive advantage.)

(Explain: A measurement system focuses typically on acquiring performance knowledge based on customer requirements, the capability to adapt with the competitors’ changes and may encompass non-financial measures.)

(Explain: The usage of cost database with strategic and marketing information to develop and identify superior strategies that will bring a sustainable competitive advantage.)

(Explain: The analysis of strategic elements in the pricing decision process.)

(Explain: A brand is valuated in financial terms through the assessment of brand strength factors.)

(Explain: This technique analyses the strategic benefits of long-term assets and projects.)

Does your organization implement the managerial technique of:

(Explain: This involves calculating profit earned from a specific customer.)

(Explain: The practice focuses on all forecasted revenue streams and costs involved in servicing a particular customer.)

The valuation of customer group

(Explain: The technique refers to the calculation of the value of customers list to the company.)

1 Please provide your contact details (they will be treated confidentially)

2 Would you like to receive a summary of the findings by email?

Yes, please provide your email:

3 Do you have any recommendation to these survey contents? h

SURVEY FORM IN VIETNAMESE

PHẦN A: THÔNG TIN CHUNG VỀ ĐỐI TƯỢNG KHẢO SÁT

1 Công ty Ông/ Bà có niêm yết trên sàn giao dịch chứng khoán tại Việt Nam không?

Không  Kết thúc bảng câu hỏi

Có, xin cung cấp mã chứng khoán  Tiếp tục câu hỏi số 2

2 Ông/ Bà vui lòng cho biết tên công ty đang làm việc:

3 Ông/ Bà có sử dụng thông tin từ bộ phận kế toán, tài chính và có tương tác công việc với bộ phận kế toán, tài chính hay không?

Có  Tiếp tục câu hỏi số 4

Không  Kết thúc bảng câu hỏi

4 Vị trí cao nhất của Ông/ Bà trong công ty là gì? (Ch ỉ chọn 1 ô)

Nhà quản trị cấp cao (ví dụ: CEO, CFO, giám đốc điều hành, thành viên hội đồng quản trị)  Tiếp tục câu hỏi số 5

Nhà quản trị cấp trung (ví dụ: Trưởng, Phó trưởng các bộ phận, phòng, ban)

 Tiếp tục câu hỏi số 5 Nhân viên không tham gia quản lý

 Kết thúc bảng câu hỏi

5 Vui lòng cho biết chức danh của Ông/ Bà trong công ty:

6 Ông/ Bà đã đảm nhiệm vị trí cao nhất này được bao nhiêu năm?

7 Ông/ Bà đã làm việc tại công ty hiện nay được bao nhiêu năm?

8 Ông/ Bà phụ trách mảng nào trong công ty? (Có th ể chọn 1 hoặc nhiều ô)

Kế toán/ Tài chính Tiếp thị h

Nghiên cứu và phát triển Công nghệ thông tin

Quản lý rủi ro và tuân thủ Pháp lý

Khác: (Xin cho biết chi tiết):

9 Chức năng tài chính/ kế toán nào Ông/ Bà thường xuyên làm việc/ giao tiếp nhiều nhất?

Lập báo cáo tài chính Lập kế hoạch/ dự toán

Quản trị chi phí Kiểm soát nội bộ

Quản lý đầu tư Quản lý nguồn vốn

Thuế Kiểm soát giá cả

Khác: (Xin cho biết chi tiết):

Công ty Ông/Bà có thực hiện việc phân tích thông tin kế toán quản trị liên quan đến tình hình kinh doanh, đối thủ cạnh tranh và khách hàng nhằm hỗ trợ cho việc xây dựng và giám sát thực thi chiến lược kinh doanh hay không?

Trong ba năm qua, xin Ông/Bà đánh giá mức độ vốn cấu trúc tại công ty của mình so với các đối thủ cạnh tranh Vốn cấu trúc bao gồm phần cứng, phần mềm, cơ sở dữ liệu, cấu trúc tổ chức, bản quyền và các yếu tố khác mà nhân viên sử dụng để tổ chức quy trình và hoạt động kinh doanh Vui lòng chọn một con số phù hợp từ 1 (kém hơn rất nhiều) đến 7 (tuyệt vời).

PHẦN B: THÔNG TIN VẬN DỤNG KẾ TOÁN QUẢN TRỊ CHIẾN LƯỢC

Hãy khoanh tròn vào con số tương ứng với sự lựa chọn của Ông/Bà Số “1” biểu thị rằng Ông/Bà cho rằng mức độ sử dụng kỹ thuật đó là thấp nhất, trong khi số “7” cho thấy mức độ sử dụng là cao nhất.

Bà cho rằng kỹ thuật kế toán quản trị chiến lược được sử dụng nhiều nhất trong công ty Ông/Bà có thể chọn bất kỳ số nào trong khoảng giữa để thể hiện mức độ đồng ý của mình, vì không có lựa chọn nào là đúng hay sai Nhà nghiên cứu chỉ muốn tìm hiểu nhận xét của Ông/Bà về việc áp dụng các kỹ thuật này tại nơi làm việc.

Tổ chức của Ông/ Bà có mức độ vận dụng các kỹ thuật sau đây như thế nào:

Chi phí theo thuộc tính sản phẩm

(Giải thích: Phân tích chi phí liên quan đến thuộc tính sản phẩm/ dịch vụ thu hút khách hàng.)

Chi phí theo chu kỳ sống

Kỹ thuật xác định chi phí chu kỳ sống của sản phẩm bao gồm các giai đoạn từ nghiên cứu và thiết kế đến tăng trưởng, bão hòa và suy thoái Phân tích này giúp xác định giá bán và xây dựng chiến lược kinh doanh phù hợp cho từng giai đoạn phát triển của sản phẩm.

Chi phí chất lượng được phân thành bốn nhóm chính: chi phí kiểm tra, chi phí phòng ngừa, chi phí thiệt hại phát sinh bên trong doanh nghiệp và chi phí thiệt hại phát sinh bên ngoài doanh nghiệp Báo cáo chi phí chất lượng đóng vai trò quan trọng trong việc đánh giá hiệu quả của quá trình quản lý chất lượng tại đơn vị.

Chi phí mục tiêu được xác định bằng cách lấy giá bán mục tiêu của sản phẩm trừ đi lợi nhuận mong muốn Việc xây dựng chi phí mục tiêu nhằm thiết kế sản phẩm sao cho phù hợp với chi phí do thị trường quy định, ngay từ giai đoạn nghiên cứu và phát triển, thay vì chỉ tập trung vào việc giảm chi phí trong từng giai đoạn sản xuất.

Chi phí chuỗi giá trị

Phân tích chi phí chuỗi giá trị là quá trình xác định và phân tích các chi phí liên quan đến từng hoạt động trong chuỗi giá trị, từ thiết kế, sản xuất đến phân phối và dịch vụ sau bán hàng Mục tiêu của phân tích này là giúp doanh nghiệp cải tiến liên tục các hoạt động nhằm tạo ra giá trị gia tăng cho khách hàng và tối ưu hóa lợi nhuận cho doanh nghiệp.

Tổ chức của Ông/ Bà có mức độ vận dụng các kỹ thuật sau đây như thế nào:

Chi phí theo hoạt động

Kế toán chi phí theo hoạt động là một mô hình giúp tập hợp chi phí từ các nguồn lực vào các hoạt động cụ thể Mô hình này phân bổ chi phí từ các hoạt động đến từng đối tượng chịu chi phí dựa trên mức độ sử dụng hoạt động của các đối tượng đó, nhằm tăng cường độ chính xác trong việc phân bổ chi phí gián tiếp.

(Giải thích: Đây là quá trình tìm hiểu, so sánh và áp dụng những kinh nghiệm thực tiễn tốt hơn nhằm đạt khả năng cạnh tranh cao hơn.)

Giám sát vị thế của đối thủ cạnh tranh

Giám sát vị thế của đối thủ cạnh tranh trong ngành là quá trình theo dõi thường xuyên các xu hướng doanh thu, thị phần và tỷ suất lợi nhuận trên doanh thu thông qua báo cáo thường niên và thông tin công khai của họ.

Phân tích chi phí đối thủ cạnh tranh

Phân tích cấu trúc chi phí của đối thủ cạnh tranh giúp doanh nghiệp đánh giá tính hợp lý trong cấu trúc chi phí của chính mình Việc này không chỉ cung cấp cái nhìn sâu sắc về chiến lược giá cả mà còn giúp tối ưu hóa quy trình sản xuất và phân phối.

10 Đánh giá thành quả của đối thủ cạnh tranh

Phân tích định lượng dựa trên các báo cáo công khai của đối thủ cạnh tranh giúp đánh giá rõ ràng nguồn lực chính tạo ra lợi thế cạnh tranh của họ Việc này không chỉ cung cấp cái nhìn sâu sắc về chiến lược kinh doanh mà còn giúp xác định điểm mạnh và điểm yếu của đối thủ trong ngành.

11 Đo lường thành quả tích hợp

Hệ thống đo lường này được sử dụng để đánh giá hiệu quả hoạt động dựa trên yêu cầu của khách hàng và khả năng thích ứng với sự thay đổi từ đối thủ cạnh tranh Thông thường, hệ thống này còn tích hợp các chỉ tiêu phi tài chính.

Tổ chức của Ông/ Bà có mức độ vận dụng các kỹ thuật sau đây như thế nào:

Sử dụng cơ sở dữ liệu chi phí kết hợp với thông tin chiến lược và tiếp thị giúp doanh nghiệp phát triển và nhận diện chiến lược ưu việt, từ đó tạo ra lợi thế cạnh tranh bền vững.

(Giải thích: Phân tích các nhân tố chiến lược trong quy trình ra quyết định giá bán.)

Một nhãn hiệu sản phẩm hoặc dịch vụ được định giá dựa trên các khía cạnh tài chính, thông qua việc phân tích các yếu tố củng cố giá trị của thương hiệu đó.

(Giải thích: Kỹ thuật này được sử dụng để phân tích các lợi ích chiến lược của các tài sản/ dự án dài hạn của công ty.)

Phân tích khả năng sinh lợi của khách hàng

(Giải thích: Kỹ thuật này liên quan đến việc tính toán lợi nhuận đạt được từ một khách hàng cụ thể.)

Phân tích chu kỳ mua hàng của khách hàng

(Giải thích: Kỹ thuật này tập trung vào việc ước tính các khoản doanh thu và chi phí phục vụ cho một khách hàng cụ thể.)

18 Định giá danh mục khách hàng

(Giải thích: Kỹ thuật này liên quan đến việc định giá danh mục khách hàng của công ty.)

1 Ông/ Bà vui lòng cho biết thông tin liên lạc: (thông tin được hoàn toàn bảo mật)

Họ và tên: _ Địa chỉ gửi thư: _ Điện thoại liên lạc:

2 Ông/ Bà có muốn nhận tóm tắt kết quả nghiên cứu từ khảo sát này qua email không?

Có, Ông/ Bà vui lòng cung cấp địa chỉ email:

3 Ông/ Bà có đề nghị gì khác cho các nội dung khảo sát này không? h

CRONBACH ALPHA AND EFA RESULTS OF THE

OF THE INDICATORS OF SMA CONSTRUCTS

Observed variables Corrected item - Total

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization a Rotation converged in 7 iterations

Source: Calculated by the author in SPSS 24.0 h

APPENDIX 16: EVALUATION OF INDICATORS AND

Construct and items Outer loadings t value p value

Strategic cost management (SCM) (Composite reliability = 0.882; AVE = 0.556)

Competitor accounting (COM) (Composite reliability = 0.895; AVE = 0.630)

Strategic accounting (STR) (Composite reliability = 0.860; AVE = 0.606)

Customer accounting (CUS) (Composite reliability = 0.873; AVE = 0.697)

Strategic management accounting (SMA) (Composite reliability = 0.950; AVE = 0.516)

Source: Calculated by the author in SmartPLS 3.1 h

CROSS LOADINGS OF REFLECTIVE MEASUREMENT

Indicators and constructs COM CUS SCM STR SMA

Source: Calculated by the author in SmartPLS 3.1 h

CORRELATIONS, SQUARE ROOT OF AVE AND HTMT

AGE COM CUS GRW HCE LEV RCE SCE SCM SIZE SMA STR ATO INVEFF ROE TOBINQ

1 st value = Correlation between variables (off-diagonal); 2 nd value = HTMT ratio (italic off-diagonal); Square root of AVE (bold diagonal)

Source: Calculated by the author in SmartPLS 3.1 h

THE ESTIMATION OF SGA EXPENDITURES AMORTIZATION

Method: Panel Two-Stage Least Squares

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1

Variable Coefficient Std Error t-Statistic Prob

Cross-section fixed (dummy variables)

S.E of regression 0.159107 Sum squared resid 9.138719

Prob(F-statistic) 0.000000 Second-Stage SSR 7.993050

Method: Panel Two-Stage Least Squares

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1

Variable Coefficient Std Error t-Statistic Prob

Cross-section fixed (dummy variables)

S.E of regression 0.290907 Sum squared resid 10.23985

Prob(F-statistic) 0.000000 Second-Stage SSR 2.346188

Method: Panel Two-Stage Least Squares

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1 LOGSGAT_2 TAT_1 ROAT_1

Variable Coefficient Std Error t-Statistic Prob

C 1.457882 0.851033 1.713073 0.0901 LOGPPET_1 0.168584 0.040437 4.169093 0.0001 LOGRDCT_1 -0.044772 0.028285 -1.582892 0.1169 LOGSGAT 1.087676 0.204778 5.311489 0.0000 LOGSGAT_1 0.404669 0.158978 2.545438 0.0126 LOGSGAT_2 -0.049071 0.180453 -0.271933 0.7863

Cross-section fixed (dummy variables)

R-squared 0.964606 Mean dependent var 5.019415 Adjusted R-squared 0.954105 S.D dependent var 0.617914 S.E of regression 0.132377 Sum squared resid 1.594659 F-statistic 88.59192 Durbin-Watson stat 2.272148 Prob(F-statistic) 0.000000 Second-Stage SSR 1.651226 Instrument rank 29 Prob(J-statistic) 0.035552

Industry: Logistics and transportation equipment

Method: Panel Two-Stage Least Squares

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1 LOGSGAT_2 TAT_1 ROAT_1

Variable Coefficient Std Error t-Statistic Prob

C 0.422972 0.682968 0.619315 0.5371 LOGPPET_1 0.079974 0.045636 1.752443 0.0827 LOGRDCT_1 0.099931 0.038298 2.609319 0.0104 LOGSGAT 0.454934 0.284434 2.599437 0.0104 LOGSGAT_1 0.427458 0.186350 2.293842 0.0238 LOGSGAT_2 -0.062421 0.128792 -0.484666 0.6289

Cross-section fixed (dummy variables)

R-squared 0.953242 Mean dependent var 4.925737 Adjusted R-squared 0.940077 S.D dependent var 0.643143 S.E of regression 0.157437 Sum squared resid 2.552987 F-statistic 65.93158 Durbin-Watson stat 1.702316 Prob(F-statistic) 0.000000 Second-Stage SSR 2.790926 Instrument rank 31 Prob(J-statistic) 0.727227 h

Industry: Real estate and construction

Method: Panel Two-Stage EGLS

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1 LOGSGAT_2 TAT_1 ROAT_1

Variable Coefficient Std Error t-Statistic Prob

C 1.255169 0.569376 2.204466 0.0287 LOGPPET_1 0.176784 0.042038 4.205290 0.0000 LOGRDCT_1 0.086690 0.032220 2.690573 0.0078 LOGSGAT 0.415312 0.203616 2.039678 0.0428 LOGSGAT_1 0.205181 0.095705 2.143894 0.0333 LOGSGAT_2 -0.073347 0.079363 -0.924192 0.3566

Cross-section fixed (dummy variables)

R-squared 0.938719 Mean dependent var 6.872057 Adjusted R-squared 0.926921 S.D dependent var 3.355704 S.E of regression 0.200712 Sum squared resid 7.533359 F-statistic 64.89805 Durbin-Watson stat 1.678936 Prob(F-statistic) 0.000000 Second-Stage SSR 9.110223 Instrument rank 38 Prob(J-statistic) 0.010910

Method: Panel Two-Stage EGLS

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1 LOGSGAT_2 TAT_1 ROAT_1

Variable Coefficient Std Error t-Statistic Prob

C 2.676132 0.388880 6.881632 0.0000 LOGPPET_1 -0.015013 0.038509 -0.389856 0.6979 LOGRDCT_1 0.036565 0.050795 0.719861 0.4741 LOGSGAT 1.273422 0.420491 3.028414 0.0035 LOGSGAT_1 0.664404 0.401478 1.994895 0.0493 LOGSGAT_2 0.134877 0.046861 2.878219 0.0054

Cross-section fixed (dummy variables)

R-squared 0.951057 Mean dependent var 9.932643 Adjusted R-squared 0.939369 S.D dependent var 4.715886 S.E of regression 0.207072 Sum squared resid 2.872872 F-statistic 107.4442 Durbin-Watson stat 2.007317 Prob(F-statistic) 0.000000 Second-Stage SSR 2.201882 Instrument rank 18 Prob(J-statistic) 0.988868 h

Method: Panel Two-Stage EGLS

Linear estimation after one-step weighting matrix

Instrument specification: C LOGPPET_1 LOGRDCT_1 LOGSGAT_1

Variable Coefficient Std Error t-Statistic Prob

Cross-section fixed (dummy variables)

S.E of regression 0.260489 Sum squared resid 3.732006

Prob(F-statistic) 0.000000 Second-Stage SSR 0.408392

Source: Calculated by the author in Eviews 9.0 h

THE ESTIMATION OF ORGANIZATIONAL CAPITAL

Panel A: Capitalization of SGA expenditures

Model: Log(Ei,t)= γ0 + γ1Log(PPEi,t-1) + γ2Log(RDCi,t-1)+ δ1Log(SGAi,t)+ δ2Log(SGAi,t-1) + δ3Log(SGAi,t-2) + εi,t

Note: Significant at: *10, **5 and ***1 percent levels

Source: Calculated by the author in Eviews 9.0 h

First year Second year Third year ω1 ω2 ω3

Source: Calculated by the author h

THE ESTIMATION OF INVESTMENT EFFICIENCY

Variable Coefficient Std Error t-Statistic Prob

S.E of regression 0.432318 Akaike info criterion 1.162329

Sum squared resid 227.2687 Schwarz criterion 1.170711

Log likelihood -705.8583 Hannan-Quinn criter 1.165484

Variable Coefficient Std Error t-Statistic Prob

Effects Specification Cross-section fixed (dummy variables)

S.E of regression 0.420418 Akaike info criterion 1.237112

Sum squared resid 184.3514 Schwarz criterion 1.970584

Log likelihood -578.4011 Hannan-Quinn criter 1.513202

Test cross-section fixed effects

Variable Coefficient Std Error t-Statistic Prob

Cross-section fixed (dummy variables)

R-squared 0.242293 Mean dependent var 0.139380 Adjusted R-squared 0.110772 S.D dependent var 0.439131 S.E of regression 0.414096 Akaike info criterion 1.210892 Sum squared resid 177.8201 Schwarz criterion 1.969512 Log likelihood -556.4335 Hannan-Quinn criter 1.496449 F-statistic 1.842234 Durbin-Watson stat 2.141141 Prob(F-statistic) 0.000000

Test cross-section and period fixed effects

Cross-section F 1.467500 (173,1037) 0.0003 Cross-section Chi-square 266.730103 173 0.0000

Cross-Section/Period F 1.611014 (179,1037) 0.0000 Cross-Section/Period Chi-square 298.849505 179 0.0000

Method: Panel EGLS (Cross-section random effects)

Swamy and Arora estimator of component variances

Variable Coefficient Std Error t-Statistic Prob

R-squared 0.028644 Mean dependent var 0.131106 Adjusted R-squared 0.027845 S.D dependent var 0.433830 S.E of regression 0.427747 Sum squared resid 222.4889 F-statistic 35.85830 Durbin-Watson stat 1.792053 Prob(F-statistic) 0.000000

R-squared 0.031511 Mean dependent var 0.139380 Sum squared resid 227.2866 Durbin-Watson stat 1.754225 h

Correlated Random Effects - Hausman Test

Test cross-section random effects

Method: Panel EGLS (Two-way random effects)

Swamy and Arora estimator of component variances

Variable Coefficient Std Error t-Statistic Prob

S.E of regression 0.422190 Sum squared resid 216.7449

Sum squared resid 227.3771 Durbin-Watson stat 1.745461

Correlated Random Effects - Hausman Test

Test cross-section and period random effects

Cross-section and period random 61.460310 1 0.0000

* Period test variance is invalid Hausman statistic set to zero

Cross-section random effects test comparisons:

Variable Fixed Random Var(Diff.) Prob

Source: Calculated by the author in Eviews 9.0 h

DESCRIPTIVE STATISTICS AND CORRELATION

ORGCE RDCE SCE HCE RCE SMA SIZE AGE GRW LEV ATO INVEFF ROE TOBINQ SCM COM STR CUS ORGCE 1.000

ORGCE RDCE SCE HCE RCE SMA SIZE AGE GRW LEV ATO INVEFF ROE TOBINQ SCM COM STR CUS INVEFF 0.094 0.392 0.477 0.421 0.671 0.776 -0.094 -0.032 0.199 0.088 0.409 1.000

Mean 0.121 0.236 0.358 3.868 0.332 52.10 5.670 1.104 2.538 2.313 1.510 -0.141 0.211 1.559 17.568 14.511 12.517 7.505 Median 0.099 0.198 0.341 3.628 0.331 51.000 5.678 1.096 0.159 1.538 1.221 -0.101 0.195 0.871 17.000 14.000 11.000 7.000 Maximum 0.437 0.879 0.887 22.919 0.700 76.000 8.084 1.623 65.318 9.649 5.298 -0.000 0.470 6.481 25.000 25.000 20.000 13.000 Minimum 0.006 0.003 0.036 1.005 0.045 26.000 3.384 0.698 -0.946 0.024 0.087 -1.460 -0.186 0.013 10.000 6.000 6.000 3.000 Std Dev 0.081 0.174 0.159 2.361 0.130 11.465 0.734 0.120 8.470 2.262 1.136 0.187 0.136 1.518 3.122 3.689 3.672 1.987 Skewness 1.180 1.121 0.563 4.074 0.296 0.004 0.055 0.542 4.940 1.462 1.387 -4.109 -0.003 1.213 -0.044 1.180 1.121 0.563 Kurtosis 4.497 3.936 3.306 29.383 2.958 2.183 3.359 5.062 29.993 4.675 4.752 28.247 2.703 3.862 2.393 4.497 3.936 3.306

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed)

Source: Calculated by the author in Eviews 9.0 & SmartPLS 3.1 h

COLLINEARITY STATISTICS – INNER VIF VALUES

Asset turnover Investment efficiency Return on equity Tobin q IC components

ATO SCE SMA INVEFF SCE SMA ROE SCE SMA TOBINQ SCE SMA HCE SCE RCE

Source: Calculated by the author in SmartPLS 3.1 h

PLS ALGORITHM RESULT WITH THE ASSET TURNOVER

Source: Calculated by the author in SmartPLS 3.1

Constructs: Adjusted R 2 (shown in the circles) h

PLS results with the Asset turnover variable

Non-mediated model Mediated model Non-mediated model

Effect on strategic management accounting practices 0.714

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed), t value (shown in brackets)

Source: Calculated by the author in SmartPLS 3.1 h

PLS ALGORITHM RESULT WITH THE INVESTMENT

Source: Calculated by the author in SmartPLS 3.1

Constructs: Adjusted R 2 (shown in the circles)

PLS results with the Investment efficiency variable

Non-mediated model Mediated model Non-mediated model

Effect on strategic management accounting practices 0.711

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed), t value (shown in brackets)

Source: Calculated by the author in SmartPLS 3.1 h

PLS ALGORITHM RESULT WITH THE RETURN ON EQUITY

Source: Calculated by the author in SmartPLS 3.1

Constructs: Adjusted R 2 (shown in the circles)

PLS results with the Return on equity variable

Non-mediated model Mediated model Non-mediated model

Effect on strategic management accounting practices 0.713

Effect on return on equity 0.683 0.870

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed), t value (shown in brackets)

Source: Calculated by the author in SmartPLS 3.1 h

PLS ALGORITHM RESULT WITH THE TOBIN Q VARIABLE

Source: Calculated by the author in SmartPLS 3.1

Constructs: Adjusted R 2 (shown in the circles)

PLS results with the Tobin q variable

Non-mediated model Mediated model Non-mediated model

Effect on strategic management accounting practices 0.718

Note: Significant at: *10, **5 and ***1 percent levels (two-tailed), t value (shown in brackets)

Source: Calculated by the author in SmartPLS 3.1 h

REGRESSION RESULTS BETWEEN IC COMPONENTS AND

Notes: ⁎⁎⁎ p < 0.01; ⁎⁎ p < 0.05; ⁎ p < 0.1 (two-tailed); Constructs: Adjusted R 2 (shown in the circles)

Source: Calculated by the author in SmartPLS 3.1

THE INTELLECTUAL CAPITAL BENCHMARKING SYSTEM

Source: Suggested by Viedma-Marti (2001) h

LIST OF PARTICIPATING FIRMS

(VND million) HCE SCE RCE SMA level

1 Becamex Asphalt & Concrete JSC ACC Manufacturing sector 322,039 2.34 0.25 0.25 49

2 American Vietnamese Biotech INC AMV Manufacturing sector 20,421 3.70 0.42 0.25 44

3 Additives & Petroleum Products JSC APP Manufacturing sector 64,828 4.07 0.51 0.34 55

4 VICEM Packaging But Son JSC BBS Manufacturing sector 261,320 3.85 0.43 0.33 44

5 Bim Son Cement JSC BCC Manufacturing sector 4,741,328 2.28 0.22 0.39 53

6 Binh Minh Plastics JSC BMP Manufacturing sector 2,891,075 3.63 0.33 0.40 70

7 Vicem Packaging Bim Son JSC BPC Manufacturing sector 213,958 2.41 0.23 0.21 41

8 Can Tho Mineral & Cement JSC CCM Manufacturing sector 309,785 5.33 0.60 0.36 62

9 Hai Duong Pump Manufacturing JSC CTB Manufacturing sector 515,694 2.59 0.38 0.24 43

10 Chang Yih Ceramic JSC CYC Manufacturing sector 305,353 3.22 0.30 0.28 42

11 Dong Nai Roofsheet JSC DCT Manufacturing sector 901,460 3.56 0.14 0.38 65

12 Dong Hai JSC of Bentre DHC Manufacturing sector 629,632 3.59 0.27 0.37 62

13 DHG Pharmaceutical JSC DHG Manufacturing sector 3,945,744 3.99 0.30 0.31 49

14 Dongnai Plastic JSC DNP Manufacturing sector 2,518,468 3.88 0.48 0.32 63

15 Da Nang Plastic JSC DPC Manufacturing sector 43,511 1.63 0.21 0.17 39

16 Danang Rubber JSC DRC Manufacturing sector 2,815,423 3.41 0.57 0.38 67

17 Dai Thien Loc Corporation DTL Manufacturing sector 2,487,316 4.29 0.07 0.42 72

18 Do Thanh Technology Corporation DTT Manufacturing sector 157,994 2.59 0.34 0.27 42

19 Dzĩ An Manufacturing PLC DZM Manufacturing sector 266,512 4.34 0.31 0.45 56 h

(VND million) HCE SCE RCE SMA level

20 Binh Thanh Im-Export Production JSC GIL Manufacturing sector 1,089,998 1.77 0.17 0.26 39

21 Saigon Garmex Manufacturing JSC GMC Manufacturing sector 883,468 1.53 0.22 0.13 34

22 Thuan An Wood Processing JSC GTA Manufacturing sector 462,991 1.71 0.19 0.13 35

23 Ha Noi - Hai Duong Beer JSC HAD Manufacturing sector 174,026 4.12 0.42 0.33 56

24 Haiha Confectionery JSC HHC Manufacturing sector 505,377 3.62 0.42 0.34 45

25 Viglacera Ha Long I JSC HLY Manufacturing sector 48,253 1.99 0.37 0.13 38

26 Vicem Hoang Mai Cement JSC HOM Manufacturing sector 1,754,287 3.26 0.27 0.30 50

27 Hoa Phat Group JSC HPG Manufacturing sector 33,226,552 15.03 0.38 0.55 69

28 Materials Biochemistry Fertilizer JSC HSI Manufacturing sector 346,344 4.08 0.48 0.34 47

29 I.D.I International Investment Corp IDI Manufacturing sector 5,080,583 3.68 0.49 0.36 48

30 Long An Food Processing Export JSC LAF Manufacturing sector 346,005 4.10 0.28 0.25 43

31 Lix Detergent JSC LIX Manufacturing sector 780,510 4.28 0.43 0.34 56

32 NET Detergent JSC NET Manufacturing sector 542,143 2.98 0.27 0.38 70

33 Nhi Hiep Brick-Tile Co-Operation NHC Manufacturing sector 66,562 7.13 0.30 0.56 67

34 OPC Pharmaceutical JSC OPC Manufacturing sector 774,747 3.00 0.28 0.37 53

35 Dry Cell And Storage Battery JSC PAC Manufacturing sector 1,684,003 3.53 0.29 0.20 35

36 Pharmaceutical Medicinal JSC PMC Manufacturing sector 296,991 3.32 0.22 0.25 42

37 Petroleum Mechanical Stock Company PMS Manufacturing sector 307,140 4.20 0.56 0.45 62

38 Phu Nhuan Jewelry JSC PNJ Manufacturing sector 3,597,987 3.29 0.28 0.35 50

39 Phong Phu Pharmaceutial JSC PPP Manufacturing sector 131,714 3.30 0.32 0.39 47 h

(VND million) HCE SCE RCE SMA level

40 Song Da 7.04 JSC S74 Manufacturing sector 858,865 2.44 0.30 0.39 56

41 Sametel Corporation SMT Manufacturing sector 185,979 4.33 0.41 0.39 51

42 Saigon Plastic Packaging JSC SPP Manufacturing sector 1,034,969 4.24 0.39 0.40 49

43 Sao Vang Rubber JSC SRC Manufacturing sector 724,257 4.59 0.42 0.44 58

44 Thai Binh Cement JSC TBX Manufacturing sector 61,365 1.49 0.26 0.07 46

45 Thanh Cong Textile Garment JSC TCM Manufacturing sector 2,820,394 2.11 0.26 0.26 43

46 Thanh Hoa Beer JSC THB Manufacturing sector 344,772 2.30 0.34 0.28 42

47 Tung Kuang Industrial JSC TKU Manufacturing sector 752,151 4.87 0.37 0.43 62

48 Traphaco JSC TRA Manufacturing sector 1,377,454 3.84 0.47 0.37 53

49 Tia Sang Battery JSC TSB Manufacturing sector 133,437 2.61 0.38 0.24 43

50 Taya Electric Wire & Cable JSC TYA Manufacturing sector 717,368 4.08 0.39 0.39 57

51 Vinh Plastic & Bags JSC VBC Manufacturing sector 380,232 2.39 0.35 0.24 42

52 Viettronics Tan Binh JSC VTB Manufacturing sector 790,716 3.73 0.31 0.32 46

53 High Grade Brick Tile Corporation MCC Manufacturing sector 74,828 5.09 0.43 0.52 54

54 Quang Ninh Construction & Cement JSC QNC Manufacturing sector 2,024,459 5.21 0.56 0.54 62

55 Viet Duc Welding Electrode JSC QHD Manufacturing sector 166,879 4.79 0.34 0.50 64

56 Rangdong Light Source & Vacuum JSC RAL Manufacturing sector 2,096,851 1.70 0.22 0.19 36

57 Taicera Enterprise Company TCR Manufacturing sector 1,286,290 3.31 0.38 0.28 48

58 Bien Hoa Packaging Company SVI Manufacturing sector 749,980 4.18 0.38 0.58 57

59 Hapaco Corporation HAP Manufacturing sector 1,013,321 4.02 0.35 0.19 43 h

(VND million) HCE SCE RCE SMA level

60 Viet Nam Dairy Products JSC VNM Manufacturing sector 29,378,656 3.78 0.32 0.46 69

61 Vinacafé Bienhoa JSC VCF Manufacturing sector 3,140,260 10.83 0.46 0.46 69

62 Vinh Hoan Corporation VHC Manufacturing sector 4,450,873 4.01 0.39 0.36 54

64 Petrolimex Saigon Transportation JSC PSC Service 240,569 4.19 0.56 0.33 55

65 HaiPhong Transportation & Services JSC PTS Service 180,729 5.40 0.65 0.34 58

66 Tran Anh Digital World JSC TAG Service 1,411,943 5.02 0.57 0.32 47

67 Power Engineering Consulting JSC 2 TV2 Service 1,460,443 2.90 0.19 0.29 41

68 Power Engineering Consunting JSC 3 TV3 Service 259,462 1.01 0.16 0.08 26

69 Power Engineering Consulting JSC 4 TV4 Service 257,065 1.53 0.13 0.21 32

70 Ocean Hospitality & Service JSC OCH Service 3,388,888 3.03 0.39 0.28 50

71 Quang Ninh Educational Equipment JSC QST Service 34,062 3.22 0.20 0.20 42

72 The Royal International Corporation RIC Service 1,370,119 3.05 0.38 0.21 46

73 Electronics Technology Corporation ELC Service 1,160,470 3.03 0.36 0.27 57

74 F.I.T Group Joint Stock Company FIT Service 4,339,323 3.01 0.36 0.25 51

75 Binh Dinh Minerals JSC BMC Mining and energy 219,552 2.67 0.22 0.21 55

76 Cholon Water Supply JSC CLW Mining and energy 457,231 4.61 0.38 0.24 50

77 Hoa An JSC DHA Mining and energy 365,250 4.66 0.38 0.60 69

78 Ha Giang Mineral and Mechinics JSC HGM Mining and energy 250,318 3.65 0.34 0.28 44

79 Nam Mu Hydropower JSC HJS Mining and energy 486,004 5.25 0.36 0.58 65 h

(VND million) HCE SCE RCE SMA level

80 Vinacomin - Ha Lam Coal JSC HLC Mining and energy 4,181,777 4.33 0.58 0.36 55

81 Hoa Binh Minerals JSC KHB Mining and energy 359,909 5.26 0.74 0.61 72

82 Mineral & Mechanical JSC MIM Mining and energy 97,582 1.61 0.10 0.21 47

83 Vinacomin - Nui Beo Coal JSC NBC Mining and energy 1,896,154 5.33 0.73 0.45 60

84 Nui Nho Stone JSC NNC Mining and energy 494,444 1.50 0.06 0.46 69

85 Southern Gas Trading JSC PGS Mining and energy 2,249,588 22.92 0.51 0.49 70

86 PetroVietNam Northern Gas JSC PVG Mining and energy 1,309,797 5.87 0.79 0.49 62

87 PetroVietnam Technical Corporation PVS Mining and energy 25,541,110 3.29 0.21 0.25 46

88 Thac Ba Hydropower JSC TBC Mining and energy 879,793 4.80 0.24 0.65 64

89 Vinacomin - Coc Sau Coal JSC TC6 Mining and energy 1,530,487 5.46 0.53 0.28 51

90 Vinacomin - Cao Son Coal JSC TCS Mining and energy 2,065,540 5.79 0.57 0.30 58

91 Vinacomin - DeoNai Coal JSC TDN Mining and energy 931,441 2.59 0.34 0.27 47

92 Vinh Son - Song Hinh Hydropower JSC VSH Mining and energy 6,110,122 8.55 0.83 0.70 68

93 Vinacomin - Mong Duong Coal JSC MDC Mining and energy 1,319,827 1.86 0.25 0.11 35

94 Ninh Binh Thermal Power JSC NBP Mining and energy 376,921 1.46 0.13 0.11 33

95 PetroVietnam Gas Joint Stock Corp GAS Mining and energy 56,753,854 5.00 0.38 0.57 72

96 Idico Urban & House Development JSC UIC Mining and energy 418,083 1.80 0.16 0.34 57

97 Mekong Fisheries JSC AAM Agriculture 257,904 3.79 0.33 0.62 68

98 Bentre Aquaproduct Export JSC ABT Agriculture 649,276 2.20 0.23 0.34 54

99 Camimex Group JSC CMX Agriculture 684,436 4.22 0.49 0.30 51 h

(VND million) HCE SCE RCE SMA level

100 Sao Ta Foods JSC FMC Agriculture 1,374,021 3.92 0.36 0.30 49

101 Ngo Quyen Seafood Processing JSC NGC Agriculture 104,190 3.61 0.20 0.58 66

102 Hung Hau Agricultural Corporation SJ1 Agriculture 701,157 4.69 0.48 0.41 63

103 TuongAn Vegetable Oil JSC TAC Agriculture 1,193,883 3.60 0.49 0.33 55

104 Seafood Joint Stock Company 4 TS4 Agriculture 1,289,943 3.58 0.32 0.38 61

105 Safoco Foodstuff JSC SAF Agriculture 166,139 2.94 0.22 0.29 47

106 Hoang Anh Gia Lai JSC HAG Agriculture 52,763,470 7.98 0.89 0.60 73

107 Danang Books & School Equipment JSC BED Commercials 53,872 3.98 0.33 0.33 49

108 Mobile Telecom Infracstructure Corp BTT Commercials 418,488 4.76 0.52 0.47 58

109 Materials - Petroleum JSC COM Commercials 529,583 2.32 0.20 0.30 52

110 DIC Investment & Trading JSC DIC Commercials 1,235,090 6.27 0.57 0.32 53

111 Education Cartography & Illustration JSC ECI Commercials 37,150 2.03 0.32 0.18 40

112 Ha Noi Beer Trading JSC HAT Commercials 118,839 3.04 0.24 0.33 49

113 Hang Xanh Motors Service JSC HAX Commercials 861,001 7.01 0.56 0.40 62

114 Phuong Nam Cultural JSC PNC Commercials 527,361 5.23 0.56 0.28 44

116 SaiGon Fuel Joint Stock Company SFC Commercials 519,328 3.83 0.29 0.44 56

117 Sa Giang Import Export Corporation SGC Commercials 167,258 2.99 0.33 0.33 48

118 Sai Gon Machinery Spare Parts JSC SMA Commercials 666,247 3.30 0.25 0.67 73

119 Saigon General Service Corporation SVC Commercials 3,337,818 4.99 0.42 0.45 47 h

(VND million) HCE SCE RCE SMA level

120 Telecom Industry Electronics JSC TIE Commercials 302,107 5.98 0.60 0.50 67

121 Vien Lien JSC UNI Commercials 167,452 5.81 0.63 0.36 60

122 Vien Dong Investment Trading Corp VID Commercials 502,119 3.97 0.24 0.38 76

124 Gemadept Corporation GMD Logistics & equipment 10,117,919 5.38 0.60 0.37 63

125 Hoang Ha JSC HHG Logistics & equipment 577,433 4.01 0.58 0.40 59

126 Ha Tien Transport JSC HTV Logistics & equipment 354,719 2.76 0.17 0.21 45

127 Maritime Supply & Techlonogy JSC MAC Logistics & equipment 230,857 2.77 0.31 0.26 46

128 Mai Linh Central JSC MNC Logistics & equipment 890,660 4.12 0.66 0.30 64

129 PGT Holdings JSC PGT Logistics & equipment 79,657 3.15 0.32 0.36 65

130 Petrolimex Joint Stock Tanker Company PJT Logistics & equipment 278,830 3.00 0.22 0.25 46

131 Tay Ninh Cable Car Tour Company JSC TCT Logistics & equipment 253,366 3.57 0.22 0.35 66

132 Transportation and Trading Services JSC TJC Logistics & equipment 195,443 4.98 0.59 0.36 59

133 Telecom Transportation Service JSC TST Logistics & equipment 215,635 2.01 0.32 0.19 42

134 VanLang Technology & Transport JSC VLA Logistics & equipment 17,079 2.15 0.33 0.19 41

135 Vietnam Container Shipping JSC VSC Logistics & equipment 2,397,438 4.62 0.58 0.32 65

136 Vietnam Sea Transport & Chartering JSC VST Logistics & equipment 1,740,122 2.35 0.13 0.24 42

137 Danang Airports Services JSC MAS Logistics & equipment 127,387 3.99 0.31 0.36 48

138 Vietnam Petroleum Transport JSC VIP Logistics & equipment 1,707,345 6.69 0.50 0.48 67

139 Vinalink Logistics JSC VNL Logistics & equipment 334,433 4.87 0.17 0.20 39 h

(VND million) HCE SCE RCE SMA level

140 Vinaship JSC VNA Logistics & equipment 948,236 3.67 0.27 0.46 53

141 VietNam Sun Copporation VNS Logistics & equipment 3,183,174 4.23 0.38 0.45 43

142 Viet Nam Ocean Shipping JSC VOS Logistics & equipment 4,238,710 4.70 0.36 0.48 67

143 Binh Duong Civil Engineering JSC BCE Real estate & construction 1,264,063 1.43 0.04 0.12 30

144 Construction & Infrastructure JSC CID Real estate & construction 15,729 4.43 0.40 0.47 64

145 Construction Joint Stock Company 6 CT6 Real estate & construction 232,660 1.53 0.19 0.15 33

146 Development Construction 2 JSC DC2 Real estate & construction 80,904 1.44 0.19 0.15 32

147 Development Construction JSC DIG Real estate & construction 5,875,806 2.12 0.24 0.28 51

148 Dalat Real Estate JSC DLR Real estate & construction 155,317 3.78 0.24 0.37 51

149 Tasco Joint Stock Company HUT Real estate & construction 9,319,853 4.02 0.62 0.37 72

150 Lilama Erection Mechanical JSC L35 Real estate & construction 243,637 1.35 0.21 0.05 31

151 Lilama 45.4 JSC L44 Real estate & construction 327,385 1.99 0.05 0.25 38

152 Erection - Electromechanics Testing JSC LCD Real estate & construction 106,068 1.66 0.15 0.14 33

153 Lilama 18 Joint Stock Company LM8 Real estate & construction 1,976,772 1.29 0.11 0.12 30

154 Ha Noi South Housing and Urban Corp NHA Real estate & construction 143,796 4.54 0.54 0.43 72

155 Hong Ha Viet Nam JSC PHH Real estate & construction 761,328 2.89 0.40 0.25 47

156 Song Da 4 JSC SD4 Real estate & construction 1,080,310 1.86 0.30 0.14 36

157 Song Da No 9 JSC SD9 Real estate & construction 1,817,347 4.85 0.38 0.42 59

158 Simco Song Da JSC SDA Real estate & construction 407,897 2.20 0.37 0.18 43

159 Song Da Electrical Engineering JSC SDE Real estate & construction 62,543 2.31 0.25 0.17 41 h