The
Impact of Intellectual Capital on Financial Performance of Small and
Medium-sized Enterprises

O Impacto do Capital
Intelectual no Desempenho Financeiro das Pequenas e Médias Empresas

Vinícius
Figueiredo de Faria

https://orcid.org/0000-0002-3924-7647

Doutorando em
Sistemas de Informação e Gestão do Conhecimento. Universidade FUMEC (FUMEC) –
Brasil. [email-masked].

Fábio Corrêa

https://orcid.org/0000-0002-2346-0187

Doutor em Sistemas de Informação e Gestão
do Conhecimento. Universidade FUMEC (FUMEC) – Brasil. [email-masked].

Renata de Sousa da Silva Tolentino

https://orcid.org/0000-0002-8284-7509

Doutora em Administração. Universidade
FUMEC (FUMEC) – Brasil. [email-masked].

Cristiana Fernandes de Muylder

https://orcid.org/0000-0002-0813-0999

Doutora em Economia Aplicada. Universidade
FUMEC (FUMEC) – Brasil. [email-masked].

ABSTRACT

The rapid growth of technologically
advanced companies in the knowledge-based economy has driven corporate
management to pay more attention to the importance of intellectual capital.
Over the last two decades, several Intellectual Capital monetary models have
gained in importance, due to the increasing need  of firms
to administer and control the efficiency of their intangible resources.
In this context, the present study is conducted to examine the impact of the
value creation efficiency of Intellectual Capital on the financial performance
of small and medium-sized enterprises. Through a quantitative approach, this
research sample consisted of 23 small and medium-sized enterprises and made use
of correlation and multiple regression analysis as methods for treating the
ambitioned. The results showed that the value creation efficiency of
intellectual capital positively influences corporate financial performance. At
last, the inclusion of relational capital efficiency, as well as the
relationship examination of Intellectual Capital and other performance
measures, are suggestions for future research.

Keywords: intellectual capital; value-added intellectual coefficient;
VAIC™; small and medium-sized enterprises; business performance.

RESUMO

O rápido
crescimento de empresas tecnologicamente avançadas em uma economia baseada no
conhecimento, tem levado a administração corporativa a prestar mais atenção à
importância do capital intelectual. Nas últimas duas décadas, vários modelos
monetários de Capital Intelectual ganharam importância, devido à necessidade
crescente das empresas de administrar e controlar a eficiência de seus recursos
intangíveis. Neste contexto, o presente estudo tem como objetivo examinar o
impacto da eficiência de criação de valor do Capital Intelectual no desempenho
financeiro de pequenas e médias empresas. Por meio de uma abordagem
quantitativa, a amostra desta pesquisa foi composta por 23 pequenas e médias
empresas e fez uso da correlação e da análise de regressão múltipla como
métodos de tratamento dos ambicionados. Os resultados mostraram que a
eficiência na criação de valor do capital intelectual influencia positivamente
o desempenho financeiro das empresas. Por fim, a inclusão da eficiência do
capital relacional, bem como o exame da relação do Capital Intelectual e outras
medidas de desempenho, são sugestões para pesquisas futuras.

Palavras-chave:
capital intelectual; coeficiente de valor agregado pelo capital
intelectual; VAIC™; pequenas e médias empresas; desempenho de negócios.

Recebido
em 20/12/2021.  Aprovado em 30/06/2022.
Avaliado pelo sistema double blind peer review. Publicado conforme normas da APA.

https://doi.org/10.22279/navus.2022.v12.p01-13.1751

1 INTRODUCTION

Knowledge, as "know-how," is
developed and exploited, according to the knowledge-based interpretation
(Grant, 1996a, 1996b; Kogut & Zander, 1992; Möller et al., 2011; Beattie & Smith, 2013).
Subramaniam and Youndt (2005) sustain that a clever
employee with tacit knowledge often brings new ideas and knowledge to the
organization, through their superior capabilities in opportunity
identification. This tacit knowledge, under a development and exploitation
stage, produces amalgamations of capabilities that are corporately difficult to
observe, isolate, and imitate (Teece et al., 1997; McInerney
& Koenig, 2011) as they are socially created and embedded within the
organization (Kogut & Zander, 1992).

In fact, a deep change has been perceived in
the knowledge economy wherein intellectual resources are gradually shedding
light on limitations of the traditional physical and financial resources to be
core contributors of value creation (Chen et al., 2005; Ding & Li, 2010).
Indeed, company management can no longer only count on physical resources,
suggesting that a good use of intellectual resources is considered essential to
achieve competitive advantage (Drucker, 1988; Petty & Guthrie, 2000; Suhendah, 2012; Halid et al., 2018).
In this scenario, Intellectual Capital may be considered a driver of corporate
performance, competitiveness, success, value creation, and financial
sustainability (Kogut & Zander, 1992; Bierly & Chakrabarti, 1996; Brennan & Connell,
2000; Bontis & Fitz-enz,
2002; Cronje & Moolman, 2013; Bontis et al., 2015;
Xu & Wang, 2018).

In any country, but especially in developing
countries, small and medium-sized enterprises are well-thought-out to be the
engines of economic growth, employment generation, and poverty reduction (Ayyagari et al., 2007). On the other hand, their
difficulties in realizing gains of scale (Patel & Jayaram, 2014; Wales et
al., 2013), certainly impose challenges to sustainability and may be the reason
why failure rates remain high. However, few authors have devoted themselves to
studying the influence of Intellectual Capital on the business financial
performance and sustainability of small and medium-sized enterprises (Yaacob et
al., 2014).

In this context, the purpose of the present
study is to empirically examine, on a sample of 23 small and medium-sized
enterprises, whether Intellectual Capital has a positive effect on small and
medium-sized enterprises' financial performance, which is proxied by ROA
(Return on Asset) and ROE (Return on Equity). The research also takes a broad
analytical perspective on Intellectual Capital valuation by using Ante Pulic’s Value Added Intellectual Coefficient (VAIC™) method
(Pulic, 2000), and it is justified by dedicating
itself to contributing to academic and scientific progress, aiming at improving
the understanding of the referred research problem through the relationship
between scientific theory and empirical market practice.

For its operationalization, this paper is
subdivided into subsections. In addition to this introduction (subsection 1),
the theoretical foundations (subsection 2) that support the discussion among
VAIC™ and the financial performance of small and medium-sized enterprises are
presented. In sequence, the methodological procedures that describe the problem
statement and the research hypotheses developed for the study (subsection 3)
are elucidated so that, subsequently, the analysis of the results (subsection
4) is evidenced by the methods outlined. Then, the final considerations
(subsection 5) are made and the references used in the course of this
investigation are listed.

2 THEORETICAL BACKGROUND

2.1 Knowledge management in small and
medium-sized enterprises

The interaction and relationships between
actors encourage the sharing of information and knowledge. It favors the creation
and conversion of knowledge and the production of Intellectual Capital which
usually leads to a growing process of acquisition of tacit knowledge, useful
for building own advantages within companies (Bontis et
al., 2000; McInerney & Koenig, 2011). The success
of a company can be measured by its capacity to engender Intellectual Capital
through the interaction between human (people), structural (infrastructure),
and relational (customers/suppliers/collaborators) capital (Novas
et al., 2017), using it to generate, transfer and apply knowledge and endorse
competitive advantage through innovation.

Moreover, the resource-based theory of the firm
suggests that firms can be seen as a unique bundle of dynamic, complex, and
intangible resources (Barney, 1991, Roos et al., 2005,
Alexandra & Mihaela, 2013). Moreover, it advocates that the sustainable
competitive advantage is resultant from the efficient employment of both
tangible and intangible resources (Tayles et al., 2006;
Velmurugan, 2010; Guthrie et al., 2012; Novas et al.,
2017; Abhayawansa et al., 2019). This set of physical
and intangible assets is at the core of the firm’s competitive advantage
(Grant, 1991). In this context, the management of knowledge figures as a key
resource for firm value creation (Bontis, 2001; Sveiby, 2000; Sveiby, 2010;
Kanchana & Mohan, 2017), and the sustainable growth of a company is
grounded on establishing know-how and transforming it into capitalization
(Wang, 2011).

According to Wolff & Pett
(2006), the success of small and medium-sized enterprises is associated with a
clear focus and strong values like independence, flexibility, entrepreneurship,
and innovation. Small and medium-sized enterprises work in close contact with
customers and suppliers, using a personal form of control and having a
long-term view of business relations. On the other hand, they suffer from
informal structures, insufficient resources, erratic decision-making, and poor
administrative and accounting procedures. In this context, Intellectual Capital
is indeed important to small and medium-sized enterprises once it reveals
hidden assets that can have a major impact on the profitability and even the
core existence of the company in the future (Ngah et
al., 2009; Xu & Li, 2019).

2.2 Accounting and Intellectual Capital

As aforementioned, Intellectual Capital plays a
crucial role when it comes to increasing a firm’s competitiveness and
performance (Seetharaman et al., 2002). Unfortunately, traditional accounting
practices are considered simplistic and lack embedding accounting rigor to
accurately measure Intellectual Capital (Sveiby,
2000). The result of this restriction is a growing divergence between the
market and the book values of organizations. In other words, the market
estimates the value of companies with high intangible assets (Intellectual
Capital) to be significantly higher than the calculated book value (Firer &
Williams, 2003; Chen et al., 2005). Therefore, accounting practitioners have
devoted much of their efforts to improving models focused on measuring
Intellectual Capital that express, in addition to financial statements, the
value and continuous benefit of managing intangible assets (Fincham & Roslender, 2003; Tayles et al.,
2006; Mårtensson, 2009; Velmurugan, 2010; Andrikopoulos, 2010; Guthrie et al., 2012; Derun, 2013; Novas et al., 2017; La
torre et al., 2018; Abhayawansa
et al., 2019).

2.3 A systematic literature review on the
value-added intellectual coefficient

A systematic review is a tool to evaluate and
interpret all researches available relevant to a particular research question,
topic area, or phenomenon of interest. Systematic reviews aim to present a fair
evaluation of a research topic by using a trustworthy, rigorous, and auditable
methodology (Kitchenham, 2004). This study has
carried out a systematic literature review, following Kitchenham’s
guidelines, which covers three phases of a systematic review: planning the
review; conducting the review, and reporting the review. Once the procedures
were defined, the protocol was applied and the results are described herein
(figure 1).

Figure 1. Systematic literature review
procedures

Source: Kitchenham (2004).

To register and compile the information, the
study made use of StArt software. StArt,
version 3.4-64, provided support to the systematic literature review process
activities and became a powerful tool to aim at the expected results (chart 1).

Protocol

Description

Main question

What is the relation
between value-added intellectual capital coefficient (VAIC) and financial
performance in small and medium-sized enterprises?

Data selection

Among databases,
indexers, virtual libraries and search tools, the following were selected: IEEEXplore: <http://ieeexplore.ieee.org>; Ebsco: < https://search.ebscohost.com>;
ScienceDirect:< https://www.sciencedirect.com>; Wiley Online
Library:< https://onlinelibrary.wiley.com>; Scopus Preview:<
www.scopus.com.

Study selection criteria - (I) inclusion and (E) exclusion

(I1) Studies that answer
the research question; (I2) Studies that present primarily or secondarily
good practices, strategies, and successful techniques, related to the
objective of this study, and that can be adopted in the identification of
this objective;(I3) Papers discussing the relation between value-added
intellectual capital and corporate performance; (I4) Papers discussing the
technical aspects of value-added intellectual coefficient. (E1) Redundant
studies; (E2) Studies that are clearly irrelevant to research, according to
the research questions raised; (E3) Studies that have not been published
between January/2015 and January/2020; (E4) Studies that do not answer any of
the research questions.

Document analysis and criteria application

Out of a total of 3,513
studies obtained in the research, 111 were excluded through criterion (E1),
3,334 through criteria (E2 and E3), and 33 were excluded through criterion
(E4). In total, 35 academic articles were selected.

Chart 1. Procedures performed at the
systematic literature review

Source: Authors (2021).

2.4 VAIC™ method and financial performance

The present study employs the VAIC™ method
since it is recognized as an appropriate approach to measure Intellectual
Capital (Chen et al., 2005; Chu et al., 2010; Maditinos
et al., 2011; Tan et al., 2007). Among several advantages, VAIC™ generates
objective, calculable and quantitative measurements without using subjective
grading. The literature on Intellectual Capital measurement and the testing of
the relationship between Intellectual Capital and corporate performance shows
that the VAIC™ method is a widely used and popular method among academic
researchers (Firer & Stainbank, 2003; Tayles et al., 2006; Chu et al., 2010; Clarke et al., 2011;
Wang, 2011; Maji & Goswami, 2016; Mondal, 2016; Hartati
& Hadiwidjaja, 2019).

Recent literature criticism leveled at the
VAIC™ method descends from a misunderstanding of Pulic’s
original idea (Lazzolino & Laise,
2013). Pulic’s VAIC™ method upholds its logical
consistency and soundness when it is correctly interpreted as an indicator of
the contribution of Intellectual Capital to value creation. Therefore, VAIC™
method mainly measures the efficiency of a firm based on three inputs: physical
and financial capital; human capital; and structural capital. The physical and
financial capital can be measured and managed and to suit the purpose of this
research will be considered as corporate assets produced.

Human capital can be defined as the knowledge,
skill, experience, talent, institution, attitude, and effectiveness of
employees to improve the firm performance (Chen et al., 2005). And Andriessen (2004) defined structural capital as company
culture, working environment, systems, and intellectual property. So, VAIC™ is
conceived by capital employed efficiency; human capital efficiency; and
structural capital efficiency. The sum of the coefficients results in an
unambiguous indicator of the level of efficiency of the organization as a whole
(figure 2).

Figure 2. The Value-Added Intellectual Coefficient

Source: Pulic (2000).

Moreover, to examine whether Intellectual
Capital has a positive effect on the performance of small and medium-sized
enterprises, the research aims to use ROA (Return on Asset) and ROE (Return on
Equity) as proxies in the model. ROA is considered to be a measure of the ability
of company to generate profits by using its total assets (wealth). It shows the
degree to which the revenues of a firm exceed over cost (Firer & Williams,
2003; Chen et al., 2005); and ROE is often referred to as the rate of return on
net worth, in other words, refer to the ability of the company to generate
profits with its own capital (Yusuf et al., 2013).

3 METHOD AND HYPOTHESIS

The above-mentioned characterize the value of
intellectual capital as a representative for a company’s financial performance.
Then, VAIC™ is, among the monetary models to evaluate the firm’s performance,
the one that acknowledges significant importance to the contribution of
intangibles, knowledge, and learning processes in the value creation (Villalonga, 2004). Therefore, keeping research objectives
in observance the study proposes to investigate the relationship between
Intellectual Capital and corporate financial performance. Through a
quantitative approach, this research made use of correlation analysis and
multiple linear regression analysis as statistic methods for treating the
ambitioned. VAIC™ model and the accounting ratios ROA and ROE have been used as
the dependent and independent variables respectively and its computation can be
observed in table 1.

Index

Formula

Description

VAIC™

= CEE + HCE + SCE

= Capital employed efficiency + Human capital
efficiency + Structural capital efficiency

CEE

= VA / CE

= Corporate value added / Total assets

SCE

= SC / VA

= Structural capital / Corporate value added

HCE

= VA / HC

= Corporate value added / salaries expenses

SC

= VA - HC

= Value added - salaries expenses

CE

= TA - NL

= Total assets - Net liabilities

HC

= S + LC + B

= Salaries + Social security contribution +
benefits

VA

= EBIT + D + A +
EC

= Earnings before interest and tax +
Depreciation + Amortization + Employee cost

ROA

= Net income/Total
assets

= (Total revenues – Total expenses) / (Total
liabilities + Owner’s equity)

ROE

= Net income/Shareholders’ equity

= (Total revenues – Total expenses) / (Total
assets -Total liabilities)

Table 1. Computation of VAIC™, ROA, and ROE

Source: Authors, 2021.

Based on the existing literature and the
information provided by the firm´s balance sheet, this study proposes a
conceptual model (figure 3) to investigate the relationship between
Intellectual Capital and financial performance in 23 small and medium-sized
enterprises. Through the advertisements of Venugopal and Subha (2015), Maji and
Goswami (2016), and Nadeem, Gan and
Nguyen (2017), the following hypotheses are
presented: there is a positive association between capital employed efficiency
(CEE) and corporate performance (CP) variables (H1); there is a positive
association between human capital efficiency (HCE) and corporate performance
(CP) variables (H2); there is a positive association between structural capital
efficiency (SCE) and corporate performance (CP) variables (H3). In line with
Mondal (2016) and Hartati and Hadiwidjaja
(2019): Intellectual Capital performance (VAIC™) can predict corporate
performance (CP) (H4).

Figure 3. Conceptual model showing hypotheses

Source: Authors, 2021.

The proposed regression analysis examines
associative relationships between a dependent metric variable and one or more independent
variables (Malhotra & Birks, 2000). It targets to answer the above-stated hypotheses and compare the
findings to the ones obtained on several other studies (McDowell et al., 2018;
Maji & Goswami, 2016; Venugopal & Subha, 2015; Deep & Narwal, 2014;
Komnenic & Pokrajcic,
2012; Zeghal & Maaloul,
2010; Sharabati et al., 2010; Tan et al., 2007). IBM
SPSS Statistics 21 was used to perform the regression analysis.

4 RESULTS

The findings (table
2) enable us to put forward some preliminary arguments about the relationship
between Intellectual Capital and financial performance.

VAIC™

ROA

ROE

SCE

HCE

CEE

VAIC™

1.000

ROA

0.211

1.000

ROE

0.770*

0.589*

1.000

SCE

0.362

0.248

0.393

1.000

HCE

0.977*

0.207

0.796*

0.367

1.000

CEE

0.207

0.029

-0.050

-0.060

-0.007

1.000

Table 2. Pearson correlation coefficients

Here,
* denotes significance at
1% level

The majority of variable pairs demonstrate a
significant and positive correlation. SCE (structural capital efficiency) shows
a significant positive relationship with ROA (0.248) and ROE (0.393). Likewise,
HCE (human capital efficiency) follows the same pattern regarding the
relationship between ROA (0.207) and ROE (0.796). This demonstrates that an
increase in value creation efficiency by structural and human capital
positively affects profitability. CEE (physical capital efficiency) is
positively correlated with ROA (0.029) and negatively correlated to ROE
(-0.050), but both can be considered not significant, demonstrating that an
increase in value creation efficiency by physical capital would not influence
profitability. Thus, hypothesis H1 stands partly accepted while hypotheses H2
and H3 stand fully accepted.

Concerning whether intellectual Capital
performance can predict corporate performance (Hypothesis H4), VAIC™ shows a
significant positive relationship with ROA (0.211) and ROE (0.770), which may
indicate a noteworthy association between intellectual capital efficiency and
firms' financial performance. The results are corroborated by the previous
findings obtained by other researchers (Maji & Goswami, 2016; Venugopal
& Subha, 2015; Deep & Narwal, 2014).

Table 3
shows the regression results for model 1 in which the Intellectual Capital
component (VAIC™) was regressed against measures of corporate financial
performance (ROA and ROE).

Model

R

R square

Adjusted R square

F-value

Sig.

Durbin-Watson

1

0.825a

0.681

0.650

21.386*

0.000

1.661

Table 3. Panel data regression model 1b

Here, * denotes significance at 5%
level

a. Predictors: (Constant), ROE, ROA

b. Dependent variable: VAIC™

The adjusted R square indicates that 65%
variance in the dependent variable (VAIC™) is explained by the variance in
corporate financial performance (ROA and ROE). When referring to the Durbin
Watson statistic test, the model designates independence in the residuals from
a statistical regression analysis. Also, the multicollinearity test result
reached 0.654, which indicates the absence of multicollinearity problems for
the model, since according to Kennedy (1985), only if the correlation among
explanatory variables exceeds 0.80, the problem of multicollinearity may arise.

Therefore, the explanatory power of the
regression is considered high as well as significant. These findings converge
with the ones obtained by and Kehelwalatenna, (2016,
p.14), Nadeem, Gan and Nguyen (2017, p.8), and Hartati
and Hadiwidjaja (2019, p.204), and suggest that the
Intellectual Capital variable is suitable for explaining measures of firm
financial performance. Thus, hypothesis H4 stands fully accepted.

5 CONCLUSION

The present study
was conducted to examine the impact of the value creation efficiency of
intellectual capital on corporate financial performance. The empirical
examination is based on the 2019 accounting data of 23 Brazilian small and
medium-sized enterprises. Undoubtedly, the research proves that Intellectual
Capital can increase the profitability of small and medium-sized enterprises.
This conclusion is sustained by the results of testing that Intellectual
Capital has a positive effect on profitability (financial performance),
measured by return on equity (ROE) and return on assets (ROA). This shows that
companies that have greater Intellectual Capital will outcome in higher
financial performance.

Moreover, the
research provides evidence that human capital and structural capital positively
affect firm financial performance, while physical capital doesn’t affect firm
financial performance, neither positively nor negatively. Also, among VAIC™
variables, HCE is found to be the most significant related to ROE, while SCE is
found to be the most significant related to ROA. Considering, ROE and ROA
proxied by VAIC™, the correlation results VAIC™-ROE are far more relevant than
VAIC™-ROA. Thus, the theoretical perspective of Intellectual Capital is fully
confirmed, according to H2, H3, and H4, and partially, according to H1, in the
market practice of small and medium-sized companies.

Finally, the
academic benefits lie in the fact that an in-depth analysis has been done to
understand the impact and predictive ability of intellectual capital on
corporate performance. On the other hand, one of the limitations of the VAIC™
model is that it does not separate out relational capital and hence future
research can add this important component of Intellectual Capital in the VAIC™
model. Future studies can examine the relationship of Intellectual Capital to
other measures of performance such as sales growth, stock price, and stock
returns.

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