Received: 8 August 2019
Accepted: 30 September 2019
This study aims to empirically examine the effect of intellectual capital, bank size, and market share on the efficiency of commercial banks in Indonesia from 2013 to 2017. The results of a panel data analysis of two models show that intellectual capital (calculated simultaneously or individually per component), bank size, and market share have a significant effect on bank efficiency, as confirmed by a fixed-effect regression model. Said model indicates that the year-to-year effect of the independent variables is influenced by individual bank differences. In other words, dissimilar characteristics of banks’ intellectual capital and its components determine the effect of said variables on bank efficiency. Likewise, the asset ownership and market share of banks also distinguish their behavior in terms of bank efficiency.
Keywords: Intellectual capital, bank size, bank market share, bank efficiency.
JEL Classification: G21, L22, O16.
Este trabajo tiene como objetivo estudiar empíricamente el efecto que el capital intelectual, el tamaño del banco y la participación en el mercado tuvieron sobre la eficiencia de los bancos comerciales en Indonesia entre 2013 y 2017. Los resultados de un análisis de datos de panel de dos modelos muestran que el capital intelectual (calculado de forma simultánea o individual por componente), el tamaño del banco y la participación en el mercado tienen un efecto significativo en la eficiencia bancaria, lo cual confirmó un modelo (regresión) de efectos fijos. Dicho modelo indica que la diferencia anual de las variables independientes está influenciada por las características particulares de las instituciones bancarias. En otras palabras, las diferentes características del capital intelectual de los bancos y sus componentes determinan el efecto de dichas variables en la eficiencia bancaria. Asimismo, los activos y participación en el mercado de los bancos distinguen su comportamiento en términos de eficiencia bancaria.
Palabras clave: capital intelectual, tamaño del banco, participación en el mercado bancario, eficiencia bancaria.
Clasificación JEL: G21, L22, O16.
As financial institutions, banks play a strategic role in national economies through banking systems, receiving funds from the community (individuals and companies) and distributing them to individuals or companies in the form of loans (
Given their vital role in a country’s economy, banks are also required to operate efficiently. Bank efficiency is an important indicator to analyze the performance of a bank (
Bank efficiency in Indonesia has been strongly emphasized after the period of the enactment of the ASEAN Economic Community (MEA), during which Bank Indonesia (BI) issued Bank Indonesia
Banking efficiency has attracted the interest of multiple researchers with various approaches. Among them,
Another finding regarding the efficiency of shari'ah banking in Indonesia was reported by
From the various findings in bank efficiency studies in Indonesia in different periods of observation, it can be concluded that banks in Indonesia, still today, do not operate efficiently. Consequently, further research is needed regarding the factors that may cause bank efficiency.
Studies into factors that cause bank efficiency have been carried out before, but the results showed inconsistencies in the variables (
In contrast,
The results of those studies show that efficiency research is still focused on financial aspects, while non-financial ones have not been widely investigated. One of those non-financial aspects is intellectual capital (IC), which has been defined as an asset that can create value to help companies achieve and maintain their competitive advantage (
In line with those arguments, the present study aims to empirically examine the effect of intellectual capital on the efficiency of conventional commercial banks in Indonesia.
Intellectual Capital and Bank Efficiency
Researchers have adopted a variety of perspectives to explore the factors that determine company performance. In this regard, Penrose in 1959, as cited in
The resources referred to in the RBV theory have four characteristics:
1) They are able to support the company’s ability to meet customer needs better than competing companies.
2) They are available in limited or rare quantities and are not easily replicated. Four situations cause resources to be difficult to imitate: (a) those resources are physically unique, (b) they require a long time and a large cost to obtain them, (c) unique resources that are difficult for competitors to use and take advantage of, and (d) resources that require large capital investments to obtain them.
3) They can provide benefits for the company. The more profits for the company due to the use of certain resources, the more valuable said resources are.
4) They are durable.
(Penrose in
In line with the views of the RBV theory, intellectual capital is now considered the resource that can facilitate the achievement of goals. According to
In terms of accounting and finance, the measurement of IC was formulated by
Several authors have proven that VAIC and each of its components influence company performance; they include
The efficiency of banks in Indonesia could benefit from a comparison between operating expenses and operating income. The lower the BOPO the more efficient the operational costs of the bank under analysis and the lower the possibility of problematic conditions for the financial institution (
H1 : VAIC has a significant effect on bank efficiency.
H1.1 : VACA has a significant effect on bank efficiency.
H1.2 : VAHU has a significant effect on bank efficiency.
H1.3 : STVA has a significant effect on bank efficiency.
The formulation developed by Pulic has encouraged researchers in several countries to conduct research assessing intellectual capital associated with company performance as measured by financial instruments. The results of their research showed that intellectual capital measured through VAIC and each component of VAIC itself had a significant influence on company performance as measured by ROA (Return on Assets), ROE (Return on Equity), NPL (Non-Performing Loans), LDR (Loan to Deposit Ratio), CAR (Capital Adequacy Ratio), and bank efficiency (BOPO). Thus, it can be concluded that the presence of IC not only has an impact on the profitability of companies because, in the banking sector, it also influences liquidity, bank adequacy, and efficiency.
Regarding the interpretation of VAIC itself,
Common performers have a VAIC between 2.5 and 4. This value indicates that each IC component can produce a value added between 2.5 and 4 rupiahs and that, in general, the company is unable to utilize IC to produce maximum value added. Common performers are characterized by the average efficiency of their workers and less technology applied to products.
Good performers exhibit a VAIC between 4.1 and 5. Such VAIC indicates that the company is able to manage most of its ICs to produce added value for the company, and each IC component can produce an added value above 4 rupiahs on average. Good performers are characterized by high appreciation of knowledge by workers, technology-based products, good customer relations, and broad markets.
Top performers have a VAIC above 5. This value indicates that the company has managed its intellectual capital very well, and each IC component can produce a value added for the company over $ 5. Companies in this group are highly technology intensive, carry out only specialized activities employing trained workers, and manufacture specific high-value customized products.
According to some current authors, IC (measured using VAIC) is related to risk governance.
The relationship between IC and risk has also been explored by
Banks can also use IC as a reference point to make credit decisions (
Bank Size and Bank Efficiency
The structure–conduct–performance (SCP) paradigm has provided guidance for banking practices. According to it, assets are input factors that become the bargaining power of banks and determine how banks behave which, in turn, will determine their performance (
Therefore, banks should assign funds to assets cautiously because, for every decision to allocate funds to a group of sensitive or fixed rate assets, they need to ponder on the risks of each asset so that it does not have a negative impact on bank losses in the short or long term (
Banks with larger assets should behave efficiently if they want to increase profitability (
Based on the literature review of bank size and bank efficiency above, we developed an additional hypothesis:
H2 : Bank size has a significant effect on bank efficiency.
Market Share and Bank Efficiency
As cited by
The structure–conduct–performance (SCP) paradigm holds that market structure can determine bank behavior which, in turn, has implications for achieving performance. Empirically, the existence of a positive relationship between market structure and performance has been proven in
“Rastin Banking complies with the nature of financial intermediary activity (partnership of depositor in the yields of the fund receiver via the bank). In order to fulfil this goal, particular formation, organisational structure, instruments and workflow are defined in a legal framework” (
Based on the conceptual description of market structure and bank efficiency above, we propose the following hypothesis:
H3 : Market share has a significant effect on bank efficiency.
In order to analyze the intellectual capital variables (bank size, market structure, and bank efficiency), the present study used a panel data regression analysis of 82 commercial banks in Indonesia observed between 2013 and 2017. The measurement of the variables under study is detailed below in Table 1.
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Independent: | |||||
Bank Efficiency | Input |
| Ratio | ||
Number of ATMs | Ratio | ||||
Amount of Third-Party Funds | Ratio | ||||
Output | Credit Amount | Ratio | |||
The amount of income | Ratio | ||||
Bank size (ASSET) | Ln Total Assets |
( | Balance sheet | ||
Market share (SHAR) | Bank Loan i/Total Loan |
( | Balance sheet | ||
The research model with panel data developed in this study is written as follows.
Model 1
BOPOi,t= b0 + b1VAICi,t + b2ASETi,t + b3SHARi,t+ ei,t (1)
Where:
BOPOi, t = Bank efficiency i in period t,
VAICi, t = Intellectual capital of bank i in period t,
ASETi, t = Natural logarithm of total bank assets i in period t,
SHARi, t = Bank market share i in period t,
ei,t = error bank term i in period t.
Model 2
BOPOi,t= b0 + b1VACAi,t + b2VAHUi,t +b3STVAi,t + b4ASETi,t + b5SHARi,t+ ei,t (2)
Where:
BOPOi, t = Bank efficiency i in period t,
VACAi, t = Value Added Capital Employed by bank i in period t,
VAHUi, t = Value Added Human Capital by bank i in period t,
STVAi, t = Bank’s Structural Value Added in period t,
ASETi, t = Natural logarithm of total bank assets i in period t,
SHARi, t = Bank market share i in period t,
ei,t = error term of bank i in period t.
The main objective of this study is to develop a model of bank efficiency using the SFA and DFA approaches and, then, estimate (with both methods) the effect of efficiency on the bank stability variable. In line with the objectives, we used two methods, namely, descriptive and causal research. The descriptive approach seeks to explain the empirical facts from the object under study based on the research data obtained (
Variable Operationalization
The independent and dependent variables in the hypotheses developed in Section 2 will be empirically tested as follows:
Population and Samples
The unit of analysis in this study is commercial banks and the population is composed of conventional and shari'ah commercial banks. All these commercial banks were registered with the Financial Services Authority (OJK) between 2006 and 2017 and listed in the Commercial Bank Publication Financial Report on the OJK website.
The population and samples were grouped based on their core capital into four BUKU (Commercial Bank Based on Business Activities) groups applying the following criteria:
1. Core Capital ˂ Rp. 1 trillion: BUKU I
2. Rp. 1 trillion Inti Core Capital ˂ Rp.5 trillion: BUKU II
3. Rp 5 trillion ≤ Core Capital ˂ Rp 30 trillion: BUKU III
4. Core Capital ≥ Rp. 30 trillion: BUKU IV
(
The test results of Fixed Effect Panel Regression Model 1 can be used to explain bank efficiency from the perspective of intellectual capital, bank size, and bank concentration. This model shows that the year-to-year effect of independent variables is influenced by individual bank differences. (see Table 2 and 3).
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C | 79.10465 | 5.680806 | 13.9249 | 0 |
VAIC | -0.55624 | 0.014676 | -37.9005 | 0 |
ASET | -2.07161 | 0.336701 | -6.15267 | 0 |
SHARE | -0.105623 | 0.05265 | -2.00615 | 0.0457 |
Effects Specification | ||||
Cross-section fixed (dummy variables) | ||||
Weighted Statistics | ||||
R-squared | 0.975383 | Mean dependent var | 267.9699 | |
Adjusted R-squared | 0.96902 | S.D. dependent var | 226.2633 | |
S.E. of regression | 7.435473 | Sum squared resid | 17968.03 | |
F-statistic | 153.3009 | Durbin-Watson stat | 1.966779 | |
Prob(F-statistic) | 0 | |||
Unweighted Statistics | ||||
R-squared | 0.877369 | Mean dependent var | 85.86276 | |
Sum squared resid | 19151.07 | Durbin-Watson stat | 2.03978 |
Dependent Variable: BOPO | ||||
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C | 134.468 | 13.05006 | 10.30401 | 0 |
VACA | -13.8768 | 1.476568 | -9.39801 | 0 |
VAHU | 0.573856 | 0.013917 | 41.23329 | 0 |
STVA | -32.6422 | 12.39345 | -2.63383 | 0.0088 |
ASET | -0.98242 | 0.240388 | -4.08681 | 0.0001 |
SHARE | -0.13483 | 0.009217 | -14.6274 | 0 |
Effects Specification | ||||
Cross-section fixed (dummy variables) | ||||
Weighted Statistics | ||||
R-squared | 0.994671 | Mean dependent var | 332.8031 | |
Adjusted R-squared | 0.993252 | S.D. dependent var | 467.5631 | |
S.E. of regression | 7.057711 | Akaike info criterion | 5.081633 | |
Sum squared resid | 16089.04 | Schwarz criterion | 5.933842 | |
Log likelihood | -954.735 | Hannan-Quinn criter. | 5.41879 | |
F-statistic | 701.0701 | Durbin-Watson stat | 1.948339 | |
Prob(F-statistic) | 0 | |||
Unweighted Statistics | ||||
R-squared | 0.896975 | Mean dependent var | 85.86276 | |
Sum squared resid | 16089.21 | Durbin-Watson stat | 2.077325 |
Intellectual capital proxied by VAIC shows that intellectual capital can partially improve bank efficiency. However, it can be seen that larger numbers of assets actually make banks more inefficient. When viewed from the perspective of market share, credit market share has a positive effect on efficiency. This shows that, as a result of greater market dominance, banks operate efficiently.
The positive effect of intellectual capital proxied by VAIC indicates that high intellectual capital encourages banks to behave efficiently. This is in line with the research findings of
Some findings show the positive effect of intellectual capital on efficiency in banking in Indonesia. In accordance with the Surat Keputusan Direksi Bank Indonesia Nomor 31/310/1999 (
In addition to intellectual capital, bank size was found to have a negative effect on bank efficiency. This shows that greater total assets owned by commercial banks in Indonesia make them unable to operate efficiently. This finding contradicts those of
These negative effects of asset size on bank efficiency further support the idea that, in the era of digital banking services, the need for physical assets has shifted towards intangible assets, such as intellectual capital. This is in line with the theory of RBV, where the necessary resources have several characteristics.
The present study also found that market share has a positive effect on bank efficiency. This means that, when banks have a greater market share, they are encouraged to behave more efficiently. This is in line with the view of Claessens and Laeven (2004).
This finding also supports the SCP theory, which explains the linear relationship between market share and bank behavior. Banks can certainly obtain economic benefits if they are able to carry out their operations in an efficient way.
In addition to describing how efficiency changes are seen from VAIC as a whole, this study also defines how each component in VAIC affects bank efficiency, bank size, and bank market structure. The results of the panel data regression analysis with EViews in Model 2 are detailed below.
Table 3 shows that each component of intellectual capital (i.e., VACA, VAHU, and STVA) has a significant effect on bank efficiency. VACA, a representation of physical capital, has a negative effect on efficiency. This shows that physical capital creates a large burden if banks are not able to manage it. A large burden combined with management inability will make a bank inefficient.
VAHU shows how much value added is generated from the funds spent on employees. Table 3 indicates that VAHU has a positive effect on bank efficiency. Therefore, banks should allocate funds for employee education and training so that their employees have adequate knowledge to do their work. Increased employee knowledge will certainly benefit banks in order to increase efficiency.
STVA represents the value added generated if, while carrying out their work activities, employees have the ability to build good networks, which refer to networking between employees and relationships with consumers and stakeholders. According to
As can been seen in Table 3, bank size and market share produce the same results; they are equally significant and have a negative impact. Thus, it can be concluded that Models 1 and 2 do not exhibit a meaningful change when the VAIC model is calculated as a whole or partially per component. This is in line with the findings of researchers in the field of intellectual capital who conducted 2-stage modeling, including
Three conclusions can be drawn from the findings of the present study and the results of the panel data analysis of Models 1 and 2:
1. The panel data analysis of the first model reports a significant effect of intellectual capital, bank size, and market share on the efficiency of commercial banks in Indonesia.
2. The second model shows a significant effect of VACA, VAHU, STVA, bank size, and market share on the efficiency of commercial banks in Indonesia.
3. The first and second models show no difference in the effects on independent variables when intellectual capital is calculated as a whole or only analyzed individually per component.
The results of this study indicate that intellectual capital and its components consistently affect bank efficiency. The company size and market share of banks also have the same effect.
Consequently, banks should make continuous efforts to improve their human resources and develop employee knowledge as much as possible with measurable effects on the output of their work. Likewise, banks with large assets need to pay attention to the optimization of assets so that they do not have implications for the operational burden on the bank. This study also opens up some opportunities for further studies to examine the interaction of intellectual capital, bank size, and market share in relation to bank efficiency. This study also opens up some opportunities for further studies to examine the interaction of intellectual capital, bank size, and market share in relation to bank efficiency measured using methods such as Data Envelopment Analysis (DEA).