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The aim of this paper is to propose extended intellectual capital (IC) indicators. The study shows that the essence of IC in the context of value is residual income, its growth rate and growth rate of equity taken together. It allows creating IC measures (modified residual income and economic value added of equity) that contain these components. The study investigates the relationship between IC and market value for Russian public firms.

The authors propose modified residual income and modified economic value added of equity as IC metrics. This study tests a relationship between market value and IC to investigate suggested metrics. Static and dynamic panel data models are used. 25 companies from the MOEX Russia Index were included in the study. The study covers the period from 2014 to 2018.

The findings show a strong positive relationship between market value and IC. The results confirm that extended IC measures have a stronger connection to market value.

Firstly, these results benefit managers. They can use proposed extended IC measures as targets for the company when planning business strategy and generating business environment. Secondly, suggested IC measures can help shareholders and investors achieve their long-term goal – wealth maximization.

The value of this article is the development of IC theory and valuation. The proposed measures differ in the way that they consider the growth rates – the main determinants of value along with efficiency.

The purpose of this study is to analyse the validity of the value added intellectual coefficient (VAIC) method as an indicator of intellectual capital.

The paper describes VAIC through its calculation formulae and aims to establish what exactly it is that the method measures. It also looks in detail at how intellectual capital is understood in the method, and discusses its conceptual confusions. Furthermore, the paper tests the hypothesis according to which VAIC correlates with a company's stock market value, and reflects the contradictory results of earlier studies.

The analyses show, first, that VAIC indicates the efficiency of the company's labour and capital investments, and has nothing to do with intellectual capital. Furthermore, the calculation method uses overlapping variables and has other serious validity problems. Second, the results do not lend support to the hypothesis that VAIC correlates with a company's stock market value. The main reasons behind the lack of consistency in earlier VAIC results lie in the confusion of capitalized and cash flow entities in the calculation of structural capital and in the misuse of intellectual capital concepts.

The analyses show that VAIC is an invalid measure of intellectual capital.

The result is important since the method has been widely used in micro and macro level analyses, but this is the first time it has been put to rigorous scientific analysis.

The purpose of this paper is to analyze the role of intellectual capital (IC) and its relationship with financial performance of Iran insurance companies during the period 2005‐2007.

In total, 39 insurance companies were selected as the sample. Regression model (partial least squares) has been applied to examine the relationship between IC and companies' return on assets ratio (ROA).

The results of the research revealed that value added intellectual capital and its components have a significant positive relationship with companies' profitability.

The VAIC™ method could be an important means for many decision makers to integrate IC in their decision‐making process, which allows insurance companies to benchmark themselves according to the IC efficiencies and develop strategies to enhance their company's performance.

This is the first research, which has used the data on value added recently calculated and published by Iran insurance firms in the “Value Added Scoreboard”.

The purpose is to analyze the impact of intellectual capital (IC) on export performance of firms and industries.

This research used value added intellectual coefficient (VAIC) to measure intellectual capital as an independent variable. An export performance, as dependent variable, was measured as growth of exports. The sample consisted of 134 firms in Bosnia and Herzegovina (B&H). Empirical analysis was done by linear regression analysis.

The results of regression analysis show a significant (p<0.01), positive influence of the value added intellectual coefficient and its components on the export growth in the sector of food and beverages and manufacturing of furniture and wood products in B&H. For other sectors there is no significant relation of independent and dependent variable.

The results correspond with the results of the EU project that determined competitive advantages of B&H by Michael Porter's methodology. Results of this research raise the possibility of further testing of the author's methodology, called the measurement of intellectual capital in export performance (MICEP) methodology, in determining the competitive advantages, because it took considerably less time and money than EU project methodology. Also, a strong influence of IC on the export performance of sectors with competitive advantages opens the way for industrial policies based on intellectual capital, not only in B&H, but in other countries.

This is the first research that has measured the impact of intellectual capital on export performance by using the VAIC methodology.

The purpose of this paper is to analyse the role of value added (VA) as an indicator of intellectual capital (IC), and its impact on the firm's economic, financial and stock market performance.

The value added intellectual coefficient (VAIC™) method is used on 300 UK companies divided into three groups of industries: high‐tech, traditional and services. Data require to calculate VAIC™ method are obtained from the “Value Added Scoreboard” provided by the UK Department of Trade and Industry (DTI). Empirical analysis is conducted using correlation and linear multiple regression analysis.

The results show that companies' IC has a positive impact on economic and financial performance. However, the association between IC and stock market performance is only significant for high‐tech industries. The results also indicate that capital employed remains a major determinant of financial and stock market performance although it has a negative impact on economic performance.

The VAIC™ method could be an important tool for many decision makers to integrate IC in their decision process.

This is the first research which has used the data on VA recently calculated and published by the UK DTI in the “Value Added Scoreboard”. This paper constitutes therefore a kind of validation of the ministry data.

The purpose of this paper is to estimate the economic (namely cost, revenue and profit) efficiency and its association with intellectual capital of 37 BSE-listed Indian banks over the period 2005–2018.

This study employs truncated Tobit regression to compute the relationship between intellectual capital and estimated cost, revenue and profit efficiency using Data Envelopment Analysis (DEA) for the 37 BSE-listed Indian banks within the panel data framework.

Estimates suggest that banks’ overall annual average cost, revenue and profit efficiency are 0.4466–0.7519, 0.4825–0.8773 and 0.4905–0.8803, respectively, during the sample period. Further, Tobit regression results indicate that the aggregate intellectual capital (value-added intellectual coefficient or Modified Value-added Intellectual Capital) has a positive but minimal impact on these efficiency parameters at 1 percent significance level for the overall sample as well as public sector banks. Among all the sub-components of intellectual capital, human capital, structural capital and relational capital have a positive and moderate impact on these efficiency measures for the overall sample. Control variables, particularly bank size, are significant drivers of the estimated efficiency of banks.

Findings suggest that banks should invest adequately to enhance their overall intellectual capital to further augment these economic efficiency measures in the long run.

This study computes cost, revenue and profit efficiency of 37 BSE-listed banks based on DEA followed by intellectual capital using the Pulic approach (1998 and 2000) and the Bontis (1998) approach in the first stage. Later, it examines the dynamics between the computed efficiency parameters and intellectual capital using Tobit regression within the panel data framework.

This paper investigates the impact of intellectual capital and its components on slack-based technical efficiency (SBM-TE) of banks.

Data envelopment analysis is used to compute SBM-TE scores and the Value-Added Intellectual Coefficient (VAIC™) model is used to measure intellectual capital. An unbalanced panel of 32 banks that operated from 2000 to 2017 has been used.

Overall, the efficiency scores are averaged at 79%, suggesting that an inefficient bank needs to enhance technical efficiency by 21% to be at par with the best performing banks. Beta-convergence and sigma-convergence exist among banks with faster speed evident among listed and local banks. Intellectual capital has a positive impact on SBM-TE and human capital is the main driver of technical efficiency among banks. This result is specifically evident among non-listed banks and foreign banks. Economies of scale property are also evident among the banks. Competition and asset tangibility inhibit technical efficiency among banks.

Banks are advised to invest in value-adding emerging technologies and their employees so as to enhance their efficiency. The study offers insights for policymakers, practitioners and researchers in emerging markets.

The study is premier in employing the SBM-TE to explain the intellectual capital and efficiency nexus, as well as, testing for both beta-convergence and sigma-convergence.

The purpose of the paper is to obtain measure of the intellectual capital (IC) performance of quoted banks on the Istanbul Stock Exchange Market (ISE) in Turkey for the period 1995‐2004 and test the effect of the intellectual capital performance on profitability.

Data required for calculating intellectual capital efficiencies were obtained from the ISE for the period 1995‐2004. The authors measured the intellectual capital performance of quoted banks in ISE using the efficiency coefficient, called Value Added Intellectual Coefficiency (VAIC^TM), and tested the effect of this intellectual capital performance on profitability using Data Envelopment Analysis (DEA). In addition, three different portfolios were constructed based on three different inputs to observe the effect of the intellectual capital on investors' behavior.

The effect of intellectual capital on profitability on the banking sector on the ISE was calculated as 61.3 percent on average and Portfolio‐1, which uses the intellectual capital measure as an input, yields the highest returns among the three portfolios constructed.

The study was applied only to quoted banks on the ISE for the period 1995‐2004.

The findings allow the banks to benchmark themselves based on the level of IC efficiency ranking, which is important for the banking sector to develop a strategic plan for their future performance. It may also be deduced that intellectual capital is an important factor for investors.

This paper can be considered as one of the most comprehensive studies on testing the effect of intellectual capital performance on profitability in the banking sector using both VAIC and DEA.

The purpose of this paper is to examine the impact of intellectual capital and its components on bank diversification choice.

Both asset and income diversification are computed and an unbalanced panel data set of 32 banks covering the period 2000–2015 have been used. The panel corrected standard error regression has been used to account for serial correlation and heteroscedasticity.

The study found that intellectual capital determines the choice of diversifying. Precisely, intellectual capital motivates asset diversity but it dissuades income diversification. Human capital and structural capital are major components that determine asset diversity decisions. Income diversification decision, in this case to choose a focus strategy, is determined by human capital. This gives credence for the human capital theory in Ghana. Competition encourages a focus strategy. Bank size and leverage enhances income diversification while stock exchange listing and government ownership fosters the focus strategy.

Diversification strategy, knowledge base of staff, corporate governance and internal control have been considered as factors leading to the collapse of some Ghanaian banks in 2017–2018. The study provides relevant insights for regulators, decision support units and corporate boards. Intellectual capital and value added metrics should be used for modelling and decision making as they have value relevance.

This is a premier study that has examined the nexus between diversification strategy and intellectual capital in banks.

The purpose of this paper is to examine the value relevance of intellectual capital (IC) by analysing the relationship between IC efficiency (ICE) and corporate book value of listed firms on main board of Nigeria Stock Exchange.

This study applies the resource-based theory in formulating two hypotheses that guide the results analysis. By employing a two-step dynamic system generalised method of moments (GMMs), and controlling for the possible endogeneity effect on the parameters estimated, for a sample of 91 listed firms on main board of Nigeria Stock Exchange, this study investigates the association of ICE and corporate book value, namely, cash flow from operation and economic value added (EVA), using data over the 2010 to 2014 financial years.

The results show a significant positive relationship between overall ICE and corporate book value (cash flow from operation and EVA). This study contributes to recent evidence concerning the value relevance of IC information to investors and other interested stakeholders.

The generalisation of the results to smaller firms, in the alternative securities market, may be inappropriate as study sampled listed firms on the main board of Nigerian Stock Exchange.

Those charged with governance should be concerned with the investment and management of IC as it enhances the economic value and operating cash flow in line with the resource-based theory.

This study is first to consider the ICE study across all sectors in the Nigerian economy using modified Pulic value added intellectual capital. The study controls for heteroscedasticity and endogeneity issues by adoption of two-step dynamic system GMMs.