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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 study explores, first, the performance effect (accounting- and market-based performance) of intellectual capital (IC), measured using the value-added intellectual coefficient (VAIC) and its modified version (MVAIC), on Islamic and conventional listed banks in Gulf Cooperation Council (GCC) countries and, second, whether Islamic banks outperform conventional banks in utilising IC.

Using resource-based view theory and literature reviews, regression analyses are conducted on data for the period 2012–2019 on 26 Islamic and 42 conventional banks. For hypothesis testing, the generalised method of moments panel data regression analysis is applied after addressing endogeneity issues.

Results, after controlling for corporate governance, indicate that the performance effects of IC (VAIC and MVAIC) on both bank types largely converge and Islamic banks do not outperform conventional banks in IC use. IC has a stronger effect on accounting performance measures for conventional banks than for Islamic banks, but IC has some effect on market performance measures for Islamic banks alone. Corporate governance variables do not play a significant role in the presence of VAIC and MVAIC although there are differences in corporate governance between the two bank types.

This study bridges the gap in GCC banking sector literature on the association between IC efficiency and performance measures of Islamic and conventional banks, from a comparative perspective. It enhances understanding, about the IC–financial performance nexus, of policymakers, regulators, bank managers and other stakeholders interested in the influence of different business models, financing/investment methods and governance structure on the performance of both bank types.

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.

This study seeks to understand the nexus between intellectual capital and profitability of healthcare firms in India with interaction effects.

Relevant data were extracted from the Centre for Monitoring Indian Economy (CMIE)'s Prowess database for a period of ten years 2009–2018 for a sample of 84 selected firms from the healthcare industry. This study uses value added intellectual coefficient (VAIC) and modified value added intellectual coefficient (MVAIC) as a measure of intellectual capital. Further, the study employs panel regression techniques to explore the relationship between intellectual capital and profitability.

The empirical findings reveal that the intellectual capital coefficient of healthcare firms in India averages 2.7757. It is also observed that a majority of the healthcare firms' intellectual capital coefficient is below the industry average. From the regression analysis, it is evident that the intellectual capital coefficient is positively related to the profitability of healthcare firms in India. As far as the components of intellectual capital coefficient are concerned, the capital employed coefficient (CEC) is the only component driving the profitability of healthcare firms in India. A further introduction of interaction terms improves model explainability and moderates the impact of the predictor variable on the response variable. Furthermore, it is observed that the intellectual capital coefficient of the healthcare industry is immune to changes in political regimes in India.

The findings reveal that intellectual capital is an important driver of corporate performance, thus healthcare firms in developing economies like India need to enhance their intellectual potential. Therefore, corporates and governments in developing economies should stimulate investments in developing intellectual capital for enhanced corporate performance and economic growth. Thus, this study might be used as a reference by policymakers while drafting the future policy for the development of intellectual capital in general and healthcare sector specifically.

This is among the first few studies to explore such an empirical relationship for healthcare firms in India and among the few studies of this kind across the globe. It also makes novel contributions in considering interaction variables and seeking the consistency of results across different political regimes. However, the study examines one nation and one industry; thus, the generalisation of findings requires caution.

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 explore and compare the extent of intellectual capital (IC) and its four components among ASEAN countries, and examine the relationship between firms’ IC, market value, and financial performance.

The study uses the data of 213 technology firms listed on five ASEAN stock exchanges. Pulic’s Value Added Intellectual Coefficient model is modified by adding an extra component, namely, relational capital efficiency (RCE). The Kruskal-Wallis one-way ANOVA and multiple regression analysis have been utilized to test the hypotheses.

The results reveal that there is no significant difference in Modified Value Added Intellectual Coefficient (MVAIC) across five ASEAN countries; however, firms in each country tend to place a different degree of emphasis on components of MVAIC to generate corporate value. The results further indicate a positive relationship between IC and market value, confirming that firms with greater IC tend to have greater market value. Likewise, a positive relationship between IC and financial performance measures is confirmed. Specifically, IC is found to be positively associated with margin ratio and return on assets. Capital employed efficiency and human capital efficiency are found to be the most influential value drivers for both market value and financial performance while structural capital efficiency and relational capital efficiency possess less importance.

This study contributes to the IC literature by expanding our knowledge of IC in the emerging economies, and providing a national comparative IC research when such research is limited.

Value-added intellectual coefficient (VAIC) is extensively used as a measure of intellectual capital (IC), but it is criticized for not capturing the totality of IC. Therefore, this study aims to analyse critiques of the original VAIC and proposes a modified VAIC by adding missing IC components and adjusting for exogenous factors. The study uses a modified VAIC model to investigate the relationship between IC, firm performance (FP) and market value (MV) for US non-financial firms.

This study employed fundamental data of US non-financial firms listed on the NYSE and NASDAQ from 1980 to 2019. A final sample consisted of 6,019 firms and 62,686 firm-year observations.

The results provide a significant positive effect of aggregate and components of modified VAIC on FP and MV. Moreover, results validate the modified VAIC model and find that the modified VAIC explains changes in shareholders' MV. In addition, findings indicate that modified VAIC serves as an additional intangible factor to explain firms' capital structure decisions.

The findings have important implications for management, owners, researchers and investors.

The modified VAIC model differs from the original VAIC model in four ways: first, it corrects the measurement of structural capital efficiency (SCE) following the accounting principle. Second, it replaces SCE with innovation capital efficiency (InVCE) and relational capital efficiency (RCE) to account for missing components of information of structural capital (SC). Third, the modified VAIC model adjusts for exogenous factors like business cycles and cross-industry variations. Finally, with the addition of InVCE and RCE as components of SCE, innovation capital (InVC) and relational capital (RC) are added to the calculation of value-added (VA) as components of IC.

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 debate on the determinants of firm value is ongoing; and the increasing gap in the book‐to‐market ratio (Lev & Sougiannis 1999) has yet to be explained in the financial literature. This article contributes to the debate by examining whether intellectual capital measured using the value added intellectual coefficient (VAICTM) (Pulic 1998) contributes to the explanation of the book‐to‐market ratio. This study used Ohlson’s 1995 valuation model and JSE Securities Exchange (SA) (JSE) data in an attempt to identify whether the book value of assets, accounting (accrual) earnings and VAICTM explain the behaviour of South African share prices. The panel data least squares model results indicate a significant relationship between share prices three months after year end, and abnormal earnings, abnormal cash dividends, book value of assets, the capital employed coefficient, and the human capital coefficient.

In developed countries, banks are perceived to accumulate a higher level of intellectual capital than firms in other sectors. However, this perception has not been considered or tested in the context of an emerging market such as Vietnam, which has one of the most dynamic economies in the Asian region. This study estimates and compares the level of accumulation of intellectual capital and its four components by financial and nonfinancial firms in Vietnam. Furthermore, this study examines the relationship between intellectual capital and its components and the performance of financial and nonfinancial firms.

This study uses data collected from the annual reports of 75 financial and 75 nonfinancial firms in Vietnam from 2011 to 2018. A modified value-added intellectual coefficient model is adopted to measure the level of intellectual capital at firms. Various aspects of intellectual capital are considered, including the efficiency of human capital, structural capital, capital employed and relational capital. In addition, the generalized method of moments is used to ensure the robustness of the findings.

Findings in this study indicate that financial firms in Vietnam have accumulated a higher level of intellectual capital than nonfinancial firms. In addition, intellectual capital contributes positively to financial firms' performance. Three components of intellectual capital – structural capital efficiency, capital employed efficiency and relational capital efficiency – positively affect performance by financial firms.

This study is limited to financial and nonfinancial firms in Vietnam. Empirical studies in the future should incorporate the efficiency aspects of these types of firms because different industries might have different characteristics, in particular, their current efficiency level, which might cause differences in relation to the accumulation of intellectual capital.

The findings of this study provide valuable evidence and implications for executives and policymakers in creating, managing and enhancing intellectual capital within the Vietnamese context, in particular in the financial sector.

To the best of our knowledge, this is the first empirical study conducted in the context of Vietnam, with the following two objectives: (1) to measure and compare the level of accumulation of intellectual capital by financial and nonfinancial firms in Vietnam; and (2) to examine the contribution of intellectual capital and its components to the performance by financial and nonfinancial firms in Vietnam.