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This paper aims to address empirical analyses of the association of the VAIC and its components with firms’ market and financial performance, demonstrating that the ill definition of variables and constructs is responsible for a non-linearity concealed in the VAIC formula between two of its components (the Structural Capital Efficiency and the Human Capital Efficiency).

Through a conceptual analysis the paper identifies and formalises the non-linearity concealed in the VAIC formula and clarifies the relevant issues through an empirical analysis of a sample of Italian listed companies.

The paper finds that the non-linearity hidden in the VAIC formula should lead scholars to completely revise the ways they test the association of the VAIC and the market and financial performance of the firm. Useful insights are also provided for scholars interested in investigating the role of human capital, for those involved in analysing the interrelations among capitals through the introduction of interaction terms in their regression models and for researchers proposing modified versions of the VAIC. Practitioners could benefit from the paper as the non-linearity here discovered leads to a substantial of the decision-making based on the VAIC.

The paper offers new insights into analyses using the VAIC as it uncovers a non-linearity hidden in the VAIC, which has hitherto not been reported in the literature. The existence of this non-linearity has substantive implications for previous and future research in this domain.

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.

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 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.

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 paper is to study the relationship between intellectual capital (IC) and performance of pharmaceutical firms in India. The secondary objective is to propose and test modified models of Value Added Intellectual Coefficient (VAIC™) method.

Data on 22 large pharmaceutical firms collected for empirical investigation. Return on assets and return on sales are performance variables. IC and its components – human capital, structural capital and relational capital (RC), are predictor variables. Three extended and modified VAIC™ models (e-VAIC™) are proposed. Multiple regression technique is applied on pooled data to draw inferences.

Results show instances of positive relationship between IC and performance variables. RC, the new variable, does not demonstrate statistically significant relationship with performance variables.

Due to inadequate reporting of IC and its components, availability of data on various proxies is difficult. The new models proposed in this paper can be a template for future research and model development.

VAIC™ model, the proposed models (e-VAIC™) and the result analysis can be useful for evaluation and value creation purposes.

Previous researchers use original VAIC™ model. This paper modifies and extends the model in accordance with contemporary description and typology of IC. Inclusion of RC as a variable in VAIC™ model and use of new proxies for components of IC are the novelties of this paper.

The purpose of this paper is to propose an extended and modified value-added (VA) intellectual coefficient (VAIC) model, which includes intellectual capital (IC) components which were missing in the original VAIC approach. The proposed model has been used to explore the relationship between IC and firm performance for Turkish manufacturing firms on a more detailed level.

Multiple regression analysis has been employed to identify the IC components, which predict the performance of the firm and the moderating effect of some IC components on IC components–firm performance relationship. Data are required to calculate the IC components, and firm performance variables have been obtained from the financial reports of the Turkish manufacturing firms for the period 2003–2013.

According to the results for Turkish manufacturing sector innovation capital efficiency has a moderating effect on the relationship between structural capital efficiency (SCE) and profitability, meaning, depending on an increase in R&D expenses, the effect of SCE on profitability also increases. On the other hand, it has been found that innovation capital efficiency has a direct impact on firms’ productivity. The results also showed that IC efficiency components have a moderating role on the relationship between capital employed efficiency and profitability.

There might be a time lag until the effect of R&D investments can be observed in firms’ performance. However, this lagged impact of innovation capital and also other IC components on future firm performance has not been investigated due to concerns related to sample size.

The proposed model differs from the original VAIC model in three ways: it, namely, includes two additional IC components, customer capital (CC) and innovation capital. It explores the moderating effect of innovation capital on structural capital–firm performance relationship and the moderating effect of IC components on employed capital–firm performance relationship. As the last difference, it proposes an alteration in the VA calculation due to newly added IC components, CC and innovation capital.

Intellectual capital (IC) has been recognized in improving the efficiency of businesses and gaining competitive edge in the developed world. The present study offers perspectives into the effect of IC on the efficiency of the Indian financial sector companies.

For the purpose of evaluating efficiency, the research has used stochastic frontier analysis (SFA). All Indian financial sector companies listed in National Stock Exchange (NSE-500) for the timeframe of ten years (2008–2018) have been considered. The paper has employed modified Pulic's Value Added Intellectual Coefficient (VAIC^TM) as a proxy to measure IC. Correlation and panel data regression have been used in order to examine the relationship.

The results of the study indicate positive and significant relationship between IC and efficiency of the firm. The results also show that all the components of IC, that is, human capital, relational capital, process capital and capital employed have a significant impact on firms' efficiency. Additionally, it has been seen that sample companies do not invest in research and development leading to no innovation capital.

The research will assist managers in managing and controlling the IC, investors in matters related to investment and financial experts in improving the company's IC and value creation.

The current research is one of the pioneering studies in the context of Indian financial sector that examines the impact of modified VAIC on operational efficiency calculated using SFA.

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 paper is to examine whether information on intellectual capital (IC) is value relevant for investors and the role played by the single components of IC (human capital, organizational capital, relational capital) in creating firm value.

The 1995 Ohlson model has been employed to investigate the relationship between the current accounting measures (book value and earnings) and future measures of profitability, proxied by IC. The Value Added Intellectual Coefficient (VAIC™) approach is used to determine the firm's efficiency in using IC resources. The sample analysis analyzed is constituted of financial sector companies listed on the Italian Stock Exchange for the period 2006‐2008.

The findings fully confirm the existence of a positive relationship between accounting values and market value on the one hand and IC components as measured by VAIC™ and market value on the other. Results show that investors attach more value relevance to human capital efficiency (HCE) than to structural capital efficiency (SCE) and that HCE plays an indirect role in the relation between IC and market value.

The paper is focused on one sector (financial) and one country (Italy). The focus on the entire financial sector allows the authors to validate results from an Italian perspective and to extend them for similar banking structures in other countries, and to favor comparisons with other similar studies.

The main implications for financial company managers are that, when developing a strategy aimed at strengthening IC, they should consider that human capital plays an indirect part with regard to the other components and that each investment in one of the IC subcategories should not be evaluated in isolation but in relation to its interactions.

The paper realizes a fusion between value relevance and IC literature. To the best of the authors' knowledge, this is the first paper that examines the relationship between VAIC™ and the market value of the Italian financial sector, using an Ohlson model modified to include IC information, comprehensive of the human capital indirect effect.