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Purpose: Consensus on how intellectual capital (IC) affects corporate performance is limited because of various measurement models of IC and corporate performance. This study thus aims to further the debate on the relationship between IC and corporate performance from the perspectives of nonlinearity, the capital values of IC and the use of a holistic measure of corporate performance. Design/methodology/approach: Using 1,395 firm-year observations derived from Vietnamese listed companies from 2010 to 2018, this study focuses on (1) presenting an IC model benchmarked on value-creating expenses; (2) using a directional distance function (DDF)-based stochastic nonparametric envelopment of data (StoNED) framework to scrutinize multiple performance indicators and the capital values of people, structures and relationships simultaneously; and (3) adopting firm-year cluster-robust regressions to analyze the nonlinear association between IC and corporate performance empirically with an appropriate U test. Findings: Results suggest that human capital (HC), structural capital (SC) and relational capital (RC) are the main contributors of high corporate efficiency, whereas only HC and RC contribute to high corporate profitability. These results are absent when this study employs the conventional data envelopment analysis (DEA), which is also a multidimensional framework, as the dependent variable. More importantly, IC and its components can improve corporate performance, namely, both corporate efficiency and corporate profitability up to a critical point, after which the effects would drop. Practical implications: Overall, this study highlights not only the need to invest in IC but also its associated costs. That is, policymakers also need to note the marginal cost of investing in IC, which may in the end outweigh the benefits from IC. Originality/value: This study extends IC-related studies by investigating the nonlinear relationship between IC and corporate performance. Moreover, the value of this study also lies in the multidimensional DDF-based StoNED framework. [ABSTRACT FROM AUTHOR]

Purpose: The main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA). Design/methodology/approach: It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital). Findings: The univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements. Research limitations/implications: The results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements. Practical implications: Overall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency. Originality/value: First, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms. [ABSTRACT FROM AUTHOR]

Purpose: First, this study assesses firms' efficiency of transforming intellectual capital (IC) components into firm performance. Second, this study examines (1) cubic S-curve relationship between board independence and IC efficiency and (2) how firm size moderates the cubic S-curve relationship. Design/methodology/approach: This study employs a stochastic nonparametric envelopment of data (StoNED) framework to estimate IC efficiency, which is derived from the estimation process of transforming structural, relational and human capitals into accounting- and market-based performance indicators. This study conducts regression analyses on 1,104 firm-year observations of Taiwanese semiconductor firms over the period of 2011–2018. Findings: StoNED results suggest that sample firms' IC efficiency can be relatively improved by approximately 80%. Regression results indicate that a cubic S-curve relationship between board independence and IC efficiency exists, and firm size moderates the nonlinear effects. Practical implications: Overall, this study highlights the importance of examining the nonlinear effect of board independence on IC efficiency from the perspective of agency theory, and the moderating effect from firm size, which may suggest availability of resources from the resource-based view of the firm. Originality/value: This study contributes to the literature through the innovative application of an efficiency-based tool for evaluating IC efficiency. The cubic S-curve relationship between board independence and IC efficiency also points to the policy concerning the appropriate number of independent directors on board. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk measures as an exogenous input in the investment-efficiency stage. Second, the current study examines the relationship between intellectual capital (IC) and banks' efficiencies. Design/methodology/approach: First, this study uses a dynamic network data envelopment analysis approach in investigating the efficiencies of 24 Taiwanese banks in 2007–2018 from two perspectives. Second, this research utilizes various regression techniques, namely, ordinary least squares (OLS), robust least squares and truncated regression, to gauge the impact of IC on banks' efficiencies. Typically, IC is determined based on a monetary value-based measure and value-added intellectual coefficient (VAICTM). Findings: Resource-utilization (investment) efficiencies were observed as 0.941 (0.964), thereby contributing to the mean overall efficiency of the sample banks at 0.952. However, the related efficiency changes decline over the sample period, thereby suggesting that the average banks' efficiencies hardly increase. Regression analyses show a significantly positive relationship between IC and banks' overall resource-utilization and investment efficiencies. Research limitations/implications: Overall, this study suggests that researchers should consider risks when estimating banks' efficiencies owing to their connection to banks' investment performance. From banks' dynamic two-stage efficiencies, this study demonstrated that investments in IC will bring improved future economic benefits. Originality/value: Different from prior studies, this study improves banks' efficiency evaluation models by incorporating risk measures and assuming weighted periods for the 2007–2008 global financial crisis. Moreover, the use of monetary value-based measure of IC provides consistent results as the commonly-used VAICTM does. [ABSTRACT FROM AUTHOR]

This paper researches a method of rating competitiveness involving the estimation of the performance of semiconductor firms through Malmquist productivity index (MPI) and metafrontier Malmquist productivity index (MMPI). Regressions are used to find the relationship between intellectual capital and performance. Overall, technological innovations contribute to the improvement in the integrated circuit (IC) design sub-industry while increases in efficient production allow the IC foundry sub-industry and the IC packaging and testing sub-industry to maintain position. The regression results show human capital was critical to technological innovation while relational capital was important to efficient production. [ABSTRACT FROM AUTHOR]

The purpose of this study is to empirically examine the role of manufacturing in improving innovation efficiency of emerging economies. Emerging economies are developing innovations to promote their industries toward high‐technology sectors to facilitate global competitiveness. Nevertheless, the role of manufacturing is often neglected, which can result in low efficiency in the innovation process. This study constructed a three‐stage innovation model that consists of human capital cultivation, manufacturing development, and innovation production to stress and verify the importance of manufacturing. The experimental results suggest that manufacturing development was a key factor affecting innovation efficiency. A performance improvement strategy map was provided to improve each country's innovation efficiency. [ABSTRACT FROM AUTHOR]