Measuring national intellectual capital: a novel approach

Vo, Duc Hong; Tran, Ngoc Phu

doi:10.1108/jic-06-2020-0183

Cited by 21 publications

(63 citation statements)

References 51 publications

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“…It is generally accepted that intellectual capital is not easily identified, captured and reported in financial statements. Academic studies often divide intellectual capital into two to four dimensions of intangible assets (Vo and Tran, 2021;Dzenopoljac et al, 2017;Hayton, 2005). Different models are proposed to measure intellectual capital in different disciplines, such as accounting, economics, finance, human resources, psychology and strategy.…”

Section: Literature Review 21 Definition and Measurement Of Intellectual Capitalmentioning

confidence: 99%

Intellectual capital and bank performance in Vietnam

Tran

2021

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PurposeFor the past two decades, intellectual capital has played an increasingly important role in firm performance around the world. However, the importance of intellectual capital in Vietnam, and especially in the banking sector, has largely been ignored in the literature. This study is the first to examine the effect of intellectual capital on bank performance in Vietnam. In this paper, intellectual capital is decomposed into three components: (1) capital employed efficiency, (2) human capital efficiency and (3) structural capital efficiency.Design/methodology/approachThe paper uses an unbalanced panel dataset on 14 listed banks in Vietnam for the period 2009–2018 for which required data are available, with the generalized method of moments.FindingsThe findings indicate that intellectual capital contributes significantly and positively to bank performance in Vietnam. In addition, bank performance is driven primarily by capital employed efficiency. Although human capital efficiency appears to contribute positively to bank performance, the effect on bank performance appears to be marginal.Originality/valueThe literature review indicates that the effect of intellectual capital on bank performance is mixed. This effect can be positive or negative or even show a U-shaped relationship. The effects of intellectual capital on firm performance are not consistent, depending on factors such as the quantitative technique and sample used. As such, this paper extends analysis of Vietnam to cover the 10-year period from 2009 to 2018. The literature review reveals that the contribution of intellectual capital to bank performance has largely been ignored in the context of Vietnam. Studies have been conducted on the Gulf countries, such as Buallay et al. (2020). However, because the context in Vietnam differs from that of the Gulf countries, their experience might not be relevant to Vietnam. Vietnam is an emerging market in Southeast Asia, whereas Gulf countries have high income levels. So, it is necessary to examine direct evidence on Vietnam.

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Section: Literature Review 21 Definition and Measurement Of Intellectual Capitalmentioning

confidence: 99%

Intellectual capital and bank performance in Vietnam

Tran

2021

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“…Structural capital is another important dimension of RIC [10,47]. The information and digital revolution have established new ways of learning and communication in the world [42], creating enormous opportunities for regional development. In this context, technology and infrastructure have gained considerable attention.…”

Section: Literature Review 21 Components Of Intellectual Capitalmentioning

confidence: 99%

A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

Liu

Jiang

et al. 2021

Mathematics

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With the dawn of economic globalization and the knowledge economy, intellectual capital has become the most important factor to determine economic growth. However, due to resource endowment, location conditions, policy differences, and other factors, provinces in China show sizeable differences in regional intellectual capital (RIC), which affects the coordinated development of the regional economy. Evaluating RIC is a typical multiple-criteria decision-making (MCDM) problem. Therefore, this study employs a set of MCDM techniques to solve this problem. First, the Delphi method is used to determine the formal decision structure based on a systematic literature review. A novel hybrid method, namely, the Grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP), i.e., GDANP, is employed to obtain the relative weight of each criterion. Finally, based on the data of 31 provinces in China, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is used to evaluate the RIC. According to the questionnaires filled out by an expert panel, we establish an evaluation index of RIC with 21 criteria. Based on the results of empirical study, the level of RIC in different regions in China is quite different. Furthermore, the RIC ranking is largely consistent with the provincial gross domestic product (GDP) ranking, in line with the current status of development in the regions. Indeed, this paper shows that the proposed hybrid method can effectively measure the level of RIC.

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“…However, albeit imperfect [ 5 ], estimate the shadow economy size for various countries worldwide. In addition [ 6 ], has recently developed the index of national intellectual capital (INIC) for many countries globally. This pioneering index is generally considered advanced and suitable for international comparison.…”

Section: Introductionmentioning

confidence: 99%

“…A potential explanation for this lack of empirical evidence is that national intellectual capital is a fuzzy concept [ 15 ]. More importantly, measuring national intellectual capital is limited and incomparable across countries because of data limitations and significant judgement [ 6 ]. Nevertheless, the established literature has considered that national intellectual capital affects economic growth [ 15 , 16 ], which affects shadow economy size [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

“…The main objective of this study is to examine the effects of national intellectual capital on the shadow economy across countries globally. To achieve our objective, we apply the index of national intellectual capital (INIC) developed by [ 6 ] to measure the level of national intellectual capital. A sample of 8 ASEAN countries is used during the 2000–2017 period.…”

Section: Introductionmentioning

confidence: 99%

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Does national intellectual capital matter for shadow economy in the Southeast Asian countries?

Tran

Nguyen

et al. 2022

PLoS ONE

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Understanding the determinants of the shadow economy plays a vital role in formulating policies for economic growth and development, particularly for the Southeast Asian countries–a new economic force for a global economy. The key drivers of a shadow economy, such as institutional quality, taxation, government expenditure, are widely examined. However, the effect of national intellectual capital, which affects macroeconomic indicators, on the shadow economy has largely been ignored in the existing literature. Our paper examines this critical link and its causality relationship for eight Southeast Asian countries from 2000 to 2017. This paper uses the dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS), which allow cross-sectional dependence and slope homogeneity in panel data analysis. Empirical findings from this paper indicate that national intellectual capital impacts negatively and significantly the shadow economy size. This finding implies that enhancing national intellectual capital reduces the shadow economy size. These two forces lead to enhanced economic growth. Our Granger causality tests confirm a bi-directional relationship between national intellectual capital and the shadow economy. As a result, policies targeted to reduce the shadow economy size can now include the accumulation of national intellectual capital, particularly for Southeast Asian Countries.

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Measuring national intellectual capital: a novel approach

Cited by 21 publications

References 51 publications

Intellectual capital and bank performance in Vietnam

Intellectual capital and bank performance in Vietnam

A Hybrid Multiple Criteria Decision-Making Technique to Evaluate Regional Intellectual Capital: Evidence from China

Does national intellectual capital matter for shadow economy in the Southeast Asian countries?

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