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National intellectual capital is generally considered a strategic advantage for national competitiveness. However, the measurement of intellectual capital across countries for comparison purposes appears to receive little attention. This study aims to use a new index of national intellectual capital (INIC) to examine the relationship between national intellectual capital and national competitiveness.

This paper uses the INIC, developed by Vo and Tran (2021), to measure, compare and contrast differences in the level of national intellectual capital across 104 countries. INIC comprises the most crucial intellectual capital components: human capital, structural capital and relational capital. Various economic and social indicators are used as the proxies for these components of intellectual capital. Principal component analysis is used to derive INIC.

The results indicate that during the study period the level of national intellectual capital gradually increased. Europe has attained the highest level of national intellectual capital, whereas Africa has achieved the lowest level. This study’s findings confirm a close relationship between the national intellectual capital level and the national income level. Among the ten biggest countries, the USA achieved the highest national intellectual capital level, and China has significantly improved its cumulative level. Finland achieved the highest level of national intellectual capital in the world. National intellectual capital enhances a country’s competitiveness.

Findings in this study shed light on an international comparison of intellectual capital across countries and understanding how national intellectual capital contributes to and improves national competitiveness. Policymakers can consider and use these findings to support the accumulation of national intellectual capital and boost national competitive advantage, especially low-income countries and emerging markets.

To the best of the authors’ knowledge, this is the first study to estimate a degree of national intellectual capital around the world and examine its impact on national competitiveness based on publicly available data.

Countries worldwide aim to improve their comparative advantages by efficiently using scarce resources for economic growth and development. While many studies have been conducted to measure intellectual capital at the firm's level, measuring it at the national level has been under-examined. In addition, while the important role of national intellectual capital in economic growth has been theoretically recognized in literature, this important link has largely been ignored in empirical analyses.

This study uses the newly developed index of national intellectual capital from Vo and Tran's (2022) study to examine its effects on national economic growth in the long run. The dynamic common correlated effects technique and the pooled mean group estimation are used on the sample of 23 economies in the Asia–Pacific region from 2000 to 2020.

Findings from this study confirm the positive and significant contribution of the national intellectual capital to economic growth in the region. The authors also find that, as a feedback effect, economic growth will also enhance and improve the accumulation of national intellectual capital.

The findings of this paper provide valuable evidence and implications for policymakers in managing and improving national intellectual capital in the Asia–Pacific region.

To the best of the authors’ knowledge, this is the first empirical study to examine the impact of national intellectual capital on economic growth in the long run in the Asia–Pacific economies.

The studies that explore the impacts of national intellectual capital on informal economy are scant. Moreover, the effect of an external factor such as institutional quality that moderates this relationship has largely been neglected in previous studies. Institutions are considered important pillars to accumulate national intellectual capital and reduce shadow economy. As such, this paper aims to investigate how institutional quality moderates the effects of national intellectual capital on informal economy in 17 Asian countries from 2000 to 2018.

This paper uses the generalized method of moments techniques, which allow cross-sectional dependence and slope homogeneity in panel data, to examine the moderating role of institutional quality on the relationship between national intellectual capital and informal economy. Various tests are conducted to ensure the robustness of the findings.

Empirical findings from this paper indicate that an increase in national intellectual capital and institutional quality declines the informal economy. Interestingly, better institutional quality aggravates the negative effects of national intellectual capital on reducing the size of informal economy. The author also finds that enhancing international trade and economic growth results in a decrease in the informal economy in Asian countries.

Empirical findings offer policymakers an indication of the relationships between national intellectual capital, institutional quality and informal economy, pointing out that national intellectual capital and institutional quality should be strengthened to allow Asian countries to limit the informal economy.

This study provides a conceptual model through which the moderating role of institutional quality on the national intellectual capital–informal economy nexus can be recognized. This approach has thus far not been investigated in the existing literature. To the best of the author’s knowledge, this study makes an original contribution to the empirical of national intellectual capital and informal economy nexus and produces new insights into the fields of the moderating effects of institutional quality on this nexus.

This study examines whether the national innovative city pilot policy (NICP) influences urban entrepreneurship (UE). To examine the underlying causal mechanism, this study modeled the city-level intellectual capital index and financing capacity (FC) in the relationship between NICP and UE.

An empirical model of NICP, intellectual capital, FC and entrepreneurship is conceptualized based on theoretical analysis. Using a quasi-natural experiment of China’s NICP, with a sample of 280 prefecture-level cities in China from 2003 to 2018, propensity score matching with difference-in-differences (PSM-DID) is used to empirically test the NICP’s impact on UE, mediating effects of intellectual capital and moderation effects of FC.

The results show that the NICP can significantly motivate UE. Intellectual capital plays mediating effects on the relationship between NICP and UE. Moreover, the NICP and intellectual capital’s effects on UE are moderated by FC.

This study provides an important reference for promoting UE through intellectual capital and FC in the construction of the NICP.

This is a pioneering study that develops a theoretical model to incorporate NICP, intellectual capital, FC and UE. This paper applies experimental governance theory in innovative urban scenarios, and verifies its applicability and particularity in the Chinese context.

This study develops a robust model to measure intellectual capital efficiency (ICE). It also analyzes ICE across Gulf companies, sectors and countries.

This study uses data envelopment analysis (DEA), the Malmquist productivity index (MPI), difference tests and additional analyses on a dataset consisting of 276 firm-year observations.

The findings indicate that the study model is robust to additional analysis. The results show significant differences in ICE between firms during the study period and noteworthy differences between countries, where the Qatari and Bahraini firms achieved the best ICE compared to other countries.

The results of this study have significant ramifications for increasing knowledge of ICE analysis models among relevant parties. In addition, the findings may affect trading strategies because investors and financiers are motivated by the potential for lucrative financial returns on their investments in companies that prioritize ICE strategies.

This research contributes to the literature by proposing a robust model for estimating the ICE. It also compares ICE across Gulf companies, industries and countries to shed light on their ICE challenges.

This study aims to identify the impact of intellectual capital (IC) on the bank’s performance using a cross-country approach with India and Gulf Cooperation Council (GCC) countries using the Skandia navigator model (SNM).

This study uses a mixed-methods research approach by taking financial and non-financial measures to assess the impact of the IC on the bank’s performance using the SNM. The study implies an analysis of the data from the top ten banks in India and twenty banks in GCC countries. The selection was done based on the volume of the bank’s business for three years (2019–2020, 2020–2021 and 2021–2022).

The research has three main findings: there is a positive impact of IC on the bank’s performance; amongst the factors of SNM, there is a direct impact of human capital and customer focus on the performance of the selected banks in both India and GCC countries; and the other factors of SNM such as structural capital and process focus, renewal and development focus also affect the selected banks.

The outcomes of the research may be useful for policymakers in India and GCC countries, as it identifies IC components that have a significant impact on the bank’s performance. This might enable them to develop policies that foster such factors, which, consequently, will improve the performance of the banks in the selected countries.

This study is an attempt to fill the gap in the existing literature on IC and bank’s performance for two different types of countries using the SNM.

Based on resource-based theory and intellectual capital theory, this paper aims to investigate the impact of digital investment on enterprise value and the mediating role of intellectual capital. Additionally, it explores the heterogeneous impacts of digital investment on enterprise value and intellectual capital.

The study utilizes a sample of listed companies in Chinese A-shares from 2013 to 2020. The entropy-weighted method is applied to measure digital investment from two dimensions: scale and increment. Finally, the research hypotheses are tested through multiple regression analysis.

The empirical results demonstrate that digital investment significantly and positively impacts enterprise value. From the channel mechanism test, digital investment can enhance enterprise value by influencing intellectual capital through human, structural and relational capital. Of these, the mediating effect of human capital is the most significant. Moreover, the impacts of digital investment on enterprise value and intellectual capital are related to the industry sectors. In the agricultural sector, digital investment has adverse effects. In the industrial and service sectors, digital investment promotes intellectual capital and enterprise value. However, in the service sector, the impact on relational capital is not significant, and the mediating effect of relational capital does not hold.

This research has a limited potential for generalization due to the lack of standard measurement models for the exploration of digital investment.

The research findings are valuable for assessing the economic effects of digital investment comprehensively and providing essential information for policy formulation and strategy implementation.

This study represents the first attempt to evaluate the relationship between digital investment and enterprise value using the entropy-weighted method. In addition, this study investigates the mediating role of intellectual capital.

The matter of interest is the reporting and disclosure of intellectual capital (IC) in the global “knowledge economy” era. The aim of the paper is twofold: to verify the level of disclosure of IC through the non-financial statements (NFSs) published by public companies and to identify the main firm-specific factors that explain the propensity to disclose.

Based on the 27 components of IC, a scoring system is designed to measure the level of disclosure of IC by 47 listed Italian companies. Content analysis (CA) is performed on the NFSs these companies published in 2020, to measure each company's so-called intellectual capital disclosure index (ICDI). A regression analysis is then applied to relate the ICDI scores to some firm-specific variables to determine their relevance and influence on the level of disclosure.

Although the NFS was not designed specifically for IC, the results of the analyses show an overall barely satisfactory ability of the NFS to give certain information on IC. Furthermore, the propensity to disclose IC appears significantly related to some firm characteristics considered here, such as capitalization, profitability, productivity, intangibility and financial structure.

The analysis relates to a representative but limited sample that does not allow for sectoral or time-series analyses. Extending the companies and years under observation would allow the results to be validated with broader and more in-depth analysis.

This paper provides exploratory but interesting evidence about the relationships between IC disclosure (ICD), firm characteristics and market capitalization. Despite several previous studies on the disclosure of IC, no analyses were found that focused on the information capacity of the NFS. Also, to the authors' knowledge, relatively few researchers have considered a set of financial ratios that include capital structure indices.

To investigate, compare and document the magnitude and extent of intellectual capital disclosure to sustainability disclosure during a transition from a voluntary to mandated “comply or explain” sustainability reporting regime. And to empirically test if, during the regime transition period, changes in the magnitude (extent) of sustainability disclosure is a significant determinant of changes in the magnitude (extent) of intellectual capital disclosure.

Content analysis of 1,744 annual reports drawn from 436 Singapore listed firms spanning a four-year observation window (i.e. April 1, 2014 to March 31, 2018). The magnitude (number of sentences) and extent (number of items) of (1) intellectual capital disclosure measured using a 38-item index; (2) sustainability disclosure of a 105-item index; and (3) 15-item index to measure the magnitude and extent of joint sustainability/intellectual capital disclosure.

The average magnitude and extent of sustainability and the joint sustainability/intellectual capital disclosure increased whilst the average magnitude and extent of intellectual capital disclosure increased when regulatory discussion of a change to mandated sustainability reporting emerged. However, in the annual period the mandated sustainability reporting became effective while the average magnitude and extent of intellectual capital disclosure declined. Regression tests indicate a significant (insignificant) association between the change in the magnitude (extent) of sustainability disclosure and intellectual capital disclosure.

From a research perspective, the analysis implies researchers investigating the consequences of mandated sustainability disclosure should consider impact on alternative non-financial disclosure themes and develop theoretical frameworks to derive why and how management may shift non-financial reporting strategies and practices.

For regulators, findings suggest there may be a need to weigh spillover costs of reductions in transparency related to intellectual capital. For investors, declines in the magnitude and extent of intellectual capital disclosure following a transition to mandated sustainability reporting may limit future firm valuation particularly of heavy intangible asset-oriented firms.

Initial study empirically investigating the impact of the transition from a voluntary to mandated sustainability reporting regime on the magnitude and extent of intellectual capital disclosure.

This paper aims to identify the strengths of the universities based on the research area which are prioritized by the Government of Indonesia in the National Medium Term Development Plan 2015–2019, in the research areas of food and agriculture; energy, new and renewable energy; health and medicine; transportation; telecommunication, information and communication; defense and security technologies and advanced materials.

The mapping of the research strength in Indonesian universities is performed by using data of the university research output in the Information System for Research and Community Service, Ministry of Research, Technology and Higher Education and categorized into seven categories, i.e. accredited national journals, international journals indexed by Scopus or others, Intellectual Property ownership, textbooks, prototypes and an appropriate technology. Based on the data obtained from Information System for Research and Community Service, there are 904 universities in Indonesia conducting research activities and generating 14,188 research outputs.

This paper analyzes 3 of the 9 National Research Priorities, namely, food, energy and health and medicine. The data show that there are 904 universities in Indonesia conducting research activities and producing 14,188 research results. The research strength index based on National Research Priorities shows that three universities have the highest cluster strength index. Gadjah Mada with an index value of 4.95 is the highest index in the food cluster. In the energy cluster of the Institut Teknologi Bandung with the highest index value of 0.63. Meanwhile, the Universitas Indonesia reached 2.06 as the highest index value in the health and medicine cluster.

Measurement of the strength of the study was conducted using data from research results from universities in 2016 which were recorded in the Information System for Research and Community Service. The University’s R&D strength is calculated from seven categories of research results: accredited national journals, international journals indexed by Scopus or others, intellectual property rights, textbooks, prototypes and appropriate technology products.