Search results

For better mapping the path of intellectual capital (IC) research, the purpose of this paper is to selectively review empirical studies of IC published, and identify theories, components and three dimensions of analysis: national IC (NIC), regional IC (RIC) and organizational IC (OIC).

The systematic literature review (SLR) subject to analysis is based on empirical studies made between 1960 and 2016, and focuses on three dimensions of analysis: NIC, RIC and OIC. Four research questions were designed, using the following databases, namely, Web of Science, Scopus and Google Scholar, for data collection purposes.

The SLR unveils a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis and provides some recommendations for future studies of NIC, RIC and OIC, by outlining the need for clear definitions of components and measures of IC and identifying strengths, limitations and future research avenues.

In order to fill the gap found in the literature and the non-existence of a study clarifying the multiple dimensions of analysis of IC, this SLR makes a twofold, original contribution to the literature on management: providing an SLR of the main empirical studies dealing with different units of analysis; and identifying a multidimensional taxonomy for measuring and classifying the type of IC applicable to the different levels of analysis.

The purpose of this paper is to analyze and group the intellectual capital components of worldwide organizations through a humanistic model called CONICCVAL^TM (contextual intellectual capital components valuation). The study aims to consider the difference of perception on the value of intangible assets according to its context.

The importance of the context as a key factor to valuate intellectual capital is highlighted. The research developed by a Mexico based Consulting and Research firm in topics related to intellectual capital and corporate strategy (Instituto de Capital Intelectual) is described, to valuate these intangible assets. The sample population in eight geographic regions, 16 types of industries, two types of operations, and three sizes of organizations was analyzed. The research results were analysed using 41 variables and four factors through the Multiple Analysis of Variance (MANOVA) methodology. The analysis of the principal components analysis (PCA) is also described, and a new model to valuate intellectual capital considering the context is proposed.

It was demonstrated that: the geographic region, the segment of the industry, and the size of the organization, are statistically significant factors that determine the weighing of intellectual capital. It was found that there are ten principal components that shape intellectual capital, and their profiles were identified to measure it according to the context.

A statistically significant sample of 38,000 executive men and women, graduates and students of Master's and Executive Education programs from a top International Management School in the USA was used. They are considered to be a representative sample of a working business community of 12,000 companies in 140 countries.

The main parameter used to valuate intellectual capital in this study was the context. It was concluded that only companies inserted in equivalent contexts could be compared.

The contribution of this paper is that it demonstrates the importance of the context in the valuation of intellectual capital.

The purpose of this paper is to explain the difference of national intellectual capital from the perspective of national culture and to illustrate how national leaders or policy-makers increase their country’s national intellectual capital.

The study conducts a descriptive analysis combining the research outcome of Lin and Edvinsson’s (2011) national intellectual capital with Hofstede’s (2001) national culture. The research findings and results of these two studies were compared before running a t-test to determine whether countries with relatively high national intellectual capital have a higher level of certain national culture.

Based on the matching data of 26 countries, the study proposed that countries with certain national culture possess lower intellectual capital. Countries with high intellectual capital tend to exhibit a common culture of low power distance, weak uncertainty avoidance, and individualism.

The study suggests that for a country to enhance its overall intellectual capital, it should strive for a culture of equality, freedom and safety, and an active competitive environment, while avoiding social class distance in order to eliminate insecurity. The study proposes some suggestions to advance the countries’ national intellectual capital. In addition to admit the weakness of their intellectual capital due to cultural reasons, these countries could go a step further to increase their own national intellectual capital by increasing or enhancing certain national cultures if possible.

The study compares national intellectual capital and national culture and finds the relationship between these two sets of constructs. This study proves that national culture not only influences the strategies or behaviors of business level but also the competitiveness of national levels.

With the emergence of the basis of intellectual capital, competitive advantage was considered as the focus of competitive strategies, and the knowledge resulting from this approach became the basis for the development and strategic directions of companies in various fields of the company such as finance and accounting. The purpose of this study is sustainable intellectual capital reporting framework and evaluation of key examples in the context of capital market companies.

The methodology of this study was exploratory from the point of view of the developmental result and based on the type of objective and qualitative and quantitative basis was used to collect the data. The statistical population in the qualitative part was university experts and in the quantitative part financial managers of capital market companies. Data collection tools were interviews in the qualitative part and fuzzy scales and language comparison checklists in the quantitative part. Therefore, first through three stages of coding, the dimensions of the model were identified, and based on the fuzzy Delphi analysis, the reliability level was determined through the average between the first round and the second round of Delphi. Finally, through the default tests, the appropriate fuzzy model was first determined, and then hierarchical fuzzy analysis based on TODIM's approach was used to determine the most favorable axis of sustainable intellectual capital reporting.

The results in the qualitative part indicate the existence of 3 categories and 6 components and 39 conceptual themes in the form of a six-dimensional model. In the quantitative part, the results showed that by confirming the dimensions identified through fuzzy Delphi analysis, the most desirable axis of intellectual capital reporting is the component of technological capital reporting, which can play a more effective role in sustainable reporting.

This study, relying on the importance of the consequences of sustainable intellectual capital reporting, tries to evaluate the consequences of this field of financial reporting due to the lack of a coherent theoretical framework about capital market companies. In addition, the framework presented in this study promotes integrated thinking for firms to it would provide some level of incentive to those charged with governance concerning the voluntary compliance with the sustainable intellectual capital reporting framework.

There are different models to measure the effect of intellectual capital on firm performance. These models depend on different dimensions of intellectual capital, the interrelations between them and the effects on performance. It is important to analyze several specificities in small and medium sized enterprises (SME) in developing countries. This paper aims to test diverse models to verify the previously mentioned relations applied to wood manufacturer SMEs of Oberá (Argentina).

A global model including the variables used in the previous literature is used. The paper establishes hypotheses for testing this model and us PLS technique to estimate the parameters of the model in a sample of 113 wood manufacturer SMEs in Oberá (Argentina).

The only dimension of intellectual capital directly affecting performance is structural capital. The other dimensions exert an indirect effect through structural capital.

The model does not use all the possible variables to characterize intellectual capital. The causality elements cannot be verified in a temporary horizon because the data are cross‐sectional. In addition, when making reference to data of a particular period of time, there may be causes that imply relations of accidental type. Moreover, the measures used were subjective. This paper only studies the SMEs of the Argentine wood industry.

The paper offers several suggestions to implement strategies for local SMEs and to support aid to projects for developing countries.

The paper tests different models to analyze the impact of dimensions of intellectual capital on performance in SMEs of developing countries and provides information on the wood manufacturer SMEs in Argentina.

This paper aims to examine the relationship between different dimensions of intellectual capital and industrial companies' financial performance. In addition, this paper aims to examine the role of organisational ambidexterity in mediating this relationship.

This paper adopted a quantitative method using a previously validated questionnaire. The questionnaire copies have been distributed to accountants and accounting managers in the context of industrial companies.

Findings indicate that there is a positive correlation between all dimensions of intellectual capital and organisational ambidexterity. Furthermore, the connection between intellectual capital dimensions and financial performance is notably positive when it comes to relational capital. Additionally, it was established that the various dimensions of capital and financial performance are interconnected through the intermediary influence of organisational ambidexterity.

This paper provides important contributions to managers, policymakers and stakeholders. Jordanian industrial companies must improve the quality of their work by enhancing levels of intellectual capital and organisational ambidexterity that leads to improving the financial performance of companies. Additionally, managers should identify and capitalise on the benefits of other intangible assets and understand more about how to increase the use level of other intangible assets.

Emerging clusters, formed by small to medium‐sized enterprises (SMEs) of slow growth and embryonic management systems present a different competitive advantage scheme. The purpose of this paper is to analyze relationships among components of intellectual capital within a model of competitive advantages in emerging clusters in a region of Latin America.

An intellectual capital model in a competitive advantage scheme is defined. A sequential method based in PLS technique is suggested to select the model and estimate the parameters. A sample of 113 wood manufacturing SMEs in a region of Argentina was selected.

The competitive advantage scheme in emerging clusters of SMEs proposes that resources affect organizational capabilities; territory and organizational capabilities affect strategic factors which improve performance. In this scheme, human capital affects structural capital and structural capital generates relational capital. SMEs organize tangible resources and relational capital to build organizational capabilities.

The sample is a cross‐section. The performance is subjectively measured by the satisfaction of the entrepreneurs with different items.

The paper establishes suggestions to strategies of the SMEs in emerging clusters and politics of developing countries. This paper enables practitioners and scholars to comprehend and make legitimate decisions and conclusions that can foster business growth.

The authors tested the impact of dimensions of intellectual capital on performance in emerging clusters of developing countries within a competitive advantage scheme, showing relationships among intellectual capital dimensions and competitive advantages. The analysis differentiates between intellectual capital dimension and organizational capabilities.

This study examines the impact of corporate social responsibility (CSR) on innovation, considering the role of the three dimensions of intellectual capital (human capital, structural capital and relational capital). Specifically, the analysis explores the direct effect of CSR and intellectual capital on innovation, the effect of CSR on intellectual capital, and the mediating effect of intellectual capital on the relationship between CSR and innovation.

Data were collected from a sample of 101 Tunisian firms operating in various industries. The conceptual model of direct and indirect effects was tested with partial least squares structural equation modelling (PLS-SEM) using SmartPLS 4 software.

CSR is positively related to innovation, as well as all dimensions of intellectual capital. Structural capital is the only dimension of intellectual capital that has a significant effect on innovation. CSR affects innovation through its impact on structural capital.

Most studies have examined the direct effect of CSR on innovation in firms in developed countries. In contrast, this research sheds light on the mediating role of intellectual capital in this relationship, underlining the specific role of human capital, relational capital and structural capital. In addition, the study focuses on a developing country, which thus differentiates it from previous studies.

As the carrier of knowledge, intellectual capital plays a crucial role in technology capability. However, most of the previous studies focus on technological capability from a static perspective, rather than take dynamic technology capability into consideration. Based on this research gap, the purpose of this paper is to investigate the effects of intellectual capital and its sub-dimensions on dynamic technology capability, measuring by the factor scores of five technological input and output variables.

The authors combine the system dynamic method and empirical study to guarantee the internal and external validity. Specifically, the authors design the system dynamic model and simulation to analyze the system mechanism of intellectual capital and its sub-dimensions on dynamic technology capabilities from four cause and effect feedback loops. Then, the authors propose eight hypotheses based on this system dynamic model. In the empirical test phase, the authors employed a panel data set pertaining to Chinese manufacturing firms from 2007 to 2017, and adopted the fixed effect panel model according to Hausman test.

The authors find that intellectual capital efficiency (ICE) and its sub-dimensions (i.e. human capital efficiency, organizational capital efficiency and capital employed efficiency (CEE) have significantly positive impacts on dynamic technology capability. The results also show that the positive effects of ICE and OC on dynamic technology capability would be strengthened in state-owned enterprises compared with non-state-owned enterprises, while this moderation effect is weakened on the relationship between CEE and dynamic technology capability.

In this study, the authors first introduce the system dynamic method to explore the relationship of intellectual capital and dynamic technology capability, which is a valuable trial on combining system science and empirical study. Additionally, the authors continue to expand the dynamic technology capability from the intellectual capital perspective, and also find the moderating effect from the ownership aspect. It is beneficial to the theoretical development of intellectual capital and dynamic technology capability. Furthermore, the authors provide significant inspirations and implications for enterprise’s managers.

The purpose of this paper is to describe the development and validation of an instrument for measuring intellectual capital in the academic research context. The current research context describes a new paradigm of scientific production characterized by interdisciplinarity, heterogeneity and the intensification of the relations between the generators of knowledge. In this scenario, traditional measures of intellectual capital do not capture all the variables that make up the environment in which the research activities are carried out. This transformation of research processes suggests the need to bring theories of organizational behavior, more appropriate to an organizational context, to the study of scientific context. Thus, the paper contextualizes the intellectual capital approach, thereby explaining how the different attributes that build it influence scientific productivity and providing a measurement instrument to evaluate relative levels of intellectual capital in an academic research context.

The scale was designed through a double qualitative–quantitative scale development process. The literature on intellectual capital does not provide strong theoretical support for the definition of a specific set of items to be applied in the specific academic research context. Consequently, the scale constructs and observable variables were initially conceptualized through a Delphi panel. This initial set of indicators was empirically validated through a second quantitative stage to a sample of 1,798 Spanish academics. Given that no prior published studies have examined the construct validity of the proposed scale, and the proposed scale is not based on other previously validated scales, the authors used exploratory and confirmatory factor analysis to assess the internal consistency, using Cronbach’s α to determine reliability.

Drawing on the evidence obtained from a double qualitative–quantitative process, a scale consisting of 47 items was proposed to measure the three dimensions of intellectual capital, namely, the researcher’s human capital, as well as the nature of the social capital and organizational capital of the team in which the scholar is integrated. The process of identifying and validating indicators of intellectual capital allowed the authors to identify certain intangible elements that are key in the research process and that, therefore, determine scientific productivity. Thus, the proposed scale contributes by conceptualizing new variables that could be used to deepen and broaden the study of the determinants of research performance. The contextualization of intellectual capital approach can also help to assess the value of intangibles, offering an external reporting tool and making universities’ social contributions more visible to public and private stakeholders, justifying the efforts made by societies in the generation of academic knowledge.

The empirical analysis was carried out with an initial sample of 1,798 Spanish scholars. The validation of the scale should therefore be confirmed in different national contexts, with larger data sets. Likewise, the use of longitudinal data sets could help to study the effects of intellectual capital in academic research, thereby contributing to the ongoing debate on the determinants of research performance.

From a practical perspective, the instrument could be considered both as a management and an external reporting tool, providing a self-assessment instrument of the levels of intellectual capital. As a management tool, a specific measure of intellectual capital in an academic context could help to identify training needs, the implementation of practices that encourage the capability for building research networks and the development of reports with intellectual capital-related inputs for the justification of the resources received. At an institutional level, the proposed set of indicators also identifies the attributes of scholars linked to higher scientific performance, and the scale could be used as an instrument for selection processes in academic institutions, to develop practices related to the distribution of workload or the publication of intellectual capital indicators of its researchers in a healthy exercise of transparency.