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The purpose of this paper is to define the elements of intellectual capital of firms in Turkey and to empirically investigate the relationship between intellectual capital and market value of firms in Istanbul Stock Exchange. To create a suitable intellectual capital measurement model for this study, a wide literature research was made. In almost every created intellectual capital measurement model, elements of intellectual capital are defined in three dimensions; i.e. human capital, structural capital and relation capital. For the research, an intellectual capital measurement model is created and four hypotheses are defined. The main conclusions from this study are that: human capital and relation capital of firms have a positive relationship with market/book value of firms in Turkey; and structural capital of firms in Turkey has a correlation with human and relation capital.

The purpose of this paper is to provide a quantitative assessment model for intellectual capital in companies.

A brief historical review of former approaches to evaluate intellectual capital construction of a new formula for an intellectual capital value. A possible empirical survey of influence factors on intellectual capital is suggested. Both, taken together, are the grounding of an integrative management model for intellectual capital still to be developed.

Shows that a quantitative figure for intellectual capital can be found and that such a figure is needed to convince managers and the public of the usefulness of activities to promote intellectual (and especially human) capital.

A quantitative measure can never picture the complete interrelations of organizational development, influence factors on intellectual capital, and performance of employees. The formula can only be a starting‐point for management and further research. Possible management tools are only touched on briefly.

Gives the manager a tool to argue his decisions regarding the promotion of human and intellectual capital. Managers talk about figures and often dislike purely philosophical arguments. Their awareness of the topic can be raised.

Even though there is a growing scientific body of quantitative models for measuring intellectual capital, this paper uses a new approach: the usage of approximation factors for motivation, commitment and job satisfaction in one formula.

The purpose of the research is to determine the perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 and to develop scientific and methodological recommendations for their implementation. For this, the directions of state regulation of competition between human and artificial intellectual capital are described, monitoring of competition between human and artificial intellectual capital by the example of modern Russia (2019) is performed and scientific and practical recommendations for state regulation of competition between human and artificial intellectual capital are developed, with their approbation by the example of modern Russia (2019).

A method of expert evaluation is used for collection of the information and empirical data. The method of comparative analysis is used for comparing the successfulness of implementing the distinguished directions of state regulation of competition between human and artificial intellectual capital (4.1) according to the official statistics to their current evaluation according to the interested parties. Also, future evaluation (forecasts) according to the interested parties (until 2045) is determined.

It is substantiated that during evaluation of state regulation of competition between human and artificial intellectual capital in Industry 4.0, one cannot use only the official statistics, as these data are fragmentary and indirect. Fuller and more precise data are provided by assessment according to the interested parties. They allow determining the current and the future state of affairs and, based on it, compiling a forecast and developing a long-term strategy of state regulation of competition between human and artificial intellectual capital in Industry 4.0.

The perspective directions of state regulation of competition between human and artificial intellectual capital in Industry 4.0 are as follows: stimulation of competition in the market of intellectual capital, social risk management of the market of intellectual capital, managing international competition in the market of intellectual capital and ecological risk management of the intellectual capital market. As the experience of modern Russia shows, even at the initial stage of transition to Industry 4.0, the measures of state regulation of competition between human and artificial intellectual capital are not enough, but their deficit is moderate. In the course of development of Industry 4.0, the necessity for the measures of regulation will grow, and their deficit will increase. That's why there's a need for strategic approach to their implementation, which envisages their systemic reconsideration and supplementing. An author's algorithm is offered for this.

The purpose of the paper is to develop a concept of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

The methods of regression and correlation analysis are used. The role of human and artificial intellectual capital for provision of effectiveness and competitiveness of the system of science and education is determined, as well as its correspondence to the modern challenges. Analysis of perspectives and limitations of automatization of the system of science and education based on AI is conducted; a model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital is compiled.

It is established that in the system of science and education, the decisive production factor is intellectual capital, but human intellect does not necessarily have to dominate in its structure. AI is one of the most popular technologies of Industry 4.0 in the system of science and education, which has wide perspectives of practical implementation. As experience of the leading world universities, which had the highest level of digitization in 2018, showed, foundation on non-breakthrough digital technologies (computer equipment and Internet) does not allow opening the potential of increase of indicators of effectiveness and competitiveness of the system of science and education and bringing it in correspondence to the modern challenges based on digitization. However, correlation of activity of application of artificial intellectual capital with these indicators is four times higher (0.2), as compared to correlation of these indicators with activity of application of human intellectual capital (0.05). This shows demand for digitization of the system of science and education, but based on breakthrough digital technologies, of which AI should become the key one.

It is substantiated that higher education could be automatized based on AI by 85% and science by 63%. Therefore, on the whole in the system of science and education, the share of AI in the structure of intellectual capital could reach 74% ((85 + 63)/2). It is recommended to use the developed model of organization of the system of science and education in the form 4.0 based on human and artificial intellectual capital.

This paper aims to analyse the relationship between intellectual capital and financial capital using a case study. This makes it possible to discuss how intellectual capital is related to value creation with a degree of nuance that is absent from most statistical studies of relationships between human, organisational, relational and financial capital.

The paper uses a case study of a firm that invests in intellectual capital in order to develop financial capital. It traces the relationship between intellectual capital elements and financial capital via interviews. This allows the development of a nuanced account of the performance of intellectual capital. This account questions the universality of the linear model typically found in statistical studies. The model makes it possible to show how items of intellectual capital not only interact but also compete.

Relationships between intellectual capital and financial capital are challenging to specify because they are complementary rather than causal. Financial capital is not only an effect but also an important input because the development of intellectual capital takes place through the firm's budgeting processes.

The findings suggest future development of accounts of the role and performance (strength) of intellectual capital be developed around imaginative, perhaps recursive and certainly dynamic, statistical models and/or more inclusive case studies of the various elements that influence the development and transformation of intellectual capital.

The case study suggests that investments in intellectual capital happen in the context of many other investments. Bounded by the budgeting process, intellectual capital has no separate agenda and therefore, intellectual capital investments compete with other types of investments.

The paper investigates the effects of strategic human resource practices on intellectual capital and new product development performance in knowledge-based firms.

A quantitative approach was adopted to conduct the present study. The respondents were sampled from knowledge-based firms in Iran. Overall, 120 managers in 60 knowledge-based firms were selected using convenience sampling. A confirmatory factor analysis was conducted to ascertain the validity and reliability of the observed items, and a structural equation model was employed for testing the proposed hypotheses.

In the studied firms, strategic human resource practices have a positive and significant effect on intellectual capital. Moreover, the findings of this study indicate that those firms that use their intellectual capital have a higher new product development performance.

The study focuses on knowledge-based firms in Iran, which limits the generalizability of the research results. Therefore, future studies should be carried out with samples from other settings and countries. Moreover, as the study was cross-sectional, the causal relationships could not be inferred directly.

With regard to key areas of improvement identified in this study, knowledge-based firms should focus on increasing new product development performance by improving employees' training, involving them in their job-related decision-making process, empowering employees to innovate, developing intellectual capital and monitoring the customer's satisfaction level of new products.

The study extends the intellectual capital literature by linking strategic human resource practices to new product development performance in knowledge-based firms via intellectual capital as a mediator.

While prior research suggests that human resource management (HRM) practices are crucial drivers of a firms' intellectual capital, few studies have tried to deconstruct this relationship and investigate how HRM practices specifically affect intellectual capital resources. Furthermore, prior research treated this relationship as universal and rarely tried to introduce important contingent factors that may alter the mechanisms involved in how HRM practices influence firms' intellectual capital. In this study, the authors examine the relationships between the ability-, motivation- and opportunity-enhancing dimensions of HRM systems and human, social and structural capital and investigate how companies' codification and personalization knowledge management (KM) strategies may alter these relationships.

The data were collected using a telephone survey of 215 knowledge-intensive companies operating in Russia. The paper utilizes partial least squares structural equation modeling (PLS–SEM) to evaluate the measurement model and test hypothesized relationships.

The findings indicate positive relationships between ability-enhancing practices and firms' human capital between motivation-enhancing practices and firms' human and social capital and between opportunity-enhancing practices and firms' social and structural capital. The authors’ results reveal the limited moderating role of KM strategies in the relationships between HRM and intellectual capital. While a personalization strategy had no impact on any of the proposed relationships, a codification strategy positively moderated the relationship between opportunity-enhancing HRM practices and firms' structural capital.

The study expands the debates in strategic HRM literature by looking “inside” the HRM–intellectual capital relationship. Additionally, the authors’ findings reveal the complexity of the contingent effect that KM strategies of codification and personalization have on the relationship between HRM practices and intellectual capital. Although some of the relationships were not moderated by the KM strategy of the firm, the HRM–intellectual capital relationship cannot be considered fully universal.

The purpose of this paper is to study the relationship between intellectual capital and organizational innovation in Kuwait Petroleum Corporation (KPC) through a case study at KPC on the employees of the corporation (The study population was 2,180 respondents and the sample size was 335 respondents).

The statistical package for social science was used to analyze the data. While trying to explore the relationship between intellectual capital and innovation, the researcher used the descriptive analytical method and the case study methodology using various references, periodicals, internal and external documents and data, in addition to conducting a field study on a sample of employees of KPC, through a questionnaire form containing the axes that reflect the study variables.

There is a relative approval between the sample of the research on the existence of a good role for training in the corporation in terms of availability for all employees and the compatibility of training programs with the actual needs of employees, and linking the training paths and career paths for promotions in the corporation. The researcher attributed this to the employees' awareness to the importance of training and its role in raising their performance levels, and the awareness of the corporation to the importance of training and capacity building of the human element.

The research, in general, demonstrated the importance of human capital as the organization's most valuable assets, especially as it supports creativity and innovation, thus enabling competitiveness. The research stressed that human capital is the most important element in the formation of intellectual capital, which requires decision-makers to support it and give the intellectual and human aspects a strategic content that meets the needs to develop innovation and institutional education and to recruit systems and indicators to measure the performance objectively to achieve the goal of survival of the corporation in a competitive sustainable environment, through providing material and moral potentials that can support the implementation of organizational innovation at various levels.

This paper seeks to investigate the impact of intellectual capital elements on business performance, as well as the relationship among intellectual capital elements from a cause‐effect perspective.

The partial least squares approach is used to examine the information technology (IT) industry in Taiwan.

Results show that intellectual capital elements directly affect business performance, with the exception of human capital. Human capital indirectly affects performance through the other three elements: innovation capital, process capital, and customer capital. There also exists a cause‐effect relationship among four elements of intellectual capital. Human capital affects innovation capital and process capital. Innovation capital affects process capital, which in turn influences customer capital. Finally, customer capital contributes to performance. The cause‐effect relationship between leading elements and lagged elements provides implications for the management of firms in the IT industry.

The model proposed in this study is applicable to the high‐tech IT industry. Modification of the proposed model may be needed in applying this model to other industries.

This study helps management identify relevant intellectual capital elements and their indicators to enhance business performance.

This paper is a seminal work to propose an integrated cause‐effect model to investigate the relationship among elements of intellectual capital for IT in Taiwan.

This study aims to investigate the intellectual capital–financial performance relationship using two models, namely the conventional Value-Added Intellectual Coefficient (VAIC) model and the adjusted Value-Added Intellectual Coefficient (A-VAIC) model.

This study is designed as a quantitative research focusing on the relationship between intellectual capital and financial performance of the banking industry in Indonesia. As many as 114 data are derived from the publicly listed banks on the Indonesia Stock Exchange for the period of 2012–2017. The multiple regression analysis is employed to test the hypotheses studied.

In general, the result confirms that intellectual capital affects financial performance. Although not all hypotheses of the study are supported by either the VAIC model or the A-VAIC model, the results provide a deeper and new insight on how each component of intellectual capital efficiency (human capital, structural capital, capital employed, innovation capital) relates to financial performance (return on asset, return on equity, asset turnover, price to book ratio). The results also justify that further improvements in measuring intellectual capital are still needed in the future.

This study limits its generalization since the sample is only in the Indonesian banking industry. Notwithstanding the limitation, the results imply that the Indonesian banking managers need to be aware of intellectual capital management because of its strategic role in enhancing financial performance.

This study contributes to the intellectual capital literature by providing empirical evidence on the use of both models, namely the conventional VAIC and the A-VAIC in the Indonesian banking industry research setting which is never been studied before.

This study has the social implication to the enhancement of the quality life of the society. The higher the quality of intellectual capital in the banking firms, the better the banks serve the needs of the community.

This study contributes to the IC literature by providing empirical research on the use of the VAIC model and the A-VAIC model in the Indonesian banking industry.