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There is a need to understand the role of innovative literacy in intellectual capital literature. This study aims to develop the innovative literacy scale, starting from the framework of innovative literacy, which is not prominent in the literature. Accordingly, this study develops and validates an innovative literacy scale.

A quantitative research methodology was used for this study, whereby a unipolar 5-point Likert scale self-report questionnaire was designed. Scale development analyses were performed in three steps: (1) The first item pool was created by literature review; (2) preliminary quantitative testing of the reliability and validity of the items, including confirmatory factor analyses (CFA), was performed; and (3) final scale validation through a discriminant and validity test was done using descriptive factor analyses (DFA) and structural equation modelling (SEM).

For the developed scale, the sample size was 220 in the first stage, 440 in the second stage, and 457 in the third stage. The validity and reliability analyses of the results were completed using Statistical Package for the Social Sciences (SPSS) and Analysis of Moment Structures (AMOS) programs. After the preliminary stages, the validity and reliability tests of the scale were carried out, and 17 items (in 4 dimensions) of the innovative literacy scale were finally developed.

This research fills a conceptual gap in the literature. However, since this concept is evaluated using the human, customer and structural components of intellectual capital, future researchers may examine this concept together with other features of intellectual capital and with larger samples.

The article contributes to understanding innovation by developing a scale to evaluate InnoLiteracy, which may be an essential factor influencing innovative literate behaviours. The perceived multi-dimensional scale of InnoLiteracy will be beneficial for academicians and human resources professionals. Although there are studies in the related literature on the importance of the concept of innovative literacy, a scale from the perspectives of intellectual capital and sustainable innovation will be unique since there is no tool for its measurement yet. The findings of the InnoLiteracy research are meaningful, and the scale has the potential to meet the needs of researchers, schools, government agencies and businesses.

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.

The purpose of this study is to analyse the validity of the value added intellectual coefficient (VAIC) method as an indicator of intellectual capital.

The paper describes VAIC through its calculation formulae and aims to establish what exactly it is that the method measures. It also looks in detail at how intellectual capital is understood in the method, and discusses its conceptual confusions. Furthermore, the paper tests the hypothesis according to which VAIC correlates with a company's stock market value, and reflects the contradictory results of earlier studies.

The analyses show, first, that VAIC indicates the efficiency of the company's labour and capital investments, and has nothing to do with intellectual capital. Furthermore, the calculation method uses overlapping variables and has other serious validity problems. Second, the results do not lend support to the hypothesis that VAIC correlates with a company's stock market value. The main reasons behind the lack of consistency in earlier VAIC results lie in the confusion of capitalized and cash flow entities in the calculation of structural capital and in the misuse of intellectual capital concepts.

The analyses show that VAIC is an invalid measure of intellectual capital.

The result is important since the method has been widely used in micro and macro level analyses, but this is the first time it has been put to rigorous scientific analysis.

This paper seeks to examine the calculated intangible value (CIV) method as a measure of intellectual capital (intangibles) in enterprises. The aim is to show the benefits and disadvantages of the method and its actual relation to intellectual capital.

The authors present a conceptual, theoretical and empirical analysis of CIV to assess its validity as a measure of firm's intangibles.

The result of the analyses is that CIV is connected to all types of capital assets (physical, financial, combined physical and financial and intangible) and thus it does not unambiguously relate or measure firm's intangible value(s). CIV should be seen solely as a measure of financial efficiency derived from companies' return on assets (ROA). CIV measures an overall financial recognized comparative advantage in comparison with competitors within the same branch of industry. There is no evidence to support the simplistic assumption that a company's CIV is a measure of its intellectual capital.

CIV is used quite widely for purposes of measuring intellectual capital in companies and industries. However, its validity has never been subjected to critical examination. The results of this paper provide valuable information on the reliable measurement of intellectual capital and the further development of these measurements.

Nobody concerned with political economy can neglect the history of economic doctrines. Structural changes in the economy and society influence economic thinking and, conversely, innovative thought structures and attitudes have almost always forced economic institutions and modes of behaviour to adjust. We learn from the history of economic doctrines how a particular theory emerged and whether, and in which environment, it could take root. We can see how a school evolves out of a common methodological perception and similar techniques of analysis, and how it has to establish itself. The interaction between unresolved problems on the one hand, and the search for better solutions or explanations on the other, leads to a change in paradigma and to the formation of new lines of reasoning. As long as the real world is subject to progress and change scientific search for explanation must out of necessity continue.

The purpose of this study is to empirically test the relationship between intellectual capital (i.e. human capital, structural capital, relational capital) and business performance within the pharmaceutical sector of Jordan.

A valid research instrument was utilized to conduct a survey of 132 top‐ and middle‐level managers from all 15 members of the Jordanian Association of Pharmaceutical Manufacturers.

A correlation and path analysis were conducted to ascertain the validity of the measures and models. Statistical support was found for the hypothesized relationships.

The findings offer valuable insights on the generalizability of intellectual capital in a novel research setting.

Intellectual capital measurement is of primary interest for senior executives of pharmaceutical firms in Jordan.

The research reported is among only a few to investigate the issue of intellectual capital in Egypt and the first to study pharmaceutical firms.

The purpose of this study is to identify the impact of intellectual capital on the innovation performance of the Jordanian banking sector and identify the moderating role of big data analytics.

For this study's purposes, 333 questionnaires were analysed. Convergent validity, discriminant validity and reliability tests were performed through structural equation modelling (SEM) in the Smart-PLS program. A bootstrapping technique was used to analyse the data.

Empirical results showed that each of the components of intellectual capital and big data analytics explains 63.5% of the variance in innovation performance and that all components of intellectual capital have a statistically significant impact on innovation performance. The results also revealed that the relationship between structural capital and innovation performance is moderated through big data analytics.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalisation of its results, and the results are limited to one country.

This study promotes the idea of focusing on components of intellectual capital to enhance innovation performance in the Jordanian banking sector and knowing the effect of big data analytics in this relationship.

This study makes recommendations for financial policymakers to improve the effectiveness of intellectual capital practices and innovation performance in the context of big data analytics.

This study has important implications for leaders in the Jordanian banking sector, in general, as the study highlights the importance of intellectual capital to enhance the innovation performance, especially in light of the big data analytics in this sector, and thus increase the innovative capabilities of this banks, which leads to an increase in the level of innovation.

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.

The main aim of this study was to examine the effect of the components of intellectual capital on the organizational performance of SMEs operating in tourism sector at Azad Jammu and Kashmir Pakistan.

In this empirical study, survey approach was used and primary data were collected through structured questionnaire. A total of 300 structured questionnaire survey forms were distributed through purposive sampling technique. Two hundred and twenty usable questionnaire survey forms were returned. Six research hypotheses were constructed to achieve the objective of this study. Smart Partial Least Square (PLS) 3 was used to test the proposed research hypotheses.

The findings showed that two out of six hypotheses were supported. Precisely, customer capital has appeared as one of the most important components of intellectual capital in model. The results showed that the overall intellectual capital has effect on the organizational performance of SMEs. Results shed more light on the effects that the components of intellectual capital have on organizational performance of SMEs, particularly in the context of Pakistan.

This research is limited to SMEs in tourism sector in Pakistan and the data were gathered through questionnaire which used mostly subjective measures. Subsequently, findings may not be applicable to other industries. The research contributes to the development of intellectual capital literature focused on the organizational performance in the perspective of SMEs in emerging economies. Future research needs to reach beyond the boundaries and understand the effect of intellectual capital on the performance of organizations.

This study extended the knowledge about the prominence of intellectual capital and its effect on the organizational performance of SMEs. Moreover, this study identified the level of existence and measurement of the six components of intellectual capital in SMEs which enables practitioners to develop adequate strategies to better manage it. To author's best knowledge, this study can be the first empirical study which investigates the impact of intellectual capital on the organizational performance of SMEs operating in tourism sector in Pakistan.

The paper aims to provide an assessment of a tool for the macro‐level measurement of intellectual capital developed by Corrado, Hulten and Sichel (CHS model).

The aim paper assesses the validity and accuracy of the CHS model in measuring intellectual capital in general and to see whether it has application at the national economy level.

The model's new accounting ideas have great potential, but some serious question marks remain. The key advantage of the model is that it accumulates capitalized intangibles over time. On the other hand, the elements of intellectual capital, i.e. spending on innovative property and economic competencies, software and other computerized information, are too vague and problematic.

CHS model is a rather frequently used method for measuring intellectual capital. However, its validity has not been under critical analysis or examination earlier. Therefore, the results of this paper bring important and valuable information into reliable measurement of intellectual capital and are a step forward to develop more valid methodologies within intellectual capital research.