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PurposeThis study suggests an alternative to confirmatory content analysis (CA) and empirically demonstrates that explorative CA enables new insights into the mechanism of intellectual capital (IC) disclosure. In so doing, this research contributes to both methodological and empirical advancements in IC disclosure research.Design/methodology/approachEmploying the assumptions of positive accounting theory and taking book value of intangible assets as a reference, our research design utilizes well-established text-mining (TM) tools based on a least absolute shrinkage and selection operator regression. We assume that the degree of cohesion between officially disclosed and evaluated intangible assets on balance sheets and those contextually delivered in narrative form may affect how IC is ultimately disclosed in annual reports.FindingsOur main finding is in line with the results and criticism of previous studies. We show that companies do not extensively disclose IC in their annual reports. However, some narrative forms for IC disclosure are identified and confirmed by several robustness checks.Research limitations/implicationsFirst, the findings provide internal validity only for large US enterprises. These firms have similar, well-structured reporting requirements. This analysis might be enriched by an examination and a comparison of different institutional contexts, such as emerging countries. Second, following previous studies, annual reports serve as the source of data. Consequently, the findings are relevant only for mandatory and voluntary disclosure of IC, mitigating the relevance of this study for contexts of involuntary disclosure.Originality/valueThis study makes two contributions. First, we add to the empirical literature by offering one more piece of evidence on whether and, if so, the extent to which companies disclose IC in their annual reports. Second, we provide further examination of confirmatory CA by proposing a number of statistically validated codes and tokens that are indicators of IC communication by companies.

Purpose The purpose of this paper is to analyse simultaneously the effect of attendance at the stadium on the size of the TV audience, taking into account the effect of price and uncertainty of outcome hypothesis on both the TV audience and stadium attendance. The paper assumes that a home-team effect exists and influences potential spectators’ decision to go to the stadium or to stay at home. Design/methodology/approach The data set consists of all 228 matches broadcast live and on open air from the Brazilian League across the seasons 2013–2015. The econometric approach of the present paper is based on three simultaneous equations through the Three-Stage Least Square estimator. This method is chosen in order to avoid endogeneity between ticket prices and live attendance and, consequently, with the television audience, too. Findings This work finds a correlation between TV audience and attendance at the stadium. However, it has been demonstrated that those matches that are more expensive have a larger TV audience. Scheduling and UO appear to be relevant for TVs and clubs. Scheduling is relevant, as weekend matches have a smaller TV audience but higher attendance at the stadium. Practical implications The findings indicate that Brazilian football clubs should find optimal prices for matches in order to maximise both TV audience and attendance. Originality/value Analysing simultaneously the effect of attendance at the stadium on the size of the TV audience, taking into account the effect of price on all three of these variables, is new. Another novel aspect is the use of data on audience size to observe a possible substitution effect. The authors also distinguish between home and away matches, assuming that a home-team effect exists and influences potential spectators’ decision to go to the stadium or to stay at home.

Purpose The purpose of this paper is to address the issue of efficiency of corporate universities. An efficiency is defined in relative terms: as having relatively better performance in comparison to other companies. Different indicators of performance were employed in order to analyze short-term and long-term efficiency. A comparative analysis of European companies and emerging Russian companies is performed in order to understand if there are country differences in the efficiency of corporate universities. Design/methodology/approach To avoid potential omitted variable bias, fixed effect within estimator is employed. This estimator enables controlling for a firm-specific time-constant effect which conditions company’s performance and is responsible for other individual traits. The rest of the characteristics are controlled with a proxy, which are traditional for corporate finance studies. Findings There are contradictory results for the efficiency of a corporate university; for the European companies, a corporate university brings positive effect for the short-term performance, nevertheless, as the authors have found that it destructs value in long term. A company with a corporate university has 70 percent less market value added than an average company. There is a negative short-term synergy while the long-term synergy is positive. The results for the Russian sample are very consistent: corporate universities have negative or neutral effect on the performance. Originality/value This study contributes to the literature about strategic management and human resources management. It addresses the issue on efficiency of corporate universities in companies considering this as one of the key strategic investment in human resource policy. It appears that the corporate university is not a panacea for all companies to develop their human development policy.

Purpose This study aims to explore value creation through intangibles in corporations, taking into consideration the endogenous nature of managerial decisions. It is stated that intangibles bring extra information asymmetry into a company and make managers and investors’ goals less aligned. Design/methodology/approach A theoretical model is elaborated and empirically tested on the assumption that managers, while investing in intangibles, simultaneously make a company competitive and attractive to investors. The authors use a conceptual model of endogenous value creation to test how intangibles affect outperforming of a company and provoke the expectations of investors. The research is carried out on a sample of more than 1,650 European companies covering the period from 2004 to 2011. Structural equation modelling is applied for the purposes of empirical analysis. Findings The authors reveal a diverse impact of intangibles on outperforming of a company measured by economic value added and its ability to create market value. The study discovers that managers are prone to indicate positive signals to investors rather than create sustainable competitive advantages. Practical implications This research emphasizes on the particular importance of awareness of policymakers, namely, companies’ top managers, about the outcomes of their decisions. Decision-making in public companies should involve as much deliberation as possible about the potential impact of what is decided. Originality/value This work contributes primarily to the field of corporate finance in companies that use intangibles. The endogenous process of value creation is modelled and tested. As a result, a number of essential problems in agent relationships in intangible-intensive corporations are discovered.

Purpose The paper aims to explore factors of the low competitiveness of Russian companies assuming that the gap in the endowment of intangible resources is responsible for the gap in competitiveness. Design/methodology/approach The framework of resources-based view is used to examine causality between the resources used and competitiveness measured by economic value added (EVA). Controlling for the most relevant factors, the authors place an emphasis on those intangible resources that are considered in the literature as being the most critical for Russian companies when contending for global competitiveness: productivity, strategic long-term orientation of companies, quality of human capital, innovative behavior of companies, foreign investments and corporate networks. The data set of more than 1,000 Russian companies benchmarked to the data set of more than 1,600 European companies during a period of 10 years: 2004-2013 is analyzed to test the hypothesis put forward. Findings Causal effect of the gap in intangible endowment and competitiveness of Russian companies compared with European rivals is revealed. According to our analysis, gaps in productivity, strategy implementation, qualifications of the board of directors and company location play critical roles in the global competitiveness of Russian companies. Meanwhile, underinvestment in structural resources, such as enterprise resource planning (ERP) systems and other intangible assets, are considered positive factors that reduce gaps in EVA. Originality/value The paper introduces original approach for studying the gap in performance caused by the gap in used resources.

In this paper, we rethink the corporate digital divide, a phenomenon not studied in detail in prior research. Motivated by innovation-diffusion, competence-based and skill-biased technical change theories, we hypothesize that all digital technologies’ innovations must be supported by demand for related skills and should be integrated into an innovation cycle. This research is conducted using a vast dataset of 1000 large Russian firms observed over ten years, with information collected from open internet-based sources and processed through content analysis. Among the key findings, the digital-innovation cycle has been explored and visualized, by identifying the most probable period of these innovations and their further diffusion. The digital-divide concept has been explicated by examining data on the relative dynamics of digital skills demanded by the same companies during the period of investigation. The empirical results deliver an interesting insight and encourage us to rethink the corporate digital divide through causality between competency accumulation and digital technological shifts. That, in turn, identifies the conditions necessary for the prediction of demand shocks in relation to digital competencies in labor markets.

Purpose – The purpose of this paper is to explore the plausibility of six elements of IC and justify the measurement ability of a set of indicators based on publicly available data for each of the proposed element in order to provide tools to managers for their decision-making process in knowledge management (KM). Design/methodology/approach – Core company's intangibles are combined into six intellectual capital (IC) elements that appear after the division of each of the traditional components (human, structural and relational capital (RC)). The human capital includes management and human resources capabilities (HRC). Structural capital is divided into innovation and internal process capabilities (IPC). RC contains networking capabilities and customer loyalty. In drawing on the relevant literature each element is described through a set of indicators collected from publicly available data. The validity of proposed IC model is justified through structural equation modeling. Each element is tested on a sample of more than 1,650 listed European companies over the period of 2004-2011. Findings – The study gives empirical support of three component IC structure and its decomposition into second level. The findings reveal that implementation of KM plays a significant role for HRC as well as for IPC. Research limitations/implications – The analysis was conducted for a particular sample that may restrict the conclusions. Practical implications – The proposed measurements for intangibles can be applied by any company for benchmarking and comparative analysis in KM. Originality/value – The study provides empirical justification of metrics for intangibles allowing a better route in an economy driven by knowledge.

PurposeThe purpose of this paper is to present a framework that is developed for analysis of intellectual capital transformation into companies’ value, including an identification of the key factors of this process.Design/methodology/approachThe paper employs intellectual capital on the intersection of value‐based management (VBM) and the resource‐based view (RBV). Starting from a review of the results provided in the literature regarding intellectual capital (IC) evaluation and its link with firm performance, a system of proxy indicators related to IC transformation in both concepts has been designed. The evaluation ability of the developed model was justified using regression analyses.FindingsA detailed algorithm for intellectual capital evaluation in terms of input‐outcome transformation. The intellectual capital transformation evaluating model (ICTEM) provides a holistic view of intellectual resources as companies’ strategic investments.Research limitations/implicationsThe paper emphasizes that the ICTEM framework could be mostly applied for the analysis of a firm as a typical representative of the industry or the country. In that sense it is not applicable for specific feature analysis of a company.Practical implicationsThe paper highlights the ICTEM as a tool of investment decisions, mostly taking into account common trends, the prospects of industries, and economies’ development.Originality/valueThe ICTEM provides the ostensive framework of intellectual capital transformation analysis using a statistical approach.

The purpose of this research is to develop cost-effectiveness tools for the analysis of company?s intellectual resources, in terms of resource-based and value-based approaches. Our study focuses on the evaluation of intellectual capital methods to discover the drivers of company growth. We suppose that the potential effectiveness of intellectual capital resources varies according to different institutional factors. Several statistical methods will be used for the empirical issues in this research, including common cross-sectional and panel data analysis, and the instrumental variables method. The database collected for this purpose will consist of financial and economic indicators underlying the intellectual capital evaluation, such as strategic performance indicators (EVA? and FGV?). The dataset includes companies from different countries and industries according to the Knowledge Economy Index of the World Bank. The industries presented in the dataset are selected according to the predominance of several intellectual capital elements. The database includes financial services, wholesale and retail trade, machinery and equipment manufacture, the chemical industry, and transport and communications. As a result of the empirical research, we expect to answer the following questions: ? Is there a close relationship between intellectual capital quality and company performance? ? What are the external and internal factors affecting this relationship? (country, industry, company size, market dynamics, etc.)

This study explores the successful strategies of companies during the 2008-2009 economic crisis. We investigate whether it is reasonable for companies to intensify intangibles when markets fall. This paper aims to find empirical evidence that companies with a clear intangible-intensive profile are likely to outperform those without a strategy. The results established in this study shed some light on the global economic crisis in 2008-2009. More than 1600 European companies were involved in the empirical analysis. The findings of this study demonstrate that companies with a conservative profile in intangibles outperform moderate and innovative ones. Still an innovative profile enables a faster recovery after a crisis.

This study explores corporate strategies regarding intangibles. We argue that companies consciously or unconsciously follow particular investment strategies in intangibles by allocating resources among intangible assets. The key contribution of our research is a new way to classify companies according to intangibles employed. The research question is if intangible-intensive profile exists. For the purpose of our each profile is identified on the intersection of the relevant theory of intellectual capital and empirical investigation. The intellectual capital concept enables elaboration of the framework of each company's profile. The empirical analysis provides us with the clusters matched with the theoretical framework. The database consists of about 1700 listed European companies observed from 2004 till 2011. The database includes figures from annual statistics and financial reports. The information about intangibles was collected from publicly available sources like company websites, patent and information bureaus, and rating agencies. As a result more than 20 indicators are involved in the analysis. K-means clustering allows us distinguishing four major profiles of intangible-intensive companies.The empirical analysis allows identification of three profiles of companies: two of them (innovative and conservative) represent intangible intensive strategy. The third profile that doesn't have clear priorities in intangibles was called in this study moderate (low) and was used as a benchmark to examine if intangible-intensive profiles enable better performance.

Purpose – The purpose of this paper is to reveal and empirically validate a new typology of company strategic profiles regarding intangible resources. Design/methodology/approach – The study is carried out in three steps. The first stage comes to identify the coordinates of intangibles in which strategic profiles are found. The second stage enables a clusterization of more than 1,600 European companies observed during seven years in the coordinates of intangibles. The last step introduces comparative analysis of these clusters in terms of their performance. Findings – As a result of empirical analysis three strategic profiles regarding intangibles are discovered. Two of these profiles are called intangible-intensive as they demonstrate clear predominance of a particular set of intangibles. The innovative profile is associated with intensive investment in innovation and networking capabilities. The conservative profile puts emphasis on managerial capabilities and development of business process. The non-intangible-intensive profile, that has been called moderate, evenly allocates resources among intangibles keeping them on a low level relative to the intangible-intensive profiles. Practical implications – This research is useful for practitioners in strategic and knowledge management. It provides insight into common features of company strategies for intangibles as well their impact on short- and long-term performance. Originality/value – This work contributes to the field of strategic knowledge management by demonstrating a new relevant typology in company behavior regarding intangibles. Moreover, it equips decision makers in companies with a tool to design strategic vision in intangibles.