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: This study explores the strategies adopted by companies during the economic crisis of 2008-2009. It investigates whether it is reasonable for companies to intensify their investment in intangibles during recession periods. The purpose of this paper is to find empirical evidence that companies with clear intangible-intensive profiles are likely to outperform those without a clear strategy. Design/methodology/approach: This paper explores the intangible-intensive strategies of companies in terms of their dynamics during the pre-crisis, crisis and post-crisis periods. Through dummy regression applied to data from more than 1,600 European companies involved in the empirical analysis, the paper aims to show moderating effects from intangible-intensive strategies on company performance, expressed in terms of economic value added and market value added. Findings: The results established in this study shed some light on the global economic crisis in 2008-2009. The findings of this study demonstrate that companies with a conservative profile towards intangibles outperform both those without a defined profile and those with an innovative one. However, an innovative profile enables faster recovery after a crisis. Originality/value: This paper contributes to the literature on the strategic management of companies, and highlights the particular importance of intangible-intensiveness when markets experience systematic distresses. It is emphasized that lessons learned during the recent global economic crisis must be taken into account in the strategic vision of any company.
Purpose. Investments in intellectual capital (IC) are often linked to competitive advantages that improve economic profit and increase the value of a company. However, this effect is reciprocal: Companies that generate higher cash flow can invest more in intellectual capital. The aim of this study is to analyze a dynamic relationship between IC components and economic profit, with a special emphasis on industry specific effects in pharmaceutical, retail, steel, telecommunications, and service sectors.
Design/methodology/approach. Panel vector autoregression (VAR) was used to deal with the mutual influence of intellectual capital components, the lag effect, and heterogeneity. The data was taken from Compustat database and covers the period from 2001 to 2010.
Findings. This research proves that there is interaction between investments in the IC components and company performance. However there are sectoral differences: there is a positive impact of economic profit on human capital in retail; in the steel industry a mutual influence is revealed. Moreover, interaction between different IC components is detected in telecommunication and steel industries.
Originality/value. This is the first study to present clear evidence of the effects of performance on IC investment decisions. The time lag in the effects of IC investments was estimated and compared for different industries. On the methodological side, the paper presents a rather simple method capable of yielding results consistent with other studies and yet rich enough to be applied to an analysis of sectoral differences in dynamic IC investment decisions.
В статье представлен подход к анализу трансформации интеллектуальных ресурсов компании в стоимость. В том числе представленная модель позволяет эмпирически выявить внешние факторы, которые могут влиять на эту трансформацию. Модель ICTEM позволяет на основе открытой информации о компаниях провести оценку статистической взаимосвязи задействованных в деятельности компании неосязаемых ресурсов и результатов ее деятельности. В статье представлены прокси показатели интеллектуального капитала, отражающие как качество и количество вовлеченных ресурсов, так и полученную от них отдачу. Помимо этого авторам удалось провести апробацию предложенного подхода, проанализировав панельные данные более чем 400 европейских компаний за период с 2005 по 2009 г.г.
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.
Purpose – The purpose of this paper is to present a framework that helps to analyze the dependence between personal welfare and individual (personal) intellectual capital (IIC). The authors also introduce the system of proxy indicator for personal intellectual capital (IC) of football coaches. Design/methodology/approach – This paper employs the idea that personal welfare depends on personal IC, particularly, talent. That is why initially the literature analysis of welfare phenomenon was provided. Then the system of available proxy indicators of football coaches’ IC was designed. To achieve the purpose a linear function is estimated with the help of ordinary least squares method. Findings – The chosen set of IC proxy indicators explain the significant part of coaches’ salary. Such proxies as improvement in the championship table and coach’s image in media have a significant and positive influence on coach’s salary. Whereas, lowering the position of the club does not considerably affect the coach’s wealth. A clubs’ financial capacities and budget also influences coaches’ salaries. Research limitations/implications – Traditional limitation of proxy indicators-based studies is connected with their eligibility and complexity. Practical implications – The possibility to codify IC of a person enables to analyze core competencies necessary in a particular activity or profession for success achievement. Moreover a policy of inequality reduction should take into account that intangible assets are at the base of those persons wealth. Originality/value – This is the first paper that employs IC concept to people wealth while previous literature is dedicated to companies’ or countries’ IC.
Based on an efficiency analysis of the Global Entrepreneurship Index (GEI), the purpose was to demonstrate that the Key Performance Indicators’ analysis leads to a misinterpretation of the dynamics of National Systems of Entrepreneurship (NSEs). This might hamper the formulation of sound initiatives in other economies, with relevant implications for developing countries.
This study categorized GEI indicators into output and input indicators. Following this procedure, each dimension was analyzed separately and then compared to each other, considering countries’ productivity rates. The main focus is given to the case of the US, the usual benchmark for NSEs and leader in the GEI Index. Lastly, a taxonomy of NSEs according to their efficiency levels was developed.
The findings of the analysis demonstrates that innovation-driven economies with lower positions in GEI ranking often have higher productivity rates when compared to economies with higher positions in GEI ranking. Specifically, the US appears not to be a good benchmark in terms of NSE efficiency.
The study’s approach is limited in scope by data availability on NSEs and the use of GEI, a representation of aggregate patterns of country-level entrepreneurial dynamics. More refined data are needed in order to clarify some insights from this research.
The perception of systemic efficiency should be considered more thoroughly when designing dedicated entrepreneurship-oriented policies in other countries that aim at establishing a more vibrant entrepreneurial system while facing resource constraints.
Simplistic views of systemic aspects may hamper the formulation of sound entrepreneurship-oriented initiatives with particularly relevant implications for public policy in laggard economies.
The value of this article relies on applied a simple metric – efficiency ratio – order than, e.g. data envelopment analysis to portray a key issue related to the interpretation of supranational rankings related to the entrepreneurship ecosystem make mainly by policymakers and scholars that is: pick the 1st one, follow the leader.