Purpose: The purpose of this paper is to review literature devoted to intangibles and their valuation and give examples of the methods that can be used for valuation of individual intangibles in financial terms.Design/methodology/approach: Paper presents a systematic review of articles dedicated to intangibles and their valuation.Findings: This review shows that there is a need for consensus in definitions of intangibles, intangible assets, knowledge assets and other related terms. These terms are used interchangeably in spite of their different meanings. Many methods for valuation of intangibles can be found in the literature, but widely accepted list of basic intangibles with suggested methods for their valuation in financial terms is still missing.Research limitations/implications: Not all the papers related to this topic could be covered in this paper. Presented list of important intangible components may be enhanced and examples of some other methods for their valuation may be added in the future.Practical implications: Paper calls for development of framework comprising list of the most important intangibles, proposals of methods used for their valuation and examples of their use. This framework can be helpful for organization, which are confronted with a difficult task of intangibles valuation.Originality/value: Basic definitions and differences between intangibles, intangible assets, identifiable intangible assets, knowledge assets and intellectual capital have not been mentioned in one paper yet. List of intangibles and methods for their valuation gives a direction for future work that can be fruitful for valuation of intangibles.

The impact of corporate intangibles on a company’s market value has been a widely debated topic. A large body of literature has separately examined the industry’s effect- or firm-specific attributes, such as industry type, company size, company age, or indebtedness and profitability, on the motivation to disclose information on intangible assets, but without considering a comprehensive view. This paper examines the role intangible assets play in a firm’s market valuation besides other firm-specific characteristics. The reducted dataset we use in this study comprises 250 publicly traded companies operating in four different business sectors in France, Germany, and Switzerland for the ten years from 2009 to 2018. Based on the panel data regression models, the study provides an extension of previous knowledge about the effect intangible assets may have on the investors’ view of a company’s value, where the value added of this paper is the empirical evidence of a possible link between the intangible assets’ disclosure and the market value of German, French, and Swiss enterprises. The importance of our contribution lies in a comparative analysis carried out to reveal substantial differences in the impact of intangible assets and innovation activity on the market value firms in three European countries and across four industry sectors. Although the results show the positive impact of intangible assets on the companies’ market value, we suggest that investors still assess companies based on their profitability rather than considering the information on intangible assets the enterprises disclose in their financial statements.

This study explores the impact of environmental, social, and governance (ESG) factors on profitability and market capitalization within the European automotive industry. Since the industry is confronted with environmental and regulatory challenges, ESG contributions are valuable to know for strategic decision making and investor attitude. With panel data from 60 automotive firms listed on the Eurostoxx 600 index from 2011 to 2022, the research utilizes panel regression techniques, such as the generalized method of moments, to control for possible endogeneity. The findings show that the social aspect of ESG has a positive effect on return on assets (ROA), illustrating that socially responsible efforts can strengthen operating performance. In contrast, environmental performance weakly negatively affects ROA, probably because substantial sustainability-related expenses are incurred. Governance has no significant impact on profitability. For market valuation, as captured by Tobin’s Q, social factors are negatively correlated, indicating investor doubt regarding quick returns on social investments, while governance is positively but weakly correlated. These results highlight the multifaceted nature of ESG integration in the automotive industry, with the implication that firms need to delicately trade off between sustainability initiatives and profitability and investor expectations.

The sustainability of agriculture in the common market of the European Union is mainly influenced by the income of agricultural enterprises, which reflects the development potential of the entire sector. The present contribution deals with the importance of income indicators for the long-term sustainability of agricultural enterprises. We aimed to identify and quantify statistically significant determinants of the main income indicators of agricultural enterprises in individual countries of the European Union—namely, the net added value of the farm expressed per unit of agricultural work, the family farm income per family work unit, and the net farm income. We performed a linear regression analysis, in which the statistical significance of independent variables was gradually tested, including economic and environmental indicators, the economic size of the enterprise, total subsidies per hectare, depreciation, taxes, and wages. The established goal was complemented by a correlation analysis tracking the dependence between the economic size of enterprises—which is presented in the literature as a decisive indicator—and the tax burden in EU countries. We used the Farm Accountancy Data Network’s harmonised database for 2009–2018. The regression analysis results confirmed the environmental indicators’ statistical significance. Furthermore, the results of the correlation analysis confirmed the proposed hypothesis that the size of the company is a strong indicator and affects the tax burden of agricultural enterprises.

This study explores the relationship between intellectual capital (IC) and the financial performance of 250 publicly traded companies in France, Germany, and Switzerland from 2009 to 2018, addressing the gaps in prior research regarding the differential impacts of IC components across countries and industries in Western and Central Europe. Using the Value-Added Intellectual Coefficient (VAIC™) approach, this study evaluates human capital efficiency (HCE), structural capital efficiency (SCE), and capital employed efficiency (CEE). Panel regression analyses at the country and industry levels were conducted to assess their effects on financial metrics, such as return on equity (ROE), return on assets (ROA), and asset turnover ratio (ATO). The findings reveal a significant positive association between SCE, CEE, and firm performance, with CEE showing the most substantial effect, while HCE had a relatively weaker impact. Additionally, the study uncovers a trade-off between the accumulation of patents and trademarks and short-term financial performance, raising new considerations for intellectual property management. This research contributes to the literature by providing a nuanced understanding of how IC components influence financial outcomes across different contexts and offers practical insights for firms aiming to optimize structural capital and capital-employed strategies for improved financial performance while acknowledging the limitations regarding the sample of publicly traded firms.

The intention of this paper is to provide new academic insights regarding an economically explainable valuation of transfer prices for European football players based on mathematical modeling. Football is the most popular sport in the world followed by approximately 3.5 billion people. The increasing commercialization and professionalization of the industry implies that every area of a football club is constantly put to the test for improvements. Especially after suffering financially under the consequences of the worldwide pandemic, clubs focus not only on sporting success but also on financial survival. Only financially stable clubs have the resources to be more successful. An expensive team does not have to be successful in terms of sports performance. However, a successful team in sports is expensive in the long run. Increasing digitalization offers new revenue potentials for football clubs that focus on selling merchandise in addition to gameday revenues and its media exploitation rights. However, player transfers have become increasingly important because these costs and revenues increased substantially in the relevance of a club’s financial situation. Regarding transfer costs, the question arises as to how transfer fees are determined and which factors have a major influence here. Clubs try to find new ways of evaluating the potential profit of player transfers to lower the risk of failed player investments. The aim of this article is to quantify the popularity of a football player in terms of his merchandising potential to amortize his transfer price. The mathematically formulated relationship calculates a reference value for a player, taking performance, age, number of customers purchasing merchandise, and player position into account. The information gained can be used by managers of European football clubs as a guide in transfer negotiations. For 6907 players of the European top leagues, we analyzed data in the period from 2003 to 2019. For 409 players in the season of 2018/2019 complete data sets were available, so that a model for calculating a theoretical transfer fee for a player during that season could be determined. The results of the study and the developed model suggest that, based on the available data, a football club should offer either one-year or three-year contracts to a transferred player, depending on the anticipated profit margin of merchandise sales and the quota of potential buyers of the products representing a percentage of the number of customers purchasing merchandise. This information gives football club’s management the chance to make better transfer decisions for the individual situation of the player and the club itself. Due to the increased importance of transfers on a football club’s financial performance, better transfer decision making leads to an improved financial stability of the respective clubs and eventually to sporting success.