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Optimal strategies for intangibles

Priority areas of development: economics
2017
The project has been carried out as part of the HSE Program of Fundamental Studies.

Goal of research: to develop a theoretical model and test empirically optimal parameters of investment strategies for intangibles in companies and organizations. The approach proposed in the project gives an opportunity to analyze the different aspects of the strategic behavior of economic agents associated with the intellectual capital phenomenon. Intangible resources are considered as the key determinant for competitiveness of organizations in the knowledge-driven economy. One of the fundamental principles of the proposed integrated approach is the transformation of the intangible nature of intellectual resources into a system of metrics (proxy-indicators) based on public available data. The elaborated system of metrics has been validated on an extensive empirical database.

Methodology: This project uses theoretical modeling tools to justify the optimal investment strategies for intangibles. The empirical validation of the proposed integrated approach has been carried out by the set of advanced econometrics techniques. The analysis of the relationship between investment in intellectual resources and company performance enabled the interpretation of causal links. The panel structure of the data employed has allowed the lagged variables’ and fixed effects’ modeling, generalized and simulated methods of moments (GMM, SMM), and the three-stages least square method (3SLS). This has improved consistency and efficiency of estimates by reducing bias brought by endogeneity. The "difference-in-difference" method is implemented to evaluate the impact of the intangible-intensive strategy (through moderation effect and dummy regression analysis). Structural equation modeling (SEM, SEM-PLS) is used to identify and estimate the latent characteristics of the intellectual resources.

Empirical base of research: This study has been carried out on the two databases of European and Russian Companies. The data settings comprise financial and non-financial indicators that reflect quantitative and qualitative characteristics of intangibles. All indicators are compiled from open sources: financial statements and annual statistical reports as well as official websites of companies, patent and information bureaus, and rating agencies. The results of the empirical testing have been validated trough a set of robustness checks. In addition, several databases have been employed to analyze the aspects related to investment in intangibles in family business and in sports industry.

The first is the database of more than 1600 public joint-stock companies representing the five European countries: United Kingdom (44%), Germany (24%), France (25%), Spain (5%) and Italy (2%). These companies are observed over 13 years starting from 2004. The structure of the sample is representative according with the country and sectorial structure of EU economies.  The industry sector is structured as follows: management of companies and enterprises (25%), manufacturing industry (20%), professional, scientific and technical services (12%), finance and insurance (10%) and other industries (33%). Large enterprises account for 64% of the sample with small- and medium-sized companies accounting for 36%.

The second data setting is based on a sample of 1096 public Russian companies observed within a period 2004-2014. Despite the bias towards large business, the industry structure corresponds to the general population according to the Statistical Classification of Economic Activities in the European Community (NACE). Thus, the proportion of manufacturing enterprises is 46%, electricity – 19%, the other industries, including services, construction, trade and finance, account for 35%.

To justify the aspects of the strategic behavior of companies regarding investment in human capital, namely the analysis of CEO remuneration, the database of 330 large (as defined by Eurostat – with over 250 employees) European traded companies has been used. The sample is the data on 7 European economies across a time period from 2008 to 2013 (UK, Germany, France, Switzerland, Italy, Spain and the Netherlands), in 19 sectors of the economy according to the NACE classification.

The 2000-2014 database compiled on 88 Chilean companies is used to test the hypotheses about the impact of investment in relational capital on the performance of family businesses. The Chilean family companies were chosen for the analysis due to the high degree of ownership concentration of individual shareholders or business groups that control firms through direct investment and pyramid structures. The final sample includes 1018 observations, 731 of which relate to family firms, 287 – to non-family businesses.

The testing of hypothesis related to the study of specific aspects of corporate governance as a key intangible resource for organization prosperity is based on the sample of 22 teams. The criteria for selecting teams were: the most frequent listing on the Deloitte "Football Money League" – 20 teams with the largest incomes within the continent. The sample includes the strongest in terms of finance and sporting achievements. The sample structure is as follows: six teams – from the English Premier League, five – from the Italian Serie A, four – from the German Bundesliga, three – from the Spanish La Liga, three – from the French League 1, and one from Turkey (Galatasaray).

The database for empirical analysis of the impact of human capital on the performance of football clubs includes 138 teams of the United States Major Soccer League (MLS) for 2005-2013. However, only 12 teams have the data available for the entire period covered. The exceptions are the teams that have been in MLS after 2005: Toronto FC (2007), San Jose Earthquakes (2008), Seattle Sounders (2009), Philadelphia Union (2010), Portland Timbers (2011), Vancouver Whitecaps (2011) and Montreal Impact (2012).

Results of research: The research results can be presented as follows:

Theoretical contribution

  • A theoretical model of companies’ recovering process in terms of value creation and its acceleration has been developed.
  • Parameters of intangibles-intensive strategies that allow higher rate of recovery after the economic crisis 2008-2009 have been theoretically modeled and justified.
  • Profiles of the intangibles-intensive strategies that provide better flexibility in business processes and offer higher rate of response to the economic turbulence have been defined.

Contribution to the methodology

  • The system of proxy indicators for intellectual resources based on publicly available data have been developed and empirically validated.
  • The approach to testing the dual causal link between human capital investments and company performance has been described.

Empirical contribution

  • The key patterns of companies' behavior on intangibles-intensive strategy have been identified. These patterns have been tested against their ability to accelerate recovery after the economic crisis of 2008-2009.
  • The impact of top management remuneration scheme on company performance has been established.
  • The role of relational capital, namely, affiliation with business groups, in creating the value of a family business has been revealed.
  • The relationship between various aspects of corporate governance in sports industry that follow the intangible-intensive strategy has been explored.

Publications:


Lopez Iturriaga F. J., Díez-Esteban J. M., García-Gómez C. D., Santamaría-Mariscal M. Corporate risk-taking, returns and the nature of major shareholders: Evidence from prospect theory // Research in International Business and Finance. 2017. Vol. 42. P. 900-911. doi
Coates D. C. Weaponization of Sports: The Battle for World Influence through Sporting Success // Independent Review. 2017. Vol. 22. No. 2. P. 215-221.
Torres J. P., Jara Bertín M., Lopez Iturriaga F. J. Corporate control and firm value: The bright side of business groups // Journal of Family Business Strategy. 2017. Vol. 8. No. 2. P. 99-108. doi
Coates D. C., Naidenova I. N., Parshakov P. Determinants of Russian Football Club Brands // International Journal of Sport Finance. 2017. Vol. 12. No. 4. P. 321-341.
Bykova A. Impact of Industry Concentration on Innovation: Evidence from Russia // Journal of Corporate Finance Research. 2017. Vol. 11. No. 1. P. 37-49.
Gasparetto T. M., Barajas A. Fan preferences: one country, two markets and different behaviours // European Sport Management Quarterly. 2018. Vol. 18. No. 3. P. 330-347. doi
Sánchez L. C., Barajas A., Sánchez- Fernández P. Does the Agency Theory play football? // Universia Business Review. 2017. No. 53. P. 18-59. doi
Parshakov P., Zavertiaeva M. A. Companies intangibles: Unique versus generic // International Review of Economics and Finance. 2017. Vol. 49. P. 266-275. doi
Parshakov P., Байдина К. О. Brands or Uncertainty? An Empirical Test of the Uncertainty of Outcome Hypothesis in Russian Football / NRU Higher School of Economics. Series WP BRP "Economics/EC". 2017. No. WP BRP 163/EC/2017.
Smirnova A. S., Zavertiaeva M. A. Which came first, CEO compensation or firm performance? The causality dilemma in European companies // Research in International Business and Finance. 2017. No. 42. P. 658-673. doi
Shakina E. A., Barajas A., Parshakov P., Chadov A. L. Status-Quo vs New Strategy in Intangibles // Journal of Economic Studies. 2017. Vol. 44. No. 1. P. 138-153. doi