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Intangible assets and resource allocation: insights from European companies

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  • Mihaela Curea

    ("Alexandru Ioan Cuza" University of Iasi, Iasi, Romania)

Abstract

This study aims to explore the nexus between CEO-Chair duality, leverage, and investments in intangible assets within the realm of energy companies listed in the European Union (EU) using multi-theoretical lenses. Robust regression is employed to analyse the panel dataset. Energy companies listed in the European Union are analysed for the period 2011-2020. Findings reveal that leverage and CEO-Chair duality exert a positive influence on investments in intangible assets. By separating the roles of CEO and Chairman and adopting appropriate leverage levels, firms can enhance their ability to invest in intangible assets, fostering innovation and improving their competitive position in the market. The results offer valuable insights for academic researchers, practitioners in the electricity and gas industry and investors, aiding in informed decision-making and resource allocation strategies.

Suggested Citation

  • Mihaela Curea, 2023. "Intangible assets and resource allocation: insights from European companies," Journal of Financial Studies, Institute of Financial Studies, vol. 8(15), pages 86-105, November.
    • Handle: RePEc:fst:rfsisf:v:8:y:2023:i:15:p:86-105
    DOI: 10.55654/JFS.2023.8.15.05
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    More about this item

    Keywords

    intangible assets; leverage; duality; European companies.Journal: Journal of Financial Studies;
    All these keywords.

    JEL classification:

    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • E22 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Investment; Capital; Intangible Capital; Capacity
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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