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Valuation And Optimization Of The Impact Of Intellectual Capital On Organizational Performance

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  • Feruccio Bilich

    (Universidade de Brasília - UnB – Brasil)

  • Ricardo da Silva

    (University of Brasilia – UnB – Brasil)

Abstract

Intellectual capital is the pre-eminent resource for creating economic wealth. Tangible assets such as property, plant and equipment continue to be important factors in the production of both goods and services. However, their relative importance has decreased over time as the importance of intangible, knowledge-based assets has increased in developing and maintaining a competitive advantage, value creation and competitiveness. This paper prescribes policies for optimizing intangible assets such as Intellectual Capital or, in other words, how and where the organization should invest, with minimum effort, in order to improve its market value and competitiveness in the technology-driven world.

Suggested Citation

  • Feruccio Bilich & Ricardo da Silva, 2008. "Valuation And Optimization Of The Impact Of Intellectual Capital On Organizational Performance," Portuguese Journal of Management Studies, ISEG, Universidade de Lisboa, vol. 0(3), pages 341-359.
    • Handle: RePEc:pjm:journl:v:xiii:y:2008:i:3:p:341-359
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    References listed on IDEAS

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    1. Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
    2. Arora, Ashish & Gambardella, Alfonso, 1994. "The changing technology of technological change: general and abstract knowledge and the division of innovative labour," Research Policy, Elsevier, vol. 23(5), pages 523-532, September.
    3. Cohendet, Patrick & Steinmueller, W Edward, 2000. "The Codification of Knowledge: A Conceptual and Empirical Exploration," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 9(2), pages 195-209, June.
    4. Richard R. Nelson, 1982. "The Role of Knowledge in R&D Efficiency," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 97(3), pages 453-470.
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    2. Miłosz Kadziński & Magdalena Martyn, 2021. "Enriched preference modeling and robustness analysis for the ELECTRE Tri-B method," Annals of Operations Research, Springer, vol. 306(1), pages 173-207, November.

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