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Using Functions of Innovation Systems to Understand the Successful Emergence of Non-traditional Agricultural Export Industries in Developing Countries: Cases from Ethiopia and Chile

Author

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  • Michiko Iizuka

    (United Nations University (UNU-MERIT))

  • Mulu Gebreeyesus

    (Ethiopian Development Research Institute (EDRI))

Abstract

Development of new export industries provides an important stimulus for economic growth and structural transformation in developing countries. In any country, numerous new export industries, whether initiated by the government or private sector, are always being pursued, but only a few become successful due to inherent uncertainties in new activities. In this paper, we adopted the functions of innovation systems framework to understand the process of system building through examination of the successful emergence of two non-traditional agricultural export industries in developing countries, namely the Ethiopian flower industry and the Chilean salmon industry to identify effective policy measures in the early phases of development.

Suggested Citation

  • Michiko Iizuka & Mulu Gebreeyesus, 2017. "Using Functions of Innovation Systems to Understand the Successful Emergence of Non-traditional Agricultural Export Industries in Developing Countries: Cases from Ethiopia and Chile," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 29(2), pages 384-403, April.
  • Handle: RePEc:pal:eurjdr:v:29:y:2017:i:2:d:10.1057_s41287-016-0004-0
    DOI: 10.1057/s41287-016-0004-0
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    2. Kuzminov Mykola, 2017. "Determination of agricultural export features in developing countries," Technology audit and production reserves, 5(37) 2017, Socionet;Technology audit and production reserves, vol. 5(5(37)), pages 49-54.
    3. Awe, Olushina Olawale & Musa, Ann Precious & Sanusi, Gbenga Peter, 2023. "Revisiting economic diversification in Africa's largest resource-rich nation: Empirical insights from unsupervised machine learning," Resources Policy, Elsevier, vol. 82(C).

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