A Computational Approach to Uncovering Economic Growth Factors

Mohsen Ahmadi ()
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Mohsen Ahmadi: Urmia University of Technology

Computational Economics, 2021, vol. 58, issue 4, No 5, 1076 pages

Abstract: Abstract The knowledge-based economy is the basis of economics in which all businesses and industries benefit from the distribution and application of knowledge in pursuit of their goals to meet their needs. But the prosperity and growth of a knowledge-based economy can only be achieved if the economic, socio-political and legal frameworks of a country have the necessary background to realize the required indicators of a knowledge-based economy. In this paper, the economy growth-effected knowledge-based indicators are classified and prioritized using logarithmic fuzzy preference programming. Based on the results, the institutional and economic regime has the priority in comparison with other measures in economic growth. The results of prioritizing alternative criteria show that the technology foundation, structure of trained manpower, trade and capital, employment and economical trademark, respectively affect economic growth. Furthermore, the trade-related indicators are a low effect on economic growth, however, the technology-related indicators are most effective on it. Therefore, today’s oil and export economies are less prioritized than the application of knowledge, and in today’s world, the industrial economy cannot be advanced and must move towards a knowledge-based economy.

Keywords: Economic Growth; Knowledge-based economy; Logarithmic fuzzy preference programming; Tukey method; Grouping; Prioritizing (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10614-020-09985-1

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