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Neoclassical versus evolutionary economics in developing countries: convergence of policy implications

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Abstract

This paper aims to determine whether the dichotomy between the science, technology, and innovation policy based on neoclassical and evolutionary schools of economics is applicable to developing countries. Regarding the fundamental differences in foundations of these two economic paradigms, policymakers have been forced to select and to follow one of the two seemingly competing views. However, in developing countries, due to various market and government coordination failures, complying with one of the schools has not been successful in practice. From the past, there has been some controversy between neoclassical and evolutionary schools on the subject of science, technology and innovation policy. Using a survey questionnaire and statistical analyses of the results, this paper shows that, due to the institutional setting and structural conditions in developing countries, despite the fundamentally different foundations of the competing schools of thought, the policy implications of the schools have converged. Drawing on Theme Analysis Method, the rationales are first conceptualized and then the fuzzy method is applied to reveal the respondents’ tendency to the extracted rationales and implications of the two competing schools. In conclusion, the statistical results validate the proposed hypothesis.

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Notes

  1. Please see (Lall and Teubal 1998) and (Bach and Matt 2005).

  2. Basic research, applied research and development - R&D, collectively, make up a structure referred to as the linear model of innovation. The model postulates that innovation starts with basic research, then adds applied research and development, and ends with production and diffusion. For almost half a century, this formation has played a decisive role in policymaking (Godin 2006) .

  3. Similar to the other members of the target population, they are graduates of the related field of science and innovation policymaking, and have work experience in this field. Five People, who have related educational and work experiences, were selected randomly as the assessors, and after implementing the assessment, they were set aside from the target population and did not complete the finalized questionnaire.

  4. The first educational program for technology and innovation policymaking in Iran was established in 2000 in the form of training courses (not an academic program), the participants in these training courses fewer than ten individuals. However, in 2010 a doctorate program was established in Tarbiat Modares University for science and technology policymaking studies. In the first year, four students were accepted. Also from 2005 four other universities in Tehran started other related programs such as technology management, entrepreneurship management, future studies in the frame of graduate programs (Master and PHD) with limited entrances. Based on the correspondence with the Vice-Presidency for Science and Technology, by 2013, when this study was conducted, fewer than 500 people in fields related to technology and innovation graduated.

  5. Key institutions (organizations) related to science and technology policymaking in Iran are as follows: vice-presidency for science and technology; Supreme council of cultural revolution; Ministry of science, research and technology; sections related to technology policymaking in ministries of information and communication technology, Oil, Energy, Defense, Health and treatment and medical education, Agriculture jihad. According to the estimates, fewer than 450 individuals in above-mentioned organizations are working in related field of innovation and technology policymaking, and more than 70% of these people have studied fields other than innovation and technology policymaking.

  6. The clustering method is utilized when the number of clusters is unknown, and when the numbers of clusters is given, the discrimination and classification test is utilized.

  7. The Mahalanobis distance is a measure of the distance between a point P and a distribution D, introduced by P. C. Mahalanobis in 1936. It is a multi-dimensional generalization of the idea of measuring how many standard deviations away P is from the mean of D.

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Authors and Affiliations

  1. Department of Information Technology, Tarbiat Modares University, Tehran, Islamic Republic of Iran

    Sepehr Ghazinoory, Meysam Narimani & Shiva Tatina

Authors
  1. Sepehr Ghazinoory
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  2. Meysam Narimani
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  3. Shiva Tatina
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Correspondence to Shiva Tatina.

Appendices

Annex No. 1

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Annex No. 2

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Annex No. 3

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Ghazinoory, S., Narimani, M. & Tatina, S. Neoclassical versus evolutionary economics in developing countries: convergence of policy implications. J Evol Econ 27, 555–583 (2017). https://doi.org/10.1007/s00191-017-0490-z

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