Modeling Iranian innovation network in nanotech for policy: applying an adopted version of SKIN model
Authored by Morteza Mahmoudzadeh, Mahmood Alborzi
Date Published: 2017
DOI: 10.1108/jstpm-08-2016-0017
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Platforms:
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Model Documentation:
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Abstract
Purpose - Iran Nanotechnology Initiative Council could significantly
increase the production of scientific articles in the field by imposing
ten-year incentive policies so that Iran ranked 7 in this area in the
year 2015. But this progress was insufficient to speed up the production
and commercialization of nanotechnology products and Iran ranked 44 with
a share of 0.03 per cent of nanotechnology production in the world.
Therefore, Iran Nanotechnology Initiative Council as a governmental
policymaker institution in this area has sought for the policy threefold
increase of funding to speed up the production and commercialization of
products in this field. But given that the result was not so clear, this
research was formed in the form of modeling Iran Nanotechnology
Innovation Network and testing various scenarios to increase its
efficiency.
Design/methodology/approach - This paper uses simulation framework of
innovation networks (SKIN) in an attempt to model the production
innovation network in Iran in the field of nanotechnology that can
measure the effect of incentive policies in changing the network
structure and, consequently, increasing the level and pace of innovation
in it. Given that the volume of articles produced in Iranian
universities in the field of Nanotechnology had a high speed and volume
in comparison with the volume of technical knowledge produced by
companies, and because the SKIN framework did not consider the
distinction between the two, in the first step, the framework is
developed using the model of absorptive capacity of knowledge provided
by Cohen and Levinthal (1990) and then the developed model was used to
model the Innovation Network.
Findings - Finally, two policies of threefold increase of budget
(Scenario 1) and increasing the support for joint projects (with
maintaining the current budget level) (Scenario 2) were tested in this
model. The social network analysis method was used to analyze the
results of the two scenarios, where innovation network topology was
compared (as an index to measure the network efficiency) in three states
of current status of the network (the baseline scenario), implementing
the first and second scenarios of extraction and with each other.
Originality/value - This paper models Iranian Nanotechnology Innovation
Network for studying the evolution of the network as a result of
executing different supportive scenarios.
Tags
Agent-based modeling
knowledge
diffusion
Innovation networks
perspective
Science
Determinants
Skin framework
Social
networks analysis