@ARTICLE{26543116_505888677_2021, 
	author = {Kiarash Fartash and Mahdi Elyasi and Amir Ghorbani and Aliasgar Sadabadi}, 
	keywords = {, policy learning, challenges, lessons, development strategy, foresight, Republic of Irantechnology and innovation policy},
	title = {<p class="text">Innovation Policy Learning in Iran&rsquo;s Development Plans</p>},
	journal = {Foresight and STI Governance},
	year = {2021},
	volume = {15},
	number = {3},
	pages = {81-92},
	url = {https://foresight-journal.hse.ru/en/2021-15-3/505888677.html},
	publisher = {},
	abstract = {Apart from "future-shaping" tools (such as forecasting, scenario planning, etc.), many countries also use "backward-looking" approaches to develop long-term strategies for switching to a new economic model. A retrospective assessment of accomplishments and failures (or policy learning, PL) helps learn lessons, and improve the effectiveness of innovation policy.Using the example of Iran, the paper examines the use of PL to assess key initiatives in the field of science, technology, and innovation over the past two decades. Field research allowed to identify the main policy goals, analyse their evolution and the changes in the perception of previously made decisions by politicians themselves. The active use of technical and conceptual PL indicates a relative progress in adjusting the policy vector. At the same time partisan policy learning remains common, applied to legitimise the current course, which indicates insufficient maturity of Iran&rsquo;s political system (as is the case in many other developing countries). It is concluded that to make real progress and increase the effectiveness of innovation policy, technical, conceptual, and social PL should be applied, while keeping the use of partisan&nbsp; policy learning at the minimum.},
	annote = {Apart from "future-shaping" tools (such as forecasting, scenario planning, etc.), many countries also use "backward-looking" approaches to develop long-term strategies for switching to a new economic model. A retrospective assessment of accomplishments and failures (or policy learning, PL) helps learn lessons, and improve the effectiveness of innovation policy.Using the example of Iran, the paper examines the use of PL to assess key initiatives in the field of science, technology, and innovation over the past two decades. Field research allowed to identify the main policy goals, analyse their evolution and the changes in the perception of previously made decisions by politicians themselves. The active use of technical and conceptual PL indicates a relative progress in adjusting the policy vector. At the same time partisan policy learning remains common, applied to legitimise the current course, which indicates insufficient maturity of Iran&rsquo;s political system (as is the case in many other developing countries). It is concluded that to make real progress and increase the effectiveness of innovation policy, technical, conceptual, and social PL should be applied, while keeping the use of partisan&nbsp; policy learning at the minimum.}
}