The Role of Technology Foresight in Prioritizing Science and Technology Policies in Iran: Evidence from an Expert-Based Assessment of Transformative Technologies

Document Type : Research paper

Authors

1 Assistant Professor of Futures Studies,National Research Institute for Science Policy(NRISP), Tehran, Iran

2 PhD Candidate Energy , Sharif University of Technology, Tehran, Iran

3 STI Policy Researcher, Institute for Science and Technology Studies, Shahid Beheshti University, Tehran, Iran,

Abstract

The accelerating pace of scientific and technological change, increasing interdisciplinary convergence, and growing uncertainty regarding future trajectories have posed fundamental challenges for science and technology policy making. Under such conditions, reliance on purely retrospective approaches and uniform support policies is not only ineffective but may also lead to resource fragmentation and increased policy decision errors. This article examines the role of technology foresight in improving the prioritization of science and technology policies in Iran and demonstrates how structured expert-based assessment can function as an effective decision-support tool under conditions of uncertainty. Drawing on a foresight-oriented framework grounded in expert evaluation, the study analyses transformative technologies across several key technological domains. To enhance analytical robustness, the results are first examined in an aggregated, cross-domain manner and subsequently interpreted in a concise, domain-specific form. The findings reveal limited overlap between short-term priorities and long-term strategic priorities, indicating that gaps between global and national levels of technological maturity necessitate simultaneous attention to institutional, infrastructural, and human capital dimensions. The study also identifies patterns of expert participation as a meaningful institutional signal and argues that the institutionalization of technology foresight requires the genuine integration of analytical tools into science and technology governance processes. Overall, the results suggest that when effectively embedded in policy decision-making, technology foresight can contribute to reducing policy errors, enhancing decision coherence, and enabling more strategic allocation of resources within the national science and technology system.

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Braun, D. (1998). The role of funding agencies in the cognitive development of science. Research Policy, 27(8), 807-821. https://doi.org/10.1016/S0048-7333(98)00092-4

Cooke, R. (1991). Experts in uncertainty: Opinion and subjective probability in science. Oxford: Oxford university press.

Cuhls, K. (2001). Foresight with Delphi surveys in Japan. Technology Analysis & Strategic Management, 13(4), 555-569. https://doi.org/10.1080/09537320127287

Cuhls, K. (2003). From forecasting to foresight processes- new participative foresight activities in Germany. Journal of Forecasting, 22(2‐3), 93-111. https://doi.org/10.1002/for.848

Dosi, G., & Nelson, R. R. (2010). Technical change and industrial dynamics as evolutionary processes. Handbook of the Economics of Innovation, 1, 51-127. https://doi.org/10.1016/S0169-7218(10)01003-8

Edquist, C. (2010). Systems of innovation perspectives and challenges. African Journal of Science, Technology, Innovation and Development, 2(3), 14-45. https://doi.org/10.1093/oxfordhb/9780199286805 .003.0007

Flanagan, K., Uyarra, E., & Laranja, M. (2011). Reconceptualising the ‘policy mix’for innovation. Research Policy, 40(5), 702-713. https://doi.org/10.1016/j.respol.2011.02.005

Geels, F. W. (2004). From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory. Research Policy, 33(6-7), 897-920. https://doi.org/10.1016/j.respol.2004.01.015

Georghiou, L., & Keenan, M. (2006). Evaluation of national foresight activities: Assessing rationale, process and impact. Technological Forecasting and Social Change, 73(7), 761-777. https://doi.org/10.1016/j.techfore.2005.08.003

Georghiou, L., & Keenan, M. (2008). 16. Evaluation and Impact of Foresight. In L. Georghiou (Ed.), The Handbook of technology foresight: Concepts and practice. Cheltenham: Edward Elgar Publishing.

Hafezi, R. (2021). Foresight, and science, technology and innovation policy. Rahyaft, 31(3), 123-128. (Persian) https://doi.org/10.22034/rahyaft.2022.13945

Hafezi, R., Malekifar, S., & Akhavan, A. (2018). Analyzing Iran’s science and technology foresight programs: Recommendations for further practices. foresight, 20(3), 312-331. https://doi.org/10.1108/FS-10-2017-0064

Hafezi, R., Wood, D. A., Alipour, M., & Taghikhah, F. R. (2023). Water-power scenarios to 2033: A mixed model. Environmental Science & Policy, 148, 103555. https://doi.org/10.1016/j.envsci.2023.103555

Kousari, S., & Sadat Rahmati, F. (2019). Future-Oriented Researches and Its Roles in STI Policy Making. Journal of Science and Technology Policy, 12(2), 103-118. (Persian)

Linstone, H. A., & Turoff, M. (1975). The Delphi method (Vol. 1975). Reading, MA: Addison-Wesley.

Lundvall, B. A. (1992). National systems of innovation: Towards a theory of innovation and interactive learning. London: Anthem Press.

Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2013). Disruptive technologies: Advances that will transform life, business, and the global economy. San Francisco: McKinsey Global Institute.

Mazzucato, M. (2018). Mission-oriented innovation policies: Challenges and opportunities. Industrial and Corporate Change, 27(5), 803-815. https://doi.org/10.1093/icc/dty034

Miles, I. (2010). The development of technology foresight: A review. Technological Forecasting and Social Change, 77(9), 1448-1456. https://doi.org/10.1016/j.techfore.2010.07.016

Nonaka, I. (2009). The knowledge-creating company. In T. Siesfeld, J. Cefola, D. Neef (Eds.), The economic impact of knowledge (pp. 175-187). Abingdon: Routledge.

Polanyi, M. (2009). The tacit dimension. In L. Prusak (Ed.), Knowledge in organisations (pp. 135-146). Abingdon: Routledge.

Popper, R. (2008a). Foresight methodology. In L. Georghiou, J. C. Harper, M. Keenan, I. Miles, R. Popper (Eds.), The handbook of technology foresight: Concepts and Practice (pp. 44-88). Cheltenham: Edward Elgar Publishing

Popper, R. (2008b). How are foresight methods selected? Foresight, 10(6), 62-89. https://doi.org/10.1108/14636680810918586

Roco, M. C., & Bainbridge, W. S. (2002). Converging technologies for improving human performance: Integrating from the nanoscale. Journal of Nanoparticle Research, 4(4), 281-295. https://doi.org/10.1023/A:1021152023349

Rowe, G., & Wright, G. (1999). The Delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 15(4), 353-375. https://doi.org/10.1016/S0169-2070(99)00018-7

Saltelli, A., Bammer, G., Bruno, I., Charters, E., Di Fiore, M., Didier, E., ... Mayo, D. (2020). Five ways to ensure that models serve society: A manifesto. Nature, 582(7813), 482-484. https://doi.org/10.1038/d41586-020-01812-9

Soete, L., & Freeman, C. (2012). The economics of industrial innovation. Abingdon: Routledge. https://doi.org/10.4324/9780203357637

Stirling, A. (2003). Risk, uncertainty and precaution: Some instrumental implications from the social sciences. In Negotiating environmental change. Edward Elgar Publishing. https://doi.org/10.4337/9781843765653.00008

Stirling, A. (2008). “Opening up” and “closing down” power, participation, and pluralism in the social appraisal of technology. Science, Technology, & Human Values, 33(2), 262-294. https://doi.org/10.1177/0162243907311265

Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185(4157), 1124-1131. https://doi.org/10.1126/science.185.4157.1124

Tversky, A., Kahneman, D., & Slovic, P. (1982). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.

Van Asselt, M. B. A., & Rotmans, J. (2002). Uncertainty in integrated assessment modelling. Climatic Change, 54(1), 75-105. https://doi.org/10.1023/A:1015783803445

Walker, W. E., Lempert, R. J., & Kwakkel, J. H. (2013). Deep uncertainty. In S. I Gass, M. C. Fu (Eds.), Encyclopedia of operations research and management science (pp. 395-402). Berlin: Springer.

 

References

Braun, D. (1998). The role of funding agencies in the cognitive development of science. Research Policy, 27(8), 807-821. https://doi.org/10.1016/S0048-7333(98)00092-4
Cooke, R. (1991). Experts in uncertainty: Opinion and subjective probability in science. Oxford: Oxford university press.
Cuhls, K. (2001). Foresight with Delphi surveys in Japan. Technology Analysis & Strategic Management, 13(4), 555-569. https://doi.org/10.1080/09537320127287
Cuhls, K. (2003). From forecasting to foresight processes- new participative foresight activities in Germany. Journal of Forecasting, 22(2‐3), 93-111. https://doi.org/10.1002/for.848
Dosi, G., & Nelson, R. R. (2010). Technical change and industrial dynamics as evolutionary processes. Handbook of the Economics of Innovation, 1, 51-127. https://doi.org/10.1016/S0169-7218(10)01003-8
Edquist, C. (2010). Systems of innovation perspectives and challenges. African Journal of Science, Technology, Innovation and Development, 2(3), 14-45. https://doi.org/10.1093/oxfordhb/9780199286805 .003.0007
Flanagan, K., Uyarra, E., & Laranja, M. (2011). Reconceptualising the ‘policy mix’for innovation. Research Policy, 40(5), 702-713. https://doi.org/10.1016/j.respol.2011.02.005
Geels, F. W. (2004). From sectoral systems of innovation to socio-technical systems: Insights about dynamics and change from sociology and institutional theory. Research Policy, 33(6-7), 897-920. https://doi.org/10.1016/j.respol.2004.01.015
Georghiou, L., & Keenan, M. (2006). Evaluation of national foresight activities: Assessing rationale, process and impact. Technological Forecasting and Social Change, 73(7), 761-777. https://doi.org/10.1016/j.techfore.2005.08.003
Georghiou, L., & Keenan, M. (2008). 16. Evaluation and Impact of Foresight. In L. Georghiou (Ed.), The Handbook of technology foresight: Concepts and practice. Cheltenham: Edward Elgar Publishing.
Hafezi, R. (2021). Foresight, and science, technology and innovation policy. Rahyaft, 31(3), 123-128. (Persian) https://doi.org/10.22034/rahyaft.2022.13945
Hafezi, R., Malekifar, S., & Akhavan, A. (2018). Analyzing Iran’s science and technology foresight programs: Recommendations for further practices. foresight, 20(3), 312-331. https://doi.org/10.1108/FS-10-2017-0064
Hafezi, R., Wood, D. A., Alipour, M., & Taghikhah, F. R. (2023). Water-power scenarios to 2033: A mixed model. Environmental Science & Policy, 148, 103555. https://doi.org/10.1016/j.envsci.2023.103555
Kousari, S., & Sadat Rahmati, F. (2019). Future-Oriented Researches and Its Roles in STI Policy Making. Journal of Science and Technology Policy, 12(2), 103-118. (Persian)
Linstone, H. A., & Turoff, M. (1975). The Delphi method (Vol. 1975). Reading, MA: Addison-Wesley.
Lundvall, B. A. (1992). National systems of innovation: Towards a theory of innovation and interactive learning. London: Anthem Press.
Manyika, J., Chui, M., Bughin, J., Dobbs, R., Bisson, P., & Marrs, A. (2013). Disruptive technologies: Advances that will transform life, business, and the global economy. San Francisco: McKinsey Global Institute.
Mazzucato, M. (2018). Mission-oriented innovation policies: Challenges and opportunities. Industrial and Corporate Change, 27(5), 803-815. https://doi.org/10.1093/icc/dty034
Miles, I. (2010). The development of technology foresight: A review. Technological Forecasting and Social Change, 77(9), 1448-1456. https://doi.org/10.1016/j.techfore.2010.07.016
Nonaka, I. (2009). The knowledge-creating company. In T. Siesfeld, J. Cefola, D. Neef (Eds.), The economic impact of knowledge (pp. 175-187). Abingdon: Routledge.
Polanyi, M. (2009). The tacit dimension. In L. Prusak (Ed.), Knowledge in organisations (pp. 135-146). Abingdon: Routledge.
Popper, R. (2008a). Foresight methodology. In L. Georghiou, J. C. Harper, M. Keenan, I. Miles, R. Popper (Eds.), The handbook of technology foresight: Concepts and Practice (pp. 44-88). Cheltenham: Edward Elgar Publishing
Popper, R. (2008b). How are foresight methods selected? Foresight, 10(6), 62-89. https://doi.org/10.1108/14636680810918586
Roco, M. C., & Bainbridge, W. S. (2002). Converging technologies for improving human performance: Integrating from the nanoscale. Journal of Nanoparticle Research, 4(4), 281-295. https://doi.org/10.1023/A:1021152023349
Rowe, G., & Wright, G. (1999). The Delphi technique as a forecasting tool: Issues and analysis. International Journal of Forecasting, 15(4), 353-375. https://doi.org/10.1016/S0169-2070(99)00018-7
Saltelli, A., Bammer, G., Bruno, I., Charters, E., Di Fiore, M., Didier, E., ... Mayo, D. (2020). Five ways to ensure that models serve society: A manifesto. Nature, 582(7813), 482-484. https://doi.org/10.1038/d41586-020-01812-9
Soete, L., & Freeman, C. (2012). The economics of industrial innovation. Abingdon: Routledge. https://doi.org/10.4324/9780203357637
Stirling, A. (2003). Risk, uncertainty and precaution: Some instrumental implications from the social sciences. In Negotiating environmental change. Edward Elgar Publishing. https://doi.org/10.4337/9781843765653.00008
Stirling, A. (2008). “Opening up” and “closing down” power, participation, and pluralism in the social appraisal of technology. Science, Technology, & Human Values, 33(2), 262-294. https://doi.org/10.1177/0162243907311265
Tversky, A., & Kahneman, D. (1974). Judgment under Uncertainty: Heuristics and Biases: Biases in judgments reveal some heuristics of thinking under uncertainty. Science, 185(4157), 1124-1131. https://doi.org/10.1126/science.185.4157.1124
Tversky, A., Kahneman, D., & Slovic, P. (1982). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
Van Asselt, M. B. A., & Rotmans, J. (2002). Uncertainty in integrated assessment modelling. Climatic Change, 54(1), 75-105. https://doi.org/10.1023/A:1015783803445
Walker, W. E., Lempert, R. J., & Kwakkel, J. H. (2013). Deep uncertainty. In S. I Gass, M. C. Fu (Eds.), Encyclopedia of operations research and management science (pp. 395-402). Berlin: Springer.
 

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