1. Abdelrazik M.K., Abdelaziz S.E., Hassan M.F., Hatem T.M. (2022) Climate action: Prospects of solar energy in Africa. Energy Reports, 8, 11363-11377. DOI: 10.1016/j.egyr.2022.08.252 EDN: HFYVME
2. Andersen P.D., Silvast A. (2023) Experts, stakeholders, technocracy, and technoeconomic input into energy scenarios. Futures, 154, 103271s. DOI: 10.1016/j.futures.2023.103271 EDN: RGXEEI
3. Blind K., Cuhls K., Grupp H. (2001) Personal attitudes in the assessment of the future of science and technology. A factor analysis approach. Technological Forecasting and Social Change, 68, 131-149. DOI: 10.1016/S0040-1625(00)00083-4
4. Bolger F., Wright G. (2017) Use of expert knowledge to anticipate the future: Issues, analysis and directions. International Journal of Forecasting, 33, 230-243. DOI: 10.1016/j.ijforecast.2016.11.001
5. Bradfield R.M. (2008) Cognitive barriers in the scenario development process. Advances in Developing Human Resources, 10(2), 198-215. DOI: 10.1177/1523422307313320
6. Buehler R., Griffin D., Ross M. (1994) Exploring the “planning fallacy”: Why people under-estimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366-381. https://psycnet.apa.org/doi/. DOI: 10.1037/0022-3514.67.3.366 EDN: HITRFN
7. Calof J., Smith J.E. (2012) Foresight impacts from around the world. Foresight, 14(1), 5-14. DOI: 10.1108/14636681211214879
8. Carlsson M., Dahl G.B., Öckert B., Rooth D.O. (2015) The Effect of Schooling on Cognitive Skills. The Review of Economics and Statistics, 97(3), 533-547. https://www.jstor.org/stable/43554993.
9. Chanchangi Y.N., Ghosh A., Sundaram S., Mallick T.K. (2020) Dust and PV performance in Nigeria: A review. Renewable and Sustainable Energy Reviews, 121, 109704. DOI: 10.1016/j.rser.2020.109704 EDN: KBPVUA
10. Chen Y., Zhao J., Lai Z., Wang Z., Xia H. (2019) Exploring the effects of economic growth, and renewable and non-renewable energy consumption on China’s CO2 emissions: Evidence from a regional panel analysis. Renewable Energy, 140, 341-353. DOI: 10.1016/j.renene.2019.03.058 EDN: KTVISK
11. Chermack T.J., Nimon K. (2008) The effects of scenario planning on participant decision-makingstyle. Human Resources Development Quarterly, 19(4), 351-372. DOI: 10.1002/hrdq.1245
12. Cuhls K. (2003) From forecasting to foresight processes - new participative foresight activities in Germany. Journal of Forecasting, 22(2-3), 93-111. DOI: 10.1002/for.848 EDN: DVROWF
13. Dagnachew A.G., Hof A.F., Roelfsema M.R., van Vuuren D.P. (2020) Actors and governance in the transition toward universal electricity access in Sub-Saharan Africa. Energy Policy, 143, 111572. DOI: 10.1016/j.enpol.2020.111572 EDN: CQMTXK
14. Del Granado P.C., Renger H., van Nieuwkoop, Kardakos E.G., Schaffner C. (2018) Modelling the energy transition: A nexus of energy system and economic models. Energy Strategy Reviews, 20, 229-235. DOI: 10.1016/j.esr.2018.03.004
15. Ebersbach M., van Dooren W., van den Noorgate W., Resing W.C.M. (2008) Understanding linear and exponential growth: Searching for the roots in 6-to-9 year olds. Cognitive Development, 23, 237-257. DOI: 10.1016/j.cogdev.2008.01.001
16. European Commission (2016) EU reference scenario 2016 - Energy, transport and GHG emissions trends to 2050, Brussels: European Commission.
17. Feld J., Sauermann J., de Grip A. (2017) Estimating the relationship between skill and overconfidence. Journal of Behavioral and Experimental Economics, 68, 18-24. DOI: 10.1016/j.socec.2017.03.002
18. Fleisher C.S., Bensoussan B. (2000) A FAROUT way to manage CI Analysis. Competitive Intelligence Magazine, 3(1), 1-8.
19. Fraunhofer ISI (2014) Optimized pathways towards ambitious climate protection in the European electricity system (EU Long-term scenarios 2050 II), Karlsruhe: Fraunhofer Institute for Systems and Innovation Research.
20. Galvin R., Healy N. (2020) The green new deal in the United States: What it is and how to pay for it. Energy Research & Social Science, 67, 101529. DOI: 10.1016/j.erss.2020.101529 EDN: NPQRIG
21. Georghiou L., Cassingena Harper J., Keenan M., Miles I., Popper R. (eds.) (2008) The Handbook of Technology Foresight. Concepts and Practice, Cheltenham: Edward Elgar.
22. Georghiou L., Keenan V. (2006) Evaluation of national foresight activities: Assessing rationale, process and impact. Technological Forecasting and Social Change, 73(7), 761-777. DOI: 10.1016/j.techfore.2005.08.003
23. Giaoutzi M., Sapio B. (2012) Recent Developments in Foresight Methodologies, Heidelberg, Dordrecht, London, New York: Springer.
24. Göke L., Weibezahn J., von Hirschhausen C. (2023) A collective blueprint, not a crystal ball: How expectations and participation shape long-term energy scenarios. Energy Research & Social Science, 97, 102957. DOI: 10.1016/j.erss.2023.102957 EDN: YSUYIT
25. Golden J., Milewicz J., Herbig P. (1994) Forecasting: Trials and tribulations. Management Decision, 32(1), 33-36. DOI: 10.1108/00251749410050642 EDN: EAYHAR
26. Guivarch C., Lempert R., Trutnevyte E. (2017) Scenario techniques for energy and environmental research: An overview of recent developments to broaden the capacity to deal with complexity and uncertainty. Environmental Modelling and Software, 97, 201-210. DOI: 10.1016/j.envsoft.2017.07.017
27. Hainsch K., Loffler K., Burandt T., Auer H., del Granado P.C., Pisciella P., Zwickl-Bernhard S. (2022) Energy transition scenarios: What policies, societal attitudes, and technology developments will realize the EU Green Deal?, Energy, 239, 122067. DOI: 10.1016/j.energy.2021.122067 EDN: NNKUPY
28. Hawila D., Mondal A.H., Kennedy S., Mezher T. (2014) Renewable energy readiness assessment for North African countries. Renewable and Sustainable Energy Reviews, 33, 128-140. DOI: 10.1016/j.rser.2014.01.066
29. Hogarth R.M. (1980) Judgment and Choice. The Psychology of Decision, NewYork: Wiley.
30. Hogarth R.M., Makridakis S. (1981) Forecasting and planning: An evaluation. Management Science, 27(2), 115-138. DOI: 10.1287/mnsc.27.2.115
31. Huard A., Fremaux B. (2020) Bright Perspectives for Solar Power in Africa?, Paris: Institut Montaigne.
32. IEA (2022) World Energy Outlook 2022, Paris: IEA.
33. IPCC (2014) Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge (UK), New York: Cambridge University Press.
34. IRENA (2018) Renewable Energy Outlook: Egypt, Abu Dhabi: International Renewable Energy Agency.
35. IRENA (2021) Renewable Capacity Statistics 2021, Abu Dhabi: International Renewable Energy Agency.
36. Kahneman D., Slovic P., Tversky A. (1982) Judgment under Uncertainty: Heuristics and Biases, Cambridge: Cambridge University Press.
37. Kahneman D., Tversky A. (1979) Intuitive prediction: Biases and corrective procedures. TIMS Studies in Management Science, 12, 313-327.
38. Kimuli D., Nabaterega R., Banadda N., Kabenge I., Ekwamu A., Nampala P. (2017) Advanced education and training programs to support renewable energy investment in Africa. International Journal of Education and Practice, 5, 8-15. DOI: 10.18488/journal.61/2017.5.1/61.1.8.15
39. Knosala K., Kotzur L., Röben F.T., Stenzel P., Blum L., Robinius M., Stolten D. (2021) Hybrid hydrogen home storage for decentralized energy autonomy. International Journal of Hydrogen Energy, 46(42), 21748-21763,. DOI: 10.1016/j.ijhydene.2021.04.036 EDN: KYPRSM
40. Ko B.K., Yang J.-S. (2024) Developments and challenges of foresight evaluation: Review of the past 30 years of research. Futures, 155, 103291. DOI: 10.1016/j.futures.2023.103291 EDN: WBUJZD
41. Levy M.R., Tasoff J. (2016) Exponential-growth bias and lifecycle consumption. Journal of the European Economic Association, 14(3), 545-583. https://www.jstor.org/stable/43965317.
42. Levy M.R., Tasoff J. (2017) Exponential-growth bias and overconfidence. Journal of Economic Psychology, 58, 1-14. DOI: 10.1016/j.joep.2016.11.001
43. Lichtenstein S., Fischhoff B. (1977) Do those who know more also know more about how much they know? The calibration of probability judgments. Organizational Behavior and Human Performance, 20, 159-183. DOI: 10.1016/0030-5073(77)90001-0
44. Linstone H.A., Turoff M. (1976) The Delphi Method: Techniques and Applications. Journal of Marketing Research, 13(3), 317-318. DOI: 10.2307/3150755
45. Luo H., Lin X. (2023) Empirical Study on the Low-Carbon Economic Efficiency in Zhejiang Province Based on an Improved DEA Model and Projection. Energies, 16, 300. DOI: 10.3390/en16010300 EDN: KCOBSC
46. Markmann C., Spickermann A., von der Gracht H.A., Brem A. (2021) Improving the question formulation in Delphi-like surveys: Analysis of the effects of abstract language and amount of information on response behavior. Futures & Foresight Science, 3(1), 1-20. DOI: 10.1002/ffo2.56 EDN: NOIBFQ
47. Martino J.P. (2003) A review of selected recent advances in technological forecasting. Technological Forecasting and Social Change, 70, 719-733. DOI: 10.1016/S0040-1625(02)00375-X
48. Meissner Ph., Wulf T. (2013) Cognitive benefits of scenario planning: Its impact on biases and decision quality. Technological Forecasting and Social Change, 80, 801-814. DOI: 10.1016/j.techfore.2012.09.011
49. Minkkinen M., Auffermann B., Ahokas I. (2019) Six foresight frames: Classifying policy foresight processes in foresight systems according to perceived unpredictability and pursued change. Technological Forecasting and Social Change, 149, 119753. DOI: 10.1016/j.techfore.2019.119753 EDN: FKIHQG
50. Moore D.A., Carter A.B., Yang H.H.J. (2015) Wide off the mark. Evidence on the underlying causes of overprecision in judgment. Organizational Behavior and Human Decision Processes, 131, 110-120. DOI: 10.1016/j.obhdp.2015.09.003
51. Nemet G.F. (2021) Improving the crystal ball. Nature Energy, 6, 860-861. DOI: 10.1038/s41560-021-00903-9 EDN: RIITWR
52. Newby-Clark I.R., Ross M., Buehler R., Griffin D.W. (2000) People focus on optimistic scenarios and disregard pessimistic scenario when predicting task completion times. Journal of Experimental Psychology Applications, 6(3), 171-182. DOI: 10.1037/1076-898x.6.3.171
53. Nwanekezie K., Noble B., Poelzer G. (2022) Strategic assessment for energy transitions: A case study of renewable energy development in Saskatchewan, Canada. Environmental Impact Assessment Review, 92, 106688. DOI: 10.1016/j.eiar.2021.106688 EDN: TJFIWS
54. Othman R., Hatem T.M. (2022) Assessment of PV technologies outdoor performance and commercial software estimation in hot and dry climates. Journal of Cleaner Production, 340, 130819. DOI: 10.1016/j.jclepro.2022.130819 EDN: TWZQXU
55. Paltsev S. (2017) Energy scenarios: The value and limits of scenario analysis. WIREs: Energy and Environment, 6(4), e242. DOI: 10.1002/wene.242
56. Rezk M.R., Radwan A., Salem N., Sakr M.M., Tvaronavičienė M. (2019) Foresight for sustainable energy policy in Egypt: Results from a Delphi survey. Insights into Regional Development, 1(4), 357-369. DOI: 10.9770/ird.2019.1.4(6)
57. Riedy C. (2009) The influence of futures work on public policy and sustainability. Foresight, 11, 40-56. DOI: 10.1108/14636680910994950
58. Rubio A., Agila W., González L., Ramirez M., Pineda H. (2023) A Critical Analysis of the Impact of the Pandemic on Sustainable Energy Scenarios. Paper presented at the 11th International Conference on Smart Grid (icSmartGrid), Paris, France, 2023. DOI: 10.1109/icSmartGrid58556.2023.10171066
59. Sareen S., Haarstad H. (2018) Bridging socio-technical and justice aspects of sustainable energy transitions. Applied Energy, 228, 624-632. DOI: 10.1016/j.apenergy.2018.06.104 EDN: YIAPRJ
60. Schoemaker P.J.H. (1993) Multiple scenario development: Its conceptual and behavioral foundations. Strategic Management Journal, 14, 193-213. https://www.jstor.org/stable/2486922.
61. Sharot T., Guitart-Masip M., Korn C.W., Chowdhury R., Dolan R.J. (2012) How Dopamine Enhances an Optimism Bias in Humans. Current Biology, 22(16), 1477-1481. DOI: 10.1016/j.cub.2012.05.053
62. Stern D.I. (2017) How accurate are energy intensity projections? Climatic Change, 143(3), 537-545. DOI: 10.1007/s10584-017-2003-3 EDN: FKFEAC
63. Tichy G. (2004) The over-optimism among experts in assessment and foresight. Technological Forecasting and Social Change, 71(4), 341-363. DOI: 10.1016/j.techfore.2004.01.003
64. Trutnevyte E. (2016) Does cost optimization approximate the real-world energy transition? Energy, 106, 182-193. DOI: 10.1016/j.energy.2016.03.038
65. UNIDO (2004) Foresight Methodologies Textbook, Wien: UNIDO.
66. Van der Steen M., van der Duin P. (2012) Learning ahead of time: How evaluation of foresight may add to increased trust, organizational learning and future oriented policy and strategy.Futures, 44 (5), 487-493. DOI: 10.1016/j.futures.2012.03.010
67. Van der Steen M.A., van Twist M.J.W. (2013) Foresight and long-term policy-making: An analysis of anticipatory boundary work in policy organizations in the Netherlands. Futures, 54, 33-42. DOI: 10.1016/j.futures.2013.09.009
68. Van Dorsser C., Taneja P., Walker W., Marchau V. (2020) An integrated framework for anticipating the future and dealing with uncertainty in policymaking. Futures, 124, 102594. DOI: 10.1016/j.futures.2020.102594 EDN: QOHKXR
69. Vervoort J., Gupta A. (2018) Anticipating climate futures in a 1.5◦C era: The link between foresight and governance. Current Opinion in Environmental Sustainability, 31, 104-111. DOI: 10.1016/j.cosust.2018.01.004
70. Videira N., Antunes P., Santos R. (2009) Scoping river basin management issues with participatory modelling: The Baixo Guadiana experience. Ecological Economics, 68, 965-978. DOI: 10.1016/j.ecolecon.2008.11.008
71. Winkler J., Moser R. (2016) Biases in future-oriented Delphi studies: A cognitive perspective. Technological Forecasting and Social Change, 105(C), 63-76. DOI: 10.1016/j.techfore.2016.01.021
72. Wright G., Goodwin P. (2009) Decision making and planning under low levels of predictability. Enhancing the scenario method. International Journal of Forecasting, 25(4), 813-825. DOI: 10.1016/j.ijforecast.2009.05.019
