Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-27T04:13:19.107Z Has data issue: false hasContentIssue false
  • English
  • Français

Development of a Methodology for Technology Demonstration Projects Evaluation

Published online by Cambridge University Press:  26 May 2022

A. Stelvaga  and
C. Fortin
A. Stelvaga*
Affiliation:
Skolkovo Institute of Science and Technology, Russia
C. Fortin
Affiliation:
Skolkovo Institute of Science and Technology, Russia
*
[email protected]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

To ensure optimal resource allocation in technology demonstration projects, the evaluation of demonstrators of various maturity, scale, and nature has to be carried out. Most of the existing approaches focus on risk assessment or projected financial return; the need for a tool supporting multi-facet projects evaluation has been identified. This paper presents R2L framework based on three major criteria, defined in detail: Leap Potential, Learning, and Risk. The framework was applied to a real flight-test demonstrator project during workshops in a major aerospace company.

Keywords

technology developmentdecision makingevaluationrisk management
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 273 - 282
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

References

Bai, L., et al. . (2021). A method of network robustness under strategic goals for project portfolio selection. Computers & Industrial Engineering. 161. 10.1016/j.cie.2021.107658.CrossRefGoogle Scholar
BenMahmoud-Jouini, Sihem & Midler, Christophe. (2020). Unpacking the notion of prototype archetypes in the early phase of an innovation process. Creativity and Innovation Management. 29. 10.1111/caim.12358.Google Scholar
Blessing, Lucienne & Chakrabarti, Amaresh. (2009). DRM, a Design Research Methodology. 10.1007/978-1-84882-587-1.CrossRefGoogle Scholar
Bragge, Johanna & Korhonen, Pekka & Wallenius, Hannele & Wallenius, Jyrki. (2010). Bibliometric Analysis of Multiple Criteria Decision Making/Multiattribute Utility Theory. 10.1007/978-3-642-04045-0_22.CrossRefGoogle Scholar
Cash, P., Hicks, B. and Culley, S. (2015), “Activity Theory as a means for multi-scale analysis of the engineering design process: A protocol study of design in practice”, Design Studies, Vol. 38, pp. 1–32. 10.1016/j.destud.2015.02.001CrossRefGoogle Scholar
Cooper, R.G. (2001) Winning at New Products: Accelerating the Process from Idea to Launch (3rd edn.). Cambridge, MA: Perseus Books.Google Scholar
Crawford, C.M. and Benedetto, C.A. (2006) New Products Management (8th edn.). New York: McGraw-Hill/Irwin.Google Scholar
Fevolden, Arne & Coenen, Lars & Hansen, Teis & Klitkou, Antje. (2017). The Role of Trials and Demonstration Projects in the Development of a Sustainable Bioeconomy. Sustainability. 9. 10.3390/su9030419.CrossRefGoogle Scholar
Forman, E. H., & Gass, S. I. (2001). The Analytic Hierarchy Process: An Exposition. Operations Research, 49(4), 469–486. http://www.jstor.org/stable/3088581Google Scholar
Garg, T., Eppinger, S.D., Joglekar, N.R., & Olechowski, A. (2017). Using TRLs and system architecture to estimate technology integration risk.Google Scholar
Mankins, J. (2009). Technology Readiness and Risk Assessments: A New Approach. Acta Astronautica. 65. 1208–1215. 10.1016/j.actaastro.2009.03.059.CrossRefGoogle Scholar
Mican Rincon, Camilo & Fernandes, Gabriela & Araújo, Madalena. (2021). A method for project portfolio risk assessment considering risk interdependencies -a network perspective. Procedia Computer Science.Google Scholar
Mohagheghi, V. & Mousavi, Sana & Vahdani, Behnam & Shahriari, Mohammad Reza. (2017). R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach. Neural Computing and Applications. 28. 10.1007/s00521-016-2262-3.CrossRefGoogle Scholar
Mokhtarzadeh, Nima & Amoozad Mahdiraji, Hannan & Beheshti, Moein & Zavadskas, Edmundas. (2018). A Novel Hybrid Approach for Technology Selection in the Information Technology Industry. Technologies. 6. 34. 10.3390/technologies6010034.CrossRefGoogle Scholar
Moenaert, R.K., Robben, H., Antioco, M., Schamphelaere, V.D. and Roks, E. (2010) Strategic innovation decisions: what you foresee is not what you get. Journal of Product Innovation Management, 27, 1, 840–855Google Scholar
Moultrie, J. (2015), Understanding and classifying the role of design demonstrators in scientific exploration, Technovation, Volumes 43–44, Pages 1-16, ISSN 0166-4972, 10.1016/j.technovation.2015.05.002Google Scholar
Mousavi, Seyedeh & Seiti, Hamidreza & Hafezalkotob, Ashkan & Asian, Sobhan & Mobarra, Rouhollah. (2021). Application of risk-based fuzzy decision support systems in new product development: An R-VIKOR approach. Applied Soft Computing. 109. 10.1016/j.asoc.2021.107456.Google Scholar
Myers, S. (1978), The Demonstration Project as a Procedure for Accelerating the Application of New Technology; Institute of Public Administration: Washington, DC, USAGoogle Scholar
National Research Council. 2012. Recapturing NASA's Aeronautics Flight Research Capabilities. Washington, DC: The National Academies Press. 10.17226/13384.Google Scholar
Noh, , Heeyong & Kim, Kyuwoong & Song, Youngkeun & Lee, Sungjoo. (2020). Opportunity-driven technology roadmapping: The case of 5G mobile services. Technological Forecasting and Social Change. 163. 10.1016/j.techfore.2020.120452.Google Scholar
Oliveira, Maicon & Rozenfeld, Henrique & Phaal, Robert & Probert, David. (2014). Decision making at the front end of innovation: The hidden influence of knowledge and decision criteria. R&D Management. 45. 10.1111/radm.12058.Google Scholar
Ordoobadi, S.M. (2008), “Fuzzy logic and evaluation of advanced technologies”, Industrial Management & Data Systems, Vol. 108 No. 7, pp. 928–946. 10.1108/02635570810898008CrossRefGoogle Scholar
Phaal, R. & O'Sullivan, Eoin & Routley, Michele & Ford, Simon & Probert, D. (2011). A framework for mapping industrial emergence. Technol Forecast Soc Chang. Technological Forecasting and Social Change - TECHNOL FORECAST SOC CHANGE. 78. 217–230. 10.1016/j.techfore.2010.06.018.CrossRefGoogle Scholar
Ravari, Sara & Mehrabanfar, Ehsan & Banaitis, Audrius & Banaitiene, Nerija. (2016). Framework for assessing technological innovation capability in research and technology organizations. Journal of Business Economics and Management. 17. 825–847. 10.3846/16111699.2016.1253607.CrossRefGoogle Scholar
Phaal, Robert, Farrukh, Clare J.P., Probert, David R., Technology roadmapping—A planning framework for evolution and revolution, Technological Forecasting and Social Change, Volume 71, Issues 1–2, 2004, Pages 5–26, ISSN 0040-1625, 10.1016/S0040-1625(03)00072-6.Google Scholar
Quiñones, Renissa & Caladcad, June & Himang, Celbert & Quiñones, Hubert & Castro, Charena & Caballes, Shirley & Abellana, Dharyll Prince & Jabilles, Eula & Ocampo, Lanndon. (2020). Using Delphi and fuzzy DEMATEL for analyzing the intertwined relationships of the barriers of university technology transfer: Evidence from a developing economy. International Journal of Innovation Studies. 4. 85–104.CrossRefGoogle Scholar
Sammut-Bonnici, Tanya & Galea, David. (2015). SWOT Analysis. 10.1002/9781118785317.weom120103.CrossRefGoogle Scholar
Shishko, Robert & Ebbeler, Donald & Fox, George. (2002). 4.3.4 NASA Technology Assessment Using Real-Options Valuation. Systems Engineering. 7. 1–13. 10.1002/sys.10052.Google Scholar
Skinner, Dick & Nelson, R. & Chin, Wynne & Land, Lesley. (2015). The Delphi Method Research Strategy in Studies of Information Systems. Communications of the Association for Information Systems. 37. 31–63.CrossRefGoogle Scholar
Walden, D., Roedler, G., Forsberg, K., Hamelin, D., Shortell, T. (2015), INCOSE Systems Engineering Handbook, 4th edition, Systems Engineering Handbook A Guide for System Life Cycle Processes and Activities, 4th edition, ISBN: 9781118999400Google Scholar