Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-25T11:11:55.390Z Has data issue: false hasContentIssue false
  • English
  • Français

IMPROVING SCENARIO-TECHNIQUE BY A SEMI-AUTOMATIZED CONSISTENCY ASSESSMENT BASED ON PATTERN RECOGNITION BY ARTIFICIAL NEURAL NETWORKS

Part of: Design Support Tools

Published online by Cambridge University Press:  11 June 2020

I. Gräßler ,
P. Scholle  and
H. Thiele
I. Gräßler
Affiliation:
Paderborn University, Germany
P. Scholle*
Affiliation:
Paderborn University, Germany
H. Thiele
Affiliation:
Paderborn University, Germany
*
*[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 enhance the success of innovations, various methods for foresight have been developed. Automatization yields the potential of shifting effort away from the process to the actual in-depth analysis of resulting scenarios in scenario-technique. Within this paper, an approach based on a user-specific classification of input factors (consistency values) is presented. Generic consistency patterns used for a semi-automatized consistency assessment based on artificial neural networks are identified using a case study approach. Hereby, the effort for scenario-technique can be reduced significantly.

Keywords

design automationdesign support systemartificial intelligence (AI)scenario technique
Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 147 - 156
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), 2020. Published by Cambridge University Press

References

Bradfield, R. et al. (2005), “The origins and evolution of scenario techniques in long range business planning”, Futures, Vol. 37 No. 8, pp. 795–812.10.1016/j.futures.2005.01.003CrossRefGoogle Scholar
Clausewitz, C.V. (1832), Vom Kriege, Berlin.Google Scholar
Dönitz, E.J. (2009), Effizientere Szenariotechnik durch teilautomatische Generierung von Konsistenzmatrizen: Empirie, Konzeption, Fuzzy- und Neuro-Fuzzy-Ansätze, Gabler Verlag, Wiesbaden.10.1007/978-3-8349-8218-6CrossRefGoogle Scholar
Gausemeier, J., Fink, A. and Schlake, O. (1998), “Scenario Management”, Technological Forecasting and Social Change, Vol. 59 No. 2, pp. 111–130.10.1016/S0040-1625(97)00166-2CrossRefGoogle Scholar
Gordon, T.J. and Hayward, H. (1968), “Initial experiments with the cross impact matrix method of forecasting”, Futures, Vol. 1 No. 2, pp. 100–116.10.1016/S0016-3287(68)80003-5CrossRefGoogle Scholar
Götze, U. (1993), Szenario-Technik in der strategischen Unternehmensplanung, DUV. Wirtschaftswissenschaft, 2nd ed., Dt. Univ.-Verl. [u.a.], Wiesbaden.10.1007/978-3-322-96174-7CrossRefGoogle Scholar
Gräßler, I., Pottebaum, J. and Scholle, P. (2017a), “Integrated Process and Data Model for Agile Strategic Planning”, paper presented at IDE Workshop, 05.04. - 07.04., Magdeburg.Google Scholar
Gräßler, I., Pottebaum, J. and Scholle, P. (2018), “Influence Factors for Innovation in Digital Self-Preparedness Services and Tools”, International Journal of Information Systems for Crisis Response and Management, Vol. 10 No. 1, pp. 20–37.10.4018/IJISCRAM.2018010102CrossRefGoogle Scholar
Gräßler, I., Scholle, P. and Pottebaum, J. (2017b), “Integrated process and data model for applying scenario-technique in requirements engineering”, In: Design Society (Ed.), ICED17: 21st International Conference on Engineering Design Vancouver, 21.-25.08.2017, Design Society, pp. 261–270.Google Scholar
Gräßler, I., Thiele, H. and Scholle, P. (2019), “Methode zur Einflussanalyse in der SzenarioTechnik auf Basis gerichteter Graphen”, in DFX 2019: Proceedings of the 30th Symposium Design for X, 18-19 September 2019, Jesteburg, Germany, 18th-19th September 2019, The Design Society.10.35199/dfx2019.12CrossRefGoogle Scholar
Grienitz, V., Hausicke, M. and Schmidt, A.-M. (2014), “Scenario development without probabilities—focusing on the most important scenario”, European Journal of Futures Research, Vol. 2 No. 1.10.1007/s40309-013-0027-0CrossRefGoogle Scholar
Kosow, H. (2015), “New outlooks in traceability and consistency of integrated scenarios”, European Journal of Futures Research, Vol. 3 No. 1, p. 16.10.1007/s40309-015-0077-6CrossRefGoogle Scholar
Meadows, D.H. (1974), The limits to growth: A report for the Club of Rome's Project on the Predicament of Mankind, 2nd ed., Universe Books, New York.Google Scholar
Mietzner, D. and Reger, G. (2005), “Advantages and Disadvantages of Scenario Approaches for Strategic Foresight”, International Journal Technology and Intelligence Planing, Vol. 1 No. 2, pp. 220–239.10.1504/IJTIP.2005.006516CrossRefGoogle Scholar
Millett, S.M. (2003), “The future of scenarios. Challenges and opportunities”, Strategy & Leadership, Vol. 31 No. 2, pp. 16–24.10.1108/10878570310698089CrossRefGoogle Scholar
Mißler-Behr, M. (1993), Methoden der Szenarioanalyse, DUV Wirtschaftswissenschaft, Dt. Univ.-Verl., Wiesbaden.10.1007/978-3-663-14585-1CrossRefGoogle Scholar
Pottebaum, J. and Grässler, I. (2016), “Reliable Input for Strategic Planning: The Integrated Scenario Data Model”, In: Villmer, F.-J. and Padoanao, E. (Eds.), 6th International Conference Production Engineering and Management, pp. 99–110.Google Scholar
Reibnitz, U.V. (1992), Szenario-Technik: Instrumente für die unternehmerische und persönliche Erfolgsplanung, 2nd ed., Gabler, Wiesbaden.10.1007/978-3-663-15720-5CrossRefGoogle Scholar
Tapinos, E. (2013), “Scenario planning at business unit level”, Futures, Vol. 47, pp. 17–27.10.1016/j.futures.2012.11.009CrossRefGoogle Scholar
Tversky, A. and Kahneman, D. (1973), “Availability. A heuristic for judging frequency and probability”, Cognitive Psychology, Vol. 5 No. 2, pp. 207–232.10.1016/0010-0285(73)90033-9CrossRefGoogle Scholar
Wack, P. (1985), “Scenarios: Shooting the Rapids”, Harvard Buisness Review, Vol. 63 No. 6, pp. 139–150.Google Scholar
Yin, R.K. (2018), Case study research and applications: Design and methods, Sixth edition, SAGE, Los Angeles, London, New Dehli, Singapore, Washington DC, Melbourne.Google Scholar