Abstract
Group decisions are hard if they are non-routine and we lack intuition about good, let alone optimal, solutions. This feature usually reflects unfamiliar elements, or value judgments about which actors disagree, or core uncertainties and complexities, which may be addressed by advanced computing methods, but only at unreasonable costs in time or resources. The decision to close a production plant, or not, is particularly worrisome for senior managers. Decisions will be widely scrutinized and criticized by trade unions, politicians, and the press, and shareholders may react negatively if they fear that share value will decrease (cf. See the chapter by, Ackermann and Eden, this volume). A real options model can support decision making in these circumstances but, if key data is imprecise, meaningful support requires a fuzzy real options model. As illustrated using a real case from the forest products industry, this support can assist management in its search for the best decision and the best timing (cf. See the chapter by Kersten, this volume) and the use of mathematical models to support negotiation processes).
Parts of this paper were earlier published asA Fuzzy Real Options Model for (Not) Closing a Production Plant: An Application to Forest Industry in Finland (Markku Heikkilä – Christer Carlsson) In Proceedings of the 12th Annual International Conference on Real Options, Rio de Janeiro, 2008
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Carlsson, C. (2010). Soft Computing for Groups Making Hard Decisions. In: Kilgour, D., Eden, C. (eds) Handbook of Group Decision and Negotiation. Advances in Group Decision and Negotiation, vol 4. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9097-3_4
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DOI: https://doi.org/10.1007/978-90-481-9097-3_4
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