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A Status Quo Biased Multistage Decision Model for Regional Agricultural Socioeconomic Planning Under Fuzzy Information

  • Janusz KacprzykEmail author
  • Yuriy P. Kondratenko
  • Jos’e M. Merigó
  • Jorge Hernandez Hormazabal
  • Gia Sirbiladze
  • Ana Maria Gil-Lafuente
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 203)

Abstract

We proposed a novel fuzzy multistage control model of sustainable regional agricultural development which better reflects specific features of human stakeholders. First, we use fuzzy logic for the modeling of imprecision in human judgments, intentions, preferences, evaluations, etc. Second, we propose to reflect in the model the so called status quo bias of the humans which basically stands for a common propensity of the humans to stay with known and already employed procedures and courses of action, avoiding larger changes. We develop therefore a human centric model. We also indicate that the inclusion of the status quo bias can be viewed as a way to mitigate risk which is crucial, notably in the case of agriculture. We present some simple example of how a best (optimal) investment policy can be obtained under different development scenarios, and indicate what change the inclusion of the status quo bias brings.

Notes

Acknowledgements

The contribution of the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems (www.rucaps.eu), funded by the European Union under their funding scheme H2020-MSCARISE-2015 is acknowledged by Janusz Kacprzyk and Jorge Hernandez Hormazabal.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Janusz Kacprzyk
    • 1
    • 2
    Email author
  • Yuriy P. Kondratenko
    • 3
  • Jos’e M. Merigó
    • 4
  • Jorge Hernandez Hormazabal
    • 5
  • Gia Sirbiladze
    • 6
  • Ana Maria Gil-Lafuente
    • 7
  1. 1.Systems Research Institute, Polish Academy of SciencesWarsawPoland
  2. 2.WIT – Warsaw School of Information TechnologyWarsawPoland
  3. 3.Department of Intelligent Information SystemsPetro Mohyla Black Sea National UniversityMykolaivUkraine
  4. 4.Department of Management Control and Information SystemsUniversity of ChileSantiagoChile
  5. 5.Management School, University of LiverpoolLiverpoolUK
  6. 6.Department of Computer SciencesIvane Javakhishvili Tbilisi State UniversityTbilisiGeorgia
  7. 7.Department of Business AdministrationUniversity of BarcelonaBarcelonaSpain

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