Abstract
The need and interest to consider cognitive and motivational biases has been recognized in many different disciplines (e.g. economics, operational research, decision theory, finance) and has recently reached environmental decision-making. Within this domain, the intrinsic presence of a spatial dimension of both alternatives and criteria calls for the use of geographical maps throughout the decision-making process to properly represent the spatial distribution of the features under analysis. This makes Spatial Multi Criteria Decision Aiding (SMCDA) a particularly interesting domain to explore new implications of cognitive and motivational biases. The present chapter presents and discusses the results of a literature review of recent applications of Spatial Multi Criteria Decision Aiding across different domains. The objective of the study is to enlighten possible biases in both the design of spatial MCDA models and in the interpretation of their results. The proposed review and classification of the relevant literature is expected to have important implications for spatial decision-making procedures, by generating better awareness on (i) the meta-choices available to model builders when designing Spatial Multi Criteria Decision Aiding processes and (ii) the consequences of these meta-choices on human judgment for both the facilitators of the modeling processes and the users of the models.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Akin, M. K., Topal, T., & Kramer, S. L. (2013). A newly developed seismic microzonation model of Erbaa (Tokat, Turkey) located on seismically active eastern segment of the North Anatolian Fault Zone (NAFZ). Natural Hazards, 65(3), 1411–1442.
Bagdanavičiute, I., & Valiunas, J. (2013). GIS-based land suitability analysis integrating multi-criteria evaluation for the allocation of potential pollution sources. Environmental Earth Sciences, 68(6), 1797–1812.
Bagheri, M., Sulaiman, W. N. A., & Vaghefi, N. (2013). Application of geographic information system technique and analytical hierarchy process model for land-use suitability analysis on coastal area. Journal of Coastal Conservation, 17(1), 1–10.
Cova, T. J., & Church, R. (2000). Exploratory spatial optimization in site search: A neighborhood operator approach. Computers, Environment and Urban Systems, 24(5), 401–419.
Dragićević, S., Lai, T., & Balram, S. (2014). GIS-based multicriteria evaluation with multiscale analysis to characterize urban landslide susceptibility in data-scarce environments. Habitat International, 45, 114–125.
Esquivel, J. M., Morales, G. P., & Esteller, M. V. (2015). Groundwater monitoring network design using GIS and multicriteria analysis. Water Resources Management, 29(9), 3175–3194.
Ferretti, V. (2013). Spatial multicriteria evaluation to support planning and evaluation procedures: A survey and classification of the literature. Geoingegneria Ambientale e Mineraria, 139(2), 53–66.
Ferretti, V., & Gandino, E. (2018). Co-designing the solution space for rural regeneration in a new World Heritage site: A choice experiments approach. European Journal of Operational Research, 268(3), 1077–1091.
Ferretti, V., & Montibeller, G. (2016). Key challenges and meta-choices in designing and applying multi-criteria spatial decision support systems. Decision Support Systems, 84, 41–52.
Gdoura, K., Anane, M., & Jellali, S. (2015). Geospatial and AHP-multicriteria analyses to locate and rank suitable sites for groundwater recharge with reclaimed water. Resources, Conservation and Recycling, 104, 19–30.
Hämäläinen, R. P. (2015). Behavioural issues in environmental modelling—The missing perspective. Environmental Modelling and Software, 73, 244–253.
Hämäläinen, R. P., & Alaja, S. (2008). The threat of weighting biases in environmental decision analysis. Ecological Economics, 68(1), 556–569.
Hamzeh, M., Abbaspour, A. R., & Davalou, R. (2015). Raster-based outranking method: A new approach for municipal solid waste landfill (MSW) siting. Environmental Science and Pollution Research, 22(16), 12511–12524.
Huang, I. V., Keisler, J., & Linkov, I. (2011). Multi-criteria decision analysis in environmental sciences: Ten years of applications and trends. Science of the Total Environment, 409, 3578–3594.
Jacobi, S. K., & Hobbs, B. F. (2007). Quantifying and mitigating the splitting bias and other value tree-induced weighting biases. Decision Analysis, 4(4), 194–210.
Jiang, B. (2013). Head/tail breaks: A new classification scheme for data with a heavy-tailed distribution. The Professional Geographer, 65(3), 482–494.
Jung, J., Kim, C., Jayakumar, S., Kim, S., Han, S., Kim, D. H., et al. (2013). Forest fire risk mapping of Kolli Hills, India, considering subjectivity and inconsistency issues. Natural Hazards, 65(3), 2129–2146.
Keeney, R. L., & Gregory, R. S. (2005). Selecting attributes to measure the achievement of objectives. Operations Research, 53(1), 1–11.
Kunc, M., Malpass, J., & White, L. (2016). Behavioral Operational Research: Theory, Methodology and Practice. London: Palgrave Macmillan.
Malczewski, J. (2004). GIS-based land-use suitability analysis: A critical overview. Progress in Planning, 62(1), 3–65.
Malczewski, J. (2006). GIS-based multicriteria decision analysis: A survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.
Malczewski, J., & Rinner, C. (2015). Multicriteria Decision Analysis in Geographic Information Science. New York: Springer.
Malekmohammadi, B., & Rahimi Blouchi, L. (2014). Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. Ecological Indicators, 41, 134–144.
Marttunen, M., Belton, V., & Lienert, J. (2018). Are objectives hierarchy related biases observed in practice? A meta-analysis of environmental and energy applications of multi-criteria decision analysis. European Journal of Operational Research, 265, 178–194.
Mighty, M. A. (2015). Site suitability and the analytic hierarchy process: How GIS analysis can improve the competitive advantage of the Jamaican coffee industry. Applied Geography, 58, 84–93.
Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81–97.
Monmonier, M. (1991). How to Lie with Maps. Chicago: University of Chicago Press.
Monmonier, M. (1993). Mapping It Out: Expository Cartography for the Humanities and Social Sciences. Chicago: University of Chicago Press.
Morton, A., & Fasolo, B. (2009). Behavioural decision theory for multi-criteria decision analysis: A guided tour. Journal of the Operational Research Society, 60, 268–275.
Romano, G., Dal Sasso, P., Trisorio Liuzzi, G., & Gentile, F. (2015). Multi-criteria decision analysis for land suitability mapping in a rural area of Southern Italy. Land Use Policy, 48, 131–143.
Saaty, T. L. (1980). The Analytic Hierarchy Process. New York: McGraw-Hill.
Saaty, T. L., & Ozdemir, M. S. (2003). Why the magic number seven plus or minus two. Mathematical and Computer Modelling, 38(3), 233–244.
Simon, J., Kirkwood, C. W., & Keller, L. R. (2014). Decision analysis with geographically varying outcomes: Preference models and illustrative applications. Operations Research, 62(1), 182–194.
Tversky, A., & Kahneman, D. (1974). Judgement under uncertainty: Heuristics and biases. Science, 185, 1124–1131.
Von Winterfeldt, D., & Edwards, W. (1986). Decision Analysis and Behavioural Research. Cambridge: Cambridge University Press.
Wanderer, T., & Herle, S. (2015). Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment. Environmental Impact Assessment Review, 52, 2–8.
Williams, R. E. (1987). Selling a geographical information system to government policy makers. URISA, 3, 150–156.
Yal, G. P., & Akgün, H. (2013). Landfill site selection and landfill liner design for Ankara, Turkey. Environmental Earth Sciences, 70(6), 2729–2752.
Acknowledgement
The author would like to thank Daniel Pfaller for his support in reviewing the relevant literature.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 The Author(s)
About this chapter
Cite this chapter
Ferretti, V. (2020). Insights from an Initial Exploration of Cognitive Biases in Spatial Decisions. In: White, L., Kunc, M., Burger, K., Malpass, J. (eds) Behavioral Operational Research. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-25405-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-030-25405-6_7
Published:
Publisher Name: Palgrave Macmillan, Cham
Print ISBN: 978-3-030-25404-9
Online ISBN: 978-3-030-25405-6
eBook Packages: Business and ManagementBusiness and Management (R0)