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  • Public defence: 2020-04-21 10:00 13:111
    Milutinovic, Goran
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Computational and Visual Tools for Geospatial Multi-Criteria Decision-Making2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Geospatial multi-criteria decision-making usually concerns quasi-continuous choice models, with the number of alternatives constrained only by the limits of the used representation model. This sets high demands on the decision-making methods used in the context. The most commonly used approach in geospatial decision-making is combining a method for assigning criteria weights with an aggregation method. As pairwise comparison of alternatives is not feasible when the number of alternatives is large, the weights are usually assigned to criteria without considering the values or the value ranges of the alternatives, an approach often criticized in the decision analysis literature. Apart from criteria weighting controversy, this approach does not allow for advanced use of interactive visualization in the choice phase of the decision-making process. In this thesis, two alternative methods for geospatial decision-making based on the even swaps method are developed. The first method relies on automation of swaps, which makes this method viable for decision problems with any number of alternatives. The second method emanates from the findings of behavioral decision theory, and combines even swaps with reduction of large data sets through quasi-satisficing, allowing for efficient use of interactive visualization in the choice phase of the decision process. Visualization frameworks for both methods are also developed in the thesis. They include both geo-specific representations, such as interactive maps, and infovis techniques such as graphs, diagrams, scatterplots and parallel coordinates. Two studies concerning the impact of interactive visualization on decision-making are presented in the thesis: a study concerning the impact of interactive visualization on geospatial decision-making, and a study concerning potential effects of visual saliency on decision-making. The results of the first study indicated positive effects of interactive visualization on coherency and consistency in performing trade-offs. The results of the second study show that visual saliency may help decision-makers make better decisions. The work presented in this thesis contributes to method development and the use of interactive visualization in the context of geospatial decision-making.

  • Public defence: 2020-04-22 13:00 12:108, Gävle
    Holmgren, Mattias
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Building Engineering, Energy Systems and Sustainability Science, Environmental Science.
    A Negative Footprint Illusion in Environmental Impact Estimates2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A major part of anthropogenic climate change is due to everyday human behavior, such as transportation, food and energy consumption. As a result, it has been argued that many barriers for mitigating climate change are psychological in nature. For example, people’s decisions and behaviors are subject to heuristics and biases which sometime harm our decisions. The benchmark of the present thesis is the finding that people believe that adding environmentally friendly items to a set of conventional items reduces the impact of the whole set. This phenomenon has been coined a negative footprint illusion (NFI). How robust is this effect, is it generalizable across judgmental dimensions and what is the mechanism that underpins the effect? This thesis concerns these three questions. Paper 1 found support for the assumption that an averaging bias underpins the NFI. On this view, the NFI appears because people intuitively respond with the average of the ‘vices’ (the unfriendly objects) and ‘virtues’ (the more environmentally friendly objects) in the combined set of objects. Paper 2 demonstrated that the NFI is insensitive to some levels of expertise. Furthermore, Paper 2 also reported the first demonstration of the NFI in the context of a within-participants design. Paper 3 found that a NFI can also be demonstrated in the context of atmospheric CO2 concentration estimates. Paper 3 also reported further evidence for the averaging bias account of the NFI and showed that the effect is at least insensitive to some variations in the framing of the problem posed to the participants. Paper 4 demonstrated that the NFI can be eliminated by priming a summative mindset before requesting participants to make the environmental impact estimates. Taken together, this thesis shows that the NFI is a robust phenomenon that can be found across various to-be-estimated stimulus materials, it appears to be underpinned by an averaging bias but can be cognitively controlled in certain conditions.