Abteilung Umweltsozialwissenschaften

Praxisorientierte Entscheidungsanalyse für eine wertefokussierte Planung von Abwasserinfrastrukturen

Bild einer Kläranlage

Wie können Entscheidungen in der Siedlungswasserwirtschaft besser abgestützt werden? Wie kann man mit unterschiedlichen Zielen und Zielkonflikten umgehen? Wie können lokalen Akteure einbezogen werden? Mit diesen übergeordneten Fragestellungen befasst sich dieses Dissertations-Projekts, mit dem Ziel, Entscheidungen in der Siedlungswasserwirtschaft künftig besser unterstützen zu können. Hierfür wird ein strukturiertes Entscheidungsverfahren und ein Ansatz zur Bewertung von Handlungsoptionen praxisnah weiterentwickelt. Dabei bauen wir auf das Projekt „Langfristige Planung nachhaltiger Wasserinfrastrukturen“ (SWIP) auf. Die theoretische Basis bildet die multikriterielle Entscheidungsanalyse (MCDA).

Forschungsfragen

Folgende Fragen leiten unsere Forschung:
•    Wie lassen sich die Ziele, die in einer Entscheidung erreicht werden sollen, strukturieren? Wie beeinflussen verschiedene Zielhierarchien die Präferenzen der Akteure und ihre Erhebung?
•    Welche Attribute (Indikatoren) sind geeignet, die Konsequenzen einer Entscheidung zu messen? Welche sind geeignet in der Kommunikation mit Akteuren?
•    Wie können wir Vorhersagen bezüglich der Auswirkungen von Abwassereinleitungen auf Gewässer verbessern?
•    Wie bilden wir die Präferenzen von Akteuren am besten in einem MCDA-Modell ab? Wie erheben wir diese Präferenzen?

Unsere Forschungsfragen untersuchen wir in Fallstudien in der Praxis. Konkret befassen wir uns mit der strategischen Planung bezüglich möglichen Zusammenlegungen von Kläranlagen. Diese Entscheidungen sind oft komplex. Sie betreffen verschiedene, teils miteinander im Konflikt stehende Ziele, sind auf lange Zeit ausgelegt und berühren eine Reihe von Interessen. Unser Verfahren ist ein vielversprechender Ansatz, mit solchen Entscheidungsproblemen besser umzugehen.

Team

Dr. Fridolin Haag

PD Dr. Judit Lienert Gruppenleiterin, Gruppe: DA Tel. +41 58 765 5574 Inviare e-mail
Prof. Dr. Max Maurer Tel. +41 58 765 5386 Inviare e-mail

Publikationen

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      title => protected'ValueDecisions, a web app to support decisions with conflicting objectives, 
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      journal => protected'Environmental Modelling and Software' (36 chars)
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      startpage => protected'105361 (19 pp.)' (15 chars)
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      categories => protected'multi criteria decision analysis; MCDA software; multi-attribute value theor
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      description => protected'Complex environmental and public policy decisions profit from structured pro
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         isions, the new open source application ValueDecisions provides advanced ana
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         lti-attribute value theory (MAVT), it offers analysis for decisions with con
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         nsequences of options. Programmed in R, the shiny web framework makes it acc
         essible via a graphical user interface in the browser. We exemplify using Va
         lueDecisions for a wastewater infrastructure planning case in the Paris regi
         on. We surveyed preferences of 655 citizens and conducted sensitivity analys
         is of preference parameters. The best management options were robust across 
         a range of preference profiles and assumptions. To evaluate the app, we deve
         loped a novel usability test based on the ISO standard for software quality 
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      authors => protected'Haag, F.; Reichert, P.; Maurer, M.; Lienert, J.' (67 chars)
      title => protected'Integrating uncertainty of preferences and predictions in decision models: a
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      categories => protected'multi-criteria decision analysis; urban water management; uncertainty; stake
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      description => protected'Decision-making in environmental management requires eliciting preferences o
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         eferences and predictions are both uncertain. Uncertainty of predictions can
          be tackled by multi-attribute utility theory, but the uncertainty of prefer
         ences remains a challenge. We demonstrate an approach for including both unc
         ertainties in a multi-criteria decision analysis (MCDA), using utility theor
         y and the concept of expected expected utility. For a decision regarding a r
         egional merger of wastewater infrastructure in Switzerland, we constructed p
         reference models for four stakeholders. These models also allowed for non-ad
         ditive interactions between objectives. We evaluated the performance of elev
         en decision alternatives for which we predicted potential outcomes. Even tho
         ugh uncertainties were high, we could draw conclusions based on the expected
          expected utility of alternatives. Building a pipeline to discharge treated 
         wastewater to a larger river emerged as a potential consensus alternative to
          mitigate the problem of micropollutants in a small stream. We investigated 
         the robustness of the findings with sensitivity analysis regarding the prefe
         rence parameters and the included objectives. In their actual decision, the 
         stakeholders partly preferred other alternatives than those proposed by the 
         model. Their choices could be explained by reduced decision models in which 
         only few objectives were included. This may indicate the use of simplified c
         hoice heuristics by the stakeholders. The presented approach is feasible for
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      authors => protected'Haag, F.; Zürcher, S.; Lienert, J.' (50 chars)
      title => protected'Enhancing the elicitation of diverse decision objectives for public planning' (76 chars)
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      categories => protected'behavioural OR; decision analysis; online elicitation; urban water managemen
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      description => protected'Identifying objectives is essential for decision making, but individuals hav
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         al decisions, the diverse views of stakeholders should be included, but elic
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         ss of individual brainstorming for eliciting objectives in a real-world sett
         ing; (2) test three interventions to support individuals in generating objec
         tives; (3) investigate which and how many stakeholders are necessary to gene
         rate a comprehensive set of objectives; and (4) develop a feasible elicitati
         on procedure for practice. In an experimental test, 71 stakeholders particip
         ated in five decisions about regional wastewater infrastructure planning in 
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         : (i) providing category cues, (ii) a perspective-taking task, and (iii) pro
         viding a predefined master list of objectives. In simple brainstorming, part
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         >M</em> = 12 objectives in <em>M</em> = 5.3 categories). With the he
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      categories => protected'decision making/process; preference modeling; multi-attribute value theory; 
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      description => protected'Multi-criteria decision analysis (MCDA) requires an accurate representation 
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         icited easily with standard methods. We present a novel approach for identif
         ying multi-attribute value functions which can have any shape. As preference
          information indifference statements are used that can be elicited by trade-
         off questions. Instead of asking one indifference statement for each pair of
          attributes, we ask for multiple trade-offs at different points in the attri
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          taking into account preference and elicitation uncertainty with a probabili
         stic model. Statistical inference supports identifying the most adequate pre
         ference model out of several candidate models through quantifying the uncert
         ainty and assessing the need for non-additivity. The approach is elaborated 
         for determining value functions by hierarchical aggregation. We apply it to 
         an assessment of the ecological state of rivers, which is used to support en
         vironmental management decisions in Switzerland. Preference models of four e
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      description => protected'Building a well-structured objectives hierarchy is central to multi-criteria
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         he size of a hierarchy can be challenging. This paper proposes and illustrat
         es the use of a set of methods to support the simplification of the hierarch
         ies in contexts that are "data rich" and characterised by many objectives. T
         he aim of using the proposed approach is to support decision analysts in dev
         eloping an appropriately concise decision model for the further interactions
          with the stakeholders. Using data from two completed environmental cases we
          show retrospectively how qualitative (means-ends networks), semi-quantitati
         ve (relevancy analysis) and quantitative (correlation analysis, principal co
         mponent analysis, local sensitivity analysis of weights) methods, used alone
          or in combination, can inform hierarchy development. We evaluate the potent
         ial benefits and challenges of each method and discuss the advantages and di
         sadvantages of the simplification of an objectives hierarchy. Questionnaire-
         based relevancy analysis can be a useful method to identify and communicate 
         important objectives in the early phases of an MCDA process with stakeholder
         s, while correlation analysis can help to identify overlapping objectives, p
         articularly in cases having many objectives and alternatives. It is intended
          that the methods support a facilitator in developing a clear understanding 
         of the problem and also prompt deeper thinking about and discussion of the a
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ValueDecisions, a web app to support decisions with conflicting objectives, multiple stakeholders, and uncertainty

Complex environmental and public policy decisions profit from structured procedures such as multi-criteria decision analysis (MCDA). To support such decisions, the new open source application ValueDecisions provides advanced analysis and visualization with no programming expected from users. Based on multi-attribute value theory (MAVT), it offers analysis for decisions with conflicting and interacting objectives, multiple stakeholders, and uncertain consequences of options. Programmed in R, the shiny web framework makes it accessible via a graphical user interface in the browser. We exemplify using ValueDecisions for a wastewater infrastructure planning case in the Paris region. We surveyed preferences of 655 citizens and conducted sensitivity analysis of preference parameters. The best management options were robust across a range of preference profiles and assumptions. To evaluate the app, we developed a novel usability test based on the ISO standard for software quality and surveyed students using ValueDecisions for case studies.
Haag, F.; Aubert, A. H.; Lienert, J. (2022) ValueDecisions, a web app to support decisions with conflicting objectives, multiple stakeholders, and uncertainty, Environmental Modelling and Software, 150, 105361 (19 pp.), doi:10.1016/j.envsoft.2022.105361, Institutional Repository

Integrating uncertainty of preferences and predictions in decision models: an application to regional wastewater planning

Decision-making in environmental management requires eliciting preferences of stakeholders and predicting outcomes of decision alternatives. Usually, preferences and predictions are both uncertain. Uncertainty of predictions can be tackled by multi-attribute utility theory, but the uncertainty of preferences remains a challenge. We demonstrate an approach for including both uncertainties in a multi-criteria decision analysis (MCDA), using utility theory and the concept of expected expected utility. For a decision regarding a regional merger of wastewater infrastructure in Switzerland, we constructed preference models for four stakeholders. These models also allowed for non-additive interactions between objectives. We evaluated the performance of eleven decision alternatives for which we predicted potential outcomes. Even though uncertainties were high, we could draw conclusions based on the expected expected utility of alternatives. Building a pipeline to discharge treated wastewater to a larger river emerged as a potential consensus alternative to mitigate the problem of micropollutants in a small stream. We investigated the robustness of the findings with sensitivity analysis regarding the preference parameters and the included objectives. In their actual decision, the stakeholders partly preferred other alternatives than those proposed by the model. Their choices could be explained by reduced decision models in which only few objectives were included. This may indicate the use of simplified choice heuristics by the stakeholders. The presented approach is feasible for supporting other difficult environmental or engineering decisions in practice, for which we give a number of recommendations.
Haag, F.; Reichert, P.; Maurer, M.; Lienert, J. (2019) Integrating uncertainty of preferences and predictions in decision models: an application to regional wastewater planning, Journal of Environmental Management, 252, 109652 (16 pp.), doi:10.1016/j.jenvman.2019.109652, Institutional Repository

Enhancing the elicitation of diverse decision objectives for public planning

Identifying objectives is essential for decision making, but individuals have difficulties stating their important objectives. In public and environmental decisions, the diverse views of stakeholders should be included, but eliciting a broad set of objectives is challenging. We (1) study the effectiveness of individual brainstorming for eliciting objectives in a real-world setting; (2) test three interventions to support individuals in generating objectives; (3) investigate which and how many stakeholders are necessary to generate a comprehensive set of objectives; and (4) develop a feasible elicitation procedure for practice. In an experimental test, 71 stakeholders participated in five decisions about regional wastewater infrastructure planning in Switzerland. Three interventions were tested with an online survey procedure: (i) providing category cues, (ii) a perspective-taking task, and (iii) providing a predefined master list of objectives. In simple brainstorming, participants stated few objectives (M = 3.3) associated with 2.9 different categories on average. Participants consistently missed objectives they later considered important. Providing a master list was the only intervention that substantially increased the number and breadth of objectives (M = 12 objectives in M = 5.3 categories). With the help of our survey, participants generated between 30 and 38 distinct objectives for each decision case. Between five and nine participants were sufficient to generate these; more participants did not contribute new objectives. Most decision makers need help generating their objectives; combining simple brainstorming with a master list is a straightforward improvement that does not require a facilitator. An online process is promising for involving a large group of stakeholders.
Haag, F.; Zürcher, S.; Lienert, J. (2019) Enhancing the elicitation of diverse decision objectives for public planning, European Journal of Operational Research, 279(3), 912-928, doi:10.1016/j.ejor.2019.06.002, Institutional Repository

Identifying non-additive multi-attribute value functions based on uncertain indifference statements

Multi-criteria decision analysis (MCDA) requires an accurate representation of the preferences of decision-makers, for instance in the form of a multi-attribute value function. Typically, additivity or other stringent assumptions about the preferences are made to facilitate elicitation by assuming a simple parametric form. When relaxing such assumptions, parameters cannot be elicited easily with standard methods. We present a novel approach for identifying multi-attribute value functions which can have any shape. As preference information indifference statements are used that can be elicited by trade-off questions. Instead of asking one indifference statement for each pair of attributes, we ask for multiple trade-offs at different points in the attribute space. This allows inferring parameters of complex value functions despite the simplicity of the preference statements. Parameters are estimated by taking into account preference and elicitation uncertainty with a probabilistic model. Statistical inference supports identifying the most adequate preference model out of several candidate models through quantifying the uncertainty and assessing the need for non-additivity. The approach is elaborated for determining value functions by hierarchical aggregation. We apply it to an assessment of the ecological state of rivers, which is used to support environmental management decisions in Switzerland. Preference models of four experts were quantified, confirming the feasibility of the approach and the relevance of considering non-additive functions. The method suggests a promising direction for improving the representation of preferences.
Haag, F.; Lienert, J.; Schuwirth, N.; Reichert, P. (2019) Identifying non-additive multi-attribute value functions based on uncertain indifference statements, Omega: the international journal of management science, 85, 49-67, doi:10.1016/j.omega.2018.05.011, Institutional Repository

Methods to inform the development of concise objectives hierarchies in multi-criteria decision analysis

Building a well-structured objectives hierarchy is central to multi-criteria decision analysis (MCDA). However, in the absence of a systematic methodology to support the process, this task has been described as "more art than science". Objectives hierarchies often tend to become large and constraining the size of a hierarchy can be challenging. This paper proposes and illustrates the use of a set of methods to support the simplification of the hierarchies in contexts that are "data rich" and characterised by many objectives. The aim of using the proposed approach is to support decision analysts in developing an appropriately concise decision model for the further interactions with the stakeholders. Using data from two completed environmental cases we show retrospectively how qualitative (means-ends networks), semi-quantitative (relevancy analysis) and quantitative (correlation analysis, principal component analysis, local sensitivity analysis of weights) methods, used alone or in combination, can inform hierarchy development. We evaluate the potential benefits and challenges of each method and discuss the advantages and disadvantages of the simplification of an objectives hierarchy. Questionnaire-based relevancy analysis can be a useful method to identify and communicate important objectives in the early phases of an MCDA process with stakeholders, while correlation analysis can help to identify overlapping objectives, particularly in cases having many objectives and alternatives. It is intended that the methods support a facilitator in developing a clear understanding of the problem and also prompt deeper thinking about and discussion of the appropriate structure and content of an objectives hierarchy with the stakeholders involved.
Marttunen, M.; Haag, F.; Belton, V.; Mustajoki, J.; Lienert, J. (2019) Methods to inform the development of concise objectives hierarchies in multi-criteria decision analysis, European Journal of Operational Research, 277(2), 604-620, doi:10.1016/j.ejor.2019.02.039, Institutional Repository

Kontakt

PD Dr. Judit Lienert Gruppenleiterin, Gruppe: DA Tel. +41 58 765 5574 Inviare e-mail

Projektdauer

2015-2019