Abteilung Umweltsozialwissenschaften

Verbesserung der Problemstrukturierung in der multikriteriellen Entscheidungsanalyse

Foto eines Wegweisers

Umweltprobleme sind heutzutage sehr komplex. Eine Voraussetzung, um gute Lösungen für sie zu finden, ist ein guter Überblick über die ökologischen, wirtschaftlichen und sozialen Systeme und die Beziehungen innerhalb und zwischen ihnen. Eine weitere Voraussetzung ist ein guter Dialog zwischen Wissenschaftlerinnen und Wissenschaftlern, Akteuren und politischen Entscheidungsträgern. Es besteht ein grosser Bedarf an Methoden die das Zusammenspiel von Wissenschaft und Praxis erleichtern und die Strukturierung und Evaluation solcher Probleme unterstützen.

Problemstrukturierungsmethoden (PSMs) sind eine Gruppe von Methoden, die eine schwierige Situation nicht lösen, mit denen sie sich jedoch gut strukturieren lässt. PSMs eignen sich, um das engagierte und strukturierte Gespräch zu fördern, um die Situation aus einer Vielzahl von Perspektiven zu betrachten und Informationen zusammenzuführen. Die bekanntesten PSMs sind Akteurs-Analyse, SWOT-Analyse (Strengths (Stärken), Weaknesses (Schwächen), Opportunities (Chancen) und Threats (Gefahren)), das DPSIR-Diagramm (Driving forces (Treibende Kräfte), Pressures (Belastungen), State (Zustand), Impact (Auswirkung), und Responses (Reaktionen)), kognitive Karten und Szenarienplanung.

Die multikriterielle Entscheidungsanalyse (MCDA) bietet eine grosse Vielfalt von Methoden, um zu einem besseres Gesamtverständnis einer Entscheidungssituation zu gelangen, Alternativen zu entwickeln und sie systematisch aus verschiedenen Perspektiven zu vergleichen. MCDA lässt sich am besten an gut strukturierten Problemen anwenden. Bisher fehlen Werkzeuge für eine angemessene Strukturierung.

Die Studie besteht aus zwei Teilen:

  1. Kombinierter Einsatz von PSMs und MCDA. Hier ist das Ziel, Wege zur Verbesserung von MCDA-Prozessen in schlecht strukturierten und komplexen Situationen zu finden. Wir begannen mit einer umfangreichen Literaturrecherche, um den Stand des Wissens zu studieren. Wir haben über 350 Artikel gefunden, die wir jetzt analysieren, um gute Praktiken und Einschränkungen in der aktuellen Anwendung der Methoden zu identifizieren. Wir werden Empfehlungen zur Unterstützung der nahtlosen Integration von PSMs und MCDA in verschiedenen Arten von Entscheidungssituationen präsentieren.
  2. Überschaubare Zielhierarchien in der MCDA. MCDA-Analysen neigen dazu, umso komplexer zu werden, je komplexer ein Entscheidungsproblem ist. Dies kann zu mühseligen und ineffizienten Studien führen. Die Struktur der Zielhierarchie kann auch eine entscheidende Auswirkung auf das Ergebnis der MCDA haben. Bei der Ausarbeitung von Zielhierarchien streben wir danach, Verfahren zu entwickeln und zu testen, die helfen können, eine gute Balance zwischen den beiden konfligierenden Zielen ‚Kürze’ und ‚Vollständigkeit’ zu finden. Wir werden auch den Einfluss der Grösse und Struktur der Zielhierarchie auf die Präferenzerhebung und das Entscheidungsergebnins systematisch erforschen.

Die Methoden und Ansätze werden in verschiedenen Wasserressourcen-Managementprojekten getestet, z.B. in der Evaluation und im Design der kantonalen Wasserqualitäts-Überwachungsprogramme der Schweiz und in der Entscheidungsunterstützung für die Abwasser-Infrastrukturplanung.
 

Team

Dr. Mika Marttunen

Prof. Dr. Valerie Belton

PD Dr. Judit Lienert Group Leader, Cluster: DA (Decision Analysis) Tel. +41 58 765 5574 Inviare e-mail
Dr. Nele Schuwirth Abteilungsleiterin und Gruppenleiterin Tel. +41 58 765 5528 Inviare e-mail

Publikationen

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

Identifying relevant objectives in environmental management decisions: an application to a national monitoring program for river restoration

Environmental monitoring covers many different management domains. They range from biodiversity conservation to water protection, natural hazard prevention, impact assessment, resource use, or environmental restoration. The need for clear objectives has long been emphasized in the management literature, but has often received only little attention in monitoring design. This is partly due to the lack of systematic approaches for setting objectives. In this paper, we present a formal approach based on Multi-Criteria Decision Analysis (MCDA), namely relevancy analysis, to prioritize management objectives. We demonstrate its use for a river restoration monitoring program in Switzerland comprising 35 physical and biological objectives. The relevancy of an objective is based on two main components, the general importance of the objective, and the problemspecific impact range. The general importance of an objective is used to identify the most important management objectives from a hierarchy within the national program (i.e. objectives to be monitored). The impact range is used to understand which management objectives are more important to monitor for different river restoration measures (i.e. sub-selection of the objectives specifically for the restoration measure). The general importance of a management objective was determined based on the frequency an objective is mentioned in selected policy documents, and the legislative power and temporal persistency of each document. The impact ranges were identified from a questionnaire involving 15 Swiss river restoration professionals. Hereby, we assumed that the impact range increases as the anticipated impact of the restoration measure on a specific management objective increases, and as the uncertainty to anticipate this impact increases. For simplicity, we applied the approach only to one restoration measure, namely river widening. Six management objectives scored high in relevancy in terms of both impact range and general importance – channel structure and diversity, structure and diversity of the banks and floodplains, sediment dynamics, longitudinal connectivity, lateral connectivity, and vertical connectivity. Hence, these objectives are both important national objectives for river monitoring (according to the legislation) and are objectives that are potentially highly impacted by a river widening project. We performed sensitivity analyses related to the calculation of the general importance, the impact range, and the relevancy of the objectives. The practice-oriented approach can be transferred to a broad diversity of decision situations where there is a need for systematic evaluation of the importance of objectives. It could be a useful tool for social learning and finding group consensus about the priority of the objectives.
Marttunen, M.; Weber, C.; Åberg, U.; Lienert, J. (2019) Identifying relevant objectives in environmental management decisions: an application to a national monitoring program for river restoration, Ecological Indicators, 101, 851-866, doi:10.1016/j.ecolind.2018.11.042, Institutional Repository

Are objectives hierarchy related biases observed in practice? A meta-analysis of environmental and energy applications of Multi-Criteria Decision Analysis

Procedural and behavioural biases have received little attention in recent Multi-Criteria Decision Analysis (MCDA) research. Our literature review shows that most research on biases was done 15–30 years ago. This study focuses on biases that are introduced at an early stage of MCDA when building objectives hierarchies and their effect on the weights. The main objective is to investigate whether prior findings regarding such biases, which were mostly based on laboratory experiments, can be found in real-world applications. We conducted a meta-analysis of the objectives hierarchies and weight elicitation procedures in 61 environmental and energy MCDA cases. Relationships between the structural characteristics of the objectives hierarchy and assigned objectives’ weights were analysed with statistical tests. Our main research questions were: (i) How does hierarchy size and structure affect the objectives’ weights? (ii) How are weights distributed across economic, social and environmental objectives? (iii) Is there support for the equalising bias? Our findings are mostly aligned with earlier research and suggest that the hierarchy structure and content can substantially influence weight distributions. For example, hierarchical weighting seems to be sensitive to the asymmetry bias, which can occur when a hierarchy has branches that differ in the number of sub-objectives. We found no evidence for the equalising bias. We highlight issues deserving more attention when developing objectives hierarchies and eliciting weights. The research demonstrates the potential to use meta-analysis, which has not previously been used in this way in the MCDA field, to learn from a collection of applications.
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(1), 178-194, doi:10.1016/j.ejor.2017.02.038, Institutional Repository

Structuring problems for multi-criteria decision analysis in practice: a literature review of method combinations

Structuring problems for Multi-Criteria Decision Analysis (MCDA) has attracted increasing attention over the past 20 years from both a conceptual and a practical perspective. This is reflected in a significant growth in the number of published applications which use a formal approach to problem structuring in combination with an analytic method for multi-criteria analysis. The problem structuring approaches (PSMs) include general methodologies such as Checkland's Soft Systems Method (SSM), Eden and Ackermann's Strategic Options Design and Analysis (SODA) and other methods that focus on a particular aspect. We carried out a literature review that covers eight PSMs (Cognitive and Causal Maps, DPSIR, Scenario Planning, SSM, Stakeholder Analysis, Strategic Choice Approach, SODA and SWOT) and seven MCDA methods (AHP, ANP, ELECTRE, MAUT, MAVT, PROMETHEE and TOPSIS). We first identified and analysed 333 articles published during 2000-2015, then selected 68 articles covering all PSM-MCDA combinations, which were studied in detail to understand the associated processes, benefits and challenges. The three PSMs most commonly combined with MCDA are SWOT, Scenario Planning and DPSIR. AHP was by far the most commonly applied MCDA method. Combining PSMs with MCDA produces a richer view of the decision situation and enables more effective support for different phases of the decision-making process. Some limitations and challenges in combining PSMs and MCDA are also identified, most importantly relating to building a value tree and assigning criteria weights.
Marttunen, M.; Lienert, J.; Belton, V. (2017) Structuring problems for multi-criteria decision analysis in practice: a literature review of method combinations, European Journal of Operational Research, 263(1), 1-17, doi:10.1016/j.ejor.2017.04.041, Institutional Repository

Kontakt

PD Dr. Judit Lienert Group Leader, Cluster: DA (Decision Analysis) Tel. +41 58 765 5574 Inviare e-mail

Informationen

Projektstart: Februar 2015

Projektdauer: 2 Jahre