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

Haag, Fridolin; Lienert, Judit; Schuwirth, Nele; Reichert, Peter

doi:10.1016/j.omega.2018.05.011

Cited by 28 publications

(41 citation statements)

References 41 publications

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“…This ensures a consistent approach for a continuous evaluation (instead of only discrete classes) that avoids the propagation of discretization errors. Furthermore, it facilitates the propagation of uncertainties through all levels of the objectives hierarchy, the identification of appropriate methods to aggregate the values of sub-objectives to higher-level objectives (Langhans et al., 2014; Haag et al. 2018), and a transparent and consistent communication of the results.…”

Section: Methodsmentioning

confidence: 99%

“…While additive aggregation allows for full compensation between good and bad sub-objectives, the minimum aggregation reflects the value of the worst sub-objective only and is insensitive to improvements or deteriorations, if they do not affect the worst sub-objective. Since neither properties are satisfactory in this context (Langhans et al., 2014; Haag et al. 2018), we propose here two other aggregation functions that are a compromise between these extremes: the additive-minimum and the geometric-offset aggregation (Table 2, Fig.…”

Section: Methodsmentioning

confidence: 99%

“…5). Both aggregation functions allow only partial compensation between good and bad sub-objectives but are able to reflect changes in all sub-objectives, according to their weights and parameters (Haag et al. 2018).…”

Section: Methodsmentioning

confidence: 99%

“…We considered four possibilities for confronting water quality effects and costs: (1) To elicit a case specific value function for costs and the trade-offs between costs and water quality effects from stakeholders and decision makers (Eisenfuehr et al., 2010; Haag et al. 2018), (2) to optimize water quality under given budget constraints, (3) to minimize costs for a certain water quality target, and (4) to visualize costs and water quality in trade-off diagrams.…”

Section: Methodsmentioning

confidence: 99%

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Multi-criteria decision analysis for integrated water quality assessment and management support

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In densely populated areas, surface waters are affected by many sources of pollution. Besides classical pollutants like nutrients and organic matter that lead to eutrophication, micropollutants from various point- and non-point sources are getting more attention by water quality managers. For cost-effective management an integrated assessment is needed that takes into account all relevant pollutants and all sources of pollution within a catchment. Due to the difficulty of identifying and quantifying sources of pollution and the need for considering long-term changes in boundary conditions, typically substantial uncertainty exists about the consequences of potential management alternatives to improve surface water quality. We therefore need integrated assessment methods that are able to deal with multiple objectives and account for various sources of uncertainty. This paper aims to contribute to integrated, prospective water management by combining a) multi-criteria decision support methods to structure the decision process and quantify preferences, b) integrated water quality modelling to predict consequences of management alternatives accounting for uncertainty, and c) scenario planning to consider uncertainty from potential future climate and socio-economic developments, to evaluate the future cost-effectiveness of water quality management alternatives at the catchment scale. It aims to demonstrate the usefulness of multi-attribute value functions for water quality assessment to i) propagate uncertainties throughout the entire assessment procedure, ii) facilitate the aggregation of multiple objectives while avoiding discretization errors when using categories for sub-objectives, iii) transparently communicate the results. We show how to use such multi-attribute value functions for model-based decision support in water quality management. We showcase the procedure for the Mönchaltorfer Aa catchment on the Swiss Plateau. We evaluate ten different water quality management alternatives, including current practice, that tackle macro- and micropollutants from a wide spectrum of agricultural and urban sources. We evaluate costs and water quality effects of the alternatives under four different socio-economic scenarios for the horizon 2050 under present and future climate projections and visualize their uncertainty. While the performance of alternatives is catchment specific, the methods can be transferred to other places and other management situations. Results confirm the need for cross-sectoral coordination of different management actions and interdisciplinary collaboration to support the development of prospective strategies to improve water quality.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Multi-criteria decision analysis for integrated water quality assessment and management support

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“…aggregation model under certainty (as presented in Footnote 1). However, these common simplifications in MAVT applications are not necessarily appropriate (Haag et al, 2018;Langhans et al, 2014;Reichert et al, 2015). Clearly, successive work could address the elicitation of other preference parameters for MCDA models, including the shape of singleattribute value functions, parameters of a non-additive aggregation model, and the decisionmakers' attitude to risks.…”

Section: On the Prototype Survey Conceptmentioning

confidence: 99%

Gamified online survey to elicit citizens’ preferences and enhance learning for environmental decisions

Aubert

Lienert

2019

Environmental Modelling & Software

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Multi-Criteria Decision Analysis (MCDA) requires a critical step, namely to elicit individual preferences. On the basis of learning theories, we formalize preference construction as learning about facts and values, and as a process; we also conceptualize an online preference elicitation survey that offers learning loops to increase factual learning and support preference construction. Another originality is gamification. Game elements (a narrative and non-player characters as motivational affordance) keep respondents engaged in the demanding task of weight elicitation. Our tool enables broad public participation in MCDA, allowing reliable online preference elicitation. The survey concept was tested with 107 students and a control treatment. Quantitative and qualitative data indicate that the concept works. Participants' factual knowledge increased. The survey helped students to learn about their own preferences concerning the importance of objectives. The practical implication is that weighting can be reliably elicited by online surveys. Participants reported a positive experience; further ways to improve it are thoroughly discussed.

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Behavioral Challenges in Practice When Dealing with Public Environmental Decision Problems

Lienert

2024

International Series in Operations Research &Amp; Management Science

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

Cited by 28 publications

References 41 publications

Multi-criteria decision analysis for integrated water quality assessment and management support

Multi-criteria decision analysis for integrated water quality assessment and management support

Gamified online survey to elicit citizens’ preferences and enhance learning for environmental decisions

Behavioral Challenges in Practice When Dealing with Public Environmental Decision Problems

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