Pairwise comparison matrices and the error-free property of the decision maker

Pairwise comparison is a popular assessment method either for deriving criteria-weights or for evaluating alternatives according to a given criterion. In real-world applications consistency of the comparisons rarely happens: intransitivity can occur. The aim of the paper is to discuss the relationship between the consistency of the decision maker—described with the error-free property—and the consistency of the pairwise comparison matrix (PCM). The concept of error-free matrix is used to demonstrate that consistency of the PCM is not a sufficient condition of the error-free property of the decision maker. Informed and uninformed decision makers are defined. In the first stage of an assessment method a consistent or near-consistent matrix should be achieved: detecting, measuring and improving consistency are part of any procedure with both types of decision makers. In the second stage additional information are needed to reveal the decision maker’s real preferences. Interactive questioning procedures are recommended to reach that goal

Modelling multicriteria value interactions with Reasoning Maps

Idiographic causal maps are extensively employed in Operational Research to support problem structuring and complex decision making processes. They model means-end or causal discourses as a network of concepts connected by links denoting influence, thus enabling the representation of chains of arguments made by decision-makers. There have been proposals to employ such structures to support the structuring of multicriteria evaluation models, within an additive value measurement framework. However, a drawback of this multi-methodological modelling is the loss of richness of interactions along the means-end chains when evaluating options. This has led to the development of methods that make use of the structure of the map itself to evaluate options, such as the Reasoning Maps method, which employs ordinal scales and ordinal operators for such evaluation. However, despite their potential, Reasoning Maps cannot model explicitly value interactions nor perform a quantitative ranking of options, limiting their applicability and usefulness. In this article we propose extending the Reasoning Maps approach through a multilinear evaluation model structure, built with the MACBETH multicriteria method. The model explicitly captures the value interactions between concepts along the map and employs the MACBETH protocol of questioning to assess the strength of influence for each means-end link. The feasibility of the proposed approach to evaluate options and to deal with multicriteria interactions is tested in a real-world application to support the construction of a population health index

EX-ANTE EVALUATION OF AGRI-ENVIRONMENTAL SCHEMES: COMBINING ELEMENTS OF PRIVATE AND PUBLIC DECISION MAKING

The objective of this paper is to set a complete ex-ante evaluation to support Decision Makers in designing more efficient and effective agri-environmental contracts, through an integrated modelling of elements of private and public decision making. Ex-ante comparison of policy design options in terms of overall effectiveness requires both simulations of farmers' behaviour and evaluation of the farms simulations outcomes. An intermediate step is the aggregation of single farms impacts at territorial level, in order to identify the aggregate impact of each alternative. Alternatives are several contract design, based on different levels of payments. Farm level analysis is based on a real options approach including in the simulations the timing of choice and the uncertainty in the future about price and decoupled payments. Aggregate policy impact is identified through the quantification of economic, social and environmental impacts at territorial level and the weights are elicited with Multiple-Criteria Robust Interactive Decision Analysis (MCRID). Simulations in the case study show that relevant opportunities to improve policy design are available. Multicriteria Analysis is then used to aggregate impacts of many criteria, including not only effects on the environment, but also economic and social impacts.Agri-environmental schemes, Real Options, Investments, Decoupled payments, Uncertainty, Agricultural and Food Policy, Environmental Economics and Policy, Risk and Uncertainty,

Desirability–doability group judgment framework for the collaborative multicriteria evaluation of public policies

Desirability–doability framework (2 × D) is a novel framework for the collaborative evaluation of public policies. Fundamental objectives and performance indicators are agreed upon in workshops, policies are characterised, and barriers to implementation identified. MACBETH interactive protocols are then applied in decision conferences to elicit qualitative judgments about the desirability of policies, within and across objectives; and about their doability under the expected graveness of barriers on contrasting scenarios. Elicited judgments allow, respectively, to construct a shared multicriteria model measuring the overall desirability of policies; and, to measure their doability. Desirability–doability graphs enable visual interactive classification of policies, with sensitivity/robustness analyses of uncertainties. 2 × D was successfully tested in a real-world urban-health policymaking case to evaluate spatial policies. The main novelty of 2 × D is that it bridges the socio-technical gap, present in OR, between the support required by a complex social decision-making process, and that usually offered by analytic techniques – while keeping modeling theoretically sound and simple

Preference Learning

This report documents the program and the outcomes of Dagstuhl Seminar 14101 “Preference Learning”. Preferences have recently received considerable attention in disciplines such as machine learning, knowledge discovery, information retrieval, statistics, social choice theory, multiple criteria decision making, decision under risk and uncertainty, operations research, and others. The motivation for this seminar was to showcase recent progress in these different areas with the goal of working towards a common basis of understanding, which should help to facilitate future synergies

Participatory Modelling and Decision Support for Natural Resources Management in Climate Change Research

The ever greater role given to public participation by laws and regulations, in particular in the field of environmental management calls for new operational methods and tools for managers and practitioners. This paper analyses the potentials and the critical limitations of current approaches in the fields of simulation modelling (SM), public participation (PP) and decision analysis (DA), for natural resources management within the context of climate change research. The potential synergies of combining SM, PP and DA into an integrated methodological framework are identified and a methodological proposal is presented, called NetSyMoD (Network Analysis – Creative System Modelling – Decision Support), which aims at facilitating the involvement of stakeholders or experts in policy - or decision-making processes (P/DMP). A generic P/DMP is formalised in NetSyMoD as a sequence of six main phases: (i) Actors analysis; (ii) Problem analysis; (iii) Creative System Modelling; (iv) DSS design; (v) Analysis of Options; and (vi) Action taking and monitoring. Several variants of the NetSyMoD approach have been adapted to different contexts such as integrated water resources management and coastal management, and, recently it has been applied in climate change research projects. Experience has shown that NetSyMoD may be a useful framework for skilled professionals, for guiding the P/DMP, and providing practical solutions to problems encountered in the different phases of the decision/policy making process, in particular when future scenarios or projections have to be considered, such as in the case of developing and selecting adaptation policies. The various applications of NetSyMoD share the same approach for problem analysis and communication within the group of selected actors, based upon the use of creative thinking techniques, the formalisation of human-environment relationships through the DPSIR framework, and the use of multi-criteria analysis through a Decision Support System (DSS) software.Modelling, Public Participation, Natural Resource Management, Policy, Decision-Making, Governance, DSS

Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country