Decision map for spatial decision making in urban planning

In this paper, we introduce the concept of decision map and illustrate the way this new concept can be used effectively to support participation in spatial decision making and in urban planning. First, we start by introducing our spatial decision process which is composed of five, non-necessary sequential, phases: problem identification and formulation, analysis, negotiation, concertation, and evaluation and choice. Negotiation and concertation are two main phases in spatial decision making but most available frameworks do not provide tools to support them effectively. The solution proposed here is based on the concept of decision map which is defined as an advanced version of conventional geographic maps which is enriched with preferential information and especially designed to clarify decision making. It looks like a set of homogenous spatial units; each one is characterised with a global, often ordinal, evaluation that represents an aggregation of several partial evaluations relative to different criteria. The decision map is also enriched with different spatial data exploration tools. The procedure of the construction of a decision map contains four main steps: definition of the problem (i.e. generation of criteria maps), generation of an intermediate map, inference of preferential parameters, and generation of a final decision map. The concept of decision map as defined here is a generic tool that may be applied in different domains. This paper focuses on the role of the decision map in supporting participation in spatial decision making and urban planning. Indeed, the decision map is an efficient communication tool in the sense that it permits to the different groups implied in the spatial decision process to ‘think visually’ and to communicate better between each other.ou

Incorporating stakeholders’ knowledge in group decision-making

International audienc

Integrating multiple criteria decision analysis in participatory forest planning

Forest planning in a participatory context often involves multiple stakeholders with conflicting interests. A promising approach for handling these complex situations is to integrate participatory planning and multiple criteria decision analysis (MCDA). The objective of this paper is to analyze strengths and weaknesses of such an integrated approach, focusing on how the use of MCDA has influenced the participatory process. The paper outlines a model for a participatory MCDA process with five steps: stakeholder analysis, structuring of the decision problem, generation of alternatives, elicitation of preferences, and ranking of alternatives. This model was applied in a case study of a planning process for the urban forest in Lycksele, Sweden. In interviews with stakeholders, criteria for four different social groups were identified. Stakeholders also identified specific areas important to them and explained what activities the areas were used for and the forest management they wished for there. Existing forest data were combined with information from interviews to create a map in which the urban forest was divided into zones of different management classes. Three alternative strategic forest plans were produced based on the zonal map. The stakeholders stated their preferences individually by the Analytic Hierarchy Process in inquiry forms and a ranking of alternatives and consistency ratios were determined for each stakeholder. Rankings of alternatives were aggregated; first, for each social group using the arithmetic mean, and then an overall aggregated ranking was calculated from the group rankings using the weighted arithmetic mean. The participatory MCDA process in Lycksele is assessed against five social goals: incorporating public values into decisions, improving the substantive quality of decisions, resolving conflict among competing interests, building trust in institutions, and educating and informing the public. The results and assessment of the case study support the integration of participatory planning and MCDA as a viable option for handling complex forest-management situations. Key issues related to the MCDA methodology that need to be explored further were identified: 1) The handling of place-specific criteria, 2) development of alternatives, 3) the aggregation of individual preferences into a common preference, and 4) application and evaluation of the integrated approach in real case studies

Stated Choice Experiments with Complex Ecosystem Changes: The Effect of Information Formats on Estimated Variances and Choice Parameters

Stated choice experiments about ecosystem changes involve complex information. This study examines whether the format in which ecosystem information is presented to respondents affects stated choice outcomes. Our analysis develops a utility-maximizing model to describe respondent behavior. The model shows how alternative questionnaire formats alter respondents’ use of filtering heuristics and result in differences in preference estimates. Empirical results from a large-scale stated choice experiment confirm that different format presentations of the same information lead to different preference parameter estimates and error variances. A tabular format results in choice parameter estimates with statistically smaller variances than parameters estimated from data obtained with a text-based format. A text-based format also appears to induce greater use of decision heuristics than does a tabular format.choice experiments, heuristics, stated preference, valuation, web surveys, wetland mitigation, Crop Production/Industries, Demand and Price Analysis,

Network Analysis, Creative System Modelling and Decision Support: The NetSyMoD Approach

This paper presents the NetSyMoD approach – where NetSyMod stands for Network Analysis – Creative System Modelling – Decision Support. It represents the outcome of several years of research at FEEM in the field of natural resources management, environmental evaluation and decision-making, within the Natural Resources Management Research Programme. NetSyMoD is a flexible and comprehensive methodological framework, which uses a suite of support tools, aimed at facilitating the involvement of stakeholders or experts in decision-making processes. The main phases envisaged for the process are: (i) the identification of relevant actors, (ii) the analysis of social networks, (iii) the creative system modelling and modelling of the reality being considered (i.e. the local socio-economic and environmental system), and (iv) the analysis of alternative options available for the management of the specific case (e.g. alternative projects, plans, strategies). The strategies for participation are necessarily context-dependent, and thus not all the NetSyMod phases may be needed in every application. Furthermore, the practical solutions for their implementation may significantly differ from one case to another, depending not only on the context, but also on the available resources (human and financial). The various applications of NetSyMoD have nonetheless in common the same approach for problem analysis and communication within a group of 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 the mDSS software.Social Network, Integrated Analysis, Participatory Modelling, Decision Support

Spatial Aggregation: Theory and Applications

Visual thinking plays an important role in scientific reasoning. Based on the research in automating diverse reasoning tasks about dynamical systems, nonlinear controllers, kinematic mechanisms, and fluid motion, we have identified a style of visual thinking, imagistic reasoning. Imagistic reasoning organizes computations around image-like, analogue representations so that perceptual and symbolic operations can be brought to bear to infer structure and behavior. Programs incorporating imagistic reasoning have been shown to perform at an expert level in domains that defy current analytic or numerical methods. We have developed a computational paradigm, spatial aggregation, to unify the description of a class of imagistic problem solvers. A program written in this paradigm has the following properties. It takes a continuous field and optional objective functions as input, and produces high-level descriptions of structure, behavior, or control actions. It computes a multi-layer of intermediate representations, called spatial aggregates, by forming equivalence classes and adjacency relations. It employs a small set of generic operators such as aggregation, classification, and localization to perform bidirectional mapping between the information-rich field and successively more abstract spatial aggregates. It uses a data structure, the neighborhood graph, as a common interface to modularize computations. To illustrate our theory, we describe the computational structure of three implemented problem solvers -- KAM, MAPS, and HIPAIR --- in terms of the spatial aggregation generic operators by mixing and matching a library of commonly used routines.Comment: See http://www.jair.org/ for any accompanying file

The Ontology of Group Agency

We present an ontological analysis of the notion of group agency developed by Christian List and Philip Pettit. We focus on this notion as it allows us to neatly distinguish groups, organizations, corporations – to which we may ascribe agency – from mere aggregates of individuals. We develop a module for group agency within a foundational ontology and we apply it to organizations

Cognitive strategic groups and long-run efficiency evaluation : the case of Spanish savings banks

In the framework of Cognitive Approach, this paper proposes a new method to identify strategic groups (SG) using Data Envelopment Analysis (DEA) methods. Two assumptions are maintained in the SG literature: first, firms grouped together value inputs and outputs similarly, and, second, some degree of stability in those valuations should be identified. Virtual weights obtained from DEA are extremely useful in the valuation of the strategic variables, but a problem emerges when longitudinal analysis is performed. This problem is addressed by defining a long run DEA evaluation. SGs are determined by means of Cluster Analysis, using virtual outputs and virtual inputs as variables and Spanish savings banks as observations. The traditional method of determining SGs by clustering on the original variables is also applied and the results are compared. It is shown that the long run DEA weights approach has advantages over the traditional methodology

Public Participation GIS for sustainable urban mobility planning: methods, applications and challenges

Sustainable mobility planning is a new approach to planning, and as such it requires new methods of public participation, data collection and data aggregation. In the article we present an overview of Public Participation GIS (PPGIS) methods with potential use in sustainable urban mobility planning. We present the methods using examples from two recent case studies conducted in Polish cities of Poznań and Łodź. Sustainable urban mobility planning is a cyclical process, and each stage has different data and participatory requirements. Consequently, we situate the PPGIS methods in appropriate stages of planning, based on potential benefits they may bring into the planning process. We discuss key issues related to participant recruitment and provide guidelines for planners interested in implementing methods presented in the paper. The article outlines future research directions stressing the need for systematic case study evaluation