Multicriteria analysis, or MCA, has been increasingly used in environmental decision-making to support the identification of suitable courses of action by integrating factual information with value-based information collected through stakeholder engagement. Multicriteria Analysis for Environmental Decision-Making provides an introduction to the key concepts of MCA and includes a series of case studies that illustrate the application of MCA to a variety of environmental decision-making problems ranging from protected area zoning to landfill siting, and from forest restoration to environmental impact assessment of tourism infrastructures. A compact reference that can be used by researchers, practitioners and planners/decision makers, Multicriteria Analysis for Environmental Decision-Making can also serve as a textbook for undergraduate and postgraduate courses in a broad range of curricula.
Davide Geneletti is associate professor at the University of Trento, Department of Civil, Environmental and Mechanical Engineering.
From introduction (pag.1-3)
Environmental decisions involve biophysical, socio-cultural, and economic issues, whose understanding necessitates appropriate methods of knowledge synthesis and stakeholder engagement, as well as the capability to handle increasingly complex and large data sets. It can be argued that all environmental decision-making processes need to consider and compare some forms of alternatives. Alternatives include all types of options, choices or courses of action to accomplish particular goals (Steinemann 2001). These alternatives can be related, for example, to “different possible purposes, different locations and design, different general approaches to serving the selected purpose, different locations and designs, different packages of mitigation and enhancement components, ad different implementation plans” (Gibson et al. 2005, p.126). In environmental decisions, alternatives are assessed against multiple and competing goals, such as protecting nature, addressing needs of communities, and fostering economic growth.
Multicriteria analysis (MCA) is an effective knowledge synthesis method that supports decision making by systematically exploring the pros and cons of different alternatives (Linkov and Moberg 2012; Geneletti and Ferretti 2015), and unveiling trade-offs. It allows comparing alternatives against a set of explicitly-defined criteria that account for the most relevant aspects in a given decision-making process. Operationally, MCA supports structuring decision problems, assessing the performance of alternatives across criteria, exploring trade-offs, formulating a decision, and testing its robustness. MCA is particularly useful when reducing a multi-objective problem into a single-objective problem is either unfeasible or undesirable, especially in participatory settings involving diverse stakeholders with diverse objectives (Linkov et al. 2006). Criteria can be incommensurable, and expressed through different units of measurement: monetary values, number of new jobs, biophysical units, qualitative evaluations, etc.
The main strength of MCA is that it allows combining the analytical performance of the alternatives with the preferences and priorities of stakeholders in a transparent and replicable fashion (French et al. 2009). For these reasons, MCA has been increasingly used in environmental decision-making to support the identification of suitable courses of action, by integrating factual information coming for example from field surveys or impact modelling, with value-based information collected through stakeholder engagement (e.g. Nordström et al. 2011). Thus, MCA is often integrated with other methods and tools, such as participatory approaches and Geographic Information Systems (GIS), as exemplified in Mustajoki et al. (2011) and Janssen et al. (2014). Participatory approaches include a wide range of methods that aim at eliciting the values, preferences, and knowledge of stakeholders, such as Delphi surveys (Bali et al., 2015), focus groups (Comino et al., 2014), and workshops and meetings (Jalilova et al., 2012; Zhang et al., 2013).
The aim of this book is to provide an overview of the principles of MCA, and a series of case studies that illustrate its application to a variety of environmental decision-making problems, ranging from the siting of facilities with critical environmental effects to Natural Park planning, and from the prioritisation of environmental restoration interventions to the assessment of the impact of tourism infrastructures. The book is structured as follows. Chapter 1 introduces the principles of MCA and describes the main stages of a generalized MCA process, by providing details and references to support the implementation of each stage. Chapter 2 reviews the application of MCA for a specific field of environmental decision-making: nature conservation. The objective is twofold: to take stock of past experiences by investigating how key stages of the MCA process have been performed, and to compare findings with best practices in order to provide recommendations for successful applications.
In Chapter 3, a case study about landfill site selection is presented. The method is based on the combination of stakeholder analysis and spatial MCA to first design possible sites for a landfill, and then rank them according to their suitability. Chapter 4 presents an application of MCA to support protected area planning. The case study illustrates the process of proposing a zoning scheme for a natural park, by combining MCA and multi-objective evaluation. Chapter 5 addresses the problem of forest landscapes restoration. In this case study, spatial and non-spatial MCA are applied to first identify forest reforestation priority areas, and then design landscape-scale reforestation options aimed at improving both ecosystem quality and human living conditions. The last case study, described in Chapter 6, shows how MCA can be combined with GIS-based indicators to assess and compare the environmental impacts of proposed ski areas in a mountain watershed. Finally, Chapter 7 provides some conclusions about the potential of MCA to support environmental decision-making, and about the set of skills required for successful MCA applications.
One final note about terminology: MCA is also referred to as Multi-Criteria Decision Analysis (e.g., in Belton and Steward, 2002) or Multi-Criteria Evaluation (e.g., in the seminal work of Voogd 1983). Although these terms are not strictly synonymous, their use and definition are not always consistent in the literature. For this book, I preferred MCA (as, for example, in Beinat and Nijkamp 1998) because it has somehow a broader meaning, suggesting that the approach is useful to frame and better understand a decision problem and to engage stakeholders and explore their views, as much as to take decisions and select alternatives.
Courtesy by Anthem Press