Comparison of multi-criteria decision analytical software for supporting environmental planning processes Jyri Mustajoki * , Mika Marttunen Finnish Environment Institute, P.O. Box 140, FI-00251 Helsinki, Finland article info Article history: Received 23 June 2016 Received in revised form 23 February 2017 Accepted 27 February 2017 Keywords: Multi-criteria decision analysis Decision support systems Environmental planning abstract In this paper, we analyze 23 multi-criteria decision analysis software tools in terms of their applicability to support environmental planning processes. Our aim is to survey what kind of software is available, and compare the features they provide to meet the characteristics of environmental problems. Our focus is on useful or innovative features of the software from the viewpoint of supporting practitioners to sys- tematically analyze and compare alternatives in environmental planning. The results can be utilized for selecting the most suitable software for supporting the needs of the environmental cases, but also for identifying good practices and innovative implementation solutions for software development. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction Multi-Criteria Decision Analysis (MCDA) is a general term for systematic approaches that can be used to support the analysis of multiple alternatives in complex problems involving multiple criteria (e.g., Belton and Stewart, 2002; Gregory et al., 2012). The process typically consists of the divergent and convergent phases (e.g., Franco and Montibeller, 2010). The divergent phase aims to enlarge the perspective by identifying all the relevant issues to be taken into account, whereas the convergent phase focuses on synthesizing this information for making concise and informed decisions. The problem is typically constructed into a tree-like hi- erarchy of criteria and alternatives. As an outcome, one gets overall values or a preference order of the alternatives, which reflect the evaluators’ preferences regarding the criteria as well as the esti- mated performance of the alternatives with respect to each crite- rion (Keeney and Raiffa, 1976). For a comparison of different MCDA methods, see Belton and Stewart (2002) or Greco et al. (2016), for example. MCDA has been increasingly applied to support environmental planning processes, in which MCDA can provide a transparent synthesis of a problem from different perspectives and a systematic evaluation of the alternatives (Kiker et al., 2005; Huang et al., 2011; Keisler and Linkov, 2014; Voinov et al., 2016). Carrying out the MCDA process in close collaboration with the stakeholders en- hances social learning and enables a transparent inclusion of the public values and concerns in the process (Salo and H€ am€ al€ ainen, 2010; Keisler and Linkov, 2014; Hamilton et al., 2015; Voinov et al., 2016). Consequently, these can contribute to increasing par- ticipants’ trust in the process, as well as its quality. Various multi-criteria software tools or decision support sys- tems (DSS) have been developed to support the application of MCDA methods in practice. Besides computational support for implementing the methods, the tools typically provide various ways to support other phases in the process, such as construction of the model and analysis of the results (e.g., Liu and Stewart, 2004; French and Xu, 2005). For example, the graphical user interfaces offer various possibilities to visualize the process and the results, and consequently, to facilitate the illustrative, transparent, and understandable realization of MCDA (e.g., Reichert et al., 2013). In this paper, we compare various MCDA tools in terms of their applicability to support systematic analysis and comparison of al- ternatives in environmental planning processes. Our motivation is that despite there being many earlier general-level comparisons of MCDA software available (e.g., Vassilev et al., 2005; Oleson, 2016; Weistroffer and Li, 2016), none of those explicitly focuses on the needs of environmental planning processes. Besides comparing the basic technical features of the tools, we analyze them in terms of their ability to meet the typical characteristics of environmental problems (e.g., Keeney, 1973; Mickwitz, 2003; Ascough et al., 2008; Maier et al., 2008), including: * Corresponding author. E-mail address: jyri.mustajoki@ymparisto.fi (J. Mustajoki). Contents lists available at ScienceDirect Environmental Modelling & Software journal homepage: www.elsevier.com/locate/envsoft http://dx.doi.org/10.1016/j.envsoft.2017.02.026 1364-8152/© 2017 Elsevier Ltd. All rights reserved. Environmental Modelling & Software 93 (2017) 78e91