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Top1. Introduction
It is recognized that collaborative modeling approaches can create value in agri-food chains (Filippi & Chapdaniel, 2016) in which numerous actors or stakeholders interact and participate in coordinated activities (Handayati et al., 2015) to create and offer a particular good or service. However, agri-food chains are complex systems in which stakeholders are prone to tensions, conflicts, policy threats and vertical integration pressure (Campbell, 2004; Balmann et al., 2006). Approaches such as consensus building (Burgess et al., 2003; Campbell, 2004) have been proposed to help increase stakeholders’ awareness of critical situations in agri-food chains (usually in deliberation processes related to policy making) and to better understand the different positions and viewpoints of the different involved parties.
1.1. Consensus Building
It is also acknowledged that stakeholders would be in a better position to make compromise if they were willing to reach a consensus-based solution and if they clearly understood the positions of the different parties. Consensus building is a conflict-resolution process mainly used to settle complex, multiparty issues (Gray, 1989). Since the 1980s, it has become widely used in the environmental and public policy arena. The process allows various stakeholders (parties with an interest in the problem or issue) to work together to develop a mutually acceptable solution (Burgess et al., 2003). The consensus-building process helps stakeholders to establish a common understanding of the attended situation (process which is often called ‘situation awareness’ (Adam et al., 1995; Endsley, 1995) and to create a framework for developing a solution that works for everyone.
1.2. Argumentation Modeling and Visualization Approaches
Gray (1989) showed that problems that are best addressed using a consensus-building approach tend to share some general characteristics such as: 1) The problems are ill-defined, or there is disagreement about how they should be defined; 2) Several stakeholders have a vested interest in the problems and are interdependent; 3) Stakeholders may have different levels of expertise and different access to information about the problems; 4) The problems are often characterized by technical complexity and scientific uncertainty; 5) Incremental or unilateral efforts to deal with the problems typically produce less than satisfactory solutions; 6) Existing processes for addressing the problems have proved insufficient and may even exacerbate them.
Interestingly, van Bruggen et al. (2003) demonstrate the value of using Computer-Supported Argumentation Visualization (CSAV) to tackle ill-structured problems, which share a large number of characteristics with the problems addressed by consensus-building approaches (Gray, 1989). The main reason is that solving ill-structured problems results from an argumentative process starting from informal reasoning (van Bruggen et al., 2003) and requires building an argumentation structure which consists, minimally, of a claim with support (e.g. evidential reasoning). Evaluation of the arguments cannot be carried out in terms of whether any argument is right or wrong, but requires the evaluator to make use of other criteria such as acceptability of the claim, and the quality of the argumentation which is assessed by taking counter-arguments into account. Argument-based and agent-based modeling approaches have recently been proposed to enhance stakeholder interactions in agrifood chains (Bourguet et al., 2013; Thomopoulos et al., 2015; Croitoru et al., 2016).