Mapping Survey Data into Agents’ Behavioral Rules for ABMs: Motivation and Challenges

Modeling land use change inevitably involves modeling of an individual behavior of land users in addition to modeling of spatial environment. The processes in the latter usually follow some physical laws. However, it is less straightforward for a modeler how to describe the process of human decision making (Berger and Schreinemachers 2006; Brown and Robinson 2006; Stites 2006). As it is observed by ABM-modelers, it is relatively easy to model the mechanical part of an ABM such as spatial environment, because their dynamics is described by a set of straightforward deterministic rules (with some uncertainty intervals sometimes). In contrast, for human-beings it is not possible to say exactly how they (i.e., we) make decisions. Theoretically, land use behavior is well formalized in economics. Farmers’ (von Thunen 1826 (reprinted in 1966)), households’ (Alonso 1964; Strazsheim 1987) and firms’ (Fujita and Thisse 2002) decision making with respect to land is fully based on the assumption of a rational maximization, equilibrium, and representative behavior. In reality people are boundedly rational, their behavior is often unrepresentative, they choose different strategies in the same situation, their decisions are biased by previous experiences and emotions, and people sometimes make irrational decisions. All these observed characteristics of human behavior make it difficult to use stylized theories of human decision making at the micro level. Thus, how people make decisions (e.g. about land use) remains a black box for a modeler. The only way to open it a little bit is to analyze real world micro level data. These data could probably be obtained either by observing a land-user decision-making in the controlled environment (for example in the setting of a role-playing game (Barreteau et al. 2001; Bousquet et al. 2005)), from interviews with stakeholders and during participatory workshops with them, or by gathering data in the form of surveys (Brown and Robinson 2006; Fernandez et al. 2005). During this workshop we would like to discuss challenges and open questions with respect to using survey data for feeding ABMs. No doubts that surveys provide very valuable data about micro level decision making. However, the following issues might arise here: