| dc.description.abstract | Illegal logging is a serious issue that not only has dire environmental and social consequences, but also bring forwards the issue of poor governance of common pool resources. The purpose of this thesis is to contribute to understanding the causes of illegal logging. I integrated existing findings into one theoretical framework for rule compliance onto which I base my knowledge contribution. Further, by building a system dynamics model on aggregate forest and policymaking dynamics, I ran simulations calibrated on historical data. Model simulations showed general fit-to-behavior with discrepancies for the logging function, pointing to the need to study how logging decisions are made. Because of this I designed a multiplayer online simulation game whose rules include an incentive, monitoring and sanctioning mechanism tied together in a scoring function. The participants in the pilot experiment played the game and then reflected about their experience in an interview. Through cross-referencing participant performance and their expressed rationale, I was able to derive initial insights on reasoning behind compliance with the allowable annual cut. Results showed that participants differed in motivation (competitive or noncompetitive) and strategy (compliant and noncompliant). Overall, participants with a compliant strategy expressed more reasons justifying their behavior compared to noncompliant participants. Illegal gain was most often used as a justification for noncompliant behavior, pointing to the incentive structure as a leverage point. Receiving news that another player has been sanctioned reinforced the participants original strategy, which highlights the role of social norms. These initial insights broaden scholarly understanding of compliance and set the stage for running a full-scale experiment. This thesis also has a methodological contribution as it outlines the process of developing a simulation game based off a system dynamics model for the specific purpose of research. Moreover, it proves the usefulness of pilot experiments for studying decision-making reasoning. | en_US |
