Feedback Economics of Colleges

This project explores microeconomics of higher education by conceptualizing a tuition-dependent college as a complex service system. We develop a system dynamics model that captures key causal interrelationships and multiple feedback effects between faculty, facilities, tuition revenue, costs, reputation, and outcomes. We then use this college model to explore how operations of academic institutions are affected by a decline of college applications and the COVID-19 pandemic.

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Higher Education as a Service

This project applies the service science framework to higher education. To understand the reasons behind the success and failure of academic programs, we build on the previous literature that conceptualizes education as a service delivered by universities which are complex systems. We introduce the Service Canvas as a tool for identifying components of academic programs.

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Feedback Economics

This book examines economic problems from the systems thinking and feedback perspectives. By using system dynamics methods and computer simulation models, the contributors apply feedback analysis and dynamic simulation modeling to local, national, and global economic issues and concerns.

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Economic Origins of the Sicilian Mafia

During the nineteenth century, Sicily underwent a series of political and land reforms that led to dismantling of large land ownership and culminated in the unification with the Italian state in 1861. But the new Italian government was ineffective at enforcing the rule of law on the island. Banditry and a general sense of lawlessness proliferated. In that environment, the mafia emerged as a private response to the inadequate protection by the state. The mafia offered private protection from bandits to landowners who could not rely on protection and enforcement of property rights by the state.

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Promoting Systems Thinking Skills in Middle Schools with Structural Debriefing of Instructional Video Games

Earlier research has shown that school children can learn systems thinking skills by playing video games. But simply playing a game without a systematic pedagogical approach is insufficient because the game remains a “black box” to students even if they implicitly understand how the system operates. Working with STEM teachers, a game development company and a non-profit, we designed and piloted game-based curricula to teach systems thinking skills. We call this approach Game-Based Structural Debriefing (GBSD).

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Improving Instructional Simulations with Structural Debriefing

Research shows that learning and task performance improve when participants in management exercises understand the structure of the system they control. However, the majority of business simulators are “black-boxes.” This article introduces structural debriefing, which is a debriefing activity aimed at helping students learn about causal relationships, feedbacks, accumulations and delays within a black-box simulation. A structural debriefing can be prepared and facilitated by following the Structural Debriefing Protocol. A pilot study was conducted in which undergraduate students participated in a structural debriefing of The LITTLEFIELD TECHNOLOGIES, a popular simulation for teaching principles of operations management. The students were able to complete all eight steps of a structural debriefing, but required considerable time (three academic terms) to do so. Not every instructional simulation will require all the steps or such a large time commitment. The successful completion of the pilot study demonstrates that structural debriefing is a useful debriefing technique. However, to be effective, the scope and format of a structural debriefing activity must suit practical and pedagogical considerations.

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Asset Price Dynamics with Heterogeneous Beliefs and Local Network Interactions

PIs: Valentyn Panchenko (University of New South Wales), Sergiy Gerasymchuk (ING Group), and Oleg V. Pavlov (WPI)

This project investigates the effects of network topologies on asset price dynamics. We introduce network communications into a simple asset pricing model with heterogeneous beliefs. The agents may switch between several belief types according to their performance. The performance information is available to the agents only locally through their own experience and the experience of other agents directly connected to them. We model the communications with four commonly considered network topologies: a fully connected network, a regular lattice, a small world, and a random graph. The results show that the network topologies influence asset price dynamics in terms of the regions of stability, amplitudes of fluctuations and statistical properties.

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