Information systems (IS) have evolved to business enablers that fundamentally change the (economic) behavior of market participants. Such “Enabling IS” mediate interactions among individuals and organizations by analyzing (customer) data, aggregating data and preferences, and coordinating transactions and resource allocation. Examples include electronic auction markets, crowd sourcing platforms, online labor markets, reputation mechanisms, e-voting systems, or recommender systems.
Designing such systems requires an in-depth understanding of how humans and organizations interact with each other, and how the parameters of a decision situation can shape its outcome. Game theory, experimental and behavioral economics provide this understanding in the form of fundamental models about the equilibrium behavior of players in complex strategic environments. They offer valuable guidelines for modelling the behavioral patterns of humans, organizations and society and for IS design. For example, game-theory and experimental economics are central in the design of ad auctions, sharing platforms, reputation mechanisms, etc. Moreover, economic theory provides the basis for the design of policy measures to mitigate negative externalities that are created through “Enabling IS” such as sharing platforms.
While economic theory provides fundamental models about the equilibrium behavior of players in markets and other complex strategic environments, the design of “Enabling IS” poses new challenges. On the one hand, IS designers often face utility functions and design desiderata, which are quite different from the ones that are described in economic textbooks. On the other hand, “Enabling IS” allow for the implementation and the evaluation of completely new designs, which have not yet been described in the theoretical literature.
Data generated by “Enabling IS” in combination with advanced analytics methods allow to address these challenges. Data analyses using innovative algorithms promise to deliver unexpected insights and contain unknown behavioral patterns, which in turn enrich economic theory and inform the design of “Enabling IS”.
This highlights the importance of the interplay between economic theory, analytics, and IS design. For instance, research on recommender systems requires to consider algorithm design and behavioral economic models simultaneously. This workshop series focuses on research at the various interfaces between IS Design, Analytics & Economic Behavior.