English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Understanding decision-making in dynamic and complex settings is a challengeyet essential for preventing, mitigating, and responding to adverse events(e.g., disasters, financial crises). Simulation games have shown promise toadvance our understanding of decision-making in such settings. However, an openquestion remains on how we extract useful information from these games. Wecontribute an approach to model human-simulation interaction by leveragingexisting methods to characterize: (1) system states of dynamic simulationenvironments (with Principal Component Analysis), (2) behavioral responses fromhuman interaction with simulation (with Hidden Markov Models), and (3)behavioral responses across system states (with Sequence Analysis). Wedemonstrate this approach with our game simulating drug shortages in a supplychain context. Results from our experimental study with 135 participants showdifferent player types (hoarders, reactors, followers), how behavior changes indifferent system states, and how sharing information impacts behavior. Wediscuss how our findings challenge existing literature.

To Trust or to Stockpile: Modeling Human-Simulation Interaction in Supply Chain Shortages