信任还是囤积：供应链短缺中的人机交互模型
To Trust or to Stockpile: Modeling Human-Simulation Interaction in Supply Chain Shortages
摘要：
了解动态和复杂环境中的决策是一项挑战，但对于预防、缓解和应对不良事件（例如，金融危机）。模拟游戏已经显示出希望，以提高我们的决策在这种情况下的理解。然而，一个悬而未决的问题仍然是我们如何从这些游戏中提取有用的信息。我们贡献了一种方法来建模人与仿真交互，利用现有的方法来表征：（1）动态仿真环境的系统状态（主成分分析），（2）人与仿真交互的行为响应（隐马尔可夫模型），以及（3）跨系统状态的行为响应（序列分析）。我们证明了这种方法与我们的游戏模拟药品短缺的供应链环境。我们对135名参与者的实验研究结果显示了不同的玩家类型（囤积者，反应者，追随者），行为在不同系统状态下如何变化，以及共享信息如何影响行为。我们讨论了我们的研究结果如何挑战现有的文献。
英文摘要：
Understanding decision-making in dynamic and complex settings is a challenge yet essential for preventing, mitigating, and responding to adverse events (e.g., disasters, financial crises). Simulation games have shown promise to advance our understanding of decision-making in such settings. However, an open question remains on how we extract useful information from these games. We contribute an approach to model human-simulation interaction by leveraging existing methods to characterize: (1) system states of dynamic simulation environments (with Principal Component Analysis), (2) behavioral responses from human interaction with simulation (with Hidden Markov Models), and (3) behavioral responses across system states (with Sequence Analysis). We demonstrate this approach with our game simulating drug shortages in a supply chain context. Results from our experimental study with 135 participants show different player types (hoarders, reactors, followers), how behavior changes in different system states, and how sharing information impacts behavior. We discuss how our findings challenge existing literature.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
