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Abstract
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This paper investigates the computational complexity of decision-making in small networks, focusing on how individuals acquire and utilize information. In many decision-making environments, individuals must balance the desire for accuracy with the social influence of others' decisions. In our study, we used an experimental asset-valuation game to investigate how participants obtain valuable information from their peers and decide which pieces of information to prioritize when making predictions. These predictions aim to incorporate both the fundamental value of the asset and the predictions of their peers.
Our findings reveal two prominent biases: under-acquisition of information and selective blindness, which are robust across four information communities characterized by varying preferences for social information. The results indicate that subjects consistently acquired less information than theoretical models predict, leading to suboptimal decisions and diminished potential earnings. Making additional connections, which provide more information, leads to potential higher payoffs. However, individuals tended to ignore a significant portion of the information they acquired, often assigning zero weight to relevant data, a behavior termed ""selective blindness."" This behavior was widespread, with over 74% of subjects exhibiting this bias, significantly impacting their decision-making and earnings. Intriguingly, we also observe a negative correlation between these two biases: individuals who acquired more information were more likely to exhibit selective blindness. These results underscore the complexity of human decision-making in networked settings, where both the quantity and quality of information processing matter and are correlated.
The study highlights the need for holistic strategies in improving decision-making processes. Addressing only the quantity or quality of information without considering how it is processed can lead to unintended consequences. These insights have broader implications for understanding how people navigate complex information environments and suggest that information acquisition and utilization must be considered together to optimize outcomes in group decision-making settings."
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