Stuck or satisfied? The role of complexity and information signals on stopping times in difficult financial decisions

Stage: Design stage, grant proposal submitted

Authors: Konstantinos Ioannidis, Zheng Li

Abstract: Many decision problems in economics and finance are NP-hard, making it difficult to find or verify the optimal solution. Consequently, individuals may over-commit by chasing negligible improvements or under-commit and miss substantial gains, reducing overall efficiency. We investigate how the computational complexity of tasks and access to signals about optimality affect people’s stopping decision in a knapsack-based experiment. Participants face both low- and high- complexity instances and receive no, binary, or value signals regarding how close they are to the optimum. We track participants’ solutions and search times to identify when and how people decide to stop trying. Our results advance understanding of effort allocation in complex economic problems and provide a measure of the value of signals on decision-making.