The Behavioural Knapsack Problem: Evidence of a Fundamental Bias in Project Selection

Abstract

The selection of projects from a set of possible alternatives is a fundamental decision problem for any organization. Governments and businesses that allocate sizeable resource budgets across projects and initiatives face the same fundamental challenge: to select the most valuable projects while respecting budget constraints. The literature proposes efficient algorithms to solve these knapsack problems, but the higher complexity of the real-world selection problems, together with the black-box behavior of these algorithms, make their adoption impractical. Instead, decision makers perform mental searches across the available options, thereby introducing behavioral effects into the knapsack problem. Through a lab experiment, we show that the decision makers’ mental search is biased towards selecting too many small projects compared to the optimal choice. This suggests that selection decisions may lead to inefficient resource allocation in organizations. We provide evidence that this fundamental bias stems from the structure of the search process: decision makers predominantly build up the feasible portfolio of projects (i.e., forward search). We discuss recommendations that could help decision makers reduce this bias and make better project selection decisions.