Decision Bias in Project Selection: Experimental Evidence from the Knapsack Problem

54 Pages Posted: 14 Sep 2019 Last revised: 28 Feb 2023

See all articles by Tom Pape

Tom Pape

Judge Business School, University of Cambridge

Stelios Kavadias

Cambridge Judge Business School

Svenja C. Sommer

HEC Paris - Operations Management and Information Technology

Date Written: Feburary 26, 2023

Abstract

Selecting the most valuable projects given a finite budget constraint is a recurring decision challenge in all organizations. The optimization literature has long recognized the mathematical complexities of this knapsack problem. However, these complexities along with real-world data imperfections, such as how to fully determine the "values" of competing projects, have severely limited the adoption of optimization algorithms. Instead, decision makers employ mental heuristics. We explore the nature of these heuristics experimentally in a computer lab, and find them to be biased towards selecting too many small projects. We attribute this bias to a key structural characteristic of the decision makers' search process. Specifically, while they search for value-maximizing combinations of projects, they consistently keep their solutions within the feasible side of the budget boundary. They rarely generate infeasible solutions during their search, and then consider which projects to drop. We test two common strategies to debias decision makers: a problem framing that subtly nudges participants to search more in the infeasible solution space, and direct advice to participants to do so. We find that only the latter one reduces the small-project bias and improves resource allocation decisions.

Keywords: project selection, behavioural operations, knapsack problem

JEL Classification: A10

Suggested Citation

Pape, Tom and Kavadias, Stylianos and Sommer, Svenja C., Decision Bias in Project Selection: Experimental Evidence from the Knapsack Problem (Feburary 26, 2023). Available at SSRN: https://ssrn.com/abstract=3448676 or http://dx.doi.org/10.2139/ssrn.3448676

Tom Pape (Contact Author)

Judge Business School, University of Cambridge ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom

HOME PAGE: http://https://www.jbs.cam.ac.uk/tompape

Stylianos Kavadias

Cambridge Judge Business School ( email )

Trumpington Street
Cambridge, CB2 1AG
United Kingdom

Svenja C. Sommer

HEC Paris - Operations Management and Information Technology ( email )

1, rue de la Liberation
Jouy en Josas, 78351
France

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