Search

Problem Definition: Project managers are responsible for setting and then revising projects' goals. As uncertainty related to project performance is resolved, a project manager is tasked with comparing ongoing costs, and potentially achieved scope, to a baseline plan. We question whether project managers can rationally anticipate and track this revision process. Academic/Practical Relevance: In practice, projects often fail to meet their goals and are subject to changes in scope, cost, and scheduled time. We consider the implications of behavioral tendencies and the revision strategy on decisions made and on overall project performance. Methodology: Our stylized model compares a rational project manager to a behavioral one. Specifically, we offer a framework for modeling mental accounting—which includes loss aversion and reference point updating—and narrow framing. We use the model to explore how project-level decisions are made. Results: We show that mental accounting results in insufficient adjustments of project scope and cost during revisions, and prevents abandoning projects even when doing so is optimal. Ultimately, mental accounting and narrow framing decrease projects' actual profits. Managerial Implications: We offer practical prescriptions for mitigating harmful effects of loss aversion, reference-point updating, and narrow framing. Beyond training, hiring less loss averse project managers, and practicing scenario planning, we show that reviewing a project using a cost milestone instead of a scope milestone helps maintain the reference cost equal to the budgeted cost, thereby inducing overall better decisions.

We propose a task for eliciting attitudes towards risk that is close to real world risky decisions which typically involve gains and losses. The task consists of accepting or rejecting gambles that provide a gain with probability p and a loss with probability 1 − p. We employ finite mixture models to uncover heterogeneity in risk preferences and find that (i) behavior is heterogeneous, with slightly less than one half of the subjects behaving as expected utility maximizers, (ii) for the others, reference-dependent models perform better than those where subjects derive utility from final outcomes, (iii) models with sign dependent decision weights perform better than those without, and (iv) there is no evidence for loss aversion. The procedure is sufficiently simple so that it can be easily used in field or lab experiments where risk elicitation is not the main experiment.