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Poor quality in construction often manifests in the need for rework to be performed. Yet, no specific theory exists in the literature to provide practical guidance to mitigate rework. While common conceptualizations of rework abound, they fall short of the strict empirical testing required to develop a “good” theory. Rumsfeld's heuristic suggests that within complex production systems such as construction, there are known knowns, known unknowns, and unknown unknowns. Using this heuristic as a metaphor, we undertake a narrative review of the literature to make sense of what is known, determine the key unsolved problems, and identify issues that research has failed to consider about rework in this article. Our article questions prevailing knowledge and aims to stimulate richer and more in-depth lines of inquiry to make headway toward developing a theory that explains rework causation. The much-needed theory would provide a platform for designing and developing effective strategies for mitigating rework in construction. This article's contributions are twofold as: (1) it identifies unresolved issues stymieing the ability to address rework effectively; and (2) promulgates new avenues of inquiry to create an improved understanding of the rework phenomenon, thus setting the foundation for sparking theoretical development.

Transport projects are regularly subjected to cost misperformance. The contingency set aside to cover any increases in cost due to risk and uncertainty issues is often insufficient. We review approaches that have been used to estimate a cost contingency. We show that some approaches such as reference class forecasting, which underpins the planning fallacy theory, take a biased view to formulate a contingency. Indeed, there is a perception that the risks and uncertainties that form the parts of a cost contingency cannot be accurately assessed using heuristics. The absence of an overarching theory to support the use of heuristics has resulted in them often being downplayed in a project's investment decision-making process. This article fills this void and provides the theoretical backdrop to support the use of heuristics to formulate a cost contingency. We make a clarion call to reconcile the duality of the bias and heuristic approaches, propose a balanced framework for developing a cost contingency, and suggest the use of uplifts to derisk cost estimates is redundant. We hope our advocacy for a balanced approach will stimulate debate and question the legitimacy of uplifts to solely debias cost estimates.

Large-scale infrastructure projects tend to experience variances between estimated and final costs. Governments, in response, have been using statistical methods (including probabilistic approaches) such as reference class forecasting to try and mitigate cost overruns. While helpful in accommodating risk, such statistical methods often fail to account for a project's cost uncertainty. To reduce cost variance under uncertainty, it is necessary to use heuristics when formulating an infrastructure project's cost contingency. This article argues a need to adopt a vision of human nature described as Homo heuristicus (heuristics-using-person). We provide awareness and rationale for developing an “adaptive toolbox” of heuristics for ecologically rational and contextually aligned cost contingency decision-making. However, the selection, recognition, and evaluation heuristics for determining cost uncertainty have yet to be examined. Thus, future research is required to cultivate the heuristics needed to address the uncertainty that surrounds the determination of a cost contingency.