In the construction industry, competitive bidding has long been used as a method for contractor selection. Because the true cost of construction is not known until the completion of the project, adverse selection is a major concern. Adverse selection is when the winner of the contract has underestimated the project’s true cost. Thus, the winning contractor will most likely earn negative or at least below normal profits. The winner’s curse is when the winning bidder submits an underestimated bid and is thus cursed by being selected to undertake the project. In the multistage bidding environment, where subcontractors are hired by a general contractor, the winner’s curse may be compounded. In general, contractors suffer from the winner’s curse for a variety of reasons including inaccurate estimates of project cost; new contractors entering the construction market; minimizing losses in case of recession of the construction industry; strong competition within the construction market; differential oppor...

Natural disasters affect the built environment’s infrastructure and disturb the economic sector’s sustainability and welfare. This requires a disaster recovery decision support tool that capitalizes on the redevelopment opportunities to elevate societies to a more-sustainable and less-vulnerable status. As such, this paper presents an agent-based model approach that aims to meet the objectives of stakeholders while decreasing the community’s economic vulnerability. Accordingly, the proposed model adopts a five-step research methodology: (1) implementing a comprehensive economic vulnerability assessment tool; (2) developing the objective functions and learning algorithms of the associated stakeholders; (3) modeling the different attributes and potential strategies of the various stakeholders; (4) creating an interdependent agent based model that simulates the aforementioned information; and (5) interpreting and analyzing the results generated from the developed model. The model is developed and tes...

Disaster recovery requires the participation of the stakeholders to repair the impacted community. Nevertheless, disaster recovery remains understudied within the context of emergency management. Various models have been developed to address disaster recovery. However, those models neither considered the stakeholders’ needs and preferences, nor the vulnerability of the host community. This paper presents a decision-making framework for disaster recovery that uses a bottom-up approach to capture the needs of the impacted residents and decreases the social vulnerability of host communities. The authors developed the following research methodology: (1) use a well-established community specific social vulnerability assessment tool to evaluate the society vulnerability; (2) model the multisector stakeholders through a root-to-grass technique that captures their objectives, strategies, and learning behaviors; (3) simulate the recovery progress of the impacted community using an agent-based simulation toolkit; and (4) interpret the results to provide the decision makers with optimal recovery strategies. The restorations efforts in the aftermath of hurricane Katrina in three coastal counties in Mississippi were used as the problem domain. Accordingly, the proposed model was implemented on a multiagent-based simulation toolkit with geographic information system (GIS) abilities. This research optimized the budget for the State Disaster Recovery Coordinator and the residents’ insurance plans choices. As such, this study provided better social vulnerability indices than the existing conditions currently found in the areas under investigation. Further, this research provided higher disaster recovery rates within the studied host communities. For future work, other vulnerability dimensions will be simultaneously integrated into the model to provide a more accurate depiction of sustainable disaster recovery processes.

The goal of sustainable disaster recovery is to regain the built environment’s functionality while decreasing the vulnerability of the society to future perturbations. This requires a new generation of decision support tools that integrate the host community’s vulnerability assessment while taking into account the stakeholders’ interactions, needs, and preferences. The available disaster recovery research focuses on the optimization and reconstruction of isolated projects rather than taking into account the host community’s overall vulnerability and welfare. Moreover, the available research did not simultaneously take into account the stakeholders’ preferences and needs. To this effect, this paper presents an agent-based model that integrates an environmental vulnerability indicator to better guide the decision-making process of the associated stakeholders. Such an approach will aid urban planners to redevelop societies into a more resilient status. This paper implements a five-step research metho...

The winner’s curse is when the winning bidder submits an underestimated bid and is thus cursed by being selected to undertake the project. This paper uses game theory to identify the degree of the winner’s curse in two common construction bidding environments; namely, single-stage bidding and multi-stage bidding. The objective is to compare the aforementioned two construction bidding environments, and determine how learning from past bidding decisions and experiences can mitigate from the winner’s curse. To this end, the authors (1) presented the symmetric risk neutral Nash equilibrium (SRNNE) as an optimal bid function; (2) developed simulation models for single and multi-stage construction bidding processes; and (3) analyzed the results of the simulation models, which is based on an actual dataset of California Department of Transportation projects. This research demonstrated that the majority of general contractors and sub-contractors suffer from the winner’s curse in both single and multi-stage bidding environments, and that the SRNNE optimal bid function provides the contractors with a tool to avoid the winner’s curse problem and to consequently gain strategic positive profits in both bidding environments. This research should reduce the industry exposure to the effects of the winner’s curse in construction bidding.

The increasing rate and magnitude of natural disasters increase the financial burden on host communities. This paper develops an ex ante disaster insurance profile. To this effect, and utilizing an evolutionary game theory, this paper presents three stakeholders: (1) home owners purchasing disaster insurance policies; (2) insurers offering different insurance policies; and (3) state government offering different ex post disaster recovery compensation plans. The utilization of evolutionary game theory approach allows for maximizing the host community’s total welfare by decreasing their losses depending on their needs and objective functions. The authors created a hypothetical sample of 1,000 home owners accounting for heterogeneous income levels, three insurers each offering three unique insurance plans and two different ex-post governmental disaster compensation plans. The results of the proposed model indicated that: (1) home owners evolved toward insurance plans with the least premium values; (2) insurance plans with the most comprehensive coverage did not survive through the evolutionary process; and (3) the evolutionary stable strategy is an oscillating line of chosen plans and insurers as a result of the stochastic and dynamics nature of the hazardous event. Currently, the authors are integrating the proposed model into a holistic decision making tool incorporating social, environmental, and economic vulnerability indicators. This should allow for a better prediction for the host communities’ disaster response, welfare, and resilience.