Evolutionary stable strategy for post-disaster insurance : a game theory approach

Natural disasters leave the impacted regions with financial burdens both on the individual and governmental levels. Thus, the goal of the associated stakeholders is to maximize the host communities’ welfare through minimizing their post-disaster financial burdens. Accordingly, this paper attempts to find a post-disaster insurance plans equilibrium so as to mitigate the financial impacts associated with the natural disasters. Utilizing an evolutionary game theory approach, the equilibrium is investigated between three different players including: resident families purchasing insurance plans; insurance companies offering different insurance plans; and the government agency that implements post disaster relief financial plans. The authors determined a set of decision actions as well as utility functions for the aforementioned stakeholders. Moreover, the authors created a hypothetical sample of 1,000 heterogeneous income level resident families, three insurance companies offering three unique and different insurance plans per company and two post disaster financial relief plans to be utilized by the government agency. The proposed model was implemented on NetBeans IDE 7.4 platform using JAVA programming language on the hypothetical case study simulating resident family evolutionary learning process in reaching an equilibrium. The results indicate that: (1) resident families tend to prefer insurance plans with the least premium value and coverage; (2) insurance plans with the most comprehensive coverage received the least demand; and (3) the evolutionary stable strategy path oscillates between chosen plans and insurers over time as a result of the stochastic and dynamics nature of the factors associated with disaster management. Currently, the authors are working to develop the model further to better account for simultaneous actions by all stakeholders (not only resident families), population growth and changes in financial and income standards. Ultimately, this evolutionary game theory model will be tested on real post natural disasters data representing physical damages in coastal Mississippi Counties post Katrina, so as to determine the significant increase in the host community welfare.Non UBCUnreviewedFacultyOthe

Solving the Negative Earnings Dilemma of Multistage Bidding in Public Construction and Infrastructure Projects: A Game Theory-Based Approach

With the tremendous increase in spending on public projects, contractors need to employ efficient and effective bidding strategies to cope with the competitive bidding environment. Usually, general contractors carry a portion of the work and subcontract other parts to eventually submit a holistic joint bid. This bidding setting is referred to as multistage bidding where subcontractors submit their quotations/bids to the general contractor, after which the general contractor submits a final joint bid for the whole project. In a multistage bidding environment, general contractors may be faced with an increase in the probability of negative or below normal profits. Despite previous research efforts for developing bidding models, there is a need for the extension of existing literature to tackle the multistage bidding environment, referred to hereinafter as multistage game (MSG). As such, the goal of this paper is to develop a bidding model for the MSG. The authors followed a multistep research methodology comprised of: (1) defining MSG in terms of game theory; (2) deriving a game-theoretic bid function for general contractors to determine the final joint bid to submit in MSG; and (3) developing a simulation model for MSG, using a data from 2,235 US public infrastructure projects. Results demonstrate that the new bid function gives general contractors a competitive advantage by avoiding the occurrence of negative profits in their part of the project. Also, results show a reduction in the occurrence and magnitude of the negative profits in relation to the final joint bids. This research significantly contributes to the body of knowledge by providing an innovative bid function for MSG. In addition, it offers substantial practical benefits for general contractors by providing a tool that facilitates dealing with the inherent complexity and uncertainties related to actual cost estimation within the MSG decision-making process

Developing a Post-Disaster Insurance Profile using an Evolutionary Game Theory

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\u27s 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\u27 disaster response, welfare, and resilience

Role of Transactional Blockchain in Facilitating Procurement in International Construction Projects

Blockchain is an evolving technological innovation that offers a distributed and secure method to record and share data, such as financial transactions, using cryptographic techniques that guarantee immutability. Due to its many benefits, blockchain has evolved into many sectors including finance and supply chain, among others. However, there is much speculation and ongoing research concerning its integration into the construction sector. Accordingly, the goal of this paper is to investigate the role of blockchain in facilitating procurement in construction projects, with a focus on international projects. This goal is achieved by: (1) studying the applications of blockchain in the construction industry; (2) analyzing case studies implementing blockchain in construction projects; and (3) performing a Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis for adopting blockchain in the construction industry. The SWOT analysis is based on the thorough interrelated analysis of the case studies and surveyed literature, and is intended to provide guidelines on how to capitalize on the advantages of transactional blockchain in construction projects. Ultimately, this research aims to provide a holistic understanding of the applications of blockchain in facilitating procurement in international construction projects

Evolutionary Stable Strategy for Postdisaster Insurance: Game Theory Approach

Mitigation of the financial impacts associated with natural disasters is becoming an urgent objective at both the national and international levels, as the rate and magnitude of natural disasters are continuing to increase. Using an evolutionary game theory approach, this paper aims to find an equilibrium profile of postdisaster insurance plans purchased by resident families and sold by insurance companies, as well as ex-postdisaster relief implemented by a government agency. This dynamic integrated assessment minimizes the total losses for the three aforementioned associated stakeholders, thus maximizing welfare within natural disaster host community systems. To this end, the authors determined a plausible set of actions and utility functions for the associated stakeholders. Also, they created a hypothetical sample of 1,000 resident families accounting for heterogeneous income levels, three insurance companies offering three unique insurance plans per company - each with different premium and coverage - and two different types of government compensation plans for postdisaster damage mitigation. The proposed model was implemented on the NetBeans IDE 7.4 platform using the Java programming language for a hypothetical case study. The results indicate that (1) resident families tend to prefer insurance plans with the lowest premium value and coverage; (2) insurance plans with the most comprehensive coverage experienced the least demand; 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 factors associated with disaster management. Currently, the authors are working to develop the model further to better account for simultaneous actions by all stakeholders (not only resident families), population growth, changes in financial and income standards, integrating input from available natural hazard prediction software systems (e.g., HAZUS-MH), and continuous data. Ultimately, this evolutionary game theory model will be tested on post-Hurricane Katrina data representing real-life physical damage in Hancock County, Mississippi

Understanding the Construction Winner\u27s Curse using Game Theory

The winner\u27s 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\u27s 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\u27s 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\u27s 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\u27s 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\u27s curse in construction bidding

Construction Bidding and the Winner\u27s Curse: Game Theory Approach

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\u27s true cost. Thus, the winning contractor will most likely earn negative or at least below normal profits. The winner\u27s 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\u27s curse may be compounded. In general, contractors suffer from the winner\u27s 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 opportunity costs, which can affect the behavior of contractors; and the intention to win the project and then remedy the losses through change orders, claims, and other mechanisms. Using a game theory approach, this paper aims to analyze - and potentially reduce - industry exposure to the effects of the winner\u27s curse in construction bidding. To this end, the authors identify the degree of the winner\u27s curse in two common construction bidding environments; namely, single-stage bidding and multistage bidding. The objective is to compare the aforementioned two construction bidding environments and determine how learning from past bidding decisions and experiences can mitigate the winner\u27s curse. To this end, and through defining the relationship between the construction bidding and auction theory, the authors utilized a three-step research methodology that involved (1) presenting the symmetric risk neutral Nash equilibrium (SRNNE) as an optimal bid function; (2) developing simulation models for single and multistage construction bidding processes; and (3) analyzing the results of the simulation models, which is based on an actual dataset of projects provided by the California Department of Transportation. This research demonstrated that the majority of general contractors and subcontractors suffer from the winner\u27s curse in both single-stage and multistage bidding environments. Moreover, from a winner\u27s curse perspective, the multistage bidding environment incurs more losses than the single-stage bidding environment. However, through learning from past experiences, the multistage bidding environment provides contractors with a better opportunity to avoid the winner\u27s curse if compared with the single-stage bidding environment. This research should be beneficial for the profession to better understand the bidding decision-making processes. For future work, cooperative game theory can be applied with the integrated project delivery principles to help all associated parties mutually achieve their project objectives