Category: Research

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ACT2: Time–Cost Tradeoffs from Alternative Contracting Methods

Incentive/disincentive (I/D) and cost-plus-time (A+B) are two of the most widely used alternative contracting methods (ACMs) for accelerating the construction of highway infrastructure improvement projects. However, little is known about the effects of trade-offs in terms of project schedule and cost performance. This study addresses this problem by creating and testing a stochastic decision support model called accelerated alternative contracting cost-time trade-off (ACT2). This model was developed by a second-order polynomial regression analysis and validated by the predicted error sum of square statistic and paired comparison tests. The results of a descriptive trend analysis based on a rich set of high-confidence project data show that I/D is effective at reducing project duration but results in higher cost compared to pure A+B and conventional methods. This cost-time trade-off effect was confirmed by the ACT2model, which determines the level of cost-time trade-off for different ACMs. This study will help state transportation agencies promote more effective application of ACMs by providing data-driven performance benchmarking results when evaluating competing acceleration strategies and techniques.

Structural Equation Modeling for the Determinants of International Infrastructure Investment: Evidence from Chinese Contractors

International infrastructure investment can effectively accelerate infrastructure development in developing countries and thus support their social and economic progress. However, little is known of the factors that may determine the flow of international infrastructure investment to those countries. This study aims to bridge that knowledge gap, first by identifying the determinants of international infrastructure investment, and then by developing a structural equation model to reveal their underlying interrelationships. The structural equation model is applied to country-level data regarding international infrastructure investment with Chinese contractors in 141 countries worldwide over the 9-year period from 2009 to 2017. The results show that three determinants, namely infrastructure quality, labor supply, and investment interdependency, have a positive relationship with a country’s international infrastructure investment inflow. However, another determinant, institutional environment, has a significantly negative impact, which suggests that when making foreign infrastructure investment, Chinese contractors enter countries with a comparatively poor institutional environment with substantial political risks. The results also highlight how much a robust infrastructure development plan can help developing countries avoid the poor-infrastructure trap, a situation in which poor infrastructure quality discourages international infrastructure investment. These research findings may assist international infrastructure investment firms to make informed decisions with regard to financing and managing projects and help policymakers who focus on attracting foreign investment in infrastructure.

“Structural..” was based on a collaboration with Professor Chris Lee and Yunhong Wang, a Ph.D. student from Tsinghua Univ who visited UW last year via the VISIT program.

Journal of Cleaner Production 257, 120527

Abstract: Precast concrete structures (PCs) are widely used in the construction industry to reduce project delivery times and improve quality. On-time delivery of PCs is critical for successful project completion because the processes involving precast concrete are the critical paths in most cases. However, existing models for scheduling PC production are not adequate for use in dynamic environments where construction projects have uncertain construction schedules because of various reasons such as poor labor productivity, inadequate equipment, and poor weather. This research proposes a dynamic model for PC production scheduling by adopting a discrete-time simulation method to respond to due date changes in real time and by using a new dispatching rule that considers the uncertainty of the due dates to minimize tardiness.

Authored by:  Taehoon Kim, Yong-Woo Kim, and Hunhee Cho

Journal of Management in Engineering 36 (3), 04020004

Abstract: This study applies empowerment theory to production planning at the level of frontline managers in a construction project. Using structural equation modeling, we investigate how empowering frontline managers impacts their planning performance. In contrast to prior studies, we find that although psychological empowerment of frontline managers has no direct effect on their production planning reliability or scheduling performance, it has an indirect effect on planning reliability and scheduling performance, as long as the organization supports empowerment structurally during production planning. This implies that a project manager should provide frontline managers at the operational level with proper formal and informal authority over workflow development, shielding, and resource allocation when planning production in order to enhance job performance through psychological empowerment.

Authored by:  Yong-Woo Kim and Byong-Duk Rhee

Production Planning & Control 30 (13), 1064-1071

Abstract:  The research investigates the relationship between the production plan reliability and the project cost performance using project data in the heavy civil construction sector.  The research also investigates the attributes of a make-ready process using statistical analysis.  This study shows that production planning reliability (i.e. Per cent Constraint Removal (PCR) and Per cent Plan Complete (PPC)) and project cost performance (CPI) are significantly correlated in the heavy construction projects.  The findings show that there is a more significant correlation between production planning reliability and project cost performance in project-scaled data than in monthly scaled data.  They suggest that there is a time-lag between when the variance of workflow occurs and when the workflow variance impacts on the project cost performance.

Authored by:  Yong-Woo Kim