Journal of Construction Engineering and Management

Contracts are a ubiquitous part of the architecture, engineering, and construction industry. Despite this, they are poorly understood by practitioners and academics. This paper empirically tests a conceptual model of the contract that seeks to improve our understanding of contracts. This model argues that the contract should be viewed as a managerial tool that provides the structure within which we accomplish the project tasks. The choice of the appropriate contract facilitates a process that allows the parties to achieve superior performance. The model views the contract as a multidimensional instrument that addresses three critical questions: (1) what is the structure of the organizational relationship between firms; (2) what is the disposition of risk and reward for involvement in the project; and (3) how will conflicts between firms be resolved? This paper empirically examines the first two dimensions. In order to address these distinct but intertwined questions, theories from Transaction Cost Economics and Agency Theory are brought to bear. The results of the study suggest that the conceptual model explains some of the variation in project performance, and therefore holds promise as a strategic management tool.

Distrust hinders disputing parties and mediators from achieving mediation success. Mediators therefore often use different trust-building tactics to generate some degree of trust in themselves and in the mediation process. This paper reports a study that identified the trust-building tactics used by construction mediators and examined the efficacy of these tactics with respect to their outcomes. Three study stages were designed. With reference to the mediation model of Sloan (1998), trust-building tactics and outcomes were first identified in Stage I. Next, the data were collected from accredited mediators with a questionnaire survey in Stage II. The collected data were then validated via reliability assessments in Stage III. With the use of multiple regression analyses, the efficacy of the trust-building tactics was examined by relating these tactics to their outcomes. The findings of this study suggest that the trust-building tactics used in Step 4 (i.e., explore interests) of Sloan’s (1998) mediation model are influential in developing trust among disputing parties and that they can also act as a time-saving tool in the mediation process. Furthermore, it was found that mediators can earn trust by adopting the trust-building tactics used in Step 3 (i.e., issues and trust) of Sloan’s (1998) model. These tactics can also serve to improve the relationships between the disputing parties. The results show that the trust-building tactics used in the final step (i.e., solutions) of Sloan’s (1998) model seem to have low efficacy in developing trust among disputing parties.

This paper portrays the development of a concession-investment optimization model for optimizing the winning potential of a concession-bid from the prospective promoters' viewpoints by taking into account imprecise investment parameters. A financial performance measure has been developed to quantify bid-winning potential. Fuzzy set theory is embedded into a genetic algorithm to optimize bid-winning prospects of concession schemes under uncertainty. The fuzzy vertex method accomplishes propagation of uncertainty in cash flows arising from imprecision in estimation of investment parameters. Genetic algorithm solves the optimization routine. The developed model yields global near-optimal solution of bid-winning potential with contributing values of concessionary items: concession length, base price, and equity level under uncertain investment environment. A numerical example demonstrates model capabilities. The model results would help promoters devise a profitable, yet competitive, financial proposal.

Municipal street maintenance can be either performed by a local authority or by a private provider through public–private partnership (PPP) or outsourcing. The choice of either alternative requires proof of economic efficiency at the planning phase of these services. The economic model presented in this paper outlines the basis for the comprehensive probabilistic comparison of the economic efficiency of two approaches: (1) self-performance (public sector delivery) and (2) performance by a private provider (PPP delivery). Based on clear system boundaries, the net present values of the two alternatives are addressed, including possible risk costs. The results of the efficiency comparison are then evaluated using the net present value difference axiom and the net present value efficiency axiom. To ensure that the short-term effects of privatizing or outsourcing street maintenance services are not overrated and the long-term economic efficiency is maintained, the analysis must cover at least two long-term periods.

The design-build (DB) method for construction project delivery continues to grow in both the private and public sector; additionally, research has shown that the DB method outperforms the design-bid-build (DBB) method. The Air Force has applied the results of these previous research efforts to its military construction (MILCON) program without performing empirical studies to validate the approach. Therefore, the objective of this study was to compare the performance of the DB delivery method with the traditional DBB approach for the Air Force MILCON program. Data related to 835 (278 DB and 557 DBB) MILCON projects for fiscal years 1996–2006 were subsequently analyzed. The DB method had better performance in three of six metrics with the performance being significantly better for cost growth and the number of modifications per million dollars. The traditional DBB method performed significantly better in terms of total project time. Furthermore, the DB method was best suited for various facility types. This study provides empirical evidence of how the DB method provides an advantage over the traditional DBB method for Air Force MILCON projects.

This paper presents a multiobjective optimization model that provides new and unique capabilities including generating and evaluating optimal/near-optimal construction resource utilization and scheduling plans that simultaneously minimize the time and maximize the profit of construction projects. The computations in the present model are organized in three major modules: (1) a scheduling module that develops practical schedules for construction projects; (2) a profit module that computes the project profit; and (3) a multiobjective module that searches for and identifies optimal/near optimal trade-offs between project time and profit. A large-scale construction project is analyzed to illustrate the use of the model and to demonstrate its capabilities in generating and visualizing optimal trade-offs between construction time and profit.

Given the dynamic nature of construction sites, analysis of construction activities and their related hazards is inadequate for reliable risk assessment if it does not explicitly account for the likelihood of exposure of potential victims to hazardous situations. In traditional risk level calculations for manufacturing industries, the number of victims is factored with the likelihood of an accident and the potential severity, but the victims are simply assumed to be those typically present at the accident location. In construction, exposure cannot be accounted for at a generic metaproject level: it must be assessed at the level of the activities and the physical context in which they are performed. Conceptually, accidents are “loss-of-control events” to which victims are exposed; without exposure, no accident is assumed to occur. A set of algorithms has been developed to demonstrate estimation of the likelihood of exposure of construction workers to loss-of-control events. The algorithms have been implemented in a prototype software application designed to predict fluctuating risk levels in construction projects. The software implements the “construction hazard assessment with spatial and temporal exposure” model for managing safety in construction, which empowers planners at all levels to adjust construction plans to mitigate high levels of risk or to undertake appropriate proactive measures to ensure safety when high risk levels are unavoidable.

This study sought to identify job characteristics associated with burnout in the context of the construction industry and then formulated job redesign as an intervention strategy of burnout. A survey was undertaken to explore the experience of burnout among 403 construction professionals working in the Hong Kong construction industry. The results of the study show that long working hours, role overload, role conflict, role ambiguity, lack of autonomy, and job security are significant job determinants of burnout. Job redesign was formulated based on these findings and implemented in a company. Levels of burnout experienced by the same respondent both before and 1 year after the job redesign demonstrate a significant difference, implying that job redesign does contribute to lower levels of burnout. The importance, ways, and constraints of job redesign as an intervention to manage burnout at organizational levels are discussed. The results of this study should be of direct benefit to policy makers by providing them with a foundation for designing effective organizational interventions to manage burnout and minimize a serious and often hidden cost.

Information technology (IT) has been used to increase automation and integration of information systems on construction projects for over two decades. However, evidence that overall costs have been reduced or project performance has been improved with IT in construction is limited and mostly focused on application specific studies. A comprehensive understanding of the relationship between IT and project performance helps industry practitioners better understand the likely outcomes of implementation of IT application and likewise benefits researchers in improving the effectiveness in their IT development efforts. An opportunity to examine new evidence exists with the emergence of the Construction Industry Institute’s Benchmarking and Metrics database on construction productivity and practices. This article presents an analysis of that data to determine if there is a relationship between labor productivity and level of IT implementation and integration. Data from industrial construction projects are used to measure the relationships between the automation and integration of construction information systems with productivity. Using the independent sample t-test, the relationship was examined between jobsite productivity across four trades (concrete, structural steel, electrical, and piping) and the automation and integration of various work functions on the sampled projects. The results showed that construction labor productivity was positively related to the use of automation and integration on the sampled projects.

In several studies it is widely accepted that human error is the main reason for up to 80% of all incidents and accidents in complex high-risk systems that exist in the aviation, petrochemical, healthcare, construction, mining, and nuclear power industries. The construction industry, greatly impacted by accidents, is accountable for more than 1,000 fatalities in each of the past 14 years. The human factors analysis classification system (HFACS) is a general human error framework originally developed and tested as a tool for investigating and analyzing the human causes of accidents with applications to rail, air, and offshore environments. This paper introduces the concept of HFACS along with the framework of human error awareness training (HEAT) and their potential contribution to the construction industry. Based on the HEAT approach, this paper proposes a new error analysis educational and classification tool for safety within the construction industry. The primary difference between HFACS and HEAT is found in the structure, content, and presentation of the information allowing for higher effectiveness in incident investigation and safety education and training in construction.

Survey results provide a preliminary assessment of the relative contribution of a range of tactical business strategies to innovation performance by firms in the Australian construction industry. Over 1,300 firms were surveyed in 2004, resulting in a response rate of 29%. Respondents were classified as high, medium or low innovators according to an innovation index based on the novelty and impact of their innovations and their adoption of listed technological and organizational advances. The relative significance of 23 business strategies concerning (1) employees; (2) marketing; (3) technology; (4) knowledge; and (5) relationships was examined by determining the extent to which they distinguished high innovators from low innovators. The individual business strategies that most strongly distinguished high innovators were (1) investing in R&D; (2) participating in partnering and alliances on projects; (3) ensuring project learnings are transferred into continuous business processes; (4) monitoring international best practice; and (5) recruiting new graduates. Of the five types of strategies assessed, marketing strategies were the least significant in supporting innovation. The results provide practical guidance to managers in project-based industries wishing to improve their innovation performance.

Risk management is an important part of construction management, yet the risk-based decision support tools available to construction managers fail to adequately address risks relating to cost, schedule, and quality together in a coherent framework. This paper demonstrates the usefulness of the Advanced Programmatic Risk Analysis and Management Model (APRAM) originally developed for the aerospace industry, for managing schedule, cost, and quality risks in the construction industry. The usefulness of APRAM for construction projects is demonstrated by implementing APRAM for an example based on an actual building construction project and comparing the results with other risk analysis techniques. The results show that APRAM simultaneously addresses cost, schedule, and quality risk together in a coherent, probabilistic framework that provides the information needed to support decision making in allocating scarce project resources.

Lean construction has recently attracted considerable attention in the home building industry. Lengthy delivery time and significant waste in the construction process have caused many home builders to seek a more effective production model that will increase process reliability, reduce total lead time, and improve quality. However, although housing construction provides the closest analogy to manufacturing, a high level of variability prevents the direct transplantation of lean paradigm and techniques. In collaboration with a local home builder, a systematic approach based on value stream mapping technique is developed in this research to analyze the current process and to formulate a lean production model. The model has four main features: synchronized first-in, first-out lane-based flow, production leveling at pacemaker, work restructuring, and improved operation reliability. A simulation template is built to verify the model and to assist in the development of interim implementation models. This paper presents data collection and value stream selection, current practice analysis, and specific changes proposed for the lean production model.

A framework is presented for optimizing the construction of decks of bridges using launching girder systems. The framework assists contractors in performing a time-cost trade-off analysis to optimize the use of resources. The proposed framework consists of three main components which interact in a cyclic manner. These components are simulation, optimization, and reporting modules. Processes and tasks of launching girder systems are described in order to illustrate the mechanism of the simulation module which utilizes STROBOSCOPE as a general purpose simulation language. The developments made in the optimization module are extensively detailed. The optimization module uses ant colony optimization and it accounts for seven optimization variables; location of casting yard, time lag, number of casting forms, number of preparation platform, curing method, number of yard reinforcement crews, and number of stressing crews. Two optimization approaches are coded in the optimization module in two algorithms (ant colony multiobjective optimization I and II) to carry out multiobjective optimization. These are function-transformation and modified distance approaches. A numerical example is presented to illustrate the practical use of the developed framework.