Journal of Construction Engineering and Management

Infrastructure projects such as the construction of expressways are often distributed over different regions and must therefore be divided into several tendering packages. The public agencies that administrate such projects manage project packages that must be integrated. All project packages may involve similar work. However, they are carried out by different contractors each with their own scheduling practices. Standardization provides a foundation for more efficient and effective schedule integration, but cannot easily be enforced without objections from contractors. This paper presents a three-stage standardization implementation framework using modularization. A set of network modules that involve normal, repetitive, cyclic, and merging activities was developed for expressway projects. Two computer systems were developed to help contractors use these modules to create schedules, and to help the owner review schedules submitted by contractors. Experiments and a survey were also carried out to validate the proposed framework, demonstrating a significant amount of time saving and errors reduced by using network modules.

Construction scheduling is the process of devising schemes for sequencing activities. A realistic schedule fulfills the real concerns of users, thus minimizing the chances of schedule failure. The minimization of total project duration has been the concept underlying critical-path method/program evaluation and review technique (CPM/PERT) schedules. Subsequently, techniques including resource management and time-cost trade-off analysis were developed to customize CPM/PERT schedules in order to fulfill users’ concerns regarding project resources, cost, and time. However, financing construction activities throughout the course of the project is another crucial concern that must be properly treated otherwise, nonrealistic schedules are to be anticipated. Unless contractors manage to procure adequate cash to keep construction work running according to schedule, the pace of work will definitely be relaxed. Therefore, always keeping scheduled activities in balance with available cash is a potential contribution to producing realistic schedules. This paper introduces an integer-programming finance-based scheduling method to produce financially feasible schedules that balance the financing requirements of activities at any period with the cash available during that same period. The proposed method offers twofold benefits of minimizing total project duration and fulfilling finance availability constraints.

This study presents a new methodology for evaluating at-completion project performance status. This new procedure uses the concept of stochastic S curves (SS curves) to determine forecasted project estimates as an alternative to using deterministic S curves and traditional forecasting methods. A simulation approach is used for generating the stochastic S curves, and it is based on the defined variability in duration and cost of the individual activities within the process. Stochastic S curves provide probability distributions for the budget and time values required to complete the project at every selected point of intermediate completion. Final project performance is determined by comparing the planned budget and project duration, with the expected forecasted final cost and elapsed time, respectively. The SS-curve methodology permits objective evaluation of project performance without the limitations inherent in a deterministic approach. The probabilistic characteristics of this approach enable users to more accurately determine at-completion cost and duration variations and evaluate the performance improvement of proposed corrective actions.

Highway project durations that are longer than necessary delay the delivery of benefits to road users. Budget constraints often preclude the use of additional funds to shorten total project duration. Therefore, state highway agencies seek ways to decrease construction project durations without increasing costs. Research has recommended formal constructibility reviews as an effective approach to meeting this goal. Formalized constructibility reviews have been effective in isolated cases but only about one-quarter of state highway agencies currently have a formal constructibility review program. An inadequate understanding of implementation issues, including the effective use of resources, is a potential cause. The effects of constructibility reviews on the design phase, construction phase, and project durations are modeled and analyzed. Results illustrate and explain how intermediate-sized constructibility reviews reduce project durations more than very large or small reviews and the potential impacts of a design-build approach on constructibility review effectiveness.

Life-cycle assessment (LCA) is a technique that is used worldwide by clients and their design team to assess the impact of their projects on the environment. The main advantage of LCA is in supporting decision making with quantitative data. LCA inventories can be either fully developed or streamlined. Fully developed LCAs are time-consuming and costly to prepare. Streamlined LCAs can be used as an effective decision-making tool when considering environmental performance during the design process, but with a loss of inventory completeness. Acknowledging the advantages and disadvantages of both types of LCA, this paper proposes a hybrid LCA method that uses input-output data to fill in those gaps routinely left in conventional LCA inventories. The developed hybrid LCA method is demonstrated using a life-cycle energy study of eight different road designs, including vehicle manufacture, maintenance, replacement, and operation. It was found that the road construction process was initially the most important, but in the long run the manufacture, use, and maintenance of vehicles using the road (which are an inevitable consequence of road construction) became paramount.

Hydraulically actuated construction equipment is rapidly being retrofitted with robotic control capabilities by several major manufacturers. However, position control errors caused by several factors are significant in these types of construction equipment. Errors are amplified if the manipulator and its operator must measure and locate objects in the equipment’s fixed reference frame. Both mechanistic and statistical approaches to correcting position errors are possible. A statistical approach is reported here that is validated based on experiments with a computer-controlled large-scale manipulator (LSM). The LSM is sufficiently representative of several types of construction equipment to be able to serve as a general test bed. In the regression analysis, three factors which are measurable in real time: distance, hydraulic pressure, and payload, were varied to determine their influence on position errors in the LSM. It was shown that with an integrated multivariable regression model, about 30% of the mean positioning error of the LSM can be reduced without the use of fixed external reference systems. The model can be implemented as simple, real-time regression equations.

Bidding for international construction projects is a critical decision for companies that aim to position themselves in the global construction market. Determination of attractive projects and markets where the competitive advantage of a company is high requires extensive environmental scanning, forecasting, and learning from the experience of competitors in international markets. In this paper, a neuronet model has been developed as a decision support tool that can classify international projects with respect to attractiveness and competitiveness based on the experiences of Turkish contractors in overseas markets. The model can be used to guide decision makers on which type of data should be collected during international business development and further help them to prepare priority lists during strategic planning. Information derived from the model demonstrates that the most important factors that increase attractiveness of an international project are availability of funds, market volume, economic prosperity, contract type, and country risk rating. Similarly, level of competition, attitude of host government, existence of strict quality requirements, country risk rating, and cultural/religious similarities are the most important factors that affect competitiveness of Turkish contractors in international markets.

Mandatory high penalty conditional bond in public works features the current U.S. construction contract bonding system, which is unique to the low penalty unconditional bond, a more popular choice on the international market. The diversity of construction contract bonding practices puzzles many transitional economies in their globalization processes, when they are to establish or reform their construction contract bonding system. Based on the research into surety bonding mechanisms, this paper illustrates that the penalty requirement is a controlling factor, and that only high penalty conditional bond and low penalty unconditional bond can bring a state of equilibrium to the market. The conditional bond is fairer, and a high penalty conditional bond is a more functional choice than the low penalty unconditional bond. However, lack of enough demand and experienced sureties hampers the application of high penalty condition bonds. Being the nominal owner of public works, the government can always save its money from construction contract bonding system and start up the demands. Therefore, a mandatory surety bonding system in public works with a high penalty requirement should be a good public policy choice for the government.

Design-build (DB) and design-bid-build (DBB) are two principal project delivery systems used in many countries. This paper reports on models constructed to predict performance of DB and DBB projects on 11 areas, using project-specific data collected from 87 building projects. The study included collecting, checking, and validating industry data, and the statistical development of multivariate linear regression models for predicting project performance. Robust models are developed to predict construction and delivery speeds of DB and DBB projects. Gross floor area of the project is the most significant factor affecting speed. Besides this, for DBB projects, contractors’ design ability, and adequacy of plant and equipment would ensure speedy completion of the projects. For DB projects, if the contract period is allowed to vary during tender evaluation, this would slow down the project. Robust models to predict turnover and system quality of DB projects are also constructed. A DB contractor’s track record is an important variable. They must have completed past projects to acceptable quality and have ability in financial, health and safety management.

An increasing number of State Highway Agencies (SHAs) are utilizing Incentive/Disincentive (I/D) bidding for highway construction. The I/D bidding concept is designed to shorten the total contract time by giving the contractor an incentive for early completion and a disincentive for late completion of a project. SHAs are then presented with the problem of determining the maximum incentive that may be awarded to the contractor. This maximum incentive amount is affected by construction cost, time, and the incentive/disincentive formula. Many SHAs use a fixed amount or fixed percent of construction cost as a maximum incentive amount. However, overestimation of the maximum incentive amount may waste public money and underestimation will reduce the effectiveness of the incentive. This research offers a quantifying model to determine a reasonable maximum incentive amount and uses projects from the Florida Department of Transportation (FDOT) to illustrate this model that is only suitable for linear I/D. A functional relationship between the construction cost and time duration is developed from the FDOT’s data. The curve with the functional relationship between the construction cost and time duration is then combined with the incentive/disincentive line to determine the optimum maximum days for incentive and incentive amount. Finally, several projects completed by the FDOT will be used to illustrate the validity of this model.

Construction claims are considered by many project participants to be one of the most disruptive and unpleasant events of a project. Construction claims occur for various reasons. There is a need to understand the dynamic nature between construction claims and opportunistic bidding. An analytical model, the Claims Decision Model (CDM), based on “game theory,” was developed to study opportunistic bidding and construction claims. This model explains (1) how people behave during a potential or existing claiming situation, (2) how different claiming situations are related to opportunistic bidding behavior, and (3) what situations encourage or discourage opportunistic behavior. The results of this pilot study indicate that the equilibrium solution of a construction claim is to negotiate and settle, which concurs with most of the claim cases in the industry. The possible range of a negotiation settlement is obtained in this paper. The model provides the rationale for recent innovations to manage disputes. The model can also help project owners identify the possibility of opportunistic bidding, and can assist the project participants in analyzing construction claims.

This paper presents a framework for optimizing earthmoving operations using computer simulation and genetic algorithms. It provides a multiobjective optimization tool geared towards selection of near-optimum fleet configurations. The optimization aims at minimizing time and cost of earthmoving operations. The proposed framework considers factors that influence earthmoving operations including equipment availability and project indirect cost. The simulation process, in the proposed methodology, utilizes discrete event simulation and object oriented modeling. The optimization process uses a recently developed genetic algorithm to search for a near-optimum fleet configuration employing Pareto optimality to account for multiobjective optimization. The algorithm considers a set of qualitative and quantitative variables that influence the production of earthmoving operations. The developed framework supports time–cost tradeoff analysis and can assist users in considering what if scenarios with respect to fleet configurations. A numerical example is presented to illustrate a number of practical features of the proposed framework and to demonstrate its capabilities in selecting near-optimum fleet configurations.

Fuzzy project scheduling has interested several researchers in the past two decades; about 20 articles have been written on this issue. Contrary to stochastic project-scheduling approaches that are used by many project schedulers, and even if the axiomatic associated to the theory of probabilities is not always compatible with decision-making situations, fuzzy project-scheduling approaches that are most suited to these situations have been kept in the academic sphere. This paper starts by recalling the differences one can observe between uncertainty and imprecision. Then most of the published research works that have been done in this field are summarized. Finally, a framework for addressing the resource-constrained fuzzy project-scheduling problem is proposed. This framework uses temporal linguistic descriptors, which might become very interesting features to the project-scheduling practitioners.

In general, U.S. industries have witnessed dramatic changes in core processes over the past 25 years. Well understood technological and managerial advances have allowed the manufacturing sector, for example, to steadily increase its productivity and its profit margins. Similar changes are far less well understood in construction. This research examines 200 construction activities for the effect of technology, specifically equipment technology, on their labor productivity from 1976 to 1998. During that time period, changes in equipment technology are measured using a technology index consisting of five technology change factors. Through analysis of variance and regression analyses, it is found that activities experiencing significant changes in equipment technology have witnessed substantially greater long-term improvements in labor productivity than those that have not experienced a change in equipment technology. This research also reveals that changes in (1) energy, (2) control, and (3) functional range are significantly and positively correlated with improvements in labor productivity.

Shoring towers are the common formwork solution for high-clearance construction. Because towers account for a remarkably high percentage of the cost of the constructed concrete element, work input data and related economic aspects of tower erection constitute important information for constructors. This paper presents three case studies of high multitier shoring towers, each representing a different tower type. Tower data, major construction parameters, and work inputs for each case are presented. Findings are compared and discussed, and due conclusions are drawn. Finally, recommendations on measures expected to increase the economy of shoring solutions using multitier towers are offered, and some restrictions on the adoption of work input data are listed.

Project alliancing is a new alternative to traditional project delivery systems, especially in the commercial building sector. The Collaborative Process is a theoretical model of people and systems characteristics that are required to reduce the adversarial nature of most construction projects. Although developed separately, both are responses to the same pressures. Project alliancing was just used successfully to complete the National Museum of Australia. This project was analyzed as a case study to determine the extent to which it could be classified as a “collaborative project.” Five key elements of The Collaborative Process were reviewed and numerous examples from the management of this project were cited that support the theoretical recommendations of this model. In the case of this project, significant added value was delivered to the client and many innovations resulted from the collective work of the parties to the contract. It was concluded that project alliances for commercial buildings offer many advantages over traditional project delivery systems, which are related to increasing the levels of collaboration among a project management team.

Different researchers have tried to determine the factors for a successful project for a long time. Lists of variables have been abounded in the literature, however, no general agreement can be made. The aim of this paper is to develop a conceptual framework on critical success factors (CSFs). Seven major journals in the construction field are chosen to review the previous works on project success. Five major groups of independent variables, namely project-related factors, project procedures, project management actions, human-related factors, and external environment are identified as crucial to project success. Further study on the key performance indicators (KPIs) is needed to identify the causal relationships between CSFs and KPIs. The causal relationships, once identified, will be a useful piece of information to implement a project successfully.