Journal of Construction Engineering and Management

Residual value is a largely unknown element within the cost calculations for construction equipment that equipment managers are preparing. Traditional estimation methods fall short of capturing its actual nature over time in detail. In this paper we consider the current state of knowledge on residual value and on other cost elements for used heavy construction equipment as implemented in a spreadsheet tool for owning and operating cost calculation. The potential influence of the factor residual value on the total owning costs, and ultimately on total hourly rates, is examined for several different types of heavy equipment. Representative examples of cost calculations are used to perform a sensitivity analysis. Intuitive contour diagrams of the total hourly cost are introduced. The need for an extended examination of residual value of construction equipment is demonstrated using statistical tests. Residual value is found to have a statistically significant contribution to the total hourly cost.

Though the progress of construction projects is most often used as a critical index for effective project management, the method, structure, data, and accuracy of detailed progress measurement may vary depending on specific characteristics of a project. This situation can lead to misinterpretation of the project status, especially under a multiproject management environment. It is also a daunting task for the inexperienced engineers to formulate and monitor the project-specific work packages. At the same time, maintaining very detailed and highly accurate progress information requires excessive managerial efforts. In order to address this issue, this study proposes the concept of standard progress measurement package. Issues for standardization of the work breakdown structure that can embody distinct characteristics of different construction projects are investigated. The proposed methodology facilitates automated formulating of work packages by using a historical database and also automates the gathering of progress information through the use of standardized methods and tools. A case-study project is evaluated in order to examine the practicability of the proposed system.

This paper details the impacts of overmanning on labor productivity for labor-intensive trades, namely mechanical and sheet metal contractors. Overmanning, as used in the following research, is defined as an increase of the peak number of workers of the same trade over the actual average manpower used throughout the project. The paper begins by reviewing literature on the effects of overmanning on labor productivity. Via a survey to various contractors, data were collected from 54 mechanical and sheet metal projects located across the United States. Various statistical analysis techniques are then performed to determine quantitative relationship between overmanning and labor productivity. These techniques include the stepwise method, T-test, $P$ -value tests, analysis of variance, and multiple regression analysis. The results indicate a 0–41% loss of productivity depending on the level of overmanning and the peak project manpower. Cross-validation is performed to validate the final model. Finally, a case study is provided to demonstrate the application of the model.

The economics of a materials management system is defined by the size of the shipments, the scheduling strategy that allows contractors to handle uncertainty and variability in the supply chain, and the timing of the shipments, which in turn depend on the environment in which the project is taking place. This study presents a simulation-based decision support system to assist contractors in selecting the most economical rebar management system prior to the start of construction by recommending lot sizes (large, small), a scheduling strategy (optimistic, neutral, pessimistic), and buffer sizes (large, medium, small) given the conditions of the project. This model is of benefit to contractors and researchers because it generates the probable cost of inventory of 18 alternative rebar management systems ranging from just in case (JIC) to just in time (JIT) and including different variations in between. It allows contractors to select the alternative with least cost of inventory at the planning stages of a project. The simulation model was tested by using actual data obtained from a trade center project in Istanbul, Turkey. As expected, the test indicated that JIC was the most economical rebar management system in a case study conducted in a developing country, as it generated a savings of 4.8% over JIT.

Construction contractor prequalification (CCPQ) is a crucial decision making process to select capable potential bidders and ensure the success of construction projects. The purpose of CCPQ is to guarantee a contractor’s characteristic to meet the construction project’s requirements, which has been established worldwide as a standard practice. However, existing methods, i.e., marking method, subjective judgment method, etc., for contractor prequalification have been inadequate because it is difficult for decision makers to investigate contractor’s capabilities against inexact, vagueness, and qualitative criteria. The objective of this paper is to propose a fuzzy framework-based fuzzy number theory to solve construction contractor prequalification issues, which include decision criteria analysis, weights assessment, and decision model development. Finally, a case study for a tunnel construction project was used to demonstrate the feasibility of fuzzy approaches.

The key to a successful implementation of a build-operate-transfer (BOT) infrastructure project is in-depth analysis of all aspects related to economic, environmental, social, political, legal, and financial feasibility of the project. For these reasons, the analysis of the project feasibility decision needs a technique to include the qualitative decision factors that have a strong impact on the project. This paper aims to introduce a decomposed evaluation model developed to assess the most common significant decision factors that strongly affect the feasibility of BOT projects. The paper describes the viability decision factors that were identified and screened with the assistance of a group of industry experts. This analysis yielded 21 significant factors that would have a certain impact on the feasibility of any BOT project. These factors were classified into three relative categories forming the structure of the suggested project viability model. This model presents a new approach, based on the analytical hierarchy process technique, to evaluate the relationships between decision factors related to project feasibility determination. The new approach has been validated by information obtained from three case studies of BOT projects. The proposed approach to project feasibility evaluation aims to increase the decision maker’s ability to determine the factors contributing the most to the viability to the BOT project at hand.

The build-operate-transfer (BOT) scheme is being used increasingly by governments in their drive to privatize major public transportation projects. In a BOT scheme, the main objective for the private investors in determining the viability of a BOT project is profit, whereas the main objective for the government is whether the construction of the BOT project will give a positive social welfare to the society. These two objectives are often seen to conflict with each other. In this paper, modeling and analysis of highway pricing and capacity choice of a BOT scheme are provided to illustrate the tradeoff between the two objectives. Regulation is normally imposed by the government to ensure that the BOT project satisfies certain requirements. Five cases of the BOT network design problem are analyzed: (1) BOT without regulation; (2) BOT with positive performance measures; (3) BOT with a maximum toll charge level; (4) BOT with a minimum roadway capacity; and (5) BOT with a maximum toll charge and a minimum roadway capacity. Numerical results using a case study of the intercity expressway in the Pearl River Delta Region in China are provided to examine the various effects of regulation on a BOT project.

Selecting the right equipment for the project is inherently a multifaceted cost and benefit evaluation process that is further compounded by the complexity of today’s building projects and the lack of systematic tools for the consideration of soft factors. This paper presents a detailed application example of a model based on an analytical hierarchy process (AHP) approach. This model was developed to address the difficulties experienced during the multifaceted process. The example illustrates how an AHP-based model helps address the multitude of qualitative, intangible factors, both among the factors themselves and then vis-à-vis costs, by means of a systematic and traceable process. The method enables project managers and their equipment selection teams to exercise their knowledge, intuition, and professional judgment, and at the same time to address the context and specifics of the particular projects under examination. The example should be helpful for construction practitioners dealing with similar equipment selection issues. Researchers may find interest in the implementation of a multiattribute-decision-making method for a typical construction management problem.

Construction contractors often finance projects using bank credit lines that allow contractors to withdraw money up to certain credit limits. Finance-based scheduling provides schedules that ensure that the contractor’s indebtedness at any time during the construction stage does not exceed the credit limit. Generally, constricted credit limits tend to yield prolonged schedules. Provided that credit limits can be adequately relaxed, compressed schedules of compressed-duration activities can be attained. Devising a compressed schedule calls for the incorporation of time-cost trade-off (TCT) analysis to strike a balance between the decreased overhead costs and the increased direct costs of the activities. Since employing TCT analysis usually causes great fluctuations in the daily resource requirements by mixing compressed-duration activities of high resource demand with others of low resource demand, therefore, the need for resource management techniques becomes inevitable to ensure efficient utilization of resources. This note used genetic algorithms to expand finance-based scheduling to devise schedules for relaxed credit limits. A prototype system was developed and coded using VISUAL BASIC, then demonstrated using a five-activity example project. The prototype was validated by comparing the results with those obtained by using the integer programming. Expanding finance-based scheduling to handle the whole spectrum of credit limits helps devise overall-optimized schedules that consider cash, time, cost, and resources.

Central to cost-based competition is the capability to accurately predict the cost of delivering a project. Most literature on cost estimation focuses on specific estimation methods as generic techniques and little attention has been paid to the unique requirements at each project stage. This note attempts to identify the critical factors for effective estimation at various stages of typical construction projects. Drawing from organization control theory and cost estimating literature, this note develops a theoretical framework that identifies the critical factors for effective cost estimation during each project phase of a conventional construction project. The underlying logic is that as a cost estimating effort progresses, both task programmability and output measurability improve. As a result, control effort will shift from input-oriented control to a combination of output and behavior control.

Measuring projects’ cost and schedule risks in an integrated framework using simulation has several modeling challenges that have yet to be addressed by researchers. This paper presents a multilevel network modeling approach that aims to integrate a combination of different networks in one framework, and presents a computer simulation implementation to the cost and time risk assessment network (CTAN). The CTAN is an integrated network that includes uncertainties in the realization of the schedule logic, in activities durations, in project scope, and in cost. The simulation model is a decision support simulation system (DSSS) that currently consists of three modules: the CTAN, the stochastic decision trees, and the stochastic shortest/longest rout network. The CTAN-DSSS may be used in cost and schedule risk assessment. It completely integrates with other DSSS networks and deals with risks associated with cost, time, and scope at equal importance. The DSSS was verified by conducting several tests and validated by its extensive use for both undergraduate and graduate courses in Civil Engineering at the University of Calgary over the last three years.