The study reported in this paper has been conducted to shed light on the use of life cycle cost analysis (LCCA) in municipal organizations. The major objectives of the study are to identify the sources of data used in LCCA, examine how cities assign values to the main parameters used in their calculations, explore the possible relationships between LCCA and value engineering, investigate the use of LCCA in the bidding and construction phases of a project, investigate the possible ways of improving the efficiency of LCCA, and define the major factors considered in assessing success in LCCA implementation. The findings indicate, among other things, that major sources of data include archives, computerized databases, and data obtained from other cities. The major criteria that cities consider when assessing the rate of success in LCCA implementation include the extent to which LCCA helps to optimize the total cost of owning and operating the physical assets, achieve lower maintenance costs, allow longer useful life, overcome the problem of limited funds, and achieve lower initial costs. For more successful LCCA implementation, cities are demanding formal guidelines that describe the method of utilization, published values for the different parameters used in LCCA, and the development of standard software.
This paper presents an automated tool named the stochastic project financing analysis system (SPFA). The system makes use of critical path method (CPM) schedule data exported from Primavera Project Planner (P3), computes the best-fit probability distribution functions (PDFs) of historical activity durations, assigns to respective activities the probability density functions identified, simulates the schedule network, computes the deterministic and stochastic project cashflows, plots the corresponding cash-flow diagrams, and estimates the best-fitPDFs of overdraft and net profit of a project without user intervention at any time. The SPFA improves the reliability of project cash-flow analysis by effectively dealing with the uncertainties of the activities' durations and costs, increases the usability of the schedule data obtained from commercial CPM software, allows the user to incorporate the contractual terms of payment into the cashflow, and effectively handles the variability of the overdrafts and net profits by finding their best-fitPDF. It is implemented as an easy-to-use computer tool programmed in matrix laboratory (MATLAB). The SPFA allows a financial manager to estimate the extent of cash-flow problems in a specific period by using both deterministic and stochastic modes. Two test cases verify the usability and validity of the system in practice
The construction industry has been criticized as an “old-school” industry, because of being a slow adopter of mobile technologies. This has changed recently. A 2014 survey of 1,048 participants found that 72% of construction practitioners have smartphones, and use smartphone applications for work purposes. While there are thousands of smartphone applications advertised as “construction apps”, the most popular smartphone applications offered by software providers to the construction industry are for field data collection, project management, bidding, building information modeling (BIM), accounting, customer relationship management, and estimating. This paper discusses the current state of smartphone applications available to the construction industry, and examines the apps’ functions. Due to the rapid growth in the smartphone applications market, new applications become available every day for use in different industries. Given the large number of choices, both companies and individuals in the construction industry must beware when selecting and purchasing smartphone applications. The business needs of the potential users and the expectations from the applications must be well identified, and the selection must be made accordingly. Properly selecting and deploying smartphone applications for construction-related tasks is expected to improve communication, enhance workflow with real time information, and increase productivity.
The accurate prediction of the future condition of bridge components is an important part of any bridge management system. Past bridge inspection data along with information on any repair and/or retrofit can provide a baseline for predicting future conditions of bridge components. As expected, such data are subject to a rather large uncertainty, primarily due to the variation in the inspection process. This uncertainty is also caused sometimes by unrecorded repairs and/or replacements conducted on various parts of the bridge. If not properly considered in the bridge data analysis, the uncertainty may result in an erroneous prediction for future bridge conditions. To develop a reasonable estimate for future bridge conditions, this paper discusses two possible methods. In these methods, discrepancies inherent in bridge condition ratings, that may have been due to unrecorded improvement works, are removed to arrive at more consistent estimates for future bridge conditions. In one method, the adjustment in condition ratings is done based on the notion that unless there is evidence of improvement work, the condition rating cannot be larger than previous ratings. In the other method, the duration between consecutive inspections is used as a means to construct deterioration curves. These methods are applied to rating data collected from 2,601 Illinois bridges in the period of 1976–1998. The results obtained by applying the two methods are presented in the form of bridge deterioration models, compared with one another and discussed in the paper.
Joint ventures have been an important research topic over the last few decades primarily because of their importance as a strategic alternative in global competition. Due to the inherent complexities of international joint ventures (IJVs), involving a mixture of different managerial systems, attitudes, and business strategies, such entities are very difficult to manage. In this study, the effect of strategic, organizational, and cultural fit between IJV partners and of interpartner relations on IN performance is examined through a questionnaire survey. IJV performance is measured by means of two constructs: "project performance" and "performance of IJV management." The results point out the significance of the quality of partner relations for a successful IJV operation. Findings of the study also suggest that the level of organizational fit between the partners has a moderate influence on IJV performance. It was observed that strategic fit between IN partners affects interpartner relations extensively, which in turn affects IJV performance. IN partners with compatible technical and managerial skills, financial resources, organizational size, workload, and project experiences are expected to achieve greater IJV success.
This paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.
Researchers have attempted to develop methods that detect collusive bidding. But no method can detect collusion with certainty unless it is based on legal evidence. A method is proposed to detect collusive bidding behaviour that improves the performance of previous methods. It analyses the historical bidding data provided by a construction owner in a two-step approach which is mainly based on a multiple regression model. The first step involves identifying the potential cartel bidders using the residual test and the cost structure stability test developed in earlier work. The second step is the focus of this paper and involves comparing the behaviour of the potential cartel bidders and non-cartel bidders by analysing bid distributions, their cost dispersion, and the differences in their cost structures. After conducting the second step of the study, it was found that the suspected cartel bidders identified in Step 1 behaved in ways to confirm collusion. Also, in an unrelated search, it was found that two of the six potential cartel bidders who were identified in this study had been audited by the public agency for bid fraud, and that another potential cartel bidder had been found guilty by the courts and forbidden from doing business with the public agency.
Computerized quantity take-off and cost-estimating systems have proliferated in the last 4-5 years. Companies that decide to computerize estimating are faced with the problem of making the right selection. Selecting a package first involves the identification of a potential user's needs. Then, a review is made of the packages available and their capabilities and, finally, the selection of a package by matching the potential user's needs with estimating system capabilities. ESSEX, whose conceptual framework is presented in this paper, is a knowledge-based expert system that facilitates the decision to be made by a potential user of estimating software as to what package to acquire. ESSEX uses an expert system shell to manipulate three main files: ‘UserMod’, the interface with the potential user that also develops the user's decision criteria; ‘SysMod’, the interface with the developers that records commercially available systems' characteristics; and ‘MatchMod’, that matches user and system characteristics to reach the most appropriate selections. An objective evaluation of ESSEX and suggestions for further research are made.
Transaction costs occur when a good or service is transferred across a technologically separable interface, and include the costs of drafting, negotiating and enforcing an agreement, and also the costs of governance and bonding to secure commitments. In the complex and high risk environment of a construction project, questionable decisions can be made in the planning and design phase, and disagreements, conflicts, disputes, change orders, and claims can occur in the construction phase. These problems contribute to an increase in transaction costs. Transaction costs at the pre-contract phase of a project are different from the transaction costs at the post-contract phase. However, there is no consensus on a standard definition of transaction costs in construction projects. In this study, a detailed literature review focusing on transaction costs in construction project management is presented. The factors that affect transaction costs are identified and categorized under the headings of the owner’s and contractor’s roles in the transaction, project management efficiency, and the characteristics of the transaction environment.
Although the general consensus is that linear scheduling methods (LSMs) are quite powerful, their use in construction has been very limited. The linkage between the characteristics of scheduling methods and the requirements of the tasks performed by schedulers has been an on-going concern in the construction industry. This study proposes a “task-technology fit” model to understand why LSMs are not being used as extensively as expected. The model aims to determine whether the characteristics of LSM (technology) satisfy the duties and obligations of construction schedulers (tasks). By scrutinizing the task-technology fit in LSM applications, deficiencies can be detected which hinder the wider use of these methods in the industry. A questionnaire survey was administered to measure task-technology fit in LSM applications. The target population included schedulers, project managers, construction managers, and other professionals listed in the directory of the Construction Management Association of America (CMAA). The findings indicate that LSM is effective in repetitive projects and is able to provide a smooth and efficient flow of resources by adjusting activities’ rate of production. In addition, research findings point out that LSM effectively shows activity sequences as well as progress. However, the findings also reveal that LSM is not applicable when reliable resource data are not available. It should also be noted that very few software packages that perform LSM scheduling are commercially available on the market.
Although line‐of‐balance (LOB) scheduling can be superior to bar charts and networks in repetitive‐unit construction, there are indications that its use is not widespread. In this study, the major limitations of the existing LOB methodology are identified and then eliminated by developing a computer program called repetitive unit scheduling system (RUSS). An effective algorithm that facilitates the implementation of LOB scheduling is developed. A tool that handles logical and strategic limitations caused by the particular characteristics of repetitive activities is provided. A learning model is developed and incorporated into LOB calculations. The program is designed to optimize resource allocation by using multiples of the natural rhythm of activities. An optimum crew size that guarantees maximum productivity in an activity is used throughout the LOB calculations to achieve cost‐optimized schedules. Non‐linear and discrete activities are incorporated into the LOB calculations. RUSS displays the LOB diagram of every individual path in the unit network. It is believed that a system such as RUSS will make the LOB method more appealing to contractors of repetitive projects.
Transaction cost economics deals with costs incurred at the pre-contract phase such as the costs of conducting market research, exploring financial opportunities, conducting a feasibility study, organizing a bidding/negotiation and managing design; and with costs incurred in the post-contract phase such as the costs of administering the contract, administering change orders and claims, resolving disputes and managing incentives. Many researchers have investigated the factors that affect project performance over the years, but neglected to consider transaction-related issues. The effects of transaction-related issues on project performance are investigated in this study. Project performance is measured on the basis of completion within budget and on schedule, compliance with quality standards, and satisfaction of the owner. Transaction-related issues include the magnitude of transaction costs, the uncertainty in the transaction environment, and the owner’s and the contractor’s roles in the transaction. Hypotheses are tested by using a structural equation model using data collected from a survey administered to construction owners. The findings indicate that project performance can be stronger if the uncertainty in the transaction environment is minimized, transaction costs are kept low, and owners and contractors are sensitive to transaction-related issues.
Due to the nature of the construction industry, disputes arise frequently. Resolving these disputes through the court system is both a time‐ and cost‐consuming process. The outcome of construction litigation is normally affected by a large number of complex and interrelated factors and therefore is very difficult to predict. Methods to predict the outcome of construction litigation are not available today because this decision carries very big risks. In this study, case‐based reasoning (CBR) is used to predict the outcome of construction litigation tried in Illinois circuit courts. These circuit court cases are organized in 43 input features and 1 output feature. If CBR systems such as the one developed in this study (prediction rate 83%) are available to the parties before they litigate, legal expenses could be avoided, and considerable time could be saved.
The belief that the design–build (D/B) project delivery system does not lend itself to effective quality assurance and control is quite common in construction circles. Total quality consists of: (1) the corporate quality culture; (2) the quality of the project service; and (3) the quality of the constructed facility. This paper describes a model that was developed to measure the total quality of a D/B firm using quality function deployment (QFD). The first part of this model is described elsewhere and measures the effectiveness of the corporate quality culture and the quality of the service when delivering a project by using QFD. The second part of the model is described in this paper. It makes use of eight building quality factors, three building performance factors, and the relationships between building quality and performance factors (obtained from building users/evaluators) and it measures the quality performance of the constructed facility by using QFD. A total quality performance index is generated by combining the quality performance at the corporate, project, and product levels. The total quality performance measurement model described in this paper can be used by D/B firms to benchmark themselves against their competitors or to monitor their own performance. It can also be used by owners to rank D/B firms relative to their total quality performance.
