A Construction Subcontractor Selection Model

In today’s construction market, subcontractors execute significant portions of construction work. Subcontractors lessen resource requirements faced by general contractors and provide specialized expertise to construction projects. The reliance of general contractors on subcontractors to execute major portions of construction work makes the success of construction projects highly susceptible to the performance of these subcontracting organizations. As a result, subcontractors' selection decisions are of crucial importance to general contractors bearing in mind that such decisions are exercised by general contractors multiple times in every single project. Existing models of subcontractors' selection do not result in one holistic view for subcontractor evaluation. This paper contributes a Data Envelopment Analysis (DEA) model to guide general contractors in their subcontractor selection decisions. The proposed DEA approach addresses the limitation associated with existing models and results in one holistic view for subcontractor evaluation

Envelopment methodology to measure and compare subcontractor productivity at the firm level

This paper describes a conceptual approach to measure and compare productivity of resource utilization at the firm level, adapting a set of techniques known as Data Envelopment Analysis (DEA). Within this approach, the paper addresses the issues of multiple inputs and multiple outputs of a construction firm, level of detail for data collection, and the required transformations to correct for differences among projects. In particular, we focus on the resource management of subcontractors. Subcontractors manage multiple, concurrent projects and must allocate limited resources across these projects. Interaction between projects and resource allocation creates non-linear effects, and therefore the productivity of the firm is not simply the productivity of its projects. The proposed measurement methodology will allow assessment of the impact of different management policies (including many of those proposed by lean construction researchers) on firm performance. It is hoped that this novel approach to productivity measurement will help subcontractors identify efficient practices and superior management policies, and will promote adoption of these policies.<br /

An Empirical Study Relating Construction Firm Performance and IT Utilization

This paper examines the impact of information technology (IT) utilization on construction firm performance. Based on empirical data collected from 74 US construction firms, the analyses provide evidence that IT has a positive impact on overall firm performance, schedule performance, and cost performance. Firm performance is a composite score of several metrics of performance: schedule performance, cost performance, customer satisfaction, safety performance, and profit. No relationship is found between IT utilization and customer satisfaction, safety, or profit, although this may be due to limitations of the study given strong correlations between IT utilization and cost and schedule performnance. The empirical evidence of positive association between performance and IT use provided by this research is significant to both construction practice and research literature. This evidence should encourage firms to adopt and invest in IT tools

Safety Management in the Jordanian Construction Industry

The Jordanian society and economy have suffered human and financial losses as a result of the poor safety record in the construction industry. The purpose of this study is to examine safety management in the Jordanian construction industry. The study collects data from 70 general contractors, who are involved in all types of construction. Collected data include information regarding organizational safety policy, safety training, safety meetings, safety equipment, safety inspections, safety incentives and penalties, workers’ attitude towards safety, labor turnover rates and compliance with safety legislation. The study reveals several factors of poor safety management. Among these are lack of safety training, occasional safety meetings, occasional safety inspections, unavailability of safety protection measures, hesitance of workers to use safety equipment, high labor turnover rates and non-compliance with safety legislation. The paper concludes by providing a set of recommendations to contractors and governmental bodies to improve safety performance

Framework for Managing the Traffic Impacts of Building Construction Projects

Major building construction projects are important to the economic development of urban areas. However, such projects have negative impacts on their surroundings, particularly on traffic. This paper presents a framework for mitigating the traffic impacts of building construction projects in urban areas. The proposed framework consists of two stages: identification of the logistical construction requirements and development of an impact mitigation plan to control the negative effects of construction traffic on the road network and the surrounding community. The adopted methodology includes (1) a review of the available construction traffic management plans for twenty large building projects worldwide, (2) site visits to seven large building construction projects in urban areas and (3) multidisciplinary focus group sessions to extract knowledge and synthesise the proposed framework for managing the traffic impacts of building construction projects. The suggested framework provides systematic guidance for construction planners and site managers in developing a traffic management and impact mitigation plan for building construction projects. This framework could also help construction planners and site managers to better plan and manage construction activities to minimise the impact on the surrounding roads and minimise unnecessary delays by organising timely movement of resources to and from the construction site

Understanding Key Bidding Factors Considered by Top Jordanian Contractors

One of the most crucial decisions that is regularly exercised by construction contractors is to determine whether to bid or not to bid on a certain project. The purpose of this paper is to understand key factors that are considered by top Jordanian contractors in their bid/no-bid decision making. Previous research in the Jordanian construction market reported the importance weights of 53 bid/no-bid factors (El-Mashaleh, 2013). Based on that work, this paper discusses the top bidding factors and compares them with international related work. Additionally, the paper examines the reliability of El-Mashaleh’s (2013) study based on Cronbach's alpha reliability test. Furthermore, the paper tests the degree of consensus among the respondents of El-Mashaleh’s (2013) work regarding the ranking of the 53 bid/no-bid decision factors based on Kendall's coefficient of concordance. Finally, analysis of variance (ANOVA) is conducted to test statistical significant differences in the importance weights of the 53 bidding factors between public and private bidders. Cronbach's alpha reliability test proves that the adopted scale of measurement for the importance of the bid/no-bid factors has excellent internal consistency reliability. Kendall's coefficient of concordance reveals a significant degree of consensus among the respondents regarding the ranking of the bid/no-bid decision factors. Analysis of variance (ANOVA) indicates statistical significant differences in importance weights between public and private bidders for 6 factors out of the 53 factors considered

A review of application of multi-criteria decision making methods in construction

Construction is an area of study wherein making decisions adequately can mean the difference between success and failure. Moreover, most of the activities belonging to this sector involve taking into account a large number of conflicting aspects, which hinders their management as a whole. Multi-criteria decision making analysis arose to model complex problems like these. This paper reviews the application of 22 different methods belonging to this discipline in various areas of the construction industry clustered in 11 categories. The most significant methods are briefly discussed, pointing out their principal strengths and limitations. Furthermore, the data gathered while performing the paper are statistically analysed to identify different trends concerning the use of these techniques. The review shows their usefulness in characterizing very different decision making environments, highlighting the reliability acquired by the most pragmatic and widespread methods and the emergent tendency to use some of them in combination

Automated trade-off between time and cost in planning repetitive construction projects

An automated model is developed to support the optimization of the planning and scheduling of repetitive construction projects. The model provides the capability of optimizing two important objectives commonly sought in scheduling repetitive construction projects: minimizing project duration; and minimizing project cost. The model performs this multi-objective optimization using a genetic algorithm approach. The output of the model is a set of optimal solutions that represent the trade-off between time and cost in planning repetitive construction projects. Furthermore, the model can be utilized to find a single scheduling solution that provides the minimum overall project cost by simply adding project indirect cost to the obtained project direct cost for each of the obtained scheduling solutions on the Pareto optimal curve. Other important time-related costs are also considered in the model including: early completion incentives, late completion penalties and lane rental costs. Providing the planners of repetitive construction projects with an automated set of optimal time-cost trade-off solutions should contribute to cost-effective and speedy delivery of this type of construction project. An application example is analysed to illustrate the use of the model and demonstrate its capabilities in generating optimal trade-off solutions between minimizing the project time and cost for repetitive construction projects.Repetitive construction, scheduling, genetic algorithms, optimization, resource utilization,