Is Construction Labor Productivity Really Declining?

Macroeconomics data suggest that labor productivity declined significantly in the construction industry during the 1979–1998 period. However, microeconomic studies indicate the contrary. This paper critically examines the construction labor productivity macroeconomic data in the United States from 1979 to 1998 to determine their validity and reliability. Data collection, distribution, manipulation, analysis, and interpretation are reviewed and problems are identified. The paper also presents a comparison of construction and manufacturing labor productivity during this period. The main conclusion of the study is that the raw data used to calculate construction productivity values at the macroeconomic level and their further manipulation and interpretation present so many problems that the results should be deemed unreliable. The uncertainty generated in the process of computing these values is such that it cannot be determined if labor productivity has actually increased, decreased, or remained constant in the construction industry for the 1979–1998 period.     

Quantifying the Impact of Schedule Compression on Labor Productivity for Mechanical and Sheet Metal Contractor

In a typical construction project, a contractor may often find that the time originally allotted to perform the work has been severely reduced. The reduction of time available to complete a project is commonly known throughout the construction industry as schedule compression. Schedule compression negatively impacts labor productivity and consequently becomes a source of dispute between owners and contractors. This paper examines how schedule compression affects construction labor productivity and provides a model quantifying the impact of schedule compression on labor productivity based on data collected from 66 mechanical and 37 sheet metal projects across the United States. The model can be used in a proactive manner to reduce productivity losses by managing the factors affecting productivity under the situation of schedule compression. Another useful application of the model is its use as a litigation avoidance tool after the completion of a project.     

Measuring and Modeling Labor Productivity Using Historical Data

Labor productivity is a fundamental piece of information for estimating and scheduling a construction project. The current practice of labor productivity estimation relies primarily on either published productivity data or an individual’s experience. There is a lack of a systematic approach to measuring and estimating labor productivity. Although historical project data hold important predictive productivity information, the lack of a consistent productivity measurement system and the low quality of historical data may prevent a meaningful analysis of labor productivity. In response to these problems, this paper presents an approach to measuring productivity, collecting historical data, and developing productivity models using historical data. This methodology is applied to model steel drafting and fabrication productivities. First, a consistent labor productivity measurement system was defined for steel drafting and shop fabrication activities. Second, a data acquisition system was developed to collect labor productivity data from past and current projects. Finally, the collected productivity data were used to develop labor productivity models using such techniques as artificial neural network and discrete-event simulation. These productivity models were developed and validated using actual data collected from a steel fabrication company.     

2000 Peurifoy Lecture: Construction Practices in Developing Countries

Many contractors are expanding into global markets. Further, many owners procure construction services to build facilities in developing countries. The construction practices in these countries differ in important respects from practices in industrialized countries. This paper reviews some of the more significant differences in construction practices in developing countries. Five primary factors are discussed: cost of labor, cost of money, technology and methods, infrastructure, and role of the design professional. The hypothesis is presented that the main driving factors affecting construction practices are the cost of labor and the cost of money. These two factors place speed of construction as a secondary objective. Low labor costs lead to construction practices being labor-intensive. There is a distinct absence of construction equipment, especially small lifting devices used for material handling. Additionally, the lack of infrastructure means that many materials commonly purchased in the United States from a vendor are fabricated using on-site labor in developing countries.     

Predicting Industrial Construction Labor Productivity Using Fuzzy Expert Systems

The objective of this technical note is to illustrate the application of fuzzy expert systems to the modeling of a practical problem—that of predicting the labor productivity of two common industrial construction activities: rigging pipe and welding pipe. This note illustrates how to develop and test such a model, given the realistic constraints of subjective assessments, multiple contributing factors, and limitations on data sets. The factors that affect the productivity of each activity are identified, and fuzzy membership functions and expert rules are developed. The models are validated using data collected from an actual construction project. The resulting models are found to have high linguistic prediction accuracies. This note is of relevance to researchers by demonstrating how a fuzzy expert system can be developed and tested. It is of relevance to industry practitioners by illustrating how fuzzy logic and expert systems modeling can be exploited to help them solve real world problems.     

Relationship between Changes in Material Technology and Construction Productivity

There have been substantial changes in both material technology and construction productivity over the past several decades. By analyzing the changes in both material technology and productivity among 100 construction activities from 1977 to 2004, this research examines the strength and types of relationships that exist within these two occurrences. Through analysis of variance (ANOVA) and regression analyses, the researchers found that activities experiencing significant changes in material technology have also experienced substantially greater long-term improvements in both their labor and partial factor productivity. The research did find that a stronger relationship exists between changes in material technology and partial factor productivity than in labor productivity. The research also found that changes in the unit weight of materials had a significant relationship to labor productivity, while changes in installation and modularity had a significant relationship to partial factor productivity. The research findings will help industry practitioners to better understand how they may leverage technology to improve construction productivity, while also helping researchers understand the theoretical relationships between technology and construction productivity.     

Measuring the Productivity of the Construction Industry in China by Using DEA-Based Malmquist Productivity Indices

Data envelopment analysis (DEA) measures the relative efficiency of decision-making units and avoids any functional specification to express production relationship between inputs and outputs. DEA-based Malmquist productivity index (MPI) measures the productivity change over time. In this paper, the MPI is used to measure the productivity changes of Chinese construction industry from 1997 to 2003. The results of analyses indicate that productivity of the Chinese construction industry experienced a continuous improvement from 1997 to 2003 except for a decline from 2001 to 2002. It is found that there are gaps in productivity development level among western, midland, eastern, and northeastern regions in the Chinese construction industry. The DEA-based MPI approach provides a good tool to support setting up policies and strategic decisions for improving the performance of the Chinese construction industry and promoting the sustainable development of the industry between different regions.     

Differences in Perspectives regarding Labor Productivity between Spanish- and English-Speaking Craft Workers

The influx of Hispanic workers helped the U.S. construction industry alleviate its shortage of craft workers in the last decade. In 2009, Hispanics accounted for nearly a quarter (22.5%) of the construction workforce in the United States. However, no research has been conducted to examine how various factors influence Hispanic craft workers’ productivity. This paper analyzes the data from a nationwide survey to obtain craft workers’ perspective on construction productivity. The respondents were categorized as Spanish- or English-speaking workers according to their declared primary language, irrespective of their ethnic background. The findings reveal that Spanish- and English-speaking craft workers generally agreed on the priority of the factors affecting labor productivity. However, Spanish-speaking workers rated factors associated with supervisor direction, safety, and labor more severely than English-speaking craft workers. Meanwhile, English-speaking craft workers perceived factors related to engineering drawing management as being more detrimental to productivity than did Spanish-speaking craft workers. Specifically, in comparison with English-speaking craft workers, Spanish-speaking craft workers experienced more severe issues with communicating with their supervisors, pay and monetary bonus for good performance, and lack of training on safety, health, and skills. These findings should be valuable for project management to effectively improve labor productivity of their Spanish-speaking craft workforce.     

The interaction of job autonomy and conflict with supervisor in China and the United States: A qualitative and quantitative comparison.

We examined employees' conflict with their supervisors in cross-cultural work settings. Both qualitative and quantitative data were collected from 332 and 302 university employees in the United States and China, respectively. First, the qualitative data revealed that 54% versus 42% of supervisor conflicts were attributable to low job control in the United States and China, respectively. The quantitative data indicated that job autonomy was negatively related to supervisor conflict in the United States but not in China. Second, both quantitative and qualitative data showed that Chinese employees had more supervisor conflict than their U.S. counterparts. Third, both type of data suggested that supervisor conflict was more strongly related to job strains in China than in the United States. Finally, job autonomy played different roles in these two countries. It buffered supervisor conflict—job strain relations in the United States but exaggerated such relations in China. Therefore, our study provided a possible explanation to the inconsistent findings regarding the buffering effect of job autonomy on job stressors. Employees' cultural background may complicate the process. The qualitative data largely supported the quantitative findings and provided detailed information on employees' job stress experience in the cross-cultural context. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Cross-Validation of Short-Term Productivity Forecasting Methodologies

Frequent and regular prediction of productivity is needed to effectively manage construction operations in progress. This need is proven by significant deviations in productivity between estimated values and actual values, and the dynamic and stochastic changes in productivity over time. Five statistical methodologies that are appropriate for contemporaneous time series were cross validated in the present study. Validation was conducted by comparing the performance of forecasting models constructed using the methodologies. Performance was measured by evaluating the residual sum of squares and the correlation coefficients. As a result, univariate time series analysis was found to be the best-performing methodology. The univariate time series model is particularly beneficial in two respects. Using a single series of contemporaneous productivity data in numeric form, it reduces the effort expended in collecting and analyzing data, and improves the objectivity of analysis.     

Impact of Extended Overtime on Construction Labor Productivity

This paper presents an analysis of the impacts of extended duration overtime on construction labor productivity. The results show a decrease in productivity as the number of hours worked per week increase and/or as project duration increases. The research focuses on labor intensive trades such as the electrical and mechanical trades. Overtime in this research is defined as the hours worked beyond the typical 40 h scheduled per week. The paper begins by presenting the effects of overtime and the need for an updated overtime productivity model. Data for the quantitative analysis was collected from 88 projects located across the United States by means of a questionnaire. Various statistical analysis techniques were performed to develop quantitative relationship curves, including multiple regression, P-value tests, and analysis of variance.     

Productivity growth in health-care delivery

OBJECTIVES: The authors compute and compare productivity growth in the health-care sectors for a sample of Organization for Economic Cooperation and Development countries over the period from 1974 to 1989. The authors compute Malmquist productivity indexes, which allow productivity growth to be decomposed into efficiency changes and technical change. These indexes also allow the use of primary quantity data (recently available from the Organization for Economic Cooperation and Development), rather than expenditure data, which the authors argue reduces bias resulting from distorted prices. METHODS: The authors specify two models. The first model focuses on the hospital sector; inputs include physicians and medical care beds, whereas outputs are the "intermediate" type used in hospital efficiency studies, namely, inpatient days and discharges. RESULTS: For the 19 countries with complete data, the authors found little productivity growth based on this model (with the exception of Denmark, with 15.4% cumulated growth, and the United States, with about 5% from 1974 to 1989). The authors did find, however, that the highest productivity levels are found in the United States (Italy and Finland were also on the frontier of technology in the base period, 1974). The second model uses the same inputs as the first (but in per capita terms), but it specifies simple proxies of health outcomes as outputs: life expectancy of women at age 40 and the reciprocal of the infant mortality rate. CONCLUSIONS: For the 10 countries with complete data for this model, the authors found evidence of much more widespread and rapid productivity growth: Denmark's cumulated growth was close to 33%, with the United States close behind. In both these countries, this growth was due solely to technical change over this period.     

Analysis of Factors Influencing Productivity Using Craftsmen Questionnaires: Case Study in a Chilean Construction Company

Improvement of productivity in construction has been a major industry challenge, given its high impact on project results. It has received increased attention from construction researchers promoting different enhancement actions, since analyzing factors affecting labor productivity is an instrumental part in this process. This paper focuses on identifying and understanding the productivity factors affecting projects in a Chilean construction company on the basis of questionnaires administered to both direct workers and midlevel employees. Analysis of the questionnaire results helped to determine organizational and managerial weaknesses and facilitated comparison of the findings with previous productivity studies. The results proved to be useful in developing recommendations for productivity improvements. The main findings indicate that the critical areas affecting construction productivity were related to materials, tools, rework, equipment, truck availability, and the workers’ motivational dynamics. These results are similar to those obtained in previous studies in the United States and in Chile. Salary expectations were found to be the main reason for turnover in the studied company, which was an aspect not mentioned in previous studies. Finally, additional analyses seem to show that some factors affecting productivity are common to construction projects across boundaries, therefore validating data aggregation and the possibility of learning from experiences in different locations and even separated in time of occurrence.     

Long-Term Impact of Equipment Technology on Labor Productivity in the U.S. Construction Industry at the Activity Level

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.     

Impact of Overmanning on Mechanical and Sheet Metal Labor Productivity

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.     

Improved Baseline Productivity Analysis Technique

Previous studies have aimed to develop effective methods to derive baseline productivity (BP) for labor-intensive activities in construction sites. However, there are two different definitions of BPs: one is defined as a performance benchmark of best practice and the other as a standard reflecting a contractor’s normal operating performance. It is necessary to clarify the difference between the two definitions and their corresponding BPs. This research introduces data envelopment analysis (DEA) as a new method for deriving BP and compares DEA with the other four BP deriving methods. DEA is concluded as the best method in terms of objectivity, effectiveness, and consistency to find BP that represents the best performance a contractor can possibly achieve. With the capability of deriving productivities of multi-input and multi-output activities, the proposed DEA has raised the scale of labor productivity from the level of single factor productivity to total factor productivity which will help construction researchers and managers to evaluate performances of interests in a much more effective way.     

Reducing Variability to Improve Performance as a Lean Construction Principle

Variability is common on construction projects and must be managed effectively. New management thinking, like that of lean production, has suggested that better labor and cost performance can be achieved by reducing output variability. Efforts to utilize lean thinking in construction, so far, have generated limited evidence to support this claim. This paper investigates the relationship between variability and project performance to test the notion that reducing output variability will result in improved labor performance. Using productivity data from concrete formwork activities on multiple projects, various measures of output variability are tested against construction performance. It is shown that variability in output is inevitable and that there is little correlation between output variability and project performance, but that variability in labor productivity is closely correlated to project performance. It is concluded that lean improvement initiatives should be redirected to adaptable workforce management capabilities to reduce variability in labor productivity instead of output in order to improve project performance.     

Multiskilled Labor Utilization Strategies in Construction

Construction industry craft divisions in the United States are currently based on narrowly defined skill groupings. The steady demand for improved productivity and the shortage of skilled craft workers call into question this traditionally accepted “single-skilled” strategy. While these craft patterns are prevalent throughout the union and nonunionized sectors of the industry, they are not necessarily responsive to construction sequence or the optimal use of worker skills. Alternative labor utilization strategies may provide increased project performance and may reduce craft shortages through better utilization of the existing workforce. An analysis model is developed in this study to measure the project impact of alternative labor utilization strategies. The model is used to assess four multiskilling strategies on the construction of a $70,000,000 project. Benefits of multiskilled labor utilization strategies were demonstrated including potentially a 5–20% labor cost savings, a 35% reduction in required workforce, a 47% increase in average employment duration, and an increase in earning potential for multiskilled construction workers.     

Attitudes toward Productivity Pay Programs

Impressive results have been achieved by implementing financial incentive programs in construction in several foreign countries and in numerous other industries in the United States. This paper identifies the historical causes for the scarcity of such programs in the U.S. construction industry, highlights current obstacles to their introduction, and recommends steps to avoid or overcome them, so as to open the way to future introduction of incentive programs. The study employs the Delphi technique and concludes that the near absence of pay programs in the construction industry in the U.S. can be attributed to: (1) Tradition and conservatism of the industry; (2) union opposition; and (3) the nature of the work. The panel predicted significant differences between the overall attitudes of the various parties toward productivity pay programs; the contractors and the owners will be supportive, the employees somewhat supportive, the government neutral, and the union opposed.     

Comparison of Contract General Conditions between United States and China

In light of the fact that construction projects are expensive, complex, and time-consuming undertakings, a well-written contract that specifies each participant’s duties and obligations is required. Furthermore, a well-written contract with regard to business practice differences between the United States and China is unquestionably needed by American owners, design firms, and construction companies conducting business in China. In response to this industry need, general conditions of construction contracts commonly used in the United States (AIA-A201) and China (GF-1999-0201) have been analyzed and compared. The findings of this research reveal that the content of subclauses in AIA-A201 and GF-1999-0201 is different in several ways. These differences may have been caused by cultural, historical, geographical, political, and language variations that exist between the American and Chinese construction markets. Understanding these differences could help U.S. companies stay competitive and profitable in China.