Construction process performance variability: Focus on labour productivity

Lema, Ninatubu Mbora; Price, Andrew D.F.

doi:10.1080/09613219608727554

Cited by 11 publications

(8 citation statements)

References 19 publications

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“…Making use of those factors that positively affect productivity and eliminating or controlling factors that have a negative effect, will ultimately improve productivity. If all factors influencing productivity are known, it will also be possible to forecast productivity (Lema 1995). Olomolaiye et al (1998) indicated that influencing factors are rarely constant and may vary from country to country, from project to project, and even on the same project depending on the circumstances, anything influencing them can subsequently affect productivity.…”

Section: Productivity Factorsmentioning

confidence: 99%

A Survey of the Factors Affecting the Productivity of Construction Projects in Iran

Ghoddousi

Hosseini

2012

Technological and Economic Development of Economy

143

127

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The intense competition between the Iranian construction companies has led them to take all appropriate measures to decrease the costs as much as possible. Hence, due to the pivotal role of human resources in construction projects cost, a major part of Iranian construction companies seek their profitability and survival in maximizing the productivity of their operatives. Because of the widespread belief among contractors about the low productivity of daily workers and operatives with basic salary, they commit a major part of their projects activities to sub-contractors. Deployment of sub-contractors by construction firms has become largely conventional in country's construction projects. The aims of this paper is defined as determining the factors and grounds affecting sub-contractors productivity and evaluate their overall negative side effects on project productivity via a structured questionnaire. A total of 31 factors selected and were divided into 7 broad categories. The perceptions of companies managers were asked about the level of effect brought about by the mentioned factors and groups upon productivity on a time based criterion. The analysis indicated that the most important grounds affecting sub-contractors productivity in descending order include: Materials/Tools, Construction technology and method, Planning, Supervision system, Reworks, Weather, and Jobsite condition. Project managers should focus on the identified major grounds and relevant factors in order to improve productivity as long as they commit construction activities to sub-contractors.

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Section: Productivity Factorsmentioning

confidence: 99%

A Survey of the Factors Affecting the Productivity of Construction Projects in Iran

Ghoddousi

Hosseini

2012

Technological and Economic Development of Economy

143

127

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“…Regardless of the trends in productivity, some relatively recent research works highlight the elements of unreliability in labour productivity raw data and uncertainties in the methods used for its interpretations (US Census, 2000; Eddy and Peerapong, 2003). Also, it is commonly acknowledged that there is considerable variability in labour productivity rates (Lema and Price, 1996) and also that productivity is considerably susceptible to parameters such as overall task durations, disruptions and length of the work day, all in addition to weather and crew related parameters. Despite the fact that labour cost represents a sizeable component of the overall cost estimate of a project, there is much inaccuracy in its estimation.…”

Section: Introductionmentioning

confidence: 99%

Significance ranking of parameters impacting construction labour productivity

Moselhi

Khan

2012

Construction Innovation

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PurposeConstruction labour productivity is often influenced by variations in work conditions and management effectiveness. It is substantially important to understand the nature and extent to which individual parameters affect productivity. The purpose of this paper is to focus on providing insight on parameters that affect daily job‐site labour productivity by investigating their relative significance and influence on work output.Design/methodology/approachThe methodology is based on the illustration and use of three different data analysis techniques to rank parameters that affect a certain process. These techniques include Fuzzy Subtractive Clustering, Neural Network Modelling and Stepwise Variable Selection Procedure. The first one belongs to inferential statistics, while the other two are artificial intelligence based techniques. The collection of field information, spanning over a time period of ten months, comprised of daily real time observations of job‐site operations, work progress information collected from project managers and supervisors by using customized forms, and daily weather condition recorded through internet sources. Nine parameters are considered in the study presented in this paper. The data on these parameters is examined and their relative influence and contribution in productivity estimates are assessed. The approach was to consider a limited set of parameters relating to daily job‐site productivity. The methodology presented in this paper provides insight on the relative impact of parameters, affecting labour productivity on short term or daily basis. The results based on each of the three methods are analyzed and transformed into a final ranking of parameters.FindingsThe three most important parameters are identified in the same order by the fuzzy logic and neural networks methods. Regression analysis, however, provided somewhat different results.Originality/valueThis research investigates the contribution of a set of parameters towards the variations in daily job‐site labour productivity. For practitioners such as site engineers, this is of practical importance for making daily work plans. On the other hand, the structured approach presented to perform significance ranking of parameters relevant to an engineering process, may also be of interest to other researchers and practitioners.

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“…It is important to set what factors influence construction productivity positively or negatively (Enshassi et al, 2007). If factors significantly affecting construction productivity are recognised, it will also be feasible to forecast productivity (Lema & Samson, 1995). In a survey carried out in the United States, material availability, tool availability, rework, overcrowded work areas and inspection delays were identified as major factors influencing productivity (Borcherding & Garner, 1981).…”

Section: Literature Reviewmentioning

confidence: 99%

Assessment of Construction Productivity in the Context of Khulna City of Bangladesh

Rakib¹,

Hasan²,

Howlader³

et al. 2021

JTMB

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This paper examines the current state of construction productivity in Khulna, Bangladeshand major factors that influence the productivity. A questionnaire survey was distributed to various stakeholders and construction projects in Khulna city. Ten projects in Khulna were selected for productivity assessment and a total of 100 respondents participated for ranking the influencing factors.The data were then used to calculate the productivity, and relative important index which enabled the factors to be ranked.Factors influencing the construction productivity were analyzed using an RII method.The average productivity of formwork, concrete work, brickwork and plastering work in Khulna construction industry is 3.40 sqft/hr, 4.98 cft/hr, 1.82 cft/hr and 8.16 sqft/hr respectively.Analysis of thesefactors showed that the top five ranked factors affectingconstruction productivity are labor supervision, skilled labor, availability of materials, availability of equipment’s and scheduling of work.Therefore, focus should be targetedon these factors to make the construction firms profitable as well as improving the progress in construction works.

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Construction process performance variability: Focus on labour productivity

Cited by 11 publications

References 19 publications

A Survey of the Factors Affecting the Productivity of Construction Projects in Iran

A Survey of the Factors Affecting the Productivity of Construction Projects in Iran

Significance ranking of parameters impacting construction labour productivity

Assessment of Construction Productivity in the Context of Khulna City of Bangladesh

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