Construction Craft Workers’ Perceptions of the Factors Affecting Their Productivity

Dai, Jiukun; Goodrum, Paul M.; Maloney, William F.

doi:10.1061/(asce)0733-9364(2009)135:3(217)

Cited by 171 publications

(111 citation statements)

References 14 publications

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“…The survey firstly addressed the various levels of factors and practices -from micro and some meso parameters at the trade level (craftspeople and foremen) to meso and macro parameters and practices at the PM level (Dai et al 2009) -and their effects on CLP. Two surveys were developed to address parameters relevant to the trade (craftspeople and foremen) and PM (project managers, supervisors, and superintendents) levels.…”

Section: Research Methodology For Identification Of Key Parametersmentioning

confidence: 99%

“…Numerous parameters that influence CLP have been identified (Thomas et al 1990;Oduba 2002;Liberda et al 2003;Dai et al 2009). Incorporating construction practitioners' opinions through surveys ensures that critical parameters are identified for further analysis and modeling.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…Liberda et al (2003) identified 51 factors grouped under three categories -human, external, and management -and carried out an interview survey with 20 PM experts from Alberta, Canada to identify the relative importance of the identified 51 factors and establish the top 15 critical factors. Dai et al (2009) identified 83 factors grouped under eleven categories: supervisor direction, communication, safety, tools and consumables, materials, engineering drawing management, labour, foreman, superintendent, PM, and construction equipment. In the most extensive and detailed existing study of factors influencing CLP, Dai et al (2009) carried out a factor survey based on an identified 83 factors with 1996 craftspeople on 28 U.S. industrial construction projects to identify the top 10 critical factors and the relationship between these factors.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…Dai et al (2009) identified 83 factors grouped under eleven categories: supervisor direction, communication, safety, tools and consumables, materials, engineering drawing management, labour, foreman, superintendent, PM, and construction equipment. In the most extensive and detailed existing study of factors influencing CLP, Dai et al (2009) carried out a factor survey based on an identified 83 factors with 1996 craftspeople on 28 U.S. industrial construction projects to identify the top 10 critical factors and the relationship between these factors. Detailed investigation of differences in perception between the different generations of craft workers (Dai and Goodrum 2012), foremen and craft workers (Dai et al 2007), union and non-union craft workers, and trades (Dai et al 2009) was carried out using the same survey data; significant differences were observed between the compared groups.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

“…In the most extensive and detailed existing study of factors influencing CLP, Dai et al (2009) carried out a factor survey based on an identified 83 factors with 1996 craftspeople on 28 U.S. industrial construction projects to identify the top 10 critical factors and the relationship between these factors. Detailed investigation of differences in perception between the different generations of craft workers (Dai and Goodrum 2012), foremen and craft workers (Dai et al 2007), union and non-union craft workers, and trades (Dai et al 2009) was carried out using the same survey data; significant differences were observed between the compared groups. Jarkas and Bitar (2012) identified 45 factors grouped under four categoriestechnological, human/labour, management, and external-and conducted a questionnaire survey with 157 practitioners from building and civil engineering construction firms in Kuwait; this study established the relative importance of the identified 45 factors and four factor categories.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

See 4 more Smart Citations

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Assefa

Robinson

2014

Can. J. Civ. Eng.

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Parameters (factors and practices) influencing construction labour productivity are multi-faceted and project dependent. A proven measurement scheme and modeling approach to investigate the effect of parameters on construction labour productivity has not yet been developed. This study identifies key parameters influencing labour productivity using contextsensitive surveys that reveal contextual differences between key parameters. The study relies on data collected through 141 surveys administered to project management and trade respondents from six Canadian projects in either of two contexts: building and industrial. Analysis revealed the top parameters influencing labour productivity on building and industrial projects. Consensus between project management and trade level respondents regarding parameters' effects within and between contexts was evaluated using statistical analysis; results indicated some differences in perception. The methodology and findings from this paper are useful for identifying enablers of and barriers to better productivity, developing context-sensitive labour productivity models for use in analysis, and developing productivity improvement strategies.Key words: construction labour productivity, parameters, practices, factors, surveys, context analysis.Résumé : Les paramètres (facteurs et pratiques) influençant la productivité de la main d'oeuvre dans le domaine de la construction ont plusieurs volets et sont fonction du type de projet. Aucune mesure éprouvée ni approche de modélisation n'ont été développées pour examiner l'effet de ces paramètres sur la productivité de la main d'oeuvre dans le domaine de la construction. La présente étude identifie des paramètres clés influençant la productivité de la main d'oeuvre en utilisant des sondages sensibles au contexte qui révèlent les différences contextuelles entre les paramètres clés. L'étude se base sur des données colligées dans 141 sondages envoyés à des répondants en gestion de projet et des métiers dans six projets canadiens dans l'un ou l'autre des contextes suivants : construction en bâtiments et industrielle. L'analyse a révélé les principaux paramètres influençant la productivité de la main d'oeuvre dans les projets industriels et de bâtiments. Le consensus entre les répondants en gestion de projet et des métiers sur les effets des paramètres dans chaque contexte et entre eux a été évalué par analyse statistique. Les résultats montrent certaines différences dans la perception. La méthode et les conclusions du présent article seront utiles pour identifier les catalyseurs et les barrières à une meilleure productivité, développer des modèles de productivité de la main d'oeuvre sensibles au contexte qui seront utilisés dans les analyses et pour développer des stratégies d'amélioration de la productivité. [Traduit par le Rédaction] Mots-clés : productivité de la main d'oeuvre dans le domaine de la construction, paramètres, pratiques, facteurs, sondages, analyse contextuelle.

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Section: Research Methodology For Identification Of Key Parametersmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Identification and comparative analysis of key parameters influencing construction labour productivity in building and industrial projects

Assefa

Robinson

2014

Can. J. Civ. Eng.

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Influence of Trade-Level Coordination Problems on Project Productivity

Hwang

Zhao

Do³

2014

Project Management Journal

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■ This study aims to investigate the influence of coordination problems in glass and metal curtain wall (GMCW) installation on project productivity in Singapore. Trade-level coordination problems in GMCW installation were identified through literature review and included in a survey questionnaire. The survey results indicated that, on average, 66.5 days of rework and 52.5 days of waiting resulted from coordination problems, and that "last-minute changes in design by the client" led to the longest rework and waiting time. Additionally, the rework and waiting time caused by trade-level coordination problems were correlated with the total rework and waiting time. . Modeling and representation of non-value adding activities due to errors and changes in design and construction projects. . The impact of project managers' communication competencies: Validation and extension of a research model for virtuality, satisfaction, and productivity on project teams.

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