Construction Productivity Improvement: A Study of Human, Management and External Issues

Liberda, Markus; Ruwanpura, Janaka Y.; Jergeas, George

doi:10.1061/40671(2003)5

Cited by 67 publications

(39 citation statements)

References 8 publications

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“…Of the 141 parameters included in the PM survey, respondents identified "use of daily job hazard assessment system" as the top parameter having a positive effect. This finding substantiates the results obtained by Liberda et al (2003) where "safety systems including protective gear requirement" was ranked last out of 53 factors based on negative effect on CLP. The PM survey respondents also identified "presence of many competing projects within the province" as the top parameter having a negative effect.…”

Section: Industrial Contextsupporting

confidence: 81%

“…A total of 169 parameters influencing CLP were first gathered from existing literature related to Alberta and North American construction projects (CII 2006;Liberda et al 2003;Jergeas 2009;Knight and Fayek 2000;Oduba 2002;O'Connor and Huh 2006;AbouRizk et al 2001;Chan et al 2004;Dissanayake et al 2005). The full list of the parameters, presented in Table 1, introduces a number of factors and practices that were not included in previous research works.…”

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%

“…Oduba (2002) identified 57 factors grouped under context and input; the factors were further classed according to project or activity level. 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.…”

Section: Background and Literature Reviewmentioning

confidence: 99%

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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: Industrial Contextsupporting

confidence: 81%

Section: Research Methodology For Identification Of Key Parametersmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

Section: Background and Literature Reviewmentioning

confidence: 99%

See 2 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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“…The construction industry has unique characteristics that differentiate it from other industry sectors [1]. It has order-based production, fixed production times, established locations for operations, non-repetitive tasks, and low productivity compared to other industries [2,3].…”

Section: Introductionmentioning

confidence: 99%

Construction Management Risk System (CMRS) for Construction Management (CM) Firms

2017

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Abstract:After the global financial crisis of 2008, the need for risk management arose because it was necessary to minimize the losses in construction management (CM) firms. This was caused by a decreased amount of orders in the Korean CM market, which intensified order competition between companies. However, research results revealed that risks were not being systematically managed owing to the absence of risk management systems. Thus, it was concluded that it was necessary to develop standard operating systems and implement risk management systems in order to manage risks effectively. Therefore, the purpose of this study was to develop a construction risk management system (CRMS) for systematically managing risks. For this purpose, the field operation managers of CM firms were interviewed and surveyed in order to define risk factors. Upon this, a risk assessment priority analysis was performed. Finally, a risk management system that comprised seven modules and 20 sub-modules and was capable of responding systematically to risks was proposed. Furthermore, the effectiveness of this system was verified through on-site inspection. This system allows early response to risks, accountability verification and immediate response to legal disputes with clients by managing risk records.

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Evaluation of Human Factors Influencing Labor Productivity in Construction Project

Tammy

Medani

Ramli

et al. 2019

Proceedings of AICCE'19

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Construction Productivity Improvement: A Study of Human, Management and External Issues

Cited by 67 publications

References 8 publications

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

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

Construction Management Risk System (CMRS) for Construction Management (CM) Firms

Evaluation of Human Factors Influencing Labor Productivity in Construction Project

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