Determinants of labor productivity for building projects in Pakistan

Abstract

This study attempts to unveil and prioritize the factors affecting labor productivity in Pakistani construction industry. A triangulation strategy was adopted, comprised of a comprehensive literature review, data collection through a questionnaire survey from contractors, clients and consultants, and Delphi survey. Fortyone labor productivity factors, shortlisted through literature review, were ranked by 315 respondents based on their past experience. The relative importance index was calculated to determine the weightage of each factor. To validate the results, top fifteen factors were further analyzed using a three-round Delphi survey. The most significant labor productivity factors are identified as: shortage of skilled labor, payment delay by owner to contractor, unrealistic scheduling and expectation of labors performance, clarity of technical specification, and delay in wages payment to labor. Shortage of skilled labor remained on top in both the ranking techniques. The study has underlined certain deviations in the ranking of labor productivity factors, attained through the analysis of questionnaire survey data and Delphi analysis. The study's results are envisaged to improve the labor productivity of building projects in Pakistan in terms of the project completion time and cost. The study's findings can be generalized with care in other developing countries having similar work environment.

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“…According to Fox and Skitmore [10] and Low, Abdul-Rahman [11], some of the factors influencing the development of the construction industry are: long-term vision and policy, basic physical and institutional infrastructure, thinking and implementing the best (a best practice and learning culture), financial and human resources, and, techniques assisting high production performance. Similarly, aspects such as time and cost overruns [12,13], quality and associated management of constructed facilities using innovative tools such as six sigma [14], management of larger infrastructure projects such as public-private partnership based endeavors [15], and labor productivity and associated assessments [16][17][18] are some other issues faced by the global construction industry.…”

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Hybrid Artificial Intelligence HFS-RF-PSO Model for Construction Labor Productivity Prediction and Optimization

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