Labor waste in housing construction projects : an empirical study

S. Nassri, S. Talebi, F. Elghaish, K. Koohestani, S. McIlwaine, M.R. Hosseini, M. Poshdar, M. Kagioglou

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Purpose: High-level labor waste is a major challenge in construction projects. This paper aims to identify, quantify and categorize labor waste in the context of Iranian housing construction projects.

Design/methodology/approach: This research uses a case study approach, with empirical data collected through direct observations and semi-structured interviews. Findings: Having triangulated the findings from the literature review and empirical studies, a list of eight types of waste was derived for the thirteen observed laborers in ten case study projects. The empirical studies allowed the labor waste identified from the literature to be verified and refined by considering it in the context of the observed activities, and led to two new types of waste being identified which were not considered in the literature. Findings indicate that nearly 62% of laborers' time is spent on non-value-adding activities. It appeared that “unnecessary movement,” “waiting” and “indirect work” make up the highest labor waste.

Research limitations/implications: This research focuses only on onsite resource flows in a housing construction site. It does not include offsite flows such as material delivery to site.

Originality/value: The findings have provided substantial evidence on type and amount of labor waste and provide a solid basis to stimulate construction actors to participate in reducing labor waste and improving productivity.
Original languageEnglish
Pages (from-to)325-340
Number of pages16
JournalSmart and Sustainable Built Environment
Volume12
Issue number2
DOIs
Publication statusPublished - 20 Feb 2023

Bibliographical note

Publisher Copyright:
© 2021, Emerald Publishing Limited.

Notes

WIP in RD

Keywords

  • Labor productivity
  • Labor waste
  • Lean construction
  • Waste identification
  • Waste measurement
  • Work sampling

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