Application of the Regression Model for Evaluating Factors Affecting Construction Workers’ Labor Productivity in Vietnam
Dinh Tuan Hai1, *, Nguyen Van Tam2
Identifiers and Pagination:Year: 2019
First Page: 353
Last Page: 362
Publisher ID: TOBCTJ-13-353
Article History:Received Date: 04/08/2019
Revision Received Date: 24/10/2019
Acceptance Date: 09/11/2019
Electronic publication date: 31/12/2019
Collection year: 2019
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
In the rapidly-developed construction industry, labor productivity has improved to a great extent, still, it is low compared with many other industries. The enhancement of labor productivity has become important that attracts much attention and focus from researchers in Vietnam and around the world.
This paper focuses on key factors affecting labor productivity of construction sites in Vietnam by introducing a regression model to evaluate the extent of each factor’s impact on the labor productivity of construction workers.
Ten groups of impacting factors were identified as factors relevant to construction worker, factors relevant to site operation and management, factors relevant to motivation, factors relevant to working time, factors relevant to labor working tools, factors relevant to labor working conditions, factors relevant to working safety, factors relevant to project informations, factors relevant to natural environment, and factors relevant to socio-economic conditions.
By referring to research results, Vietnamese construction contractors will be able to come up with workable solutions towards a better performance of construction workers.
On that basis, the productivity of construction firms and the workers will be improved correspondingly.