A More Effective Labour Management Model for Construction Projects to Increase Productivity and Enhance Profitability
Dennis Mumo Ndolo1, Diang’a Stephen2, Gwaya Abednego3
1Mr, Dennis Mumo Ndolo, Dept. Construction Management, Jomo Kenyatta University of Agriculture & Technology, Nairobi, Kenya.
2Prof. Stephen Onyango Diang’a, Dept. Construction Management, Jomo Kenyatta University of Agriculture & Technology, Nairobi, Kenya.
3Dr. Abednego Oswald Gwaya, Dept. Construction Management, Jomo Kenyatta University of Agriculture & Technology, Nairobi, Kenya.
Manuscript received on July 02, 2018. | Revised Manuscript received on July 03, 2018. | Manuscript published on July 30, 2018. | PP: 5-11 | Volume-8 Issue-3, September 2018. | Retrieval Number: C3148098318/2018©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Construction industry is labour intensive compared to other sectors with a range of 25-30 %. According to Wibowo (2002), the industry comprises of three major inputs namely labour, equipment and materials. Labour is therefore unpredictable in nature compared to other inputs (materials and equipment) which are affected and determined by the current market rates. Therefore, proper labour management is required all through the construction process; this can be achieved by introduction of effective management models for use in the construction industry. The research sought to develop an affective labour management model which can be used to increase productivity. The research used questionnaires and interviews to seek information from the practicing construction personnel who expressed their views and gave their opinions concerning labour management. The study found out that most practitioners are aware of the labour management models and their contribution in increasing productivity and some admitted that they have not used the models due to their complexity. The study used inferential statistics to generate correlation, which aimed to examine and describe the association and relationship between individual factors and their relationship to labour productivity. All factors affecting productivity were grouped in to five thematic coefficients which were used to create a model. The five coefficients are Labour planning (plan), Training of workforce (train), Motivation of labour (motivate), Mechanization of labour (mech) and availability of raw materials (raw). The model developed is: Productivity = βplan + βtrain + βmotivate + βmech + βraw + βplan: βmech + β0 + ɛi Logistic odds were assigned to each individual coefficient in order to give the model a simpler meaning; the odds generated were as shown below. Productivity = 3.29plan + 1.31train + 0.85motivate + 2.7mech + 0.93raw + (3.29plan: 2.7mech) + constant (intercept)
Keywords: Labour, Labour Management Model, Labour Productivity, Production Efficiency.