Influence of Technology on Labour Productivity in the Construction Industry in Nairobi City County, Kenya
Abstract
The construction industry in Nairobi City County, Kenya, significantly contributes to economic growth, infrastructure development, and job creation. However, rapid urbanisation has exposed inefficiencies such as project delays, resource constraints, and low labour productivity. This study aimed to examine the influence of technology adoption, specifically safety technology, Building Information Modelling (BIM), construction automation, and remote monitoring on labour productivity in the construction sector. Guided by the Theory of Constraints, the study sought to identify how technology alleviates productivity limitations in construction processes. The specific objectives were to establish the influence of safety technology and assess the impact of BIM on labour productivity. The research targeted a population of 2,610 construction professionals in Nairobi, including engineers, architects, quantity surveyors, contractors, technicians, and artisans. A sample size of 261 was selected through simple random sampling. Primary data were collected using semi-structured questionnaires and interview guides. The questionnaires featured closed-ended and Likert-scale questions to gather quantitative data, while interviews provided qualitative insights. The study achieved an 88% response rate (230 responses). Data analysis was conducted using SPSS, employing correlation, regression, and ANOVA techniques. The results revealed a significant positive correlation (r = 0.386, p < 0.05) between technology use and labour productivity. Regression findings showed that technology use accounted for 14.9% of the variance in productivity levels. The study concludes that technology adoption enhances efficiency, safety, and project outcomes in Nairobi’s construction industry. It is recommended that construction firms invest in affordable technologies and capacity building. Policymakers should support technological innovation through training and incentives. Further research should explore the impact of artificial intelligence and digital tools in other regions of Kenya and Sub-Saharan Africa.
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Copyright (c) 2025 David Aganyo Nyangau, Stephen Ondieki, Abednego Oswald Gwaya, PhD, Mathew Winja
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