Understanding off-site readiness in Indian construction organisations

Abstract

Purpose This paper presents a bespoke model for understanding off-site construction (OSC) readiness among Indian construction organisations. This model presents 17 variables for discussion, the results from which help support OSC strategic decision making. Design/Methodology/Approach Factor analysis was used to investigate the relationship between variables in order to group them into factors. After identifying 26 different variables, these were reduced to 17 using factor analysis and categorised into four groups. Descriptive statistical analysis and factor analysis using SPSS was used to develop a hierarchy of factors that affect OSC readiness in India. These findings were reinforced by five domain experts to support the results. Findings Minimising on-site duration, ensuring cost and time certainty and transportation issues were identified as the three most important factors. Whereas, lack of guidance and scepticism were among the lowest factors affecting the Indian OSC sector. Practical Implications The proffered off-site construction readiness model offers OSC practitioners an ability to assess the OSC readiness of construction organisations in India. This includes the evaluation and benchmarking of processes in both strategic and operational phases; including highlighting areas of concern and scope for further development (to achieve optimal advantage of OSC methods). Originality/Value Originality rests with the use of factor analysis and descriptive statistical analysis to study the influence of different construction-related factors and variables on the OSC sector in India. This impact readiness model is context-specific to the Indian OSC sector – providing a unique insight into the causal factors and dependencies that can affect the adoption and uptake of modern methods of construction in India. Limitations This research is specifically focused on OSC within the Indian construction sector. As such, data collection, propagation and analysis should be constrained to the population context regarding inference, generalisability and repeatability.