Abstract
The growth in construction productivity is low and do not continue for a long span of time. The purpose of the present research paper is to analyse the factors affecting on-site construction productivity in Indian construction industry. The tools used for the analysis are reliability analysis to check the consistency of the data, Pearson correlation analysis to mathematically validate the factor analysis, and linear regression analysis to propose a framework of factors affecting construction productivity. The findings of the reliability analysis concludes that the all the factors having a value of more than 0.67, which is considered to be good for the study, and the findings of the study conclude that the most significant 3 attributes grouped in linear regression analysis change in scope (R2), revision in drawings (R15), and response to change orders (R3) having maximum impact over the construction productivity. The research paper attempts to provide an insight and better understanding of the factors affecting on-site construction productivity in India and the ways and means to control and improve construction productivity of construction projects."This paper is the revised version of the paper that has been published in the proceedings of the Creative Construction Conference 2018: Dixit, S., Mandal, S. N., Thanikal, J. V, & Saurabh, K. (2018). Critical Analysis of Factors Affecting the on-site Productivity in Indian Construction Industry, (July), 38–45. https://doi.org/10.3311/CCC2018-006"
Highlights
Each and every project is unique in nature and a number of factors associated with it
3 Research Methodology The methodology adopted for the study is to identify the factors affecting construction productivity form the literature review and the factors have been analyzed and explained in detail in this paper
This paper is the extended version of the previous paper and the statistical test applied to the paper are: Correlation between the factors has been calculated and the factors have been analyzed, and the Kaiser– Meyer–Olkin (KMO)'s table has been prepared to check the applicability of factor analysis, and a regression model has been proposed on the basis of results generated using SPSS 23
Summary
Each and every project is unique in nature and a number of factors associated with it. Li and Liu (2011) proposed an analysis technique to measure capital productivity changes by the evaluation of factors influencing productivity levels in the construction industry. Air terminals (90 % extra cost) and doctor's facilities (62 % extra cost) were cited as the most pessimistic scenarios with different undertakings running from 26 to 43 % extra cost They utilized these figures to infer that Australia is a high cost, low-productivity condition for building infrastructure project. 3 Research Methodology The methodology adopted for the study is to identify the factors affecting construction productivity form the literature review (to be specific from the paper "Critical Analysis of Factors Affecting the on-site Productivity in Indian Construction Industry") and the factors have been analyzed and explained in detail in this paper. This paper is the extended version of the previous paper and the statistical test applied to the paper are: Correlation between the factors has been calculated and the factors have been analyzed, and the KMO's table has been prepared to check the applicability of factor analysis, and a regression model has been proposed on the basis of results generated using SPSS 23
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