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Research Article Open access

Critical Issues in Reforming the Nigerian Construction Industry

Aniekwu Nathaniel Anny, C. Igboanugo Anthony, Onifade Morakinyo Kehinde

Current Journal of Applied Science and Technology · pp. 321–332 · Published 23 Oct 2014

10.9734/BJAST/2015/12617

Abstract

It is the consensus of scholars that the productivity of the construction industry in Nigeria is very low compared with other industries. This situation has been attributed to the fragmented approach commonly adopted in the delivery of construction projects and does not effectively encourage the integration, coordination and communication between participants in the construction industry [1]. Many studies have enunciated this fact and suggested various ways to improve the performance, including the adoption of new construction delivery concepts from other more successful industries. This work therefore seeks to identify the critical elements that will be influential in diffusing these new delivery concepts into the Nigerian construction industry in order to improve their productivity. A detailed literature search and preliminary questionnaire survey were conducted and identified 63 variables that will influence the adoption of new construction delivery concepts in the Nigerian construction industry. The Kendall coefficient of concordance was applied to the responses from 25 experienced construction professionals who ranked the variables in their order of importance and also compute the degree of agreement among these respondents to improve the reliability of the results. A coefficient of concordance (W=0.56) was obtained indicating a good level of agreement. The 46 topmost variables out of 63 were selected and used to design a wieldy 5-step ordinal scale Likert type questionnaire, which was distributed to 459 professionals in the construction industry with a 57% response rate. Principal Component Analysis (PCA), based on a 260 x 46 data matrix, was conducted on the survey responses. PCA was chosen over other models due to the fact that it identifies patterns in data, and expresses the data in a way that highlights their similarities and differences. It also reduces the number of dimensions, without much loss of information. Further analysis using StatistiXL and SPSS software packages using PCA output as input. A correlation matrix of 46 dimensions was obtained from which communalities and Kaiser-Olkin-Mayer (KMO) of the variables was developed. The construction life cycle variable had the highest communalities of 0.752 and a meritorious KMO value of 0.840 for the entire variables, thus justifying the adequacy of the sample. The eigen-values obtained for the variables ranged between + or- 0.001 and + or – 0.499, indicating that the variables had more characteristics of relating with others and were clearly correlated. The Varimax rotation grouped the 46 variables into 10 clusters based on their similarities. Cluster 7 which was creatively labeled Regulatory Environment housed the highest number of variables with above average factor loading between 0.09 to 0.0.657. The severity index (SI) analysis of the data matrix presented Delayed Remuneration, a variable under Regulatory Environment, as the most influential variable with SI of 4.396. The work identified that the focus of any ameliorative measures should be on Regulatory environment, which should aim at building credible Institutions and Infrastructure. A policy framework for diffusing innovations and new construction delivery systems will be a good extension to this work.

Coefficient of concordance correlation matrix communalities new construction delivery concept eigen-values variable clusters regulatory environment.

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