To read this content please select one of the options below:

Modeling the key barriers to lean construction using interpretive structural modeling

Sorokhaibam Khaba (Department of Management Studies, Indian School of Mines, Dhanbad, India)
Chandan Bhar (Department of Management Studies, Indian School of Mines, Dhanbad, India)

Journal of Modelling in Management

ISSN: 1746-5664

Article publication date: 6 November 2017

1080

Abstract

Purpose

The purpose of this study is to identify and analyze the key barriers to lean implementation in the construction industry using interpretive structural modeling (ISM) and Matrice d’ Impacts Croisés-Multiplication Appliquée á un Classement (MICMAC) analysis.

Design/methodology/approach

In this study, 13 barriers to lean construction (LC) have been identified through extensive review of literature and subsequently eliciting expert opinions. A proper hierarchy and contextual relationship of the barriers have been developed using ISM, and based on the driving and dependence power of the barriers, three groups of barriers have been found using MICMAC analysis.

Findings

Cultural differences are found to be the most important barrier to LC, whereas employees’ resistance to change and lack of performance measurement systems are the least significant barriers.

Research limitations/implications

The work is limited to literature review and experts’ opinion, and the model may be tested using structural equation modeling to verify the relationship of the barriers.

Practical implications

This ISM-based model would help the decision-makers, researchers and practitioners to prioritize and manage these barriers by better utilizing their resources for eliminating or minimizing the barriers to lean implementation.

Originality/value

The study of barriers to LC through an ISM-based model and the classification of barriers is a new attempt in the field of construction.

Keywords

Citation

Khaba, S. and Bhar, C. (2017), "Modeling the key barriers to lean construction using interpretive structural modeling", Journal of Modelling in Management, Vol. 12 No. 4, pp. 652-670. https://doi.org/10.1108/JM2-07-2015-0052

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

Related articles