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A Bayesian network for selecting improvement management tools to increase customer satisfaction in the construction industry: case study of Mexico

David Joaquín Delgado-Hernández (School of Engineering, Autonomous University of Mexico State, Toluca, Mexico)
Ulises Jairo Palacios-Navarro (School of Engineering, Autonomous University of Mexico State, Toluca, Mexico)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 28 February 2023

125

Abstract

Purpose

The use of improvement tools in the construction sector has shown to be an important determinant of quality. Companies endeavoring to enhance their daily practices require assistance, evidence, standards, frameworks and quantitative models from existing experts to help them set out for the road. This paper is aimed to assist construction managers in the selection of tools to increase customer satisfaction.

Design/methodology/approach

This piece of research is based on the results of a previous empirical study on the use, within a sample of Mexican firms, of a set of more than 30 tools. It then proposes a Bayesian network (BN) to select them. By analyzing the variables under study, it is possible to establish their interaction and dependencies. The resultant BN comprises 24 nodes, and it is useful for choosing some tools that help to increase customer satisfaction.

Findings

Customers and their needs now have become more complicated and harder to meet than in the past. Then, the use of improvement tools that put quality at the heart of the management strategies is crucial for achieving customer satisfaction. In order to reduce prices, keep product quality and meet delivery times, these tools should be used on a daily basis. Along this line of thought, the overall results from the hypothetical scenarios explored in this were positive, reflecting the relevance of the proposed model. In particular, the use of tools for gathering customer needs, the utilization of technology and the implementation of a quality department are relevant for increasing customer satisfaction in the sector.

Research limitations/implications

The sample size could be further expanded. The customer satisfaction dimensions could be enhanced.

Practical implications

While the sample in which the investigation is based could be expanded along with the number of variables and their states, the BN can help practitioners in the global construction industry to improve their quality practices, to foster loyalty and to grow revenues.

Originality/value

Most of the research reported in the area of continuous improvement in construction focuses on qualitative considerations, and it is still scarce in terms of developing mathematical models for selecting existing tools and, ultimately, satisfying customer’s requirements. This investigation is aimed to bridge this gap in the literature.

Keywords

Acknowledgements

The authors would like to thank all the companies that took part in the original study. Thanks also go to the Autonomous University of the State of Mexico for the support given to carry out this research.

Citation

Delgado-Hernández, D.J. and Palacios-Navarro, U.J. (2023), "A Bayesian network for selecting improvement management tools to increase customer satisfaction in the construction industry: case study of Mexico", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-01-2022-0089

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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