Back to Search
Start Over
A Bayesian network for selecting improvement management tools to increase customer satisfaction in the construction industry: case study of Mexico.
- Source :
- Engineering Construction & Architectural Management (09699988); 2024, Vol. 31 Issue 7, p2900-2915, 16p
- Publication Year :
- 2024
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- CUSTOMER satisfaction
BAYESIAN analysis
CONSTRUCTION industry
CONSUMERS
PRICES
Subjects
Details
- Language :
- English
- ISSN :
- 09699988
- Volume :
- 31
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Engineering Construction & Architectural Management (09699988)
- Publication Type :
- Academic Journal
- Accession number :
- 178139173
- Full Text :
- https://doi.org/10.1108/ECAM-01-2022-0089