Providing a model to choose the most appropriate agile method in construction projects

Author:

Pouyandeh Faraz1,Golabchi Mahmood1,Taghizadeh Katayoon2

Affiliation:

1. Department of Project and Construction Management, School of Architecture, University of Tehran, Tehran, Iran

2. Department of Architectural Technology, School of Architecture, University of Tehran, Tehran, Iran

Abstract

The use of agile methods according to the success criteria that meet the needs of building projects will increase the efficiency of the construction industry. Most previous research has examined the effects of agility application on one of the success metrics or the implementation of a single agile approach, and no research has been found to select an agile method based on success criteria in construction. In this research, by creating a relationship between success criteria and agile methods and adopting a systematic approach, the appropriate technique was selected in accordance with the needs of the construction industry. This research aims to select the appropriate agile method based on the success criteria of construction projects. By conducting a thorough literature review, a longlist of success criteria and most common agile methods in construction was identified. Then, using the Delphi technique, the most critical criteria were extracted. Additionally, by employing the analytic hierarchy process method, the most appropriate agile technique was determined and ranked. The results show that Scrum is the most adaptable agile method in the construction industry. Furthermore, the most critical criterion affecting the selection of agile methods was determined to be ‘completion of the project on time’.

Publisher

Thomas Telford Ltd.

Subject

Safety, Risk, Reliability and Quality,General Business, Management and Accounting,Civil and Structural Engineering,Building and Construction

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Editorial;Proceedings of the Institution of Civil Engineers - Management, Procurement and Law;2023-01-01

2. Toward new data for IT and IoT project management method prediction;Mathematical Modeling and Computing;2023

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