Evaluating the Challenges Hindering Widespread Adoption of the Design–Build Delivery Method.
Saved in:
| Title: | Evaluating the Challenges Hindering Widespread Adoption of the Design–Build Delivery Method. |
|---|---|
| Authors: | Al-Bayati, Ahmed Jalil1 aalbayati@ltu.edu, Chellappa, Vigneshkumar2 vkumar.chellappa@polyu.edu.hk, Hasbrook, Bill3 bill@wurstconsulting.com |
| Source: | Journal of Structural Design & Construction Practice. Aug2026, Vol. 31 Issue 3, p1-7. 7p. |
| Subjects: | Construction industry, Construction projects, Contractors, Inferential statistics |
| Geographic Terms: | United States |
| Abstract: | The design–build (DB) delivery system has gained popularity in the United States construction industry, offering numerous advantages and demonstrating proven results. Nevertheless, contractors' challenges when utilizing the DB method have not always been adequately addressed. This study used a survey-based design to examine challenges construction professionals face with the DB method. Sixty-three practitioners participated in the survey using convenience sampling. The survey findings were summarized using descriptive and inferential statistics, and the challenges were ranked based on their perceived impact on project delivery. The findings indicated that the top five challenges hindering the implementation of DB project delivery were complex coordination and communication, intricate cost estimation steps, complex procurement procedures, the involvement of external consultants, and the preparation of comprehensive requests for proposals (RFPs). The findings suggest key areas needing attention, improvement, and education to enhance the use of the DB method. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Structural Design & Construction Practice is the property of American Society of Civil Engineers and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
