Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 12 results ...
Barajei, C, Kusi, E, Ackon, F, Osman, A M, Mohammed, A M Z, Simpeh, F and Gyimah, F (2024) Success factors of the consultant selection stage of the Ghanaian public construction projects: The road sector’s perspective. Construction Economics and Building, 24(01-02), 144-62.
Bello, A O, Abdulraheem, A A, Afolabi, O P, Aka, A and Gbenga, P O (2024) Assessing the underlying factors affecting trust and transparency in the construction industry: A mixed method approach. Construction Economics and Building, 24(01-02), 3-28.
Chiponde, D, Gledson, B and Greenwood, D (2024) The institutional field of learning from project-related failures: opportunities and challenges. Construction Economics and Building, 24(01-02), 163-81.
Debs, L and Hubbard, B (2023) Gathering and disseminating lessons learned in construction companies to support knowledge management. Construction Economics and Building, 23(01-02), 56-76.
Domínguez-Herrera, M M, González-Morales, O and González-Díaz, E (2023) Social responsibility of construction company as strategy for sustainability in island territories. Construction Economics and Building, 23(01-02), 30-55.
Hong, J, Akotia, J and Egbu, C (2024) Virtual reality in construction activities: Barriers for adoption in China. Construction Economics and Building, 24(01-02), 77-93.
Kapogiannis, G, Palaios, P and Sawhney, A (2024) Digital construction led growth asymmetries in Europe: The need for collaborative culture. Construction Economics and Building, 24(01-02), 50-76.
Khan, I H and Munawer, T (2024) A systematic review of economic sustainability of vertical greenery systems for buildings. Construction Economics and Building, 24(01-02), 119-43.
Suriyanon, N, Sutheerawatthana, P, Kaewmoracharoen, M and Klansai, V (2023) The utility and value of contract terms: A case study on interior contractors. Construction Economics and Building, 23(01-02), 77-94.
Uddin, S M J, Albert, A, Pradhananga, N, Ganapati, N E and Prajapati, J (2023) Health and safety challenges among post-disaster reconstruction workers. Construction Economics and Building, 23(01-02), 4-30.
Upadhyaya, D and Malek, M S S (2024) An exploratory factor analysis approach to investigate health and safety factors in Indian construction sector. Construction Economics and Building, 24(01-02), 29-49.
Wood, X, Ghimire, P, Kim, S, Barutha, P and Jeong, H D (2024) Framework for evaluating the success of integrated project delivery in the industrial construction sector: A mixed methods approach & machine learning application. Construction Economics and Building, 24(01-02), 94-118.
- Type: Journal Article
- Keywords: industrial construction; integrated project delivery; machine learning; mixed methods research; project success framework
- ISBN/ISSN: 2204-9029
- URL: https://doi.org/10.5130/ajceb.v24i1/2.8783
- Abstract:
Integrated project delivery (IPD) has gained traction as a collaborative approach to managing complexity and uncertainty in large industrial capital projects. While IPD emphasizes team integration and process alignment to drive better outcomes, the lack of standardized benchmarks to evaluate its performance relative to traditional methods persists as a barrier. To bridge this gap, this study developed a practical, and unbiased Project Success Framework (PSF) for IPD on industrial projects. A mixed methods research approach including subject matter experts' survey, research charrette, and validation survey was conducted to build and validate the PSF. In addition, this study proposed a machine learning (ML)-based application tool embedding PSF to enhance the practicality and applicability of PSF. The machine learning-based application tool was validated by comparing the results with the PSF suggested in this research. The PSF developed in this study allows researchers and practitioners to empirically evaluate the integrated project delivery's efficacy on key industrial project outcomes. In addition, it offers a method to compare project delivery methods across diverse projects, aiding organizations in precise selection using empirical evidence for optimal results. Moreover, this framework aids clients in crafting shared risk/reward models that foster successful outcomes by encouraging desirable behaviors.