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Adaku, E, Osei-Poku, V, Ottou, J A and Yirenkyi-Fianko, A (2024) Contractor payment delays: a systematic review of current trends and future directions. Construction Innovation, 24(05), 1205–27.

Almasabha, G, Shehadeh, A, Alshboul, O and Al Hattamleh, O (2024) Structural performance of buried reinforced concrete pipelines under deep embankment soil. Construction Innovation, 24(05), 1280-96.

Hilu, K A and Hiyassat, M A (2024) Qualitative assessment of resilience in construction projects. Construction Innovation, 24(05), 1297-319.

Jayamaha, B H V H, Perera, B A K S, Gimhani, K D M and Rodrigo, M N N (2024) Adaptability of enterprise resource planning (ERP) systems for cost management of building construction projects in Sri Lanka. Construction Innovation, 24(05), 1255-79.

Kedir, F, Hall, D M, Brantvall, S, Lessing, J, Hollberg, A and Soman, R K (2024) Circular information flows in industrialized housing construction: the case of a multi-family housing product platform in Sweden. Construction Innovation, 24(05), 1354-79.

Kineber, A F, Othman, I, Oke, A E, Chileshe, N and Zayed, T (2024) Modeling the relationship between value management implementation phases, critical success factors and overall project success. Construction Innovation, 24(05), 1380-400.

  • Type: Journal Article
  • Keywords: critical success factors; Egypt; partial least square; project success; structural equation modeling; value management
  • ISBN/ISSN: 14714175
  • URL: https://doi.org/10.1108/CI-01-2022-0018
  • Abstract:

    Purpose: This study aims to develop an overall project success (OPS) model by investigating the mediation impact of value management (VM) implementation between VM critical success factors (CSFs) and OPS as well as the moderation impact of VM CSFs between VM implementation and OPS. Design/methodology/approach: In total, 335 structured questionnaires were administered to relevant stakeholders in the study area. The research used a partial least square structural equation modeling (PLS-SEM) to model the relationship among VM implementation, CSFs and OPS. Findings: The results revealed that there is an indirect positive and significant correlation among the variables. The model prediction analysis also significantly impacted with 59.9% on OPS by setting VM implementation as a mediator variable and 61% by setting VM CSFs as a moderation variable. Practical implications: This research work will serve as a guide or benchmark for decision-makers who want to use VM to improve the success of their building projects. Originality/value: This study fills the knowledge gap by identifying and emphasizing the impact of VM CSFs and activities on OPS.

Nguyen Ngoc, H, Mohammed Abdelkader, E, Al-Sakkaf, A, Alfalah, G and Zayed, T (2024) A hybrid AHP-maut model for assessing competitiveness of construction companies: A case study of construction companies in Vietnam and Canada. Construction Innovation, 24(05), 1320-53.

Sammour, F, Alkailani, H, Sweis, G J, Sweis, R J, Maaitah, W and Alashkar, A (2024) Forecasting demand in the residential construction industry using machine learning algorithms in Jordan. Construction Innovation, 24(05), 1228-54.

Shang, G, Pheng, L S and Zhong Xia, R L (2024) Adoption of smart contracts in the construction industry: an institutional analysis of drivers and barriers. Construction Innovation, 24(05), 1401-21.

Zabidin, N S, Belayutham, S and Che Ibrahim, C K I (2024) The knowledge, attitude and practices (kap) of industry 4.0 between construction practitioners and academicians in Malaysia: A comparative study. Construction Innovation, 24(05), 1185-204.