Abstracts – Browse Results
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Aboseif, E and Hanna, A S (2024) Benchmarking of construction projects performance for comparative assessment and performance improvement: a statistical quantitative approach. Engineering, Construction and Architectural Management, 31(07), 2829-51.
Al-Hadidi, S, Sweis, G, Abu-Khader, W, Abu-Rumman, G and Sweis, R (2024) Managing future urbanization growth patterns using genetic algorithm modeling. Engineering, Construction and Architectural Management, 31(07), 2648-68.
Delgado-Hernández, D J and Palacios-Navarro, U J (2024) A Bayesian network for selecting improvement management tools to increase customer satisfaction in the construction industry: case study of Mexico. Engineering, Construction and Architectural Management, 31(07), 2900-15.
Gibson, G E, El Asmar, M, Yussef, A and Ramsey, D (2024) A novel approach for measuring the accuracy of front end engineering design. Engineering, Construction and Architectural Management, 31(07), 2669-96.
- Type: Journal Article
- Keywords: accuracy; construction planning; novel method; project management
- ISBN/ISSN:
- URL: https://doi.org/10.1108/ECAM-05-2022-0418
- Abstract:
Purpose: Assessing front end engineering design (FEED) accuracy is significant for project owners because it can support informed decision-making, including confidence in cost and schedule predictions. A framework to measure FEED accuracy does not exist in the literature or in practice, not does systematic data directly linking FEED accuracy to project performance. This paper aims to focus first on gauging and quantifying FEED accuracy, and second on measuring its impact on project performance in terms of cost change, schedule change, change performance, financial performance and customer satisfaction. Design/methodology/approach: A novel measurement scheme was developed for FEED accuracy as a comprehensive assessment of factors related to the project leadership and execution teams, management processes and resources; to assess the environment surrounding FEED. The development of this framework built on a literature review and focus groups, and used the research charrettes methodology, guided by a research team of 20 industry professionals and input from 48 practitioners representing 31 organizations. Data were collected from 33 large industrial projects representing over $8.8 billion of installed cost, allowing for a statistical analysis of the framework's impact on performance. Findings: This paper describes: (1) twenty-seven critical FEED accuracy factors; (2) an objective and scalable method to measure FEED accuracy; and (3) data showing that projects with high FEED accuracy outperformed projects with low FEED accuracy by 20 percent in terms of cost growth in relation to their approved budgets. Practical implications: FEED accuracy is defined as the degree of confidence in the measured level of maturity of the FEED deliverables to serve as a basis of decision at the end of detailed scope, prior to detailed design. Assessing FEED accuracy is significant for project owners because it can support informed decision-making, including confidence in cost and schedule predictions. Originality/value: FEED accuracy has not been assessed before, and it turned out to have considerable project performance implications. The new framework presented in this paper is the first of its kind, it has been tested rigorously, and it contributes to both the literature body of knowledge as well as to practice. As one industry leader recently stated, “it not only helped to assess the quality and adequacy of the technical documentation required, but also provided an opportunity to check the organization's readiness before making a capital investment decision.”. © 2023, Emerald Publishing Limited.
Guo, J, Xiang, P, Liu, Q and Luo, Y (2024) Transportation infrastructure network optimisation based on computer simulation using Sichuan Province, China as an example. Engineering, Construction and Architectural Management, 31(07), 2740-69.
Khan, S, Panuwatwanich, K and Usanavasin, S (2024) Integrating building information modeling with augmented reality: application and empirical assessment in building facility management. Engineering, Construction and Architectural Management, 31(07), 2809-28.
Khanapure, V U and Shastri, S S (2024) A sustainable–lean implementation methodology: a catalyst for sustainability enhancement of high-rise residential projects. Engineering, Construction and Architectural Management, 31(07), 2585-603.
Kum, Y T, Yap, J B H, Lew, Y L and Lee, W P (2024) Transforming construction health and safety management during COVID-19 pandemic using innovative technologies: PLS-SEM approach. Engineering, Construction and Architectural Management, 31(07), 2770-808.
Lad, V H, Patel, D A, Chauhan, K A and Patel, K A (2024) Prioritisation of bridge for improving its resilience using multi-criteria decision-making techniques. Engineering, Construction and Architectural Management, 31(07), 2952-76.
Li, T, Li, Z and Cai, J (2024) Antecedents and consequence of intra-organizational diffusion of prefabricated construction technology: a contingency theory perspective. Engineering, Construction and Architectural Management, 31(07), 2932-51.
Li, X, Chang, C T, Zhu, Y Y and Li, L L (2024) Key influence factors on the evacuation route selection for fire emergencies in urban underground complexes. Engineering, Construction and Architectural Management, 31(07), 2630-47.
Lin, Q, Zhang, C, Cai, H, Li, X and Xiao, H (2024) Urban night lighting evaluation system and case study: blending popular contemporary elements, cultural traditions and advanced lighting technologies. Engineering, Construction and Architectural Management, 31(07), 2916-31.
Lu, Y, Liu, J and Yu, W (2024) Social risk analysis for mega construction projects based on structural equation model and Bayesian network: a risk evolution perspective. Engineering, Construction and Architectural Management, 31(07), 2604-29.
Masood, R, Roy, K, González, V A, Lim, J B P and Nasir, A R (2024) A supply chain perspective of prefabricated housebuilding diffusion in New Zealand. Engineering, Construction and Architectural Management, 31(07), 2697-720.
Tennakoon, G A, Rameezdeen, R and Chileshe, N (2024) Walking the talk towards sustainable consumption: interventions to promote the uptake of reprocessed construction materials. Engineering, Construction and Architectural Management, 31(07), 2878-99.
Wang, Z, Shi, L and Cui, H (2024) Effects of the host-country institutional environment on the operation mode change of international construction enterprises. Engineering, Construction and Architectural Management, 31(07), 2721-39.
Xie, L L, Chen, Y, Wu, S, Chang, R D and Han, Y (2024) Knowledge extraction for solving resource-constrained project scheduling problem through decision tree. Engineering, Construction and Architectural Management, 31(07), 2852-77.
Zhou, X, Wang, Y, Zhang, Y and Liu, F (2024) Macro investigation on China's engineering insurance industry: based on industrial organization theories. Engineering, Construction and Architectural Management, 31(07), 2977-94.