Browsing by Author "Yamour, Jenaideb S"

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Creating value using Big Data applications in complex projects: a systematic review of the construction sector in a risk management perspective
(Saudi Digital Library, 2023-09-04) Yamour, Jenaideb S; Qazi, Kamal
The study delineates several key objectives: a comprehensive exploration of Big Data's integration in the sector; an assessment of its merits and challenges; a historical mapping of its evolution; and proffering trajectories for future scholarly and practical endeavours. It underscores the inherent inadequacy of conventional risk assessment tools, particularly for contemporary construction undertakings characterized by intricate designs and stringent timelines, emphasizing the revolutionary potential of Big Data in bolstering industry resilience and predictive prowess. The methodology underpinning this research is anchored in a systemic literature review, aiming to holistically encapsulate the extant body of knowledge on the subject. Pivotal inquiries driving this investigation include the value-addition of Big Data in construction risk management, and its interplay with project complexity. A methodological flowchart shows the research's steps. Key revelations from this investigation points up the reputation of Big Data-centric technologies in risk detection and mitigation throughout construction phases. Techniques like Monte Carlo simulations using Big Data, employing probabilistic assessments for diverse scenarios, have gained prominence. Furthermore, Building Information Modelling (BIM) leverages Big Data for enhanced design fidelity, minimizing design-associated risks. The research also highlights the potency of the MapReduce Hadoop programming paradigm in fortifying risk identification and management. The study also sheds light on Big Data's instrumental role in improving the occupational environment for construction personnel. Conclusively, the paper clarifies the expanding potential of Big Data in refining construction processes, risk mitigating, and bolstering the efficacy and foresight of project management. In essence, this review offers a holistic perspective on Big Data's role in the construction sector's risk management, enhancing existing literature through the discussion of contemporary frameworks. The insights garnered will undoubtedly prove invaluable to researchers and industry practitioners keen on refining risk management strategies through Big Data integrations
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