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<p>This study examines the revolutionary influence of digital transformation (DT) on infrastructure asset management (IAM), particularly regarding their effects on efficiency, cost reduction, and performance enhancement. This study employs a comprehensive systematic review methodology to collect and analyze recent research, industry case studies, and conference proceedings. It employs data-driven methodologies from the Scopus database to evaluate the efficacy of digital solutions such as internet of things (IoT), artificial intelligence (AI), big data, and building information modeling (BIM) in infrastructure operations. The study indicates that DT markedly increases operational efficiency, lowers lifetime costs, and boosts asset performance through predictive maintenance, real-time monitoring, and data-driven decision-making. This study’s uniqueness stems from its integrative approach, merging technical innovations with managerial methods to offer a thorough comprehension of the advantages across all asset categories and sectors. Significant challenges faced during the evaluation encompass the inconsistency of digital adoption rates across various locations and sectors, as well as the intricacy of connecting disparate technological platforms. To tackle these challenges, this study formulated a series of pragmatic guidelines for surmounting obstacles to DT, encompassing the standardization of data formats and the augmentation of digital literacy through a quantitative analysis examining temporal trends, spatial distribution of research trajectories, and the keywords of the incorporated research and review articles. After the screening process to identify relevant journals and strategic papers concerning DT classifications and content analysis, only 128 studies were considered pertinent, while 246 articles were excluded. Through a thorough quantitative analysis, this study’s integration of various aspects of DT, such as data standardization and digital literacy, demonstrates its novelty. This methodology offers significant insights into the existing research environment regarding the mitigation of obstacles to DT and underscores potential avenues for future inquiry and advancement in the discipline. This method can ultimately result in more efficient tactics for firms aiming to manage the intricacies of DT.</p>

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Exploring the Benefits of Digital Transformation (DT) for Infrastructure Asset Management (IAM) in Terms of Efficiency, Cost Savings, and Performance Optimization

  • 期刊论文

  • 发表日期：

    2025年5月20日

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  • Wesam Beitelmal,
  • Omar Alruwaythi

摘要

This study examines the revolutionary influence of digital transformation (DT) on infrastructure asset management (IAM), particularly regarding their effects on efficiency, cost reduction, and performance enhancement. This study employs a comprehensive systematic review methodology to collect and analyze recent research, industry case studies, and conference proceedings. It employs data-driven methodologies from the Scopus database to evaluate the efficacy of digital solutions such as internet of things (IoT), artificial intelligence (AI), big data, and building information modeling (BIM) in infrastructure operations. The study indicates that DT markedly increases operational efficiency, lowers lifetime costs, and boosts asset performance through predictive maintenance, real-time monitoring, and data-driven decision-making. This study’s uniqueness stems from its integrative approach, merging technical innovations with managerial methods to offer a thorough comprehension of the advantages across all asset categories and sectors. Significant challenges faced during the evaluation encompass the inconsistency of digital adoption rates across various locations and sectors, as well as the intricacy of connecting disparate technological platforms. To tackle these challenges, this study formulated a series of pragmatic guidelines for surmounting obstacles to DT, encompassing the standardization of data formats and the augmentation of digital literacy through a quantitative analysis examining temporal trends, spatial distribution of research trajectories, and the keywords of the incorporated research and review articles. After the screening process to identify relevant journals and strategic papers concerning DT classifications and content analysis, only 128 studies were considered pertinent, while 246 articles were excluded. Through a thorough quantitative analysis, this study’s integration of various aspects of DT, such as data standardization and digital literacy, demonstrates its novelty. This methodology offers significant insights into the existing research environment regarding the mitigation of obstacles to DT and underscores potential avenues for future inquiry and advancement in the discipline. This method can ultimately result in more efficient tactics for firms aiming to manage the intricacies of DT.