Abstract: This research paper seeks to research the place of logistics agility and intelligent quality management. The conundrum is represented by rapid evolution in the industrial supply chain operations due to digital transformation especially in the developing countries. Thus, this research aims at exploring how digital logistics agility impacts intelligent quality management with the moderated impact of green sourcing strategy in the Jordanian industrial sector. This was a quantitative research methodology; the study was done by the use of a structured survey questionnaire which was sent to those working in supply chain and operations of a sample size of Jordanian industrial firms. We employed the partial least squares structural equation modeling (PLS-SEM) to test the hypothesis of the direct and indirect correlations between digital logistics agility and green sourcing strategies and intelligent quality management. This analysis established that the idea of digital logistics agility has a considerable impact on green sourcing policies and smart quality management activities. The indirect impact of the logistics on the quality of the outcomes through the mediation of a green-sourcing is also substantial, meaning that, in as much as an agile logistics system can enhance the quality outcomes, its ability to do so will be greater in case it also involves the introduction of environmentally friendly sourcing practices. The current research demonstrates that the digital logistics agility can be used to improve the intelligent quality control in the industrial environment when combined with the green sourcing strategies. The findings explain the ways that supply chain managers, sustainability officers, as well as policymakers can educate the design of resilient, evidence-based, and sustainable industrial systems in Jordan.

Abstract: This study examines the impact of supply chain management (SCM) practices and innovation strategies on competitive advantage through operational performance in West Java. Using a quantitative approach, the study surveyed 150 SME managers/owners via Google Forms, analyzing the data with Structural Equation Modeling (SEM) and AMOS 20 software. The results reveal that SCM practices positively influence operational performance and competitive advantage, while innovation strategies also enhance operational performance and competitive advantage. Furthermore, the study finds that although SCM practices and innovation strategies improve competitive advantage, operational performance does not mediate the relationship between these factors and competitive advantage. The implications of these findings suggest that SMEs should focus on enhancing SCM practices and fostering innovation strategies to improve competitive advantage directly. Although operational performance is important, it does not play a central mediating role in boosting competitive advantage. Therefore, businesses should prioritize optimizing SCM and innovation independently for more effective outcomes, without relying on operational performance as an intermediary. This insight can guide policy development and strategic planning for SMEs in West Java, fostering more efficient operations and stronger market positioning.

Abstract: This study reviews the literature on Supply Chain Management (SCM) and Project Management (PM) to serve the Sustainable Development Goals (SDGs) through technological integration. Technological innovations may enhance operational efficiency and decision-making as per SDGs 8 and 9. However, the success of such innovations depends on managerial competency. In this regard, operational coordination can optimize multi-actor networks, which can improve resource allocation and productivity. Moreover, inter-organizational relationships would nurture governance and trust. Additionally, lifecycle project management and stakeholder engagement can enhance operational continuity and sustainability, which can further be supported by stochastic optimization and AI-enabled decision making. The study recommends to integrate circular economy, lean practices, and environmentally responsible frameworks with operational objectives to achieve SDGs. Thus, the interdependence of technology, human capital, governance, and strategy is necessary to achieve efficient SCM and PM.

Abstract: The Multiple Travelling Salesman Problem (MTSP) is one of the prominent combinatorial optimization problems with both theoretical interest and practical applications. However, its less-explored variants, such as the Open-Close Multiple Travelling Salesman Problem (OCMTSP), have received comparatively limited attention. In the OCMTSP, all salesmen commence their routes from a central depot, but unlike the classical MTSP, not all are required to return to the starting point upon completing their deliveries. Additionally, allowing any salesman to visit the maximum number of cities can lead to an imbalanced workload distribution among the salesmen. To address this imbalance, the current study incorporates a load balancing constraint into the OCMTSP framework, ensuring a fair distribution of cities among all salesmen. This extended problem variant is termed as Open-Close Multiple Travelling Salesman Problem with Load Balancing (OCMTSPLB). The primary objective of the OCMTSPLB is to minimize the total travel distance or cost incurred by the combined open and closed tours while maintaining balanced workloads. To solve this variant, the study proposes two distinct crossover based multi-chromosome Genetic Algorithm (GA) frameworks. Given the novelty of this problem, the algorithms are assessed using standardized benchmark instances from the TSPLIB. Experimental findings indicate that one of the proposed GA variants consistently achieves superior solution quality, a result further validated through non-parametric statistical tests.

Abstract: The manufacturing firms are trying to attain digitalization of operations and supply chains in the fast changing technological era. Digital transformation was more agile and efficient. However, the issue of how and why digital transformation is going to create a sustained competitive advantage is a question. The survey was carried out in the form of a quantitative survey among the managers of 326 Jordanian manufacturing firms, which were involved in digital projects. SEM and AMOS were used to test the hypotheses. The results illustrate that the digital transformation has positive and significant effects on the competitive advantage of the supply chains. The mediation analysis showed that the dynamic capabilities are important to the competitive advantage of the digital transformation. The results suggest that digital transformation is a strategic enabler that enhances the dynamic capabilities of a company, which is later translated into the high-level of supply chain performance. Digitalization is an enabler of building of capability, according to the Dynamic Capabilities Theory. These increased capabilities, in turn, enable firms to attain and maintain competitive advantages in the form of faster delivery, increased flexibility, and reduced costs. The research builds on theoretical knowledge by introducing digital transformation to the capability-based perspective on competitiveness, in which the value of digital investments is achieved by the capabilities of organizations and managers to a large extent.

Abstract: Managing change is essential to achieving high levels of organizational performance, enabling companies to effectively adapt to highly dynamic environments by considering new structures, adopting technologies, and implementing new processes. In this context, this research examines the effect of change management on organizational performance, mediated by organizational culture, in Peruvian companies in the service sector. This quantitative, non-experimental study collected cross-sectional data from 544 managers of service-providing companies, one of the most important sectors of the Peruvian economy, through an online survey comprising a 21-item Likert-based questionnaire with five options for rating each item. The data were processed in SPSS and AMOS, confirmatory factor analysis was applied to test the proposed model and modeled through structural equations, in order to test the veracity of the hypotheses raised. The results revealed that, in service companies, there is partial mediation of culture, relating change management to organizational performance, with a coefficient of 0.093. Furthermore, change management has a direct positive effect on organizational performance (β=0.273, SE=0.138, p<0.05), as well as on organizational culture (β=0.603, SE=0.145, p<0.01). Likewise, organizational culture has a positive impact on organizational performance (β=0.433, SE=0.071, p<0.01). This study integrates three variables within the service business environment, provides valuable empirical evidence, and addresses an important gap in the literature, highlighting organizational culture as a key mediator in organizational change processes, enabling organizations to achieve improved performance levels.

Abstract: Transparency in the supply chain is crucial for enhancing integration, efficiency, and responsiveness, but it also carries the risk of strategic information leakage. Management commitment and the effective use of digital technology are essential to creating safe and transparent environments. This study aims to investigate the impact of management commitment on the adoption of information technology, supply chain transparency, and practices that enhance operational performance. Data collection was conducted at 221 manufacturing companies that have adopted information technology as their primary system. Testing the research instrument using SmartPLS version 4 data analysis showed a good goodness-of-fit model. The study's results indicate that management commitment has a significant influence on the adoption of information technology and supply chain practices. However, its impact on supply chain transparency is less pronounced. The resulting operational performance is not directly determined by supply chain transparency, but rather by the adoption of information technology and the implementation of effective supply chain practices. The adoption of information technology has an impact on supply chain practices through supply chain transparency. The results of this study contribute practically to company management by enabling the update of information technology and the implementation of supply chain practices and transparency, thereby facilitating continuous evaluation and control of the company system. The results of this study contribute to enriching the theory of digitalization in the manufacturing industry's supply chain.

Abstract: Behavior-Based Safety (BBS) is the art of communicating and correcting unsafe behaviors of project and factory staff. It was developed from behavioral sciences through direct observations of behavior changes. Scholars across the globe have examined the efficacy of BBS in ensuring safe behaviors in projects. However, the available literature is fragmented, and there is a need to have a panoramic, systematic, and comprehensive understanding of BBS. This study synthesizes, analyzes, and categorizes the BBS literature to provide a conceptual framework and inputs for further research. The study was conducted using bibliometric analysis of 56 research articles from the Scopus database. The results present a bird's-eye view of published materials on BBS. The bibliographic coupling helped categorize the outcomes of BBS into various clusters. The study also found that most highly cited articles were from the construction industry. Future researchers may examine the findings of seminal studies, identified as the most cited documents, to inform design choices and trade-offs that address the major hindrances to implementing BBS in its true spirit.

Abstract: This study investigates the key factors influencing intention to use e-commerce in an emerging market context, focusing on individuals residing in Saudi Arabia. A quantitative research approach was adopted, and data were collected using a structured questionnaire from 281 respondents through a convenience sampling technique. Data were analyzed using structural equation modeling with SmartPLS to test the hypothesized relationships. The results revealed that attitude, subjective norms, self-efficacy, and trust all had significant positive effects on intention to use e-commerce. Moreover, trust in e-commerce was found to influence attitude, which in turn mediated the relationship between trust and intention, highlighting the importance of trust as both a direct and indirect driver of online purchasing behavior. The R-square values indicated that 47.9% of the variance in attitude and 65.4% of the variance in intention were explained by the model, confirming strong explanatory power. The study concludes that trust, confidence, social influence, and positive attitudes are crucial for enhancing consumers’ willingness to engage in e-commerce. The study delivers essential information which helps e-commerce companies and marketing professionals and government officials to enhance consumer trust and digital shopping experience and build favorable digital commerce attitudes in Saudi Arabia.

Abstract: This study investigates the independent and combined effects of human capital management and financial development upon energy transition within the Saudi Arabian economy. The autoregressive distributed lag (ARDL) model is applied to analyze annual data for the period 1990-2020. The findings reveal a complex dynamic shaping the energy transition. Human capital management initially acted as a barrier to progress. However, the implementation of Vision 2030 has significantly altered this trajectory. Secondly, financial development positively influences renewable energy consumption while potentially also contributing to increased CO2 emissions. Lastly, the study highlights a synergistic relationship between effective human capital management and financial development, demonstrating that their strategic alignment accelerates the energy transition. These insights underscore the need for coordinated policies that integrate workforce development with financial mechanisms to drive sustainable Saudi Arabia's sustainable energy transformation.

Abstract: The purpose of this study was to analyze the relationship between public open space management and visitor comfort in tourist areas and environmental quality. The approach used in this study is a quantitative approach. The type of research used in this study is non-experimental, used to find relationships between variables. Based on its objectives, this study is a correlational study that seeks relationships or associations between two or more variables used in the study. The respondents of this study were 254 visitors to tourist attractions selected using a simple random sampling technique based on the ease of finding potential participants from trusted sources (participants who have completed the questionnaire). The researchers also contacted potential respondents who matched the characteristics of the participants through direct messages on WhatsApp, Line, and Instagram. Next, questionnaires were given to a number of respondents through social media such as email, WhatsApp, Line, and direct messages on Instagram. This questionnaire uses an ordinal scale using a Likert scale. The scale used in data collection in this study is a scale with a range of 1 to 5. The analysis technique used in this study is Partial Least Squares-Structural Equation Modeling (PLS-SEM) which was carried out using SmartPLS software version 4.0.9.9. The data testing stages include validity testing, reliability testing, significance testing, and hypothesis testing. The results showed that public open space management had a positive relationship with visitor comfort in tourist areas, and environmental quality had a positive relationship with visitor comfort in tourist areas. Project management has a positive relationship with visitor comfort in tourist areas.

Abstract: This study investigates the role of frontier operational efficiency in predicting financial performance within Egypt’s emerging market. Data Envelopment Analysis (DEA) quantifies operational efficiency, and its predictive power is assessed within a machine learning (ML) framework, extending beyond traditional financial ratios. A Super Learner ensemble is developed, integrating Random Forest (RF) and Categorical Gradient Boosting (CatBoost) with a linear regression meta-learner. The Super Learner enhances accuracy and robustness by dynamically weighting and combining predictions from diverse base models, using a meta-learner to minimize error, reduce overfitting, and improve generalization. Empirical results demonstrate that incorporating DEA significantly improves predictive performance, increasing R² by 3.8% (t = 5.45, p < 0.01). The Super Learner achieves an R² of 0.612, with an RMSE of 0.061 and MAE of 0.046, outperforming both linear regression and state-of-the-art ML models. Feature importance analysis (via CatBoost) identifies net working capital (11.5%) and DEA efficiency (10.0%) as the top predictors. SHapley Additive exPlanations (SHAP) and partial dependence analyses further indicate that DEA efficiency, net working capital, and cash holdings exhibit positive but nonlinear associations with financial performance, while leverage demonstrates a concave, nonlinear relationship. These findings provide practical implications for investors, managers, and policymakers, highlighting the strategic value of operational efficiency. Additionally, the study introduces a scalable, interpretable framework combining frontier efficiency metrics with explainable ML, offering a robust tool for financial decision-making.

Abstract: This study aims to develop a disaster mitigation model for the eruption of Mount Sinabung based on the integration of local wisdom from the Karo community and social resilience theory. The recurring eruptions since 2010 have resulted in complex socio-ecological impacts, yet existing mitigation approaches have tended to be technocratic and lacked contextual relevance. This research employs a descriptive qualitative approach within a constructivist paradigm, relying on in-depth interviews, observation, documentation, and Focus Group Discussions (FGDs) as data collection techniques. Data analysis is conducted using the Miles, Huberman, and Saldana model, encompassing data reduction, presentation, and conclusion drawing. The main finding of this study is the formulation of the RiRi Model, which comprises four components: Respect (recognition of local knowledge), Initiation (active community participation), Runggun (optimization of traditional social networks), and Integration (collaboration between local and modern approaches). This model offers a more inclusive mitigation strategy, rooted in the cultural values of the Karo community, and capable of holistically strengthening community resilience. The study also reveals that local wisdom practices such as aron, runggu, and the use of jambur hold strategic potential as community-based disaster mitigation instruments. By synergizing social, cultural, and technical dimensions, the RiRi Model is expected to serve as an alternative framework for national disaster mitigation policy that is more adaptive, sustainable, and responsive to local contexts.

Abstract: The article investigates the formation of Ukraine’s business climate during the transition period triggered by the full-scale military invasion of 2022 and explores factors influencing entrepreneurial adaptation to new economic and security challenges. The study underscores the need for a scientific understanding of transformation processes in the business environment, which is affected by military actions, economic instability, inflation, and devaluation, and highlights the role of state policy in supporting businesses during this period. The aim of the research is to comprehensively assess the dynamics of Ukraine’s business climate from 2012 to 2023, identify key factors shaping it, and determine future prospects for entrepreneurial development. Methodologically, the study utilizes horizontal and vertical economic analysis, comparative methods, and statistical data from 2020–2024. Indicators such as the Ukrainian Business Index (UBI) and diffusion index (DI) were employed to measure activity, alongside fundamental and technical analysis techniques. The results show a significant drop-in business activity in 2022 (UBI fell to 29.82), followed by a recovery in 2023 (UBI rose to 38.92), reflecting adaptability under crisis conditions. Small and medium enterprises, particularly in pharmaceuticals, agriculture, and telecommunications, demonstrated resilience, and a 5% GDP growth in 2023 was supported by stabilization in the energy sector and international aid. Future research should further explore the effects of digitalization, deregulation, and financial assistance on the business climate and develop models to forecast economic activity in conditions of uncertainty.

Abstract: There is abundant literature on sustainable construction projects. This review study collects a set of studies to understand the depth of the topic as per the Sustainable Development Goals (SDGs). For this purpose, the Scopus database is explored with a systematic review approach, and 80 studies are selected. The literature emphasizes the integration of human capital, technological innovation, governance, and financial support to achieve sustainable objectives in construction projects. Moreover, education can improve technical and strategic competencies in graduates to promote experiential learning for the construction industry. Furthermore, sustainable construction can be enhanced by circular economy principles. In addition, risk management also needs attention to ensure operational reliability in construction projects. For this purpose, institutions and governance can align technical and ecological priorities in a project to achieve sustainability objectives. Innovations can also improve efficiency and knowledge management. Lastly, economic and financial mechanisms can also support this phenomenon. The study suggests promoting education, technology, and governance to support sustainable construction as per the SDGs.

Abstract: The influence of climate risk disclosures on audit engagements remains unclear, largely due to a scarcity of empirical evidence regarding their effect on audit efforts. This study addresses this gap by examining the impact of climate risk disclosures on auditors’ workload. Additionally, it investigates whether political connections and Environmental, Social, and Governance (ESG) performance moderate this relationship within emerging markets in Egypt. The analysis uses data from non-financial companies listed on the Egyptian Stock Exchange between 2017 and 2022. Multiple regression models were developed to test the research hypotheses. Results reveal that greater climate risk disclosure prompts auditors to exert increased effort. Furthermore, this effect is amplified in companies with political connections and higher ESG performance. Robustness tests, employing alternative measures of climate risk disclosure, confirm these findings.

Abstract: The aim of this research is to analyze the relationship between Innovation Projects and work productivity and work environment and work productivity, analyze the relationship between job satisfaction and work productivity and analyze the relationship between organizational culture and work productivity. This study employed a quantitative approach with an explanatory research design, aiming to examine the effect of integrity, organizational commitment, and motivation on sustainable employee performance with job satisfaction as a mediating variable. The population consists of all employees of the manufacturing organization, totaling 470 employees. The sampling technique applied is simple random sampling. The research instrument was a questionnaire using a 5-point Likert scale. The study variables were: Digital Work Environment (X1), Job Satisfaction (X2), Organizational Culture (X3), Innovation Projects (X4) and Employee Work Productivity (Y). Data were analyzed using Partial Least Square – Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The analysis consisted of two stages: Outer Model (Measurement Model): Convergent validity, discriminant validity, and reliability testing. Inner Model (Structural Model): Path coefficient testing, R² values, and both direct and indirect effects among variables. The results show that the digital work environment has a positive relationship with work productivity. Job satisfaction has a positive relationship with work productivity. Organizational culture has a positive relationship with work productivity. Innovation Projects have a positive relationship with work productivity.

Abstract: This study aims to analyze the relationship between government digitalization and the enhancement of community participation in development in North Sumatra Province. Digitalization is understood as an effort to transform bureaucracy through information technology, manifested in official regional government websites such as sumutprov.go.id, which provide various public services online. However, the effectiveness of such digital platforms in encouraging active citizen participation has not been widely explored, particularly in non-metropolitan areas. This research employs a descriptive qualitative approach with data collection techniques including observation, documentation, and semi-structured interviews with ten informants from various regions in North Sumatra. Data were analyzed using the Miles, Huberman, and Saldana model, supported by NVivo 15 software for thematic coding and data visualization. The findings reveal that although the public has access to digital government services, the level of engagement remains low due to structural barriers (internet access and digital literacy), cultural factors (offline habits), and institutional constraints (limited bureaucratic responsiveness). Based on the Diffusion of Innovation theory, most of the population falls into the late majority and laggards’ categories, indicating that digital innovation adoption is not yet widespread. This study offers novelty by specifically mapping the forms of digital community participation based on direct experiences and identifying the dynamics of digital innovation adoption within the context of regional governance. These findings have significant implications for the development of a more adaptive, inclusive, and participation-oriented digital government strategy in regional development.

Abstract: The rapid advancement of artificial intelligence (AI) has revolutionized project portfolio management (PPM), as it has in many other areas, by introducing data-driven methods that improve decision-making, risk assessment, and strategic alignment. Unlike traditional project management, which emphasizes individual project execution, PPM requires balancing multiple initiatives to optimize value creation and resource allocation. This paper presents a systematic review of scientific research on the integration of AI techniques into PPM, focusing on their applications, benefits, and challenges. The review synthesizes findings from 73 peer-reviewed studies covering a wide range of AI methodologies, such as machine learning, deep learning, neural networks, reinforcement learning, natural language processing, and hybrid optimization models. These approaches have been applied in diverse fields, including information technology, construction, healthcare, defense, energy, and telecommunications. Analysis shows that AI significantly improves project portfolio performance by predicting project outcomes, identifying interdependencies, optimizing resource allocation, and supporting adaptive strategies in dynamic environments. In addition, advanced AI tools provide project portfolio managers with predictive and prescriptive analytics, transforming PPM from reactive monitoring to proactive governance. Despite these advances, challenges remain regarding data quality, organizational readiness, and interpretability of AI-based models. Concerns about transparency, ethical implications, and integration with existing management frameworks also hinder wider adoption. However, recent developments indicate a growing trend toward hybrid systems that combine AI with traditional decision-making models, increasing both accuracy and practical applicability. This review contributes to theory and practice by synthesizing current knowledge, highlighting research gaps, and identifying emerging directions such as the use of large language models, ensemble methods, and sustainability-focused project portfolio optimization. The findings highlight the transformative potential of AI in advancing PPM and provide valuable insights for researchers and practitioners seeking to design smarter, more adaptive, and more sustainable project portfolio management strategies.

Abstract: The purpose of this study is to analyze the relationships between project leadership style and performance, innovation work behavior and performance, and openness to experience and performance. A quantitative research method was employed, and the analysis was conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM) via SmartPLS software version 4.0.9.9. PLS-SEM was chosen for its suitability in analyzing complex models with multiple constructs and pathways, particularly in exploratory research contexts. The study surveyed 430 SME employees, selected through snowball sampling based on the accessibility of reliable participants—those who had already completed the questionnaire. PLS-SEM is especially effective for handling small to medium sample sizes, non-normal data distributions, and both reflective and formative constructs. It also prioritizes maximizing the explained variance of dependent variables and is well-suited for testing relationships between latent constructs. A five-point Likert scale was used to measure respondents’ agreement with statements related to the variable indicators, ranging from 1 (strongly disagree) to 5 (strongly agree). The data analysis included validity testing, reliability testing, significance testing, and hypothesis testing. The results indicate that project leadership style has a positive and significant relationship with performance. Similarly, innovation work behavior and openness to experience both show positive and significant associations with performance.

Abstract: This study was conducted along the Disparate River, located in the Huancavelica province of Peru. Within the river's marginal area, numerous residential constructions and infrastructures are at risk of incurring material, economic, and human damage. Consequently, a disaster risk assessment was undertaken with the purpose of preventing potential harm. The primary aim of the research was to evaluate the level of flood risk posed by the Disparate River in the Huancavelica district during the year 2024. To this end, a descriptive design was employed, utilizing the risk assessment tables from the "Manual for the Evaluation of Risks Originating from Natural Phenomena," Version 02, published by the National Centre for Disaster Risk Estimation, Prevention, and Reduction. Additionally, social, economic, and environmental data were collected through various methodologies, including observation, meteorological data acquisition, mapping, random household selection, and interviews. The study analyzed hazard, vulnerability, and associated risks of potential flooding, intending to propose measures for reducing risk through both structural and non-structural interventions. Following the analysis of the data collected from fieldwork and desktop research, it was found that both the hazard and vulnerability levels were high, leading to the conclusion that the risk associated with the Disparate River is significantly elevated for the structures located along its banks. Finally, a technical proposal was presented that aims to mitigate the flood risk and its consequences in the city.

Abstract: In this paper, we extend the multi-skilled resource-constrained multi-project scheduling problem (MSRCMPSP) by introducing the concept of multiple project types (MSRCMPMTSP). The study considers two categories of projects: investment projects, which generate positive net present values (NPVs), and mandatory projects, which result in negative NPVs but are required to be executed. To solve this problem, we employ a priority rule-based heuristic approach. Specifically, forward scheduling is applied to projects expected to yield positive NPVs, whether they are optional or mandatory. In contrast, backward scheduling is used for projects with negative NPVs, as this strategy minimizes the impact of excessive negative NPVs. The dataset for this study is constructed using the design of experiments (DoE) methodology, enabling a comprehensive evaluation of the proposed heuristic. We compare the performance of our approach against randomly generated schedules through extensive simulations. The results indicate that the heuristic is effective in addressing the MSRCMPMTSP.

Abstract: Critical utility projects cannot pause scheduled milestones without risking severe operational and regulatory disruptions. This study introduces U–CARE–PM, a six-component framework—Real-Time Continuity Gate (RTCG), Continuity–Compliance Gauge (CCG), Log-Scaled Catastrophic Risk (LSCR) index, Regulatory Feed Engine (RFE), Resource Allocation Matrix (RAM), and an optional Early Compliance Drift Indicator (ECDI)—designed to manage high-impact, low-probability (HILP) threats under continuous operations. A multi-case study was conducted across four anonymized organizations—engineering services, infrastructure construction, IoT water-tech, and a multinational energy–water operator—over a six- to twelve-month period. U–CARE–PM was integrated into existing ERP-BPMS or SCADA systems, with tiered implementations reflecting digital maturity. Data sources included operational logs, semi-structured interviews (8–15 participants per site), and Delphi panel validation thresholds (CCG = 0.85; LSCR = 10). Pilot deployments reduced downtime by 18–24%, lowered compliance breaches by 30–40%, and improved schedule adherence by eight points. One site prevented an estimated USD 1 million outage through near-real-time resource reallocation. While the ECDI occasionally generated false positives, it accelerated regulatory response and reduced overnight emergencies. Unlike static milestone-based controls, U–CARE–PM integrates real-time continuity metrics, log-based risk weighting, and continuous compliance updates. This framework offers a replicable, data-driven approach for nonstop infrastructure projects, enhancing resilience and agility in the face of catastrophic risks. Compared with existing literature on project resilience, it advances the field by shifting from retrospective control toward proactive, continuous risk-compliance management.