Mahdi Safa

Public transit agencies are increasingly expected to support smart city goals, but the existing assessment tools often examine transit technology, urban design, environmental performance, or service quality separately. This paper develops a multidisciplinary framework for assessing how ready a public transit system is for integration into a smart city environment. The framework organizes readiness into eight dimensions: technological integration, accessibility, mobility, sustainability and environmental impact, data security and privacy, resilience and adaptability, community engagement and feedback, and safety, security, and rider comfort. These dimensions are further divided into operational subcategories that can be examined using quantitative indicators, public documents, and expert ratings. The framework is applied to Austin, Texas, using CapMetro service information, static GTFS data, census and ACS data, public agency documents, and a short expert rating exercise. The Austin case indicates relatively stronger performance in sustainability and technology adoption, supported by electric and hybrid fleet investments, mobile fare payment, and real-time vehicle information. Lower scores are observed in resilience, community feedback, mobility, and spatial accessibility, particularly in areas where peripheral neighborhoods have limited stop coverage or long scheduled headways. The paper contributes a practical screening tool that can help planners identify where public transit systems are aligned with smart city objectives and where additional investment, governance, or data transparency is needed.

Human factors remain a leading cause of occupational accidents and fatalities in the construction industry. Although human factors are a major contributor to construction accidents, their relative impact across different construction subsectors has not been fully quantified. This study presents a comparative analysis of accident and fatality data from the U.S. Occupational Safety and Health Administration (OSHA) for three major construction subsectors, NAICS 236 (Construction of Buildings), 237 (Heavy and Civil Engineering Construction), and 238 (Specialty Trade Contractors) from January 2010 through June 2025. Seventy human-factor-related keywords were categorized into eight categories, and accident counts, fatality counts, and fatality rates, defined as the proportion of investigated cases that were fatal, were computed. Twenty-four high-frequency keywords (≥60 investigated accidents) were further analyzed across the three subsectors. Descriptive methods, including risk matrices, Pareto analysis, and category-level fatality rate comparisons, were applied to identify the factors contributing most to fatalities. Differences between subsectors were tested using permutation-based chi-square tests with Benjamini–Hochberg correction for multiple comparisons. Results indicate substantial variation in both frequency and severity among keywords. At the category level, cognitive or perceptual errors, procedural violations and unsafe acts, and judgment and awareness failures in equipment use showed significantly higher fatality proportions in Heavy and Civil Engineering Construction than in the other two subsectors, whereas at the keyword level only lost balance and inattention differed significantly once the correction was applied. The findings provide a data-driven basis for prioritizing targeted safety interventions and tailoring human factor mitigation strategies to subsector-specific risks.

Purpose ‑ This study examines how digital transformation strengthens fiscal resilience and administrative continuity in Ukraine under conditions of large-scale wartime disruption. The research addresses the structural challenges caused by infrastructure destruction, institutional pressure, and the need to sustain socio-economic stability during armed conflict. The paper aims to evaluate digitalization as a strategic mechanism for reinforcing state fiscal security and institutional adaptability. Methodology ‑ The study applies a systems-based analytical framework combining scientific abstraction, comparative analysis, and deductive reasoning. Empirical analysis uses time-series data for 2014–2025. Methodological triangulation and third-degree polynomial regression are employed to assess the relationship between GovTech implementation and fiscal resilience. Findings ‑ The findings show that public-sector digitalization has become a key driver of Ukraine’s institutional resilience. Regression analysis reveals a strong correlation (R² = 0.94) between the implementation of GovTech solutions, including Diia, NCTS, and AEO systems, and fiscal resilience. The study identifies a model of “forced technological adaptation,” in which wartime pressures accelerate modernization more effectively than conventional reforms, while workforce aging and resistance to digital technologies highlight the need for educational modernization and digital skills development.

This paper explores the relationship between human factors in construction safety and their effects on operational efficiency. It investigates how safety incidents resulting from human errors influence productivity, project timelines, and overall costs, while examining how strategic safety management can improve organizational performance. The study employs a mixed-methods design that combines quantitative statistical modeling with qualitative case analysis to ensure both empirical rigor and contextual depth (R² = 0.87, p < 0.001). Data were drawn from four construction firms, encompassing a sample of 120 employees across residential, commercial, and infrastructure projects. Variables such as training hours, fatigue levels, safety compliance, and technology adoption were analyzed against key operational performance indicators, including rework hours, schedule adherence, and productivity scores. Statistical analyses were performed using SPSS 29 and AMOS 28, incorporating descriptive statistics, regression analysis, and mediation testing to examine the pathways linking human factors, safety performance, and operational productivity. Reliability and validity were confirmed through Cronbach’s alpha and variance inflation factor (VIF) diagnostics. Results demonstrate that safety compliance acts as a mediating variable connecting training, fatigue, and technology adoption to measurable business outcomes. By providing a quantitative framework that links human factor management to operational efficiency, this research contributes to both construction management theory and practice, emphasizing safety as a strategic driver of performance and competitiveness.

A safety plateau in the construction industry has been reported in the US and Canada, which has prompted researchers to seek new factors affecting construction safety performance. Tapping into advancements in the theory of human and organizational behaviors can yield valuable new perspectives. Therefore, by leveraging the advancement of the Job Demand Control Support model in the field of occupational safety and health, this paper firstly tested the impact of one newly added hindrance stressor (i.e., interpersonal conflicts on construction sites) by researchers on organizational behaviors on the safety performance of construction workers, based on two cross-sectional studies in the US and Canada. Differentiations were made between conflicts with supervisors and conflicts with coworkers. One personal resource factor, i.e., individual resilience, was also considered in this paper. A “causal” chain that shows the mitigation impact of individual resilience on conflicts with supervisors or coworkers, and the adverse impact of conflicts with supervisors or coworkers, on unsafe events were found to hold true for both US and Canadian construction sites, based on the results from measurement invariance tests and structural equation modelling. Recommendations regarding how to improve construction workers’ individual resilience and reduce interpersonal conflicts on site, thereby reducing safety incidents on site, are provided.

The world’s supply chains are changing as both expected and unexpected environmental pandemics occur. Even though some may be expected, the full extent and ramifications a pandemic will have is an estimate at best. Thus, both flexibility and resiliency are becoming crucial to efficient supply chain systems. This study analyses the recent COVID-19 phenomenon and uses it to gauge reactions, best practices, resilience-based issues and operational performance metrics in order to assist with potential future pandemics. Education, as seen, plays a pivotal role in effectively offering options to combat uncertainty and fluid situations. Such dynamic environments have historically posed a serious problem to operations; however, with proper preparation and care taken options are available today that help marginalize harm of future pandemics.

The advent of technologies has created a need for a system that can provide better management and application of smart technologies in smart cities. The paper attempts to provide a review of legal and ethical considerations in adopting digital solutions for smart cities. There are challenges in terms of legal and ethical issues regarding the application of autonomous and near-autonomous vehicles, robotics technology, three-dimensional (3D) printing, mobile technology, and the Internet of Things that act as a primary or secondary source of new regulatory and legal challenges. The paper addresses the concerns through an extensive literature review and suggests a roadmap for better adoption of smart technologies in smart cities. The legal and ethical implications are observed in the examples of the digital payment, waste management, and contractual systems. This study focuses on the legal and ethical issues arising in the application of smart technologies in smart cities. The methodology focuses on the analysis of the literature review to derive some critical points to explain the impact of legal and ethical issues on smart city applications. The legal and ethical concerns are studied in terms of use of data, application of technology, proper functioning of technology, misuse of the data, commercialization of the data, and unwanted calls.

The presence of Xenobiotic Organic Compounds (XOCs) in municipal wastewater treatment plants’ effluent raises a global concern due to the easy consumption of these micropollutants by organisms. The fate of XOCs removal mechanisms of these compounds remains a challenge in recent scientific research. This study aimed to create an uncalibrated mathematical fate model within the professional wastewater modeling simulation software in a first step that was able to address the fate of Sulfamethoxazole (SMX), its metabolite, and Nonylphenol ethoxylates (NPEOs) along with conventional compounds during an activated sludge process. For the calibration process as a next step, two different case studies were created with assigning related removal mechanisms to each group of compounds. In the calibration process, model parameters are tuned such that the model can best simulate the experimental data using optimization methods. The validation results showed that the proposed model successfully simulates the removal of XOCs. Results of sensitivity analysis showed that the fate model is more sensitive to biodegradation rate constant than Solid Retention Time (SRT).