This study analyzes the effect of Capital Adequacy Ratio (CAR), Net Interest Margin (NIM), and Operational Efficiency Ratio (BOPO) on Return on Assets (ROA) in 36 banks listed on the Indonesia Stock Exchange (IDX) in 2024. The analysis was conducted using multiple linear regression, including a simple robustness test through winsorizing to reduce the influence of outliers. The results show that BOPO has a significant negative effect on ROA in both the original model (β = –0.086; p < 0.001) and winsorized data (β = –0.090; p = 0.000), while NIM has a significant positive effect in the original model (β = 0.096; p = 0.031) but is not significant after winsorizing (β = 0.075; p = 0.070), and CAR has no significant effect in both models. Simultaneously, all three independent variables influenced ROA (F = 87.036; p < 0.001). The regression model explained 89.1% of the variation in ROA in the initial model and 91.0% after winsorizing, confirming the stability of the results. These findings emphasize that bank profitability is significantly influenced by operational efficiency and net interest margin management, while capital adequacy does not contribute significantly. Robustness tests confirmed the validity of the model, showing that conclusions remained consistent even when the data was smoothed to remove outliers.

This study presents the design, development, and field evaluation of Vabot, an artificial intelligence (AI)-powered, fully electric autonomous agricultural ground vehicle intended for accurate pesticide application in orchard settings. The platform integrates a YOLOv5-based computer vision algorithm into the control system to enable real-time canopy detection and selective spraying. The main aim of the study was to evaluate the system's performance under real orchard conditions and compare two spraying mechanisms: a fixed-arm system and an oscillating-arm system. Field experiments were performed in apple orchards at Ankara University, Türkiye, to assess droplet size, spray coverage, canopy penetration, and operational efficiency. The oscillating-arm mechanism substantially enhanced spray uniformity and canopy penetration, achieving a coverage rate of 60.43%, compared with 14.87% for the fixed-arm configuration. Measured droplet sizes ranged 125-242 μm for the fixed-arm configuration and 147-182 μm for the oscillating-arm system, indicating a more homogeneous distribution in the latter. The field efficiency of the vehicle was calculated as 41% over a 1200 m2 area. These findings demonstrate the potential of AI-integrated autonomous systems to improve spray effectiveness, reduce pesticide usage, and minimize environmental contamination in orchards. The Vabot platform offers a practical and scalable solution for intelligent spraying in precision agriculture. Overall, the results highlight the synergy between AI and mechanical systems in delivering precise, efficient, and sustainable spraying performance in orchard environments. © 2026 Society of Chemical Industry.

Errors in the use of Q-Code in NOTAM publication can lead to miscommunication of information, which may negatively impact flight safety and operational efficiency. This study aims to analyze the factors causing Q-Code errors in NOTAM issued by the Notam Office Indonesia and to evaluate the impact and solutions to these problems. The research applies a qualitative approach through interviews with AIS personnel at the Notam Office Indonesia and an analysis of NOTAM documents that indicate potential Q-Code errors. . The findings show that the errors occur due to several factors, including limitations in the Q-Code reference within the Navgate application and incomplete or unclear raw data submissions from NOTAM originators. These errors result in stakeholder misinterpretation, disruptions to flight operations, and a decline in NOTAM data quality. As a form of mitigation, it is recommended to update the Q- Code database in Navgate and strengthen coordination between NOTAM proposing units and the Notam Office Indonesia. With these improvements, the overall quality of NOTAM can be enhanced to better support aviation safety.

Fe2+ primarily regulates nitrate nitrogen removal from groundwater in sulfur-driven autotrophic denitrification systems by regulating nitrite reduction.

Background Artificial Intelligence (AI) is increasingly integrated into oncology, offering opportunities to improve diagnostics, treatment planning, and operational efficiency. However, patient perspectives on AI, especially regarding data protection and ethical implications, remain underexplored. Objective The objective of this study is to investigate cancer patients' attitudes toward the use of Artificial Intelligence (AI) in healthcare, focusing on their awareness of data protection, perceived risks and benefits, and the conditions under which AI is considered acceptable. Additionally, the study aims to examine how demographic and educational factors influence patients' views within the context of an Italian comprehensive cancer center. Methods A cross-sectional survey was conducted with 117 cancer patients who completed a 28-item online questionnaire. The survey evaluated levels of AI knowledge, perceptions of data privacy, concerns about AI in medical contexts, and willingness to share health data for research. Results Most participants demonstrated moderate awareness of AI (70.1%) and its medical applications (85.5%), with higher familiarity observed among younger and more educated individuals. While data protection understanding varied, 76.9% were willing to share personal health data for research aimed at improving cancer care. Concerns included reduced physician autonomy (52.1%) and diminished physician-patient interaction (63.3%). However, 82.9% of respondents found AI acceptable when clinical decisions remained under physician control. AI was most favorably viewed for administrative support and care process optimization. Conclusion Cancer patients generally view AI in healthcare positively, especially when it maintains physician oversight and safeguards data privacy. To ensure equitable and informed adoption, targeted educational initiatives and transparent communication strategies should address generational, educational, and digital literacy differences.

This study aims to analyze the influence of education and training, personnel innovation, service orientation, and reward-punishment system on the implementation of reform in the Indonesian National Police (Polri). Institutional transformation requires strengthening the capacity of officers through systematic education and training, fostering innovation in policing tasks, focusing on public service orientation, and implementing fair reward and punishment mechanisms. The study employs a literature review method, reviewing 50 scholarly articles, national and international journals, and official Polri reports over the last ten years (2015–2025). The findings indicate that continuous education and training enhance technical and managerial competence, while personnel innovation promotes creativity and operational efficiency. Service orientation reinforces an organizational culture that is responsive to public needs, and the reward-punishment system ensures compliance with procedural and ethical standards. The integration of these four variables contributes significantly to the success of reform implementation. The literature emphasizes the need for education planning based on organizational needs, fostering operational innovation, enhancing service orientation, and applying a transparent and fair reward-punishment system. These findings provide a foundation for policymakers to design more effective, adaptive, and sustainable reform strategies, improving professionalism, accountability, and public trust in the institution.

Unlocking operational efficiency gains from construction robotics (CR) in commercial residential projects (CRPs) hinges critically on agile management rather than technology deployment alone. We propose the Construction Robotics Agile Success Model (CR-ASM), which formalizes feedback-driven, subproject-level mechanisms that convert localized CR productivity into project-wide gains. To test CR-ASM, we analyze 224 CRPs across 37 Chinese provinces using a dual-stage methodology combining partial least squares–structural equation modeling (PLS-SEM) and artificial neural networks (ANNs). Key findings reveal that time/budget/security constraints significantly compel top management commitment (β=0.723), which is the most significant driver of project success (β=0.702) through the sociotechnical capabilities of middle management. By contrast, direct CR work efficiency demonstrates a negligible influence on management commitment, positioning robotics as a catalyst rather than a direct efficiency driver. Multigroup analysis indicates core management pathways remain statistically indifferent between CR adopters and nonadopters, underscoring the primacy of agile practices. Complementary ANN results confirm project success as the overwhelming predictor of operational efficiency (57% normalized importance), validating the model’s nonlinear dynamics. By bridging technology and organizational strategy, CR-ASM advances understanding of how the construction management field can achieve project-wide efficiency gains and provides an empirical foundation for future research in construction engineering and management.

This study investigates the fluid-structure interaction dynamics induced by underwater explosive, focusing on the impact of localized damage effects of explosive on the transient interaction between plate structures. To accurately characterize this localized effect, numerical experiments were conducted on the damage to a steel plate subjected to underwater explosive shock under various charge and explosion distance conditions. Results indicate that the diameter of plate perforations caused by contact explosions is smaller than that under conditions with a certain explosion distance. By establishing the relationship between relative explosion distance and plate perforation diameter, the optimal range for the localized damage effect of explosive is determined to be a relative explosion distance of 1.1–2. Furthermore, the relationship between the impact factor and the structural dimensionless factor, established based on the plate damage results, conforms to a quadratic function dependency. This relationship characterizes the role of the local effect of the munition in the inherent local damage mechanism of the target structure. These research findings provide empirical guidance for enhancing the lethality of underwater weapons and optimizing the efficiency of underwater mining, underwater de-icing, and other engineering operations.

This research aims to analyze and synthesize findings from various empirical studies on the implementation of supply chain management (SCM) strategies and their impact on company performance in the 2014-2024 timeframe. This research uses the literature review method by collecting and analyzing relevant scientific articles from various sources, such as academic journals, conference proceedings, and research databases. The articles selected are empirical studies that directly discuss the implementation of SCM strategies and the measurement of company performance. The results of the literature review show that effective implementation of SCM strategies has a positive and significant impact on firm performance. SCM strategies that focus on increased collaboration with suppliers and customers, business process integration, efficient information sharing, and the use of information technology are proven to improve operational efficiency, reduce costs, improve product quality, speed up delivery times, and increase customer satisfaction. In addition, the research also highlights the importance of aligning SCM strategies with the company's overall business strategy to achieve optimal performance.

Inferring the structure of pedestrian flows at a transportation hub.

Development of a practical GMP-compliant manufacturing process for T cell-derived induced pluripotent stem cells.

This study aims to analyze and classify best-selling and least-selling products in the Babygear.Project store using the Naïve Bayes algorithm. The data used includes sales and user interaction data collected from the store management system, then a preprocessing stage is carried out to ensure data quality before being used in modeling. The testing process is carried out by dividing the dataset into training data and test data using a 60:40 ratio. The test results show that the Naïve Bayes model has an accuracy of 92.68%, with consistently high precision, recall, and F1-score values across both product categories. Further analysis reveals that the features of sales volume, purchase frequency, product category, product price, and user interaction are the most dominant factors in the classification process. The implementation of this model provides strategic benefits, especially in optimizing stock management, promotional planning, and data-driven decision making to improve operational efficiency and customer satisfaction. This study also opens up opportunities for further development, such as the addition of predictor variables, the use of larger datasets, and testing benchmark algorithms to improve prediction accuracy in the future.

The article examines marketing logistics as an integrated management system within transport enterprises, emphasizing its role in creating sustainable competitive advantages through the effective management of flows and delivery of services that preserve consumer value. In modern economic conditions, traditional isolated application of marketing and logistics tools often fails to ensure the achievement of strategic objectives, particularly under circumstances of high uncertainty, resource limitations, and disruptions in supply chains, such as those experienced during martial law. Marketing logistics emerges as an integrative mechanism that combines market-oriented approaches with process- and flow-oriented logistics, aligning demand generation with the enterprise’s operational capabilities. A critical review of domestic and international literature reveals a lack of unified conceptual understanding of marketing logistics. Foreign studies tend to interpret it from a logistics perspective, emphasizing operational efficiency and physical distribution, while domestic research increasingly views it as a comprehensive, integrative system that coordinates marketing and logistics decisions to achieve long-term competitive advantages. The article classifies approaches to marketing logistics into three groups: functional-distributional, integration-oriented, and value-oriented (synthetic), reflecting its evolution from a narrowly operational function to a strategic management concept. The study offers a conceptual generalization of marketing logistics as an integrated management system under conditions of high uncertainty. The study identifies key objectives and tactical tasks of marketing logistics, including ensuring full and timely satisfaction of consumer demand, optimizing logistics costs, maintaining service quality, enhancing resilience, and supporting sustainable development and digital transformation. The article further delineates the core functions of marketing logistics — analytical, planning, organizational, coordination, control, and value-oriented — demonstrating their integrative nature in harmonizing marketing and logistics processes. Comparative analysis highlights that marketing logistics not only delivers physical products but also generates additional value for the consumer by balancing service levels with operational efficiency. The findings underscore the relevance of marketing logistics as a holistic management tool for transport enterprises operating in dynamic and uncertain environments. Prospects for further research include the development of digital, data-driven, and adaptive approaches to enhance efficiency, resilience, and sustainability in marketing logistics processes.

Aim: The primary aim of this research is to design a unified architectural framework that seamlessly integrates microservices with DevOps practices, continuous integration and continuous delivery pipelines, and runtime orchestration mechanisms. The proposed framework addresses the growing complexity of managing distributed microservice systems in dynamic cloud-native environments by improving deployment consistency, operational efficiency, and system scalability while significantly reducing manual intervention across the software delivery lifecycle. Emphasis is placed on reliability, automation, and continuous feedback to enable faster, safer, and more resilient software delivery. Method: This study adopts a system-oriented architectural design approach that combines conceptual modeling with workflow abstraction. Existing microservices architectures, DevOps workflows, and orchestration platforms are systematically analyzed to identify integration gaps and operational inefficiencies. Based on this analysis, a layered architectural framework is proposed to unify development, deployment, and runtime management. The framework incorporates standard DevOps tools, CI/CD automation strategies, and container orchestration principles, with logical workflows validated through representative architectural scenarios. The methodological focus remains on modularity, interoperability, and end-to-end automation. Results: The results demonstrate that the proposed framework improves deployment frequency and reduces system downtime through tight integration of CI/CD pipelines with orchestration engines, enabling automated scaling and rollback mechanisms. Centralized monitoring and logging enhance operational observability, while the unified architecture supports continuous delivery with minimal configuration overhead. Performance analysis further indicates faster system recovery and improved fault isolation, confirming the effectiveness of the unified architectural approach. Conclusion: In conclusion, this research establishes that integrating DevOps practices, CI/CD pipelines, and runtime orchestration within a unified microservices architecture significantly enhances system manageability and reliability. The framework reduces operational complexity while ensuring deployment consistency and rapid feedback across the software lifecycle. Its adaptability to diverse cloud-native platforms positions it as a strong foundation for future intelligent, autonomous, and self-healing software systems.

The success of every organisation depends on her financial capacity, which plays a fundamental role in production. In recent time, poor financial capacity among industries in the Nigerian productive sector has resulted into poor internal Control policies. This study investigated the impact of internal control and financial performance on small and medium scale enterprises in Kebbi State, Nigeria. A descriptive survey design research was adopted. The estimated workers’ population of all respondents selected as of 2025 were 2,200 which consist of CEO’s, Managers, and Internal control units of the various SMEs in Kebbi State, Nigeria. A total of 338 respondents were sampled for the study using simple random sampling technique. A self-designed questionnaire was administered. The Pearson Product Moment Correlation Coefficient Analysis was employed to test the five hypotheses with a two-tailed test of significance at P<0.01 level. The results revealed that there is a significant relationship between individual internal control components and financial performance of small and medium enterprises in Kebbi state Nigeria. There also exists combined relationship between the internal control components (control environment, risk assessment, control activities, monitoring, information, and communication) and financial performance of small and medium enterprises in Kebbi state NNigeria. The study recommends regular and timely financial audits to help SMEs detect any gaps in their financial systems and financial performance. The management of the SME should conduct an annual evaluation of the financial reporting process and implement an internal audit system that permits monitoring of operational efficiency. The study also suggests that a frequent risk assessment be conducted so that SME management may determine whether or not their goals will be reached. In addition to implementing proper controls in the custody and disposal of assets, the management of a small to medium-scale enterprise (SME) should consider; control activities and information, and communication in order to improve financial performance.

This study aims to analyze the implementation of Management Information Systems (MIS) in a state-owned mining company, with a case study of PT Aneka Tambang Tbk. The mining industry is characterized by complex operations that require integrated and accurate information to support managerial decision-making. This research adopts a qualitative descriptive approach using secondary data derived from ANTAM’s 2024 Annual Report and recent academic literature. The results indicate that Management Information Systems plays a strategic role in supporting operational efficiency, financial performance monitoring, sustainability management, and corporate governance. The findings demonstrate that Management Information Systems contributes to improved decision-making quality and organizational performance in state-owned mining enterprises. This study provides academic and practical insights into Management Information Systems implementation within capital-intensive and sustainability-driven industries. This study contributes to the literature on Management Information Systems implementation in capital-intensive state-owned enterprises by providing empirical insights from the mining industry

Proper allocation of resources within the Emergency Departments (EDs) is very important in enhancing patient outcomes, wait times, and operational efficiency. The following paper introduces a Hybrid Simulation-Optimization Approach, which is a hybrid of the Discrete-Event Simulation (DES) and optimization algorithms in the allocation of resources, including medical staff, beds, and equipment dynamically. The implementation of the model was based on real-life ED data available in a hospital in a metropolitan city, and the model was compared to the traditional cloud-based and heuristic resource allocation models. The findings indicated a great improvement using the Hybrid Simulation-Optimization Model with 85 percent staff utilization, 4.5 patients treated / hour per staff member and 15 percent staff idle time, in comparison to Cloud-Based System that achieved 70 percent staff utilization and the staff-patient ratio was 1:6. More so, the Hybrid Model cut patient waiting time to 10 minutes as compared to the Cloud-Based System that recorded 15 minutes. These results pinpoint the power of the integration of Simulation and optimization to optimize the allocation of staff, manpower, and usage of resources in EDs. The staff-patient ratio was also streamlined to 1:4, which allowed enhancing the balance of work. The results of the staff utilization and patient care time improvements prove the usefulness of real-time information integration and optimization algorithms. Further studies on the subject should aim at extending the method to multiple hospitals, adding real-time data feeds, and machine learning algorithms to better predict demand and allocate resources, eventually enhancing the management of healthcare resources in a wide range of EDs.

This study examined the relationship between digital transformation (DT), strategy execution (SE), and operational efficiency (OE) in Uganda's medical facilities. Although digital adoption is promoted in healthcare modernization, little is known about its performance implications in low-resource settings. The study explored both direct and indirect effects of DT on OE, with SE as a mediator. A mixed-methods design was employed using quantitative structured questions and qualitative open-ended interviews. Data were collected from 60 heads of public and private medical facilities, including 12 purposively selected key informants for contextual depth and validation. Partial least squares structural equation modeling (PLS-SEM) tested the hypothesized relationships among DT, SE and OE, guided by the technology-organization-environment (TOE) framework and dynamic capabilities theory (DCT). DT did not directly affect OE but significantly enhanced SE, which strongly improved OE. SE fully mediated the DT-OE relationship, underscoring the role of execution capabilities in translating digital initiatives into performance outcomes. The study reveals that digital transformation alone does not enhance operational efficiency in Uganda's medical facilities; rather, its impact is realized through effective strategy execution. Policymakers should focus on integration, governance and capacity-building beyond technology adoption. The research extends TOE and DCT frameworks, emphasizing managerial execution, contextual alignment and institutional capability as key to realizing digital value. It informs curriculum design by advocating training in digital governance, strategy, and change management to build leadership capacity. Societally, successful digital health outcomes depend on governance quality and execution, not technology alone. Future longitudinal studies should explore moderating factors influencing sustainable digital health reforms. Policymakers should align digital investments with strategic goals, emphasizing interoperability, workforce readiness and sustainable financing. The findings highlight that digital health success in low- and middle-income countries (LMICs) depends more on execution quality and governance than technology adoption. The findings of this study have significant societal implications for Uganda's healthcare sector and similar LMIC contexts. The evidence that digital transformation does not directly enhance operational efficiency, but rather operates through effective strategy execution, highlights that technology alone cannot improve public health outcomes, patient satisfaction or equity in access to care. This means that while the introduction of digital tools such as electronic health records, e-prescriptions and telemedicine platforms has the potential to enhance service delivery, their societal value depends on how effectively they are implemented, aligned with strategy and integrated into patient-centered workflows. This study contributes novel empirical evidence from LMICs, emphasizing organizational and managerial enablers leadership, process alignment and executional capacity as true drivers of digital value creation. Integrating quantitative and qualitative insights, it offers actionable guidance for policymakers and practitioners.

Purpose This study aims to investigate the impact of self-service technologies on customer experience in the food service sector, with a specific focus on small food service enterprises operating in food halls. Design/methodology/approach A multiple-case study was conducted involving small food service enterprises operating within a food hall operation. Findings The study findings shed light on how self-service technologies drive customers' experiences in food hall operations. First, research findings show that these businesses benefit from operating in a food hall environment with automated customer service. Second, the adoption of self-service technologies contributes to resource optimization by reducing direct labor costs and enhancing business and food hall competitiveness. Third, findings reveal a significant reduction in operational costs and an increase in customer service efficiency, further facilitated by complementary product portfolios that enable the companies to expand their offerings to consumers. Research limitations/implications Self-service technologies enhance customer satisfaction by improving efficiency, convenience and speed, particularly during disruptions in food halls. Customers are increasingly adopting these technologies for their convenience, reducing staffing needs, cutting costs and ensuring quick service. Aligned with protection motivation theory, self-service platforms offer benefits such as safety, convenience and autonomy, encouraging adoption. To maximize engagement and satisfaction, service design should focus on user-centered, intuitive interfaces that reduce friction and promote ease of use, ultimately boosting both operational efficiency and customer experience. Practical implications This study offers new insights for scholars, trade associations and small food service operations that implement self-service technologies to enhance the service encounter, examining their effects on key business aspects such as staffing levels and purchasing process dynamics. Originality/value The article enhances the existing literature on service operations and food services by addressing knowledge gaps related to the use of self-service technologies in food hall operations, a relatively underexplored topic.

ABSTRACT Surface mines supply more than 96% of the raw minerals used across industrial sectors, making its transportation systems a critical component of operational efficiency and environmental performance. This study develops an integrated stochastic discrete–continuous simulation-based optimization framework for transportation decision-making in surface mining operations. The framework couples a mixed-integer linear programming (MILP) optimization model with a discrete–continuous simulation model to evaluate system performance under operational uncertainty. The proposed approach simultaneously considers economic and environmental objectives by minimizing transportation costs while reducing greenhouse gas (GHG) emissions. The framework is applied to an operating surface copper mine to determine the optimal size of the transportation fleet. Results demonstrate that the integrated simulation–optimization approach improves transporter waiting time at loading points by 33%, leading to a 3.5% increase in production. In addition, the framework enables significant environmental benefits, achieving a 72% reduction in carbon dioxide emissions. Sensitivity analysis is conducted to evaluate the influence of key operational parameters on system performance and to examine trade-offs between cost efficiency and emission reduction.