Search Results (29)

Background: Nurse-manager competencies shape workforce stability, yet role-based perception gaps between managers and staff may influence staff nurses’ turnover cognitions. Objectives: To (1) compare nurse managers’ self-ratings with staff nurses’ ratings of the same managers on the Nurse Manager Competency Inventory (NMCI); (2) compare both groups’ perceptions of staff nurses’ turnover intention (EMTIS); (3) examine domain-specific links between perceived competencies and perceived turnover intention; and (4) explore demographic influences (age, education, experience) on these perceptions. Methods: Cross-sectional dual-rater study with 225 staff nurses and 171 nurse managers in two tertiary hospitals in Saudi Arabia. Data were collected from August to November 2024. Managers completed NMCI self-ratings, and staff nurses rated their managers on the same NMCI domains; both groups rated staff nurses’ turnover intention using EMTIS. Between-group differences were tested with one-way ANOVA (two-tailed α = 0.05), and associations were examined with Pearson’s r (95% CIs). Findings: Managers consistently rated themselves higher than staff rated them across all nine NMCI domains; the largest descriptive gaps were in Promoting Staff Retention, Recruit Staff, Perform Supervisory Responsibilities, and Facilitate Staff Development (e.g., overall NMCI: managers M = 3.67, SD = 0.61 vs. staff M = 3.04, SD = 0.74; F = 0.114, p = 0.73)with comparatively smaller divergence for Ensure Patient Safety and Quality. Managers and staff did not differ significantly on EMTIS (overall EMTIS: managers M = 3.16, SD = 1.28 vs. staff M = 3.00, SD = 1.15; F = 21.32, p = 0.173). Specific competency domains—retention, supervision, staff development, safety/quality leadership, and quality improvement—showed small inverse correlations with EMTIS facets (typical r ≈ −0.11 to −0.19; p < 0.05), whereas the global NMCI–overall EMTIS correlation was non-significant (r = −0.077, p = 0.124). Effect sizes were modest and should be interpreted cautiously. Conclusions: Actionable signals reside at the domain (micro-competency) level rather than in global leadership composites. Targeted, continuous, unit-embedded development in human- and development-focused competencies—tracked with dual-lens (manager–staff) measurement and linked to retention KPIs—may help nudge turnover cognitions downward. Key limitations include the cross-sectional, perception-based design and two-site setting. Findings nonetheless align with international workforce challenges and may be transferable to similar hospital contexts. Full article

Key Performance Indicators (KPIs) play a crucial role in systematically evaluating employee performance. This study integrates the Simple Additive Weighting (SAW) method with Design Science Research (DSR) to develop and validate a web-based KPI assessment system for IT Support staff. This system categorizes performance into three key areas: supervisor evaluation, routine tasks, and request-based tasks. SAW is chosen due to its effectiveness in multi-criteria decision-making and the objective ranking of employees. This research presents a scalable and practical solution for performance management through a structured web-based application. A simulation utilizing Bootstrap 5.1 incorporates real-time monitoring, ticket tracking, and KPI dashboards, enhancing data visualization and reporting. The results indicate that the proposed system enhances transparency, minimizes evaluation bias, and supports objective, data-driven decision-making. By integrating SAW within a structured decision support system, this approach fosters standardized performance assessments, ensuring fairer and more consistent employee evaluations. Future work should focus on real-world implementation and empirical validation. Full article

Non-fungible tokens (NFTs) are an emerging application of blockchain technology, with the potential to transform various industries, including tourism. Despite conceptual discussions that have highlighted opportunities and challenges associated with using NFTs—such as in digital souvenirs, ticketing systems, loyalty programmes, and conservation initiatives—there is a critical gap in the literature consisting of the lack of a structured methodological framework to empirically evaluate the impact of real-world NFT implementations. This study addresses this gap by proposing a conceptual model and methodological framework designed to assess NFT projects in the tourism sector. The framework integrates diverse data collection methods, advanced analytical techniques (including econometric analysis, natural language processing, and machine learning), and a technological workbench for tracking key performance indicators (KPIs). To demonstrate its applicability, the framework is applied to the Dalmatia NFT project, an exploratory application in cultural tourism. The considered example highlights the potential of NFTs to enhance tourism experiences while addressing challenges such as scalability, sustainability, and user engagement. This study concludes with insights into the framework’s practical implications for stakeholders and outlines future research directions for empirical validation. By bridging the gap between theory and practice, this study aims to provide a robust foundation for effectively integrating NFTs into the tourism industry. Full article

In today’s competitive industrial landscape, effective performance measurement is crucial for achieving operational success. Key Performance Indicators (KPIs) are widely used to track progress, but their implementation often lacks a comprehensive framework that considers both financial outcomes and managerial insights. A quali-quantitative analysis model is introduced to optimize the implementation of KPIs in industrial settings, demonstrated through a case study of a Cambodian charcoal factory. By integrating Cost–Benefit Analysis (CBA) and Fuzzy Analytic Hierarchy Process (FAHP), the model combines both quantitative financial analysis and qualitative managerial evaluations to assess and rank a selected set of KPIs. This dual approach ensures a more comprehensive understanding of KPI impacts, enabling informed decision-making. The results highlight the critical need for balancing measurable financial benefits with qualitative insights, particularly in industries within developing nations that are forced to compromise in constrained environments, and where both economic outcomes and strategic considerations are essential for sustainable growth. Furthermore, the proposed model has universal applicability across different industrial contexts, providing a flexible and adaptable framework for KPI selection beyond the specific case study analyzed. Full article

This paper examines the use of interactive Google Sheets for the automatic measurement of key performance indicators (KPIs) in higher education, particularly in the context of academic accreditation. As institutions face increasing pressure to demonstrate quality and effectiveness, reliable data tracking and reporting have become essential. Traditional methods of managing academic records and performance metrics can be cumbersome and error-prone, underscoring the need for an automated solution. By leveraging Google Sheets’ dynamic capabilities, institutions can efficiently monitor KPIs related to student performance, curriculum effectiveness, and faculty qualifications. This approach allows for real-time data updates, facilitating timely insights that support accreditation processes and continuous improvement initiatives. The study outlines the design and implementation of a dynamic Google Sheets framework tailored to higher education KPIs, highlighting its benefits in enhancing data accuracy, reducing administrative burden, and fostering collaboration among faculty and administration. Through illustrative case studies, we demonstrate how this tool empowers institutions to meet accreditation standards and drive educational excellence. Ultimately, the research emphasizes the potential of automation to transform academic record management and enhance institutional accountability in higher education. Full article

The determinants of hospital project or healthcare project (HP) success are divergent and difficult to generalize because of the heterogeneous perceptions of various stakeholders. There is also a paucity of HP life cycle success evaluations from planning to post-construction phases. Meanwhile, the successful delivery and continual functionality of HPs are pivotal for sustainable development, as evident in the United Nations’ Sustainable Development Goal 3 about ensuring healthy lives and promoting wellbeing for all people. To contribute to sustainable development, a novel evaluation framework is essential to define robust metrics of selected key performance indicators (KPIs) for monitoring and controlling HPs at the life cycle phases thereof. Fuzzy set theory, namely the bisector error method (BEM), was applied to questionnaire survey outputs of an expert panel to establish performance metrics of HPs within five grades, namely, poor, average, good, very good and excellent. The novel evaluation framework comprising indexes, indicators and grades are demonstrated on hypothetical HPs to provide objective, reliable and practical outcomes for performance comparison, benchmarking and improvement purposes. The findings show that a high standard is required for excellent planning, execution, and performance in HPs. The life cycle success evaluation framework is foundational in policymaking. Thus, policymakers can track the success of HPs by linking the performance metrics to goals and policy priorities in benchmarking and strategic planning for sustainable development in HPs. Full article

Clinical trials inform cancer care, yet real-world outcomes often diverge due to patient-related factors, like age, organ dysfunction, and nonadherence to oral anticancer agents (OAAs). While oncology organizations emphasize patient support programs, practical guidance on designing and implementing these programs is limited. We conducted a two-phase, mixed-methods study to enhance the adoption, implementation, and sustainability of an OAA adherence program (OAP). In phase 1, we used implementation mapping (IM) with a multidisciplinary expert panel to develop six strategies: (1) memorandum of understanding (MOU), (2) data-driven presentation, (3) standard operating procedures (SOPs), (4) motivational interviewing (MI) training, (5) electronic health record (EHR) templates, and (6) key performance indicators (KPIs). In phase 2, oncology professionals (n = 34) completed surveys, and a subset (n = 10) participated in interviews to assess feasibility, acceptability, and appropriateness. EHR templates and SOPs were rated as the most feasible and acceptable strategies, while MI training and formal agreements received moderate ratings. Interviews highlighted the importance of leadership buy-in, incremental implementation, and clear documentation. Participants valued KPIs for tracking adherence and outcomes but noted resource constraints and staff workload as challenges. Using IM, we co-developed strategies to activate OAA adherence-focused clinical programs. Tools standardizing care, like EHR templates and SOPs, were highly endorsed. Future work will test these strategies in a hybrid trial to improve real-world oncology outcomes. Full article

Hospital projects or healthcare projects (HPs) are major contributors of greenhouse gas emissions, high energy consumption, and environmental pollution. These problems serve as a clarion call for the development of a standardized list of metrics that define the triple bottom line of sustainability performance, track sustainability progress, and allow for essential comparisons or benchmarking of HPs. Through a comprehensive literature review, a Delphi survey with experts, and a fuzzy synthetic evaluation, the ten most suitable key performance indicators (KPIs) were identified, categorized, and modeled into a normalized HP success index (HPSI). The HPSI comprises relatively weighted (in brackets) KPI categories, namely, ‘project prosecution performance’ (0.287), ‘project purpose performance’ (0.353), and ‘project people performance’ (0.360), for evaluating and comparing success levels of HPs. The HPSI provides understanding on the relative contribution levels of the standardized KPIs to achieve predictable life cycle success levels of HPs. Ultimately, it can be used by policymakers and practitioners to inform life cycle decision-making (e.g., resource/effort allocation toward important contributors to success) in HPs. Future studies should seek to develop a computerized HPSI system, by adding quantitative indicators and ranges of KPIs to current findings, to objectively and practically assess, monitor, benchmark, and improve HP success across the life cycle. Full article

An unavoidable adverse consequence of industrial development is the contamination of urban atmospheres. Deterioration of air quality leads to a decrease in the quality of life of the population, creates a lot of risks of serious diseases, and threatens to increase life expectancy. This phenomenon is particularly evident in many large Russian cities, where historically a powerful industry has developed. In recent decades, the Russian government has acknowledged environmental remediation as a pivotal priority for the National Development Goals. The dedicated funding from the National ‘Ecology’ Project in 2018–2024 allowed for large-scale public and private investments to address the problem of improving the air quality of urban areas in Russia. What is the effectiveness of this spending? In this article, we answer this question by analyzing the effectiveness of the Federal ‘Clean Air’ Project, part of the National ‘Ecology’ Project, which aimed to improve air quality in 12 of the most polluted Russian cities. We show that the project’s key performance indicators (KPIs) underwent significant changes over the 2018–2024 period. The emissions reduction target was lowered from 22% to 20%, the methodology for measuring pollution was revised, and new targets were set. One of the main reasons for this was the suboptimal quality of the data on which the initial plan was based. As a result, the revised emissions estimates produced by the project were found to exceed not only the target benchmarks but also the baseline. The planned targets are largely on track, and it is likely that the target of a 20% reduction in emissions from the 2017 baseline will be met. However, the link between the KPIs and the improvement in urban air quality is questionable. The initial phase of the ‘Clean Air’ Project was a valuable first step, particularly in establishing an air quality monitoring network and conducting detailed pollution assessments in 12 cities. However, to further improve project performance, it is essential to base project KPIs on estimates of air pollution-related health damage and economic losses. Full article

Environmental disturbances represent significant challenges to the performance and accuracy of autonomous systems, especially in marine environments, where their impact varies based on disturbance severity and the employed guidance law. This paper comprehensively investigates a marine target tracking system using time-domain simulations incorporating realistic environmental disturbances. Three guidance laws and four key performance indicators are analysed to evaluate system performance under disturbed and ideal conditions. A robust and systematic evaluation pipeline is developed and applied to a case study featuring a scaled tugboat model. This approach provides a reliable method to assess tracking accuracy and robustness in adverse conditions. The results are selected from a wide range of possibilities to show the effect of the disturbances on the selected target tracking motion control scenario with two manoeuvres and two environmental conditions. The results are measured through the selected key performance indicators, and several phases are identified for each manoeuvre to extend the analysis not only to the global KPI values but also to the partial values of defined phases. They reveal the quantitative effects of environmental disturbances, exposing different system behaviours and trends. These findings demonstrate the effectiveness of the proposed pipeline in quantifying tracking system performance, delivering useful understandings of the system under environmental disturbances. The broader implications of this study are substantial, offering enhanced predictive accuracy for the performance of the analysed systems, particularly in the context of target tracking. Furthermore, introducing numerical key performance indicators facilitates a more rigorous comparison of different system characteristics, enabling informed decisions in designing and optimising autonomous operations in challenging environments. Full article

The central aim of this paper is to present the Green Web Meter software, which is designed to support the measurement of the digital ESG performance of websites and web apps, as well as providing sound-based analytic tools for improving their overall quality. In this work, we will discuss the process our research team adhered to in order to provide a basic structure to the general framework of our tool, select a consistent set of KPIs that are suitable for automated real-time tracking, and determine the proper calculation methods to compute the final scores on which the ESG assessment is based. Specifically, we began from the analysis of the UNI PdR 147 guidelines on digital sustainability, highlighting the relevance of the quality construct, and subsequently selected three quality assessment models (E-S Qual, Sitequal, and Webqual 4.0) to define the core references to structure the basic framework. Starting from this general perspective, we proceeded to define the eight related KPIs and the individual scores based on the automatic calculations. Full article

Integrating renewable energy sources (RESs), such as offshore wind turbines (OWTs), into the power grid demands advanced control strategies to enhance efficiency and stability. Consequently, a Deep Fractional-order Wind turbine eXpert control system (DeepFWX) model is developed, representing a hybrid proportional/integral (PI) fractional-order (FO) model predictive random forest alternating current (AC) bus voltage controller designed explicitly for OWTs. DeepFWX aims to address the challenges associated with offshore wind energy systems, focusing on achieving the smooth tracking and state estimation of the AC bus voltage. Extensive comparative analyses were performed against other state-of-the-art intelligent models to assess the effectiveness of DeepFWX. Key performance indicators (KPIs) such as MAE, MAPE, RMSE, RMSPE, and R² were considered. Superior performance across all the evaluated metrics was demonstrated by DeepFWX, as it achieved MAE of [15.03, 0.58], MAPE of [0.09, 0.14], RMSE of [70.39, 5.64], RMSPE of [0.34, 0.85], as well as the R² of [0.99, 0.99] for the systems states [X₁, X₂]. The proposed hybrid approach anticipates the capabilities of FO modeling, predictive control, and random forest intelligent algorithms to achieve the precise control of AC bus voltage, thereby enhancing the overall stability and performance of OWTs in the evolving sector of renewable energy integration. Full article

The rapid development of active safety systems in the automotive industry and research in autonomous driving requires reliable, high-precision sensors that provide rich information about the surrounding environment and the behaviour of other road users. In practice, there is always some non-zero mounting misalignment, i.e., angular inaccuracy in a sensor’s mounting on a vehicle. It is essential to accurately estimate and compensate for this misalignment further programmatically (in software). In the case of radars, imprecise mounting may result in incorrect/inaccurate target information, problems with the tracking algorithm, or a decrease in the power reflected from the target. Sensor misalignment should be mitigated in two ways: through the correction of an inaccurate alignment angle via the estimated value of the misalignment angle or alerting other components of the system of potential sensor degradation if the misalignment is beyond the operational range. This work analyses misalignment’s influences on radar sensors and other system components. In the mathematically proven example of a vertically misaligned radar, pedestrian detectability dropped to one-third of the maximum range. In addition, mathematically derived heading estimation errors demonstrate the impact on data association in data fusion. The simulation results presented show that the angle of misalignment exponentially increases the risk of false track splitting. Additionally, the paper presents a comprehensive review of radar alignment techniques, mostly found in the patent literature, and implements a baseline algorithm, along with suggested key performance indicators (KPIs) to facilitate comparisons for other researchers. Full article

Resistance spot welding is a process with high variability regarding the quality of the produced joints. This means that key performance indicators (KPIs) such as geometrical and mechanical features as well as failure modes can deviate from the initial design even if the same process parameters are used. The industry has developed quality assurance programs and quality control methods for tracking these KPIs; however, most of them are based on offline or/and destructive practices. On the other hand, state-of-the-art approaches have made online quality assessment feasible and proved its necessity if a 100% quality rate is required. However, limited attention has been given to “closing the loop” and providing feedback for preventing and correcting process anomalies that cause quality variations in real time. In this study, the main gaps between the state of practice and the state of the art are discussed in the context of quality assurance for resistance spot welding. Finally, the role and importance of digital twins by taking into consideration the entire welding ecosystem in quality assurance are discussed in order to form the prospects for the road ahead. Full article

One of the most important challenges in the construction industry is to develop projects covering all three dimensions of sustainability: economic, social, and environmental. However, the construction project management literature lacks clarity regarding the fundamental principles and effective strategies for implementing sustainability for on-site construction processes. This article provides a comprehensive analysis of the sustainability dimensions in the construction sector, highlighting sustainability key performance indicators (KPIs) for on-site practices. The analysis stems from a systematic literature review sourced from the Web of Science and Scopus databases. The search identified 17 environmental, 20 social, and 15 economic indicators, with the most relevant being those associated with key terms such as cost, profit, labor, customer satisfaction, community impact, resource utilization, and contaminant management. The theoretical implications of this study contribute a critical framework for integrating the sustainability dimensions into construction practices, advancing the industry’s sustainability. For practitioners, the findings offer a prioritized guide to enhance on-site construction processes (O-SCP) sustainability and provide measurable KPIs for tracking progress toward sustainable development goals. This study not only sheds light on the current application of sustainability in O-SCP but also paves the way for future research to further this field. Full article