Management Model Research Articles

Barriers and facilitators to the delivery of a biopsychosocial education and exercise programme for patients with chronic low back pain in Ghana. A qualitative study

Purpose Low back pain management has evolved with researchers advocating for a biopsychosocial management model. The biopsychosocial management model has been predominantly applied in high-income countries and underexplored in low- and middle-income countries including Ghana. This study aimed to explore the potential barriers and facilitators to patients with chronic low back pain (CLBP) and physiotherapists engagement with a biopsychosocial intervention (exercise and patient education) as part of a feasibility study. Material and methods This was a qualitative study embedded within a mixed-methods, sequential, feasibility study, in Ghana, applying semi-structured interviews. Two categories of participants involved in this study were, two trained physiotherapists, and six patients with CLBP, sampled within the feasibility study. Results Regarding the barriers and facilitators to the delivery of the BPS intervention, five interlinked themes emerged from the thematic analysis. These were: structure and process of delivery; patients’ expectations; patients’ health beliefs, autonomy, and engagement; external influences and personal and professional characteristics of physiotherapists. Conclusion The themes that emerged from this study demonstrated many positive facilitators based on participants’ improved understanding of LBP and the clarity and purpose of the biopsychosocial intervention. The results therefore demonstrate a potential to deliver the biopsychosocial intervention in a Ghanaian context.

Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach

Sustainable forest resources management model through Pythagorean fuzzy MEREC–MARCOS approach

Challenges and opportunities of digital transformation in Ukrainian education

An important and necessary trend in the modern Ukrainian education system is the digitalisation of the educational process due to the forced transition of many educational institutions to distance learning due to the coronavirus pandemic and the Russian-Ukrainian war. The purpose of the article is to theoretically substantiate the challenges and opportunities for the introduction of digital learning technologies in Ukrainian educational institutions. The following methods were used to write the article and to reveal its purpose: conceptual and terminological analysis, comparative and contrastive analysis, analysis, synthesis, comparison, classification, systematisation and generalisation. The study found that, despite the many opportunities provided by the digital learning environment, including the development of software applications for the development of students' practical experience and access to high-quality and diverse sources of information, the education system in Ukraine needs to rethink the content, determine models of digitalisation of educational institutions, master the digital competencies of all participants in the educational process, and actively use the tools of Google Meet, Zoom, Microsoft Teams, and Cisco Webex, It is determined that the services are not without drawbacks in use, but their effective use contributes to digitalisation. The scientific novelty of the obtained results lies in the interpretation of the concept of “challenges of introducing digital technologies in education” and the identification of the main obstacles and ways to ensure the process of digitalisation of education. The conclusions recommend ways to overcome the difficulties of digitalisation of education, in particular, the need to create a model of digital transformation of an educational institution based on three models: a functionally independent model of information management; a concentric model of information technology for digital transformation of an educational institution; and a model of interlayer information interaction. Prospect for further research is to study the mechanisms for adapting teacher training systems to the use of digital technologies in the classroom.

Portfolio construction using explainable reinforcement learning

AbstractWhile machine learning's role in financial trading has advanced considerably, algorithmic transparency and explainability challenges still exist. This research enriches prior studies focused on high‐frequency financial data prediction by introducing an explainable reinforcement learning model for portfolio management. This model transcends basic asset prediction, formulating concrete, actionable trading strategies. The methodology is applied in a custom trading environment mimicking the CAC‐40 index's financial conditions, allowing the model to adapt dynamically to market changes based on iterative learning from historical data. Empirical findings reveal that the model outperforms an equally weighted portfolio in out‐of‐sample tests. The study offers a dual contribution: it elevates algorithmic planning while significantly boosting transparency and interpretability in financial machine learning. This approach tackles the enduring ‘black‐box’ issue and provides a holistic, transparent framework for managing investment portfolios.

A Blockchain-Based Model for Traceability and Quality Management of Raw Materials in Clothing Products

In this study, we employ blockchain-based traceability technology to construct a comprehensive model for raw material traceability and quality management in clothing products. Additionally, we investigate engineered water nanostructures (EWNS) for their antibacterial, hydrophilic, and anti-pilling effects on textiles. The EWNS can serve as an effective tool for monitoring quality, enabling precise tracking and verification of nanomaterials during clothing production. The research validated the traceability performance of the blockchain-based model for raw material traceability and quality management in clothing products, achieving a remarkable traceability accuracy of 99.92% and an exceptionally low traceability response time of merely 1.83 seconds. Moreover, after being treated with EWNS, antibacterial rates against E. coli and S. aureus in clothing antibacterial quality management reached 99.9% and 99.0%, respectively. In the hydrophilicity test, EWNS was applied to clothing for a duration of 1 to 7 hours, resulting in a significant reduction in the wetting time of clothing from 10.8 seconds to 1.2 seconds. In the anti-pilling tests, there was a notable enhancement in the effectiveness of anti-pilling properties after EWNS treatment. In summary, our model has achieved remarkable outcomes in material traceability and quality management, offering consumers and the clothing industry a reliable method to ensure product quality and traceability, while simultaneously improving performance aspects such as antibacterial efficacy, hydrophilicity, and resistance against pilling.

Một số giải pháp hoàn thiện công tác quản trị chất lượng toàn diện tại ngân hàng

Facing intensifying competition from domestic and foreign banks, enhancing service quality and customer satisfaction is a prerequisite for Vietnamese commercial banks (VCBs) to ensure sustainable development. Total Quality Management (TQM) has emerged as a breakthrough solution, providing the key to success in this challenging landscape for all organizations, regardless of industry.TQM is a management model that starts with leadership commitment, through communication and the involvement of all members of the organization to build a customer-centric culture together, towards the common goal of the organization is to develop and develop sustainably through continuous improvement of product/service quality, meeting customer needs and increasing competitiveness.Therefore, the effective application of TQM will help VCBs create a customer-centric culture, improve operational efficiency and optimize profits. Using a theoretical research method, the author has synthesized and analyzed data from many reputable sources such as documents, books, newspapers, and specialized journals. Thereby, analyzing the current status of TQM application in VCBs, comprehensively evaluating the strengths and weaknesses, and proposing a number of solutions to improve the work of total quality management in VCBs.

Một số giải pháp hoàn thiện công tác quản trị chất lượng toàn diện tại ngân hàng

Facing intensifying competition from domestic and foreign banks, enhancing service quality and customer satisfaction is a prerequisite for Vietnamese commercial banks (VCBs) to ensure sustainable development. Total Quality Management (TQM) has emerged as a breakthrough solution, providing the key to success in this challenging landscape for all organizations, regardless of industry.TQM is a management model that starts with leadership commitment, through communication and the involvement of all members of the organization to build a customer-centric culture together, towards the common goal of the organization is to develop and develop sustainably through continuous improvement of product/service quality, meeting customer needs and increasing competitiveness.Therefore, the effective application of TQM will help VCBs create a customer-centric culture, improve operational efficiency and optimize profits. Using a theoretical research method, the author has synthesized and analyzed data from many reputable sources such as documents, books, newspapers, and specialized journals. Thereby, analyzing the current status of TQM application in VCBs, comprehensively evaluating the strengths and weaknesses, and proposing a number of solutions to improve the work of total quality management in VCBs.

Mechanistic indoor air quality model and data-driven calibration for intelligent HVAC AI control system through real-time data in underground buildings

Abstract Modeling the dynamics of indoor air quality (IAQ) in subway environments is challenging due to the complex interplay of variables like subway schedules, ventilation, and passenger numbers. This study developed a high-precision mechanistic model for IAQ management and intelligent HVAC control in underground buildings, focusing on Y-station. Global Sensitivity Analysis (GSA) highlighted the significance of the train piston factor during operational hours and the increased sensitivity of penetration and deposition factors when trains are not operational. The model, calibrated in real-time using a Genetic Algorithm (GA), exhibited remarkable accuracy in simulating PM2.5 levels, affirming its effectiveness in forecasting future air quality. The model adeptly captures the complexities of air quality dynamics, providing a comprehensive understanding of temporal IAQ variations. The result demonstrates the model’s efficacy as a tool offering a foundation for strategies to forecast IAQ and control the HVAC system in underground buildings.

Energy management enhancement of a smart home supplied by renewable energy system

Solar energy is a reliable and eco-friendly solution for power outages in Karbala, Iraq. This study presents a smart grid technology model for energy management in electrical systems, optimizing power schemes and economic benefits through a unique spatial distribution approach in Iraq, with the primary objective of ensuring consistent base loads for smart homes while achieving other economic goals. The algorithm’s effectiveness was tested in three different scenarios. The energy was supplied by the national grid and battery bank-powered base loads. Meteorological data, including temperature and solar radiation, was gathered from a station in Karbala city for testing and evaluation. The study found that energy consumption decreased by 85% in April, with solar energy accounting for 37% of the total consumption. Smart homes saved 48% of energy, reducing reliance on the grid to 15%, as well as the reduction of energy consumption reached up to 47% and 60% in January and July, respectively, with solar energy estimated at 14% and 26% in those months.

Providing an innovative model for social customer relationship management: Meta synthesis approach

Social Customer Relationship Management (SCRM) has revolutionized the interaction between companies and customers, creating new opportunities and challenges for both parties. This study aims to present an innovative model for identifying the dimensions and components of SCRM. The data were collected based on a qualitative research design utilizing the meta-synthesis method, following the seven steps outlined by Sandelowski and Barroso (2007). Considering the relevance to the research topic and the quality of sources, 31 studies were selected for the final evaluation. To assess the reliability of the findings, the kappa coefficient for inter-coder agreement was used, resulting in a kappa value of 0.79. The results, analyzed using MAXQDA20 software, 2 dimensions, 6 categories, and 16 concepts identified. The company-focused dimension included 3 categories: factors influencing adoption, inhibitors, and outcomes of implementation. Similarly, the customer-focused dimension identified 3 categories: factors influencing adoption, inhibitors, and outcomes of implementation. Ultimately, a comprehensive model for SCRM was developed. The results of this research can be utilized by academic references as well as companies and consumers.

Turning peril into opportunity: Construction and validation of a resilience assessment system for China's coastal megacities

Enhancing urban resilience and strengthening risk resistance capacities have emerged as pivotal concerns in the construction and governance of contemporary urban landscapes globally. Given the uniqueness of coastal megacities in terms of geography and population, a more targeted and effective resilience assessment is urgently needed. This investigation develops a comprehensive, multidimensional index system to assess the resilience life cycle of China's coastal megacities. First, we creatively introduce the process perspective of the 4R model of crisis management into urban resilience assessment, revealing the preventive, defensive, recovery, and transformative resilience of China's coastal megacities. Second, we propose a spatio-temporal assessment matrix that integrates four processes of urban resilience and six representative subsystems in coastal megacities: social, economic, ecological, infrastructural, technological, and institutional. Third, we select 59 indicators to construct a three-level assessment index system for China's coastal megacities. This index system is strictly screened and optimized through qualitative and quantitative methods. Fourth, we validate the assessment system using Qingdao's data by calculating an urban resilience index and analyzing trends. We find the most important improvement goals and resilience enhancement suggestions for Qingdao by analyzing the indicator sensitivity. This study contributes to the development of urban resilience theories and identifies weaknesses in different dimensions to strengthen and improve the resilience of coastal megacities.

Portability rules detection by Epilepsy Tracking META-Set Analysis

Epilepsy is a severe and common neurological disease that causes sudden and irregular seizures, necessitating patient-specific detection models for effective management. The proposed methodology, Epilepsy Tracking META-Set Analysis, establishes portability rules that identify similar patients, enabling the transfer of these detection models from one patient to another. Main issue is to identify clusters of patients analyzing a set of meta-features of each patient in terms of clinical descriptors, performance metrics of a machine learning model for seizure detection, and data complexity measures. The investigation of complexity measures represents a novelty in such a medical field, allowing to compare patients and to support automated seizure detection methods. The proposed methodology is validated using the well-known Epileptic Seizure EEG Database from the Epilepsy Center of the University Hospital of Freiburg and demonstrates promising results in transferring detection models to new cases.

Dynamic incentive mechanisms in mega project-risk management considering the participation of the insurance company

PurposeThe construction of megaprojects often involves substantial risks. While insurance plays an important role as a traditional risk transfer means, owners and insurance companies may still suffer huge losses during the risk management process. Therefore, considering the strong motivation of insurance companies to participate in the on-site risk management of megaprojects, this study aims to propose a collaborative incentive mechanism involving insurance companies, to optimize the risk management effect and reduce the risk of accidents in megaprojects.Design/methodology/approachBased on principal-agent theory, the research develops the static and dynamic incentive models for risk management in megaprojects, involving both the owner and insurance company. The study examines the primary factors influencing incentive efficiency. The results are numerically simulated with a validation case. Finally, the impact of parameter changes on the stakeholders' benefits is analyzed.FindingsThe results indicate that the dynamic incentive model is available to the achievement of a flexible mechanism to ensure the benefits of contractors while protecting the benefits of the owner and insurance company. Adjusting the incentive coefficients for owners and insurance companies within a specified range promotes the growth of benefits for all parties involved. The management cost and economic benefit allocation coefficients have a positive effect on the adjustment range of the incentive coefficient, which helps implement a more flexible dynamic incentive mechanism to motivate contractors to carry out risk management to reduce risk losses.Originality/valueThis study makes up for the absence of important stakeholders in risk management. Different from traditional megaproject risk management, this model uses insurance companies as bridges to break the island effect of risk management among multiple megaprojects. This study contributes to the body of knowledge by designing appropriate dynamic incentive mechanisms in megaproject risk management through insurance company participation, and provides practical implications to both owner and insurance company on incentive contract making, thus achieving better risk governance of megaprojects.

Attentional Biases and Nonsuicidal Self-Injury Urges in Adolescents.

Nonsuicidal self-injury (NSSI) is a significant clinical concern among adolescents. Exposure to NSSI-related content on social media platforms has been suspected to potentially act as a trigger for NSSI. To use free-viewing eye-tracking and dot-probe paradigms to examine attentional bias and psychophysiological responses to NSSI-related pictorial and textual stimuli in adolescents with and without a history of NSSI. From June 2022 to April 2023, adolescent participants in Vienna, Austria with and without a history of NSSI were exposed to NSSI-related stimuli in this nonrandomized controlled trial. Data were analyzed from December 2023 to January 2024. Exposure to NSSI-related stimuli. During both tasks, subjective arousal, NSSI urges, and autonomic nervous system activity were assessed. A total of 50 adolescents in 2 groups, 25 who engaged in NSSI (mean [SD] age 15.86 [1.14] years; 19 female participants [76%]) and 25 who did not (mean [SD] age 16.40 [1.71] years; 19 female participants [76%]) were included. Adolescents with a history of NSSI-but not those without a history of NSSI-showed a clear attentional bias toward NSSI-related images during eye-tracking, as indicated by increased initial fixations (500 ms stimulus presentation mean difference, 28.64%; 95% CI, 18.31%-38.98%; P < .001; 1000 ms stimulus presentation mean difference, 18.50%; 95% CI, 9.05%-27.95%; P < .001) and longer fixation durations (500 ms mean difference, 29.51 ms; 95% CI, 4.3-54.72 ms; P < .001; 1000 ms mean difference, 39.83 ms; 95% CI, 6.90-72.76 ms; P < .001), regardless of stimulus duration. This bias was associated with a heightened urge to engage in NSSI (d = 1.22; 95% CI, 0.69-1.73; P < .001), a trend not seen in adolescents without a history of NSSI. Similarly, in the dot-probe task, only the NSSI group showed an attentional bias toward NSSI images but not toward trauma images, emphasizing the specificity of their attentional bias. Physiological measures revealed no significant differences, suggesting that viewing NSSI images is not associated with increased autonomic arousal. Textual NSSI content did not provoke an attentional bias or heighten NSSI urges in either group. In this nonrandomized controlled trial of 50 adolescents, results highlighted a specific attentional bias toward NSSI-related pictorial stimuli in adolescents with a history of NSSI, particularly a difficulty in disengaging from NSSI images. These findings contribute to understanding maladaptive information processing in NSSI and suggest implications for clinical management and cognitive models addressing NSSI triggers. German Clinical Trials Register identifier: DRKS00025905.

Integrated environmental management and GPS-X modelling for current and future sustainable wastewater treatment: A case study from the Middle East

In the context of today's rapidly changing environmental challenges, accurately predicting the performance and efficiency of environmental management strategies is crucial. Particularly in the Middle East, where research on wastewater treatment plants (WWTPs) is notably lacking, addressing this need is imperative. This study investigates the treatment efficiency of a wastewater treatment plant and proposes various techniques to enhance its performance. Employing a case study method, we utilise the GPS-X model to forecast the plant's performance under diverse scenarios, offering solutions for future challenges. The results reveal that the current plant layout operates efficiently, with removal efficiencies for Total Suspended Solids (TSS), Chemical Oxygen Demand (COD), and Biochemical Oxygen Demand (BOD) at 98.3 %, 95.1 %, and 96.1 %, respectively. The outlet Dissolved Oxygen (DO) of 1.9 mg/L meets local wastewater reuse standards. Furthermore, the GPS-X model forecasts the plant's performance under different scenarios, suggesting the feasibility of a new layout within 20–25 years and the need for additional units after 40 years. As inflow approaches maximum design capacity, simulation results underscore the importance of utilising the full plant design and expanding it for optimal operation over 60 years. This research provides critical insights for improving WWTP performance and emphasizes the significance of strategic planning in addressing long-term environmental management challenges. Moreover, this study represents a pioneering effort in addressing critical water scarcity challenges in Jordan by exploring the potential of treated wastewater (TWW) as a sustainable solution, thus contributing to the advancement of environmental management practices in the region.

Study on the Influence of Agricultural Scale Management Mode on Production Efficiency Based on Meta-Analysis

Agricultural scale management is an important means of improving agricultural production efficiency. To answer the controversy over whether different agricultural scale management models can improve production efficiency, this paper obtained 117,627 samples from 68 domestic and foreign literature and used meta-analysis to study the effects of land-scale operation (LSO) and service-scale operation (SSO) on agricultural production efficiency (APE). The moderators that affect the relationship between LSO, SSO, and APE are also examined. The research results show that (1) both LSO and SSO positively impact production efficiency, but LSO has a stronger impact. (2) The relationship between LSO and APE is positively regulated by the agricultural production and operation environment, characteristics of the agricultural location, degree of farmers’ participation, and types of APE, and negatively regulated by the research situation. (3) The relationship between SSO and APE is negatively regulated by APE types and data types. Therefore, the government should promote agricultural dual-scale operation according to the local conditions through the complementary advantages of LSO and SSO, so as to fully release the promotion potential of APE.

Smart Patient Consent Management Model for Health Information Exchange Based on Blockchain Technology

Smart Patient Consent Management Model for Health Information Exchange Based on Blockchain Technology

Clinical Pharmacy Services in a Neurosurgical Intensive Care Unit in Iran: A Focus on a Comprehensive Medication Management Model

Clinical Pharmacy Services in a Neurosurgical Intensive Care Unit in Iran: A Focus on a Comprehensive Medication Management Model

BI in simulation analysis with gaming for decision making and development of knowledge management

Increasing technology advancements have led to a number of problems with modern corporate decision-making, which is a challenging occurrence in the absence of business intelligence and machine learning (ML). Because effective decision-making is impossible without ML, integration of ML with business intelligence (BI) is essential to both corporate decision-making and business intelligence as a whole. Only once they have learned anything again may machines assist in your educational process. This study suggests a fresh approach to knowledge building in company management decision-making through the use of gaming and machine learning models. Using a game model that involves decision-making, knowledge analysis based on business management is conducted. Subsequently, quantum reinforcement reward neural networks build knowledge. The accuracy, precision, recall, F_1 score, MSE, NSE of business management modelling with knowledge growth are all assessed by simulation. The student’s gender had no bearing on the income they were offered throughout the job placement process or their MBA specialisations in Marketing and Finance (Mkt & Fin) or Marketing and Human Resource (Mkt & HR), according to a statistical t-test with a significance threshold of 0.05 (p > 0.05).

Multi-objective Optimization Model for Medical Waste Supply Chain Management Without Landfill Tax During COVID-19 In Indonesia

The COVID-19 pandemic has brought various problems into our daily life, and one of them is an increase in the volume of medical waste, which poses a risk to the environment and health.An evaluation of how optimal the supply chain management of medical waste as a whole can assist in the development of medical waste management and policy making. In this paper, the study on observing and reformulating the existing medical waste supply chain optimization model using Mixed Integer Linear Programming (MILP) is discussed. This study is done by modifying the objective function and the constraints with considering elimination of the landfill tax variable. The resulted model is also a multi-objective optimization problem. To this end, the Lexicographic Method is employed to obtained the optimal solution. In this model, the most prioritizes that is considered in the environmental condition to the medical waste supply chain. A numerical experiment is done in this paper which it results suggests two things, first, the cost of medical waste processing is much greater than its revenue, and second, the waste processing through incineration is not favorable. Thus, it can be concluded that this study provides a modified medical waste optimization model and decisions in determining the combination of the amount and method for each subtype of medical waste to be processed by maximizing profit and the amount of waste sent to the landfill.