Management Model Research Articles

Impact of Articulated Management Models on Educational Quality in Peru: A Systematic Review

This study aimed to analyze the impact of articulated management models on improving educational quality and equity in Peru. Through a systematic review of the literature with a qualitative approach that applied the PRISMA methodology in the search in the databases: Scopus, SciELO, Redalyc, Dialnet, and the library of the César Vallejo University, various studies are identified that explore the characteristics, implementation and results of these models. The results showed that articulated management models have significant potential to improve the quality of teaching and learning, especially when the participation of the educational community is promoted and transformative leadership is available. However, challenges are identified such as lack of resources, resistance to change and the need for continuous teacher training. It is concluded that articulated management models represent a promising way to improve education in Peru, but their implementation requires a comprehensive approach and educational policies that support them.

Analysis of Institutional Design of European Union Cyber Incident and Crisis Management as a Complex Public Good

ABSTRACTEffective cyber incident response and crisis management increasingly relies on the coordination of relevant actors at supranational levels. A polycentric governance structure is one of the institutional arrangements that can promote active participation of involved actors, an aspect decisive for the rapid and effective response to cyber incidents and crises. This research aims to dissect whether, and to what extent, a polycentric structure is manifested within the cyber crisis management framework of the European Union (EU) and assesses the extent to which these policies signal a balance between centralization and decentralization. By employing Institutional Grammar 2.0, we examine the roles and interactions among actors delineated within four key policies to identify the structural characteristics, institutional essentials, and prerequisites indicative of a polycentric governance system. Additionally, we apply network analysis to evaluate dyadic relationships of actors, further assessing the balance between centralization and decentralization in the EU's cyber crisis management framework. Our analysis reveals that the EU has adopted a polycentric governance model for cyber crisis management, characterized by a nuanced distribution of responsibilities and authorities. The findings highlight a tendency toward centralization, especially in the roles of Member States and the European Union Agency for Cybersecurity (ENISA), while maintaining a polycentric structure that blends centralization and decentralization. This balance can ensure structural integrity and coherence of the system, while theoretically providing the flexibility and resilience needed to adapt to the dynamic cyber threat landscape. The study contributes methodologically, offering a framework that can be applied to other domains, and provides insights into the effective coordination of cyber incident response and crisis management at supranational levels.

Evaluating Supply Chain Network Models for Third Party Logistics Operated Supply-Processing-Distribution in Thai Hospitals: An AHP-Fuzzy TOPSIS Approach

Background: This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, hospitals can enhance their operational efficiency, allowing healthcare professionals to focus on core tasks and ultimately improving service delivery. Methods: This research employed a dual methodology, combining an analytic hierarchy process (AHP) with a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). These approaches evaluated various SCM models based on multiple hospital logistics performance attributes. Results: The AHP results highlighted on-time delivery, patient safety, utilisation rate, and emergency procurement as critical criteria for selecting the optimal model. Fuzzy TOPSIS analysis identified the SCIII: W-G-H model as the most suitable for implementation in Thai hospitals. This model incorporates a centralised warehouse for negotiation leverage, a Group Purchasing Organisation (GPO) for cost efficiency, and regional SPD hubs for effective inventory management and rapid responses to demand fluctuations or emergencies. Conclusions: Adopting this SCM model is expected to significantly enhance supply chain performance, reduce operational costs, and improve the quality and safety of patient care in Thai hospitals.

The Theory and Path of Constructing an Integrated Management Model for One-Stop Student Communities

The construction of the "one-stop" integrated management model for student communities emphasizes bringing the educational resources and strength of universities directly to student communities, providing the warmest care to accompany students' healthy growth. By strengthening the "student-centered" philosophy of university governance, the aim is to improve the quality of working for, caring for, and serving students, thereby achieving comprehensive management and services within student communities.

Data management solutions for real-time analytics in retail cloud environments

In today's rapidly evolving retail landscape, the importance of real-time data analytics has surged, driven by the need for businesses to make informed decisions and enhance customer experiences. This paper explores the critical role of effective data management solutions within cloud environments, focusing on retailers' unique challenges, such as data integration, latency, security, and storage costs. It presents practical solutions, including data partitioning, caching, AI-driven analytics, and the strategic use of data warehousing and data lakes. By adopting hybrid data management models, retailers can optimize their data processes and leverage real-time insights to drive operational efficiency and competitive advantage. This paper offers valuable recommendations for retail businesses and data architects to enhance their cloud-based data management strategies, ensuring they can navigate the complexities of real-time data effectively and sustainably. Keywords: Real-time analytics, Data management, Retail, Cloud environments, Data integration, AI-driven solutions.

Innovative factors affecting performance of local government organizations in Thailand

This dissertation aimed (1) to study factors that have causal influences that affect the performance of municipalities. (2) to study the causal relationship model of innovative organizations, innovative capabilities, service innovation and performance management that influences the performance of municipalities. (3) to develop a linear structural equation model of the influence of service innovation, innovation organization, innovative capabilities and performance management that affects the performance of local government organizations in the category of municipalities in Thailand. The sample group were 320 executives of local government organizations in the category of municipalities in Thailand. Sampling was done in 2 steps: stratified and systematic sampling. This study is a quantitative study, and the research tool was a structured questionnaire and data were analyzed by percentage, mean, standard deviation, skewness, kurtosis, and confirmatory component analysis and structural equation model analysis. The findings of this study demonstrate significant direct effects of innovative capabilities, service innovation and performance management on performance of local government organizations in Thailand. Moreover, it was observed that innovative organizations and innovative capabilities also exerted indirect effects on performance of local government organizations through their influence on performance management, serving as mediator variables. Through the development of a structural equation model, it was determined that innovative capabilities had the greatest overall influence on the performance of local government organizations in the category of municipalities in Thailand, followed by performance management, service innovation and innovation organization, respectively. This research study made executives of local government organizations in category of municipalities in Thailand can be used as a guideline in determining strategies for managing their organization to be able to keep up with changes in the digital world and to ensure that the performance of the local government organization achieves the specified goals in terms of both efficiency and effectiveness.

The impact of health insurance integration on patient choice of providers in China

ABSTRACT This paper utilizes a nationwide integration reform of two public health insurance programmes in China to examine the impact of health insurance integration on patient choice of medical providers. Using a dataset that combines longitudinal survey data and government regulations data, we find that the integration leads to an increasing probability of outpatients in nearby primary care facilities and decreased outpatient visits to public healthcare providers. Moreover, the effects of integration vary with patient demographics, the type of healthcare, and the model of insurance management. No significant evidence suggests that the integration affects health behaviours or health status in the short term. These findings provide empirical evidence on the effects of insurance integration and policy implications for building an efficient hierarchical healthcare system.

Large Language Models for Financial and Investment Management: Applications and Benchmarks

Large Language Models for Financial and Investment Management: Applications and Benchmarks

Large Language Models for Financial and Investment Management: Models, Opportunities and Challenges

Large Language Models for Financial and Investment Management: Models, Opportunities and Challenges

ANALISIS PENYALURAN PEMBIAYAAN DAN MODEL PENGEMBANGAN KOPRASI IBNU AFFAN PATANI THAILAND

This study aims to examine the financing distribution system and the development model of the Ibnu Affan Cooperative in Thailand. A qualitative approach with descriptive methods was utilized, involving interviews and documentation as data collection techniques.Based on the analysis conducted, Koperasi Ibnu Affan applies Sharia principles with a focus on transparency. The transparency referred to involves the openness of information and decision-making processes carried out by the cooperative, where the cooperative is able to manage finances openly to both the management and all members, as well as the supervisory board. Furthermore, the welfare of the members is one of the cooperative's main programs aimed at improving the welfare of its members and the community in general. This is achieved through the use of a modern management model that focuses on the application of efficient and professional management principles while considering cooperative values based on democracy, transparency, and solidarity for operational success.

Machine learning-based optimal temperature management model for safety and quality control of perishable food supply chain

The management of a food supply chain is difficult and complex because of the product's short shelf-life, time-sensitivity, and perishable nature which must be carefully considered to minimize food waste. Temperature-controlled perishable food supply chain provides the highly crucial facilities necessary to maintain the quality and safety of the product. The storage temperature is the most vital factor in maintaining both the quality and shelf-life of a perishable food. Adequate storage temperature control ensures that perishable foods are transported to the end-users in good quality and safe to consume. This paper presents perishable food storage temperature control through mathematical optimal control model where the storage temperature is regarded as the control variable and the deterioration of the perishable food’s quality follows the first-order reaction. The optimal storage temperature for a single perishable food is determined by applying the Pontryagin's maximum principle to solve the optimal control model problem. For multi-temperature commodities supply chain, an unsupervised machine learning (ML) method, called k-means clustering technique is used to determine the temperature clusters for a range of perishables. Based on descriptive analysis, it is observed that the k-means clustering technique is effective in identifying the best suitable storage temperature clusters for quality control of multi-commodity supply chain.

Application of detailed nursing management intervention in neurosurgical nursing.

In the contemporary healthcare environment, optimizing patient care strategies is of importance, particularly in neurosurgical environments. While traditional nursing methods have the foundation of patient care, there exists a growing recognition of the potential benefits of comprehensive nurse management. Despite this acknowledgment, there remains a gap in understanding the comparative effectiveness of comprehensive nurse management versus traditional approaches in reducing postoperative psychological stress, enhancing patient satisfaction, and promoting adherence in neurosurgical patients. This study compares the efficacy of comprehensive nurse management against traditional methods in facilitating the postoperative recovery of neurosurgical patients. Taking the traditional nursing management and detailed nursing management of neurosurgical patients in a municipal neurosurgical hospital from March 2021 to March 2022 as an example, the neurosurgery was divided into 50 patients in the detailed nursing management group and 50 patients in the traditional nursing management group. In the clear nursing management group, there were 50 patients, 20 male patients, with an average age of 58.7 ± 3.8 years, and 30 female patients, with an average age of 60.4 ± 4.3 years; In the traditional nursing management group, there were 50 patients, 26 male patients, with an average age of 59.7 ± 3.7 years, and 24 female patients, with an average age of 59.4 ± 3.9 years; Among the 100 patients, there were 60 cases of cerebral infarction, 25 cases of intracerebral hemorrhage and 15 cases of other neurosurgical diseases. Hundred neurosurgical patients were divided into two groups: comprehensive nursing management group and traditional nursing management group. The results showed that the comprehensive treatment effect of patients with detailed nursing management was better than that of the routine nursing group. At the same time, the complications were reduced, and the patient's satisfaction was higher. Through retrospective analysis and investigation of patients, this paper discusses the clinical application of a detailed nursing management model in neurosurgery, which can reduce the probability of infection and other complications and improve the quality of life and treatment effect of patients.

Innovation and Sustainability in the Amazon with the Use of Blockchain

Objective: The general objective of this study is to model the implementation of a blockchain system for solid wastemanagement in a government agency. The specific objectives of the results are to identify the main challenges in implementing a blockchain system for solid waste management in Public Management (1); characterize the blockchain models identified in this investigation (2); and develop a blockchain system model for solid waste management in a government agency (3). Theoretical Framework: The Theory of New Public Management, discussed in Madan and Ashok (2022), is the basis of this study, considering the notes of these authors, who address the dominant paradigm in public administration. Method: This research has a qualitative or mixed approach, as it includes parametric elements based on architecture such as blockchain, supported by bibliographical research and documentary analysis. The bibliographical research was based on elements of an integrated solid waste management system, through a framework, as conceptualized in the specific topic of this study. The Content Analysis method was used to research documents and other textual or audiovisual databases on solid waste management and blockchain technology. This research method allowed us to extract relevant information from the data collected, organize it into thematic categories, and interpret it in light of the theoretical framework obtained. By applying Content Analysis, patterns, meanings, and nuances were identified that could enrich the understanding of the phenomenon studied, ensuring an in-depth and contextualized analysis. Results and Discussion: The scenario of research on solid waste management in Brazil is marked by significantchallenges that reflect the complexity of the country's socioeconomic and environmental context. According to Agência Brasil (2023), the generation of solid waste has increased alarmingly, with data from 2021 indicating that more than 80 million tons were produced, of which only 32.5% were correctly disposed of. Thisreality highlights the urgent need for effective and innovative public policies that address integrated waste management. Research Implications: The relevance of implementing a blockchain system in public governance is highlighted, considering the growing demand for innovative and sustainable solutions. Originality/Value: This study is of interest to government managers, academics involved in applied research onblockchain in waste management, politicians and other leaders committed to excellence in management, and other professionals committed to promising results in the relationship between innovation and sustainability in organizations.

Diabetes knowledge and behaviour: a cross-sectional study of Jordanian adults.

Diabetes mellitus is a significant global health concern that is projected to affect 7.7% of the global population by 2030. Understanding factors that influence diabetes knowledge and management adherence is crucial for effective diabetes mellitus management and prevention. This study investigates the relationships between demographic and clinical factors and their impact on diabetes knowledge and behaviour, as well as the potential influence of diabetes knowledge on management behaviours. The study comprised a cross-sectional survey of 1050 adults, collecting data on age, sex, marital status, education, employment, hypertension, dyslipidaemia (any lipid imbalance, such as high cholesterol, high LDL-cholesterol or low HDL-cholesterol), smoking and diabetes status. Two multiple linear regression models were used to identify factors associated with diabetes knowledge and behaviour, and a simple linear regression model was used to assess the relationship between knowledge and behaviour. Significant associations were found between diabetes knowledge and the following factors: age (44.32 ± 9.53 for ≥50 years vs 39.73 ± 9.95 for 18 to <25 years; p<0.0001), sex (49.00 ± 12.35 for women vs 45.09 ± 13.27 for men; p<0.0001), marital status (50.92 ± 11.69 for married vs 45.39 ± 13.10 for single; p<0.0001), smoking status (45.78 ± 13.22 for smokers vs 48.22 ± 12.15 for non-smokers; p=0.003), hypertension (46.46 ± 13.11 for present vs 47.31 ± 12.87 for absent; p=0.007) and diabetes status (69.49 ± 17.35 for present vs 62.76 ± 16.88 for absent; p<0.001). Behaviour scores correlated similarly with these factors except for diabetes and smoking status. The adjusted simple linear regression model revealed that diabetes knowledge was significantly associated with better management behaviours (coefficient=0.0794, p<0.001) after adjusting for demographic and clinical factors. This study highlights the importance of demographic and clinical factors in the context of diabetes knowledge and behaviours, underscoring the need for targeted educational and preventive programmes to improve diabetes management, especially in vulnerable populations. Additionally, the strong association between diabetes knowledge and management behaviours supports a knowledge-attitude-behaviour (KAB) model of diabetes management.

Governance of rural solid waste under a multi-subject governance model

Rural solid waste (RSW) exhibits distinct characteristics compared to municipal solid waste (MSW), such as dispersed distribution, long governance chains, and low recycling value, making it unsuitable to apply the same management measures as MSW. Government-led RSW management results in excessive administrative costs, and the inherent characteristics of RSW reduce market enthusiasm for its management. To address these issues, this paper integrates the “ multi-subject governance “ model with RSW management and establishes a systematic evaluation index system for RSW governance. Utilizing the Best-Worst Method (BWM), key factors were identified. Utilizing the VIKOR method, representative provinces in China were used as case studies to validate the scientific nature of the evaluation indices. The research findings indicate that the multi-subject governance model is an effective approach for RSW management. Key factors influencing RSW management effectiveness include various governmental measures, waste sorting, and a long-term multi-subject governance mechanism. Case analysis reveals a strong correlation between the level of economic development and the effectiveness of RSW management. However, constructing a government-led, multi-subject collaborative urban-rural interconnected RSW management model can effectively address RSW management issues in economically underdeveloped areas. This research provides innovative solutions for RSW management, contributing to high-quality and sustainable development in rural areas.

Effectiveness of the intelligent hypertension excellence centers (iHEC) therapy model in the blood pressure management of older hypertensive patients: a randomized controlled trial.

Intelligent hypertension excellence centers (iHEC) may improve blood pressure (BP) management in older hypertensive patients. However, this has not yet been rigorously evaluated, so we conducted a prospective randomized open-label clinical trial to verify this hypothesis. Older patients with hypertension were recruited between January and June 2022. The control group received conventional treatment and visited doctors in clinic. The intervention group received the iHEC therapy model, including remote BP management, online consultation, and follow-up services with support from the internet. Both groups received 12 months follow-up. Finally, 540 older patients with hypertension participated in the study; of these, 517 completed the follow-up. The average age was 71.4 ± 3.7years, 81 patients with frailty (15.7%). When follow-up was terminated, the SBP of the intervention group was 4.2 mmHg lower than that of the control group (95% CI, 2.0 to 6.4, P < 0.001), and the overall BP control rate in the intervention group was higher than that in the control group (60.2% vs. 48.1%, P < 0.05). During follow-up, the new-onset rate of excessive BP lowering in the intervention group was lower than that in the control group (3.8% vs. 9.0%, P < 0.05). Patients with a median age or above and high school education or above had higher numbers of online consultations and home BP measurements (P < 0.05).Our study confirmed those who received the iHEC therapy model achieved better BP reduction, higher rates of BP control, and alleviated the risk of excessive BP reduction.

Grey Relation System Applications in Multi-Attribute Decision-Making and Forecasting in Financial Management

Objective: The objective of the paper is to verify the Grey relation analysis methods and compare them with known models in financial management. The first part is devoted to MADM (multi-attribute decision methods) and the second one to grey forecasting methods. Method: Localization GRA and globalization GRA multi-criteria models are described and compared with the TOPSIS method. The forecasting GRA(1,1) model based on cumulative data is described, derived and compared with the linear growth model. The models are verified on the data set. Results and Discussion: The globalisation model based on a pair-wise comparison of alternatives is different, and the ranking of alternatives is fully different in comparison with the TOPSIS model. It was found that the localisation GRA model and TOPSIS, both constructed on similarity measures, present similar and comparable results. So, the grey relation approach considers the uncertainty of input data. The forecasting model GRA(1,1) is computed and compared with the growth model. Results show that the growth model is the trendy model, and the non-trendy series is overestimated or underestimated, so the GRA model looks more robust. Research Implications: The problem of imprecise data is investigated. And it is a realistic condition for practical decision-making. The problem of lack of data is often a phenomenon in decision-making. Traditional statistical methods cannot be applied. Therefore, grey relation methodology is one approach to overcoming the problem of imprecise data and lack of data. Uncertainty and lack of data problems are topics important for research and the managerial community. Originality/Value: Sometimes, in financial decision-making, high-quality data or long-term time series is not at our disposal, and on the other hand, decisions have to be made. This problem is often neglected and solved by not-relevant traditional statistical models. Therefore, methods that allow the solving of such problems are useful. It was shown that a grey relation methodology for multicriteria financial performance evaluation and forecasting shows more robust and stable results and could be more relevant for imprecise data or short time series data in financial decision-making problems.

The genesis of entropy in the conditions of the digital economy and socio-economic relations: globalization challenges and opportunities for sustainable development

The article traces the genesis of entropy in the minds of the digital economy and social economic developments, which stems from the rapid digitalization and accelerated globalization of current economic systems. The author has conducted research to highlight how digital transformations bring increased insignificance, creating new challenges for traditional models of management and social interaction. In the article, special attention is paid to the analysis of the legacy of the shift in the level of entropy for social unevenness, cybersecurity, technological accessibility and adaptation of enterprises to new minds in the market, which is We are important in the current information space. The emphasis is on the fact that the growing information and economic entropy is a critical factor that contributes to the ongoing development, which can lead to the destabilization of social and economic structures. The influx of globalization processes on entropy processes in the economies of the countries that are developing, where digital inequality is a factor in the growth of entropy, has been closely observed. Also, the role of government regulation in minimizing the negative legacies of entropy through promoting the policy of digital integration and supporting the development of harmonization of all processes has been analyzed. Opportunities for changing entropy are seen through the use of new innovative technologies, such as artificial intelligence, great data and automation, which allow optimizing resource management and reducing the level of insignificance. It is emphasized that the genesis of entropy in the digital economy requires further investigation, from which the economic stability of systems, as well as social harmony and equality have access to resources. The article also makes recommendations for further direct investigation of entropy in the minds of Swedish digitalization and globalization, which is aimed at developing strategies for managing complexity and insignificance in current social and economic systems.

Mental health status and influencing factors among Chinese college students in the post-COVID-19 pandemic period

After almost 3 years of battling against the coronavirus disease 2019 (COVID-19) pandemic, the static infection prevention had evolved to a dynamic management model at the end of 2022. However, the considerable rebound from pandemic in some areas is generally accompanied by increasing public pressure and depression. Hence, we investigated the impacts of the pandemic on the mental health and sleep quality of college students in China by conducting a cross-sectional survey on undergraduate, graduate, and doctoral students (n = 1105) through the Questionnaire Star survey platform. Demographic data, COVID-19-related stressors, information from four standardized scales (namely anxiety, depression, stress, and sleep), and other information were gathered through the survey. A total of 1120 questionnaires were collected, of which 1105 met the inclusion criteria. Most respondents were medical students (64%), and almost all of them had received the COVID-19 vaccine (99%). More people had been infected with COVID-19 (75%), with 33% showing mild to severe anxiety. A total of 54% of the respondents had mild to severe depression, 70% had moderate to severe perceived stress, and 28% had sleep disturbances. Further, analysis showed that the level of mental health was correlated with sleep. In addition, respondents from the medical specialty experienced more severe depression and anxiety (P &lt; 0.01), and the increase in stress after the outbreak, in terms of anxiety and depression, became significantly more pronounced (P &lt; 0.001). After the lifting of COVID-19 restrictions, the mental health level of college students was affected to some extent. The COVID-19 cases surge in some areas also resulted in psychological pressure and negative mental health among college students to a large extent even after the easing of COVID-19 restrictions. Despite the exigency to address the COVID-19 cases, attention must also be focused on the associated mental health problems, which require more systematic resolution from relevant authorities or departments.

Drosophila melanogaster experimental model to test new antimicrobials: a methodological approach

Given the increasing concern about antimicrobial resistance among the microorganisms that cause infections in our society, there is an urgent need for new drug discovery. Currently, this process involves testing many low-quality compounds, resulting from the in vivo testing, on mammal models, which not only wastes time, resources, and money, but also raises ethical questions. In this review, we have discussed the potential of D. melanogaster as an intermediary experimental model in this drug discovery timeline. We have tackled the topic from a methodological perspective, providing recommendations regarding the range of drug concentrations to test based on the mechanism of action of each compound; how to treat D. melanogaster, how to monitor that treatment, and what parameters we should consider when designing a drug screening protocol to maximize the study’s benefits. We also discuss the necessary improvements needed to establish the D. melanogaster model of infection as a standard technique in the drug screening process. Overall, D. melanogaster has been demonstrated to be a manageable model for studying broad-spectrum infection treatment. It allows us to obtain valuable information in a cost-effective manner, which can improve the drug screening process and provide insights into our current major concern. This approach is also in line with the 3R policy in biomedical research, in particular on the replacement and reduce the use of vertebrates in preclinical development.