Management Model Research Articles

The implementation of an optimized neural network in a hybrid system for energy management

In the face of increasing global energy demand and volatile energy prices, many countries are searching for solutions to ensure their energy independence. One of the most popular solutions is to incorporate renewable energy sources in their energy systems. While there are many advantages to integrating renewable energy sources, it is important to note that their intermittent operation can present challenges. Energy storage and smart grid management systems are key solutions to overcome these challenges and ensure sustainable, reliable use of renewable energy sources. In this article, we present an intelligent electrical energy management system for hybrid energy systems. This management system is based on a multi-layer neural network that has undergone an architecture optimization phase to improve the accuracy of real-time energy management and simplify its implementation. The management model that was built demonstrated highly good performance across a range of test circumstances.

Community participation and effective water management: A study on water user organizations (WUOs) in Thailand

This study examines the factors enhancing the effectiveness of Water User Organizations (WUOs) in Thailand, spotlighting the integration of geo-informatics and community involvement in water management. Employing a community-based participatory research approach, we assessed the impact of advanced technological tools and increased community engagement on WUOs' operations and sustainability. Our methodology included surveys, interviews, and an analysis of water management practices before and after geo-informatics implementation. Findings reveal a significant increase in community participation and an improvement in water management knowledge. The use of geo-informatics led to notable advancements in water allocation efficiency and conflict resolution, directly contributing to the financial sustainability of WUOs. Specifically, the application of geo-informatics facilitated more accurate and timely water resource allocation, evidenced by enhanced community engagement metrics and the resolution of longstanding conflicts. These results underscore the value of combining geo-informatics with community-driven approaches to water management, offering valuable insights for policymakers and practitioners. The study advocates for policies that support the adoption of technological innovations and promote community-centric governance, providing a scalable model for sustainable water resource management. This approach not only improves the functionality and sustainability of WUOs but also sets a precedent for holistic water governance practices globally.

“I felt so powerful to have this love in me”: A grounded theory analysis of the experiences of people living with and recovering from eating disorders while in diverse romantic relationships

Romantic partners have the potential to influence attitudes and behaviors related to body image and disordered eating. However, the role that romantic relationships can play in eating disorder (ED) recovery has not been comprehensively investigated. The present study aimed to explore the ways that people living with and recovering from EDs experience their romantic relationships, with the specific objective of developing a novel theoretical framework, grounded in the experiences of people in diverse romantic relationships, to guide future research on the topic. Semi-structured individual interviews were conducted with 66 people (45 cisgender women, 11 cisgender men, 9 nonbinary people, and 1 transgender man) living with and recovering from EDs while in romantic relationships. Our grounded theory analysis yielded a theoretical model of ED management in romantic relationships, revealing that Individual and Relationship Characteristics intersected with Relationship-Related Stressors and were navigated using Eating Disorder and Relationship Management Strategies. Combined with Partner Support and Tensions, these management strategies were related to Relationship and Mental Health Outcomes, which affected and were affected by Future Concerns. Future researchers should continue to build on, expand, and modify this model and further explore the role of romantic relationships in the experience of people living with EDs.

Mass evacuation planning for disasters management: A household evacuation route choice behavior analysis

This paper presents a multi-methodological approach to analyzing household evacuation route choice behaviors and the related decision-making for mass evacuation planning in disaster management. Specifically, the proposed multi-methodological approach integrates a syncretic risk perception conceptual model with a household-based group utility evolution model. The dynamics of household evacuation route choice are explored in two stages, namely the individual utility initiation and accommodation. The unique feature of the proposed approach is that it links individual risk perception, survival psychology, and group behavioral dynamics together to characterize household decision-making about choosing the evacuation routes. An empirical study coupled with experiments is conducted to help validate the proposed household evacuation route choice behavior model. Through various designed disaster scenarios, the applicability and strengths of the proposed model for mass evacuation planning and management are demonstrated. Particularly, the mean relative prediction errors of the proposed model with respect to household-based evacuation route switching probability and path flow splits are 3.79% and 6.88%, respectively, all within an acceptable range of ±10 %. This demonstrates that the proposed model and analytical results align closely with household choice behavior.

STRATEGIC PERSONNEL MANAGEMENT MODELS AND THE IMPORTANCE AND NECESSITY OF THEIR REDESIGN TODAY

In the article - "Strategic personnel management models and the importance and necessity of their redesign today" - strategic management models are listed and discussed. Among them are: D. Guest model, Michigan and Harvard models, Armstrong model, Fottler model, Cheveldry model, Shuler and Jackson model. These models were developed in previous centuries. The authors of the article have compared them with their current requirements, in particular with the current needs of companies in this field. Today's needs are to provide managers not with general models of strategic personnel management, but with specific ways of achieving the characteristics that are fixed in these models. In the article, the authors have performed exactly this work on the model of scientist Fottler and have also shown it graphically. Keywords: personnel; strategic management; Models of strategic personnel management.

Advanced risk management models for supply chain finance

This review paper delves into the transformative potential of advanced risk management models in enhancing the resilience and efficiency of supply chain finance (SCF). By examining the application and development of Artificial Intelligence (AI), Machine Learning (ML), Big Data analytics, and blockchain technology, the paper highlights their role in transitioning from traditional reactive strategies to proactive and predictive risk management approaches. Despite the promising advantages, the paper also addresses the significant implementation challenges, model limitations, and regulatory and ethical considerations accompanying these technological advancements. Recommendations for effective deployment and areas for future research, particularly in overcoming existing hurdles and exploring emerging technologies, are also discussed. This comprehensive analysis aims to guide academics, industry professionals, and policymakers in harnessing advanced risk management models for a more robust SCF ecosystem.

Cyber Risk Assessment Framework for the Construction Industry Using Machine Learning Techniques

Construction 4.0 integrates digital technologies that increase vulnerability to cyber threats. A dedicated cyber risk assessment framework is essential for proactive risk mitigation. However, existing studies on this subject within the construction sector are scarce, with most discussions still in the preliminary stages. This study introduces a cyber risk assessment framework that integrates machine learning techniques, pioneering a data-driven approach to quantitatively assess cyber risks while considering industry-specific vulnerabilities. The framework builds on over 20 literature reviews related to construction cybersecurity and semi-structured interviews with two industry experts, ensuring both rigor and alignment with practical industrial needs. This study also addresses the challenges of data collection and proposes potential solutions, such as a standardized data collection format with preset fields that computers can automatically populate using data from construction companies. Additionally, the framework proposes dynamic machine learning models that adjust based on new data, facilitating continuous risk monitoring tailored to industry needs. Furthermore, this study explores the potential of advanced language models in cybersecurity management, positioning them as intelligent cybersecurity consultants that provide answers to security inquiries. Overall, this study develops a conceptual machine learning framework aimed at creating a robust, off-the-shelf cyber risk management system for industry practitioners.

Harnessing the runoff reduction potential of urban bioswales as an adaptation response to climate change

Nature-based solutions (NbS), including China's Sponge City Program (SCP), can address the challenges urban communities face due to surface runoff and flooding. The current capacity of SCP facilities in urban environments falls short of meeting the demands placed on communities by climate change. Bioswales are a form of SCP facility that plays an important role in reducing surface runoff by promoting infiltration. This study assesses the potential of SCP facilities to reduce runoff in urban communities under climate change using the storm water management model. The study site in Ningbo, China, was used to evaluate the potential role of bioswales in reducing runoff risks from climate change. We found that bioswales were most effective in scenarios when rainfall peaks occurred early and were less effective in right-skewed rainfall events. The overall performance of SCP facilities was similar across all climate scenarios. To maintain the current protection level of SCP facilities, bioswales would need to cover at least 4% of the catchment area. These findings from Ningbo provide a useful method for assessing NbS in other regions and indicative values for the increase in the bioswale coverage needed to adapt to climate change.

The development of day surgery in China and the effectiveness and reflection of day surgery in ophthalmology-specialized hospitals.

This survey investigates the development of day surgery in China, and analyzes the national policy support, medical service management model, disease types of day surgery, medical insurance payment methods, and the medical service capacity, efficiency, quality and safety, health economics indicators, and patient satisfaction after the implementation of day surgery in a tertiary eye hospital. After more than 20 years of development, China's day surgery has shown a good development trend. The implementation of day surgery in eye hospitals accounts for more than 70% of elective surgery, and patients, medical institutions, and medical insurance institutions have all achieved good social benefits.

Transfer pricing, earnings management and corporate governance among listed firms: Evidence from Ghana

Purpose This study aims to examine the prevalence of transfer pricing and earnings management activities, and how they are impacted by corporate governance mechanisms. Design/methodology/approach Using the political cost theory, the study provides insights into how opportunistic managerial behaviours which have a strong link to profit shifting and tax evasion are driven by corporate governance using data from 16 listed firms for the period 2008–2020. Findings The results reveal that the transaction-based transfer pricing model is better than the index-based model and the accrual-based earnings management model suits the political cost theory more than the real earnings management metric. Board size and female CEO increase transfer pricing aggressiveness but board independence, CEO tenure, CEO nationality and female Board Chairwomanship reduce transfer pricing aggressiveness. The findings also reveal the role of multinational enterprise status, private ownership, industry type, firm size, financial leverage, asset tangibility and firm age. For accrual-based earnings management, board independence, CEO tenure, and female Board Chairwomanship significantly decrease earnings management. Other factors include private ownership, firm size, and firm age. Practical implications The findings of the study are relevant for shaping industry-level policies on earning management, transfer pricing and related-party transactions. Since these opportunistic managerial behaviours are the foremost drivers of tax avoidance and profit shifting, the findings of this study provide relevant insights for practitioners, tax and other regulatory authorities, policymakers and the academic community alike. Originality/value This is among the premier studies on the transfer pricing and earnings management nexus with corporate governance factors using the political cost theory, especially in the developing country context. It also reveals the significant impact of gender and suggests the need for gender diversity in corporate management.

Efficacy of a full management model in daytime surgery for gastrointestinal polyps based on WeChat: A study protocol for randomized controlled trials.

The objective of this study is to improve the efficiency of daytime surgery for gastrointestinal polyp and ensure the safety of patients. We tried an information management method based on WeChat platform in patients undergoing daytime gastrointestinal polypectomy and to explore the feasibility and effectiveness of a full management model. Five hundred and ninety-three patients were randomly divided into two groups: the control group was treated with traditional management methods and the experimental group was treated with the whole-process management mode based on the WeChat platform. The WeChat platform-based full management model included establishing a day surgery management WeChat group, developing multidisciplinary, full-management protocols and processes for day surgery, establishing an information-based surgical scheduling system and adopting diverse forms of day surgery education and continuity of care. This feature included illustrated brochures, vivid verbal presentations, WeChat public numbers and Internet management platforms. The treatment time, hospitalization cost and patient satisfaction of the two groups were counted. In the experimental group, 408 patients were enrolled. The preoperative waiting time and patients' length of stay were 3 days and 1 day, respectively. The medical and nursing intake time was 7 min. The procedure cancellation rate and postoperative complications rate was 0.07% and 0.02%. In the control group, 185 patients were enrolled in the study, The preoperative waiting time and patients' length of stay was 7 days and 3 days. The medical and nursing intake time was 28 min. The procedure cancellation rate and postoperative complications rate were 0.13% and 0.05%, respectively. The hospitalization costs were reduced by an average of $140/person and the satisfaction scores were higher than the control group. In summary, the preoperative waiting time, medical reception time, surgical cancellation rate, length of hospital stay and hospitalization cost in the observation group were less than those in the control group (p < 0.05). Patient satisfaction scores were significantly higher than those in the control group (p < 0.05). Through the full management model based on WeChat, the preoperative waiting time, medical reception time, surgical cancellation rate, length of hospital stay and hospitalization cost in the experimental group were less than those in the control group. Patient satisfaction scores were significantly higher than those in the control group and the difference was statistically significant.

Reliability of large language models for advanced head and neck malignancies management: a comparison between ChatGPT 4 and Gemini Advanced.

This study evaluates the efficacy of two advanced Large Language Models (LLMs), OpenAI's ChatGPT 4 and Google's Gemini Advanced, in providing treatment recommendations for head and neck oncology cases. The aim is to assess their utility in supporting multidisciplinary oncological evaluations and decision-making processes. This comparative analysis examined theresponses of ChatGPT 4 and Gemini Advanced to five hypothetical cases of head and neck cancer, each representing a different anatomical subsite. The responses were evaluated against the latest National Comprehensive Cancer Network (NCCN) guidelines by two blinded panels using the total disagreement score (TDS) and the artificial intelligence performance instrument (AIPI). Statistical assessments were performed using the Wilcoxon signed-rank test and the Friedman test. Both LLMs produced relevant treatment recommendations with ChatGPT 4 generally outperforming Gemini Advanced regarding adherence to guidelines and comprehensive treatment planning. ChatGPT 4 showed higher AIPI scores (median 3 [2-4]) compared to Gemini Advanced (median 2 [2-3]), indicating better overall performance. Notably, inconsistencies were observed in the management of induction chemotherapy and surgical decisions, such as neck dissection. While both LLMs demonstrated the potential to aid in the multidisciplinary management of head and neck oncology, discrepancies in certain critical areas highlight the need for further refinement. The study supports the growing role of AI in enhancing clinical decision-making but also emphasizes the necessity for continuous updates and validation against current clinical standards to integrate AI into healthcare practices fully.

The Role of Traditional Chinese Medicine in the Management of Cervical Cancer.

Globally, cervical cancer poses a substantial public health challenge, with low and middle-income countries bearing the highest burden [Rajkhowa, P., D.S. Patil, S.M. Dsouza, P. Narayanan and H. Brand. Evidence on factors influencing HPV vaccine implementation in South Asia: a scoping review. Glob. Public Health 18: 2288269, 2023]. The incidence rate ranks second highest among female malignant tumors in China, following only breast cancer. The prognosis of advanced cervical cancer is extremely poor, with a 5-year progression-free survival (PFS) rate of only 15%, and the treatment of advanced recurrent or metastatic cervical cancer remains a huge challenge. An increasing amount of evidence suggests that traditional Chinese medicine (TCM) can significantly enhance sensitivity to chemotherapeutic drugs, strengthen antitumor effects, and notably improve adverse reactions associated with cancer such as fatigue and bone marrow suppression. In recent years, the therapeutic effects and mechanisms of Chinese herbal medicines, such as the Guizhi-Fuling-decoction, the compound Yangshe granule, Huangqi, and Ginseng, herbal monomers (e.g., Ginsenoside Rh2, Tanshinone IIA, and Tetrandrine), and the related extracts and compound formulations, have received extensive attention for the treatment of cervical cancer. This paper reviews the research progress of TCM in cervical cancer. In addition, we reported a case of an advanced cervical cancer patient with multiple abdominal and pelvic metastasis who initially received chemotherapy, was then treated with TCM alone, and subsequently survived for 22 years. The model of whole-process management with TCM can enable more cancer patients to obtain longer survival periods.

Temperature control by simulated adaptive layer times in powder bed fusion processes

AbstractIn this work, a simulation-based thermal management model for metal parts produced through powder bed fusion (PBF) is proposed. PBF is an additive manufacturing technique that employs a high-energy beam to selectively melt and fuse powder particles layer by layer. The productivity and efficiency of PBF processes can be significantly increased using multi-laser systems with larger build volumes. However, this approach affects the parts thermal history, which can significantly impact their mechanical properties, microstructure, and defects. To address this issue, an algorithm has been developed to calculate adaptive cooling times reaching predefined temperatures at the end of each layer. The algorithm is used in a fast thermal process simulation using layer lumping. The simulation model is applied to a modern multi-laser machine, and the effectiveness of the adaptive cooling times and minimal layer times is evaluated. The results indicate that lower maximum temperatures can be achieved in less manufacturing time with adaptive cooling times than with minimal layer times. However, the significant increase in manufacturing time highlights the need for active cooling systems to utilize multi-laser machines fully. In summary, this paper presents a significant contribution to the field of additive manufacturing, emphasizing the importance of thermal management in ensuring the quality and performance of metal parts produced through PBF.

СОПОСТАВИТЕЛЬНЫЙ АНАЛИЗ ЖИЗНЕННОГО ЦИКЛА ОРГАНИЗАЦИИ ПО МОДЕЛИ И. АДИЗЕСА И ЖИЗНЕННОГО ЦИКЛА ПРОЕКТА В РАМКАХ ПРОЕКТНООРИЕНТИРОВАННОЙ МЕТОДОЛОГИИ УПРАВЛЕНИЯ

The relevance of the topic is determined by the existing conditions of transition of modern organizations to new management paradigms. World trends of project-oriented management are increasingly penetrating into domestic management practices. In domestic practice, the diversification of operational processes of the organization from projects faces difficulties in determining the intersection of the stages of the life cycle of the organization and the life cycle of the project, especially in the framework of strategic projects of the organization. Project-oriented management methodology is a modern means of ensuring a high level of competitiveness, but does not have sufficient understanding on the part of strategic and operational management of the organization. The greatest interest in this article is shown to the search for ways to form new approaches to the organization of project-oriented management in modern domestic organizations. Also, special attention is paid to the analysis of the current mechanisms of organization life cycle management of the organization and the project, based on the mechanism of combining the two approaches to management. The analysis of the application of the life cycle model of I. Adizes in the management of modern domestic organizations, as well as the analysis of the applicability of the traditional life cycle model of project management. The aim of the study is to identify ways to manage modern organizations by combining Adizes' life cycle model and the project life cycle model. The objectives of the study are reduced to the analysis of key factors contributing to the integration of the two approaches to the management of project-oriented organizations. Research results. The comparative analysis of the model of the life cycle of the organization I.Adizes and the model of the life cycle of the project is carried out. on the basis of results of the analysis of characteristics of stages of each of the models, proposals on use of the model of the life cycle of the project as a basic paradigm of management of the project-oriented organization as a whole are made. The problem of applicability of the proposed methodology is revealed, which requires practical confirmation and additional theoretical study.

South Tyrol Healthcare Company: A Look at a Peculiar Model of Claims Management in Italy and Analysis of Its Last 11 Years

Background: Alternative Disputes Resolution (ADR) systems are becoming increasingly important tools in recent years for the management and resolution of health responsibility cases, but their dissemination and efficiency are still poorly described. The purpose of this paper is to present an ADR system in the autonomous province of Bolzano: the Conciliation Commission. Methods: systematic collection of all claims of the South Tyrol Sanitary Service that were dealt with in the Conciliation Commission from 1 January 2012 to 31 December 2022. Results: closing times of the applications received turn out to be less than a year in 63.8% of the cases, with a number of cases managed rather stably in the time, even if minimal if compared to the number of complaints received to the South Tirol Health Service. Only 5.3% of the application continued the legal process before a civil court. Conclusions: the Conciliation Commission of South Tirol appears to be an excellent instrument for the resolution of disputes in the healthcare field, with rapid resolution times and little to zero costs for the healthcare company, a public health institution. Despite its effectiveness, it seems to be a tool that is still little-known in South Tyrol.

Evaluating Community Forest User Groups (CFUGs)’ Performance in Managing Community Forests: A Case Study in Central Nepal

The community forests (CF) in Nepal, facilitated by Community Forest User Groups (CFUGs), is widely recognized as an effective model of community-based forest management. Despite this recognition, there is a notable lack of comprehensive studies assessing the performance of CFUGs in sustaining community forests. Addressing this gap, this study examined twenty-two indicators across five performance criteria, such as user group management, forest management, financial management, livelihood management, and collaboration and networking management, within four CFUGs in central Nepal. Data were collected through household surveys (n = 275) and focus group discussions (n = 4), and indicators of performance criteria were assessed using a Likert scale. Reliability was measured using the coefficient of Cronbach’s alpha. ANOVA was employed to compare mean performance criteria across the four CFUGs, providing an evaluative perspective on overall CFUG performance. The findings underscored collaboration and networking management as high performers, showing an index value of 0.71, while user group management exhibited moderate performance with an index value of 0.56, alongside other moderately performing criteria. Noteworthy disparities were evident across the four performance criteria (p &lt; 0.01), with the exception of collaboration and network management. Approximately 55% of the indicators were rated low to moderate, revealing CFUGs’ deficiencies in regular functions, limited uptake of adaptive and market-oriented management practices, minimal contributions to biodiversity conservation, insufficient capacity for forest revenue generation and mobilization, and restricted income generation and benefit-sharing with communities. The absence of timely and pertinent actions further stifled interaction between CFUGs and community forests, undermining the potential for revenue generation, job creation, and collective actions essential for productive community forest management. Prioritization of the indicators based on the performance index value offers critical policy direction to ensure CFUG sustainability and augment participatory management of common pool resources. Strategies to address identified weaknesses and build on strengths are essential for the success of Nepal’s community forests.

Assessing the Effects of Environmental Flows on Water Quality for Urban Supply

This paper analyses the effects of environmental flows on water quality within a highly regulated basin, focusing on the Turia River basin in the eastern Iberian Peninsula. Through water management and water quality models, a series of simulations were conducted, introducing variations in the outflows of the Loriguilla reservoir to evaluate the effects of different environmental flow scenarios on water quality, particularly at the location of the intake for the water supply to Valencia. Three environmental flow scenarios were analyzed, alongside an alternative management scenario, considering their implications on water quality and reliability of water demand. The findings of this paper, particularly the nitrate (NO3−) concentration evolution, highlight the influence of minimum e-flow and e-flow regimes on water quality within the basin. These results suggest that while modifying the current flow regime can lead to some improvements in nitrate concentrations at the Valencia supply intake point, the primary cause of high nitrate concentrations is attributed to irrigation return flow and the pre-existing contamination of the aquifer. This analysis offers valuable insights into the complexities of water quality management in regulated basins, emphasizing the need for a multi-faceted approach to address the diverse factors influencing water quality and demand supply reliability.

An Assessment of Container Seaport Efficiency Determinants

Maritime transport plays a pivotal role in the global economy, facilitating the majority of international trade and serving as a cornerstone for efficient and expansive logistics networks. The proliferation of economic globalisation has resulted in a significant upsurge in intercontinental transactions, thereby fostering the utilisation of ports and shipping enterprises as cost-effective and expeditious means of accessing a wide range of destinations in Europe, Asia, Africa, and North America. The objective of this study is to evaluate the significance of five exogenous variables, namely, GDP per capita, water depth, commodity-type diversification, management model, and European directional division, in relation to the performance of seaports. Measuring the impact of exogenous variables in seaport performance is crucial for understanding how external factors influence efficiency, enabling informed decision-making, and facilitating the development of targeted policies for sustainable and effective port operations. This assessment will be conducted using robust benchmarking analysis methods, specifically the nonparametric order-α model. Several findings suggest that there is a negative relationship between GDP per capita and the performance of seaports when GDP per capita reaches very high levels. However, seaports located in regions with lower GDP per capita tend to exhibit superior performance. The inefficiency of southern seaports is evident, whereas seaports located in Central/Eastern Europe exhibit superior performance, irrespective of their model orientation. These findings underscore the importance of considering economic context and regional factors in understanding seaport performance and highlight potential areas for improvement in southern seaports.

Exploring the applicability of the experiment-based ANN and LSTM models for streamflow estimation

AbstractThe Yeşilırmak River Basin in northern Türkiye is crucial for the region’s water supply, agriculture, hydroelectric power generation, and clean drinking water. The primary goal of this study is to determine which modeling approach is most appropriate for various locations within the basin and how well meteorological data can predict river flow rates. Hydrological and meteorological forecasting both depend on the prediction of river flow rates. An artificial neural network (ANN), Univariate and Multivariate Long Short-Term Memory (LSTM) models have been utilized for streamflow forecasting. This research aims to determine the best model for several provinces in the basin area and give decision-makers a tool for reliable river flow rate estimates by combining LSTM and ANN models. According to research findings, the supervised multivariate LSTM model performed better than the unsupervised model in accuracy and precision. The sliding window methodology is suitable for estimating river flow based on meteorological datasets because it offers a primary method for reinterpreting time-series data in a supervised learning style. Compared to LSTM models, the ANN model that has been statistically optimized through experiments (DoE) design performs better in forecasting the river flow rate in the Yeşilırmak River basin (R2 = 0.98, RMSE = 0.18). The study’s findings provided prospective cognitive models for the strategic management of water resources by forecasting future data from flow monitoring stations.