Resource Management Model Research Articles

A water pollution haven hypothesis in a dynamic agglomeration model for fisheries resource management

A water pollution haven hypothesis in a dynamic agglomeration model for fisheries resource management

Comparative Analysis of Educational Resource Management Models

The aim of this research is a comparative analysis of educational resource management models. Educational resource management Refers to the context and factors that influence how educational resources are managed and utilized to achieve set educational goals. In its application, the educational resource model involves evaluating and comparing various approaches, methods or strategies in management, development and utilization of resources to achieve educational goals. The education system in Indonesia has formal, non-formal and informal education systems, and existing educational support must be able to provide adequate educational resources. In writing this article, the library study or library research approach is used, where the researcher collects research-related materials from books, magazines, scientific works, literature, mass media reports, etc., then describes and explains the data.

A moderated mediation model of green human resource management

ABSTRACT Our paper develops and tests a moderated mediation model of green human resource management (HRM). Time-lagged data gathered were utilized to assess climate for green initiative (GI) as a mediator of the impact of green HRM on green voice behavior (GVB) and test green servant leadership (SL) as a moderator of the indirect link of green HRM to GVB via climate for GI. Results from partial least squares structural equation modeling denote that climate for GI partly mediates the linkage between green HRM and GVB. Unexpectedly, green SL reduces the indirect positive relationship of green HRM to GVB via climate for GI. By gauging the aforesaid relationships, our paper augments the existing knowledge regarding the mediating mechanism relating green HRM to GVB. Our paper also augments the green management literature by treating green SL as a moderator.

The impact of artificial intelligence on human resource management systems - Applications and risks

Organizations traditional human resource management model has been impacted by the ongoing optimization and advancement of artificial intelligence skills and technology, and the broadening of its application scope. The impact of artificial intelligence (AI) systems on employee recruitment, human resources allocations, and talent management is significant. This paper examines the interplay among AI, data applications, human resource management (HRM) systems and the resultant effects. It will examine the significance of effectively managing the deployment of AI systems, as existing literature defines. This study examines the effects of artificial intelligence AI technology on the effectiveness of company administration compared to traditional human resource management systems (HRMS). Several recommendations are offered to enhance the reformation and optimization of the organizations human resources (HR) division. The research findings indicate that incorporating the new system in conjunction with human involvement can significantly enhance the efficiency of employee recruitment, allocation of human resources, and management of talent within the firm. There was an improvement observed in both employee happiness and productivity elements.

New Approach to Equitable Intervention Planning to Improve Engagement and Outcomes in a Digital Health Program: Simulation Study.

Digital health programs provide individualized support to patients with chronic diseases and their effectiveness is measured by the extent to which patients achieve target individual clinical outcomes and the program's ability to sustain patient engagement. However, patient dropout and inequitable intervention delivery strategies, which may unintentionally penalize certain patient subgroups, represent challenges to maximizing effectiveness. Therefore, methodologies that optimize the balance between success factors (achievement of target clinical outcomes and sustained engagement) equitably would be desirable, particularly when there are resource constraints. Our objectives were to propose a model for digital health program resource management that accounts jointly for the interaction between individual clinical outcomes and patient engagement, ensures equitable allocation as well as allows for capacity planning, and conducts extensive simulations using publicly available data on type 2 diabetes, a chronic disease. We propose a restless multiarmed bandit (RMAB) model to plan interventions that jointly optimize long-term engagement and individual clinical outcomes (in this case measured as the achievement of target healthy glucose levels). To mitigate the tendency of RMAB to achieve good aggregate performance by exacerbating disparities between groups, we propose new equitable objectives for RMAB and apply bilevel optimization algorithms to solve them. We formulated a model for the joint evolution of patient engagement and individual clinical outcome trajectory to capture the key dynamics of interest in digital chronic disease management programs. In simulation exercises, our optimized intervention policies lead to up to 10% more patients reaching healthy glucose levels after 12 months, with a 10% reduction in dropout compared to standard-of-care baselines. Further, our new equitable policies reduce the mean absolute difference of engagement and health outcomes across 6 demographic groups by up to 85% compared to the state-of-the-art. Planning digital health interventions with individual clinical outcome objectives and long-term engagement dynamics as considerations can be both feasible and effective. We propose using an RMAB sequential decision-making framework, which may offer additional capabilities in capacity planning as well. The integration of an equitable RMAB algorithm further enhances the potential for reaching equitable solutions. This approach provides program designers with the flexibility to switch between different priorities and balance trade-offs across various objectives according to their preferences.

Fuzzy Decision-Making and Resource Management Model of Performance Evaluation Indices

The Performance Evaluation Matrix (PEM) is an excellent decision-making tool for assessment and resource management. Satisfaction Index and Importance Index are two important evaluation indicators of construction and PEM. Managers can decide whether the service item needs to be improved based on the Satisfaction Index of the service item. When resources are limited, managers can determine the priority of improving the service item based on the Importance Index. In order to avoid the risk of misjudgment caused by sample errors and meet the needs of enterprises’ rapid decision-making, this study proposed a fuzzy test built on the confidence intervals of the above two key indicators to decide whether essential service items should be improved and determine the priority of improvement. Since the fuzzy test was relatively complex, this study further came up with fuzzy evaluation values and fuzzy evaluation critical values of service items following fuzzy testing rules. Besides, evaluation rules were established to facilitate industrial applications. This approach can be completed with any common word processing software, so it is relatively convenient in application and easy to manage. Finally, an application example was presented in this paper to explain the applicability of the proposed approach.

Sustainable Human Resource Practices and Framework in the Selected Philippine State Universities and Colleges (SUCs): A Case Study

Despite the significance of Sustainable Human Resource Management (SHRM), there is a dearth of academic literature on this subject in the context of Philippine State Universities and Colleges (SUCs). The goal of this research is to analyze current human resource practices, look at the key underlying factors that affect them, and develop a comprehensive and integrated model of human resource management that considers shifting social and economic conditions as well as the demographics of the workforce in SUCs. The proposed model can be used as a roadmap to enhance human resource practices, develop human capital, and create more sustainable human resource planning in the Philippine public sector. For this case study, information was gathered through in-depth interviews with 30 key respondents from selected SUCs who held managerial, supervisory, and rank-and-file positions. The study's findings will offer advice to academic HR managers on how to improve HR procedures and administration to be more employee-focused. Thus, the proposed framework is useful for making decisions about how to sustain employees in the Philippine SUCs.

АДАПТАЦИЯ МОДЕЛЕЙ УПРАВЛЕНИЯ КАДРАМИ ДЛЯ СТИМУЛИРОВАНИЯ РАЗВИТИЯ ГОРНОДОБЫВАЮЩИХ ПРЕДПРИЯТИЙ

This article examines the issue of adapting HR management models in the context of mining companies in order to stimulate their development. In today's dynamic economic environment, mining companies face a number of challenges that require effective personnel management to ensure competitiveness and sustainable growth.
 The author analyzes the features of personnel management in the mining industries, highlighting key aspects such as the specifics of the production process, the characteristics of the workforce and the risks associated with occupational safety. Then modern models of personnel management are considered, including approaches to the selection, development and motivation of employees.
 The concept of adapting these models to the specifics of mining companies, taking into account their unique needs and challenges, is also proposed, which includes the development of specialized training and development programs, the introduction of motivation systems that take into account the dangers and difficulties of the working environment, as well as the creation of flexible management structures for rapid adaptation to changing market conditions.
 In conclusion, the importance of continuous improvement of human resources management models in mining companies in a rapidly changing economic environment is emphasized, which will allow them not only to survive, but also to thrive in modern competitive conditions.

Human Resource Management Through Artificial Intelligence Model in the Healthcare

The increasing complexity of the healthcare industry necessitates the recognition of human resources as a primary sustainable source of competitive advantage within healthcare management systems. This significance is magnified when healthcare professionals, physicians and nurses are considered. When human resource management (HRM) is discussed, it must be acknowledged that personnel are not devoid of emotions. The fostering of a healthy and sustainable working atmosphere is considered a critical responsibility by professional managers. In this research, a novel human resource management model is presented, which is based on AI: machine learning within the healthcare context. A deep learning model architecture based on CNN has been designed and optimized, which is trained in two scenarios through four datasets and also customized for the target hospital. The 92% accuracy is the power of the model in the recognition. The effectiveness of the model is assessed by curating a new dataset consisting of facial images of hospital professional staff displaying eight emotions: happiness, contempt, anger, sadness, disgust, fear, surprise, and neutrality. According to the post-implementation survey findings, the model has a positive impact on human resource management and enhances staff performance, making it suitable for modern and critical organizations such as hospitals and health canters. In the healthcare domain, effective communication is deemed essential for interactions with patients, as emotions play a significant role. Emotion recognition in human resource management has a profound impact not only on optimal work output but also on the relationships among personnel, clients, and the entire managed team.

Exploration of Human Resource Management in Enterprise Business Management

Human resource management is an integral part of enterprise operation and management, contributing to the avoidance of financial risks, alleviation of performance problems, promotion of organizational development, enhancement of operational efficiency, and fostering sustainable enterprise development. Enterprise management should prioritize attention to human resource management by establishing an independent human resource management department and strategically planning human resource management tasks. This involves building an information management platform, developing a professional human resource management model to mitigate market risks, actively recruiting human resource management talents to form a competent team, and enhancing the human resource management and supervision system. These measures are essential for comprehensively improving the level of enterprise operation and management.

Incipient Salinization: A Case Study of the Spring of Asclepieion in Lentas (Ancient Lebena), Crete

Sanctuaries devoted to Asclepius were established and operated for almost a thousand years in various Greek and Roman cities throughout the Mediterranean region. The Asclepieion sanctuary in Lentas (formerly known as Ancient Lebena) in Crete was famous for receiving water from a sacred spring. In Ancient Lebena, Levinaion was a famous centre for hydrotherapy, physiotherapy, and a psychiatric hospital. In the present paper, we aim to assess the hydrochemical status of this sacred spring that holds a prominent position in archaeological and historical studies. The main objectives of this study are: Initially, to present supervisory evidence (archaeological, geological, hydrochemical) of an area that was a water resource management model for many centuries, carrying out therapeutic work. The second objective is to present and compare hydrochemical data in the last century, i.e., from 1915 to 2021. The third objective is to highlight and warn of an incipient saltwater intrusion in the area along the Lentas coast. The fourth objective is to propose an alternative and sustainable form of water resources management in the region that requires the study and rational utilization of the sporadic small water springs in the region. Our study focuses on a basic hydrochemical analysis of spring and borehole water in the remains of Levinaion in the Lentas region, and their comparison with sparse historical data of the sacred spring water, aiming to interpret the impact of the changes in the spring water resources that occurred in recent decades due to urban modernization. Our results highlight (i) visible fluctuations in chemical composition of borehole water samples; (ii) a neutral to alkaline pH in borehole waters and an alkaline pH in spring waters; (iii) undetectable arsenic in Lentas borehole water, unlike historical data of Lentas spring water; (iv) low values of dissolved radon in Lentas borehole water and the spring water of Kefalovrysa; and (v) a timeless constant and hypothermic nature of the water of both the sacred spring and borehole of Lentas, and also of the Kefalovrysa spring. The recorded historical data, i.e., from 1915 to 1957, due to the absence of substantial anthropogenic activity in the area, can be used as reference values (natural background levels, NBLs) for the Lentas area. Our findings emerge with the need to bring again the flowing spring water of the sacred spring of Lentas in its original form through sustainable management and re-discover its beneficial therapeutical effects.

Identification of hydrologically homogenous watersheds and climate-vegetation dynamics in the Blue Nile Basin of Ethiopia

Abstract Identification of hydrologically homogenous watersheds in the Upper Blue Nile Basin of Ethiopia is challenging due to the large number of watersheds and the lack of consistent and reliable data. Traditional methods, such as expert-based classification, are time-consuming, subjective, and often not reproducible. Therefore, this study aims to identify homogenous gauged watersheds using hydrometeorological and remote sensing data. In this study 76 watersheds were delineated from a 30-m digital elevation model (SRTM-DEM). Twelve watershed characteristics were selected to aid the classification process. Three homogenous climate regions were identified using rainfall data from 42 stations, and for each homogeneous climate region, gauged watersheds were identified. Principal component analysis (PCA) and K-means clustering were used for classification. The PCA reduced 12 watershed characteristics into three principal components using a threshold of 80% accounted variance and eigenvalues greater than one. K-means clustering classified the 76 watersheds into nine homogenous clusters. In the classified regions, vegetation dynamics within three decades have also been analyzed. This helped identify trends in vegetation cover and its spatial and temporal dynamics. The results of the investigation will potentially be used for runoff prediction of ungauged watersheds and for water resource management models in the future.

Retracted: A Performance Analysis Model for Corporate Human Resource Management Based on Extenics Theory

Retracted: A Performance Analysis Model for Corporate Human Resource Management Based on Extenics Theory

Optimal service resource management strategy for IoT-based health information system considering value co-creation of users

PurposeThis paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.Design/methodology/approachAn adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.FindingsThe results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.Practical implicationsThe findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.Originality/valueThis study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

Resource Management Solutions for Modern Law Firms: A Comprehensive Database

In the modern legal landscape, resource management plays a crucial role in the sustained development of law firms and in delivering high-quality legal services to clients. However, there are still law firms that have deviated from database technology and continue to rely on traditional resource management models, which cannot meet the needs of modern enterprise management. This paper aims to explore the current status of resource management in law firms and introduces the design of a universal resource database tailored to the needs of law firms, lawyers, and clients. This paper provides a detailed introduction to the design of the comprehensive resource management database from the perspectives of requirement analysis, conceptual level design, logical level design and physical level design. The comprehensive database primarily store data related to staffs, orders, and clients, providing efficient resource management, and allowing for further expansion on this foundation. Effective resource management is paramount for law firms to maintain their competitiveness and provide excellent legal services, ultimately enhancing the overall client experience.

Integrated approach to water resource management in Mashhad Plain, Iran: actor analysis, cognitive mapping, and roadmap development.

Iran's Mashhad Plain faces a severe water crisis due to the excessive exploitation of groundwater, leading to the depletion of its aquifer. While water demand management is recognized as a superior solution compared to supply projects, its implementation presents notable challenges. This study addresses the urgent necessity to curtail water demand in the Mashhad Plain by alleviating conflicts among various stakeholders, including water resource managers and consumers. Initially, the research identifies key water resource actors who collaborate in devising a comprehensive roadmap and conceptual model for efficient water resource management. An analysis uncovers significant conflicts among actors, representing approximately 6% of identified issues, with minor conflicts in 30% of cases. Encouragingly, stakeholders demonstrate potential for consensus on the remaining conflict items, with specific actors emerging as pivotal in conflict resolution. Efficient water resource management in regions facing scarcity, diverse interests, and sustainability challenges demands a multifaceted strategy. Future endeavors involve developing a dynamic system model to simulate policy impacts and strengthen conflict resolution efforts. This research introduces a roadmap-driven approach aimed at resolving conflicts and implementing water demand management in the Mashhad Plain. It emphasizes the critical need to address water scarcity challenges while effectively mitigating conflicts among water resource stakeholders.

ПОТЕНЦИАЛ РЕСУРСНОЙ МОДЕЛИ УПРАВЛЕНИЯ ОРГАНИЗАЦИЕЙ В НОВЫХ УСЛОВИЯХ

In conditions of high dynamics of the external environment, global risks and constraints, ensuring the competitiveness of Russian business becomes an even more difficult managerial task that requires non-traditional approaches. The key issue of management in a modern organization is the question of choosing an approach and methods for creating and retaining a competitive advantage. The purpose of the study is to reveal the competitive potential of the resource management model of an organization in conditions of increasing development constraints. The study compared different models and schools united by a resource approach. The strategic parameters of the organization's resources are disclosed, in the presence of which the strategic goals of the organization are achievable. The significant features of the resource model are highlighted, which assumes the formation of competitive advantages of the organization by optimizing unique and standard resources. It is revealed that the development of the resource model in modern conditions is supported by the concept of "dynamic abilities", which is based on the potential of using "organizational abilities" and "dynamic resources" of the organization. It is shown that the resource model of an organization in modern conditions is dynamic and can be effectively implemented both if it is oriented towards environmental factors and the internal resource potential of the organization. The study of modern resource management models, highlighting their specific features and advantages will make it possible to make an informed choice of the model that will maximally correlate with the goals of the organization, its abilities and capabilities, as well as maximally meet the conditions of external dynamics. As a result, the company will have a wide range of methods and models to achieve competitive advantages in the market.

Construction and Application of Intelligent Optimization Model of Urban Resource Management for Sustainable Development

Abstract In this paper, we first digitally design the urban management resource base and then construct a dynamic bargaining resource allocation model based on super-marginal analysis with corner point equilibrium and dynamic bargaining. In the context of sustainable development, an intelligent optimization model is used to analyze the problem of water resource allocation and optimize urban traffic infrastructure paths in order to achieve carbon reduction targets. Finally, six recommendations are made for optimizing and managing urban resources in the context of sustainable development. The results of the prioritization coefficients of each subarea are 0.186, 0.164, 0.153, 0.158, 0.153, 0.0769, and 0.111, respectively, and the results of the allocation of the optimal solution for the social objective, the optimal solution for the economic benefit, the optimal solution for the ecological benefit, and the optimal solution for the comprehensive benefit are very close to each other. In addition, the rates of water shortage for agricultural, industrial, and other uses. are 3.29%, 4.85%, 3.94%, 2.92%, and 3.87%, respectively. The variation range of the average passenger load factor and departure frequency under the carbon reduction target is between ±40%, the average vehicle area varies in the range of ±20%, and the variation range of the energy consumption factor and CO2 emission factor is -40%-0%. The intelligent optimization model for urban resource management proposed in this paper has practical significance for urban water resource planning and transportation structure optimization.

МОДЕЛЮВАННЯ ЗАДАЧ ОПТИМІЗАЦІЇ УПРАВЛІННЯ ІТ-ПРОЕКТАМИ

Abstract. The article focuses on exploring mathematical models for optimizing business processes in project management within IT companies in the context of contemporary trends and challenges. Project management involves the process of guiding and coordinating people's activities, as well as managing material and financial resources throughout the project's lifecycle. This process encompasses applying modern management methods and techniques to achieve project goals. The dynamic allocation modeling of IT projects among teams to ensure high-quality development at maximum efficiency with minimal costs is a pertinent task in IT project management. The article's objective is to select a mathematical framework for decision-making regarding the optimal IT project management program to enhance the efficiency of each IT team and the entire IT company. The research involved an analysis of scientific literature on modeling project management in IT companies. The article proposes focusing on developing dynamic multi-criteria optimization models for human resource management, emphasizing the distribution of IT projects among executing teams. The research aims to elevate the strategic and operational levels of IT personnel management to achieve optimal outcomes in information technology. The analysis concludes that despite the advantages of various mathematical modeling methods, none of them in isolation allows for constructing a sufficiently detailed mathematical model. Methods and models addressing IT enterprise modeling problems may oversimplify the issue or, conversely, overly complicate it, complicating the selection of input data. The functioning of the IT enterprise was analyzed through the lens of external and internal indicators concerning the solved task. A verbal model of IT project distribution among teams, considering the time factor, was developed. This model formulated a system of basic concepts and ideas, allowing the dynamic formulation of the problem using widely accepted linear optimization models. This will facilitate finding optimal solutions for IT project distribution tasks over a specific period. Future research should focus on selecting a solution method for the model and implementing the constructed mathematical model using appropriate tools. The research findings presented can serve as a basis for further academic exploration and practical application in the field of IT project management. Keywords: modeling, optimization, business processes, project management, labor resources, IT projects.

Integrated farming systems model for resource management and rural employment in Vidarbha region under rainfed condition

Integrated farming systems model for resource management and rural employment in Vidarbha region under rainfed condition