Resource Management Framework Research Articles

HRMF-DRP: A next-generation solution for overcoming provisioning challenges in cloud environments

The cloud computing infrastructure is a distributed environment and the existing research works have some provisioning problems such as suboptimal resource utilization and high execution time. The Heterogeneity Resource Management Framework for Dynamic Resource Provisioning (HRMF-DRP) is proposed for focusing on task scheduling and workload management. This framework incorporates advanced algorithms for dataset preprocessing, task clustering, workload prediction, and dynamic resource provisioning. For data preprocessing, the real-world workload traces were captured from the Planet Lab dataset that are taken as input for the preprocessing stage. The data preprocessing is responsible for ensuring data quality and reliability by using different models like missing data handling, outlier detection and removal as well as standardization and normalization. In this paper, the tasks are grouped into clusters by utilizing Density-Based Spatial Clustering of Applications with Noise (DBSCAN) model and this model categorizes the data points into border points, core points and noise points based on their density. The temporal dependencies are captured for the workload prediction by using Long Short-Term Memory (LSTM) neural network model. A Gaussian Mixture Model (GMM) model is responsible for estimating the number of Virtual machines (VMs) present in the workload prediction process. The Self-Adaptive Genetic Algorithm (SAGA) is implemented for task mapping that adjusts the parameters to change workload patterns for contributing adaptability and robustness. The different experimental evaluations are conducted based on the task completion time, workload balance index, resource utilization efficiency and workload prediction accuracy. The proposed model achieved the workload prediction accuracy of 98.5%, cost of $89.6, execution time of 125ms, Task Completion Time (TCT) of 40ms, Workload Balance Index (WBI) of 0.96 and Resource Utilization Efficiency (RUE) of 0.93. The quantitative results collectively position HRMF-DRP as a practical and efficient solution, promising advancements in dynamic resource provisioning for cloud computing, particularly within the Infrastructure as a Service (IaaS) cloud model.

Medical Resource Management in Emergency Hierarchical Diagnosis and Treatment Systems: A Research Framework.

The occurrence of major public health crises, like the COVID-19 epidemic, present significant challenges to healthcare systems and the management of emergency medical resources worldwide. This study, by examining the practices of emergency medical resource management in select countries during the COVID-19 epidemic, and reviewing the relevant literature, finds that emergency hierarchical diagnosis and treatment systems (EHDTSs) play a crucial role in managing emergency resources effectively. To address key issues of emergency resource management in EHDTSs, we examine the features of EHDTSs and develop a research framework for emergency resource management in EHDTSs, especially focusing on the management of emergency medical personnel and medical supplies during evolving epidemics. The research framework identifies key issues of emergency medical resource management in EHDTSs, including the sharing and scheduling of emergency medical supplies, the establishment and sharing of emergency medical supply warehouses, and the integrated dispatch of emergency medical personnel. The proposed framework not only offers insights for future research but also can facilitate better emergency medical resource management in EHDTSs during major public health emergencies.

Retraction Note: Towards an adaptive human-centric computing resource management framework based on resource prediction and multi-objective genetic algorithm

Retraction Note: Towards an adaptive human-centric computing resource management framework based on resource prediction and multi-objective genetic algorithm

Intellectual property protection in the oil, gold sectors and mineral resources rent on indigenous populations: Preserving innovation and value

This study investigates into the intricate relationship between intellectual property protection and the wellbeing of indigenous communities within the oil, gold, and mineral sectors. Covering the period from 1990 to 2020 and focusing on nations rich in natural resources such as Russia, China, India, Indonesia, Nigeria, South Africa, Brazil, Canada, Mexico, Argentina, and Australia, the research employs advanced econometric models to dissect the dynamics between intellectual property protection, innovation within these sectors, and the preservation of economic and cultural values. The dependent variable in our analysis encompasses a composite measure that reflects the overall socio-economic and cultural impact of these sectors on indigenous communities. Our findings reveal that stronger intellectual property protection measures potentially foster innovation and value generation in these sectors. However, it also emerges that these measures could lead to adverse consequences for indigenous communities, including restricted access to resources and potential displacement. This work significantly contributes to understanding the complex interplay among intellectual property protection, indigenous communities, and the economic benefits derived from natural resource revenues, offering insights into optimizing policy frameworks for sustainable and equitable resource management.

OCL-MEC: An online CPU-core prediction based on load balancing framework for offloading resource management in mobile edge computing environment

Clients can increase or decrease the number of resources they use dynamically over time due to the elasticity of cloud resources. As a result, variations in resource demands and predefined VM sizes result in a lack of resource utiliation, load imbalances, and excessive power consumption. A framework of efficient resource management is proposed to address these issues, balancing the load accordingly and anticipating the resource utilization of the servers. By optimizing resource utilization and minimizing the number of active servers, this technique facilitates power savings. Under/overloaded servers reduce energy consumption, execution delay, and performance degradation through a resource prediction system that is deployed at the CPU. Moreover, OCL-MEC load-balancing and resource allocation algorithms are proposed to reduce data center network traffic and power consumption. Experiments on real-world workload datasets, namely Bitsbrain VM traces, are conducted to evaluate the proposed framework. Different performance metrics demonstrate the superiority of the proposed framework over state-of-the-art approaches. Power savings of up to 98 % can be achieved by the OCL-MEC framework using a decision tree load balancing model based on HMM prediction systems.

Water Resources Management In Small Islands: A Review of Public Policy Implementation In The Development of Lekloor Reservoir, Nomaha Island

Water scarcity in small island regions, including Kisar Island in Maluku, presents a pressing issue due to inadequate water resource management. This article aims to describe a holistic approach to addressing the challenges of water resource management and water scarcity on Kisar Island, Maluku. The research methodology employed is a mixed-method approach, combining technical feasibility studies for reservoir technology, policy analysis through literature reviews, and field assessments to evaluate the topographic, hydrological, and environmental conditions of Kisar Island. In the technical context, the article analyzes reservoir technology as a solution to address water issues, supported by the topographic and hydrological characteristics of Kisar Island. Additionally, the article examines relevant public policies, such as Government Regulation No. 7 of 2013 on National Spatial Planning, Provincial Regulation No. 16 of 2013 on Provincial Spatial Planning in Maluku, and District Regulation No. 1 of 2023 on District Spatial Planning in Maluku Barat Daya. Through this review, the article highlights the crucial role of policy in establishing a supportive framework for water resource management. Furthermore, the importance of local community participation in water resource management on Kisar Island is emphasized, asserting that active engagement from the local community is key to achieving success in sustainable water management efforts.

Assessment of Human Resource Management Framework from Islamic Paradigm: Proposition of an Islamic Model of Human Resource Management

The study of Human Resource Management (HRM) in the context of Islamic philosophy has gained traction especially in the last two decades. This paper aims to assess the HRM purpose, processes and practices in the light of Islamic doctrine to eventually present an Islamic model of HRM that is hinged upon Islamic principles and values. The postulated model offers a unique perspective by incorporating both contemporary and spiritual dimensions to HRM framework in order to provide a holistic outlook to the study of Islamic Human Resource Management (IHRM). The proposed model named The “AF Islamic HRM Model” is driven by two key Islamic concepts of Adl (justice) and Falah (wellbeing or success), where Adl represents an essential underlying element for all HRM processes as per the proposed IHRM model and the conception of Falah implies an ultimate reward or success in this world as well as in the world hereafter, as perceived from the Islamic belief system. The paper entails a qualitative research approach by evaluating the existing HRM models as well as analyzing the already available literature regarding Islamic perspective to the HRM theory to ultimately posit a model which contributes value to the existing knowledge base of Islamic HRM. There is not much research regarding the application of Islamic ideology to various facets of HRM and this study endeavors to address this research gap by proposing an IHRM model which consolidates both the contemporary HRM philosophy as well as the Islamic tenets and guidelines, encompassing diverse aspects of both religion and worldly life by providing insights about the conventional HRM body of knowledge with a touch of ethics and spirituality.

Development of big data assisted effective enterprise resource planning framework for smart human resource management.

The planning of human resources and the management of enterprises consider the organization's size, the amount of effort put into operations, and the level of productivity. Inefficient allocation of resources in organizations due to skill-task misalignment lowers production and operational efficiency. This study addresses organizations' poor resource allocation and use, which reduces productivity and the efficiency of operations, and inefficiency may adversely impact company production and finances. This research aims to develop and assess a Placement-Assisted Resource Management Scheme (PRMS) to improve resource allocation and usage and businesses' operational efficiency and productivity. PRMS uses expertise, business requirements, and processes that are driven by data to match resources with activities that align with their capabilities and require them to perform promptly. The proposed system PRMS outperforms existing approaches on various performance metrics at two distinct levels of operations and operating levels, with a success rate of 0.9328% and 0.9302%, minimal swapping ratios of 12.052% and 11.658%, smaller resource mitigation ratios of 4.098% and 4.815%, mean decision times of 5.414s and 4.976s, and data analysis counts of 6387 and 6335 Success and data analysis increase by 9.98% and 8.2%, respectively, with the proposed strategy. This technique cuts the switching ratio, resource mitigation, and decision time by 6.52%, 13.84%, and 8.49%. The study concluded that PRMS is a solid, productivity-focused corporate improvement method that optimizes the allocation of resources and meets business needs.

Developing an integrated framework for Marine Cultural Heritage (MCH) and Marine Protected Areas (MPA) across Africa and the Middle East

There is currently a significant imbalance in existing marine resource management frameworks. Across Africa and the Middle East there is a developing network of marine protected areas focused on natural heritage but with very limited engagement with area-based management for cultural heritage. Yet both natural and cultural heritage resources are subject to the same considerable threat levels from both natural and anthropogenic processes of change. The MarEA project is engaged in an extensive programme of mapping and documentation of endangered cultural heritage sites and landscapes across the MENA region. During the course of this and aligned work, its engagement with coastal communities and international practice has identified a clear need for more informed and holistic approaches to marine resource management. This study presents a model for the integrated management of natural and cultural heritage and proposes a framework for the future identification and designation of Marine Cultural Heritage in Protected Areas.

Inter-organisational human resource management and network orientation of worker representatives: a practice-based perspective

We develop a practice-based framework of inter-organisational human resource management that puts multi-employer work arrangements in inter-firm networks at its centre. By reinterpreting existing knowledge on multi-employer work arrangements and how they are managed, we delineate four processes in the assemblage of inter-organisational HR management. To illustrate the usefulness of our framework, we explore the question of whether and how an inter-organisational HR management develops in four exemplary cases of multi-employer work arrangements. These cases reveal that the quality and degree of inter-organisational HR management varies considerably, also depending on whether worker representatives show network awareness and orient their activities towards inter-organisational relations.

Female leadership in sports coaching: a case analysis of Chinese coaches through the ability–motivation–opportunity framework

Purpose This study aims to investigate how the role of female leadership works in sports coaching. Drawing key insights from the ability–motivation–opportunity (AMO) framework of human resource management, the authors explore the underlying mechanisms of female leadership and the role female coaches play in enabling athletes to develop their self-initiative through AMO enhancement. Design/methodology/approach The sample in this study is made up of 11female coaches from eight teams in China selected using purposive sampling. Data was collected and analyzed on various aspects of female leadership. Findings Analysis of interviews and secondary data show that the mechanisms and enablers related to AMO enhancing practices stimulated by female coaching leadership can increase team performance. Research limitations/implications This study opens new avenues for sports science research and strengthens the theoretical and practical understanding of the intentions and mechanisms female coaches implement as leaders in sports coaching. Originality/value First, this study contributes to the AMO framework by helping form new theoretical insights based on the understanding of female sports coaching mechanisms. Second, this study provides novel insights into female leadership literature by investigating the mechanisms of female leadership in the context of sports exercise. Third, this study also contributes to the body of research on sports coaching in Asia, especially that of Chinese women in such leadership roles.

Redesigning the HR processes for scaling up ISOQAR (India) Private Limited

Learning outcomes Post analysis of the case study, students will be able to comprehend the significance of Six Sigma and its integration with the human resources (HR) processes in the service sector. Post case study discussion, students will be able to: examine the HR processes of ISOQAR (India) and deduce the reasons to seek change in their approach; validate the importance of integrating Six Sigma in the human resource management (HRM) framework of an organization; and categorize the difficulties encountered while implementing Six Sigma in the service sector compared to those in a manufacturing environment. Case overview/synopsis In September 2006, four senior employees of an audit firm made the decision to start their own venture. They identified a gap in a sizable and fiercely competitive auditing industry. Nishid Shivdas, Suhas Risbood, Shiv Prakash Bhutra and Burgis Bulsara, co-founders of ISOQAR (India), had distinct leadership experiences that drove the organization to concentrate on developing a broad range of services, with a focus on management consulting, training and audit services. They created a distinctive positioning in market in a short span and reported growth by building strong customer relationships, providing high-quality service and personalized attention to individual clients and meeting deadlines. The wide gamut of services included areas such as the payment card industry, data security standard, information security management systems, business continuity management, service management systems, food safety management system, Responsible Jewellery Council certification services, retail audit services and risk assessment services. They concentrated on collaborating with UKAS for their accreditations. The focus on offering great services with faster response times, a varied array of services and the expertise of its founders let them to price their services at par with some of its competitors, and even higher in few cases. It did not have a large support staff; however, the ones they had were multifaceted, both full time and contractual. Being in the service industry, the founders realized that to maintain growth as the firm aims to grow geographically, their heavy engagement in the existing operations would have to give way to more standardized processes in general and HR in particular. Ensuring the integration of the current workforce to the Six Sigma framework presented challenges. Complexity academic level This case is designed for second-year students enrolled in Master of Business Administration/Post Graduate Diploma in Management (MBA/PGDM) or equivalent postgraduate-level programmes, in the domain of “Human Resource.” It will enable the students to engage with the significance of “Six Sigma” being used in various processes in the HRM framework. It can also be taught to students in the domain of Marketing because of its relevance to the service sector. Supplementary materials Teaching notes are available for educators only. Subject code CSS 6: Human Resource Management.

User-Centric Flexible Resource Management Framework for LEO Satellites With Fully Regenerative Payload

User-Centric Flexible Resource Management Framework for LEO Satellites With Fully Regenerative Payload

AI-driven resource management strategies for cloud computing systems, services, and applications

Cloud computing is a way for businesses and individuals to It has changed and revolutionized the way we access and use resources. However, efficient resource management in cloud computing systems remains a major challenge due to the scalability, heterogeneity, and dynamic nature of these environments. To address these challenges, artificial intelligence (AI) technology has emerged as an effective solution to improve resource management efficiency. This paper provides an overview of AI-based strategies for efficient resource management in cloud computing systems, services, and applications. This paper first reviews resource management challenges in cloud computing, including scalability, heterogeneity, quality of service requirements, and cost optimization. Below is an overview of the various AI techniques used for resource management. B. Algorithms for machine learning, reinforcement learning, predictive analytics, natural language processing, and genetic algorithms. Next, this paper considers specific AI-based strategies for efficient resource management. These strategies include automated resource provisioning and scaling, intelligent workload planning and task allocation, predictive maintenance and fault detection, and energy-efficient resource management. We also present case studies and applications of AI-driven resource management in various cloud computing scenarios, including large-scale cloud providers, edge computing, serverless computing, and container environments. This paper describes evaluation metrics and performance analysis techniques to evaluate the effectiveness of AI-based resource management approaches. It highlights the importance of ethical considerations, transparency, and explainability in AI-powered resource management systems. Additionally, the integration of AI technologies into existing resource management frameworks is discussed, and future directions are identified, including B. real-time resource optimization and coordination.

Fostering second-life applications for electric vehicle batteries: A thorough exploration of barriers and solutions within the framework of sustainable energy and resource management

Electric vehicles (EVs) play a crucial role in achieving Sustainable Development Goals (SDGs), specifically focusing on Goal 7, which ensures access to Affordable and Clean Energy, and Goal 9, promoting advancements in Industry, Innovation, and Infrastructure. However, the growing stockpile of used EV Batteries (EVBs) presents challenges. These EVBs, however, hold potential for second-use applications, aligning with energy conversion, resource optimization, and sustainable energy systems. This study employs a rigorous multi-criteria approach to bridge the research-practice gap by systematically evaluates and prioritizes barriers hindering the widespread adoption of second-use EVBs. The study's overarching objectives are to overcome these barriers, aligning with broader sustainability goals, and to offer insights shaping policies addressing environmental, social, and economic impacts, in coherence with SDGs 8, 11, 12, and 13. The research unfolds through a three-phase approach involving literature reviews, field visits, and expert interviews for barrier identification, theoretical framework development through literature and Delphi studies, and prioritization using the Fuzzy Best-Worst Method (FBWM). Results indicate that addressing Cost and Technological Challenges is pivotal for successful second-use EVB adoption, with proposed solutions involving regulations, recycling, and awareness. The study underscores the circular economy perspective, connecting identified barriers to specific SDGs. The FBWM proves effective in prioritizing barriers, providing actionable insights for policymakers and stakeholders. This research contributes significantly to the existing literature by systematically evaluating second-use EVBs, addressing a crucial research gap, and offering valuable pathways for broad adoption.

Legal Framework of Community-Based Water Resource Management to Achieve SDGs and “No One Left Behind”

This study aims to examine community-based water resources management implemented in Umbul Ponggok Village, Klaten Regency, Central Java, Indonesia, based on the Water Resources Law (2019) and was subsequently modified by the Job Creation Law (2023), which prioritizes the well-being of the local community and in order to achieve sustainable development goals (SDGs), especially the principle of No.-One Left Behind. Community involvement in water resources management is very important. Therefore, communities no longer only act as consumers but also as those who determine their own needs for water resources. One area that has implemented this approach is the community in Ponggok Village, Klaten Regency. Therefore, this study addressed the compliance of the community-based water resource management in Ponggok Village, Klaten Regency, with the existing regulations. The study also determined whether the community complies with the principles of Sustainable Development Goals (SDGs) through a juridical-empirical method. Data was collected through documentation and interviews, and qualitatively analyzed. The result showed that the practices of water resource management in Ponggok Village aligned with existing regulations. However, a notable gap existed in adhering to reporting regulations, attributed to a lack of awareness among the village apparatus. Then, the water resource management in Ponggok Village has fully aligned with the current regulations and the SDGs' principles.

A Trustworthy and Responsible Decision-Making Framework for Resource Management in Food-Energy-Water Nexus: A Control-Theoretical Approach

This paper introduces a hybrid framework for trustworthy and responsible natural resource management, aimed at building bottom-up trust to enhance cooperation among decision makers in the Food, Energy, and Water sectors. Cooperation is highly critical for the adoption and application of resource management alternatives (solutions), including those generated by AI-based recommender systems, in communities due to significant impact of these sectors on the environment and the economic productivity of affected communities. While algorithms can recommend solutions, effectively communicating and gaining community acceptance of these solutions is crucial. Our research stands out by emphasizing the collaboration between humans and machines, which is essential for addressing broader challenges related to climate change and the need for expert trade-off handling in the management of natural resources. To support future decision-making, we propose a successful control-theory model based on previous decision-making and actor behavior. We utilize control theory to depict how community decisions can be affected by how much individuals trust and accept proposed solutions on irrigation water rights and crop operations in an iterative and interactive decision support environment. This model interacts with stakeholders to collect their feedback on the acceptability of solutions, while also examining the influence of consensus levels, trust sensitivities, and the number of decision-making rounds on the acceptance of proposed solutions. Furthermore, we investigate a system of multiple decision-making and explore the impact of learning actors who adjust their trust sensitivities based on solution acceptance and the number of decision-making rounds. Additionally, our approach can be employed to evaluate and refine potential policy modifications. Although we assess potential outcomes using hypothetical actions by individuals, it is essential to emphasize our primary objective of developing a tool that accurately captures real human behavior and fosters improved collaboration in community decision-making. Ultimately, our aim is to enhance the harmony between AI-based recommender systems and human values, promoting a deeper understanding and integration between the two.

Retraction notice: Federate learning of corporate social authority and industry 4.0 that focus on young people: a strategic management framework for human resources

Retraction notice: Federate learning of corporate social authority and industry 4.0 that focus on young people: a strategic management framework for human resources

Generative Artificial Intelligence in Business: Towards a Strategic Human Resource Management Framework

AbstractAs businesses and society navigate the potentials of generative artificial intelligence (GAI), the integration of these technologies introduces unique challenges and opportunities for human resources, requiring a re‐evaluation of human resource management (HRM) frameworks. The existing frameworks may often fall short of capturing the novel attributes, complexities and impacts of GAI on workforce dynamics and organizational operations. This paper proposes a strategic HRM framework, underpinned by the theory of institutional entrepreneurship for sustainable organizations, for integrating GAI within HRM practices to boost operational efficiency, foster innovation and secure a competitive advantage through responsible practices and workforce development. Central to this framework is the alignment with existing business objectives, seizing opportunities, strategic resource assessment and orchestration, re‐institutionalization, realignment and embracing a culture of continuous learning and adaptation. This approach provides a detailed roadmap for organizations to navigate successfully the complexities of a GAI‐enhanced business environment. Additionally, this paper significantly contributes to the theoretical discourse by bridging the gap between HRM and GAI adoption, the proposed framework accounting for GAI–human capital symbiosis, setting the stage for future research to empirically test its applicability, explore its implications on HRM practices and understand its broader economic and societal consequences through diverse multi‐disciplinary and multi‐level research methodologies.

Conceptual Framework of Green Human Resource Management (GHRM) for Corporate Sustainability

Conceptual Framework of Green Human Resource Management (GHRM) for Corporate Sustainability