Resource Management Problem Research Articles

Analysis of Employee Satisfaction in Non-Profit Organisations - Based on a Survey of an Association in Nanjing City

Since the beginning of the 21st century, with the gradual expansion of the non-profit organization team, its related needs in human resource management have become increasingly urgent. And the related research on human resource management in non-profit organizations has gradually attracted attention. However, compared with the more mature research on human resource management in for-profit organizations, there are relatively few studies on human resource management in non-profit organizations. This paper selects employee satisfaction as the starting point to study the human resource management of non-profit organizations. Employee satisfaction, as one of the dimensions for judging the human resource management level of non-profit organizations, can detect problems in the human resource management of the organization as early as possible and make corresponding improvements to meet the needs of employees and enhance their work enthusiasm. At the same time, employee satisfaction can also predict employees' mobility intentions and become an important reference for preventing brain drain in advance. This research is based on the relevant theory of job satisfaction, using a questionnaire survey and in-depth interviews as research methods. Take an association in Nanjing as an example to conduct field research and analysis on employee satisfaction in non-profit organizations. In-depth analysis, using SPSS software to carry out descriptive statistical analysis on the data collected by the questionnaire survey and test the reliability and validity of the questionnaire results, found the shortcomings of human resource management in non-profit organizations. Through relevant theoretical analysis, taking into account the actual situation of the association, it puts forward corresponding improvement measures and suggestions for the human resource management of non-profit organizations.

Use of an Ecological Compensation Model in Water Resource Development: A Case Study from Shaanxi Province, China

This study aims to analyze the current situation of water resource management in Shaanxi Province, study the basic principles of ecological compensation, evaluate the impact of water conservation projects on the ecological environment by establishing a model, and propose a sustainable water resource management model. Hanzhong City has certain typicality and representativeness within Shaanxi Province, and the problems it faces in water resource management and ecological environment may represent the entire province or similar regions. At the same time, Hanzhong City has rich data and research foundations. Therefore, by conducting a detailed analysis of the current water resource status in the Hanzhong City area of Shaanxi Province, the problems in current water resource management are revealed, and the basic principles of ecological compensation are intensely studied. The original ecological compensation plan in Shaanxi Province has been summarized. Guided by the concept of sustainable development, an ecological compensation model is established using algorithms, and the model is applied to sustainable water resource management. Establish a model for water conservation and water resource management through data collection, preprocessing, and cleaning, and apply it to practical cases in Hanzhong City. Through simulation and analysis of Hanzhong City, the new water resource management model effectively mitigates the adverse effects of water conservation projects on the ecological environment while improving water resource utilization efficiency. The changes in various environmental parameters indicate that the new plan has improved the ecological environment. Through the application of the model, the ecological compensation plan formulated has achieved sustainable protection of the ecological environment while promoting economic development. This study proposes a sustainable water resource management model through a comprehensive study of water resource management and ecological compensation in Shaanxi Province and verifies it in practical cases, demonstrating that the model has not only good applicability but also has significant effects in promoting economic growth and ecological environment protection.

A Self-Adaptive Collaborative Differential Evolution Algorithm for Solving Energy Resource Management Problems in Smart Grids

A Self-Adaptive Collaborative Differential Evolution Algorithm for Solving Energy Resource Management Problems in Smart Grids

The correlative factors of enterprise culture and enterprise human resource based on data analysis and federated learning

Under the current big topic of enterprise management, how to cultivate, use, and maintain talents is the critical problem of modern human resource management. Based on big data mining, cloud computing, and other related model optimization technologies, this study explores the crucial significance of enterprise culture construction and enterprise human resource management in achieving the business objectives of the entire enterprise. The establishment of this model also means that the enterprise’s profit margin and business indicators have been improved and developed under a certain model. The case results demonstrate that the optimized competency model is significant to studying corporate culture management system behavior, policy analysis, and improving corporate human resource management policies.

Strategies to Improve Employee Engagement and HR Quality at M Educational Institution Jakarta

The development of education is no less important than the economic and social world. However, in recent years the workforce in the world of education has experienced significant turnover which has hampered the development of teaching. Therefore, it is necessary to analyze and discuss the level of employee engagement and the quality of human resource management using the example of the educational institution M Educational Institution Jakarta. This research was conducted by conducting interviews and distributing questionnaires to educational personnel as subjects. In this study, we identified the core concepts of employee engagement in educational institutions, designed an engagement questionnaire and a satisfaction questionnaire, and conducted a survey. Getting the results from this research, there are problems such as incomplete human resource development mechanism, high human resource mobility, serious exit of high-quality human resources, unbalanced faculty staffing structure, and incomplete performance evaluation and incentive mechanism. Analyzing the problems and their causes, it is necessary to propose constructive solutions and countermeasures, identify common problems in employee participation and human resource management in educational institutions, and improve strategy development and policy adjustment depending on the problems. The result of this research is that increasing employee engagement and the quality of human resources is very important. In the development of the M Educational Jakarta institution, it requires the implementation of a scientific and rational human resource management mechanism, with the concept of project management as a systematic implementation framework, which can also be a guide in managing HR in educational institutions, and ensuring the effectiveness of HR operations.

Lean sustainability and triple bottom line performance of manufacturing industries in a developing economy: does top management commitment matter?

PurposeAlthough literature abounds on lean sustainability (LS), its contributions to manufacturing industries’ triple bottom line performance (TBLP) through top management commitment (TMC) remain scanty. This research explores the mediating role of TMC in the nexus between LS and TBLP.Design/methodology/approachGiven the study’s quantitative focus, the causal design was utilised. The structured questionnaire, a survey instrument, was used to gather primary data from 285 manufacturing organisations in Ghana, a developing country. Data analysis was done with structural equation modelling.FindingsIt was found that LS and TMC positively influence TBLP, whereas TMC partially mediates the connection between LS and TBLP of Ghanaian manufacturing organisations.Research limitations/implicationsThe study concentrates on Ghana’s manufacturing industry and embraces the stakeholder theory and quantitative methods.Practical implicationsThis research underlines why top managers must prioritise investment in LS to promote sustainable development and attain their organisations’ TBLP targets. The study also provides key insights for top managers to consistently commit enormous resources towards developing lean practices, contributing favourably to TBLP. By establishing the interplay among LS, TMC and TBLP, manufacturing practitioners and researchers can further advance new strategies to address the growing sustainability concerns and achieve higher economic, social and environmental performance.Originality/valueThe study’s originality lies in analysing the mediation effect of TMC on the linkage between LS and TBLP in a developing economy where manufacturing organisations are continuously exposed to resource and waste management problems and lack adequate commitments from top managers towards sustainability initiatives. It is also the first to establish relationships between top management commitment and TBLP in the manufacturing industries of developing economies, concentrating on Ghana.

Rethinking Urban Water Management Through Drivers-Pressures-States-Impacts-Responses Framework Application in Chennai, India

Cities suffering water scarcity are projected to increase in the following decades. However, the application of standardized indicator frameworks for assessing urban water resource management problems is on an early stage. India is expected to have the highest urban population facing water scarcity in the world by 2050. In this study, the authors assess how the Drivers-Pressures-States-Impacts-Responses framework, a causal framework adopted by the European Environment Agency, can contribute to evaluate water management challenges in cities and apply it to Chennai, India´s fourth-largest urban agglomeration. The framework proved to be a helpful tool for the evaluation of water management challenges in cities by disentangling relationships between environmental indicators and structuring dispersed data that allows a better understanding for policymakers. The main drivers identified in Chennai were population growth and economic development which generated impacts such as loss of aquatic ecosystems, low water table, low water quality, and reduction of biodiversity and human health. As a response, better urban planning, projects for new water infrastructure, and water bodies restoration have been implemented. Nevertheless, Chennai keeps facing difficulties to achieve proper water management. The severe hit of the COVID-19 pandemic on the Indian economy and its future management will be key for achievements related to water management.

Biophysical Resource Characterization, Identification and Prioritization of Major Constraints and Potentials of Gara Ebanu Community Watershed in Sululta District, Ethiopia

Baseline characterization helps to understand the initial livelihood condition of the people in the watershed before and after the intervention of the project to measure the amount of change attained by the project. The objective of the study was to characterize baseline information on the existing biophysical resource used as benchmark for planning and impact monitoring and to identify and major constraints and potential in the watershed. The watershed was selected depending on agro-ecological representation, prevalence of resource management and land degradation problems and accessibility for intensive follow-up. Based on the preliminary outlet identified during the watershed selection process, the watershed boundary was delineated using GPS data and the map of watershed was geo-referenced and digitized for its contour, roads, rivers, and other features. Both primary and secondary data were used for the study and primary data was collected through field observation, household survey, focus group discussion and interview of the key informants. From the total 103 household heads living in the watershed, 62 household heads were selected as a respondent for the study. The collected data was managed and analyzed using Statistical Package for Social Sciences (SPSS) and Microsoft excel 2010. The results of the study showed that about 29.4% of the watershed slope was characterized by flat lands, 45.7% moderate slope and 24.9% steep lands. As well as soil fertility status of cultivated land in the watershed were 33.9% low, 55.9% moderate and 10.2% high. The results of the study showed that the major constraints identified by sampled household heads were decline of soil fertility, soil erosion, climate change, land shortage, and deforestation were significantly contributed to the low crop yield in the watershed. About 27.4% of the sampled households had encountered decline of soil fertility problems, 25.8% of sample farmers encountered soil erosion problem, and 22.6% of sample farmers encountered climate change problem in the watershed. From the identified major constraints, the highest priorities were given for decline of soil fertility, soil erosion problem, shortage of feed and fodder, and decline of crop productivity respectively. In the watershed, immediate short-term actions should be taken particularly participatory integrated watershed management were recommended.

Relationship between perceived human resource management system strength, thriving at work, and employee's turnover intention in Chinese hotels

AbstractThe high turnover rate of employees is one of the core problems of human resource management (HRM) in the hotel industry. We aim to propose a fresh perspective on hotel HRM by examining the impact of HRM system strength on employees' turnover intentions from a motivational process perspective. Introducing thriving at work as a mediator, we argue that employees' perceived HRM system strength not only provides a basis for rational judgment but also elicits affective evaluation through thriving at work to reduce turnover intention. Grit, a motivation‐related personality trait, is also considered a moderator. Data from 420 Chinese hotel employees showed that perceived HRM system strength (distinctiveness, consistency, and consensus) reduced turnover intention. Thriving at work partially mediated the relationship, while employee grit moderated the link between HRM strength and thriving. The theoretical and practical implications are discussed.

Client selection and resource scheduling in reliable federated learning for UAV-assisted vehicular networks

Federated Learning (FL), a promising deep learning paradigm extensively deployed in Vehicular Edge Computing Networks (VECN), allows a distributed approach to train datasets of nodes locally, e.g., for mobile vehicles, and exchanges model parameters to obtain an accurate model without raw data transmission. However, the existence of malicious vehicular nodes as well as the inherent heterogeneity of the vehicles hinders the attainment of accurate models. Moreover, the local model training and model parameter transmission during FL exert a notable energy burden on vehicles constrained in resources. In view of this, we investigate FL client selection and resource management problems in FL-enabled UAV-assisted Vehicular Networks (FLVN). We first devise a novel reputation-based client selection mechanism by integrating both data quality and computation capability metrics to enlist reliable high-performance vehicles. Further, to fortify the FL reliability, we adopt the consortium blockchain to oversee the reputation information, which boasts tamper-proof and interference-resistant qualities. Finally, we formulate the resource scheduling problem by jointly optimizing the computation capability, the transmission power, and the number of local training rounds, aiming to minimize the cost of clients while guaranteeing accuracy. To this end, we propose a reinforcement learning algorithm employing an asynchronous parallel network structure to achieve an optimized scheduling strategy. Simulation results show that our proposed client selection mechanism and scheduling algorithm can realize reliable FL with an accuracy of 0.96 and consistently outperform the baselines in terms of delay and energy consumption.

Integrated Sensing, Communication, and Computing for Cost-effective Multimodal Federated Perception

Federated learning (FL) is a prominent paradigm of 6G edge intelligence (EI), which mitigates privacy breaches and high communication pressure caused by conventional centralized model training in the artificial intelligence of things (AIoT). The execution of multimodal federated perception (MFP) services comprises three sub-processes, including sensing-based multimodal data generation, communication-based model transmission, and computing-based model training, ultimately competitive on available underlying multi-domain physical resources such as time, frequency, and computing power. How to reasonably coordinate the multi-domain resources scheduling among sensing, communication, and computing, therefore, is vital to the MFP networks. To address the above issues, this article explores service-oriented resource management with integrated sensing, communication, and computing (ISCC). Specifically, employing the incentive mechanism of the MFP service market, the resources management problem is defined as a social welfare maximization problem, where the concept of “expanding resources” and “reducing costs” is used to enhance learning performance gain and reduce resource costs. Experimental results demonstrate the effectiveness and robustness of the proposed resource scheduling mechanisms.

Advancing sustainable development through circular economy and skill development in EV lithium-ion battery recycling: a comprehensive review

The rapid worldwide transition to electric vehicles (EVs), propelled by progress in lithium-ion battery (LIB) technology, brings opportunities and problems in sustainable development and resource management. This study examines how incorporating circular economy ideas and enhancing skills in EV LIB recycling can be a strategic approach to meeting the 2030 Agenda for Sustainable Development. The article explores the relationship between environmental sustainability, economic growth, and social fairness by studying EV battery recycling, the workforce skills gap, and the economic ramifications of a circular approach. Based on the existing literature, the study highlights the importance of circular economy practices in improving resource efficiency, decreasing environmental pollution, and supporting various Sustainable Development Goals (SDGs), especially those concerning responsible consumption and production (SDG 12), climate action (SDG 13), and industry, innovation, and infrastructure (SDG 9). The study highlights the significance of Education for Sustainable Development (ESD) in preparing the workforce with the essential skills to adapt to a more sustainable and circular economy. It also highlights significant obstacles in present recycling methods, such as technological limitations, legislative discrepancies, and the necessity for worldwide collaboration and standardization. The paper suggests practical policy suggestions and future research paths to improve the sustainability of EV battery recycling. The initiatives involve establishing global recycling standards, promoting circular economy models through incentives, boosting technological innovation, and facilitating international collaboration and knowledge exchange.

Collaborative Computation Offloading and Resource Management in Space–Air–Ground Integrated Networking: A Deep Reinforcement Learning Approach

With the increasing dissemination of the Internet of Things and 5G, mobile edge computing has become a novel scheme to assist terminal devices in executing computation tasks. To elevate the coverage and computation capability of edge computing, a collaborative computation offloading and resource management architecture was proposed in space–air–ground integrated networking (SAGIN). In this manuscript, we established a novel model considering the computation offloading cost constraints of the communication, computing and cache model in the SAGIN. To be specific, the joint optimization problem of collaborative computation offloading and resource management was modeled as a mixed integer nonlinear programming problem. To address this issue, this paper proposed a computation offloading and resource allocation strategy based on deep reinforcement learning (DRL). Differing from traditional methods, DRL does not need a well-established formulation or previous information, and it is capable of revising the strategy adaptively according to the environment. The simulation results demonstrate the proposed approach can achieve the optimal reward values in the case of different terminal device numbers. Furthermore, this manuscript provided the analysis with variant parameters of the proposed approach.

Deep Learning-Assisted Online Task Offloading for Latency Minimization in Heterogeneous Mobile Edge

With the proliferation of smart devices in recent years, many applications requiring high computing capability and low latency have emerged. Edge computing is one of the promising paradigms to support such applications. Due to the high volatility of edge environments, e.g., frequent movements of mobile devices, varying task sizes, and time-variant channel conditions, we have to make the offloading and resource management decisions on the fly. This paper formulates and studies the problem of online task offloading and resource management in heterogeneous mobile edge environments. The goal of the problem is to minimize the overall system latency. We prove that the problem is NP-hard. Moreover, traditional algorithms needing long decision-making times are insufficient to support applications with high volatility. This paper proposes a deep learning-assisted online algorithm that can make fast decisions. In particular, we design an offline solver for the proposed problem and use a deep neural network to emulate the solver. We conduct extensive simulations to evaluate the proposed approach. Results show that the proposed approach is around <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$50,000\times$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$500\times$</tex-math></inline-formula> faster than the commercial Gurobi solver for the optimal solution and the proposed offline approximation solver, respectively. Moreover, the overall latency under the proposed approach is near-optimal.

Fundamental Problems of Water Resources Management in the Helmand River Basin, Afghanistan

The closed hydrology and the geopolitical nature of the Helmand River basin in terms of leadership, management, and use of water resources have created serious threats to its integrity, environmental health, and human security in this river basin. The Helmand River basin, where about 8 million people live, includes about 49 percent of the soil and 11 percent of the water flow of this country. Agricultural sectors and related industries are the main drivers of the economy in this basin and due to the increasing need for food in the country and the region, the population shift towards cities, industrialization, and most importantly climate change and water shortage, competition between major water consumers in this basin is increasing. Despite the increasing number of studies on the water management of the Helmand River basin, no practical research carried out to strengthen and summarize the common conclusions and findings related to the fundamental problems facing the water resources management of this river basin. Therefore, in this article, to fill the aforementioned gap, all related documents, studies, and topics have been comprehensively reviewed and analyzed. To achieve this goal, the qualitative-analytical research method was used to analyze and find the key issues raised, and as a result, the basic problems facing the water resources management of this basin were investigated as much as possible. In the following, the necessary suggestions are also presented so that by implementing it, this country would be able to solve the existing problems by using its hydro political capacities and opportunities and it would also be placed at the center of the water interactions in the river basin, to provide a sustainable and all-round development of the country.

Spatio-Temporal Evolution of Olive Tree Water Status Using Land Surface Temperature and Vegetation Indices Derived from Landsat 5 and 8 Satellite Imagery in Southern Peru

Land surface temperature (LST) and its relationship with vegetation indices (VIs) have proven to be effective for monitoring water stress in large-scale crops. Therefore, the objective of this study is to find an appropriate VI to analyse the spatio-temporal evolution of olive water stress using LST images and VIs derived from Landsat 5 and 8 satellites in the semi-arid region of southern Peru. For this purpose, VIs (Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index 2 (EVI2) and Soil Adjusted Vegetation Index (SAVI)) and LST were calculated. The information was processed in Google Earth Engine (GEE) for the period 1985 to 2024, with an interval of every five years for the summer season. The triangle method was applied based on the LST-VIs scatterplot analysis, a tool that establishes wet and dry boundary conditions for the Temperature Vegetation Dryness Index (TVDI). The results indicated a better appreciation of olive orchard water stress over time, with an average of 39% drought (TVDINDVI and TVDISAVI), 24% severe drought (TVDINDVI) and 25% (TVDISAVI) of the total area, compared to TVDIEVI2, which showed 37% drought and 16% severe drought. It is concluded that TVDINDVI and TVDISAVI provide a better visualisation of the water stress map of the olive crop and offer a range of options to address current and future problems in water resource management in the olive sector in semi-arid areas of southern Peru.

Guiding Fuzzy Cognitive Mapping With Structured Decision Making to Inform Complex Natural Resource Management Problems in Waiʻanae Hawaiʻi

AbstractFire is one example of a larger class of wicked environmental management problems that require community‐based management for long‐term success. This study aimed to support participatory decision making in a data poor and complex system by using Fuzzy Cognitive Mapping (FCM) within the decision‐making framework Structured Decision Making (SDM) to develop a community‐based wildfire management plan in partnership with a local group in Wai‘anae Hawaiʻi. SDM is an organized process to create and evaluate decisions that can clarify trade‐offs and increase transparency. FCM is a semi‐quantitative method to describe system relationships that can handle low data and high uncertainty. We used SDM to define the problem, articulate community concerns related to wildfire, and identify management actions. We then used FCM to model how these actions affected valued ecosystem services and other stakeholder‐identified objectives. Modeling results highlighted the trade‐offs across three valued ecosystem services from three community‐led wildfire management actions. We found that native species outplanting was the most beneficial action to each of the three valued ecosystem services. Through this participatory research, we conclude that the SDM and FCM pairing provided an inclusive and cost‐effective way to engage with a specific wildfire management context, and that the process effectively engaged stakeholders while tackling uncertainty. This process also aided consensus‐building and group member communication. This pairing can be used to aid community decision‐making across diverse management problems as it provides a way to elicit objectives and model trade‐offs, even under uncertainty and data limitations, while including stakeholders impacted by such decisions.

Power-Efficient Dispatching of Time-Sensitive Requests in the Fog-Enabled Industrial Internet of Things

Recent advancements in service offerings and the emergence of new application areas have reveal the limitations of cloud computing as a solely solution. One of these new areas is the industrial internet of things, where industrial processes are controlled in a network-based and automated way which brings many new challenges. To solve the challenges, fog computing has been introduced as a complementary paradigm to the cloud. Resource management is one of those challenges need further investigation. The industrial internet of things by its own characteristics has led traditional methods to be inefficient within this evolving ecosystem. Therefore, fully utilizing potential of the new system necessitates effective resource management. This manuscript aims to investigate the problem of resource management in the emerging cloud-fog ecosystem of the industrial internet of things. Considering the dynamic nature of users, this study proposes the algorithms for dynamic resource allocation and provisioning based on deadlines. We formulate the problem as a multiple criteria stochastic problem and introduced an online solution. Our proposed solution takes into account the unique characteristics of Fog computing and the dynamic behavior of users. To effectively handle the scheduling of requests, the research suggests utilizing the Lyapunov optimization method and Lyapunov drift theory. The Lyapunov method helps to merge and measure all the related objectives in terms drift. The objective function is optimized, in each time slot, using a drift-plus-penalty weight parameter. By adopting this approach, the system can operate efficiently while meeting the constraints and performance requirements of IoT applications.

SOFTWARE FOR SOLVING THE TWO-STAGE LOCATION-ALLOCATION PROBLEMS

This article explores the construction of the mathematical model, method, and algorithm for solving the two-stage optimal location-allocation problem, along with the software implementation for algorithm execution. The developed algorithm enables the resolution of resource management and transportation problems from supply centers to consumer spaces. Considering that in the contemporary world where all resources and goods are transported over considerable distances in substantial volumes, the task of optimizing delivery routes and minimizing delivery costs remains relevant. The created algorithm can be integrated into a logistics system comprising two layers of resource delivery: initially to an intermediate supply center and subsequently to the ultimate consumer.

Development and implementation of human resources management policies and strategies in the Romanian public administration

Human activity seen from various perspectives: social, economic, political, administrative is carried out by people organized in collectives, depending on its importance. The administrative approach comes to order the logic of activity in a community entrusted to an authority that carries out planning, organization and control actions, in order to achieve the social mission and the purpose of the establishment and operation of public administration institutions. In this context, we propose a brief, specified approach to the need to streamline the activities of public administration authorities. The problem of human resources management in public administration requires a specified approach to the objectives of streamlining the activities of public administration authorities based on a human resources management strategy, which would contribute to the creation of a professional, transparent, flexible and responsive public function to the needs of society. The policies in the field of public office and civil servants represent a particularly important and always current key issue for ensuring the competitiveness and success of any public institution, even more so of the public administration.