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Rezhen, Harun, Hameed Khansa, Sirwan Kawan, et al. "The Effect of Human Resource Management on Employees and Business Performance: An Environmental Perspective." Contemporary Research Analysis Journal 02, no. 03 (2025): 163–72. https://doi.org/10.5281/zenodo.15056892.
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ABSTRACT: The impact of human resource management (HRM) on organization efficiency is analyzed in this article. The key aim was to analyze the literature in the area of human resources management and business performance critically and systematically, culminating in a succinct literature review. A body of literature discusses the human resources management and business performance relation, so there was plenty of space for a detailed review of different articles. To be more accurate, eighteen articles from several stages in the review process were reviewed. The outcome indicates a positive relationship between human resource management practices and overall business performance. Additionally, human resource management positively influences worker wellbeing, competitiveness, and organizational environment. Indeed, there is a good chance that good human resource management practices are not the cause but the effect of good business performance. This topic is introduced and elaborated in the current article. This systematic review paper is rightly based on the information obtained from the data collected and the findings derived. Finally, the paper should be regarded as a preliminary study in the field of human resource management activities and their influence on performance of business for further research.
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Bayer, Rachel, and Catherine Sorenson. "Resource Review: Breakout EDU." Journal of Youth Development 15, no. 6 (2020): 326–33. http://dx.doi.org/10.5195/jyd.2020.919.
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Game-based learning is becoming an increasingly popular pedagogical technique for providing engaging learning experiences for youth. The Breakout EDU platform provides an opportunity to bring game-based learning into formal and non-formal learning environments using an escape-room-like approach while teaching specific subject areas and building life skills. There are more than 1,500 ready-made games for teaching a variety of topic areas, from science and math to team building, in any learning context. It also provides resources and tools to support youth development professionals in creating their own games. This review provides an overview of Breakout EDU and its kit and digital platform components and offers considerations for youth development professionals.
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Gingerich, Barbara Stover. "Resource Review: Introduction to Community-Based Nursing." Home Health Care Management & Practice 19, no. 3 (2007): 224–26. http://dx.doi.org/10.1177/108482230296832.
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Francoeur, Mine. "Book Review: Adventure Based Resource Index System." Journal of Experiential Education 12, no. 1 (1989): 46. http://dx.doi.org/10.1177/105382598901200115.
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Taib, Khairul Mizan Bin, and Thrisny Regina Febrianti Sanjaya. "Project Human Resource Management: Literature Review." Edulib 13, no. 1 (2023): 1–12. http://dx.doi.org/10.17509/edulib.v13i1.72803.
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This paper aims to define the role of project human resource management inside a company, as well as its stages and impacts. using the semantic method of literature review. Based on the study's findings, companies could maintain relationships amongst their human resources and make the greatest use of their current resources through implementing human resource management projects along with overseeing their own business activities.
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Evans, W. Randy, Milorad M. Novicevic, and Walter D. Davis. "Resource-based foundations of strategic human resource management: a review and extension." International Journal of Learning and Intellectual Capital 4, no. 1/2 (2007): 75. http://dx.doi.org/10.1504/ijlic.2007.013824.
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Mahboob, M. A., T. Celik, and B. Genc. "Review of machine learning-based Mineral Resource estimation." Journal of the Southern African Institute of Mining and Metallurgy 122, no. 11 (2023): 1–10. http://dx.doi.org/10.17159/2411-9717/1250/2022.
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Mineral Resources estimation plays a crucial role in the profitability of the future of mining operations. The conventional geostatistical methods used for grade estimation require expertise, understanding and knowledge of the spatial statistics, resource modelling, geology, mining engineering as well as clean validated data to build accurate block models. However, the geostatistical models are sensitive to changes in data and would have to be rebuilt on newly acquired data with different characteristics, which has proved to be a time-consuming process. Machine learning methods have in recent years been proposed as an alternative to the geostatistical methods to alleviate the problems these might suffer from in Mineral Resource estimation. In this paper, a systematic literature review of machine learning methods used in Mineral Resource estimation is presented. This has been conducted on such studies published during the period 1990 to 2019. The types, performances, and capabilities, of several machine learning methods have been evaluated and compared against each other, and against the conventional geostatistical methods. The results, based on 31 research studies, show that the machine learning-based methods have outperformed the conventional grade estimation modelling methods. The review also shows there is active research on applying machine learning to grade estimation from exploration through to exploitation. Further improvements can be expected if advanced machine learning techniques are to be used.
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Ramgopal, K. Ratnawat. "Competency Based Human Resource Management: Concepts, Tools, Techniques, and Models: A Review." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 05 (2018): 119–24. https://doi.org/10.5281/zenodo.1253424.
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The concept of competency based human resource management has gained significant momentum in last couple of decades especially since McClleland (1973) defined competencies as a critical differentiator for performance. Competency mapping as a part of competency-based management has thus attracted the attention of researchers and practitioners alike. The researcher through this article takes a review of relevant literature to describe how competency mapping has been applied in managing different human resource functions. The synthesis of knowledge gathered through this review is expected to provide a comprehensive account of the evolution of the concept and a review of relevant theories, models, and processes stimulating further research.
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MILUPI, I. D. "A REVIEW OF COMMUNITY-BASED NATURAL RESOURCE MANAGEMENT." Applied Ecology and Environmental Research 15, no. 4 (2017): 1121–43. http://dx.doi.org/10.15666/aeer/1504_11211143.
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Ibiba, Ambie Georgewill. "Entrepreneurial Human Resource Management: A Conceptual Review." European Journal of Business and Innovation Research 11, no. 1 (2023): 21–30. http://dx.doi.org/10.37745/ejbir.2013/vol11n12130.
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Entrepreneurial human resource is best defined as the set or sets of human resources practices that will increase the likelihood that new knowledge will be converted to new products or services through innovativeness and proactive actions. This paper conceptually entrepreneurial human resource management. The paper conceptualised the dimensions of entrepreneurial human resource management as entrepreneurial-based compensation, entrepreneurial-based training and development, entrepreneurial-based performance management. The paper used a desk research methodology since it is largely a literature review. Based on the review of extant literature, the paper concludes that entrepreneurial human resource management influences the efficiency of organizations positively. The paper recommends that this study should be approved for an empirical study to be carried out within Indigenous oil and gas companies in South-South, Nigeria, as data generating unit, so as to test the conceptual model developed and validate the concepts reviewed.
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HamaAli, Kurdistan Wns, and Subhi R. M. Zeebaree. "Resources Allocation for Distributed Systems: A Review." International Journal of Science and Business 5, no. 2 (2021): 76–88. https://doi.org/10.5281/zenodo.4462088.
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Resource allocation in a distributed system is the process of allocating the workload across multiple resources to optimize the required performance criteria. Different techniques are used to manage resource allocation in such distributed systems. The resource allocation for distributed systems such as cloud computing, cellular network, Software-Defined Networking (SDN), Radar Imaging and 5G Networks are used. In this paper many resource allocation algorithms in different environment and area that mentioned before are reviewed, compared and summarized. for instance, Cloud-based computation algorithm implementations in cloud computing, Direction Method of Multipliers (ADMM) algorithm for SDN Networking, FFR algorithm application in cellular network, Fairness-based Distributed Resource Allocation (FDRA) algorithm for 5G networks, then each the results in each area are discussed in critique point of view.
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Xie, Huirong, and Teck Chai Lau. "Evidence-Based Green Human Resource Management: A Systematic Literature Review." Sustainability 15, no. 14 (2023): 10941. http://dx.doi.org/10.3390/su151410941.
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To better understand the empirical development of green human resource management (GHRM) research and theories and to provide evidence-based suggestions, the article conducts a systematic review of evidence-based studies within the academic field of GHRM. The review follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Protocol 2020 to select GHRM-focused and highly qualified articles, published in the final stage by the end of December 2022 and written in English from the Scopus and Web of Science Core Collection databases. Independent assessments of studies were performed by two researchers in the selection and analysis process, and bibliometric and statistical analyses were applied to synthesize the results from 141 articles. The results reveal the increasing interest, diversification, and tendencies of GHRM research and highlight the disequilibrium of research context and methodology, the classification and evolution of research emphasis, the mechanism for theories, the constructs, the measurements, and the framework of the literature. Based on the results, evidence-based recommendations were provided for both practitioners and researchers regarding the context and trend, access and approach, and mechanism and innovation for GHRM development. This review possesses significance as providing the original findings of detailed empirical GHRM research context, the relationships between GHRM practices dimensions and measurements, and the interrelation of theory application and framework design. Despite the discoveries having the potential to offer scholars and practitioners GHRM suggestions with a reliable basis, the authors recognize the scope of the current review is limited and call for verification of current findings with a wider range of studies.
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Trivedi, Ayushi, Pragya Pandey, Nirjharnee Nandeha, Rishika Choudhary, Amit Kumar Pandey, and Ashutosh Singh. "A Systematic Review and Conceptual Framework for Natural Resource Performance Management." Journal of Scientific Research and Reports 30, no. 6 (2024): 816–25. http://dx.doi.org/10.9734/jsrr/2024/v30i62098.
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The topic of "Performance management of natural resources" has drawn more attention in the last few decades. Investigating how to manage natural resource performance more optimally is crucial for the long-term social and economic advancement of a nation. This study reviews the research progress of performance management of natural resources (including water resources) based on the pertinent literature of "Performance management of natural resources" and "performance management and evaluation of nature resources" in Web of Science. Through a review of the literature and inductive analysis, the authors found that the pursuit of sustainable resource consumption and management has emerged as the frontier direction of study. However, there is still room for development in the natural resource performance management evaluation system and methods, as well as the requirement for a comprehensive conceptual interpretation and analytical framework. As the literature on the factors impacting the success of natural resource management is currently lacking in depth, future research should concentrate on bolstering the usage of quantitative models. Enhancing the combination of research and quantitative models is also essential. This study builds research framework for natural resource performance management based on the body of current literature and the real-world experience of nations worldwide. In order to support decision-making for the sustainable use of natural resources, the authors describe the process and mechanism of performance management of natural resources and provide some workable evaluation methods based on a variety of evaluation objectives, subjects, and means.
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Wu, Hao, Xiaoyu Lu, and Hanyu Wang. "The Application of Artificial Intelligence in Health Care Resource Allocation Before and During the COVID-19 Pandemic: Scoping Review." JMIR AI 2 (January 30, 2023): e38397. http://dx.doi.org/10.2196/38397.
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Background Imbalanced health care resource distribution has been central to unequal health outcomes and political tension around the world. Artificial intelligence (AI) has emerged as a promising tool for facilitating resource distribution, especially during emergencies. However, no comprehensive review exists on the use and ethics of AI in health care resource distribution. Objective This study aims to conduct a scoping review of the application of AI in health care resource distribution, and explore the ethical and political issues in such situations. Methods A scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). A comprehensive search of relevant literature was conducted in MEDLINE (Ovid), PubMed, Web of Science, and Embase from inception to February 2022. The review included qualitative and quantitative studies investigating the application of AI in health care resource allocation. Results The review involved 22 articles, including 9 on model development and 13 on theoretical discussions, qualitative studies, or review studies. Of the 9 on model development and validation, 5 were conducted in emerging economies, 3 in developed countries, and 1 in a global context. In terms of content, 4 focused on resource distribution at the health system level and 5 focused on resource allocation at the hospital level. Of the 13 qualitative studies, 8 were discussions on the COVID-19 pandemic and the rest were on hospital resources, outbreaks, screening, human resources, and digitalization. Conclusions This scoping review synthesized evidence on AI in health resource distribution, focusing on the COVID-19 pandemic. The results suggest that the application of AI has the potential to improve efficacy in resource distribution, especially during emergencies. Efficient data sharing and collecting structures are needed to make reliable and evidence-based decisions. Health inequality, distributive justice, and transparency must be considered when deploying AI models in real-world situations.
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Kisser, Johannes, Maria Wirth, Gusseme Bart De, et al. "A review of nature-based solutions for resource recovery in cities." Blue-Green Systems 2, no. 1 (2020): 138–72. https://doi.org/10.2166/bgs.2020.930.
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Our modern cities are resource sinks designed on the current linear economic model which recovers very little of the original input. As the current model is not sustainable, a viable solution is to recover and reuse parts of the input. In this context, resource recovery using nature-based solutions (NBS) is gaining popularity worldwide. In this specific review, we focus on NBS as technologies that bring nature into cities and those that are derived from nature, using (micro)organisms as principal agents, provided they enable resource recovery. The findings presented in this work are based on an extensive literature review, as well as on original results of recent innovation projects across Europe. The case studies were collected by participants of the COST Action Circular City, which includes a portfolio of more than 92 projects. The present review article focuses on urban wastewater, industrial wastewater, municipal solid waste and gaseous effluents, the recoverable products (e.g., nutrients, nanoparticles, energy), as well as the implications of source separation and circularity by design. The analysis also includes assessment of the maturity of different technologies (technology readiness level) and the barriers that need to be overcome to accelerate the transition to resilient, self-sustainable cities of the future.
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Vasudevan, Hemaloshinee. "RESOURCE-BASED VIEW THEORY APPLICATION ON THE EDUCATIONAL SERVICE QUALITY." International Journal of Engineering Applied Sciences and Technology 6, no. 6 (2021): 174–86. http://dx.doi.org/10.33564/ijeast.2021.v06i06.026.
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Background and Objectives: The purpose of this study is to review the resource-based view theory on service quality that contribute to and expand internal resources and services of high quality. Several empirical studies have examined how to apply resource-based view theory to exploiting opportunities in higher education. With the help of this resource-based view theory, urban higher education can apply how to obtain and mobilize additional resources or use existing resources more efficiently and effectively to increase the productivity of existing resources to improve the quality of education services. Perhaps providing high-quality service based views are hampered by a lack of resources for urban education institutions and new ventures, and for them to survive, the resource constraints should address effectively. The issue in this paper is how the RBV theory or concept is to be studied in urban higher education so that researchers and organizations can benefit from this perspective. Methodology: The RBV framework was used to delimit the review so that the research method used in this paper is an empirical approach through a study of journals and supporting journals related to the topic under study. This paper evaluated and reviewed several empirical studies in terms of methodology and strategy that used to apply and implement the resourcebased view theory to improve the service based view quality of students' retention. Many articles indicated quantitative methods as the method strategy, but restrictions showed qualitative and mixed methods that should be concerned in future research. Findings: This article's literature search aimed at obtaining a usable sample of recently published papers to provide a sense of the conceptual gaps, knowledge gaps, methodological gaps and problem gaps in several resource-based (RBV) industries, but lesser are using in education. The dynamics and heterogeneity in this field of science encourage university researchers to develop and strengthen RBV theory. With this development, the concepts and theories of management are expected to be useful for academics. Recommendation & Limitation: On the critical reviews above, specific recommendations may in future serve as the key to enriching resource-based views. In this article, mixed and qualitative methods should be used to obtain accurate results. Additional attention should be paid to future research into higher education institutional resources, and integrate tangible and intangible resources into organizational capacity. Conclusion & Contribution: Resource-based view theory appears to have the capability to leverage resources and create more opportunities with fewer funds when applied to urban systems. One of the biggest contributions of this article is the direct strategy of scholars towards empirical studies and finding of resources as an essential antecedent to service quality and end to educational performance.
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Gibson, Cristina B., Stephen C. Gibson, and Quinn Webster. "Expanding Our Resources: Including Community in the Resource-Based View of the Firm." Journal of Management 47, no. 7 (2021): 1878–98. http://dx.doi.org/10.1177/0149206320987289.
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We apply insights from organizational behavior, psychology, and sociology to make the case that the community in which a firm is embedded is a valuable, rare, inimitable, and nonsubstitutable resource that holds potential as a source of sustained competitive advantage. First, we review several key principles of the resource-based view (RBV) and show how they apply to community as a strategic resource, incorporating prior work that simultaneously addresses communities and RBV. Next, we juxtapose pairs of firms in the same industries, comparing those that have embraced this strategy with those that have not, demonstrating the superior sustainability of the firms that consider community as a strategic resource. Finally, we conclude with thoughts as to a future research agenda that allows for an expansion of the concept of resources to further the development of RBV, the firms that apply it, and the communities in which they are embedded. In doing so, we demonstrate how expanding RBV to incorporate the community as strategic resource contributes to managerial theory, research, and practice.
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S, Sahoo. "Molecular Marker Based Genetic Diversity Study of Curcuma Caesia Roxb. – A Mini Review." Open Access Journal of Microbiology & Biotechnology 8, no. 2 (2023): 1–4. http://dx.doi.org/10.23880/oajmb-16000266.
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The availability of genetic resource provides an opportunity for plant breeders to develop new cultivars with desirable characteristics and these characteristics encompass various traits preferred by farmers (high yield potential, larger seed size, etc) as well as traits favored by breeders (pests and disease resistance). Genetic resources are also essential for conservation, as they provide a basis for identifying threatened species and developing conservation strategies. Curcuma caesia Roxb. (Zingiberaceae) is an underutilized perennial herb with bluish-black tuberous rhizome having the characteristic of aromatic and medicinal properties. There is an ample genetic diversity of Curcuma plants with medicinal importance around the world. Authentication and ensuring the genuineness of Curcuma are crucial aspects for marker-based analysis. Therefore, genetic variation serves as the base for the identification and characterisation of the plants. Molecular marker technology is widely used in genetic diversity analysis, germplasm resource identification, and molecular marker-assisted breeding technique. Multiple molecular markers have been used for characterization and identification of species for its sustainable utilization and conservation. The molecular investigation, which involves techniques like RAPD, SCAR, ISSR, and AFLP for fingerprinting, plays a crucial role in establishing molecular markers to assess the authenticity and diversity of plant species. Various marker analyses have demonstrated a significant degree of genetic variation among the species and these patterns tend to differ due to environmental influences and genetic factors. This review facilitates a complete information about the molecularassisted genetic diversity study of Curcuma caesia Roxb. (Black turmeric) which may be used as a database while exploring the diversity analysis.
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Diaz-Elsayed, Nancy, Nader Rezaei, Tianjiao Guo, Shima Mohebbi, and Qiong Zhang. "Wastewater-based resource recovery technologies across scale: A review." Resources, Conservation and Recycling 145 (June 2019): 94–112. http://dx.doi.org/10.1016/j.resconrec.2018.12.035.
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Cherry, D. A. "Book Review: An Evidence-Based Resource for Pain Relief." Anaesthesia and Intensive Care 27, no. 6 (1999): 673. http://dx.doi.org/10.1177/0310057x9902700624.
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Moloney, J. "Book Review: Evidence Based Resource in Anaesthesia and Analgesia." Anaesthesia and Intensive Care 29, no. 5 (2001): 562–63. http://dx.doi.org/10.1177/0310057x0102900529.
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Aulia, R., A. N. Putri, M. F. Raihan, M. Ayub, and J. Sulistio. "The Literature Review of Cloud-based Enterprise Resource Planning." IOP Conference Series: Materials Science and Engineering 598 (September 6, 2019): 012036. http://dx.doi.org/10.1088/1757-899x/598/1/012036.
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Liu, Ze, Jingzhao Zhou, Xiaoyang Yang, Zechuan Zhao, and Yang Lv. "Research on Water Resource Modeling Based on Machine Learning Technologies." Water 16, no. 3 (2024): 472. http://dx.doi.org/10.3390/w16030472.
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Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific basis for water resource management, protection, and planning. Traditional hydrological observation methods, often reliant on experience and statistical methods, are time-consuming and labor-intensive, frequently resulting in predictions of limited accuracy. However, machine learning technologies enhance the efficiency and sustainability of water resource modeling by analyzing extensive hydrogeological data, thereby improving predictions and optimizing water resource utilization and allocation. This review investigates the application of machine learning for predicting various aspects, including precipitation, flood, runoff, soil moisture, evapotranspiration, groundwater level, and water quality. It provides a detailed summary of various algorithms, examines their technical strengths and weaknesses, and discusses their potential applications in water resource modeling. Finally, this paper anticipates future development trends in the application of machine learning to water resource modeling.
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Cooke, Samuel, David Nelson, Heidi Green, Kathie McPeake, Mark Gussy, and Ros Kane. "Rapid systematic review on developing web-based interventions to support people affected by cancer." BMJ Open 12, no. 9 (2022): e062026. http://dx.doi.org/10.1136/bmjopen-2022-062026.
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ObjectiveTo systematically identify and explore the existing evidence to inform the development of web-based interventions to support people affected by cancer (PABC).DesignA rapid review design was employed in accordance with the guidance produced by the Cochrane Rapid Reviews Methods Group and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. A rapid review was chosen due to the need for a timely evidence synthesis to underpin the subsequent development of a digital resource (Shared Lives: Cancer) as part of an ongoing funded project.Methods and outcomesKeyword searches were performed in MEDLINE to identify peer-reviewed literature that reported primary data on the development of web-based interventions designed to support PABC. The review included peer-reviewed studies published in English with no limits set on publication date or geography. Key outcomes included any primary data that reported on the design, usability, feasibility, acceptability, functionality and user experience of web-based resource development.ResultsTen studies were identified that met the pre-specified eligibility criteria. All studies employed an iterative, co-design approach underpinned by either quantitative, qualitative or mixed methods. The findings were grouped into the following overarching themes: (1) exploring current evidence, guidelines and theory, (2) identifying user needs and preferences and (3) evaluating the usability, feasibility and acceptability of resources. Resources should be informed by the experiences of a wide range of end-users taking into consideration current guidelines and theory early in the design process. Resource design and content should be developed around the user’s needs and preferences and evaluated through usability, feasibility or acceptability testing using quantitative, qualitative or mixed methods.ConclusionThe findings of this rapid review provide novel methodological insights into the approaches used to design web-based interventions to support PABC. Our findings have the potential to inform and guide researchers when considering the development of future digital health resources.Trial registration numberThe review protocol was registered on the Open Science Framework (https://osf.io/ucvsz).
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Chukwuma, Isaac Onyeyirichukwu, Patrick Chukwunwike Chukwuma, and Ifeanyi Leo Madu. "Organisational Learning: A Resource-Based View Analysis." International Journal of Scientific Research and Management (IJSRM) 12, no. 04 (2024): 6079–87. http://dx.doi.org/10.18535/ijsrm/v12i04.em03.
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This study theoretically analyzed the relationship between organisational learning (OL) and resource-based view (RBV) in line with examining the concept of OL, concept of RBV, nexus between OL and RBV, response between OL and RBV, calibrating the challenges in synergizing OL and RBV and exploring the competitive advantage in optimizing OL to feature non-substitutable, rare, inimitable, and valuable (NRIV) attributes of RBV. The methodology engaged was the narrative literature review which is validated by its potency to align numerous authors’ perspectives for correlation and explanation. The paper is of the position that OL and its components when optimally refined and optimized are capable of attaining NRIV status and can position an organization at the leading cadre in its industry. The review explored and uncovers relevant literature, and made postulations in comprehending and validating the dynamic relationship in the interplay between OL and RBV.
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Arvind, Kumar Singh. "Provision and use of e-resource licensing: A study based on model license agreement (MLA)." i-manager's Journal on Information Technology 11, no. 4 (2022): 9. http://dx.doi.org/10.26634/jit.11.4.19180.
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Electronic resource information licensing challenges libraries as they acquire new resources in academic institutions. There are some crucial key components of a licensing agreement, such as access concerns, use of an electronic information resource, vendor support and technical considerations, cancellation and termination, legal issues, and the review and renewal process. Developing licensing guidelines makes licensing work more accessible by providing more consistency in the approach to license review and by making the practice and policy of the institution on the basis of the licensing review.
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Sungkar, Armu, and Tena Kogoya. "A REVIEW OF GRID COMPUTING." Computer Science & IT Research Journal 1, no. 1 (2020): 1–6. http://dx.doi.org/10.51594/csitrj.v1i1.128.
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Grid computing is a combination of interconnected resources which can be spread all over the world having higher computing capabilities. The benefit of grid computing includes higher computation and memory capacity because of grid resources spread all over the world. The grid computing is managed by intra-grid scope which refers to the methodologies and the algorithms used for managing the grid network related issues such as task scheduling, resource balancing and security of the network. The advantages of grid computing include access to inaccessible resources, resource utilization and balancing, reliability, and parallel computing and scalability. The limitations of the grid computing include application in limited fields and suitability with applications running in batch mode only based on parallel processing
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Clinebell, Howard. "Book Review and Resource: The Resources of Pastoral Theology and Psychology for Justice-Based Peacemaking." Journal of Pastoral Care 44, no. 4 (1990): 412–13. http://dx.doi.org/10.1177/002234099004400417.
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Child, Brian. "Book Review: Rights, Resources and Rural Development: Community-Based Natural Resource Management in Southern Africa." Journal of Environment & Development 15, no. 4 (2006): 448–50. http://dx.doi.org/10.1177/1070496506295023.
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Sahoo, Kamalakanta, Richard Bergman, Sevda Alanya-Rosenbaum, Hongmei Gu, and Shaobo Liang. "Life Cycle Assessment of Forest-Based Products: A Review." Sustainability 11, no. 17 (2019): 4722. http://dx.doi.org/10.3390/su11174722.
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Climate change, environmental degradation, and limited resources are motivations for sustainable forest management. Forests, the most abundant renewable resource on earth, used to make a wide variety of forest-based products for human consumption. To provide a scientific measure of a product’s sustainability and environmental performance, the life cycle assessment (LCA) method is used. This article provides a comprehensive review of environmental performances of forest-based products including traditional building products, emerging (mass-timber) building products and nanomaterials using attributional LCA. Across the supply chain, the product manufacturing life-cycle stage tends to have the largest environmental impacts. However, forest management activities and logistics tend to have the greatest economic impact. In addition, environmental trade-offs exist when regulating emissions as indicated by the latest traditional wood building product LCAs. Interpretation of these LCA results can guide new product development using biomaterials, future (mass) building systems and policy-making on mitigating climate change. Key challenges include handling of uncertainties in the supply chain and complex interactions of environment, material conversion, resource use for product production and quantifying the emissions released.
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Holland, Daniel S. "Collective Rights–Based Fishery Management: A Path to Ecosystem-Based Fishery Management." Annual Review of Resource Economics 10, no. 1 (2018): 469–85. http://dx.doi.org/10.1146/annurev-resource-100517-023110.
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Fishery rents may be dissipated across margins not well defined or controlled by an individual transferable quota system. Collective rights–based fishery management (CRBFM), where catch rights are held by a group, can sometimes generate greater benefits and can also address external impacts of the fishery. I discuss potential failures of individual quotas and how these problems were addressed by CRBFM institutions. I then focus on the role of CRBFM in addressing environmental and social impacts external to the group of fishers, such as bycatch, habitat impacts, and spatial conflicts. The review suggests that CRBFM can effectively address both intrafishery and external impacts, provided there is sufficient incentive to do so, including maintaining access to preferred markets or the threat of further regulation. However, CRBFM can create moral hazard and adverse selection problems, and successful CRBFM institutions generally have homogeneous membership with well-aligned interests and/or formal contracts with monitoring and enforcement provisions.
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J, Anurag. "Review of AI-driven Cloud Optimization." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34000.
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Cloud automation is the key to realization a fully-optimized performance of modern cloud platforms while cloud resources utilization. Resource allocation efficiency is valuable. We are however faced with increasing pressure for computational resources. The Long Short-Term Memory (LSTM) algorithms have found a great use case in the dynamic resource allocation problem when the problem is solved by the proactive provisioning of resources based on historical usage patterns taking advantage of recurrent neural networks. Furthermore, the concern over quality-of-service delivery (QoS) and energy efficiency is now almost as challenging for cloud providers when implementing the utilization of cloud resources, especially in a dynamic setting. Deep Reinforcement Learning (DRL) allows to pursue that end by developing agents, which might guide the work of optimizing resource allocation and reducing energy expenses at the same time. It improves the result and adaptability of the applications running on clouds. Artificial intelligence, in its diverse form, for the instance machine learning and optimization algorithms, brings in a great influence in the areas of cloud operations, resource management, and security. Furthermore, the 3rd generation of FPGAs (Reconfigurable Digital Computing-In-Memory or ReDCIM processors) and the bitwise parallelism via-memory core multipliers also improve the efficiency of computing in cloud environments. Adopting these inputting methodologies is a consequence of cloud systems achieving top performance, high scalability, and low costing. Keywords - Cloud Automation, Long Short-Term Memory (LSTM) algorithms, Deep Reinforcement Learning (DRL), Reconfigurable Digital Computing-In-Memory (ReDCIM) processors, Resource sAllocation, Energy Efficiency.
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Qin, Hua, Martha Bass, Jessica D. Ulrich-Schad, David Matarrita-Cascante, Christine Sanders, and Barituka Bekee. "Community, Natural Resources, and Sustainability: Overview of an Interdisciplinary and International Literature." Sustainability 12, no. 3 (2020): 1061. http://dx.doi.org/10.3390/su12031061.
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The Special Issue Community, Natural Resources, and Sustainability seeks to engage in an interdisciplinary and international dialogue on the interrelationships of society, natural resources, and sustainability at the community level. In addition to introducing the twelve research articles published in this collection, we provide an overview of the existing literature on community and natural resource management, mainly through a review of previous reviews and a bibliometric analysis. While this literature is dominated by studies on various aspects of community-based natural resource management, the present Special Issue showcases multiple thematic areas of research that collectively contribute to a more complete understanding of the community-resources-sustainability linkages. Our review also pinpoints important gaps in existing meta-analyses and bibliometric analyses. Promising directions for future research are highlighted.
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Gélinas, Daniel, Arman Sadreddin, and Rustam Vahidov. "Artificial Intelligence in Human Resources Management: A Review and Research Agenda." Pacific Asia Journal of the Association for Information Systems 14 (January 2022): 1–42. http://dx.doi.org/10.17705/1pais.14601.
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Background: Researchers and practitioners both exhibit a growing interest in the application of Artificial Intelligence in Human Resources Management. However, research shows that there remains a substantial gap between the promise of AI and its practical application in organizations. Previous research has identified some of the challenges facing the application of Artificial Intelligence in Human Resources Management. Among these challenges is the varied nature of Human Resources functions. To address this, we adopt the Human Resource Life Cycle, which is composed of 6 dimensions that closely mirror the Human Resource functions that exist in many organizations: 1) Strategic Planning, 2) Recruitment and Deployment, 3) Training and Development, 4) Performance Management, 5) Compensation Management, and 6) Human Relations Management. Method: Through a scoping literature review, we have identified 85 articles on the topic and classified them based on the 6 dimensions of the Human Resource Life Cycle. Results: Our scoping review found that Artificial Intelligence has already been studied in relation to all 6 dimensions of the Human Resource Life Cycle. In addition, a seventh dimension was identified and integrated into the existing Human Resource Life Cycle framework: Legal and Ethical Issues. Based on the scoping review, a research agenda is presented to provide guidance for future research in the field of Artificial Intelligence in Human Resources Management. Conclusion: All 6 dimensions of the Human Resource Life Cycle, along with the seventh dimension – Legal and Ethical Issues – are already present in the literature. Future research could focus on the impact of AI on connections between dimensions, as well as the impact on HR-specific outcomes. Practitioners must recognize the limitations related to the application of AI in Human Resources Management, even though AI should still be viewed as a solution to many challenges facing Human Resources Management in organizations.
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Hafiz, Nusrat, Ahmad Shaharudin Abdul Latiff, Md Asadul Islam, Abu Naser Mohammad Saif, and Sazali Abd Wahab. "Towards the Underlying Theories of Small Firm Growth: A Literature Review." FIIB Business Review 11, no. 1 (2021): 36–51. http://dx.doi.org/10.1177/23197145211049627.
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As a pre-condition for the economic growth of a country, the concept of firm growth has emerged as a critical strategic issue for small businesses from the strategic management perspective. While some literature reviews have been conducted on small firm growth, a comprehensive review of theories emphasizing the association of intangible resources with the growth of small firms has not been conducted. This study aims to provide a literature review of extant theoretical perspectives of small businesses literature. For the review, materials are collected and extracted from various online databases, and results are analysed using classifier variables. Five theories of firm growth, namely, the resource-based theory, knowledge-based theory, dynamic capabilities theory, upper echelon theory and resource-dependency theory, are selected to review, associating the present research aim. The theories are compared using key attributes and outcomes. A clear direction towards an optimum theory to underpin the small firms’ growth has been provided from a resource-management perspective. By validating various theoretical perspectives to explain small business growth, the present study provides first-hand insights for managers to formulate strategies and creates a cornerstone for future empirical studies.
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Janssen, Luca, Aggie Paulus, William Hollingworth, Joanna Thorn, and Silvia Evers. "OP122 Resource Use Measurement Issues: A Scoping Review." International Journal of Technology Assessment in Health Care 35, S1 (2019): 27–28. http://dx.doi.org/10.1017/s0266462319001557.
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IntroductionResource use measurement is known to be a challenging and time-consuming, but essential step in economic evaluations of health care interventions. Measuring true quantities of resources utilized is of major importance for generating valid costing estimates. As consequence of the absence of a gold standard and of acknowledged guidelines, the choice of a measurement method is often based on practicality instead of methodological evidence. An overview of resource use measurement issues is currently lacking. Such overview could enhance clearance in the quality of resource use measurement methods in economic evaluations and may facilitate to opt for evidence based measurement methods in the future. This study aims to provide an overview of methodological evidence regarding resource use measurement issues in economic evaluations.MethodsLiterature was searched by three different methods. First, a search strategy was used in six different databases. Second, the Database of Instruments for Resource Use Measurement (DIRUM) was hand-searched. Third, experts from six different European Union countries within the field of health economics were asked to provide relevant studies. Data was analyzed according to the Resource Use Measurement Issues (RUMI-) framework, which was developed for this study.ResultsOf the 3,478 articles provided in the initial search, 77 were fully analyzed. An overview with evidence is provided for every resource use measurement issue. Most research focused around the issue ‘how to measure’, in particular the effect of self-reported data versus administrative data. In contrast, little to no research has been done on issues ‘what to measure’ and ‘for which purpose to measure’.ConclusionsResults of this study provide insight in the effect of a chosen measurement method. The results stress the importance of measuring the true quantities of resources utilized for generating valid costing estimates. Furthermore, this article highlights the lack of evidence in appropriate resource use measurement methods.
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Yang, Mei. "A Review of Regional Innovation System Studies in Resource-Based City." Advanced Materials Research 524-527 (May 2012): 2751–56. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.2751.
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Scholars pay close attention to regional innovation system research in resource-based cities. The thesis analysis linked research results which are resource-based cities transform and regional innovation system from two aspects, resource-based cities transform and sustainable development, and presents major research trend and shortage in this field.
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Vinay, Khatod. "A Priority based Resource Provisioning by Dynamically Balancing Load using VM Dynamic Threshold and Novel Method: Review." Recent Trends in Cloud Computing and Web Engineering 2, no. 2 (2020): 1–8. https://doi.org/10.5281/zenodo.3961214.
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<em>In recent years, the demand from organizations as well as individuals for Cloud (Virtual) Resources reached a peak due to their advantages such as resources available at cheaper rates, maintenance free infrastructure, applications with latest updates, anytime and anywhere availability of resources, etc. As with every technology there are cons of using Cloud Resources including increased energy consumption, infrastructure location is not transparent, security for the data stored on cloud. In this paper, method to efficiently allocate resources to consumer based on Priority has been proposed by combining load balancing approach to reduce energy consumption. Not only resource will be allocated by altering the load between Physical Machines (PMs), but also a Priority based resource provisioning criteria will be implemented. The evaluation criteria will be user satisfaction, service quality, number of migrations, least Service Level Agreement (SLA) violation and energy saving.</em>
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Benevene, Paula, and Ilaria Buonomo. "Green Human Resource Management: An Evidence-Based Systematic Literature Review." Sustainability 12, no. 15 (2020): 5974. http://dx.doi.org/10.3390/su12155974.
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The United Nations’ report “Our Common Future” contributed to underline the crucial role of human resource management in strategically greening the organization and, in turn, economics and society at large. This awareness gave birth to green human resource management (GHRM). Despite the high number of papers addressing GHRM, this topic lacks a proper theoretical, methodological, and empirical systematization. A possible step towards a better understanding of GHRM is an evidence-based analysis of its practices’ outcomes. Developing these reflections and considerations, we conducted a systematic literature review on the evidence-based literature about the antecedents and outcomes of GHRM practices, following the PRISMA guidelines. We selected 48 papers. Most selected studies (n = 25) did not tackle single GHRM activities and processes. Studies considering specific GHRM areas tackled some dimensions more frequently (e.g., “training and development”, “performance management and appraisal”), while underrepresenting others (e.g., “Job analysis and description”). At the same time, selected studies focused on GHRM consequences for organizations, showing a high adherence to the ability, motivation, opportunity (AMO) theoretical framework. Suggestions for future research are provided.
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Malik, Antim. "A Review of Resource Scheduling in Fog based Cloud Environment." International Journal for Research in Applied Science and Engineering Technology 7, no. 6 (2019): 1073–77. http://dx.doi.org/10.22214/ijraset.2019.6185.
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Gunawan, Joko, Yupin Aungsuroch, and Mary L. Fisher. "Competence-based human resource management in nursing: A literature review." Nursing Forum 54, no. 1 (2018): 91–101. http://dx.doi.org/10.1111/nuf.12302.
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Pham, Do Dieu Thu, Pascal Paillé, and Norrin Halilem. "Systematic review on environmental innovativeness: A knowledge-based resource view." Journal of Cleaner Production 211 (February 2019): 1088–99. http://dx.doi.org/10.1016/j.jclepro.2018.11.221.
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Manzoor, Muhammad Faraz, Adnan Abid, Muhammad Shoaib Farooq, Naeem A. Azam, and Uzma Farooq. "Resource Allocation Techniques in Cloud Computing: A Review and Future Directions." Elektronika ir Elektrotechnika 26, no. 6 (2020): 40–51. http://dx.doi.org/10.5755/j01.eie.26.6.25865.
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Cloud computing has become a very important computing model to process data and execute computationally concentrated applications in pay-per-use method. Resource allocation is a process in which the resources are allocated to consumers by cloud providers based on their flexible requirements. As the data is expanding every day, allocating resources efficiently according to the consumer demand has also become very important, keeping Service Level Agreement (SLA) between service providers and consumers in prospect. This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. In the light of the uniqueness of the models and techniques, the main aim of the resource allocation is to limit the overhead/expenses associated with it. This research aims to present a comprehensive, structured literature review on different aspects of resource allocation in cloud computing, including strategic, target resources, optimization, scheduling and power. More than 50 articles, between year 2007 and 2019, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and they are reviewed under clearly defined objectives. It presents a topical taxonomy of resource allocation dimensions, and articles under each category are discussed and analysed. Lastly, salient future directions in this area are discussed.
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Sasmita, Kumari Nayak. "Nature inspired algorithms in dynamic task scheduling: A review." World Journal of Advanced Research and Reviews 20, no. 3 (2023): 829–33. https://doi.org/10.5281/zenodo.12748311.
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The process of scheduling involves allocating shared resources gradually so that tasks can be completed effectively within the allotted time. In task scheduling and resource allocation, the terms are used independently for tasks and resources, respectively. In computer science and operational management, scheduling is a hot topic. Efficient schedules guarantee system effectiveness, facilitate sound decision-making, reduce resource waste and expenses, and augment total productivity. Selecting the most accurate resources to complete work items and schedules for computing and business process execution is typically a laborious task. Particularly in dynamic real-world systems, where scheduling different dynamic tasks involves multiple tasks, is a difficult problem. Emerging technology known as "nature inspired algorithms" has the ability to dynamically solve the problem of optimal task and resource scheduling. This review paper discusses a study that looked at algorithms inspired by nature and used them to schedule tasks dynamically. The Nature Inspired Algorithms used in dynamic task scheduling and a comparative analysis of those methods are used in this paper to address the study's findings.
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D’Oria, Laura, T. Russell Crook, David J. Ketchen, David G. Sirmon, and Mike Wright. "The Evolution of Resource-Based Inquiry: A Review and Meta-Analytic Integration of the Strategic Resources–Actions–Performance Pathway." Journal of Management 47, no. 6 (2021): 1383–429. http://dx.doi.org/10.1177/0149206321994182.
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Understanding why some firms outperform others is central to strategy research. The resource-based view (RBV) suggests that competitive advantages arise due to possessing strategic resources (i.e., assets that are valuable, rare, nonsubstitutable, and inimitable), and researchers have extended this logic to explain performance differences. However, RBV is relatively silent about the actions managers could use to create or capitalize on a resource-based advantage. Enriching RBV, the resource orchestration framework describes specific managerial actions that use such resources to realize performance gains. After reviewing the conceptual evolution of these two literature streams as well as related streams, we use meta-analytic structural equation modeling to aggregate evidence from 255 samples involving 111,614 observations to answer outstanding research questions regarding the strategic resources–actions–performance pathway. The results show strong complementarity and interdependence between their logics. Additional inquiry drawing on their complementarity is a clear path toward enhancing scholars’ understanding of how and why some firms outperform others. We build on our findings to lay a foundation for such inquiry, including a call for theorizing centered on the interdependence of resources and actions, as well as new theoretical terrain that can help resource-based inquiry continue to evolve.
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Ying, Liu. "Insurance and medical resource allocation: a literature review." Advances in Social Sciences Research Journal 7, no. 1 (2020): 1–9. http://dx.doi.org/10.14738/assrj.71.7493.
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The contribution of the existing research results of insurance and resource allocation in theory and policy proposition has important reference value for the study of the operation mechanism and policy orientation of insurance resource allocation. On the basis of combing the research path of the existing research results, this paper combines the insurance theory with the general economic theory, based on China's national conditions, tries to think and choose new research path with new thinking mode, and systematically and deeply discusses the effective allocation of China's insurance resources.
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Khan, Fahim Ullah, Ibrar Ali Shah, Sadaqat Jan, Shabir Ahmad, and Taegkeun Whangbo. "Machine Learning-Based Resource Management in Fog Computing: A Systematic Literature Review." Sensors 25, no. 3 (2025): 687. https://doi.org/10.3390/s25030687.
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This systematic literature review analyzes machine learning (ML)-based techniques for resource management in fog computing. Utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, this paper focuses on ML and deep learning (DL) solutions. Resource management in the fog computing domain was thoroughly analyzed by identifying the key factors and constraints. A total of 68 research papers of extended versions were finally selected and included in this study. The findings highlight a strong preference for DL in addressing resource management challenges within a fog computing paradigm, i.e., 66% of the reviewed articles leveraged DL techniques, while 34% utilized ML. Key factors such as latency, energy consumption, task scheduling, and QoS are interconnected and critical for resource management optimization. The analysis reveals that latency, energy consumption, and QoS are the prime factors addressed in the literature on ML-based fog computing resource management. Latency is the most frequently addressed parameter, investigated in 77% of the articles, followed by energy consumption and task scheduling at 44% and 33%, respectively. Furthermore, according to our evaluation, an extensive range of challenges, i.e., computational resource and latency, scalability and management, data availability and quality, and model complexity and interpretability, are addressed by employing 73, 53, 45, and 46 ML/DL techniques, respectively.
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Ahmed, Kosrat Dlshad, and Subhi R. M. Zeebaree. "Resource Allocation in Fog Computing: A Review." International Journal of Science and Business 5, no. 2 (2021): 54–63. https://doi.org/10.5281/zenodo.4461876.
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Coupled with resource retrained system and devices, Internet of things network requires effective utilization of Fog Computing system. With increasing demand and requirements for enhancing the performance, fog computing scenario requires increased output, less latency, greater performance etc. This review takes the concept of fog computing one step further by reviewing available literature on the components of fog computing to determine the effective outcomes for different settings and management of the network consideration. Contributing to the development appropriate settings and management of the cloud based support, necessary analysis has been carried out in this review. Systematic analysis on the development of fog computing such as system model has been analyzed. To review the prospects and development of fog computing, necessary relationships have been established such as fog computing, fog – cloud computing and fog – fog computing. Based on the learning of the research, future direction for the research has been suggested as well.
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Rizka, Fauzia Amalia Ananda, and Sowiyah. "Human Resource Management: A Literature Review." International Journal of Current Science Research and Review 05, no. 06 (2022): 1881–86. https://doi.org/10.5281/zenodo.6616969.
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<strong>ABSTRACT: </strong>This article aims to find how human resource management based on literature review from previous research from several countries around the world. This article uses search and review methods, where the review process began with a search engine, Google scholar, to search articles with keywords. The authors found the scope of the reviewed articles was still limited so it needs to be followed up related to human resource management. Result of the review show that human resource can run optimally if they apply good management. The research about this topic is limited and this article is a literature review, so further research needs to be done related to human resource management and to include other data collection methods including interview and questionnaire. The theoretical benefit of this article is to add knowledge about human resource management and the practical benefit is as an information for further research.
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Lockett, Andy, and Steve Thompson. "The resource-based view and economics." Journal of Management 27, no. 6 (2001): 723–54. http://dx.doi.org/10.1177/014920630102700608.
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This paper analyzes the link between economics and the resource-based view (RBV) of the firm. Although, historically there has been a strong link between the disciplines of strategy and economics, explicit citations of key RBV works has been disappointingly low in mainstream economics journals. However, there are substantial bodies of works that build implicitly on the ideas of the RBV, in particular the consequences of path dependency on firm behavior, to explain a number of different economic issues. The issues we review in the paper are all influenced by path dependency and include: (1) diversification and market entry, (2) corporate refocusing, and market exit, (3) explaining innovative activity among firms, (4) diversification and performance and (5) industry evolution with rapidly changing products. Furthermore, we identify a number of reasons that may have limited the explicit use of the RBV in economics, which include the problems of causal ambiguity, tautology and firm heterogeneity. Finally, potential areas for future research are identified, which include the interaction of the RBV and Agency Theory, the RBV as a dynamic theory, using the RBV to explain radical change and the application of the RBV to issues of antitrust.