35 resultados para Human Resource Management Practices


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The work motivation construct is central to the theory and practice of many social science disciplines. Yet, due to the novelty of validated measures appropriate for a deep cross-national comparison, studies that contrast different administrative regimes remain scarce. This study represents an initial empirical effort to validate the Public Service Motivation (PSM) instrument proposed by Kim and colleagues (2013) in a previously unstudied context. The two former communist countries analyzed in this dissertation—Belarus and Poland— followed diametrically opposite development strategies: a fully decentralized administrative regime in Poland and a highly centralized regime in Belarus. The employees (n = 677) of public and nonprofit organizations in the border regions of Podlaskie Wojewodstwo (Poland) and Hrodna Voblasc (Belarus) are the subjects of study. Confirmatory factor analysis revealed three dimensions of public service motivation in the two regions: compassion, self-sacrifice, and attraction to public service. The statistical models tested in this dissertation suggest that nonprofit sector employees exhibit higher levels of PSM than their public sector counterparts. Nonprofit sector employees also reveal a similar set of values and work attitudes across the countries. Thus, the study concludes that in terms of PSM, employees of nonprofit organizations constitute a homogenous group that exists atop the administrative regimes. However, the findings propose significant differences between public sector agencies across the two countries. Contrary to expectations, data suggest that organization centralization in Poland is equal to—or for some items even higher than—that of Belarus. We can conclude that the absence of administrative decentralization of service provision in a country does not necessarily undermine decentralized practices within organizations. Further analysis reveals strong correlations between organization centralization and PSM for the Polish sample. Meanwhile, in Belarus, correlations between organization centralization items and PSM are weak and mostly insignificant. The analysis indicates other factors beyond organization centralization that significantly impact PSM in both sectors. PSM of the employees in the studied region is highly correlated with their participation in religious practices, political parties, or labor unions as well as location of their organization in a capital and type of social service provided.

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This phenomenological study explored how HR professionals who identified themselves as facilitators of strategic HRD (SHRD) perceived the experience of being an organizational agent-downsizing survivor. Criterion and snowball sampling were used to recruit 15 participants for this study. A semi-structured interview guide was used to interview participants. Creswell’s (2007) simplified version of Moustakas’s (1994) Modification of the Stevick-Colaizzi-Keen Method of Analysis of Phenomenological Data was used to analyze the data. Four main themes and corresponding sub-themes emerged from an inductive data analysis. The four main themes were a) the emotionality of downsizing, b) feeling responsible, c) choice and control, and d) possibilities for growth. Participants perceived downsizing as an emotional organizational change event that required them to manage their own emotions while helping others do the same. They performed their roles within an organizational atmosphere that was perceived as chaotic and filled with apprehension, shock, and a sense of ongoing loss, sadness and grieving. They sometimes experienced guilt and doubt and felt deceptive for having to keep secrets from others when planning for downsizing. Participants felt a strong sense of responsibility to protect employees emotionally, balance employee and organizational interests, and try to ensure the best outcomes for both. Often being there for others meant that they put on their games faces and took care of themselves last. Participants spoke of the importance of choosing one’s attitude, being proactive rather than reactive, and finding ways to regain control in the midst of organizational crisis. They also perceived that although downsizing was emotionally difficult to go through that it provided possibilities for self, employee, and organizational growth.

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Florida is the second leading horticulture state in the United States with a total annual industry sale of over $12 Billion. Due to its competitive nature, agricultural plant production represents an extremely intensive practice with large amounts of water and fertilizer usage. Agrochemical and water management are vital for efficient functioning of any agricultural enterprise, and the subsequent nutrient loading from such agricultural practices has been a concern for environmentalists. A thorough understanding of the agrochemical and the soil amendments used in these agricultural systems is of special interest as contamination of soils can cause surface and groundwater pollution leading to ecosystem toxicity. The presence of fragile ecosystems such as the Everglades, Biscayne Bay and Big Cypress near enterprises that use such agricultural systems makes the whole issue even more imminent. Although significant research has been conducted with soils and soil mix, there is no acceptable method for determining the hydraulic properties of mixtures that have been subjected to organic and inorganic soil amendments. Hydro-physical characterization of such mixtures can facilitate the understanding of water retention and permeation characteristics of the commonly used mix which can further allow modeling of soil water interactions. The objective of this study was to characterize some of the locally and commercially available plant growth mixtures for their hydro-physical properties and develop mathematical models to correlate these acquired basic properties to the hydraulic conductivity of the mixture. The objective was also to model the response patterns of soil amendments present in those mixtures to different water and fertilizer use scenarios using the characterized hydro-physical properties with the help of Everglades-Agro-Hydrology Model. The presence of organic amendments helps the mixtures retain more water while the inorganic amendments tend to adsorb more nutrients due to their high surface area. The results of these types of characterization can provide a scientific basis for understanding the non-point source water pollution from horticulture production systems and assist in the development of the best management practices for the operation of environmentally sustainable agricultural enterprise

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

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With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.