40 resultados para human resource management(HRM)

em Instituto Politécnico do Porto, Portugal


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This investigation reviews literature on human resource management practices that influence the retention of repatriates. The processes of selection and training/preparation before the departure, the role of the mentor and of communication during the international assignment, a program of readjustment to repatriation and a career development plan after return to the home firm are the practices identified in the literature as the main promoters of repatriates’ retention. Evidence suggests that greater responsibility on the part of the firms before, during and after the international assignment allows for more efficiency in the management of their repatriates.

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Framed on a wider project on Individual Human Resource Management and Development (HRMD), this project aims to explore Individual Career Management and Development (CMD) as an emergent professional field of HRMD.

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Given the increasingly demanding labor market, today’s professional should act according to certain generic competencies, which allows him to perform as required by the contemporary world. In parallel, human resource management (HRM) current trends, highlight the importance that managing by competencies has in the organizational context, in the sense that it impels a more strategic and integrated HRM. The evidence of the theoretical and practical pertinence of this theme resulted in an exploratory study of a qualitative nature, which findings lead us to conclude that the most valued generic competencies by firms are flexibility, interpersonal relationship, adjustment to change and teamwork. Another finding is that HRM managing by competencies practices is characterized by informality. Managing by competencies is more frequent presence in processes as: recruitment, retention and in the employees’ development plans.

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The purpose of this study is to investigate the association between the satisfaction with HRM practices in an organization and the workers' perceived performance. We are interested in learning if indeed workers that are more satisfied with the organization’s practices will also perceive themselves as more hardworking than others, thus confirming the happy-productive worker hypothesis, from an individual perception standpoint. Data originates from a large Portuguese hospital, with a sample of 952 clinical and nonclinical hospital workers. Data was originally explored using SPSS software and later tested in AMOS software where a multiple regression model was constructed and tested. Results indicate that overall satisfaction with HRM practices are related with the workers’ perceived performance; most of the HRM satisfaction subscales also relate, except for pay and performance appraisal, that do not seem to be good predictors of the workers perceived performance. The present study is based on a single large public hospital, and thus, these findings need to be further tested in other settings. This study offers some clues regarding the areas of HRM that seem to be more related with the workers’ perceived performance, and hence provide an interesting framework for managers dealing with healthcare teams. This study contributes to the happy-productive worker hypothesis research, by including seldom used variables in the equation and taking a different perspective. Results provide new clues for investigation and practice regarding the areas of action in HRM that seem to be more prone to elicit perceived effort from the workers.

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This paper presents the main Human Resources Management (HRM) specificities’ on Portuguese hotel units. We try to understand the role of HRM on behavior of co-workers and quality service in hotel units and to know the future tendency of human capital profile on Portuguese hotel units and the role of HRM function on management of their staff. We, also, try to explore if Portuguese culture has influence on HRM specificities’ of hotel units. This phenomenon has a special relevance in the Portuguese context, because this country is known a growing process of tourism industry in recent years. Furthermore, little is known about HRM department’ contributions to their human capital management and development. This paper is one of the first to focus specifically on Portuguese hotel units and it also seeks to present findings that stem from the Human Resources Managers’ perspective. The paper is based on qualitative case studies. The data were collected through semi-structured interviews of 12 human resource managers from 12 hotel units located in Portugal. The results show that although there is not an effective HRM, current HRM practices are enough to encouraging pro-environmental behavior in their staff and they have a direct effect on customer satisfaction and competitiveness of sector. However, managers recognize there is need introduce some change on short-term to promote a better performance of staff with effect on customers satisfaction and competitiveness on sector in Portugal. According to these results, the paper discusses the major theoretical and practical implications.

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The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

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The smart grid concept appears as a suitable solution to guarantee the power system operation in the new electricity paradigm with electricity markets and integration of large amounts of Distributed Energy Resources (DERs). Virtual Power Player (VPP) will have a significant importance in the management of a smart grid. In the context of this new paradigm, Electric Vehicles (EVs) rise as a good available resource to be used as a DER by a VPP. This paper presents the application of the Simulated Annealing (SA) technique to solve the Energy Resource Management (ERM) of a VPP. It is also presented a new heuristic approach to intelligently handle the charge and discharge of the EVs. This heuristic process is incorporated in the SA technique, in order to improve the results of the ERM. The case study shows the results of the ERM for a 33-bus distribution network with three different EVs penetration levels, i. e., with 1000, 2000 and 3000 EVs. The results of the proposed adaptation of the SA technique are compared with a previous SA version and a deterministic technique.

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This paper proposes a simulated annealing (SA) approach to address energy resources management from the point of view of a virtual power player (VPP) operating in a smart grid. Distributed generation, demand response, and gridable vehicles are intelligently managed on a multiperiod basis according to V2G user´s profiles and requirements. Apart from using the aggregated resources, the VPP can also purchase additional energy from a set of external suppliers. The paper includes a case study for a 33 bus distribution network with 66 generators, 32 loads, and 1000 gridable vehicles. The results of the SA approach are compared with a methodology based on mixed-integer nonlinear programming. A variation of this method, using ac load flow, is also used and the results are compared with the SA solution using network simulation. The proposed SA approach proved to be able to obtain good solutions in low execution times, providing VPPs with suitable decision support for the management of a large number of distributed resources.

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Energy resources management can play a very relevant role in future power systems in a SmartGrid context, with intensive penetration of distributed generation and storage systems. This paper deals with the importance of resource management in incident situations. The paper presents DemSi, an energy resources management simulator that has been developed by the authors to simulate electrical distribution networks with high distributed generation penetration, storage in network points and customers with demand response contracts. DemSi is used to undertake simulations for an incident scenario, evidencing the advantages of adequately using flexible contracts, storage, and reserve in order to limit incident consequences.

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We examine volunteer satisfaction with HRM practices, namely recruitment, training and reward in NPOs and attitudes regarding the appropriateness of these practices. The participants in this study are 76 volunteers affiliated with four different NPOs, who work in hospitals and have direct contact with patients and their families. Analysing aggregate results we show that volunteers are more satisfied with training, and consider the training strategies to be very appropriate. After identifying differences between organisations we discover that in some organisations volunteers are satisfied with rewards but they have negative attitudes regarding the appropriateness of the recognition strategies. We also identify the volunteers who are the most and the least satisfied.

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Dissertação apresentada no Instituto Superior de Contabilidade e Administração do Porto para a obtenção do Grau de Mestre em Auditoria ORIENTADOR: DOUTORA MARIA CLARA DIAS PINTO RIBEIRO

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The introduction of electricity markets and integration of Distributed Generation (DG) have been influencing the power system’s structure change. Recently, the smart grid concept has been introduced, to guarantee a more efficient operation of the power system using the advantages of this new paradigm. Basically, a smart grid is a structure that integrates different players, considering constant communication between them to improve power system operation and management. One of the players revealing a big importance in this context is the Virtual Power Player (VPP). In the transportation sector the Electric Vehicle (EV) is arising as an alternative to conventional vehicles propel by fossil fuels. The power system can benefit from this massive introduction of EVs, taking advantage on EVs’ ability to connect to the electric network to charge, and on the future expectation of EVs ability to discharge to the network using the Vehicle-to-Grid (V2G) capacity. This thesis proposes alternative strategies to control these two EV modes with the objective of enhancing the management of the power system. Moreover, power system must ensure the trips of EVs that will be connected to the electric network. The EV user specifies a certain amount of energy that will be necessary to charge, in order to ensure the distance to travel. The introduction of EVs in the power system turns the Energy Resource Management (ERM) under a smart grid environment, into a complex problem that can take several minutes or hours to reach the optimal solution. Adequate optimization techniques are required to accommodate this kind of complexity while solving the ERM problem in a reasonable execution time. This thesis presents a tool that solves the ERM considering the intensive use of EVs in the smart grid context. The objective is to obtain the minimum cost of ERM considering: the operation cost of DG, the cost of the energy acquired to external suppliers, the EV users payments and remuneration and penalty costs. This tool is directed to VPPs that manage specific network areas, where a high penetration level of EVs is expected to be connected in these areas. The ERM is solved using two methodologies: the adaptation of a deterministic technique proposed in a previous work, and the adaptation of the Simulated Annealing (SA) technique. With the purpose of improving the SA performance for this case, three heuristics are additionally proposed, taking advantage on the particularities and specificities of an ERM with these characteristics. A set of case studies are presented in this thesis, considering a 32 bus distribution network and up to 3000 EVs. The first case study solves the scheduling without considering EVs, to be used as a reference case for comparisons with the proposed approaches. The second case study evaluates the complexity of the ERM with the integration of EVs. The third case study evaluates the performance of scheduling with different control modes for EVs. These control modes, combined with the proposed SA approach and with the developed heuristics, aim at improving the quality of the ERM, while reducing drastically its execution time. The proposed control modes are: uncoordinated charging, smart charging and V2G capability. The fourth and final case study presents the ERM approach applied to consecutive days.

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Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

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The massification of electric vehicles (EVs) can have a significant impact on the power system, requiring a new approach for the energy resource management. The energy resource management has the objective to obtain the optimal scheduling of the available resources considering distributed generators, storage units, demand response and EVs. The large number of resources causes more complexity in the energy resource management, taking several hours to reach the optimal solution which requires a quick solution for the next day. Therefore, it is necessary to use adequate optimization techniques to determine the best solution in a reasonable amount of time. This paper presents a hybrid artificial intelligence technique to solve a complex energy resource management problem with a large number of resources, including EVs, connected to the electric network. The hybrid approach combines simulated annealing (SA) and ant colony optimization (ACO) techniques. The case study concerns different EVs penetration levels. Comparisons with a previous SA approach and a deterministic technique are also presented. For 2000 EVs scenario, the proposed hybrid approach found a solution better than the previous SA version, resulting in a cost reduction of 1.94%. For this scenario, the proposed approach is approximately 94 times faster than the deterministic approach.