Gestão de recursos humanos na indústria do turismo em Portugal: tendências futuras do capital humano: um estudo exploratório em unidades hoteleiras no Distrito de Coimbra

No setor do turismo, devido a evolução social e tecnológica, surgiram exigências relativamente ao conhecimento, inovação, informação e qualidade, que resultaram numa maior procura de perfis profissionais adaptados às necessidades a médio prazo (Eurico, 2012). Assim, as unidades hoteleiras têm sentido uma forte necessidade de recrutar e reter pessoas qualificadas e capazes de antecipar múltiplos fatores decisivos na satisfação do cliente. Neste sentido, o presente estudo procura explorar e compreender as tendências futuras ao nível do Capital Humano na indústria do Turismo, mais especificamente no que respeita as unidades hoteleiras, tendo como amostra unidades localizadas no distrito de Coimbra. A análise incidiu nas competências específicas requeridas no setor, qualificações, formação profissional, recrutamento e seleção, sistema de remuneração e recompensa e do sistema de progressão na carreira. Assim, foi escolhido para o presente estudo a metodologia qualitativa, em que os dados foram recolhidos a partir do inquérito por entrevista realizado a sete Diretores e um assistente de direção de oito unidades hoteleiras no Distrito de Coimbra. Para o tratamento dos dados foi aplicada a análise do conteúdo através do processo de preparação das entrevistas transcritas, que, após uma leitura exaustiva, foram transformados em unidades de análise que permitiram a criação de categorias dessas unidades. Após a criação de categorias de análise foi possível realizar a descrição através de uma síntese dos dados fazendo uso de citações diretas dos dados recolhidos. Por fim, foi realizada a interpretação dos dados que traduz-se na relação das categorias das unidades de análise e a fundamentação teórica presente neste estudo (Santos, 2012). Os resultados obtidos a partir deste estudo revelam que os requisitos exigidos para os colaboradores e para determinadas práticas de gestão de recursos humanos nas unidades hoteleiras atualmente e num futuro próximo serão essencialmente os mesmos. Todavia, foi possível estabelecer o perfil ideal dos futuros colaboradores das unidades hoteleiras e tendências de práticas de gestão de recursos humanos como formação e desenvolvimento, recrutamento e seleção, planos de progressão na carreira e sistemas de remuneração e recompensa. Foi igualmente possível verificar que a maioria das unidades hoteleiras analisadas é de pequena e média dimensão não dispõe de um departamento de Recursos Humanos, sendo aplicada pelos gestores de topo.

Tendências de recompensas em empresas portuguesas

Esta dissertação tem como objetivo central conhecer os sistemas de recompensas em empresas portuguesas. Primeiramente é realizada uma abordagem aos conceitos subjacentes ao sistema de recompensas e, simultaneamente é exposta teoria sobre o tipo de recompensas mais utilizadas e como estas diferem consoante o cargo/função. Foi aplicado um inquérito por questionário a uma amostra de 144 empresas localizadas por todo o país. Foram testadas hipóteses de estudo capazes de permitir caraterizar o sistema de recompensas desenvolvido nas empresas em estudo. Os resultados do estudo permitem concluir que: 1) os sistemas de recompensas baseados na antiguidade estão atualmente em desuso, ao contrário dos sistemas de recompensas baseados na função/cargo, no desempenho e nas competências; 2) o principal objetivo do sistema de recompensas das empresas do estudo é a motivação dos colaboradores; 3) a conjugação das recompensas monetárias e não monetárias são as mais valorizadas pelas empresas; 4) predomina a compensação variável nos sistemas de recompensas das empresas bem como os incentivos mistos (individuais e de grupo); 5) predominam os incentivos de curto-prazo no sistema de recompensas; 6) o bónus anual é o incentivo mais utilizado; 7) os benefícios e alguns dos incentivos tendem a ser maiores à medida que se sobe na hierarquia funcional da empresa; 8) o benefício predominante é a atribuição de telemóvel e o seguro de saúde; 9) as formas de reconhecimento mais comuns são os prémios de desempenho, o feedback contínuo, as promoções e as placas comemorativas; 10) a maioria dos inquiridos acredita que as oportunidades de desenvolvimento de carreira é uma importante medida para a retenção dos colaboradores; 11) as oportunidades de desenvolvimento são mais utilizadas pelas empresas de maior dimensão e; 12) os benefícios sociais são considerados a componente mais importante para garantir a retenção dos colaboradores. Com base nestes resultados, na parte final da dissertação são apresentadas algumas implicações teóricas e práticas, algumas limitações do estudo, bem como pistas para investigações futuras.

Learning management systems usage on higher education institutions

Learning Management Systems (LMS) are used all over Higher Education Institutions (HEI) and the need to know and understand its adoption and usage arises. However, there is a lack of information about how LMSs are being used, which are the most adopted, whether there is a country adoption standard and which countries use more LMSs. A research team is developing a project that tries to fill this lack of information and provide the needed answers. With this purpose, on a first phase, it a survey was taken place. The results of this survey are presented in this paper. Another purpose of this paper is to disseminate the ongoing project.

An architecture for an effective usage of data mining in business intelligence systems

Business Intelligence (BI) is one emergent area of the Decision Support Systems (DSS) discipline. Over the last years, the evolution in this area has been considerable. Similarly, in the last years, there has been a huge growth and consolidation of the Data Mining (DM) field. DM is being used with success in BI systems, but a truly DM integration with BI is lacking. Therefore, a lack of an effective usage of DM in BI can be found in some BI systems. An architecture that pretends to conduct to an effective usage of DM in BI is presented.

Knowledge and technologies in innovative information systems

7th Mediterranean Conference on Information Systems, MCIS 2012, Guimaraes, Portugal, September 8-10, 2012, Proceedings Series: Lecture Notes in Business Information Processing, Vol. 129

Organization knowledge management change from a complex adaptive systems perpective with ability for ambidexeterity

We are working on the confluence of knowledge management, organizational memory and emergent knowledge with the lens of complex adaptive systems. In order to be fundamentally sustainable organizations search for an adaptive need for managing ambidexterity of day-to-day work and innovation. An organization is an entity of a systemic nature, composed of groups of people who interact to achieve common objectives, making it necessary to capture, store and share interactions knowledge with the organization, this knowledge can be generated in intra-organizational or inter-organizational level. The organizations have organizational memory of knowledge of supported on the Information technology and systems. Each organization, especially in times of uncertainty and radical changes, to meet the demands of the environment, needs timely and sized knowledge on the basis of tacit and explicit. This sizing is a learning process resulting from the interaction that emerges from the relationship between the tacit and explicit knowledge and which we are framing within an approach of Complex Adaptive Systems. The use of complex adaptive systems for building the emerging interdependent relationship, will produce emergent knowledge that will improve the organization unique developing.

Multi-criteria short-term maintenance outage scheduling in smart distribution systems

Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

Self-optimization for dynamic scheduling in manufacturing systems

Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT).

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

Hybrid fuzzy Monte Carlo technique for reliability assessment in transmission power systems

This paper proposes a new methodology to reduce the probability of occurring states that cause load curtailment, while minimizing the involved costs to achieve that reduction. The methodology is supported by a hybrid method based on Fuzzy Set and Monte Carlo Simulation to catch both randomness and fuzziness of component outage parameters of transmission power system. The novelty of this research work consists in proposing two fundamentals approaches: 1) a global steady approach which deals with building the model of a faulted transmission power system aiming at minimizing the unavailability corresponding to each faulted component in transmission power system. This, results in the minimal global cost investment for the faulted components in a system states sample of the transmission network; 2) a dynamic iterative approach that checks individually the investment’s effect on the transmission network. A case study using the Reliability Test System (RTS) 1996 IEEE 24 Buses is presented to illustrate in detail the application of the proposed methodology.

The verification of temporal KBS: SPARSE - a case study in power systems

In this paper we present VERITAS, a tool that focus time maintenance, that is one of the most important processes in the engineering of the time during the development of KBS. The verification and validation (V&V) process is part of a wider process denominated knowledge maintenance, in which an enterprise systematically gathers, organizes, shares, and analyzes knowledge to accomplish its goals and mission. The V&V process states if the software requirements specifications have been correctly and completely fulfilled. The methodologies proposed in software engineering have showed to be inadequate for Knowledge Based Systems (KBS) validation and verification, since KBS present some particular characteristics. VERITAS is an automatic tool developed for KBS verification which is able to detect a large number of knowledge anomalies. It addresses many relevant aspects considered in real applications, like the usage of rule triggering selection mechanisms and temporal reasoning.

Adaptive learning in multiagent systems: a forecasting methodology based on error analysis

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.

An efficient method for optimal location and sizing of fixed and switched shunt capacitors in large distribution systems

This paper proposes a computationally efficient methodology for the optimal location and sizing of static and switched shunt capacitors in large distribution systems. The problem is formulated as the maximization of the savings produced by the reduction in energy losses and the avoided costs due to investment deferral in the expansion of the network. The proposed method selects the nodes to be compensated, as well as the optimal capacitor ratings and their operational characteristics, i.e. fixed or switched. After an appropriate linearization, the optimization problem was formulated as a large-scale mixed-integer linear problem, suitable for being solved by means of a widespread commercial package. Results of the proposed optimizing method are compared with another recent methodology reported in the literature using two test cases: a 15-bus and a 33-bus distribution network. For the both cases tested, the proposed methodology delivers better solutions indicated by higher loss savings, which are achieved with lower amounts of capacitive compensation. The proposed method has also been applied for compensating to an actual large distribution network served by AES-Venezuela in the metropolitan area of Caracas. A convergence time of about 4 seconds after 22298 iterations demonstrates the ability of the proposed methodology for efficiently handling large-scale compensation problems.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.