943 resultados para Customers Loyalty
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Mestrado em Controlo de Gestão e dos Negócios
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Mestrado em Controlo e Gestão dos Negócios
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Mestrado em Gestão e Empreendedorismo
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Dissertação Apresentada ao Instituto Politécnico do Porto para obtenção do Grau de Mestre em Gestão das Organizações, Ramo Gestão de Empresas Orientada pelo Professor Doutor José de Freitas Santos
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Dissertação de Mestrado Apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital, sob orientação de Professor Doutor Freitas Santos
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Mestrado em Gestão e Empreendedorismo
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Mestrado em Contabilidade e Gestão de Instituições Financeiras
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Relatório de estágio apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Gestão Estratégica das Relações Públicas.
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SERVQUAL is the most popular instrument to ascertain service quality. However, some debate exists about its ability to characterize different service environments. Furthermore, there is not a consensus about the inclusion of customer expectations in the model. The research presented in this paper intends to discuss the applicability of SERVQUAL to restaurant services and to analyze the inclusion of customer expectations in such environment. The research was developed in a Portuguese resort and more than 300 customers, from two different restaurants, were invited to participate in the study.
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Cloud SLAs compensate customers with credits when average availability drops below certain levels. This is too inflexible because consumers lose non-measurable amounts of performance being only compensated later, in next charging cycles. We propose to schedule virtual machines (VMs), driven by range-based non-linear reductions of utility, different for classes of users and across different ranges of resource allocations: partial utility. This customer-defined metric, allows providers transferring resources between VMs in meaningful and economically efficient ways. We define a comprehensive cost model incorporating partial utility given by clients to a certain level of degradation, when VMs are allocated in overcommitted environments (Public, Private, Community Clouds). CloudSim was extended to support our scheduling model. Several simulation scenarios with synthetic and real workloads are presented, using datacenters with different dimensions regarding the number of servers and computational capacity. We show the partial utility-driven driven scheduling allows more VMs to be allocated. It brings benefits to providers, regarding revenue and resource utilization, allowing for more revenue per resource allocated and scaling well with the size of datacenters when comparing with an utility-oblivious redistribution of resources. Regarding clients, their workloads’ execution time is also improved, by incorporating an SLA-based redistribution of their VM’s computational power.
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Electricity markets are systems for effecting the purchase and sale of electricity using supply and demand to set energy prices. Two major market models are often distinguished: pools and bilateral contracts. Pool prices tend to change quickly and variations are usually highly unpredictable. In this way, market participants often enter into bilateral contracts to hedge against pool price volatility. This article addresses the challenge of optimizing the portfolio of clients managed by trader agents. Typically, traders buy energy in day-ahead markets and sell it to a set of target clients, by negotiating bilateral contracts involving three-rate tariffs. Traders sell energy by considering the prices of a reference week and five different types of clients. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.
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The electricity industry throughout the world, which has long been dominated by vertically integrated utilities, has experienced major changes. Deregulation, unbundling, wholesale and retail wheeling, and real-time pricing were abstract concepts a few years ago. Today market forces drive the price of electricity and reduce the net cost through increased competition. As power markets continue to evolve, there is a growing need for advanced modeling approaches. This article addresses the challenge of maximizing the profit (or return) of power producers through the optimization of their share of customers. Power producers have fixed production marginal costs and decide the quantity of energy to sell in both day-ahead markets and a set of target clients, by negotiating bilateral contracts involving a three-rate tariff. Producers sell energy by considering the prices of a reference week and five different types of clients with specific load profiles. They analyze several tariffs and determine the best share of customers, i.e., the share that maximizes profit. © 2014 IEEE.
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Trabalho realizado sob orientação do Prof. António Brandão Moniz para a disciplina “Factores Sociais da Inovação” do Mestrado Engenharia Informática realizado na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa
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Dissertation presented to obtain a Masters degree in Computer Science
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.