Group decision making for selection of an information system in a business context

The main objective of this work is to report on the development of a multi-criteria methodology to support the assessment and selection of an Information System (IS) framework in a business context. The objective is to select a technological partner that provides the engine to be the basis for the development of a customized application for shrinkage reduction on the supply chains management. Furthermore, the proposed methodology di ers from most of the ones previously proposed in the sense that 1) it provides the decision makers with a set of pre-defined criteria along with their description and suggestions on how to measure them and 2)it uses a continuous scale with two reference levels and thus no normalization of the valuations is required. The methodology here proposed is has been designed to be easy to understand and use, without a specific support of a decision making analyst.

A importância das consultoras no processo de internacionalização das micro, pequenas e médias empresas em Portugal

Relatório de Estágio Apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Empreendedorismo e Internacionalização, sob orientação da Mestre Inês Veiga Pereira

Gestão de risco: articulação com o planeamento estratégico e a contabilidade de gestão: estudo aplicado a empresas não financeiras do concelho de Vila do Conde

Este trabalho de investigação tem como objetivo analisar se as empresas do concelho de Vila do Conde, efetuam planeamento estratégico, contabilidade de gestão e/ou gestão de risco. Pretende-se ainda verificar se o facto de existir articulação entre estas três áreas da empresa influencia o resultado do seu EBIT (Earning Before Interest and Taxes). Através da literatura relevante, verificou-se que o planeamento estratégico, a contabilidade de gestão e a gestão de risco têm progredido de modo a responder às mudanças do meio envolvente onde as empresas estão a operar. Contudo, em termos práticos, este estudo permitiu verificar que a implementação da gestão de risco e da contabilidade de gestão no tecido empresarial de Vila do Conde tem sido muito lenta. Os dados foram recolhidos através dum inquérito eletrónico efetuado a 505 empresas do concelho de Vila do Conde de diversas atividades económicas pertencentes aos três grandes sectores (serviços, indústria e comércio). De acordo com os resultados obtidos, concluiu-se que apenas 17% das empresas do concelho de Vila do Conde efetuam simultâneamente planeamento estratégico, contabilidade de gestão e gestão de risco. Conclui-se ainda que as empresas do concelho de Vila do Conde que efetuam em simultâneo planeamento estratégico, contabilidade de gestão e gestão de risco apresentam em média um EBIT (2010) aparenta ser superior às que não fazem planeamento estratégico, contabilidade de gestão e gestão de risco.

China's space program : a new tool for PRC "soft power" in international relations?

When China launched an anti-satellite (ASAT) weapon in January 2007 to destroy one of its inactive weather satellites, most reactions from academics and U.S. space experts focused on a potential military “space race” between the United States and China. Overlooked, however, is China’s growing role as global competitor on the non-military side of space. China’s space program goes far beyond military counterspace applications and manifests manned space aspirations, including lunar exploration. Its pursuit of both commercial and scientific international space ventures constitutes a small, yet growing, percentage of the global space launch and related satellite service industry. It also highlights China’s willingness to cooperate with nations far away from Asia for political and strategic purposes. These partnerships may constitute a challenge to the United States and enhance China’s “soft power” among key American allies and even in some regions traditionally dominated by U.S. influence (e.g., Latin America and Africa). Thus, an appropriate U.S. response may not lie in a “hard power” counterspace effort but instead in a revival of U.S. space outreach of the past, as well as implementation of more business-friendly export control policies.

Information professionals in business context: new professionals, old skills

This communication aims to present some reflections regarding the importance of information in organizational context, especially in business context. The ability to produce and to share expertise and knowledge among its employees is now a key factor in the success of any organization. However, it’s also true that workers are increasingly feeling that too much information can hurt their performance. The existence of skilled professionals able to organize, evaluate, select and disseminate information in organizations appears to be a prerequisite for success. The skills necessary for the formation of a professional devoted to the management of information and knowledge in the context of business organizations will be analysed. Then data collected in two focus group discussion with students from a graduate course in Business Information, from Polytechnic Institute of Porto, Portugal, a will be examined.

Strategic environmental assessment in Tróia (Portugal)

Proceedings of the First International Conference on Coastal Conservation and Management in the Atlantic and Mediterranean, p. 91-98

Intelligent Remuneration and Tariffs for Virtual Power Players

Power systems have been through deep changes in recent years, namely due to the operation of competitive electricity markets in the scope the increasingly intensive use of renewable energy sources and distributed generation. This requires new business models able to cope with the new opportunities that have emerged. Virtual Power Players (VPPs) are a new type of player that allows aggregating a diversity of players (Distributed Generation (DG), Storage Agents (SA), Electrical Vehicles (V2G) and consumers) to facilitate their participation in the electricity markets and to provide a set of new services promoting generation and consumption efficiency, while improving players’ benefits. A major task of VPPs is the remuneration of generation and services (maintenance, market operation costs and energy reserves), as well as charging energy consumption. This paper proposes a model to implement fair and strategic remuneration and tariff methodologies, able to allow efficient VPP operation and VPP goals accomplishment in the scope of electricity markets.

Stochastic Framework for Strategic Decision-making of Load-serving Entities for Day-ahead Market

The deregulation of electricity markets has diversified the range of financial transaction modes between independent system operator (ISO), generation companies (GENCO) and load-serving entities (LSE) as the main interacting players of a day-ahead market (DAM). LSEs sell electricity to end-users and retail customers. The LSE that owns distributed generation (DG) or energy storage units can supply part of its serving loads when the nodal price of electricity rises. This opportunity stimulates them to have storage or generation facilities at the buses with higher locational marginal prices (LMP). The short-term advantage of this model is reducing the risk of financial losses for LSEs in DAMs and its long-term benefit for the LSEs and the whole system is market power mitigation by virtually increasing the price elasticity of demand. This model also enables the LSEs to manage the financial risks with a stochastic programming framework.

Strategic Bidding for Electricity Markets Negotiation Using Support Vector Machines

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which simulates the electricity markets environment. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. This paper presents the application of a Support Vector Machines (SVM) based approach to provide decision support to electricity market players. This strategy is tested and validated by being included in ALBidS and then compared with the application of an Artificial Neural Network, originating promising results. The proposed approach is tested and validated using real electricity markets data from MIBEL - Iberian market operator.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Strategic Bidding in Electricity Markets: An agent-based simulator with game theory for scenario analysis

Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

Metalearner based on Dynamic Neural Network for Strategic Bidding in electricity Markets

The restructuring of electricity markets, conducted to increase the competition in this sector, and decrease the electricity prices, brought with it an enormous increase in the complexity of the considered mechanisms. The electricity market became a complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. Software tools became, therefore, essential to provide simulation and decision support capabilities, in order to potentiate the involved players’ actions. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotiation entities. The proposed metalearner executes a dynamic artificial neural network to create its own output, taking advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that provides decision support to electricity markets’ players. The proposed metalearner considers different weights for each strategy, depending on its individual quality of performance. The results of the proposed method are studied and analyzed in scenarios based on real electricity markets’ data, using MASCEM - a multi-agent electricity market simulator that simulates market players’ operation in the market.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

Lean enterprise resource planning

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia e Gestão Industrial

Dados, informação, conhecimento, o business intelligence e as suas motivações

Dissertação para obtenção do Grau de Mestre em Engenharia Informática