Learning in higher education: strategies to overcome challenges faced by adult students - lessons drawn from two studies in portugal

Int’l J. of Information and Communication Technology Education, 3(2), 1-14, April-June 2007

Internacionalização do vinho do Porto – estudo de caso Grupo Sogevinus

Dissertação apresentada ao Instituto Superior de Contabilidade para a obtenção do Grau de Mestre em Empreendedorismo e Internacionalização Orientada por Professor Doutor José Freitas Santos

Learning business strategies for competitive electronic marketplaces

This paper presents a Multi-Agent Market simulator designed for developing new agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. This tool studies negotiations based on different market mechanisms and, time and behavior dependent strategies. The results of the negotiations between agents are analyzed by data mining algorithms in order to extract rules that give agents feedback to improve their strategies. The system also includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agent reactions.

A congestion management and transmission price simulator for competitive electricity markets

In a liberalized electricity market, the Transmission System Operator (TSO) plays a crucial role in power system operation. Among many other tasks, TSO detects congestion situations and allocates the payments of electricity transmission. This paper presents a software tool for congestion management and transmission price determination in electricity markets. The congestion management is based on a reformulated Optimal Power Flow (OPF), whose main goal is to obtain a feasible solution for the re-dispatch minimizing the changes in the dispatch proposed by the market operator. The transmission price computation considers the physical impact caused by the market agents in the transmission network. The final tariff includes existing system costs and also costs due to the initial congestion situation and losses costs. The paper includes a case study for the IEEE 30 bus power system.

Long-term price range forecast applied to risk management using regression models

Long-term contractual decisions are the basis of an efficient risk management. However those types of decisions have to be supported with a robust price forecast methodology. This paper reports a different approach for long-term price forecast which tries to give answers to that need. Making use of regression models, the proposed methodology has as main objective to find the maximum and a minimum Market Clearing Price (MCP) for a specific programming period, and with a desired confidence level α. Due to the problem complexity, the meta-heuristic Particle Swarm Optimization (PSO) was used to find the best regression parameters and the results compared with the obtained by using a Genetic Algorithm (GA). To validate these models, results from realistic data are presented and discussed in detail.

A short-term risk management tool applied to OMEL electricity market using particle swarm optimization

Short-term risk management is highly dependent on long-term contractual decisions previously established; risk aversion factor of the agent and short-term price forecast accuracy. Trying to give answers to that problem, this paper provides a different approach for short-term risk management on electricity markets. Based on long-term contractual decisions and making use of a price range forecast method developed by the authors, the short-term risk management tool presented here has as main concern to find the optimal spot market strategies that a producer should have for a specific day in function of his risk aversion factor, with the objective to maximize the profits and simultaneously to practice the hedge against price market volatility. Due to the complexity of the optimization problem, the authors make use of Particle Swarm Optimization (PSO) to find the optimal solution. Results from realistic data, namely from OMEL electricity market, are presented and discussed in detail.

Virtual power producers market strategies

This paper presents MASCEM - a multi-agent based electricity market simulator. MASCEM uses game theory, machine learning techniques, scenario analysis and optimisation techniques to model market agents and to provide them with decision-support. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. The paper detail some of the most important aspects considered in VPP formation and in the aggregation of new producers and includes a case study.

Transmission price simulator in a liberalized electricity market

This paper presents a software tool (SIM_CMTP) that solves congestion situations and evaluates the taxes to be paid to the transmission system by market agents. SIM_CMTP provides users with a set of alternative methods for cost allocation and enables the definition of specific rules, according to each market and/or situation needs. With these characteristics, SIM_CMTP can be used as an operation aid for Transmission System Operator (TSO) or Independent System Operator (ISO). Due to its openness, it can also be used as a decision-making support tool for evaluating different options of market rules in competitive market environment, guarantying the economic sustainability of the transmission system.

Multi-agent electricity market simulation with dynamic strategies & virtual power producers

Distributed energy resources will provide a significant amount of the electricity generation and will be a normal profitable business. In the new decentralized grid, customers will be among the many decentralized players and may even help to co-produce the required energy services such as demand-side management and load shedding. So, they will gain the opportunity to be more active market players. The aggregation of DG plants gives place to a new concept: the Virtual Power Producer (VPP). VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets. In this paper we propose the improvement of MASCEM, a multi-agent simulation tool to study negotiations in electricity spot markets based on different market mechanisms and behavior strategies, in order to take account of decentralized players such as VPP.

Mergers and acquisitions as strategies of business expansion in the pharmaceutical industry

Introduction: The present paper deals with the issue of the increasing usage of corporation mergers and acquisitions strategies within pharmaceutical industry environment. The aim is to identify the triggers of such business phenomenon and the immediate impact on the financial outcome of two powerful biopharmaceutical corporations: Pfizer and GlaxoSmithKline, which have been sampled due to their successful approach of the tactics in question. Materials and Methods: In order to create an overview of the development steps through mergers and acquisitions, the historical data of the two corporations has been consulted, from their official websites. The most relevant events were then associated with adequate information from the financial reports and statements of the two corporations indulged by web-based financial data providers. Results and Discussions: In the past few decades Pfizer and GlaxoSmithKline have purchased or merged with various companies in order to monopolize new markets, diversify products and services portfolios, survive and surpass competitors. The consequences proved to be positive although this approach implies certain capital availability. Conclusions: Results reveal the fact that, as far as the two sampled companies are concerned, acquisitions and mergers are reactions at the pressure of the highly competitive environment. Moreover, the continuous diversification of the market’s needs is also a consistent motive. However, the prevalence and the eminence of mergers and acquisition strategies are conditioned by the tender offer, the announcer’s caliber, research and development status and further other factors determined by the internal and external actors of the market.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Nodal price simulation in competitive electricity markets

Locational Marginal Prices (LMP) are important pricing signals for the participants of competitive electricity markets, as the effects of transmission losses and binding constraints are embedded in LMPs [1],[2]. This paper presents a software tool that evaluates the nodal marginal prices considering losses and congestion. The initial dispatch is based on all the electricity transactions negotiated in the pool and in bilateral contracts. It must be checked if the proposed initial dispatch leads to congestion problems; if a congestion situation is detected, it must be solved. An AC power flow is used to verify if there are congestion situations in the initial dispatch. Whenever congestion situations are detected, they are solved and a feasible dispatch (re-dispatch) is obtained. After solving the congestion problems, the simulator evaluates LMP. The paper presents a case study based on the the 118 IEEE bus test network.

Residential property loans and performance during property price booms: evidence from European banks

Understanding the performance of banks is of the utmost relevance, because of the impact of this sector on economic growth and financial stability. Of all the different assets that make up a bank portfolio, the residential mortgage loans constitute one of its main. Using the dynamic panel data method, we analyse the influence of residential mortgage loans on bank profitability and risk, using a sample of 555 banks in the European Union (EU-15), over the period from 1995 to 2008. We find that banks with larger weights of residential mortgage loans show lower credit risk in good times. This result explains why banks rush to lend on property during booms due to the positive effects it has on credit risk. The results show further that credit risk and profitability are lower during the upturn in the residential property price cycle. The results also reveal the existence of a non-linear relationship (U-shaped marginal effect), as a function of bank’s risk, between profitability and the residential mortgage loans exposure. For those banks that have high credit risk, a large exposure of residential mortgage loans is associated with higher risk-adjusted profitability, through lower risk. For banks with a moderate/low credit risk, the effects of higher residential mortgage loan exposure on its risk-adjusted profitability are also positive or marginally positive.

Residential property loans and performance during property price booms: evidence from European

Understanding the performance of banks is of the u tmost importance due to the impact the sector may have on economic growth and financial stability. Residential mortgage loans constitute a large proportion of the portfolio of many banks and are one of the key assets in the determination of performance. Using a dynamic panel model , we analyse the impact of res idential mortgage loans on bank profitability and risk , based on a sample of 555 banks in the European Union ( EU - 15 ) , over the period from 1995 to 2008. We find that banks with larger weight s in residential mortgage loans display lower credit risk in good market conditions . This result may explain why banks rush to lend on property during b ooms due to the positive effect it has on credit risk . The results also show that credit risk and profitability are lower during the upturn in the residential property cy cle. Furthermore, t he results reveal the existence of a non - linear relationship ( U - shaped marginal effect), as a function of bank’s risk, between profitability and residential mortgage exposure . For those banks that have high er credit risk, a large exposur e to residential loans is associated with increased risk - adjusted profitability, through a reduction in risk. For banks with a moderate to low credit risk, the impact of higher exposure are also positive on risk - adjusted profitability.

Entrepreneurship Strategies in a Portuguese and in a Polish Region

In the present paper we will consider strategies of innovation, risk and proactivity as entre/ intrapreneurship strategies. This study was done in a Portuguese and in a Polish region. In Portugal the region was Vale do Sousa, located in the northern Portugal. The Polish region was Lublin Voivodeship and it is situated in the south-eastern part of the country. The study focused on Industrial and Construction sectors. In order to get a valid sample, a group of 251 firms were analysed in Portugal, and 215 in Poland. However, the minimum sample size in Poland should be 323. Since this is a work in progress, we are aiming for this number of questionnaires. Each strategy was analysed individually for both regions and the results pointed to a lack of culture of entrepreneurship in firms’ management. Only Proactivity presented a positive result in firms’ management. Polish firms tend to be more innovative and more risk takers, while in proactivity Portuguese ones present a slightly higher result. Combining the strategy results, it was possible to identify that 61.2% of Portuguese firms present a low level of entrepreneurship, while 60% of Polish firms present a moderate level. Considering intrapreneurship good levels, while Portugal account for 5.2% this figure is 19.1% in Poland.