Alianças estratégicas: análise do sector exportador de produtos português

Dissertação de Mestrado em Finanças Empresariais

Metalearning in ALBidS: A Strategic Bidding System for electricity markets

Metalearning is a subfield of machine learning with special pro-pensity for dynamic and complex environments, from which it is difficult to extract predictable knowledge. The field of study of this work is the electricity market, which due to the restructuring that recently took place, became an especially complex and unpredictable environment, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. This paper presents the development of a metalearner, applied to the decision support of electricity markets’ negotia-tion entities. The proposed metalearner takes advantage on several learning algorithms implemented in ALBidS, an adaptive learning system that pro-vides decision support to electricity markets’ participating players. Using the outputs of each different strategy as inputs, the metalearner creates its own output, considering each strategy with a different weight, depending on its individual quality of performance. The results of the proposed meth-od are studied and analyzed using MASCEM - a multi-agent electricity market simulator that models market players and simulates their operation in the market. This simulator provides the chance to test the metalearner in scenarios based on real electricity market´s data.

MASCEM: electricity markets simulation with strategic agents

Electricity markets are complex environments, involving numerous entities trying to obtain the best advantages and profits while limited by power-network characteristics and constraints.1 The restructuring and consequent deregulation of electricity markets introduced a new economic dimension to the power industry. Some observers have criticized the restructuring process, however, because it has failed to improve market efficiency and has complicated the assurance of reliability and fairness of operations. To study and understand this type of market, we developed the Multiagent Simulator of Competitive Electricity Markets (MASCEM) platform based on multiagent simulation. The MASCEM multiagent model includes players with strategies for bid definition, acting in forward, day-ahead, and balancing markets and considering both simple and complex bids. Our goal with MASCEM was to simulate as many market models and player types as possible. This approach makes MASCEM both a short- and mediumterm simulation as well as a tool to support long-term decisions, such as those taken by regulators. This article proposes a new methodology integrated in MASCEM for bid definition in electricity markets. This methodology uses reinforcement learning algorithms to let players perceive changes in the environment, thus helping them react to the dynamic environment and adapt their bids accordingly.

Strategic bidding methodology for electricity markets using adaptive learning

The very particular characteristics of electricity markets, require deep studies of the interactions between the involved players. MASCEM is a market simulator developed to allow studying electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is implemented as a multiagent system, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. This paper also presents a methodology to define players’ models based on the historic of their past actions, interpreting how their choices are affected by past experience, and competition.

When Corporate Governance crosses the firm borders: family firms in local productive systems

The family involvement in firms is observable is most economies around the world, although there are significant differences among these countries, not only regarding its predominance in these economies, but also in what refers to the levels of involvement of the family in business. This research aims at understanding the family-based firms’ management when compared to non family based, with particular regards to the forms of corporate governance. This analysis is based on case studies and on secondary data found in the literature to support the findings from the empirical research. The data was collected via face to face in-depth interviews with entrepreneurs from the furniture and the events organisation industries (where the family is predominantly present in the furniture but not on the events organisation industry) and with industry and regional business associations. The case studies used in this research allowed the comparison between the Portuguese firms when the family plays an important role in business and those in which the family is absent. It has been found that there are important differences in businesses in countries/industries/local productive systems in which the family is seen as a dominant institution in the society (where businesses are based on strong ties; there is a harmonious relationship between the family members; and the family is accepted locally and dominates the firm organization) and on situations in which the family plays a more marginal role in the society. In fact, the family brings special characteristics to the business, in terms of management, corporate governance, inter and intra firm relationships and succession. Our findings confirm other empirical studies’ results found in the literature. Thus, this article provides a discussion on the factors that play a role in the form of corporate governance structure in family firms highlighting the pros and cons of organising the firm around the family.

Os modelos de governance nas nonprofit organizations de actuação local: uma revisão de literatura

O crescimento do sector não lucrativo, por força da criação de novas organizações sem fins lucrativos, tem-se acentuado nos últimos anos tentando dar resposta ao serviço público que a comunidade exige e que o Estado não tem sabido dar resposta. O sector não lucrativo, ou terceiro sector, realiza funções sociais ou culturais relevantes para a sociedade sem o objectivo de produzir lucros. Em Portugal não existem, para este sector, padrões específicos para os modelos de gestão nem tipologias de informação a utilizar pelos seus stakeholders e, por isso, utilizam-se os mesmos moldes do sector empresarial, cumprindo assim a real consistência do isomorfismo mimético. Existe claramente uma diferença entre os objectivos da informação financeira e não financeira nas organizações lucrativas e nas não lucrativas, e essa destrinça tem a ver directamente com os tipos de destinatários e utilizadores da informação. A abordagem às práticas de corporate governance é uma incontornável realidade no mundo organizacional actual face ao crescente aumento das preocupações das organizações enquanto agentes económicos, sociais e políticos. A sociedade exige às organizações não lucrativas transparência e accountability da informação financeira e não financeira (Carvalho & Blanco, 2007a)) e por isso a adopção de práticas de governance pode trazer benefícios na solução de alguns problemas de gestão. Esta investigação pretende, assim, fazer uma revisão de literatura sobre os modelos de governance, numa abordagem à gestão das organizações sem fins lucrativos de âmbito local, contribuindo assim para a possível definição de um modelo de governance próprio para o sector não lucrativo português.

Corporate governance nas empresas familiares em contexto de sistemas produtivos locais

O envolvimento de famílias em empresas é observável nas economias de todo o mundo, apesar das diferenças evidentes entre países diferentes, não só no que diz respeito à sua predominância nas economia, mas também ao tipo de envolvimento que se pode observar. Esta investigação visa compreender a gestão das empresas familiares quando comparados com os das empresas não familiares, nomeadamente em termos de corporate governance. A análise é baseada em dados secundários de estudos de caso recolhidos da literatura e em dados primários obtidos para se perceber qual o impacto que a organização empresarial familiar tem na relações intra e inter-empresas. Estes estudos de caso possibilitam a oportunidade de comparar as empresas familiares em Portugal, por um lado, e nas economia Anglo-saxónicas, por outro. Este estudo demonstrou que há diferenças importantes no mundo dos negócios em países em que a família é uma instituição muito dominante na sociedade (onde o negócio é baseado em laços fortes, existe uma relação harmoniosa entre os membros da família, e a família é aceite localmente e domina a organização da empresa) e nos países onde a família desempenha um papel mais marginal n sociedade e economia. Os resultados obtidos dos dados primários confirmam a teoria e outros estudos empíricos investigados. Assim, este artigo mostra quais os factores determinantes na estrutura de corporate governance nas empresas familiares sublinhando as vantagens e desvantagens destas em comparação com empresas não familiares

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.

Strategic Planning and Organizational Effectiveness in Social Service Organizations in Portugal

This study aims to understand the reality of social service organizations, the level of implementation of the strategic planning as well as the impact of its application on organizational effectiveness. At first, we will group organizations in clusters according to the level of strategic planning implementation and its degree of effectiveness. Secondly, we will analyse all the different groups. Given the growing number of social service organizations and the consequent complexity of their structures, it turns out the need for these organizations adopt formal management techniques. Strategic planning is a valuable strategic management tool and one of its main objectives is to make organizations more effective. Therefore, the research has been conducted in order to determine if strategic planning is implemented in social service organizations and which effects has its application on organizational effectiveness. The survey, applied to 220 social service organizations, allowed us to gather them into different clusters, showing that different levels of strategic planning determine distinct degrees of organizational efficiency. Finally, it should be noted that findings of this research may be essential to decision makers of these organizations, because it was shown that the adoption of strategic planning has a positive influence on organizational effectiveness of social service organizations.

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.

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.

Strategic Drivers for Implementing Sustainability Programs in Portuguese Organizations– Let’s Listen to Aristotle: From Triple to Quadruple Bottom Line

This article describes a study that investigated the main strategic drivers that influence the implementation of sustainability/social responsibility programs. An online survey was administered to managers of Portuguese organizations with certified management systems. The findings suggest that the implementation of such programs is mainly correlated to: 1.) the approach to understanding and working toward the satisfaction of the community’s needs (in the broad sense of social responsibility); 2.) how systematically sustainability within the organization is identified and managed (e.g., pollution prevention, improved environmental performance, and compliance with the applicable environmental laws); and 3.) the degree to which the organization tries to understand the needs of the employees and works toward satisfying them. In addition to the survey, five interviews with top managers of the surveyed organizations provided some useful insights. There was no consensus on the meaning of sustainability and social responsibility: some described it as an instrumental approach for obtaining better organizational results, while others regarded it as the right thing to do (i.e., it is values driven). In all cases, however, the managers supported a kind of umbrella construct under which different size corporations use different models (for example, the Dow Jones Sustainability Index (DJSI), Global Reporting Initiative (GRI), ISO 14001 environmental management systems), although some managers reported that they simply do not know what to do. All of those surveyed agreed that the lack of a systematic approach could represent a major threat to their organization, making them willing to pay more attention and take more action on the issue of sustainability. An additional suggestion made by managers was to change from a triple bottom line (economic dimension, environmental dimension, social equity dimension) to a quadruple bottom line by adding another dimension: personal and family happiness. This fourth dimension was recognized by the Greek philosopher/thinker Aristotle (384-322 BCE) who thought of happiness as the highest good (virtue) and ultimate goal and purpose of life, achieved through living well, in harmony. Such harmony suggests a balance and a lack of excess—in other words a sustainable existence.

Strategic trade policy and signaling costs with differentiated goods

We consider a trade policy model, where the costs of the home firm are private information but can be signaled through the output levels of the firm to a foreign competitor and a home policymaker. We compute the separating equilibrium and the Bayesian Nash equilibrium, and we compare the subsidies, firms’ expected profits and home government’s welfare in both equilibria, for different values of the own price effect parameter.