Planeamento estratégico através da implementação da metodologia Balanced Scorecard numa empresa de construção

Atualmente, existe uma constante necessidade de inovação tecnológica e organizacional das empresas, face às exigências do mercado e ao aumento constante da competitividade. No contexto da economia atual, e para contrariar a falta de investimento dos últimos anos, as empresas concentram-se no desenvolvimento de negócios bem estruturados e organizados, que satisfaçam as exigências de cada cliente. Revela-se, assim, muito importante a avaliação de desempenho para o alcance do seu sucesso, permitindo alinhar as atividades operacionais com a visão organizacional, fomentar a comunicação da estratégia e gerir o seu desempenho. É neste contexto que ganha importância o Balanced Scorecard, um instrumento que permite avaliar o desempenho organizacional, funcionando também como uma ferramenta de gestão. Tem, portanto, como principais objetivos definir claramente uma estratégia, definir objetivos, indicadores e medidas estratégicas, planear e estabelecer metas e melhorar continuamente os resultados obtidos. Esta ferramenta analisa a organização em quatro diferentes perspetivas: financeira, clientes, processos internos e apendizagem e crescimento. Cada uma delas deve estrututrar os seus próprios objetivos, indicadores, metas e iniciativas de forma a contribuir para o desenvolvimento da estratégia da organização e avaliar o seu desempenho. O desafio deste relatório é adaptar esta metodologia durante a realização de um estágio curricular na empresa Bysteel, que tem por base a implementação de um processo de gestão estratégica nas suas empreitadas, através do Balanced Scorecard. Este planemamento surge como um dos principais requisitos para uma gestão eficaz de custos e de tempo planeados para cada empreitada da Bysteel. Este processo torna-se bastante complexo dado que cada obra apresenta diferentes particularidades. A implementação desta metodologia numa empresa desta dimensão é um fator muito motivador, tornando-se ainda mais interessante pelo facto de se tratar de uma implementação numa nova vertente.

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.

Influence of entrepreneurial orientation in export performance

This study aims at investigating the influence that entrepreneurial orientation has on export performance of Portuguese footwear small and mediumenterprises (SMEs). Therefore, a quantitative methodological approach was used, conducting a descriptive, exploratory and transversal empirical study, having applied a questionnaire to a sample of Portuguese companies exporting footwear. The research results suggest that entrepreneurial orientation enhances export performance in the analysed SMEs, particularly innovation and proactiveness, through the amount of funds invested, human resources dedicated to this activity, number of new products or services introduced in the market and frequent change in product lines or services and materialization of a long-term perspective, which is accompanied by innovative activities or new businesses. Therefore, the findings sustain the necessity to invest in entrepreneurial orientation as a strategic determinant, which contributes to the growth of small firms in foreignmarkets. Finally, the main limitation of this study is related to the sample size, since it was difficult to find companies willing to collaborate with this kind of research.

Performance of state space and ARIMA models for consumer retail sales forecasting

Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.