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.

Full-scale biological phosphorus removal: quantification of storage polymers, microbial performance and metabolic modelling

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

Numerical Evaluation of Ventilation Performance in Children Day Care Centres

Modelling of ventilation is strongly dependent on the physical characteristics of the building of which precise evaluation is a complex and time consuming task. In the frame of a research project, two children day care centres (CDCC) have been selected in order to measure the envelope air permeability, the flow rate of mechanical ventilation systems and indoor and outdoor temperature. The data obtained was used as input to the computer code CONTAM for ventilation simulations. The results obtained were compared with direct measurements of ventilation flow from short term measurements with CO2 tracer gas and medium term measurements with perfluorocarbon tracer (PFT) gas decay method. After validation, in order to analyse the main parameters that affect ventilation, the model was used to predict the ventilation rates for a wide range of conditions. The purpose of this assessment was to find the best practices to improve natural ventilation. A simple analytical method to predict the ventilation flow rate of rooms is also presented. The method is based on the estimation of wind effect on the room through the evaluation of an average factor and on the assessment of relevant cross section of gaps and openings combined in series or in parallel. It is shown that it may be applied with acceptable accuracy for this type of buildings when ventilation is due essentially to wind action.

An ANP model to support decision-making in a Portuguese pharmaceutical supply chain

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

A simulation model for lean, agile, resilient and green supply chain management: practices and interoperability assessment

Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial

Bank capital and stock performance around the subprime lending risis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

A framework for efficient model transformations

The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.

E-Health individual adoption - empirical model based on UTAUT 2.

The future of health care delivery is becoming more citizen-centred, as today’s user is more active, better informed and more demanding. The European Commission is promoting online health services and, therefore, member states will need to boost deployment and use of online services. This makes e-health adoption an important field to be studied and understood. This study applied the extended unified theory of acceptance and usage technology (UTAUT2) to explain patients’ individual adoption of e-health. An online questionnaire was administrated Portugal using mostly the same instrument used in UTAUT2 adapted to e-health context. We collected 386 valid answers. Performance expectancy, effort expectancy, social influence, and habit had the most significant explanatory power over behavioural intention and habit and behavioural intention over technology use. The model explained 52% of the variance in behavioural intention and 32% of the variance in technology use. Our research helps to understand the desired technology characteristics of ehealth. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt e-health systems or not.

Construction of Lean and Green indexes to measure companies’ performance

The demand for costs and time reductions in companies’ processes, in order to increase efficiency, leads companies to seek innovative management paradigms to support their needs for growth and continuous improvement. The Lean paradigm has great relevance in companies’ need for waste reduction, particularly in manufacturing companies. On the other hand the demand of companies for waste reduction has gained a new dimension not only at the material level, but also at the environmental level with the introduction of the Green paradigm. As such, manufacturing companies have been adopting practices that reduce the impact of their activities on the environment. Although nowadays many manufacturing companies already implement waste reduction practices related to Lean and Green paradigms, many of them are unable to understand specifically if their efforts are enough for the application of these practices to be successful or even if their actual performance in implementing Lean or Green practices reflects the self-assessment that they have of themselves. Thus, besides the study of the development of Lean and Green paradigms in recent years, the present dissertation has the important objective of the construction of two indexes (the Lean Index and the Green Index) enabling the measurement of the performance of Portuguese manufacturing companies relating the implementation of Lean and Green practices. The data used to create the Lean and Green indexes where obtained from the implementation of the European Manufacturing Survey 2012 in Portugal. The survey questions related to the implementation of Lean and Green practices are used as variables in the development of the model for the two indexes. For the construction of representative expressions of Lean Index and Green Index it was applied the Factorial Analysis for assigning the variables weights and aggregation.

A model to screen and improve business potential of micro and small enterprises in developing countries: Evidence from the Island of Mozambique

Programmes supporting micro and small enterprises in developing countries have been showing that capital is not enough to allow business success: survival and growth. Literature does not provide comprehensive and practical tool to support business development in this context, but allowed the collection of forty-nine success variables that were studied in a sample of successful and unsuccessful businesses in the Island of Mozambique to discover what were the key factors affecting those businesses’ performance. Empirical data gave the insights for the development of a model to screen and improve business potential of micro and small enterprises in this context.

Performance analysis of an SRI screen based on employment quality in high and low capital industries: International evidence

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics and Maastricht University School of Business and Economics

Post-merger innovative performance in the renewable energy sector

Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate.

The relationship between the education level of successor's and the firm performance in German publicly listed family firms- an empirical analysis

The purpose of this thesis is to investigate how far the education level of the second or third generation of publicly traded German family firms affects the post-succession firm performance. By conducting a correlational and regression design, the aim is to examine how several variables influence the performance of family firms. Performance measures, for example ROA and Tobin’s q and variables, like Education level and succession periods, examine analytically that a positive succession trend will occur. However, with the used model, only a less rigid model shows empirical evidence.

High performance fiber reinforced concrete for the shear reinforcement: experimental and numerical research

High performance fiber reinforced concrete (HPFRC) is developing rapidly to a modern structural material with unique rheological and mechanical characteristics. Despite applying several methodologies to achieve self15 compacting requirements, some doubts still remain regarding the most convenient strategy for developing a HPFRC. In the present study, an innovative mix design method is proposed for the development of high17 performance concrete reinforced with a relatively high dosage of steel fibers. The material properties of the developed concrete are assessed, and the concrete structural behavior is characterized under compressive, flexural and shear loading. This study better clarifies the significant contribution of fibers for shear resistance of concrete elements. This paper further discusses a FEM-based simulation, aiming to address the possibility of calibrating the constitutive model parameters related to fracture modes I and II.