On Business Analytics: Dynamic Network Analysis for Descriptive Analytics and Multicriteria Decision Analysis for Prescriptive Analytics.

Ferry Jules. Collèges communaux. — Classement des professeurs. In: Bulletin administratif de l'instruction publique. Tome 24 n°467, 1881. pp. 836-842

Partner selection in virtual enterprises

Tese de doutoramento. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 200

Sustainable energy transitions in Austria: a participatory multi-criteria appraisal of scenarios

In the light of advancing climate change and the anticipated scarcity of affordable fossil fuels, a transition towards more sustainable energy systems is vital to allow for the long-term sustainability of human wellbeing. Energy is a key sustainability issue, at the heart of the complex interactions of socioeconomic and biophysical systems. The overall aim of this study is to contribute to furthering the understanding of these systems interactions. It intends to deliver methodological insights on how to identify and appraise favourable energy futures in a changing and uncertain world. In order to cope with the complexity and uncertainty of future developments and with the plethora of partly contradictory social preferences, a participatory approach was combined with scenario development and the application of an appraisal tool that takes account of the multidimensionality of system interlinkages. In a case study for Austria, favourable renewable energy scenarios were developed in a participatory setting, involving key Austrian energy stakeholders. The scenario development consisted of two stages: first an exploratory stage with stakeholder engagement and second a modelling stage generating forecasting-type scenarios. Accordingly, the scenarios consist of a narrative part, the storyline, and a modelled, quantitative part. The application of Multi-Criteria Analysis (MCA) allowed the integration of multi-dimensional sustainability information (social, environmental, economic, and technological criteria) and the social preferences of the stakeholders into the appraisal of the energy scenarios. In the case study presented, five renewable energy scenarios for Austria for 2020 were compared against 17 sustainability criteria. The study illustrates how the combined use of participatory scenario building techniques and MCA acknowledges and integrates inherent complexity, irreducible uncertainty, multi-dimensionality, and, a multiplicity of legitimate perspectives in the appraisal. The main empirical result of the sustainability appraisal undertaken shows that, contrary to the current energy policy in Austria, a profoundly decentralised energy system (scenario E) and an innovative long-term investment strategy (scenario C) rank highest, whereas the renewable strategy based on biomass (scenario D), which represents the dominant political trajectory in Austria’s renewable energy policy, ranks very low. The research demonstrates the integration of biophysical, social, economic, and, technological appraisal criteria, presents and discusses best practice criteria, and, illustrates the challenges and opportunities to incorporate bio-physical aspects into the concept of sociotechnical systems and their transitions in the light of a more sustainable development

Interpretive Structural Model of Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry

This paper aims to analyze the relationships among the Key Performance Indicators (KPIs) for sustainable manufacturing evaluation in the cement industry. The initial KPIs have been identified and derived from literature, and then validated by industry survey. As a result, three factors dividing into a total of thirteen indicators have been proposed as the KPIs for sustainable manufacturing evaluation in cement industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs. The results show the indicators of economic factor are regarded as the basic indicator, while the indicators of environmental factor are indicated to be the leading indicator. Of those indicators, raw material substitution is regarded as the most influencing indicator. The ISM model can aid the cement companies by providing a better insight in evaluating sustainable manufacturing performance

Interpretive Structural Model of Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry

This paper aims to analyze the relationships among the Key Performance Indicators (KPIs) for sustainable manufacturing evaluation in the cement industry. The initial KPIs have been identified and derived from literature, and then validated by industry survey. As a result, three factors dividing into a total of thirteen indicators have been proposed as the KPIs for sustainable manufacturing evaluation in cement industry. Interpretive structural modeling (ISM) methodology is applied to develop a network structure model of the KPIs. The results show the indicators of economic factor are regarded as the basic indicator, while the indicators of environmental factor are indicated to be the leading indicator. Of those indicators, raw material substitution is regarded as the most influencing indicator. The ISM model can aid the cement companies by providing a better insight in evaluating sustainable manufacturing performance

Decision Support System for facility location problems in fleet management

Businesses that are growing by providing more services, reaching more customers or improving their business strategy, might need to create or relocate a facility location to expand the geographical coverage and improve their services. This decision is complex, and it is crucial to analyse their client locations, journeys and be aware of the factors that may affect their geographical decision. These organisations must weigh all these factors, such as security levels, taxes or costs due to the importance and impact that they can have in the short and long term business strategy. Therefore, the decision-maker needs to ensure that the location is the most profitable site according to the business scope and future perspectives. To help the businesses on this complex decision, this dissertation details the development of a Decision Support System (DSS) capable of providing facility location suggestions based on the existing journeys and the factors that the decision-maker considers more relevant to the company. The developed DSS has three main components: (1) Decision Support System; (2) Geospatial Analysis System; and (3) Facility Location Factors System. The Decision Support System is responsible for producing ordered facility location suggestions by performing the multicriteria decision analysis (MCDA) that implements the TOPSIS algorithm. The Geospatial Analysis System, through the use of the DBSCAN algorithm, is responsible for retrieving the alternatives by identifying the geospatial clusters based on the existing journeys. Lastly, the Facility Location Factors System is responsible for retrieving the criterion by gathering the data from external sources according to the chosen factors. The evaluation analysis shows that the perspective of the users about the assistance of the system by helping them choose appropriate facility location is favourable. This analysis showed that the users agree about the accuracy and the value of the facility location suggestions. The output helps the business managers to make better decisions by returning facility locations that have potential to maximise the company’s profit by reducing transportation and fuel costs and maximise the number of covered customers by expanding their territorial coverage. This project handles data provided by Fonix Telematics from their United Kingdom clients that have relevance to the study, such as a high number of assets, journeys and geographical coverage.As empresas em crescimento por via da disponibilização de mais serviços, do aumento do seu leque de clientes ou da melhoria da sua estratégia, podem pretender criar ou realocar um centro de operações de modo a expandir a sua cobertura geográfica e, consequentemente, melhorar os seus serviços. Esta decisão é complexa e é fundamental analisar vários aspetos, assim como, a localização dos seus clientes, as viagens recorrentes e, acima de tudo, estar consciente dos fatores que podem afetar a sua decisão geográfica. As organizações devem pesar todos esses fatores, assim como níveis de segurança, impostos ou custos, devido à importância e ao impacto que podem ter na estratégia da empresa a curto e a longo prazo. Portanto, o decisor necessita de garantir que o local é rentável e que capta o âmbito do negócio e as perspetivas futuras. De modo a auxiliar as empresas nesta complexa decisão, esta dissertação detalha o processo de desenvolvimento de um Sistema de Apoio à Decisão (SAD) capaz de fornecer um conjunto de sugestões com os locais mais indicados para a criação de um centro de operações com base nas viagens efetuadas e nos fatores que o decisor considera mais relevantes para a organização. O SAD desenvolvido possui três componentes: (1) Decision Support System; (2) Geospatial Analysis System; e (3) Facility Location Factors System. O Decision Support System é responsável por produzir as sugestões geoespaciais, através da Análise de Decisão Multicritério (MCDA) que por sua vez implementa o algoritmo TOPSIS. O Geospatial Analysis System, através da utilização do algoritmo DBSCAN, é responsável por retornar as alternativas através da identificação dos clusters geográficos com base nas viagens existentes. Por último, o Facility Location Factors System é responsável por retornar os critérios, que são compostos por dados recolhidos através de fontes externas de acordo com os fatores previamente selecionados. A avaliação da solução demonstra que a perspetiva dos utilizadores sobre o sistema é positiva e que, de facto, os auxilia na decisão do local mais indicado para as suas instalações. A análise indica ainda que os utilizadores estão de acordo com a precisão e com locais sugeridos para os centros de operações. Estas sugestões auxiliam os decisores a tomarem decisões mais sustentadas, visto que os locais sugeridos possuem potencial para maximizar a rentabilidade da empresa, reduzir os custos de transporte e combustível, assim como maximizar a cobertura de clientes através do posicionamento geográfico. Este trabalho utiliza dados de clientes da Fonix Telematics que atuam no Reino Unido e que possuem relevância para o estudo, como um número significativo de veículos, viagens e cobertura geográfica