A conceptual model to approach the scaling process of social entreprises: The case of Cozinha com Alma

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

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Neuronal adaptation effects in decision making

Recently, there has been an increased interest on the neural mechanisms underlying perceptual decision making. However, the effect of neuronal adaptation in this context has not yet been studied. We begin our study by investigating how adaptation can bias perceptual decisions. We considered behavioral data from an experiment on high-level adaptation-related aftereffects in a perceptual decision task with ambiguous stimuli on humans. To understand the driving force behind the perceptual decision process, a biologically inspired cortical network model was used. Two theoretical scenarios arose for explaining the perceptual switch from the category of the adaptor stimulus to the opposite, nonadapted one. One is noise-driven transition due to the probabilistic spike times of neurons and the other is adaptation-driven transition due to afterhyperpolarization currents. With increasing levels of neural adaptation, the system shifts from a noise-driven to an adaptation-driven modus. The behavioral results show that the underlying model is not just a bistable model, as usual in the decision-making modeling literature, but that neuronal adaptation is high and therefore the working point of the model is in the oscillatory regime. Using the same model parameters, we studied the effect of neural adaptation in a perceptual decision-making task where the same ambiguous stimulus was presented with and without a preceding adaptor stimulus. We find that for different levels of sensory evidence favoring one of the two interpretations of the ambiguous stimulus, higher levels of neural adaptation lead to quicker decisions contributing to a speed–accuracy trade off.

A new aggregation method for strategic decision making and its application in assignment theory

A new aggregation method for decision making is presented by using induced aggregation operators and the index of maximum and minimum level. Its main advantage is that it can assess complex reordering processes in the aggregation that represent complex attitudinal characters of the decision maker such as psychological or personal factors. A wide range of properties and particular cases of this new approach are studied. A further generalization by using hybrid averages and immediate weights is also presented. The key issue in this approach against the previous model is that we can use the weighted average and the ordered weighted average in the same formulation. Thus, we are able to consider the subjective attitude and the degree of optimism of the decision maker in the decision process. The paper ends with an application in a decision making problem based on the use of the assignment theory.

Decision-making with distance measures and inducedaggregation operators

[spa] Se presenta un nuevo modelo para la toma de decisiones basado en el uso de medidas de distancia y de operadores de agregación inducidos. Se introduce la distancia media ponderada ordenada inducida (IOWAD). Es un nuevo operador de agregación que extiende el operador OWA a través del uso de distancias y un proceso de reordenación de los argumentos basado en variables de ordenación inducidas. La principal ventaja el operador IOWAD es la posibilidad de utilizar una familia parametrizada de operadores de agregación entre la distancia individual máxima y la mínima. Se estudian algunas de sus principales propiedades y algunos casos particulares. Se desarrolla un ejemplo numérico en un problema de toma de decisiones sobre selección de inversiones. Se observa que la principal ventaja de este modelo en la toma de decisiones es la posibilidad de mostrar una visión más completa del proceso, de forma que el decisor está capacitado para seleccionar la alternativa que está más cerca de sus intereses.

Decision-making with distance measures and inducedaggregation operators

[spa] Se presenta un nuevo modelo para la toma de decisiones basado en el uso de medidas de distancia y de operadores de agregación inducidos. Se introduce la distancia media ponderada ordenada inducida (IOWAD). Es un nuevo operador de agregación que extiende el operador OWA a través del uso de distancias y un proceso de reordenación de los argumentos basado en variables de ordenación inducidas. La principal ventaja el operador IOWAD es la posibilidad de utilizar una familia parametrizada de operadores de agregación entre la distancia individual máxima y la mínima. Se estudian algunas de sus principales propiedades y algunos casos particulares. Se desarrolla un ejemplo numérico en un problema de toma de decisiones sobre selección de inversiones. Se observa que la principal ventaja de este modelo en la toma de decisiones es la posibilidad de mostrar una visión más completa del proceso, de forma que el decisor está capacitado para seleccionar la alternativa que está más cerca de sus intereses.

A method for decision making with the OWA operator

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

Points to consider for prioritizing clinical genetic testing services: a European consensus process oriented at accountability for reasonableness.

Given the cost constraints of the European health-care systems, criteria are needed to decide which genetic services to fund from the public budgets, if not all can be covered. To ensure that high-priority services are available equitably within and across the European countries, a shared set of prioritization criteria would be desirable. A decision process following the accountability for reasonableness framework was undertaken, including a multidisciplinary EuroGentest/PPPC-ESHG workshop to develop shared prioritization criteria. Resources are currently too limited to fund all the beneficial genetic testing services available in the next decade. Ethically and economically reflected prioritization criteria are needed. Prioritization should be based on considerations of medical benefit, health need and costs. Medical benefit includes evidence of benefit in terms of clinical benefit, benefit of information for important life decisions, benefit for other people apart from the person tested and the patient-specific likelihood of being affected by the condition tested for. It may be subject to a finite time window. Health need includes the severity of the condition tested for and its progression at the time of testing. Further discussion and better evidence is needed before clearly defined recommendations can be made or a prioritization algorithm proposed. To our knowledge, this is the first time a clinical society has initiated a decision process about health-care prioritization on a European level, following the principles of accountability for reasonableness. We provide points to consider to stimulate this debate across the EU and to serve as a reference for improving patient management.

A method for decision making with the OWA operator

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a new aggregation operator that we call the ordered weighted averaging index of maximum and minimum level (OWAIMAM) operator. The main advantage is that it provides a parameterized family of aggregation operators between the minimum and the maximum and a wide range of special cases. Then, the decision maker may take decisions according to his degree of optimism and considering ideals in the decision process. A further extension of this approach is presented by using hybrid averages and Choquet integrals. We also develop an application of the new approach in a multi-person decision-making problem regarding the selection of strategies.

The importance of package design to Japanese consumers: The role of visual and informational elements of package design in decision making

The importance of package design as a marketing tool is growing as the competition in retail environment increases. However, there is a lack of studies on how each element of package design affects consumer decisions in different countries. The objective of this thesis is to study the role of package design to Japanese consumers. The research was conducted through an experiment with a sample of 37 Japanese female participants. They were divided into two groups and were given different tasks: one group had to choose a chocolate for themselves, and the other for a group of friends. The participants were presented with 15 different Finnish chocolate boxes to choose from. The qualitative data was gathered through observation and semi-structured interviews. In addition, data from questionnaires was quantified and all the data was triangulated. The empirical results suggest that visual elements strongly affect the decision making of Japanese consumers. Image was the most important element which acted as both, a visual and an informational aspect in the experiment. Informational elements on the other hand have little effect, especially when the context is written in a foreign language. However, informational elements affected participants who were choosing chocolates for a group of friends. A unique finding was the importance of kawaii (cuteness) to Japanese consumers.

The psychophysics of decision making in a two-direction random dot motion target selection task

La tâche de kinématogramme de points aléatoires est utilisée avec le paradigme de choix forcé entre deux alternatives pour étudier les prises de décisions perceptuelles. Les modèles décisionnels supposent que les indices de mouvement pour les deux alternatives sont encodés dans le cerveau. Ainsi, la différence entre ces deux signaux est accumulée jusqu’à un seuil décisionnel. Cependant, aucune étude à ce jour n’a testé cette hypothèse avec des stimuli contenant des mouvements opposés. Ce mémoire présente les résultats de deux expériences utilisant deux nouveaux stimuli avec des indices de mouvement concurrentiels. Parmi une variété de combinaisons d’indices concurrentiels, la performance des sujets dépend de la différence nette entre les deux signaux opposés. De plus, les sujets obtiennent une performance similaire avec les deux types de stimuli. Ces résultats supportent un modèle décisionnel basé sur l’accumulation des indices de mouvement net et suggèrent que le processus décisionnel peut intégrer les signaux de mouvement à partir d’une grande gamme de directions pour obtenir un percept global de mouvement.

Contact Sensing: A Sequential Decision Approach to Sensing Manipulation Contact

This paper describes a new statistical, model-based approach to building a contact state observer. The observer uses measurements of the contact force and position, and prior information about the task encoded in a graph, to determine the current location of the robot in the task configuration space. Each node represents what the measurements will look like in a small region of configuration space by storing a predictive, statistical, measurement model. This approach assumes that the measurements are statistically block independent conditioned on knowledge of the model, which is a fairly good model of the actual process. Arcs in the graph represent possible transitions between models. Beam Viterbi search is used to match measurement history against possible paths through the model graph in order to estimate the most likely path for the robot. The resulting approach provides a new decision process that can be use as an observer for event driven manipulation programming. The decision procedure is significantly more robust than simple threshold decisions because the measurement history is used to make decisions. The approach can be used to enhance the capabilities of autonomous assembly machines and in quality control applications.

Reinforcement Learning by Policy Search

One objective of artificial intelligence is to model the behavior of an intelligent agent interacting with its environment. The environment's transformations can be modeled as a Markov chain, whose state is partially observable to the agent and affected by its actions; such processes are known as partially observable Markov decision processes (POMDPs). While the environment's dynamics are assumed to obey certain rules, the agent does not know them and must learn. In this dissertation we focus on the agent's adaptation as captured by the reinforcement learning framework. This means learning a policy---a mapping of observations into actions---based on feedback from the environment. The learning can be viewed as browsing a set of policies while evaluating them by trial through interaction with the environment. The set of policies is constrained by the architecture of the agent's controller. POMDPs require a controller to have a memory. We investigate controllers with memory, including controllers with external memory, finite state controllers and distributed controllers for multi-agent systems. For these various controllers we work out the details of the algorithms which learn by ascending the gradient of expected cumulative reinforcement. Building on statistical learning theory and experiment design theory, a policy evaluation algorithm is developed for the case of experience re-use. We address the question of sufficient experience for uniform convergence of policy evaluation and obtain sample complexity bounds for various estimators. Finally, we demonstrate the performance of the proposed algorithms on several domains, the most complex of which is simulated adaptive packet routing in a telecommunication network.

One rapidly growing market of Sweden: organic food : A qualitative study portraying some consumers’ decision to purchase organic food

In recent years there has been a significantly rising trend amongst consumers for health and environmental issues, which has resulted in greater attention for and sales of organic food. Organic food production strives to use natural resources, such as land, energy and water in a sustainable way and the products does not contain artificial fertilizers or chemical pesticides. However, organic food products are also often more expensive and less available in comparison to conventional food products. Despite this, interest for and sales of organic food products have increased around the globe, and in Sweden particularly, the increase in sales has grown largely from an international perspective. This thesis is of qualitative character and is focused on studying some consumers from the Swedish market of organic food. The purpose of this thesis is to contribute with a better understanding on the buying decision process regarding organic food purchase. To achieve this, the authors have studied some consumers that purchase organic food and have searched for patterns that could be identified in the decision process. The consumer buying decision process model has been used for portrayal of the chosen consumers’ decision to purchase organic food products. Interviews with six Swedish consumers were conducted, whereas each respondent continuously purchase organic food products. Results show that the purchase of organic food products begins with discovering an unsatisfied need state, which the consumers of this study desired to change with the purchase of organic food products. This study show how six consumers reason when passing through the stages of the buying decision process, in order to satisfy their desired need state. The authors found that the respondents feel satisfied with purchasing organic food products, which lead them in to continuously buying these products. Altogether, the findings contribute with knowledge that can come to be helpful when wanting to understand more about the consumer decision to purchase organic food.

Factors influencing consumer decision in crowdfunding

Crowdfunding é um método recente e emergente de captar dinheiro para desenvolvimento de projetos (tanto orientados a lucro ou não) sem a intermediação tradicional de instituições financeiras, liberando empreendedores de custos, regulações e burocracia associada a essa prática. Além disso, também é um método de pré-testar novos produtos com um público selecionado e entusiasmado. O objetivo dessa dissertação é entender que fatores estão influenciando a decisão do consumidor de investir em projetos. A literatura contribui com: (1) fatores intrínsecos, como desejo de patronagem; (2) fatores extrínsecos, como a apresentação do projeto; e (3) pressão social. Há ainda fatores associados com o nível atual de captação e número de investidores, assim como tipo de projeto envolvido, sendo ele de caridade ou não. Além disso, atitudes também possuem um papel em afetar a decisão de compra. Para responder a pergunta de pesquisa, uma metodologia de duas fases foi usada: uma entrevista de profundidade para capturar intenção de investir e motivação, de forma a construir um processo de decisão que englobasse todas as possibilidades descritas pela literatura. Após essa pesquisa qualitativa, uma pesquisa quantitativa foi feita para validar as informações coletadas pela fase anterior e coletar dados adicionais para gerar uma associação entre intenção de investir e comportamento. Dentre as informações geradas pela fase qualitativa, temos o fato que a maioria dos investidores tiveram como principal motivação a compra do produto sendo oferecido como se eles estivessem participando de uma pré-venda. Entretanto, essa não foi a principal razão para o investidor de caridade. Além disso, os respondentes que pré-compraram os produtos o fizeram para única razão que esses produtos satisfizeram desejos que tinham. Esses desejos variavam, sendo desde saudade de jogos antigos como resolver um problema de organização da carteira. Outra característica da pré-compra foi que eles não investiam valores simbólicos, pela razão que se o fizessem não receberiam o produto em troca. Recompensas tiveram um grande papel em atrair os respondentes para investimento em valores maiores que consideravam anteriormente. Também é verdade para o investidor em caridade, que também doou mais. A fase quantitativa confirmou as informações acima e gerou informação extra sobre as categorias de produto. Projetos de caridade e arte concentraram a maioria dos respondentes que disseram que a principal razão para investir foi basicamente ajudar a desenvolver o projeto sem demandar um produto em retorno. Entretanto, outros projetos como Música também apresentaram altos números de comportamento caridoso, possivelmente por causa do envolvimento emocional com o artista. Outras categorias apresentaram um mix de razões para investir ou enviesado a comprar o produto apenas, o que pode ser explicado pelo efeito de recompensas e pelo fato que essas categorias estão simplesmente pré-vendendo produtos. Essa pesquisa também confirmou as principais fontes usadas para conhecer mais sobre os projetos: recomendação pessoal e blogs e fóruns. Outro resultado dessa fase foi o desenvolvimento de fatores a partir de frases atitudinais que puderam explicar intenção de investir. Seis fatores foram criados: Entusiasmo (por crowdfunding), Exclusividade (compra de recompensas), Caridade (doações pequenas para ajudar o desenvolvimento do projeto), Cautela (similar à difusão de responsabilidade, isto é, espera por mais investidores para dar o primeiro passo), Intimidade (projeto foi recomendado ou há ligação emocional com o criador) e Compartilhamento (compartilhar para ajudar a trazer mais investidores para o projeto). Categorias com alto envolvimento emocional apresentaram associação com Intimidade, como música, filme e tecnologia. Dado o fato que a amostra não continha muitos entusiastas por crowdfunding, esse fator não apresentou qualquer associação com as categorias. Categorias que não entregam produtos em troca, como comida e fotografia, apresentaram altos níveis de associação com o fator caridade. Compartilhamento é altamente associado com tecnologia, dado o fato que essa categoria concentra os respondentes que são mais orientados à inovação e entusiastas sobre o produto, então precisam compartilhar e gerar boca-a-boca para ajudar a atingir a meta de investimento.