Foresight exercises as a tool for decision-making: the example of two case studies in health

Based on the report for the unit “Foresight Methods Analysis” of the PhD programme on Technology Assessment at the Universidade Nova de Lisboa, under the supervision of Prof. Dr. António B. Moniz

Decision-making process of Nova Executivos’ students

Field lab: Consumer insights

Importance of decision-making in a purchasing context – DPS Case Study

This work project has the objective of exploring the importance of making good decisions on supplier selection, so that the purchasing department can contribute to the success of a company. For that it is presented a short bibliography review of the latest insights that were found relevant, on the subjects of purchasing, technology, outsourcing, supplier selection and decision-making techniques. For a better understating on how to deal with a decision-making situation, a case study is also presented: Digital Printing Solutions (DPS) is a Portuguese company that provides complete and integrated printing solutions and has been planning to contract a software supplier. DPS has no formal supplier-selection model and it has to choose between 2 suppliers. The case study was solved using the M-MACBETH software. I have found that complex decisions-making situations can be easily overcome by using the M-MACBETH decision model. Moreover, the usage of a model, instead of decision that follows no formal procedure, provides the decision maker with insights that can be useful to negotiate with the supplier.

How to improve consumer decision skills in children? A case study of an intervention with institutionalized children

The aim of this study is to assess the institutionalized children’s skills as consumers but also to assess how we can improve their knowledge through an intervention. The sample was composed of two subgroups (38 institutionalized children and 36 non-institutionalized children). In order to assess children’s knowledge, a questionnaire and an interview were used. The method used as intervention was a 30-minute class. Results suggested that institutionalized children have lower levels of knowledge regarding consumption-related practices and lower levels of accuracy at estimating prices than non-institutionalized children. However, results also showed that the attitudes of institutionalized children towards advertising and making decisions based on price/quantity evaluation or based on the use of the same strategy in different situations are not significantly different from the non-institutionalized children. Regarding the intervention, it was possible to conclude that one class is not the best method to improve children’s knowledge. Institutionalized children need a longer and more practical intervention.

Challenges of converting nonprofit in for-profit-reasons decision making and key success factores of a conversion

Due to external constraints (opposed by the market and legal system) and internal changes nonprofit organizations have been converting to for-profit entities combining commercial revenue and social value creation. To create an understanding of the conversion process considering its challenges, the reasons, the decision-making process and key success factors of a conversion are examined. Therefore, a two-step research procedure is used combining literature research and a multiple case study approach based on expert interviews with known companies. The outcome is a helpful guideline (including a decision matrix) for social entrepreneurs that might face a conversion.

The firm delocalization decision

In the current paper, the determinants of firm international relocation decision in twenty-six European countries during the period 2004-2014 are analyzed. We demonstrate, at light of three different but complementary theories that neoclassical, behavioural and institutional „push‟ factors have an impact in a firm decision-making process. Findings support that firm size, access to a global network, foreign capital, and negative internal growth in the workforce induce firm relocation. On the other hand, the degree of sunk assets has a negative effect on the probability of relocation. Delocalization decisions are also sector-dependent with low-tech manufacturing firms paying high salaries relocating abroad with a greater likelihood.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Essays on bounded rationality: Individual decision and strategic interaction

Economics is a social science which, therefore, focuses on people and on the decisions they make, be it in an individual context, or in group situations. It studies human choices, in face of needs to be fulfilled, and a limited amount of resources to fulfill them. For a long time, there was a convergence between the normative and positive views of human behavior, in that the ideal and predicted decisions of agents in economic models were entangled in one single concept. That is, it was assumed that the best that could be done in each situation was exactly the choice that would prevail. Or, at least, that the facts that economics needed to explain could be understood in the light of models in which individual agents act as if they are able to make ideal decisions. However, in the last decades, the complexity of the environment in which economic decisions are made and the limits on the ability of agents to deal with it have been recognized, and incorporated into models of decision making in what came to be known as the bounded rationality paradigm. This was triggered by the incapacity of the unboundedly rationality paradigm to explain observed phenomena and behavior. This thesis contributes to the literature in three different ways. Chapter 1 is a survey on bounded rationality, which gathers and organizes the contributions to the field since Simon (1955) first recognized the necessity to account for the limits on human rationality. The focus of the survey is on theoretical work rather than the experimental literature which presents evidence of actual behavior that differs from what classic rationality predicts. The general framework is as follows. Given a set of exogenous variables, the economic agent needs to choose an element from the choice set that is avail- able to him, in order to optimize the expected value of an objective function (assuming his preferences are representable by such a function). If this problem is too complex for the agent to deal with, one or more of its elements is simplified. Each bounded rationality theory is categorized according to the most relevant element it simplifes. Chapter 2 proposes a novel theory of bounded rationality. Much in the same fashion as Conlisk (1980) and Gabaix (2014), we assume that thinking is costly in the sense that agents have to pay a cost for performing mental operations. In our model, if they choose not to think, such cost is avoided, but they are left with a single alternative, labeled the default choice. We exemplify the idea with a very simple model of consumer choice and identify the concept of isofin curves, i.e., sets of default choices which generate the same utility net of thinking cost. Then, we apply the idea to a linear symmetric Cournot duopoly, in which the default choice can be interpreted as the most natural quantity to be produced in the market. We find that, as the thinking cost increases, the number of firms thinking in equilibrium decreases. More interestingly, for intermediate levels of thinking cost, an equilibrium in which one of the firms chooses the default quantity and the other best responds to it exists, generating asymmetric choices in a symmetric model. Our model is able to explain well-known regularities identified in the Cournot experimental literature, such as the adoption of different strategies by players (Huck et al. , 1999), the inter temporal rigidity of choices (Bosch-Dom enech & Vriend, 2003) and the dispersion of quantities in the context of di cult decision making (Bosch-Dom enech & Vriend, 2003). Chapter 3 applies a model of bounded rationality in a game-theoretic set- ting to the well-known turnout paradox in large elections, pivotal probabilities vanish very quickly and no one should vote, in sharp contrast with the ob- served high levels of turnout. Inspired by the concept of rhizomatic thinking, introduced by Bravo-Furtado & Côrte-Real (2009a), we assume that each per- son is self-delusional in the sense that, when making a decision, she believes that a fraction of the people who support the same party decides alike, even if no communication is established between them. This kind of belief simplifies the decision of the agent, as it reduces the number of players he believes to be playing against { it is thus a bounded rationality approach. Studying a two-party first-past-the-post election with a continuum of self-delusional agents, we show that the turnout rate is positive in all the possible equilibria, and that it can be as high as 100%. The game displays multiple equilibria, at least one of which entails a victory of the bigger party. The smaller one may also win, provided its relative size is not too small; more self-delusional voters in the minority party decreases this threshold size. Our model is able to explain some empirical facts, such as the possibility that a close election leads to low turnout (Geys, 2006), a lower margin of victory when turnout is higher (Geys, 2006) and high turnout rates favoring the minority (Bernhagen & Marsh, 1997).

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

Analysis of a controversial decision process: the case of the pumped hydro storage power plant Atdorf in Germany

Based on the report for the unit “Métodos Interactivos de Participação e Decisão A” (Interactive methods of participation and decision A), coordinated by Prof. Lia Maldonado Teles de Vasconcelos and Prof. Nuno Miguel Ribeiro Videira Costa. This unit was provided for the PhD Program in Technology Assessment in 2015/2016.

A decision- theoretic model for M&A sale processes

A Work Project, presented as part of the requirements for the Award of a Masters Double Degree in Economics and International Business from the NOVA – School of Business and Economics and Insper Instituto de Ensino e Pesquisa

Learning domain-specific sentiment lexicons with applications to recommender systems

Search is now going beyond looking for factual information, and people wish to search for the opinions of others to help them in their own decision-making. Sentiment expressions or opinion expressions are used by users to express their opinion and embody important pieces of information, particularly in online commerce. The main problem that the present dissertation addresses is how to model text to find meaningful words that express a sentiment. In this context, I investigate the viability of automatically generating a sentiment lexicon for opinion retrieval and sentiment classification applications. For this research objective we propose to capture sentiment words that are derived from online users’ reviews. In this approach, we tackle a major challenge in sentiment analysis which is the detection of words that express subjective preference and domain-specific sentiment words such as jargon. To this aim we present a fully generative method that automatically learns a domain-specific lexicon and is fully independent of external sources. Sentiment lexicons can be applied in a broad set of applications, however popular recommendation algorithms have somehow been disconnected from sentiment analysis. Therefore, we present a study that explores the viability of applying sentiment analysis techniques to infer ratings in a recommendation algorithm. Furthermore, entities’ reputation is intrinsically associated with sentiment words that have a positive or negative relation with those entities. Hence, is provided a study that observes the viability of using a domain-specific lexicon to compute entities reputation. Finally, a recommendation system algorithm is improved with the use of sentiment-based ratings and entities reputation.

Exploring the consumer decision journey and online shoping experience through an emotional prespective

Traditional consumer decision-making models have long used quantitative research to address a link between emotional and rational behavior. However, little qualitative research has been conducted in the area of online shopping as an end-to-end experience. This study aims to provide a detailed phenomenological account of consumers’ online shopping experience and extend Mckinsey & Companys’s consumer decision journey model from an emotional perspective. Six semi-structured interviews and a focus group of nine people are analyzed using Interpretive Phenomenology Analysis and five superordinate themes emerged from the results: emotional experience, empathy and encouragement, in relation to brand preference, emotional encounters in relation to consumer satisfaction and emotional exchange and relationship with a company or brand. A model interrelating these themes is then introduced to visually represent the emotional essence of a large online purchase. This study promises to be applicable as a descriptive, and perhaps, better predictive report for understanding the complex consumer decision-making process as it relates to online consumer behavior. Future research topics are also identified.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.