6 resultados para emotional choice

em RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal


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We examine the drivers behind the establishment mode choice of German multinational enterprises (MNEs) in the sectors of Automotive, Chemicals and Mechanical Engineering in Brazil for the years 1993-2013 using a novel sample of primary data obtained directly from German MNEs. Based on prevalent theories found in the literature, we test the most common hypotheses on our sample. Firms with high R&D activities and firms with prior market knowledge in Brazil in from of previous sales offices are more likely to enter Brazil by a Greenfield investment. We also show that it is the specific private ownership of the German so-called hidden champions that drive those specific SMEs to enter Brazil by Greenfield, a sneaking suspicion that has been made before. Finally, we show that the establishment mode choice between Brazil and the USA only deviates to a low extent, with German MNEs preferring to enter Brazil by Greenfield and the USA by M&A. Thereby, we provide valuable insights for future research in this field.

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This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.

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An infinite-horizon discrete time model with multiple size-class structures using a transition matrix is built to assess optimal harvesting schedules in the context of Non-Industrial Private Forest (NIPF) owners. Three model specifications accounting for forest income, financial return on an asset and amenity valuations are considered. Numerical simulations suggest uneven-aged forest management where a rational forest owner adapts her or his forest policy by influencing the regeneration of trees or adjusting consumption dynamics depending on subjective time preference and market return rate dynamics on the financial asset. Moreover she or he does not value significantly non-market benefits captured by amenity valuations relatively to forest income.

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In the increasingly competitive market of higher education introduced by the Bologna Declaration, understanding the decision-making of master in management students is at the center of institutional management and marketing efforts on its mission to attract prospective students in a less costly, more efficient manner. The means-end chain approach, applied to the choice of a Portuguese institution in which to pursue a master in management, points to the position in rankings and to the non-specificity of the program as the most important attributes. Additionally, results show that students with distinct demographic, household, or background characteristics choose in significantly different manners.

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Recently researchers showed that more choice is not always better. Choosing from large assortments can be overwhelming, raising expectations and decreasing overall level of consumer satisfaction. Author contributes to existing overchoice studies by using real assortment of online stores to find influence of assortment size on customer satisfaction. 90 students participated in the main experiment, where they chose a smartphone case for their friend. Results of the study show that large assortment size leads to higher expectations, higher choice difficulty and higher level of satisfaction. This research does not show overchoice presence and author suggests future studies could focus more on assortment variety and more personal characteristics of consumers, like preference uncertainty.

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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.