http://hdl.handle.net/10256/16289 2025-08-13T04:59:08Z 2025-08-13T04:59:08Z Ferrer Rosell, Berta Martín Fuentes, Eva Vives Mestres, Marina Coenders, Germà http://hdl.handle.net/10256/26652 2025-04-04T09:38:03Z 2021-10-22T00:00:00Z

Chapter 3: When size does not matter: compositional data analysis in marketing research Ferrer Rosell, Berta; Martín Fuentes, Eva; Vives Mestres, Marina; Coenders, Germà Compositional Data analysis (CoDa) is the standard statistical methodology when data contain information about the relative importance of parts of a whole. Many research questions in marketing have to do with distribution of a whole (e.g., market share, product portfolio, spending distribution), or with relative importance (e.g., advertising content or style, preferred product attributes). CoDa solves the statistical problems that arise when treating compositional data with classical statistical methods and focuses on research questions about relative importance. In a costumer opinion platform the dominant types of reviews matter more than the number of reviews. We show how to apply the most common CoDa tools (visualization and linear models), by means of real data from an electronic word-of-mouth platform: are hotel characteristics affecting the share of valuation categories (e.g., from terrible to excellent reviews), or is it related to other compositions (e.g., by type of travelers)?

2021-10-22T00:00:00Z Saus Sala, Elisabet Farreras Noguer, M. Àngels Arimany Serrat, Núria Coenders, Germà http://hdl.handle.net/10256/26651 2025-04-30T05:54:39Z 2021-01-01T00:00:00Z

Compositional DuPont Analysis. A Visual Tool for Strategic Financial Performance Assessment Saus Sala, Elisabet; Farreras Noguer, M. Àngels; Arimany Serrat, Núria; Coenders, Germà DuPont analysis is a classical tool for assessing the determinants of financial performance of firms. It is based on financial ratios comparing revenues with costs (the so-called margin ratio), revenues with assets (turnover ratio), and debt with assets (leverage ratio). DuPont analysis thus focuses on comparing accounting values in relative terms and lends itself naturally to compositional analysis. In this chapter, we show how to graphically display firms according to margin, turnover and leverage by means of a standard compositional biplot, and how to cluster firms into strategic groups by means of k-means compositional cluster analysis. Practitioners who prefer to stick to the classic definitions of industry or cluster-level financial ratios can compute them with the usual formulae from the centre of the composition, i.e. from the industry or cluster geometric averages rather than the totals or arithmetic averages commonly used. An illustration is presented with farm-tourism firms

2021-01-01T00:00:00Z Ferrer Rosell, Berta Coenders, Germà Martín Fuentes, Eva http://hdl.handle.net/10256/26650 2025-04-30T05:53:48Z 2022-01-01T00:00:00Z

Compositional Data Analysis in E-Tourism Research Ferrer Rosell, Berta; Coenders, Germà; Martín Fuentes, Eva Compositional Data (CoDa) contain information about the relative importance of parts of a whole, which the researcher deems more interesting than overall size or volume. In web mining, for instance, the relative frequency of a term is normally given more importance than absolute frequency, which mostly tells about web size, in other words, the sheer volume of online content. Many research questions in e-tourism are either related to the distribution of a whole or relative importance: How do the most salient contents in hotel Facebook accounts relate to hotel characteristics? What are the dominant topics on TripAdvisor comments about fish freshness in seafood restaurants? How does the relative popularity of search terms in Google relate to destination market share? In CoDa, most of the basic statistical notions, such as center, variation, association, and distance, are flawed unless they are re-expressed by means of logarithms of ratios. The appeal of log-ratios is that once they are computed, standard statistical methods can be used. On the other hand, since one part can only increase in relative terms if some other(s) decrease, statistics need to be multivariate. This chapter uses an example based on TripAdvisor hotel reviews from one of the most visited cities worldwide, Barcelona, focusing on what users complain about, to illustrate the main multivariate exploratory and descriptive tools in CoDa, including imputation of zeros prior to computing the log-ratios, multivariate outlier detection, principal component analysis, cluster analysis, and multivariate data visualization tools. The use of CoDaPack, a popular CoDa freeware, is described in a step-by-step fashion

2022-01-01T00:00:00Z Gutiérrez del Moral, María Jesús http://hdl.handle.net/10256/23981 2024-01-19T07:42:07Z 2024-01-01T00:00:00Z

Mujer, discriminación, odio y creencias. Análisis del marco jurídico de Naciones Unidas, Consejo de Europa y Unión Europea Gutiérrez del Moral, María Jesús Análisis del marco jurídico de Naciones Unidas, Consejo de Europa y Unión Europea sobre discriminación y odio contra la mujer por motivos de sexo, género y de religión o creencias; Anàlisi del marc jurídic de Nacions Unides, Consell d'Europa i Unió Europea sobre discriminació i odi contra la dona per motius de sexe, gènere i religió o creences

2024-01-01T00:00:00Z