1,720,960 research outputs found
Neural networks in accounting: Clustering firm performance using financial reporting data
No full textThis paper considers the use of neural networks—namely self-organizing maps (SOMs)—to analyze and cluster firms’ financial performance. Applying SOMs to financial statement data is a consolidated practice; however, in this paper SOMs are used to overcome several limitations encountered in previous works on financial reporting indicators such as the small number of companies in the sample, the limited number of ratios, the homogeneity of the economic sector, and the lack of explanation and further analysis of the SOM outputs. This study uses a large financial dataset related to more than 3,000 companies belonging to every economic sector; it demonstrates that SOMs can effectively process a large dataset of heterogeneous data. Moreover, the SOM results are supported by detailed explanations of the research methodology applied, and further traditional financial analysis addresses the black box nature of the SOMs and can help professionals in the understanding and use of SOMs
Accounting e accountability per le smart city: misurare e orientare il loro contributo ai Sustainabile Development Goals
No full textIl tema della sostenibilità economica, sociale e ambientale rappresenta una priorità assoluta per il nostro
pianeta. La città può contribuire notevolmente a implementare azioni volte a migliorare la sostenibilità urbana
e a ridurre il proprio footprint ambientale, anche grazie alle azioni di smartness, già da tempo perseguite. La
smart city infatti è una strategia urbana che mira a utilizzare le tecnologie più avanzate per migliorare la qualità
della vita dei cittadini, anche mediante il perseguimento della difesa dell’ambiente. Tuttavia, ad oggi la
eterogeneità dei progetti smart e l’assenza di strumenti di misurazione delle performance hanno reso difficile
misurare il contributo delle smart city alla sostenibilità. Lo scopo del presente lavoro è quello di rivedere le
definizioni di smart city alla luce dei Sustainable Development Goals dell’ONU e suggerire un percorso di
progettazione del sistem
Smart Mobility portfolio analysis: the case of Barcelona
No full textIn this work, we explore the application of machine learning models
(MLM) to the analysis of firms’ performance. To such aim, we consider a bunch of
financial indicators on firms operating in the Information and Communication
Technology (ICT) sector, with attention to enterprises providing ICT
related-services. The rationale is to highlight the potential of MLM to exploit the
complexity of financial data, and to offer a handy way to visualize the related
information. In fact, instead of performing classical analysis, we discuss how to
apply to those indicators Self-Organizing Maps-SOMs—that are well suited to
manage high dimensional and complex datasets to extract their relevant features. It
emerges that SOMs are useful in clustering companies depending on
multi-dimensional criteria and in analysing hidden relations in companies’
performances
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Mapping Financial Performances in Italian ICT-related firms via Self-Organizing Maps
No full textIn this work, we explore the application of machine learning models
(MLM) to the analysis of firms’ performance. To such aim, we consider a bunch of
financial indicators on firms operating in the Information and Communication
Technology (ICT) sector, with attention to enterprises providing ICT
related-services. The rationale is to highlight the potential of MLM to exploit the
complexity of financial data, and to offer a handy way to visualize the related
information. In fact, instead of performing classical analysis, we discuss how to
apply to those indicators Self-Organizing Maps-SOMs—that are well suited to
manage high dimensional and complex datasets to extract their relevant features. It
emerges that SOMs are useful in clustering companies depending on
multi-dimensional criteria and in analysing hidden relations in companies’
performances
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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