1,721,084 research outputs found
Measuring spatial dispersion: an experimental test on the M‐Index
Full text linkDespite representing a very accurate method for assessing spatial distribution, Marcon and Puech's M has been insufficiently exploited so far, most likely because its computation relies on pairing every point of interest (i.e., firms, plants) with every other point within the area under analysis. Such a figure rapidly grows to unmanageable levels when said area is larger than a neighborhood or when every industry is taken into account. Consequently, practical applications of M have been exclusively experimental and circumscribed to very limited areas or to a handful of industries. This seems much regrettable since M provides many advantages compared to conventional measures of spatial distribution and also to alternative distance measures. In this article, we assess the reliability of using small administrative units instead of exact postal addresses for the localization of plants, in order to reduce M's computational burden. Working with a dataset that provides the location, the specific industry and the number of employees for every single plant/establishment in Italy for both manufacturing and services, we can also draw a preliminary but certainly interesting picture of Sardinia's economic geography and its development through the Great Recession toughest years between 2007 and 2012
Measuring Spatial Dispersion: an experimental test on the M-index
Full text linkIn this paper, we assess the viability of a geographic approximation aimed to reduce the computational intensity necessary to measure spatial agglomeration with Marcon & Puech’s (2017) M index. Indeed, despite representing a potentially very accurate way of measuring spatial distribution, M has not been sufficiently exploited so far because its computation needs crossing every point (i.e. firms, plants) with each other within the area under analysis: such a figure rapidly grows to unmanageable levels when the area is larger than a neighborhood or when every industry is taken into account. Consequently, practical applications of M have been exclusively experimental and circumscribed to very limited areas or to a handful of sectors. In our opinion, this is much regrettable since M provides many advantages compared to conventional measures of spatial distribution and also to other distance measures. In order to verify whether a slight geographic approximation is tolerable – which would be consistent with Marcon & Puech’s (2017, p. 30) assumption that “cumulative functions are insensitive to errors at smaller scales than the distance they consider” - we compute both actual M (with no approximation whatsoever) and approximate M for every industry in Sardinia. Our aim is to compare the results obtained when plants are located exactly where they are with those obtained when plants’ positions are approximated to the centroid of the municipality where they are located. We rely on a comprehensive dataset that allows us to identify the location, the specific industry and the number of employees for every single plant, and not only for firms as a whole. Our dataset’s scope is not restricted to manufacturing, as it is often the case, but covers every area of activity, ranging from construction to transports and from retailers to other service industries. Moreover, we did not considered distance between approximated positions as the crow flies, but we relied on actual street distance and travel time between them: in the frequent case of orographically dishomogenous territories, it might be the case that such a measurement more accurately reflects the actual distance between establishment, than theoretical flying distance between actual locations. If our approximation in the location of plants is positively outweighed by the great accuracy of M in operationalizing detailed geographic and economic information, then such an index could really be exploited for assessing agglomeration and dispersion patterns across space and along time, especially when much information is available, as it is ever more often the case
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
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
Gathering round Big Tech: how the market for acquisitions hurts left-behind places
No full textSmall businesses within the digital sector are spread across the USA. However, a significant number of promising small businesses concentrate in major technology hubs, either initially or through relocation. This phenomenon can be attributed to the influential role played by localized markets for financing and acquisition, which is, in turn, driven by the dominant market positions held by major digital platforms. Our research demonstrates a clear pattern of localized acquisition markets, particularly in sectors frequently targeted by the seven largest American digital giants-Amazon, Alphabet (Google), Apple, Microsoft, Meta (Facebook), Oracle, and Adobe, collectively known as 'Big Tech'. This localization trend has become more pronounced between 2000 and 2020. Our analysis indicates that the gravitational pull of these acquisition markets poses challenges to local initiatives aimed at fostering digital businesses. These efforts would be more successful if measures were taken to limit the market influence of digital platforms
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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