1,721,167 research outputs found
On the determination of the own and competitive effects of different platforms and content on market shares
Although the attention of academic literature about the relationship between social media and
brand sales has grown, literature is still lacking analyses on competitive effects amongst
brands. Additionally, effects of firm-generated content (FGC) is often generalized to the
volume of posts, which combines the effects of different types of content and use of different
platforms. We adopte a differential effects Market Share Attraction (MSA) model to capture
different effects across brands allowing also for different effects across two social media
platforms. We use a unique dataset covering 4 yoghurt brands in the Italian market spanning
over 3 years, for which we focus on the social media posts of the brands (i.e., FGC) on both
Twitter and Facebook, while controlling for the engagement (i.e., user-generated content
derived from FGC) these posts create, as well as for traditional marketing-mix variables. We
extend this analysis by looking at differences in effectiveness based on the type of content of
the post (Informational, Emotional, and Activating), and consider whether effectiveness
changed over time by employing a Dynamic Linear Model version of the MSA. Our
preliminary findings indicate that different brands use different strategies over time and that
the content of the message might influence the effectiveness in terms of market shares
Knowledge Generation in Marketing
In the present chapter, we briefly discuss how knowledge generation in marketing can be accomplished. In particular, we argue that generalizations offered by meta-analyses are very useful for managers in their decision making. To support this argument, we perform an empirical study on subjective estimations of price elasticities, advertising elasticities, and price promotion elasticities, showing that actual and future managers (i.e., master and PhD students) usually underestimate the effects of price changes, overestimate the impact of advertising, and heavily underestimate that of price promotions. We also demonstrate that subjective estimations improve after being confronted with the outcomes of meta-analyses
Going Beyond Counting First Authors in Author Co-citation Analysis
The 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
“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
We 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
We 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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