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Big deal and long tail: e‐journal usage and subscriptions

2012; Emerald Publishing Limited; Volume: 61; Issue: 7 Linguagem: Inglês

10.1108/00242531211288245

1758-793X

Joachim Schöpfel, Claire Leduc,

scientometrics and bibliometrics research

Purpose This paper is aimed primarily at academic library managers and acquisition librarians. By analogy to Pareto studying the relationship between clients and turnover, the paper will study subscriptions to e‐journals and usage statistics. The aim is to evaluate the long tail of usage statistics and to compare it with subscription lists of individually selected titles and packages (big deals). Design/methodology/approach The paper exploits usage statistics and subscription data from a national usage study of an academic publisher. Data are from 2010. Findings Usage statistics are partly shaped by the long tail effect. Individual subscriptions of journals are more selective than big deals, and trend towards a traditional retail curve. Unlike subscriptions through packages, usage and individual subscriptions can be related by a similar inclination. But both types of subscriptions fail to predict the popularity of a title in its usage. Research limitations/implications The paper uses data from a national usage study and tries to identify global trends. Thus, it does not distinguish between customer categories, disciplines or activity domains. Practical implications The paper considers the opportunity provided by big deal for acquisition policy. Ready‐made big deals sometimes appear as an unbounded and excessive supply, not suited to true and sufficient users' needs, but on the other hand, selective acquisition policy cannot completely anticipate online usage behaviour. Originality/value Only a few studies distinguish Pareto from long tail distributions in usage statistics, and there is little empirical evidence on the impact of selected subscriptions versus big deals on these statistics.