Explaining article influence: capturing article citability and its dynamic effects

Shibo Li, Eugene Sivadas, Mark S. Johnson

Journal of the Academy of Marketing Science · 2015 · Volume 43 · Issue 1

Abstract

Researchers from diverse disciplines have examined the many factors that contribute to the influence of published research papers. Such influence dynamics are in essence a marketing of science issue. In this paper, we propose that in addition to known established, overt drivers of influence such as journal, article, author, and Matthew effects, a latent factor “citability” influences the eventual impact of a paper. Citability is a mid-range latent variable that captures the changing relationship of an article to a field. Our analysis using a discretized Tobit model with hidden Markov processes suggests that there are two states of citability, and these dynamic states determine eventual influence of a paper. Prior research in marketing has relied on models where the various effects such as author and journal effects are deemed static. Unlike ours, these models fail to capture the continuously evolving impact dynamics of a paper and the differential effect of the various drivers that depend on the latent state a paper is in at any given point of time. Our model also captures the impact of uncitedness, which other models fail to do. Our model is estimated using articles published in seven leading marketing journals during the years 1996–2003. Findings and implications are discussed.

Keywords

Citation, Citability, Matthew effect, Uncitedness, Scientometrics, Hidden Markov model, Tobit

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