A new model that generates Lotka's law

  • Authors:

  • John C. Huber

  • Affiliations:

  • Institute for Invention and Innovation, Austin, TX

  • Venue:
  • Journal of the American Society for Information Science and Technology
  • Year:
  • 2002

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Abstract

In this paper, we develop a new model for a process that generates Lotka's Law. We show that four relatively mild assumptions create a process that fits five different informetric distributions: rate of production, career duration, randomness, and Poisson distribution over time, as well as Lotka's Law. By simulation, we obtain good fits to three empirical samples that exhibit the extreme range of the observed parameters. The overall error is 7% or less. An advantage of this model is that the parameters can be linked to observable human factors. That is, the model is not merely descriptive, but also provides insight into the causes of differences between samples. Furthermore, the differences can be tested with powerful statistical tools.