New approaches for increasing the reliability of the h index research performance measurement

TL;DR

This paper proposes new methods to enhance the reliability of the h index, a widely used metric for assessing scientific research performance, by applying additional bibliometric measures.

Contribution

It introduces h2 lower, h2 upper, and sRM as complementary approaches to improve the discriminative reliability of the h index.

Findings

h2 lower, h2 upper, and sRM improve reliability

Applied to molecular biology data set

Demonstrates enhanced discrimination of research performance

Abstract

In the year 2005 Jorge Hirsch introduced the h index for quantifying the research output of scientists. Today, the h index is a widely accepted indicator of research performance. The h index has been criticized for its insufficient reliability - the ability to discriminate reliably between meaningful amounts of research performance. Taking as an example an extensive data set with bibliometric data on scientists working in the field of molecular biology, we compute h2 lower, h2 upper, and sRM values and present them as complementary approaches that improve the reliability of the h index research performance measurement.