Academic and demographic characteristics as predictors of scholarly productivity in the Israeli academia

Weinberger, Maor; Zhitomirsky-Geffet, Maayan; Bouhnik, Dan

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https://hdl.handle.net/2142/106541 Copy

Description

Title

Academic and demographic characteristics as predictors of scholarly productivity in the Israeli academia

Author(s)

• Weinberger, Maor
• Zhitomirsky-Geffet, Maayan
• Bouhnik, Dan

Issue Date

2020-03-23

Keyword(s)

• Scholarly productivity
• Academic productivity
• Researcher evaluation
• Gender
• Seniority
• Faculty
• Bibliometrics
• Scientometrics
• H-index

Date of Ingest

2020-03-17T23:28:44Z

Abstract

In this study we investigated the influence of various researchers' characteristics, such as faculty, department, gender and seniority, on their scholarly productivity. A quantitative research was conducted with 601 professors with tenure from two leading Israeli universities, in order to construct a comprehensive model for assessment and prediction of the scholarly productivity. We found a great variability in seniority and productivity of the examined professors. In addition, a multivariate linear regression showed significant differences between the examined faculties. The faculty of Life Sciences was the most scholarly productive, while Social Sciences was the least scholarly productive faculty. Overall, there was a positive influence of academic seniority on scholarly productivity, however, scholars with over twenty years of seniority appeared to be less productive than those with the middle level seniority. One of the most interesting findings was gender differences of the scholarly productivity distribution. Contrary to the past research, we found that women were more productive than men. This is a first large-scale quantitative research of senior scholars in Israel which sheds some light on the productivity evaluation and its influence factors in the Israeli academia.

Publisher

iSchools

Series/Report Name or Number

iConference 2020 Proceedings

Type of Resource

text

Genre of Resource

Conference Poster

Language

eng

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http://hdl.handle.net/2142/106541

Copyright and License Information

Copyright 2020 Maor Weinberger, Maayan Zhitomirsky-Geffet, and Dan Bouhnik

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