Measuring the attractiveness of academic journals: A direct influence aggregation model

Fabien Cornillier; Vincent Charles

Measuring the attractiveness of academic journals: A direct influence aggregation model

Fabien Cornillier
, Vincent Charles

Sección de Posgrado en Negocios

Universidad del Pacífico

Research output: Contribution to journal › Article › peer-review

4 Scopus citations

Abstract

Various journal-ranking algorithms have been proposed, most of them based on citation counts. This article introduces a new approach based on the reciprocal direct influence of all pairs of a list of journals. The proposed method is assessed against an opinion-based ranking published in 2005 for 25 operations research and management science (OR/MS) journals, and seven methods based on citation counts. The results show a strong correlation with the opinion-based ranking.

Original language	Spanish
Pages (from-to)	172-176
Number of pages	5
Journal	Operations Research Letters
Volume	43
State	Published - 1 Jan 2015

Cite this

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title = "Measuring the attractiveness of academic journals: A direct influence aggregation model",

abstract = "Various journal-ranking algorithms have been proposed, most of them based on citation counts. This article introduces a new approach based on the reciprocal direct influence of all pairs of a list of journals. The proposed method is assessed against an opinion-based ranking published in 2005 for 25 operations research and management science (OR/MS) journals, and seven methods based on citation counts. The results show a strong correlation with the opinion-based ranking.",

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AB - Various journal-ranking algorithms have been proposed, most of them based on citation counts. This article introduces a new approach based on the reciprocal direct influence of all pairs of a list of journals. The proposed method is assessed against an opinion-based ranking published in 2005 for 25 operations research and management science (OR/MS) journals, and seven methods based on citation counts. The results show a strong correlation with the opinion-based ranking.

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