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The Journal Impact Factor (JIF) is one of the very important numerical measures
of scientific or research importance of a journal. Notwithstanding the observations
of Rossner et al. (2007), who question the veracity of JIF data altogether, the
importance or quality of a paper/article (and, by implication, the author(s) of the
paper/article) published in a journal is often judged by the JIF of the journal concerned. After
the University Grants Commission, India, notified its Regulation on
Minimum Qualifications for Appointment of Teachers and Other Academic Staff in
Universities and Colleges and Measures for the Maintenance of Standards in Higher
Education on September 23, 2009, JIF has become all the more important since publication
of research papers/articles in high-impact journals has become an important factor
in assessment of the academic performance of teachers in colleges and universities
in India (Mishra, 2009). Impact factors are calculated every year for those
journals that are indexed in Thomson Reuters' Journal Citation Reports.
In the past, researchers have hypothesized various types of statistical
distributions underlying the generation mechanism of JIFs. These are: negative
exponential (Brookes, 1970), combination of exponentials (Avramescu, 1979), Poisson
(Brown, 1980), generalized inverse Gaussian-Poisson (Sichel, 1985; and Burrell and
Fenton, 1993), lognormal (Matricciani, 1991; and Egghe and Rao, 1992), Weibull
(Hurt and Budd, 1992; and Rousseau and West-Vlaanderen, 1993),
gamma (Sahoo and Rao, 2006), negative binomial (Bensman, 2008), approximately normal
(Stringer et al., 2008), normal (Egghe, 2009),
generalized Waring (Irwin, 1975; Panaretos and Xekalaki, 1986; and Glänzel, 2009) and so on. |
