Search (4 results, page 1 of 1)

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Abstract

Citation rates are becoming increasingly important in judging the research quality of journals, institutions and departments, and individual faculty. This paper looks at the pattern of citations across different management science journals and over time. A stochastic model is proposed which views the generating mechanism of citations as a gamma mixture of Poisson processes generating overall a negative binomial distribution. This is tested empirically with a large sample of papers published in 1990 from six management science journals and found to fit well. The model is extended to include obsolescence, i.e., that the citation rate for a paper varies over its cited lifetime. This leads to the additional citations distribution which shows that future citations are a linear function of past citations with a time-dependent and decreasing slope. This is also verified empirically in a way that allows different obsolescence functions to be fitted to the data. Conclusions concerning the predictability of future citations, and future research in this area are discussed.

Date

26.12.2007 19:22:05

Source

Information processing and management. 42(2006) no.6, S.1451-1464

Type

a

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Abstract

This paper considers the use of the h-index as a measure of a journal's research quality and contribution. We study a sample of 455 journals in business and management all of which are included in the ISI Web of Science (WoS) and the Association of Business School's peer review journal ranking list. The h-index is compared with both the traditional impact factors, and with the peer review judgements. We also consider two sources of citation data - the WoS itself and Google Scholar. The conclusions are that the h-index is preferable to the impact factor for a variety of reasons, especially the selective coverage of the impact factor and the fact that it disadvantages journals that publish many papers. Google Scholar is also preferred to WoS as a data source. However, the paper notes that it is not sufficient to use any single metric to properly evaluate research achievements.

Source

Information processing and management. 48(2012) no.2, S.234-241

Type

a

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Abstract

The Leiden Rankings can be used for grouping research universities by considering universities which are not statistically significantly different as homogeneous sets. The groups and intergroup relations can be analyzed and visualized using tools from network analysis. Using the so-called "excellence indicator" PPtop-10%-the proportion of the top-10% most-highly-cited papers assigned to a university-we pursue a classification using (a) overlapping stability intervals, (b) statistical-significance tests, and (c) effect sizes of differences among 902 universities in 54 countries; we focus on the UK, Germany, Brazil, and the USA as national examples. Although the groupings remain largely the same using different statistical significance levels or overlapping stability intervals, these classifications are uncorrelated with those based on effect sizes. Effect sizes for the differences between universities are small (w < .2). The more detailed analysis of universities at the country level suggests that distinctions beyond three or perhaps four groups of universities (high, middle, low) may not be meaningful. Given similar institutional incentives, isomorphism within each eco-system of universities should not be underestimated. Our results suggest that networks based on overlapping stability intervals can provide a first impression of the relevant groupings among universities. However, the clusters are not well-defined divisions between groups of universities.

Source

Journal of the Association for Information Science and Technology. 70(2019) no.5, S.509-525

Type

a

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Abstract

In this work we develop new journal classification methods based on the h-index. The introduction of the h-index for research evaluation has attracted much attention in the bibliometric study and research quality evaluation. The main purpose of using an h-index is to compare the index for different research units (e.g. researchers, journals, etc.) to differentiate their research performance. However the h-index is defined by only comparing citations counts of one's own publications, it is doubtful that the h index alone should be used for reliable comparisons among different research units, like researchers or journals. In this paper we propose a new global h-index (Gh-index), where the publications in the core are selected in comparison with all the publications of the units to be evaluated. Furthermore, we introduce some variants of the Gh-index to address the issue of discrimination power. We show that together with the original h-index, they can be used to evaluate and classify academic journals with some distinct advantages, in particular that they can produce an automatic classification into a number of categories without arbitrary cut-off points. We then carry out an empirical study for classification of operations research and management science (OR/MS) journals using this index, and compare it with other well-known journal ranking results such as the Association of Business Schools (ABS) Journal Quality Guide and the Committee of Professors in OR (COPIOR) ranking lists.

Source

Information processing and management. 51(2015) no.2, S.50-61

Type

a