Papers of possible interest to Sig Metrics readers

[Eugene Garfield]

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TITLE:          An analysis of scholarly productivity in United States
                academic anaesthesiologists by citation bibliometrics (Article, English)
AUTHOR:         Pagel, PS; Hudetz, JA
SOURCE:         ANAESTHESIA 66 (10). OCT 2011. p.873-878
                WILEY-BLACKWELL, MALDEN

SEARCH TERM(S):  HIRSCH JE          P NATL ACAD SCI USA   102:16569 2005;
                 BIBLIOMETR*  item_title; CITATION  item_title;
                 CITATION*  item_title

KEYWORDS+:       H-INDEX; PHYSICIAN SCIENTISTS; KINGDOM; IMPACT; RADIOLOGY;
                JOURNALS; TIME

ABSTRACT:       The h-index is used to evaluate scholarly productivity in
academic medicine, but has not been extensively used in anaesthesia. We analysed the publications, citations, citations per publication and h- index from 1996 to date using the Scopus (R) database for 1630 (1120 men, 510 women) for faculty members from 24 randomly selected US academic anaesthesiology departments The median (interquartile range [range]) h- index of US academic anaesthesiologists was 1 [0-5 (0-44)] with 3 [0-18 (0-398)] total publications, 24 [0-187 (0-8515)] total citations, and 5
[0-14 (0-252)] citations per publication. Faculty members in departments with National Institutes of Health funding were more productive than colleagues in departments with little or no government funding. The h- index increased significantly between successive academic ranks concomitant with increases in the number of publications and total citations. Men had higher median h-index than women concomitant with more publications and citations, but the number of citations per publication was similar between groups. Our results suggest that h-index is a reasonable indicator of scholarly productivity in anaesthesia. The results may help comparisons of academic productivity across countries and may be used to assess whether new initiatives designed to reverse recent declines in academic anaesthetic are working.

AUTHOR ADDRESS: PS Pagel, Anesthesia Serv, Milwaukee, WI 53234 USA

   

 
 
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TITLE:          The Hirsch Index and Related Impact Measures (Article,
                English)
AUTHOR:         Egghe, L
SOURCE:         ANNUAL REVIEW OF INFORMATION SCIENCE AND TECHNOLOGY 44.
                2010. p.65-114 WILEY-BLACKWELL, MALDEN

SEARCH TERM(S):  HIRSCH JE          P NATL ACAD SCI USA   102:16569 2005;
                 SMITH LC           LIBR TRENDS            30:83    1981;
                 EGGHE L  primaryauthor,author

KEYWORDS+:       SUCCESSIVE H-INDEXES; ACADEMY-OF-SCIENCES; DEPENDENT
                LOTKAIAN INFORMETRICS; RANKING SCIENTIFIC INSTITUTIONS;
                STANDARD BIBLIOMETRIC MEASURES; EGGHES G-INDEX; RESEARCH
                OUTPUT; GOOGLE SCHOLAR; CITATION ANALYSIS; R-INDEX

AUTHOR ADDRESS: L Egghe, Univ Hasselt, Diepenbeek, Belgium

 
 
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TITLE:          Are We Wielding this Hammer Correctly? A Reflective
                Review of the Application of Cluster Analysis in Information Systems
                Research (Review, English)
AUTHOR:         Balijepally, V; Mangalaraj, G; Iyengar, K
SOURCE:         JOURNAL OF THE ASSOCIATION FOR INFORMATION SYSTEMS 12
                (5). 2011. p.375-413 ASSOC INFORMATION SYSTEMS, ATLANTA

SEARCH TERM(S):  GARFIELD E  rauth;
                 GARFIELD E         JAMA-J AM MED ASSOC   295:90    2006

KEYWORDS:       Cluster Analysis; Taxonomy Development; Configurational
                Research; Classification; Methodology
KEYWORDS+:       COMMON METHOD VARIANCE; MIS RESEARCH; RESOURCE-MANAGEMENT;
                STRATEGIC GROUPS; IMPACT FACTOR; WEB SITES; PERFORMANCE;
                SOFTWARE; TECHNOLOGY; PATTERNS

ABSTRACT:       Cluster analysis is a powerful statistical procedure for
extricating natural configurations among the data and the populations.
Cluster analysis, with its seemingly limitless power to produce groupings in any dataset, has all the trappings of a super-technique. However, the method produces clusters even in the absence of any natural structure in the data, and has no statistical basis to reject the null hypothesis that there are no natural groupings in the data. Application of cluster analysis, therefore, presupposes sound researcher judgment and responsible analysis and reporting. This paper summarizes the results of a reflective review of the application of cluster analysis in Information Systems (IS) research published in major IS outlets. Based on the analysis of 55 IS applications of cluster analysis, various deficiencies noticed in its use are discussed along with suggestions for future practice. By analyzing the results over two time periods, longitudinal trends in the application of this technique are highlighted.