Scientometrics
Volume/Issue:
Volume 87: Issue 3
Research trends analysis by comparing data mining and customer relationship management through bibliometric methodology
Author:
Hsu-Hao Tsai Department of Management Information System, National Chengchi University, No. 64, Sec. 2, Zhinan Rd., Wenshan District, Taipei City 11605, Taiwan, R.O.C.

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Pages:
425–450
Online Publication Date:
18 Feb 2011
Publication Date:
01 Jun 2011
Article Category:
Research Article
DOI:
https://doi.org/10.1007/s11192-011-0353-6
Keywords:
Data mining; Customer relationship management; Research trend analysis; Bibliometric methodology
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Abstract

There are few comprehensive studies and categorization schemes to discuss the characteristics for both data mining and customer relationship management (CRM) although they have already become more important recently. Using a bibliometric approach, this paper analyzes data mining and CRM research trends from 1989 to 2009 by locating headings “data mining” and “customer relationship management” or “CRM” in topics in the SSCI database. The bibliometric analytical technique was used to examine these two topics in SSCI journals from 1989 to 2009, we found 1181 articles with data mining and 1145 articles with CRM. This paper implemented and classified data mining and CRM articles using the following eight categories—publication year, citation, country/territory, document type, institute name, language, source title and subject area—for different distribution status in order to explore the differences and how data mining and CRM technologies have developed in this period and to analyze data mining and CRM technology tendencies under the above result. Also, the paper performs the K–S test to check whether the analysis follows Lotka's law. The research findings can be extended to investigate author productivity by analyzing variables such as chronological and academic age, number and frequency of previous publications, access to research grants, job status, etc. In such a way characteristics of high, medium and low publishing activity of authors can be identified. Besides, these findings will also help to judge scientific research trends and understand the scale of development of research in data mining and CRM through comparing the increases of the article author. Based on the above information, governments and enterprises may infer collective tendencies and demands for scientific researcher in data mining and CRM to formulate appropriate training strategies and policies in the future. This analysis provides a roadmap for future research, abstracts technology trends and facilitates knowledge accumulations so that data mining and CRM researchers can save some time since core knowledge will be concentrated in core categories. This implies that the phenomenon “success breeds success” is more common in higher quality publications.

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Cover Scientometrics
Scientometrics
Print ISSN:
0138-9130
Online ISSN:
1588-2861

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Scientometrics
Language English
Size B5
Year of
Foundation		 1978
Volumes
per Year		 1
Issues
per Year		 12
Founder Akadémiai Kiadó
Founder's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Publisher Akadémiai Kiadó
Springer Nature Switzerland AG
Publisher's
Address		 H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
CH-6330 Cham, Switzerland Gewerbestrasse 11.
Responsible
Publisher		 Chief Executive Officer, Akadémiai Kiadó
ISSN 0138-9130 (Print)
ISSN 1588-2861 (Online)

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