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Research trends analysis by comparing data mining and customer relationship management through bibliometric methodology

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  • Hsu-Hao Tsai

    (National Chengchi University)

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.

Suggested Citation

  • Hsu-Hao Tsai, 2011. "Research trends analysis by comparing data mining and customer relationship management through bibliometric methodology," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 425-450, June.
    • Handle: RePEc:spr:scient:v:87:y:2011:i:3:d:10.1007_s11192-011-0353-6
    DOI: 10.1007/s11192-011-0353-6
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    References listed on IDEAS

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    Cited by:

    1. Mohammad Rabiei & Seyyed-Mahdi Hosseini-Motlagh & Abdorrahman Haeri, 2017. "Using text mining techniques for identifying research gaps and priorities: a case study of the environmental science in Iran," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 815-842, February.
    2. Escuadra, Catherine Joy & Magallanes, Krizia & Lee, Sunbok & Chung, Jae Young, 2023. "Systematic analysis on school violence and bullying using data mining," Children and Youth Services Review, Elsevier, vol. 150(C).
    3. Jamali, Seyedh Mahboobeh & Md Zain, Ahmad Nurulazam & Samsudin, Mohd Ali & Ale Ebrahim, Nader, 2015. "Publication Trends in Physics Education: A Bibliometric study," MPRA Paper 79524, University Library of Munich, Germany, revised 2015.
    4. Jabłońska-Sabuka, Matylda & Sitarz, Robert & Kraslawski, Andrzej, 2014. "Forecasting research trends using population dynamics model with Burgers’ type interaction," Journal of Informetrics, Elsevier, vol. 8(1), pages 111-122.
    5. Wei Liu & Zongshui Wang & Hong Zhao, 2020. "Comparative study of customer relationship management research from East Asia, North America and Europe: A bibliometric overview," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 735-757, December.
    6. Silvio Addolorato & Ferran Calabuig & Vicente Prado-Gascó & Leonor Gallardo & Jorge García-Unanue, 2019. "Bibliometric Analysis of Fitness Equipment: How Scientific Focuses Affect Life-Cycle Approaches and Sustainable Ways of Development," Sustainability, MDPI, vol. 11(20), pages 1-16, October.

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