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Evaluating OR/MS Journals via PageRank

Author

Listed:
  • Zhou Xu

    (Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong)

  • Brenda Cheang

    (School of Management, Huazhong University of Science and Technology, 430074 Wuhan, China)

  • Andrew Lim

    (Department of Management Sciences, The City University of Hong Kong, Kowloon Tong, Hong Kong)

  • Qi Wen

    (Department of Management Sciences, The City University of Hong Kong, Kowloon Tong, Hong Kong)

Abstract

Scholars, practitioners, and students in operations research and management science (OR/MS) often hesitate to use traditional approaches to evaluate journal quality because of the inconsistency of these approaches to perceptions and other associated biases. We introduce an alternative approach, which is based on Google's PageRank, to evaluate 31 OR/MS journals. This approach enhances the impact factor method by considering both citation quantity and quality. When we apply our method to OR/MS journals, the results match survey opinions and significantly outperform rankings based on impact factors. In addition, we provide an extensive discussion of other methods that have been used to assess journal quality. Compared to these methods, our method is better able to discern quality differences for journals that are perceived to be of relatively higher quality. Most importantly, we integrate our method into a Web-based journal-ranking system.

Suggested Citation

  • Zhou Xu & Brenda Cheang & Andrew Lim & Qi Wen, 2011. "Evaluating OR/MS Journals via PageRank," Interfaces, INFORMS, vol. 41(4), pages 375-388, August.
    • Handle: RePEc:inm:orinte:v:41:y:2011:i:4:p:375-388
    DOI: 10.1287/inte.1110.0557
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    References listed on IDEAS

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    Cited by:

    1. Brenda Cheang & Samuel Kai Wah Chu & Chongshou Li & Andrew Lim, 2014. "OR/MS journals evaluation based on a refined PageRank method: an updated and more comprehensive review," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 339-361, August.
    2. Rosenthal, Edward C. & Weiss, Howard J., 2017. "A data envelopment analysis approach for ranking journals," Omega, Elsevier, vol. 70(C), pages 135-147.
    3. Venkata Mrudula Bhimavarapu & Shailesh Rastogi & Preeti Mulay, 2023. "A Bibliometric Study on Corporate Transparency and Disclosures," FIIB Business Review, , vol. 12(2), pages 138-157, June.
    4. Liao, Huchang & Tang, Ming & Li, Zongmin & Lev, Benjamin, 2019. "Bibliometric analysis for highly cited papers in operations research and management science from 2008 to 2017 based on Essential Science Indicators," Omega, Elsevier, vol. 88(C), pages 223-236.
    5. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
    6. Brenda Cheang & Chongshou Li & Andrew Lim & Zhenzhen Zhang, 2015. "Identifying patterns and structural influences in the scientific communication of business knowledge," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 159-189, April.

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