Evaluating and Ranking Anti-Counterfeiting Strategies to Combat Hijacked Journals: A Hybrid Multi-Criteria Decision-Making Approach
The proliferation of hijacked journals poses a significant threat to academic integrity by deceiving researchers, misappropriating intellectual property, and undermining trust in scholarly publishing. Despite the growing seriousness of this issue, systematic evaluations of strategies to deal with this problem remain scarce. This study fills the gap by employing a hybrid Multi-Criteria Decision-Making (MCDM) framework that integrates the Best-Worst Method (BWM) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) to assess and rank strategies for combating hijacked journals. Drawing on expert insights, the study evaluates five key strategies - legislation, education of stakeholders, aggressive advertising, investigation and surveillance, and coalition-building - against a set of social, economic, and journal-ranking criteria. The results indicate that educating stakeholders at source is the most effective strategy, followed by aggressive advertising, investigation and surveillance, coalition, and legislation. These findings highlight the importance of awareness-driven and preventive approaches, supported by monitoring and collaborative efforts, while suggesting that legal enforcement alone may have limited effectiveness. The study contributes to literature by providing an empirically grounded decision-making framework for addressing hijacked journals and offers practical implications for academic publishers and institutions.
Authors
- Anh H. G. Nguyen (ORCID: https://orcid.org/0000-0002-0259-2068)
- Thị Thanh Bình Nguyễn (ORCID: https://orcid.org/0009-0009-2407-9407)
- My Phan Hiệp Dương (ORCID: https://orcid.org/0009-0005-9755-4783)
- Khôi Văn Mã (ORCID: https://orcid.org/0009-0008-0593-0377)
- Qui Duong Khai
Institutions
- Vietnam National University Ho Chi Minh City (VN)
Publication Details
- Journal
- Serials Review
- Published
- 2026-06-17
- DOI
- https://doi.org/10.1080/00987913.2026.2679233
- Primary Topic
- Spam and Phishing Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00