Plagiarism Policy

Plagiarism Screening
Alamanda Research in Management (ARiM) routinely screens all submissions for text similarity during the initial editorial check. Similarity reports are used as a diagnostic tool and are interpreted by the editorial team in context (e.g., proper quotation, citation, and standard academic phrasing).

As a general guideline, manuscripts may be desk-rejected if the overall similarity index is 30% or higher (excluding references, quoted material, and bibliographic sections). In addition, ARiM monitors concentrated overlap: matches from any single source should normally not exceed 5% of the manuscript text. When high single-source similarity is driven by legitimate and properly cited material (e.g., standard methods, widely used instruments, or appropriately quoted passages), the editors may exercise discretion and may request revision rather than reject.

If a submission is desk-rejected due to excessive similarity, authors may resubmit after addressing the overlap and ensuring appropriate citation and quotation practices, provided the manuscript falls below the journal’s similarity thresholds.

Types of Plagiarism (Examples)
Plagiarism can take multiple forms, including verbatim copying, paraphrasing without attribution, translation plagiarism, and idea-based plagiarism. It may also include code plagiarism and undisclosed AI-generated content, as well as more sophisticated forms such as obfuscated or cross-language plagiarism and duplicate/redundant publication (Amirzhanov et al., 2025).

Post-publication Concerns
If plagiarism is suspected in a published article, ARiM will conduct a formal investigation. Depending on the findings, the journal may issue a correction/notice, an expression of concern, or a retraction in line with responsible publishing practices. See the journal’s Withdrawal, Corrections, and Retractions Policy for details.

Reference

Amirzhanov, A., Turan, C., & Makhmutova, A. (2025). Plagiarism types and detection methods: A systematic survey of algorithms in text analysis. Frontiers in Computer Science, 7, 1504725. https://doi.org/10.3389/fcomp.2025.1504725.