Plagiarism Policy

Manuscripts submitted to the Journal of Digital Business and Data Science will be screened for plagiarism using the Turnitin plagiarism detection tool. Journal of Digital Business and Data Science will immediately reject papers leading to plagiarism or self-plagiarism.

Journal of Digital Business and Data Science want to ensure that all authors are careful and comply with international standards for academic integrity, particularly on the issue of plagiarism.

Plagiarism occurs when an author takes ideas, information, or words from another source without proper credit to the source. Even when it occurs unintentionally, plagiarism is still a serious academic violation and is unacceptable in international academic publications.

When the author takes an idea from another author, a citation is required even if the author then develops the idea further. This might be an idea about how to interpret the data, either what methodology to use or what conclusion to draw. It might be an idea about broad developments in a field or general information. Regardless of the idea, authors should cite their sources. In cases where the author develops the idea further, it is still necessary to cite the original source of the idea, and then in a subsequent sentence, the author can explain their more developed idea.

When the author takes words from another author, citation and quotation marks are required. Whenever four or more consecutive words are identical to a source that the author has read, the author must use quotation marks to denote the use of another author's original words; just a citation is no longer enough.

Policy:

Papers must be original, unpublished, and not pending publication elsewhere. Any material taken verbatim from another source needs to be clearly identified as different from the present original text by (1) indentation, (2) use of quotation marks, and (3) identification of the source.

Any text of an amount exceeding fair use standards (herein defined as more than two or three sentences or the equivalent thereof) or any graphic material reproduced from another source requires permission from the copyright holder and, if feasible, the original author(s) and also requires identification of the source; e.g., previous publication.

When plagiarism is identified, the Editor in Chief responsible for the review of this paper and will agree on measures according to the extent of plagiarism detected in the paper in agreement with the following guidelines:

Level of Plagiarism

1. Minor: A short section of another article is plagiarized without any significant data or idea taken from the other paper

Action: A warning is given to the authors and a request to change the text and properly cite the original article is made

2. Intermediate: A significant portion of a paper is plagiarized without proper citation to the original paper

Action: The submitted article is rejected and the authors are forbidden to submit further articles for one year

3. Severe: A significant portion of a paper is plagiarized that involves reproducing original results or ideas presented in another publication

Action: The paper is rejected and the authors are forbidden to submit further articles for five years.

the Journal of Digital Business and Data Science takes academic integrity very seriously, and the editors reserve the right to withdraw acceptance from a paper found to violate any of the standards set out above. For further information, potential authors can contact the editorial office at [email protected]