Academy of Marketing Science
Publishing Code of Ethics
This code of ethics should be considered as advisory guidelines based on existing best practices to be used by the various participants in the scientific publishing process (i.e., authors, reviewers, and editors). The guidelines are developed to inform and promote integrity in academic publishing. There will always be judgments about best practices, and the code is designed to provide guidance on the most appropriate ways to promote publishing integrity. The purpose of the code is for providing information, not creating new standards. The scientific community has developed principles, standards, and guidelines that this code represents. The Committee on Publishing Ethics (COPE) is an excellent source for additional guidelines and cases on specific breaches of publication ethics and the resolution of conflicts.
From time to time, AMS may have to make decisions that involve violations of this Code of Ethics. Where the violations involve publication in our journals, consequences may include journal article retraction, removal, or tagging with an expression of concern. The AMS publishing committee relies on the article retraction and expression of concern guidelines published by the Committee on Publication Ethics (COPE). To learn more about article retraction or removal of publications, go to https://publicationethics.org/guidance/guideline/retraction-guidelines . For more on Expressions of Concerns, see:https://publicationethics.org/guidance/guideline/expressions-concern.
1. Conducting Research
Research projects need to be designed to use the most appropriate methodology to address the topic under investigation.
All data sources and methods must be accurately disclosed. A data availability statement must accompany empirical research submissions. The default position is that data should be made available in some fashion. Coinciding with the need for data transparency, any material source coding necessary to produce the results should also be made available. See the AMS Data Policy page for more details: https://www.ams-web.org/data-policy.
Sources of potential bias should be identified and reported.
The discovery of errors requiring corrections or clarifications should be made available at any stage of the research and publishing process.
Assessment instrument(s) should be valid and reliable for the stated use. When validity or reliability has not been determined, strengths and limitations of results must be disclosed.
Integrity of data handling and analysis is critical to the scientific process; authors’ procedures should be transparent to reviewers and authors should avoid opportunistically manipulating findings or omitting data to enable support for a desired pattern of results.
For any research project that includes human participants as data sources, there needs to be a discussion that identifies the overall “defined target population” of interest as well as “inclusion” and/or “exclusion” of the factors used to determine individuals’ qualifications as participants in the research project.
If data are involved in the manuscript, the author(s) must state whether the authors are equally responsible for the integrity of the data, data analyses, and data reporting. Note that all authors risk negative consequences of retractions or other sanctions should the data be later determined as problematic due to fabrication, selection, misinterpretation, careless handling, failure to exercise due diligence in considering construct validity of multi-item measures, or selective reporting of empirical results, including the suppression of results inconsistent with the preconceived notions of the author(s).
If incentives are provided for participation in research, efforts should be made to offer reasonable and appropriate inducements for participation. In no case should coercion be involved in obtaining respondents (i.e. participate or lose points in a class).
Only individuals who make significant intellectual contribution(s) to the development of the project (e.g., in positioning, design, data collection, and/or analysis) and/or the crafting of the manuscript (including subsequent revisions) should be considered co-authors.
Generative artificial intelligence agents cannot be listed as co-author (or author) on a published paper or paper submitted for publication. The primary intellectual content must be due to human intelligence.
Financial support of research and publication, such as fees associated with open-source publication or submission fees, or financially supporting the acquisition/access of/to data, does not constitute a basis for co-authorship.
Any form of contribution of others, including the general discussion of ideas, carrying out aspects of data collection on behalf of the author team, suggesting analyses or offering technical assistance, or copy-editing and providing comments, can be recognized in the acknowledgements, but this scope of work does not rise to co-authorship and the provider of the work should not have such expectation.
Solely being a member of a research “team”, “center,” or “consortium” does not qualify one as an article author or coauthor. If such members serve in a consultative role to a specific project, they may qualify as a “contributor.”
In planning the research, it is important to determine those who will qualify for authorship; contributors, but not authors; and the order of authorship.
The practice of placing co-authors on the article for reasons other than their active participation (i.e., gift authorship) is not acceptable.
Before submitting a manuscript, all co-authors involved must approve the final content and agree to take responsibility for problems with the research as evidenced in the final manuscript.
The author(s) are entirely responsible for the intellectual property developed in this work and must submit work with the acknowledgment that these authors know of no other person(s)/entity who can later claim to ownership (authorship) of this work.
Any change in authorship during the course of the review process must be accompanied by individual, signed consent stating full agreement and volition to any addition, deletion, or change of authorship order from that stated in the original title page and in the submission system documentation.
Faculty committee members or dissertation advisors must not use coercive influence to be named an author on the work stemming from a thesis/dissertation. Faculty or committee members must not submit the work of a student as their own.
2. Authorship
The use of published or unpublished ideas or content from other sources must be referenced fully.
When two or more papers share the same conceptual framework, hypothesis, and/or data, all previous articles should be identified. Redundant publication must be avoided when papers are published without proper cross-references.
All references should be based on the original publication, not taken from the reference(s) of other publications.
Since plagiarism among junior authors may result from poor mentorship or supervision, co-authors must provide appropriate oversight to prevent plagiarism.
Self-plagiarism, or ideoplagiarism, should be avoided by citing previous work. The author(s) must certify that the work is not plagiarized from other published or publicly available sources, including previously published works by a member of the author team.
Copying or adopting sentences from a wide range of sources without documentation must be avoided.
Recognizing that technological tools can have legitimate and illegitimate uses in research, we expect transparency in the use of generative artificial intelligence technology agents. The author must fully disclose and document the material use of generative artificial intelligence technology agents in any stage of the research described in a manuscript submitted for publication. Citations to work generated by such agents must document the date, and question (input or prompt), and provide the URL from which the content was taken.[1] Direct quotes must be noted as such and included in “quotes.” The undocumented use of such agents will be considered plagiarism.
If data are analyzed by an AI agent and/or the result written by an AI agent, such use must be fully disclosed and the text placed in quotations if taken verbatim.
[1] For instance, ChatGPT, Perplexity.ai, BARD, GPT-4, DALL-E, CoPilot, any AI-Assist, represent a sample of such agents with the number expected to grow over time.
3. Plagiarism
Any interest or involvement that could influence an editor, associate editor, guest editor, or a reviewer needs to be disclosed.
Editors have a responsibility not to develop, explicitly or implicitly, reciprocation agreements with other editors or to engage in behavior that results in mutual facilitation of publishing each other’s work across journals. Such restriction does not preclude an editor from inviting other editors to contribute on a topic of special expertise from time to time.
Attempting to influence editors, by either individuals or institutions, by providing extraordinary payments, rewards, or other tangible benefits, with the expectation (implicit or explicit) of special publishing favor, is not acceptable. Likewise, it is not acceptable for an editor, associate editor, or guest editor to accept any consideration that would create the appearance of a quid-pro-quo relationship.
Journal owners and publishers have a duty to exercise oversight of potential conflicts of interest and such oversight includes the selection of editors and journal affiliates in an effort to signal integrity.
Editors must use due care in selecting Associate Editors, Guest Editors and reviewers, avoiding individuals with a propensity to engage in unethical conduct related to publishing or academic dishonesty.
Authors should not suggest reviewers who know the authors’ work intimately or who are close associates of any member of the author team.
Financial support of the research needs to be acknowledged if material.
A manuscript cannot be submitted to a second publication outlet until the manuscript has been withdrawn or a decision has been made at a prior outlet at which the manuscript is under review.
4. Conflicts of Interest
Subjects or respondents must provide informed consent allowing for voluntary participation.
Informed consent should not be coerced or improperly pressured on any participant in the research process.
Subjects or respondents should not be encouraged to withdraw from the research for the purpose of impacting results.
The privacy and the confidentiality of subjects and respondents must be protected.
Organizational compliance and training for human subjects and respondents must be implemented as required.
Proper Human Subjects documentation (IRB Requirements) need to be filed with the supervising institution as per current practices of the institution represented.
Experimental subjects must be debriefed properly immediately following the research procedure.
5. Human Subjects and Respondents
Reviewing for journals is a professional activity, and the integrity of the discipline depends on this responsibility.
Reviewers must respect the confidentiality of and the proprietary rights of the author(s).
A reviewer should avoid offering detailed criticism on matters where he/she lacks expertise.
Report any ethical violations or irregularities such as plagiarism or conflicts of interest by reporting observations to the editor.
Reviewers must inform the editor if assigned a manuscript for which they recognize the author(s).
Revised September 24, 2025 by vote of the AMS Board of Governors.
Provide appropriate feedback of the strengths and weaknesses of the manuscript.
Provide suggestions based on academically valid reasons, avoiding criticisms that are presented without explanation or justification. Reviewers should inform the editor if he/she has previously reviewed an assigned manuscript for another publication.
Reviewers should not agree to review a submission at a point in time when they know in advance that they cannot return the review in a timely manner or should disclose that information to the soliciting editor.
Reviewers must not review papers for which an author or agent of the author has provided notification to the reviewer that he/she was listed as a potential reviewer.
Reviewers should apply their own intellectual matter to reviewing manuscripts. Reviewers must not rely on AI-agents to provide a review requested by an editor. If an AI-agent is consulted in the review process, that reviewer should disclose such use to the requesting editor.