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How to Order Authors in Scientific Papers

It’s rare that an article is authored by only one or two people anymore. In fact, the average original research paper has five authors these days. The growing list of collaborative research projects raises important questions regarding the author order for research manuscripts and the impact an author list has on readers’ perceptions.

With a handful of authors, a group might be inclined to create an author name list based on the amount of work contributed. What happens, though, when you have a long list of authors? It would be impractical to rank the authors by their relative contributions. Additionally, what if the authors contribute relatively equal amounts of work? Similarly, if a study was interdisciplinary (and many are these days), how can one individual’s contribution be deemed more significant than another’s?

Why does author order matter?

Although an author list should only reflect those who have made substantial contributions to a research project and its draft manuscript (see, for example, the authorship guidelines of the International Committee of Medical Journal Editors ), we’d be remiss to say that author order doesn’t matter. In theory, everyone on the list should be credited equally since it takes a team to successfully complete a project; however, due to industry customs and other practical limitations, some authors will always be more visible than others.

The following are some notable implications regarding author order.

• The “first author” is a coveted position because of its increased visibility. This author is the first name readers will see, and because of various citation rules, publications are usually referred to by the name of the first author only. In-text or bibliographic referencing rules, for example, often reduce all other named authors to “et al.” Since employers use first-authorship to evaluate academic personnel for employment, promotion, and tenure, and since graduate students often need a number of first-author publications to earn their degree, being the lead author on a manuscript is crucial for many researchers, especially early in their career.
• The last author position is traditionally reserved for the supervisor or principal investigator. As such, this person receives much of the credit when the research goes well and the flak when things go wrong. The last author may also be the corresponding author, the person who is the primary contact for journal editors (the first author could, however, fill this role as well, especially if they contributed most to the work).
• Given that there is no uniform rule about author order, readers may find it difficult to assess the nature of an author’s contribution to a research project. To address this issue, some journals, particularly medical ones, nowadays insist on detailed author contribution notes (make sure you check the target journal guidelines before submission to find out how the journal you are planning to submit to handles this). Nevertheless, even this does little to counter how strongly citation rules have enhanced the attention first-named authors receive.

Common Methods for Listing Authors

The following are some common methods for establishing author order lists.

• Relative contribution. As mentioned above, the most common way authors are listed is by relative contribution. The author who made the most substantial contribution to the work described in an article and did most of the underlying research should be listed as the first author. The others are ranked in descending order of contribution. However, in many disciplines, such as the life sciences, the last author in a group is the principal investigator or “senior author”—the person who often provides ideas based on their earlier research and supervised the current work.
• Alphabetical list . Certain fields, particularly those involving large group projects, employ other methods . For example, high-energy particle physics teams list authors alphabetically.
• Multiple “first” authors . Additional “first” authors (so-called “co-first authors”) can be noted by an asterisk or other symbols accompanied by an explanatory note. This practice is common in interdisciplinary studies; however, as we explained above, the first name listed on a paper will still enjoy more visibility than any other “first” author.
• Multiple “last” authors . Similar to recognizing several first authors, multiple last authors can be recognized via typographical symbols and footnotes. This practice arose as some journals wanted to increase accountability by requiring senior lab members to review all data and interpretations produced in their labs instead of being awarded automatic last-authorship on every publication by someone in their group.
• Negotiated order . If you were thinking you could avoid politics by drowning yourself in research, you’re sorely mistaken. While there are relatively clear guidelines and practices for designating first and last authors, there’s no overriding convention for the middle authors. The list can be decided by negotiation, so sharpen those persuasive argument skills!

As you can see, choosing the right author order can be quite complicated. Therefore, we urge researchers to consider these factors early in the research process and to confirm this order during the English proofreading process, whether you self-edit or received manuscript editing or paper editing services , all of which should be done before submission to a journal. Don’t wait until the manuscript is drafted before you decide on the author order in your paper. All the parties involved will need to agree on the author list before submission, and no one will want to delay submission because of a disagreement about who should be included on the author list, and in what order (along with other journal manuscript authorship issues).

On top of that, journals sometimes have clear rules about changing authors or even authorship order during the review process, might not encourage it, and might require detailed statements explaining the specific contribution of every new/old author, official statements of agreement of all authors, and/or a corrigendum to be submitted, all of which can further delay the publication process. We recommend periodically revisiting the named author issue during the drafting stage to make sure that everyone is on the same page and that the list is updated to appropriately reflect changes in team composition or contributions to a research project.

Who Should Be the Corresponding Author, What Are Their Responsibilities, and What Email Address Should They Provide?

• Published: 14 July 2023
• Volume 37 , pages 1039–1040, ( 2023 )

Cite this article

• Yochai Birnbaum 1 ,
• Masafumi Kitakaze 2 ,
• David Grieve 3 &
• Barry F. Uretsky 4 , 5  

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Avoid common mistakes on your manuscript.

The essential and major goal for scientific researchers has been, and will be, to publish original articles to provide new scientific information. After successful completion of rigorous research, dissemination in a timely manner of their novel findings for the benefit of other scientists and the broader research community should be the next goal.

This communication clarifies the proposed authorship and responsibility of the authors. The first author is typically the investigator who has “championed” the research. This person typically is the designer of the study protocol and the investigator who was responsible for the promulgation of the research. The first author is typically credited with the research although it is understood that all the authors participated. The last author is typically the “senior” author, often the lab director for a basic science study or the most experienced clinician in a clinical trial, particularly if that person has been the financial supporter for the study. The co-authors, which have increased in recent years with growing emphasis on global and multidisciplinary collaboration, must qualify for authorship based on the International Committee of Medical Journal Editors requirements.

One author is designated the “corresponding” author. The corresponding author, i.e., the author with whom the Editor communicates, is responsible for the integrity of the manuscript contents such as the veracity of the results, the lack of plagiarism, the contribution of each author, and other issues related to production of the manuscript. To analogize to creating a motion picture, the corresponding author is akin to the producer who not only supports financially the film but assures adequate locations to film, paying the actors, and other functions. The film director may be considered akin to the first author.

To summarize, some of the roles of the corresponding author are the following:

Article preparation, submission, and acceptance [ 1 , 2 ]:

Pre-publication: submission of the manuscript, communication with the editor, coordination of revisions, signing the copyright owner agreement and the publishing agreement, paying the article processing charge/publication fee (if needed), and final proofing of the manuscript.

Integrity: responsibility for ensuring integrity of both the published data and authorship contributions. In addition, the corresponding author is responsible for meeting the journal administrative requirements, documentation of ethics committee approval, documentation of clinical trial registration, complete disclosure of conflict-of-interest statement, etc.

Post-publication: responsibility for providing timely responses to queries related to the manuscript, including individual approaches, letters to the editor, and requests for data sharing.

Peer review: the authors could be invited to provide peer reviews of manuscripts focused on similar research topics.

Based on the expectations of the corresponding author, it seems intuitive that the corresponding should for the most part be the first author or the last author. That is not always the case as described below.

While the first two roles are accepted by most publishers, the third and fourth roles (c and d) are not mentioned by all. For example, Springer, the publisher of this journal, does not specify the third and fourth roles. The publisher states that articles can be published with more than one corresponding author, but only one can be accommodated by the Peer Review System. Moreover, they specify: “The corresponding author does not need to be the first author or a senior author. The order of authors can be arranged during the submission process, in whichever order suits but submissions must be made by the corresponding author and not on behalf of the corresponding author” ( https://support.springer.com/en/support/solutions/articles/6000214118-corresponding-author-defined ).

While in the past, hard copies of submitted manuscripts were mailed to the journals, the corresponding author was almost always the senior (usually the last) author. As such, the funding agencies or research institutions typically regarded the corresponding author as the essential scientist for each article. However, virtually universal transition to electronic submissions mandates that the official corresponding author is required to submit revisions, respond to editor queries, and proof the final manuscript. As this can be onerous based on individual website applications, many senior authors prefer not to be actively involved in this process, so they defer this role to more junior authors (usually the first author) as the corresponding author. While this perfectly serves the short-term role, while also benefiting professional development of junior researchers, it may create difficulties in fulfilling the longer-term responsibilities of the role. Due to various reasons, including fixed-term contracts, career progression, and family commitments, many junior faculty researchers and trainees move on to new employment, and thus, their email addresses are no longer active for communication. Teunis et al. assessed the response rate of the corresponding authors for manuscripts published between May 2003 and May 2013. In the study published in 2015, they found that there was a 20% (89/446) rate of undeliverable emails [ 2 ]. Only 53% (190/357) of the corresponding authors with working email addresses responded to query requests [ 2 ]. The odds of replying decreased by 15% per year between the publication and the query.

However, this can be easily resolved by listing the email addresses of all co-authors, including the senior and named corresponding authors. For this reason, cardiovascular drugs and therapy have implemented the requirement to include the email addresses of all co-authors in submissions to our journal.

Another important issue is the specific email address provided by the corresponding authors. Many academic institutions and hospitals have implemented heightened Internet security measures. This results in filtering and eliminating many emails sent to such email addresses, meaning that they are often not received by the corresponding author. In addition, some authors, especially more junior contributors, may be employed on fixed-term contracts or training programs, so are likely to change their place of work overtime, so their originally specified email address is no longer active. Use of personal email addresses or professional email addresses that can be accessed independent of the employing institution can resolve these issues. Ideally, each author should use a unique email address that can be linked to their personal ORCID identifier number ( www.ORCID.ORG ) alone or in addition to the institutional email address. Therefore, this journal will encourage the corresponding author to use an email address that will be available for a prolonged period typical 1–2 years at minimum.

McNutt MK, Bradford M, Drazen JM, et al. Transparency in authors’ contributions and responsibilities to promote integrity in scientific publication. Proc Natl Acad Sci USA. 2018;115(11):2557–60.

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Teunis T, Nota SP, Schwab JH. Do corresponding authors take responsibility for their work? A covert survey. Clin Orthop Relat Res. 2015;473(2):729–35.

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Authors and affiliations.

The Section of Cardiology, Baylor College of Medicine, Houston, TX, USA

Yochai Birnbaum

Hanwa Memorial Hospital, Osaka, Japan

Masafumi Kitakaze

Wellcome-Wolfson Institute for Experimental Medicine, Queen’s University, Belfast, UK

David Grieve

Central Arkansas Veterans Health System, Little Rock, AR, USA

Barry F. Uretsky

University of Arkansas for Medical Sciences, Little Rock, AR, USA

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All co-authors contributed to the content of this editorial. All co-authors read and approved the final version of the editorial.

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Correspondence to Yochai Birnbaum .

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Birnbaum, Y., Kitakaze, M., Grieve, D. et al. Who Should Be the Corresponding Author, What Are Their Responsibilities, and What Email Address Should They Provide?. Cardiovasc Drugs Ther 37 , 1039–1040 (2023). https://doi.org/10.1007/s10557-023-07486-5

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Accepted : 05 July 2023

Published : 14 July 2023

Issue Date : December 2023

DOI : https://doi.org/10.1007/s10557-023-07486-5

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What does last authorship mean in various fields? [duplicate]

Author order has been discussed extensively on this site, e.g. here , but these typically focus on the first author. I'm curious as to the meaning of the last author in various fields.

In (theoretical, non high-energy) physics, the last author is typically the one who conceived and directed the project, but may not have done the actual work of performing experiments/simulations/calculations (that would be the first author). The last author usually is someone more senior, but is not necesarily the PI or the most senior author. In fact, one often sees physics papers with a postdoc as the last author and the PI as a middle author. In fields with this convention (which I'll call "last=project leader"), last authorship is as coveted as first authorship, and it is desired for people at the postdoc/early faculty stage of their career to produce last-author papers, as it demonstrates leadership and ability to come up with ideas.

It seems that there are also other conventions. For example, my impression is that there exists a similar but distinct convention: the "last=PI" convention, where the last author is by default the PI, and doesn't come with any connotation of level of intellectual contribution, or the same strong significance attached to the first author position.

As a (possible) example of the difference between these conventions: in physics (or fields with the same convention) a junior person who performed a major leadership role might be "promoted" to last author, while in fields with the "last=PI" convention, they might be promoted to first or co-first author instead.

And (in some fields?) there is the "decreasing-contribution" system, where authors are simply arranged in order of level of contribution and hence the last position would just be the least important one.

So, among fields where author order is non-alphabetical, which follow the "last=project leader" vs "last=PI" vs "decreasing contribution" conventions? Are there possibilities other than these?

• author-order

• 3 There are probably as many conventions as fields, and more papers that use an individual style than follow the rule. –  Wolfgang Bangerth Commented May 29 at 17:27
• 1 While the title of your linked question mentions first authorship only, most of the answers also address the other author slots, including last author. So, this may be a duplicate of the linked question. –  cag51 ♦ Commented May 29 at 19:16
• @cag51 I did not find the information I wanted from the other question, and given that that is an old question, it is highly unlikely that such information will emerge in the future. Yes, there is some slight overlap, but the new question highlights a deemphasized aspect of the old question. Questions such as this are a useful way of generating new knowledge. –  Aqualone Commented May 29 at 20:01
• As an answer, do you expect a list of all academic fields and what the significance of being the last author is in each of them? –  user188590 Commented May 29 at 21:04
• @Ben I am just curious in general, and I hope that this question can also be useful for others who are also curious. I imagine that as an answer, one can write about their own field and any adjacent fields that they are aware of. –  Aqualone Commented May 29 at 21:16

8 Answers 8

In (pure) mathematics it means that the last name of the author comes last when sorted alphabetically.

As a statistician, I have worked in a few fields and, as a statistical reviewer, I've reviewed in more fields. I haven't really got a great answer for field by field, but I've seen:

1a. Alphabetical list of authors

1b. Random order

2a. First author most important, then alphabetical

2b. Same only with random order

Last author 2nd most important

Last author = PI, or the person who got the grant money, or the most senior

But each of this seems to happen in all the fields I've worked in (psychology, epidemiology, general medicine, neurology, neonatology, social networks, education, …). I'd say there is more variation within field (often by journal) than across fields, but maybe some fields do have a standard --- there are tons of fields I haven't worked in!

In biology is say its both last author=PI AND last author is project leader. Project leader IS the PI, almost always. In fact, PI is short for principal investigator. PIs are usually, but not always, the head of a research group, so the head of the research group is usually the last author. But not always. If a postdoc conceived of, planned, got authorisation and funding for a study. That is, if they were legally responsible for it. If it would be then in the dock if the data were fake, or ethical rules were not followed, then that postdoc would be the PI and the last author. I believe this situation is more common in physics than biology.

The last author is also usually the corresponding author. This is the author most likely to be contactable at the same address and able to answer questions across the total content of the paper in 10 years time.

• 1 I generally agree with this pattern in my experience with biology, but corresponding author can also be the first author. Some PIs/advisors have their subordinates/students do the legwork of submitting, others, prefer to be the corresponding author. –  Richard Erickson Commented May 30 at 14:04
• @RichardErickson I think you may be confusing the author who submits the article with the "corresponding author" who is going to be responsible for the work and future correspondence. You can submit on behalf of the corresponding author, and I often have my senior graduate students do this. That is not to "pawn off work", it is actually an important skill they have to learn if they intend to remain in academia. –  R1NaNo Commented May 30 at 15:12
• 1 @RichardErickson, yes, I've also seen this happen. I've also seen people use corresponding author to mark "joint last author" type situations. But last author being corresponding is most common. –  Ian Sudbery Commented May 30 at 22:29
• 1 Mind that the term corresponding author is used in two distinct ways in different fields. It can refer to the author who handles the submission or to the author who handles correspondence after submission. For details see this question of mine. (CC @RichardErickson) –  Wrzlprmft ♦ Commented May 31 at 8:07
• 1 @aqualone I'd say it probably is less common. Most biology project need ongoing reagent costs beyond equipment. Plus the biggest cost is salary. That doesn't mean people should get authorship just for funding. But generally the person getting the funding has official responsibility for the conduct of people on the project. Still, this is one of the situation is one a postdoc would be the PI for a particular project. –  Ian Sudbery Commented May 31 at 14:43

In chemistry/nanoscience/materials science/applied physics, last author with * is the corresponding author and main-PI. You can have multiple PIs with * for collaborative works, and they appear typically in order of contribution at the end of the author list (the last being the project leader). This goes out the window when people do alphabetical which is less common but still done.

• 2 Applied physics is not really a field with a homogeneous culture. I have published many papers in what can be considered applied physics where this did not apply: I was the first author, not the PI, had an asterisk next to my name, and was the corresponding author in both senses of that term . –  Wrzlprmft ♦ Commented May 31 at 8:08

If there is one default convention in condensed matter physics*, it is that the (main) PI is the last author. Many projects may involve multiple PIs, who then tend to collectively be at the end of the author list. In those cases, the precise order can be a matter of politics, or done according to level of involvement. If a postdoc is listed as last author (which seems to happen most often from European research groups?), I would expect them to have had some kind of supervisory role. Last authorships can indeed count more depending on career status, making them more desirable for some authors.

As for who conceived of the project, it is highly variable and cannot be reliably deduced from the author list. For big-budget projects it's most often the PI, but for specific papers it can often be a student or postdoc who had a specific idea for further investigation. Perhaps that is particularly prevalent in theory work. Or it could be that another PI had the idea, but not the expertise**, time or resources to carry out the project. In such cases, depending on the distribution of work, the idea-haver might go anywhere in the author list (or even the acknowledgments). That said, junior people are often motivated to work on their own research ideas so it could well be that the first or second author is the one who was actually driving the project.

*Especially mathematical physics work in the condensed matter context sometimes uses alphabetical order, which is ignored here.

**Commonly seen in experiment-theory collaborations, for example.

In medical research, there are guidelines by the International Committee of Medical Journal Editors for what are the responsibilities and meaning of authorship Basically, it agrees with some of the descriptions already in the answers above: The one who contributed the most for the realization of the research presented in the paper goes in front, while the PI or postdoc (little PI ;-) ) is at the end. Usually the last author conceptualized the research developed and presented in the paper.

About the discussion with the corresponding author: This is the person that will answer ANY question regarding the research presented, including files used for images, code for data analysis, ethics grant documentation for animal or human research, etc. I hope this helps you to see the variability in fields.

I am in the social sciences, and from what I have seen - and experienced myself - thus far, the last author of a lab-driven project/paper tends to be the lab P.I.

We use the ordering of authors to denote contribution. The first author did the lion's share of the work and is the communicating author. From there it's declining contribution or specialist contribution (such as preparation of maps... I'm a Geographer). The last author contributed the least relative to the others. By least, I don't mean of little importance. Everyone plays an important role hence they are acknowledged. It is just that these roles and their contribution to the publication are different. In this model there are no freeloaders who are named without contributing. Having discussions at the outset of the writing is critical as this sets the stage for who does what and how people will be acknowledged etc. If roles change, we discuss this openly. Typically, we share responsibilities and hence where people are acknowledged across a series of outputs. I'll lead this one while you do other things... You lead this one while I do other things etc. This model is particularly good when co-publishing with PHD candidates as it provides a framework for them to understand their role and what they have to deliver while socialising them in an open and collegial publishing approach. I hope this helps you 🙂

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Guidance on authorship in scholarly or scientific publications, general principles.

The public’s trust in and benefit from academic research and scholarship relies upon all those involved in the scholarly endeavor adhering to the highest ethical standards, including standards related to publication and dissemination of findings and conclusions.

Accordingly, all scholarly or scientific publications involving faculty, staff, students and/or trainees arising from academic activities performed under the auspices of Yale University must include appropriate attribution of authorship and disclosure of relevant affiliations of those involved in the work, as described below.

These publications, which, for the purposes of this guidance, include articles, abstracts, manuscripts submitted for publication, presentations at professional meetings, and applications for funding, must appropriately acknowledge contributions of colleagues involved in the design, conduct or dissemination of the work by neither overly attributing contribution nor ignoring meaningful contributions.

Financial and other supporting relationships of those involved in the scholarly work must be transparent and disclosed in publications arising from the work.

Authorship Standards

Authorship of a scientific or scholarly paper should be limited to those individuals who have contributed in a meaningful and substantive way to its intellectual content. All authors are responsible for fairly evaluating their roles in the project as well as the roles of their co-authors to ensure that authorship is attributed according to these standards in all publications for which they will be listed as an author.

Requirement for Attribution of Authorship

Each author should have participated sufficiently in the work to take public responsibility for its content. All co-authors should have been directly involved in all three of the following:

• planning and contribution to some component (conception, design, conduct, analysis, or interpretation) of the work which led to the paper or interpreting at least a portion of the results;
• writing a draft of the article or revising it for intellectual content; and
• final approval of the version to be published.  All authors should review and approve the manuscript before it is submitted for publication, at least as it pertains to their roles in the project.

Some diversity exists across academic disciplines regarding acceptable standards for substantive contributions that would lead to attribution of authorship. This guidance is intended to allow for such variation to disciplinary best practices while ensuring authorship is not inappropriately assigned.

Lead Author

The first author is usually the person who has performed the central experiments of the project. Often, this individual is also the person who has prepared the first draft of the manuscript. The lead author is ultimately responsible for ensuring that all other authors meet the requirements for authorship as well as ensuring the integrity of the work itself. The lead author will usually serve as the corresponding author.

Co-Author(s)

Each co-author is responsible for considering his or her role in the project and whether that role merits attribution of authorship. Co-authors should review and approve the manuscript, at least as it pertains to their roles in the project.

External Collaborators, Including Sponsor or Industry Representatives

Individuals who meet the criteria for authorship should be included as authors irrespective of their institutional affiliations. In general, the use of “ghostwriters” is prohibited, i.e., individuals who have contributed significant portions of the text should be named as authors or acknowledged in the final publication. Industry representatives or others retained by industry who contribute to an article and meet the requirements for authorship or acknowledgement must be appropriately listed as contributors or authors on the article and their industry affiliation must be disclosed in the published article.

Acknowledgements

Individuals who do not meet the requirements for authorship but who have provided a valuable contribution to the work should be acknowledged for their contributing role as appropriate to the publication.

Courtesy or Gift Authorship

Individuals do not satisfy the criteria for authorship merely because they have made possible the conduct of the research and/or the preparation of the manuscript. Under no circumstance should individuals be added as co-authors based on the individual’s stature as an attempt to increase the likelihood of publication or credibility of the work. For example, heading a laboratory, research program, section, or department where the research takes place does not, by itself, warrant co-authorship of a scholarly paper. Nor should “gift” co-authorship be conferred on those whose only contributions have been to provide, for example, routine technical services, to refer patients or participants for a study, to provide a valuable reagent, to assist with data collection and assembly, or to review a completed manuscript for suggestions. Although not qualifying as co-authors, individuals who assist the research effort may warrant appropriate acknowledgement in the completed paper.

Senior faculty members should be named as co-authors on work independently generated by their junior colleagues only if they have made substantial intellectual contributions to the experimental design, interpretation of findings and manuscript preparation.

Authorship Disputes

Determinations of authorship roles are often complex, delicate and potentially controversial. To avoid confusion and conflict, discussion of attribution should be initiated early in the development of any collaborative publication. For disputes that cannot be resolved amicably, individuals may seek the guidance of the dean of their school or the cognizant deputy provost in the Faculty of Arts & Sciences.

Disclosure of Research Funding and Other Support

In all scientific and scholarly publications and all manuscripts submitted for publication, authors should acknowledge the sources of support for all activities leading to and facilitating preparation of the publication or manuscript, including, but not limited to:

• grant, contract, and gift support;
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Correspondence

Author Sequence and Credit for Contributions in Multiauthored Publications

* To whom correspondence should be addressed. E-mail: [email protected]

• Michael E Hochberg,
• Tatyana A Rand,
• Vincent H Resh,
• Jochen Krauss
• Teja Tscharntke, 
• Michael E Hochberg, 
• Tatyana A Rand, 
• Vincent H Resh, 

Published: January 16, 2007

• https://doi.org/10.1371/journal.pbio.0050018
• Reader Comments

Citation: Tscharntke T, Hochberg ME, Rand TA, Resh VH, Krauss J (2007) Author Sequence and Credit for Contributions in Multiauthored Publications. PLoS Biol 5(1): e18. https://doi.org/10.1371/journal.pbio.0050018

Copyright: © 2007 Tscharntke et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: The authors received no specific funding for this article.

Competing interests: The authors have declared that no competing interests exist.

The increasing tendency across scientific disciplines to write multiauthored papers [ 1 , 2 ] makes the issue of the sequence of contributors' names a major topic both in terms of reflecting actual contributions and in a posteriori assessments by evaluation committees. Traditionally, the first author contributes most and also receives most of the credit, whereas the position of subsequent authors is usually decided by contribution, alphabetical order, or reverse seniority. Ranking the first or second author in a two-author paper is straightforward, but the meaning of position becomes increasingly arbitrary as the number of authors increases beyond two. Criteria for authorship have been discussed at length, because of the inflationary increase in the number of authors on papers submitted to biomedical journals and the practice of “gift” authorship [ 3 , 4 ], but a simple way to determine credit associated with the sequence of authors' names is still missing [ 4–7 ] ( http://www.councilscienceeditors.org ).

The situation in our area of research—the ecological and environmental sciences—has changed in recent years. Following informal practices in the biomedical sciences, the last author often gets as much credit as the first author, because he or she is assumed to be the driving force, both intellectually and financially, behind the research. Evaluation committees and funding bodies often take last authorship as a sign of successful group leadership and make this a criterion in hiring, granting, and promotion. This practice is unofficial, and hence not always followed, meaning that sometimes last authors “mistakenly” benefit when they actually are not principal investigators. Moreover, there is no accepted yardstick in assessing the actual contribution of a group leader to given scientific publications [ 8 , 9 ], so interpretation of author sequence can be like a lottery. Hence, one really does not know if being last author means that the overall contribution was the most or least important.

Although reducing evaluation of authors' complex contributions to simple metrics is regrettable, in reality it is already in practice in most evaluation committees. Hence, in our opinion, we need a simple and straightforward approach to estimate the credit associated with the sequence of authors' names that is free from any arbitrary rank valuation. In multiauthored papers, the first author position should clearly be assigned to the individual making the greatest contribution [ 4–6 ], as is common practice. However, authors often adopt different methods of crediting contributions for the following authors, because of very different traditions across countries and research fields, resulting in very different criteria that committees adopt to quantify author's contributions [ 8 , 9 ]. For example, some authors use alphabetical sequence, while others think that the last author position has great importance or that the second author position is the second most important. Still others detail each author's contribution in a footnote.

We suggest that the approach taken should be stated in the acknowledgements section, and evaluation committees are asked to weigh the contribution of each author based on the criteria given by the authors. This would make reviewers aware that there are different cultures to authorship order. The usual and informal practice of giving the whole credit (impact factor) to each author of a multiauthored paper is not adequate and overemphasises the minor contributions of many authors ( Table 1 ). Similarly, evaluation of authors according to citation frequencies means often overrating resulting from high-impact but multiauthored publications. The following approaches may be identified.

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Comparison of the Credit for Contributions to This Paper under the Four Different Models Suggested in the Text

https://doi.org/10.1371/journal.pbio.0050018.t001

(1) The “sequence-determines-credit” approach (SDC). The sequence of authors should reflect the declining importance of their contribution, as suggested by previous authors [ 4–6 ]. Authorship order only reflects relative contribution, whereas evaluation committees often need quantitative measures. We suggest that the first author should get credit for the whole impact (impact factor), the second author half, the third a third, and so forth, up to rank ten. When papers have more than ten authors, the contribution of each author from the tenth position onwards is then valuated just 5%.

(2) The “equal contribution” norm (EC). Authors use alphabetical sequence to acknowledge similar contributions or to avoid disharmony in collaborating groups. We suggest that the contribution of each author is valuated as an equal proportion (impact divided by the number of all authors, but a minimum of 5%).

(3) The “first-last-author-emphasis” norm (FLAE). In many labs, the great importance of last authorship is well established. We suggest that the first author should get credit of the whole impact, the last author half, and the credit of the other authors is the impact divided by the number of all authors [as in (2)].

(4) The “percent-contribution-indicated” approach (PCI). There is a trend to detail each author's contribution (following requests of several journals) [ 7 ]. This should also be used to establish the quantified credit.

The SDC approach (as a new suggestion), the EC norm (alphabetical order), the FLAE norm, and the PCI approach may be combined (e.g., FLAE and SDC), but need to be explicitly mentioned in the acknowledgements.

Our suggestion of explicit indication of the method applied, including the simple method of weighing authors' rank in publications in a quantitative way, will avoid misinterpretations and arbitrary a posteriori designations of author contributions. Multidisciplinary scientific collaboration indeed must be encouraged, but we need to avoid misinterpretations so that current and future scientific communities can evaluate author contributions.

Acknowledgments

We applied the SDC approach for the sequence of authors. We are grateful for the stimulating discussions and comments by Jan Bengtsson, Charles Godfray, Bradford A. Hawkins, Christian Körner, William F. Laurance, Bernhard Schmid, Wim van der Putten, and Louise Vet.

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Article Contents

How it began: the digitization of consumer research practice, how it’s going: the democratization of powerful ai tools, where it’s going: the human adoption of ai in research, will we be the last human editors of jcr .

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Bernd Schmitt, June Cotte, Markus Giesler, Andrew T Stephen, Stacy Wood, Will We Be the Last Human Editors of JCR ?, Journal of Consumer Research , Volume 51, Issue 3, October 2024, Pages 451–454, https://doi.org/10.1093/jcr/ucae053

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Early in our editorial tenure, we enjoyed an animated discussion of the expanding potential of artificial intelligence (AI). Bernd Schmitt wondered aloud if he would be the last human Editor-in-Chief at JCR to the (almost) universal eye-rolling of the other editors. That was in 2021. But in 2024, the question seems more prescient than ridiculous.

The quick and easy answer is, of course not . There is a new human editorial team whose tenure runs from 2025 to 2028, and commitments will be honored.

However, the long answer is considerably more difficult and is the focus of this editorial. Thinking through the ways that we utilize AI in the creation, review, and publication of consumer research requires a specificity of analysis that goes beyond a polarized black-or-white approach. We see essays on the topic that take a simple yes (“Welcome to our robot future!”) or no (“Robots in research are a sign of the end-times”) viewpoint. But increasingly, scholars must consider how human effort and AI can combine in productive and responsible ways to enhance the quality, efficiency, and accessibility of our work. Here, we offer a brief analysis specific to consumer research.

It has been decades since the Internet and other technologies changed the way we do research. We no longer sit among the library stacks or borrow colleagues’ journals (and tap into their human memories) to find papers for our literature reviews. This has been beneficial. We access journals easily from any location, we can search for work that is obscure or forgotten, we search for literature in adjacent fields, and it all takes so much less time and less paper than it did before. What we lost was some of the human element—asking colleagues for ideas, browsing the library shelves, attending conference talks just to see what papers the speakers referenced. There was serendipity and magic in crafting a literature review, and it is easy to feel nostalgic for those times (at least for those of us who remember). Yet not every scholar had access to the colleagues, the libraries, and the conference circuit, and so digital technology has operated as a game-changer, making consumer research more widely accessible.

Similarly, we have witnessed the rise of digital sources for data. We can survey and experiment with “real consumer” populations using online research panels, accessing research participants from all over the world. Digital tools also expand the reach of qualitative research, allowing for participants to respond in situ via prompts on their phones, to record their experiences, and to provide a richer collage of informational modalities. The online world of human communities provides opinions, reviews, sales pitches, influencer behaviors, and countless other forms of consumer and seller information that can be scraped, sorted, and analyzed using increasingly sophisticated machine learning tools. In each of these situations, the consumer research community has helped promote, instruct, and caution other community members about how these data sources can be best accessed and used. Over time, new digital sources have been adopted and adapted through the market forces of publication.

And, without doubt, we use digital tools like email, instant messaging, and video software programs to communicate easily and at low cost with colleagues around the world. An entire editorial could be devoted to the benefits and costs of this transition from working only with colleagues within your university’s department to being able to work with anyone, anywhere.

While many digital advances have emerged and evolved over time, affecting our lives as consumer researchers, academics, and broadly as people, the recent widespread emergence of generative AI (GenAI), particularly large language models (LLMs) such as OpenAI’s ChatGPT, feels different. Just two years ago, many scholars had not yet tried LLMs themselves and did not know how to approach it with their students, let alone in their research practice. The question then was, ‘should we embrace or exclude GenAI?’ Now, it is a question of how we embrace it in ways that make our work better and more meaningful. Consider how GenAI can be used in each stage of a research project.

Ideation: Idea Creator versus Idea Elaborator

Current models of GenAI can be asked to generate new research ideas by assessing gaps in the extant literature. Because the relevant literature for many consumer researchers is quite large at this stage in our field’s development and because we are also considering adjacent fields given the inherently cross-disciplinary nature of consumer research, AI can exceed human abilities around this task. Perhaps AI-generated ideas could also be more applicable and more actionable because they can include both academic literatures and industry publications in their codex. So this could be helpful to researchers who want access to industry executives. GenAI may also be used to elaborate on human-generated research questions. Here, the ability of AI to search vast online sources may uncover related research questions, real-world stakeholders who ask the question, or cross-disciplinary sources relevant to the question. Many issues arise when we consider AI as an idea creator or an idea elaborator. Should scholars be required to disclose when AI was used in either of these instances? Should AI be listed as a coauthor when used as an idea creator? Should different AI sources be triangulated to improve information accuracy? Ethics committees may say yes and no to these questions, but our field continues to evolve, and we too need to debate these and other questions in our community.

Conceptualization: Hypothesis Generator versus Hypothesis Validator

Researchers can use carefully crafted prompts to find papers for their literature review, summarize these papers, and offer hypotheses that logically follow from that summary. In generating hypotheses, AI is becoming increasingly better at performing synthesizing and conceptual tasks previously considered to be defining traits of human scholars. When will GenAI outperform human conceptual creativity? We imagine that GenAI will first be used as a hypothesis validator, one that can effectively draw out evidence across published studies. However, as GenAI improves, how will it step into creative roles? We expect that doctoral programs will have courses dedicated to the effective use of AI in conceptual development and hypothesis generation. AI-generated or AI-elaborated hypotheses may be very helpful to researchers (and potentially minimize costs of unsuccessful projects) by steering us away from studies where hypotheses are either not novel or not logistically consistent.

Data Collection and Analysis: Data Collector and Analyst versus Data and Analysis Recommender

During data collection, researchers can use GenAI to create data through silicon samples and synthetic datasets. For example, creating well-designed digital personas allows marketers to create synthetic, yet insightful, interview data. But should academic researchers do that? There has been a flurry of research investigating whether GenAI can replicate human findings, whether a small subsample of humans will do, or whether we can do original research using no humans at all. Researchers could also use GenAI-created content not only for pretests and pilot studies, assessing survey items and creating stimuli, but also in the actual studies; for example, GenAI (e.g., DALL-E, RUNWAY) excels at creating verbal, pictorial, and video stimuli. But, will the rational “right” answer AI produces reflect what actual consumers (with all our biases) would answer? These and other issues remain significant, but the accuracy and relevance of LLMs are rapidly improving. While LLMs seem reasonably proficient at generating themes in qualitative data (largely because they are language-based), these systems still lack advanced quantitative skills. We anticipate that soon the data collection and analysis phase of our research could be fully automated: from procedures and stimuli to data collection and analysis. But should it be?

Writing: Co-Writer versus Writing Assistant

Should GenAI help co-write one’s own scholarly work or not is a very timely and pressing question. Even now, scholars can use a collection of careful prompts in ChatGPT to write reasonable sounding analytical narratives. The quality of this writing has improved dramatically in recent times and is expected to improve at even higher rates. Yet, this particular use of AI has created the strongest pushback among academics. For those whose superlative (and often hard-won) skills in writing have conferred success, using GenAI to draft a manuscript may feel like cheating. For those whose native language is not English, it may feel like empowering and equalizing. And in universities where resources are not abundant, significantly reducing the time that scholars spend writing up completed studies is a material saving. In many fields, and we argue that consumer research is one of them, the goal of most manuscripts is to offer straightforward, accurate, and purposeful language, not boundary-pushing creative or emotive prose. Using AI as a writing assistant, however, seems less daunting. AI can take existing passages and edit them to match the style of different journals and avoid errors of grammar and spelling effectively and efficiently. Journals are publishing policies on the use of GenAI in writing, and we imagine that many will revise these policies as norms change.

Publishing: Editor versus Editorial Manager

As a journal, we must also consider how far GenAI will replace human editors, reviewers, and publishing managers. To what extent is the title of this editorial a future fact or a foolish fantasy? With several years of editorial experience in a quickly evolving landscape, we believe that several common editorial tasks could potentially be “outsourced” to AI. First, JCR receives large numbers of submissions. Many are not suitable for review. The job of determining and communicating desk-rejection decisions could be a trainable task for GenAI. A more complex, and arguably subjective, editorial task is determining whether the paper has the potential to make a strong theoretical or substantive contribution. Would an effectively trained AI make these decisions more consistently and equitably? The selection of AEs and reviewers could certainly be more efficiently done by AI; currently editors rely on their overtaxed memories to find the most appropriate reviewers while, at the same time, trying their best to avoid conflicts of interest. It is hard to imagine GenAI as reviewers. After all, humans have the nuance, instinct, and expertise to judge research. At the same time, however, human reviewers can be biased and territorial, forget the criteria of the journal or submission type, use faulty statistical heuristics, have pet peeves, and may respond harshly to unfamiliar ideas. If there is disclosure of the use of AI, will reviewers be influenced by such disclosures and make inferences about the work based on the use of AI? Conversely, will authors respond to AI reviewers more (or less) effectively than to human reviewers? Likewise, when reviews are completed, could GenAI produce the AE report? Could it synthesize the reviews, offer a realistic path toward publication, and make valid recommendations to the editor? Could it make the ultimate editorial decision? With learning, GenAI might be able to make increasingly accurate assessments of what the most likely editorial decision is. But editorships come with the call to chart a strategic course and sometimes that means going somewhere new. AI makes its decisions based on its training data—executing a novel strategic vision may not be its strong suit.

Like any innovation, the tasks we assign to GenAI will likely begin with supporting roles like idea elaborator, hypothesis validator, data/analysis recommender, writing assistant, and editorial manager. But before very long, scholars will experiment with defining roles like idea creator, hypothesis generator, data collector, data analyst, writer, and editor. How we think about the use of GenAI in 21st century research will depend on many of the same factors studied in the 1960–70s when computers and other technologies were transforming 20th century scholarship from its 19th century forebears. Here are a few factors that we think are important to consider.

Lowered Costs

Every A-level business journal publication costs the author’s university hundreds of thousands of USDs. The largest contributor to this damning calculation is the professor’s salary. One way to significantly shrink this number is by increasing productivity. If GenAI is fundamentally beneficial for tasks that take a lot of time when done by humans, an increase in productivity is possible. Imagining increasing productivity as we work now is a stress-inducing vision. But with a radical change in how the most time-intensive aspects of research (making sure our ideas are novel, honing a hypothesis, gathering data, and writing the manuscript) are conducted, perhaps the financial burden of research will ease.

Equity and Accessibility to Conduct Research

As JCR works to embrace a more global community, we see that there are some privileges associated with being part of an English-speaking, North American, Tier 1 research university. The JCR Editorial Review Board disproportionately reflected this for many years and is still not where it could be. Using GenAI can bring researchers who lack some of these resources to a more equitable level. AI can free time, access the world’s publications, read top scholars’ online opinions, collect data, analyze data, and write a manuscript in excellent English and “the style of JCR .” AI-assisted review and publication of works could be fairer by avoiding in-group signals and reviewer idiosyncrasies. However, an AI-assisted review process has many issues. Poorly done research destined for rejection could be added to the training data, and authors (and participants) need privacy protection. Perhaps future authors will be asked to grant permission for an AI-assisted review process.

Researcher Satisfaction and Morale

It is not clear how the increasing use of GenAI in consumer research will affect researcher satisfaction and morale. We think of our field as a fun one—full of interesting topics, methodologies, and personalities. Unlike other fields, our endeavors are not solo efforts to write a book, nor giant lab efforts where authorship is a cast of thousands. Some researchers may find AI to be the help that makes life/work balance possible. Some researchers may find that using AI robs the research process of a handmade authenticity or the social serendipity of collegial input. Productivity will take on a new signal and it is hard to tell now if it will increase or decrease scholarly prestige.

The Likelihood of Segmentation

GenAI offers enough of an existential disruption to traditional processes that we expect different scholars will have different preferences about the best way to do “real research.” And, as consumer researchers, we all should expect groups of like-minded “consumers” (academics) to cluster together. Segmentation is not a problem to be solved, but a sustainable reality. Consider the current world of farming. Some consumers appreciate the low cost and accessibility of produce from factory farming that utilizes cutting-edge technology to make harvests cheap and reliable. Others happily pay higher prices for produce from traditional small-batch farms, where local harvests are smaller and more variable. For all consumers, it is important that both local heirloom tomatoes and low-priced hothouse tomatoes sit on the shelf together. For those privileged to afford it, the heirloom tomatoes will be preferred—as long as the small-batch handmade approach yields better quality. When that changes, norms may shift.

Ultimately, the use of GenAI within research is not only up to individual researchers. New AI innovations will be impacted by the regulatory environment (human editors, policy makers, etc.), competition (other authors), and the development and capabilities of the technology. We have offered some possible scenarios, and we believe that the field should now have more conversations about AI. As has always been the case at JCR , we will rely on our community of scholars to suggest, consider, deconstruct, adapt, tinker, and test the ways that we can best use AI to improve our research.

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• v.5(1); 2007 Jan

Author Sequence and Credit for Contributions in Multiauthored Publications

A transparent, simple, and straightforward approach that is free from any arbitrary rank valuation is required to estimate the credit associated with the sequence of authors' names on multiauthored papers.

The increasing tendency across scientific disciplines to write multiauthored papers [ 1 , 2 ] makes the issue of the sequence of contributors' names a major topic both in terms of reflecting actual contributions and in a posteriori assessments by evaluation committees. Traditionally, the first author contributes most and also receives most of the credit, whereas the position of subsequent authors is usually decided by contribution, alphabetical order, or reverse seniority. Ranking the first or second author in a two-author paper is straightforward, but the meaning of position becomes increasingly arbitrary as the number of authors increases beyond two. Criteria for authorship have been discussed at length, because of the inflationary increase in the number of authors on papers submitted to biomedical journals and the practice of “gift” authorship [ 3 , 4 ], but a simple way to determine credit associated with the sequence of authors' names is still missing [ 4–7 ] ( http://www.councilscienceeditors.org ).

The situation in our area of research—the ecological and environmental sciences—has changed in recent years. Following informal practices in the biomedical sciences, the last author often gets as much credit as the first author, because he or she is assumed to be the driving force, both intellectually and financially, behind the research. Evaluation committees and funding bodies often take last authorship as a sign of successful group leadership and make this a criterion in hiring, granting, and promotion. This practice is unofficial, and hence not always followed, meaning that sometimes last authors “mistakenly” benefit when they actually are not principal investigators. Moreover, there is no accepted yardstick in assessing the actual contribution of a group leader to given scientific publications [ 8 , 9 ], so interpretation of author sequence can be like a lottery. Hence, one really does not know if being last author means that the overall contribution was the most or least important.

Although reducing evaluation of authors' complex contributions to simple metrics is regrettable, in reality it is already in practice in most evaluation committees. Hence, in our opinion, we need a simple and straightforward approach to estimate the credit associated with the sequence of authors' names that is free from any arbitrary rank valuation. In multiauthored papers, the first author position should clearly be assigned to the individual making the greatest contribution [ 4–6 ], as is common practice. However, authors often adopt different methods of crediting contributions for the following authors, because of very different traditions across countries and research fields, resulting in very different criteria that committees adopt to quantify author's contributions [ 8 , 9 ]. For example, some authors use alphabetical sequence, while others think that the last author position has great importance or that the second author position is the second most important. Still others detail each author's contribution in a footnote.

We suggest that the approach taken should be stated in the acknowledgements section, and evaluation committees are asked to weigh the contribution of each author based on the criteria given by the authors. This would make reviewers aware that there are different cultures to authorship order. The usual and informal practice of giving the whole credit (impact factor) to each author of a multiauthored paper is not adequate and overemphasises the minor contributions of many authors ( Table 1 ). Similarly, evaluation of authors according to citation frequencies means often overrating resulting from high-impact but multiauthored publications. The following approaches may be identified.

Comparison of the Credit for Contributions to This Paper under the Four Different Models Suggested in the Text

(1) The “sequence-determines-credit” approach (SDC). The sequence of authors should reflect the declining importance of their contribution, as suggested by previous authors [ 4–6 ]. Authorship order only reflects relative contribution, whereas evaluation committees often need quantitative measures. We suggest that the first author should get credit for the whole impact (impact factor), the second author half, the third a third, and so forth, up to rank ten. When papers have more than ten authors, the contribution of each author from the tenth position onwards is then valuated just 5%.

(2) The “equal contribution” norm (EC). Authors use alphabetical sequence to acknowledge similar contributions or to avoid disharmony in collaborating groups. We suggest that the contribution of each author is valuated as an equal proportion (impact divided by the number of all authors, but a minimum of 5%).

(3) The “first-last-author-emphasis” norm (FLAE). In many labs, the great importance of last authorship is well established. We suggest that the first author should get credit of the whole impact, the last author half, and the credit of the other authors is the impact divided by the number of all authors [as in (2)].

(4) The “percent-contribution-indicated” approach (PCI). There is a trend to detail each author's contribution (following requests of several journals) [ 7 ]. This should also be used to establish the quantified credit.

The SDC approach (as a new suggestion), the EC norm (alphabetical order), the FLAE norm, and the PCI approach may be combined (e.g., FLAE and SDC), but need to be explicitly mentioned in the acknowledgements.

Our suggestion of explicit indication of the method applied, including the simple method of weighing authors' rank in publications in a quantitative way, will avoid misinterpretations and arbitrary a posteriori designations of author contributions. Multidisciplinary scientific collaboration indeed must be encouraged, but we need to avoid misinterpretations so that current and future scientific communities can evaluate author contributions.

Acknowledgments

We applied the SDC approach for the sequence of authors. We are grateful for the stimulating discussions and comments by Jan Bengtsson, Charles Godfray, Bradford A. Hawkins, Christian Körner, William F. Laurance, Bernhard Schmid, Wim van der Putten, and Louise Vet.

Teja Tscharntke is Professor and Tatyana A. Rand is Postdoc with the Agroecology Group, University of Göttingen, Göttingen, Germany. Michael E. Hochberg is Research Director at Centre National de la Recherche Scientifique, University of Montpellier II, Montpellier, France. Vincent H. Resh is Professor at the Department of Environmental Science, Policy and Management, University of California, Berkeley, California, United States of America. Jochen Krauss is Postdoc with the Institute of Environmental Sciences, University of Zurich, Zurich, Switzerland, and the Department of Animal Ecology, Population Ecology, Bayreuth, Germany.

Funding. The authors received no specific funding for this article.

Competing interests. The authors have declared that no competing interests exist.

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House prices react rapidly to rates shocks – BIS paper

Monetary policy transmission stronger in us property market than previously thought, study argues.

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House prices in the US respond far more quickly to surprising rates decisions than was previously thought, the latest working paper from the Bank for International Settlements (BIS) argues.

The authors – Denis Gorea, Oleksiy Kryvtsov and Marianna Kudlyak – say this suggests that the property market constitutes a strong transmission channel for monetary policy.

Their paper, which is based on house price data from 2001 to 2019, observes a strong causal relationship between interest rates and

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