Saturday, January 31, 2026

What really happened to Journal of Cleaner Production?


The recent downgrading of Journal of Cleaner Production in the ABDC ranking, from A to C, has triggered a familiar explanation: too many papers. The raw numbers certainly make that reaction understandable. 

Annual output rose from a few hundred papers a decade ago to well over four thousand in recent years. For many observers, volume became the story.

But volume alone is a blunt diagnosis. Plenty of journals have grown without collapsing in reputation. The more interesting question is why scale stopped working as a virtue and started functioning as a negative signal. 

Over the past years there has been a series of conversations in cyberspace ranging from Journal of Cleaner Production tolerating plagiarism to retraction controversies. 

Acacemic scholars concur that the degradation is a correct decision.


But what caused this fall from Journal of Cleaner Production to Journal of Mass Production?

1. Dilution of editorial coherence

In its earlier years, Journal of Cleaner Production had a relatively clear intellectual identity. It sat at the intersection of production systems, environmental impact, and operational improvement. Readers knew roughly what kind of paper belonged there and, just as importantly, what did not.

As the journal expanded, that boundary loosened. Today, the journal hosts work spanning engineering, policy, behavioural science, supply chains, consumer research, ESG reporting, psychology, agriculture, and governance. Individually, many of these papers are defensible. Collectively, they create a problem: the journal no longer communicates a clear centre of gravity.

Ranking bodies and senior scholars tend to penalise journals that feel like repositories rather than curators. When readers cannot easily articulate what a journal is “about”, they struggle to associate it with intellectual leadership. Over time, breadth starts to look like drift, not inclusivity.

The trajectory also points to a failure of editorial leadership, not in intent but in stewardship. Editors are custodians of a journal’s identity, selectivity, and long-term reputation. Allowing output to expand to several thousand papers a year without visibly tightening scope, rejection thresholds, or review governance signalled a loss of strategic control. Rather than actively shaping the field, editorial leadership appeared reactive to submission volume and publisher incentives. In ranking-driven environments, this is read as weakened gatekeeping. When editors stop drawing hard lines, the journal’s brand erodes, and responsibility for that erosion ultimately sits at the top.

2. Uneven review standards at scale

Running a journal that publishes several thousand papers a year is not just a logistical challenge; it is a governance challenge. Editorial decisions are necessarily decentralised across hundreds of associate editors and thousands of reviewers. Even with strong guidelines, consistency becomes fragile.

Small variations matter. One editor may desk-reject aggressively. Another may be more developmental. One reviewer panel may insist on deep theory and robustness. Another may focus mainly on novelty or context. None of this is malicious. But at scale, these variations accumulate into a reputation for unevenness.

Once authors begin to believe that acceptance depends heavily on who handles the paper, perceptions of lowered standards emerge, regardless of actual average quality. Rankings tend to respond to these perceptions rather than auditing individual review files.


The graph shows a striking and sustained rise in the number of papers published, moving from just 231 articles in 2011 to a peak of over 5,300 papers in 2021, before stabilising at a very high level above 4,400 papers per year. This growth did not happen gradually; it accelerated sharply after 2015, coinciding with the journal’s aggressive expansion in scope, special issues, and submission intake. While this scale-up increased visibility and throughput, it also introduced a classic quantity-over-quality problem. At such volumes, maintaining consistent editorial scrutiny, reviewer depth, and theoretical contribution becomes extremely difficult. The signal of selectivity weakens, average contribution becomes more uneven, and the journal begins to resemble a high-capacity outlet rather than a curated intellectual venue. In reputation-based systems like journal rankings, this kind of mass production is not interpreted as productivity, but as dilution, where growth itself becomes a negative quality signal rather than a strength.


3. Citation quality versus citation quantity

High publication volume often brings high total citations. On the surface, this looks positive. But modern journal evaluation looks beyond raw counts.

A large share of papers receiving very low citations, or citations concentrated within a narrow sustainability citation loop, weakens perceived influence. In other words, who cites the journal, and why, starts to matter more than how often it is cited.

When influence is diffuse rather than sharp, a journal can look busy without looking central. This is particularly damaging in ranking systems that rely on peer perception surveys, where senior academics draw on mental shortcuts rather than metric tables.

4. Special issues as a reputational risk multiplier

Special issues were a major growth engine for the journal. They attracted submissions, expanded networks, and allowed topical agility. But they also introduced structural risk.

Guest editors vary widely in experience, selectivity, and ambition. Some special issues are tightly curated and genuinely field-shaping. Others become loose collections of loosely connected papers responding to a fashionable keyword.

Readers rarely differentiate between “regular” and “special issue” quality when forming impressions. A few weak or repetitive special issues can disproportionately damage a journal’s reputation, because they are encountered as blocks rather than isolated papers. At scale, this effect compounds quickly.

5. Field-level saturation and fatigue

Sustainability research has grown explosively. With that growth has come repetition: similar models, recycled constructs, minor contextual tweaks, and limited theoretical advancement. This is not unique to one journal, but journals that publish at scale absorb more of this saturation.

When a journal becomes the primary outlet for incremental sustainability work, it inherits the field’s fatigue. Reviewers and readers start to associate the title with “more of the same”, even when genuinely strong papers are present.

In mature fields, journals are judged less on volume and more on their ability to filter, prioritise, and say no. Failure to do so signals declining gatekeeping power, which ranking bodies tend to interpret as declining quality.


Pulling it together

None of these factors alone explains the downgrade. Together, they form a coherent story. This is not a moral failure or a sudden collapse. It is a structural outcome of rapid growth in a reputation-based system.

For Elsevier, the challenge is not to defend past growth, but to demonstrate renewed editorial control. For authors, the lesson is that journal labels lag reality. And for other journals watching closely, the message is clear: expansion without curation is not neutral. It is a strategic choice with long-term reputational costs.


Thursday, January 1, 2026

Are fake citations really an AI problem?

 


The recent case reported by Retraction Watch involving fake references in the Journal of Academic Ethics is easy to frame as a generative AI problem. The corresponding author openly admitted that ChatGPT was used to generate the references, and nearly two-thirds of them turned out to be fabricated. That admission makes the story feel settled. AI hallucinated citations, the journal missed them, and the system failed. But that conclusion is too neat, and ultimately misleading.

What this case really shows is not that generative AI creates fake citations, but that authors chose not to verify them. Large language models do not submit manuscripts, format reference lists, or click “submit” on journal portals. Humans do. In this article, the research itself was described as real and based on real data. The failure occurred at the most basic scholarly task: checking whether cited work exists. That is not a new problem introduced by AI. It is an old one, now made more visible and easier to scale.

The details uncovered by Erja Moore make this clear. The references were not random strings. Many looked plausible. Some cited real authors writing on similar topics, but paired them with nonexistent article titles. Others listed real journals but incorrect volumes, issues, or page numbers that pointed to entirely different papers. These are the kinds of errors that slip through when references are copied uncritically, padded to satisfy reviewers, or assembled to signal familiarity with a field rather than to support an argument. Long before generative AI, scholars were already citing papers they had not read.

The uncomfortable irony is that this happened in an ethics journal, and that many fabricated references pointed to another flagship ethics outlet, the Journal of Business Ethics. But the deeper issue is not hypocrisy. It is institutional complacency. Peer reviewers typically do not check references line by line. Editors rarely audit citation accuracy unless something triggers suspicion. Publishers rely on trust, not verification, because the system was built for a slower, smaller volume of submissions. Generative AI did not break that system. It exposed how fragile it already was.

So no, generative AI is not solely responsible for fake citations. It is an accelerant, not the fire. The responsibility still lies with authors to verify sources, with editors to enforce basic standards, and with publishers to adapt integrity checks to a world where plausible text can be generated instantly. Blaming AI alone is convenient, but it lets the academic community avoid a harder conversation: that citation misconduct has always existed, and we simply no longer have the excuse of not seeing it.