Reported details
What happened
The work is titled “Artificial Intelligence Enabled Demand Forecasting for Sustainable Fashion Retail” and lists Dr. Sushmaa Mohana Krishnan as its author.
The record identifies the International Journal of Current Engineering and Technology as the venue and gives a publication year of 2026.
The work has DOI 10.14741/ijcet/v.16.4.4 and OpenAlex ID W7204827024.
The publication status is unknown, and the retained evidence contains no abstract, full text, quotation, methods, sample, results, or effect sizes.
Business relevance
Why it matters
Demand forecasting is directly relevant to fashion merchants because inventory decisions affect availability, markdown exposure, and the handling of unsold goods. The supplied record, however, does not establish that this work demonstrated an improvement in any of those areas.
The sustainable-fashion framing makes the topic commercially relevant for sellers balancing product availability with excess inventory concerns, but the evidence does not identify a specific forecasting system, workflow, or sustainability outcome.
The immediate signal is a research topic, not a validated operating recommendation. Merchants should treat it as a prompt for investigation rather than proof that an AI forecasting tool will improve performance.
Editorial perspective
Analysis & judgment
The title suggests a connection between AI-enabled demand forecasting and sustainable fashion retail, but that connection cannot be evaluated from bibliographic metadata alone. Without the paper’s methods or results, sellers cannot judge accuracy, suitability for their category, or operational trade-offs.
For merchants, the practical question is not whether AI forecasting sounds relevant, but whether a specific system can improve decisions using the seller’s own demand history, product lifecycle, returns, promotions, and stock constraints. No such system or evidence is identified in the supplied record.
The record may merit further source checking because it includes a DOI, venue, author, and stable OpenAlex identifier. Until publication status and the underlying content are verified, OpenAlex should be used here as a discovery record rather than as evidence of peer-reviewed validation.
Applicability
Seller impact
Sellers considering forecasting software should compare any vendor claim against their own category-level data and operational goals; this research record alone does not support a purchase or rollout decision.
Fashion businesses with recurring overstock or stockout issues may use the topic to frame a measurement plan, provided they define baseline metrics before testing any forecasting change.
Sustainability claims should remain limited to measurable inventory or waste outcomes that a seller can verify, because the supplied evidence reports no sustainability result.
Action plan
What to do now
- 1
Record the research lead without treating it as validation
nowSave DOI 10.14741/ijcet/v.16.4.4 and OpenAlex ID W7204827024 in the research log, and label the publication status as unknown.
- 2
Define a forecasting baseline
this-weekIf forecasting is a current business priority, document existing accuracy, stockout, markdown, and excess-inventory measures before evaluating an AI-enabled workflow.
- 3
Check the underlying publication before citing conclusions
monitorLook for an authoritative version of the work and verify its publication status and contents before relying on any claimed methods, results, or sustainability benefits.
What not to do yet
- Do not describe this record as peer-reviewed or use it to claim that AI forecasting reduces waste, improves accuracy, or increases retail performance.
- Do not buy, deploy, or publicly promote a forecasting system solely because its approach resembles the topic named in this research record.
Sources & context
Evidence and sources
A source may provide only a headline or summary. Read the evidence scope below. Links and workflow checks are not independent fact verification. Internal confidence values are workflow signals, not probabilities of factual correctness.
- 01Source link
Artificial Intelligence Enabled Demand Forecasting for Sustainable Fashion Retail — unknown — International Journal of Current Engineering and Technology
OpenAlex Ecommerce Research Discovery · Workflow status: single-source
Retrieved: September 3, 2026 at 04:17 a.m. UTC
Bibliographic metadata only; no body, abstract, quotation, or PDF is retained.