Does Standardized Manuscript Structure Aid Publishing? Evidence from IMRD on Acceptance, Visibility, and Impact

The adoption of standardized manuscript structures has become widespread in scholarly publishing, with the IMRD format (Introduction, Methods, Results, and Discussion) promoted to improve clarity and transparency. Despite its prevalence, empirical evidence on its effects on publication outcomes remains limited. This study examines the impact of IMRD structure on editorial acceptance, citation impact, and article downloads using a longitudinal dataset of 716 manuscripts (2016–2025). Logistic regression and zero-inflated models are employed to account for different outcome types and data characteristics. Results show that IMRD is strongly associated with higher editorial acceptance rates, suggesting that standardized formats facilitate evaluation. However, no significant effect is found on citation counts once overdispersion and excess zeros are considered. In contrast, IMRD reduces the likelihood of zero downloads, indicating improved initial visibility. Overall, manuscript structure influences editorial decisions and early dissemination but does not directly affect long-term scientific impact. These findings highlight the importance of distinguishing between acceptance, visibility, and influence, and suggest that while IMRD improves accessibility, it does not substitute for research quality.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-07-16
DOI
https://doi.org/10.5281/zenodo.21399810
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Does Standardized Manuscript Structure Aid Publishing? Evidence from IMRD on Acceptance, Visibility, and Impact

Fausto Jacome Lopez
Zenodo (CERN European Organization for Nuclear Research)
scientometrics and bibliometrics research
article

Does Standardized Manuscript Structure Aid Publishing? Evidence from IMRD on Acceptance, Visibility, and Impact

Fausto Jacome Lopez
article en

Abstract

The adoption of standardized manuscript structures has become widespread in scholarly publishing, with the IMRD format (Introduction, Methods, Results, and Discussion) promoted to improve clarity and transparency. Despite its prevalence, empirical evidence on its effects on publication outcomes remains limited. This study examines the impact of IMRD structure on editorial acceptance, citation impact, and article downloads using a longitudinal dataset of 716 manuscripts (2016–2025). Logistic regression and zero-inflated models are employed to account for different outcome types and data characteristics. Results show that IMRD is strongly associated with higher editorial acceptance rates, suggesting that standardized formats facilitate evaluation. However, no significant effect is found on citation counts once overdispersion and excess zeros are considered. In contrast, IMRD reduces the likelihood of zero downloads, indicating improved initial visibility. Overall, manuscript structure influences editorial decisions and early dissemination but does not directly affect long-term scientific impact. These findings highlight the importance of distinguishing between acceptance, visibility, and influence, and suggest that while IMRD improves accessibility, it does not substitute for research quality.

Zenodo (CERN European Organization for Nuclear Research)
Escuela Superior Politecnica del Litoral (EC)
Quality Education
Openalex Percentile: Top 8%
scientometrics and bibliometrics research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.