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Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns

Identification

Public canonical key
doi:10.1007/s43621-026-04243-0
Authors
Mohamed Amin Abdel Gawad Mekheimer · Walid Abdelhalim
Reported year
2026
Reported language
en
Source type
article
First detected
2026-11-09T19:04:47.783686+00:00
Last metadata observation
2026-11-09T19:04:47.783686+00:00
Last HTTP verification
Not checked

Institutions reported by the source

Beni-Suef University

Reported affiliation countries

EG

Documentary abstract — original language

Abstract This study examines how university faculty perceive and navigate the tradeoff between AI-enabled research productivity and the maintenance of academic integrity, a central challenge for sustainable scholarly ecosystems. Using an explanatory sequential mixed-methods design, the study surveyed 478 faculty members across six universities in Upper Egypt and then used 118 individual follow-up interviews to contextualize the quantitative patterns. Descriptively, respondents reported moderate integrity concerns (M = 3.81 on a 1–5 scale) alongside neutral-to-slight endorsement of AI productivity benefits (M = 3.06), indicating that integrity concerns remain salient amid emerging instrumental use. MANOVA revealed small but statistically significant group differences by discipline (eta_p squared = 0.023) and academic rank (eta_p squared = 0.031): early-career and STEM faculty reported comparatively higher AI adoption and stronger productivity orientations, whereas senior and humanities/social-science faculty reported comparatively higher integrity concerns. Theory-guided hierarchical regression showed that institutional context was positively associated with perceived productivity benefits after accounting for discipline, career stage, and AI-use frequency, while AI-use frequency was negatively associated with integrity-risk perceptions in the corresponding associational model. Because AI Adoption & Usage and Productivity Perception were very highly correlated ( r = .914), the results are interpreted as construct-proximate co-variation rather than causal evidence. Harman’s single-factor check did not indicate a single dominant method factor at item level, but common-method inflation remains a limitation. Qualitative findings show that faculty managed this tradeoff through principled resistance, pressure-driven adoption, pragmatic task segmentation, innovation-oriented experimentation, active risk management, and discipline-specific boundary setting. The study supports explicit AI-literacy training, disclosure guidance, and verification frameworks for responsible AI integration in academic publishing.

Identifiers

OPENALEX
W7201857627
DOI
10.1007/s43621-026-04243-0

Documentary context

Documentary family
Scholarship
Source-reported types
article
Natural entities mentioned
Ecosystem

Entity mentions are not evidence of legal recognition. Jurisdiction studied is separate from author affiliation country.

Sources

OpenAlex · Record 1 · Record 2

Documented bibliographic relations

Source-declared references and links; they do not establish legal support or UGLC qualification. Up to 20 outgoing references are displayed.

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  • openalex:w4286238856 · CITES
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0 incoming references within the detected corpus

Documentary field provenance

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Cite this reference

Mohamed Amin Abdel Gawad Mekheimer; Walid Abdelhalim. Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns. 2026. https://doi.org/10.1007/s43621-026-04243-0

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APA
Mohamed Amin Abdel Gawad Mekheimer; Walid Abdelhalim. (2026). Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns. https://doi.org/10.1007/s43621-026-04243-0
Chicago
Mohamed Amin Abdel Gawad Mekheimer; Walid Abdelhalim. Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns. 2026. https://doi.org/10.1007/s43621-026-04243-0
ISO 690
Mohamed Amin Abdel Gawad Mekheimer; Walid Abdelhalim. Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns. 2026. https://doi.org/10.1007/s43621-026-04243-0

UDTR Global Rights of Nature Legal Library. Artificial intelligence in academic publishing and the faculty tradeoff between productivity benefits and academic integrity concerns. Documentary record: https://www.declarationuniverselledesdroitsdelarbre.org/global-rights-of-nature-radar/reference/r-e7da4816bc3a0c5c257ece66db6b2f83/ · Last HTTP verification: not performed

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Field provenance and record version

Version d5e06919078a2a6a · udtr-reference-1.1.2

Title
OpenAlex · source · 2026-11-09T19:04:47.783686+00:00
Authors
OpenAlex · source · 2026-11-09T19:04:47.783686+00:00
Year
OpenAlex · source · 2026-11-09T19:04:47.783686+00:00
Identifiers
OpenAlex · source · 2026-11-09T19:04:47.783686+00:00
Source URL
OpenAlex · source · 2026-11-09T19:04:47.783686+00:00

History tracks record metadata and does not certify the state of the law.

8a32f1519a94287b · 2026-11-09T19:04:47.783686+00:00

9c3f1b99342bfde4 · 2026-11-09T19:04:47.783686+00:00

56376a9c63906201 · 2026-11-09T19:04:47.783686+00:00

d5e06919078a2a6a · 2026-11-09T19:04:47.783686+00:00

Frozen-version metadata

Research dossiers and documentary relations

Beni-Suef University

Mohamed Amin Abdel Gawad Mekheimer

Walid Abdelhalim

Source roles

Discovery source · https://doi.org/10.1007/s43621-026-04243-0

Discovery source · https://openalex.org/W7201857627

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Documentary status

Relevance pending

Library

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