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Generation Process and Early Warning Methods of Academic Misconduct A Grounded Theory Analysis Based on Academic Misconduct Cases

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DOI: 10.23977/infkm.2026.070109 | Downloads: 1 | Views: 69

Author(s)

Yang Lei 1

Affiliation(s)

1 Yunnan Open University, Kunming, China

Corresponding Author

Yang Lei

ABSTRACT

Academic misconduct erodes the foundation of academic integrity and seriously threatens the sound operation of the academic ecosystem. Existing studies mostly focus on phenomenon description and governance countermeasures, while lacking in depth logical explanations for the generation mechanism of academic misconduct based on practical data. Taking publicly available research integrity investigation reports, official notices of investigated academic misconduct cases and typical cases as data sources, this paper adopts grounded theory to systematically reveal the generation logic of academic misconduct among researchers, and constructs a generation mechanism model of "situational pressure -individual cognition -behavioral choice -consequence feedback". The study finds that the mutual coupling of imbalanced institutional incentives, regulatory gaps, weakened organizational awareness on the one hand, and individual utilitarian motives and fluke mentality on the other hand constitutes the deep seated inducement of academic misconduct. From the three links of ex ante prevention, in process monitoring and ex post accountability, combined with artificial intelligence and knowledge graph technologies, this paper puts forward an early warning framework covering the whole life cycle of scientific research, so as to provide theoretical support and technical paths for research integrity governance.

KEYWORDS

Academic misconduct; Research integrity; Grounded theory; Behavior generation mechanism; Early warning method

CITE THIS PAPER

Yang Lei. Generation Process and Early Warning Methods of Academic Misconduct A Grounded Theory Analysis Based on Academic Misconduct Cases. Information and Knowledge Management (2026). Vol. 7, No.1, 76-84. DOI: http://dx.doi.org/10.23977/infkm.2026.070109.

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