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Moral Decision Training Platform AI and Psychological Modeling for Information Management

Jianming Zhang & Shu Zhang

Information Resources Management Journal2026https://doi.org/10.4018/irmj.404755article
AJG 1ABDC C
Weight
0.50

What the paper says

The integration of artificial intelligence (AI) into organizational decision-making has turned AI-driven moral judgment into a strategic information resource, while its effective management remains underexplored. In this study, the authors constructed a moral decision-making training platform based on psychological modeling, focusing on three dimensions: responsibility attribution, intention cognition, and decision rationality. By analyzing human attitudes toward AI behavior in organizational scenarios, the authors built a recursive psychological model and verified it with empirical data, where the dynamic weight neural model achieved a high goodness of fit (R2 = 0.82). The platform realizes adaptive feedback management of moral decision information resources, which helps optimize organizational decision efficiency and ethical governance. The results show that the platform's application is scenario dependent, and its long-term value needs further verification in diverse organizational contexts. This study provides a practical tool for information resource management in the ethical AI era.

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https://doi.org/https://doi.org/10.4018/irmj.404755

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@article{jianming2026,
  title        = {{Moral Decision Training Platform AI and Psychological Modeling for Information Management}},
  author       = {Jianming Zhang & Shu Zhang},
  journal      = {Information Resources Management Journal},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.4018/irmj.404755},
}

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Moral Decision Training Platform AI and Psychological Modeling for Information Management

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.