Management impression and bank’s performance with NLP for chairperson’s statement

Tam Phan Huy et al.

European Journal of Government and Economics2025https://doi.org/10.17979/ejge.2025.14.2.11713article
ABDC C
Weight
0.50

What the paper says

Impression management within chairperson’s statements is a prominent area of study, particularly in the banking sector. This research seeks to understand the nuanced strategies banks deploy in these statements to shape stakeholder perceptions regarding their financial performance. Utilizing a mixed-method approach that combines qualitative content analysis with algorithmic techniques, the study applies Natural Language Processing (NLP), including sentiment analysis, topic modeling, word vectorization, and readability scoring to systematically examine chairperson’s statements, using data from 2012 to 2022 of commercial banks in Vietnam. The results revealed that banks facing financial adversities tend to craft strategic narratives to underscore their resilience and adaptability. Crucially, elements such as public visibility and consumer proximity emerged as dominant factors influencing the direction and tone of these narratives. The study underscores the pivotal role of chairperson’s statements in molding and upholding a bank's image. The effectiveness of these statements is contingent upon their alignment with stakeholder expectations and the prevailing market dynamics, providing invaluable insights for investors, bank executives, and regulatory institutions.

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https://doi.org/https://doi.org/10.17979/ejge.2025.14.2.11713

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@article{tam2025,
  title        = {{Management impression and bank’s performance with NLP for chairperson’s statement}},
  author       = {Tam Phan Huy et al.},
  journal      = {European Journal of Government and Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.17979/ejge.2025.14.2.11713},
}

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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.