Paper Type
ERF
Abstract
Data breaches impose severe financial and reputational costs, requiring firms to signal accountability and control to restore stakeholder trust. This study examines how post-breach disclosure language functions as a strategic signal shaping investor reaction. Drawing on Signaling Theory, we conceptualize disclosures along a Defensive–Accommodative Continuum and a Cybersecurity Response Disclosure dimension that captures verifiable technical signals. Using a multi-source archival dataset of breaches, we integrate text analytics with event-study methods to assess the effects of breaches on cumulative abnormal returns around breach announcements. Texts from notification letters and SEC filings are analyzed using TF–IDF with Word2Vec-based keyword expansion. We expect defensive language to amplify negative market reactions, while accommodative framing may reduce them. This study advances IS and cybersecurity research by integrating linguistic framing and technical disclosure into a unified signaling framework, offering theoretical and practical guidance for restoring trust and financial stability after a security breach.
Paper Number
1848
Recommended Citation
Majumder, Arindam; Bera, Debalina; and Kim, Dan J., "Is Transparency the Best Policy? The Financial Impact of Post-Breach Disclosure Tone and Strategy" (2026). AMCIS 2026 Proceedings. 39.
https://aisel.aisnet.org/amcis2026/sig_sec/sig_sec/39
Is Transparency the Best Policy? The Financial Impact of Post-Breach Disclosure Tone and Strategy
Data breaches impose severe financial and reputational costs, requiring firms to signal accountability and control to restore stakeholder trust. This study examines how post-breach disclosure language functions as a strategic signal shaping investor reaction. Drawing on Signaling Theory, we conceptualize disclosures along a Defensive–Accommodative Continuum and a Cybersecurity Response Disclosure dimension that captures verifiable technical signals. Using a multi-source archival dataset of breaches, we integrate text analytics with event-study methods to assess the effects of breaches on cumulative abnormal returns around breach announcements. Texts from notification letters and SEC filings are analyzed using TF–IDF with Word2Vec-based keyword expansion. We expect defensive language to amplify negative market reactions, while accommodative framing may reduce them. This study advances IS and cybersecurity research by integrating linguistic framing and technical disclosure into a unified signaling framework, offering theoretical and practical guidance for restoring trust and financial stability after a security breach.
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