Classifying the contents of cybersecurity risk disclosure through textual analysis and factor analysis

Arion Cheong, Kyunghee Yoon, Soohyun Cho, Won Gyun No

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Cybersecurity has garnered much attention due to the increasing frequency and cost of cybersecurity incidents and has become a significant concern for organizations and governments. Regulators such as the Securities and Exchange Commission (SEC) have also shown an interest in cybersecurity and the quality of cybersecurity risk disclosures. This paper examines the informativeness of cybersecurity risk disclosures when cybersecurity incidents or related internal control weaknesses are reported. In particular, we propose a quantitative methodology, which is a combination of textual analysis and factor analysis, for classifying cybersecurity risk disclosures into nine factors. Our results show different disclosing patterns among firms depending on whether they had cybersecurity incidents and internal control weaknesses. Further, our analysis indicates that firms disclose control-related factors to mediate the negative effect of disclosing vulnerability-related factors. This study provides various stakeholders, including investors, regulators, and researchers, with insight into the informativeness of cybersecurity risk disclosures.

Original languageEnglish (US)
Pages (from-to)179-194
Number of pages16
JournalJournal of Information Systems
Volume35
Issue number2
DOIs
StatePublished - Jun 1 2021

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Software
  • Information Systems
  • Accounting
  • Human-Computer Interaction
  • Information Systems and Management
  • Management of Technology and Innovation

Keywords

  • Cybersecurity
  • Factor analysis
  • Risk factor disclosure
  • Textual analysis

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