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Managerial hubris detection: the case of Enron

Author

Listed:
  • Eyal Eckhaus

    (Ariel University)

  • Zachary Sheaffer

    (Ariel University)

Abstract

Hubris is a known risk for leadership failure. We show that hubristic tendencies can be detected semantically ex-ante in textual reports, and offer a novel methodology aimed at detecting real-time hubristic propensities. The methodology employs text mining based on natural language processing (NLP) on Enron email corpus. NLP can capture information about employees and predict change patterns. Employing NLP real-time mechanism, Enron executives’ hubristic tendencies were detected. Findings indicate that hubristic expressions amongst senior executives are significantly more frequent than amongst their non-senior counterparts, and that the frequency of hubristic expressions increases the closer one gets to Enron’s collapse. Whilst both Enron’s CEO’s were hubristic, we found Skilling to be typified with severer hubris. Our study is the first to employ NLP real-time analytical process to detect the hubris disposition. Predicated on Enron’s case study, we demonstrate the methodology’s strengths, notably immediate recognition of accumulated symptoms and prevalence.

Suggested Citation

  • Eyal Eckhaus & Zachary Sheaffer, 2018. "Managerial hubris detection: the case of Enron," Risk Management, Palgrave Macmillan, vol. 20(4), pages 304-325, November.
    • Handle: RePEc:pal:risman:v:20:y:2018:i:4:d:10.1057_s41283-018-0037-0
    DOI: 10.1057/s41283-018-0037-0
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    Cited by:

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    6. Janina Sundermeier & Tyge-F. Kummer, 2022. "Does personality still matter in e-commerce? How perceived hubris influences the assessment of founders’ trustworthiness using the example of reward-based crowdfunding," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1127-1144, September.

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