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Managerial hubris detection: the case of Enron

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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.

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Authors and Affiliations

  1. Department of Economics and Business Administration, Ariel University, Ariel, Israel

    Eyal Eckhaus & Zachary Sheaffer

Authors
  1. Eyal Eckhaus
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  2. Zachary Sheaffer
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Correspondence to Eyal Eckhaus.

Appendix: Garrard et al. (2014)’s Tony Blair words

Appendix: Garrard et al. (2014)’s Tony Blair words

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2-gramsa

3-gramsa

Engagements

Position exactly

Will have further

Learned

Things about

I will have

Condolences

Our human

House my hon

ME

For allocation

And learned gentleman

Killed

I will

My engagements I

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Get under

Hon and learned

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Can working

Right that is

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Rejoin the

Have further such

Important

Let me

Condolences to the

Antisocial

Of enforcing

Me in wishing

  1. aN-gram is the sequence of n items

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Eckhaus, E., Sheaffer, Z. Managerial hubris detection: the case of Enron. Risk Manag 20, 304–325 (2018). https://doi.org/10.1057/s41283-018-0037-0

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  • DOI: https://doi.org/10.1057/s41283-018-0037-0

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