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Truce Breaking and Remaking: The CEO’s Role in Changing Organizational Routines

2015· book-chapter· en· W2144480472 on OpenAlexaff
Sarah Kaplan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrofoundationsCognitionCognitive dimensions of notationsOrganizational changeDimension (graph theory)Political sciencePsychologyPublic relationsSocial psychologySociologyEconomics

Abstract

fetched live from OpenAlex

Abstract This chapter reports on the “CEO’s-eye-view” of the 1990 financial crisis at Citibank using unique data from CEO John Reed’s private archives. This qualitative analysis sheds light on questions that have perennially plagued executives and intrigued scholars: How do organizations change routines in order to overcome inertia in the face of radical change in the environment? And, specifically, what is the role of the CEO in this process? Inertial behavior in such circumstances has been attributed to ingrained routines that are based on cognitive and motivational truces. Routines are performed because organizational participants find them to cohere to a particular cognitive frame about what should be done (the cognitive dimension) and to resolve conflicts about what gets rewarded or sanctioned (the motivational dimension). The notion of a “truce” explains how routines are “routinely” activated. Routines are inertial because the dissolution of the truce would be inconsistent with frames held by organizational participants and fraught with the risk of unleashing unmanageable conflict among interests in the organization. Thus, the challenge for the CEO in making intended change is both to break the existing truce and to remake a new one. In this study, I uncover how the existing organizational truce led to the crisis at Citibank, why Reed’s initial attempts to respond failed, and how he ultimately found ways to break out of the old truce and establish new routines that helped the bank survive. These findings offer insight into the cognitive and motivational microfoundations of macro theories about organizational response to radical change.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.778
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.202
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations19
Published2015
Admission routes1
Has abstractyes

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