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Record W1973041216 · doi:10.1108/ejtd-05-2013-0055

Teaching corporate crisis management through business ethics education

2014· article· en· W1973041216 on OpenAlexaff
Sheldene Simola

Bibliographic record

VenueEuropean journal of training and development · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicEthics in Business and Education
Canadian institutionsTrent University
Fundersnot available
KeywordsCrisis managementBusiness ethicsPsychologyPerceptionAction (physics)CurriculumManagement developmentManagementPublic relationsPolitical sciencePedagogyEconomics

Abstract

fetched live from OpenAlex

Purpose – The purpose of this research was threefold, including to provide a four-point rationale for teaching corporate crisis management as a module within a course on ethical decision-making in business and organizations; to provide evaluative data supporting this approach; and to highlight the implications of this approach for human resource development and training. Design/methodology/approach – Thirty-four undergraduates in a required course on ethical decision-making in business and organizations completed pre- and post-course assignments assessing their knowledge about crisis/management, as well as their skills in crisis recognition, evaluation and action planning. Participants also completed a survey on their perceptions of the crisis management module and its placement within the ethics course. Findings – Statistical analyses demonstrated significant knowledge acquisition on crisis/management; significant skill development on crisis recognition, evaluation and action planning; and significantly greater “true positives” and significantly fewer “false negatives” in post-course identification of crisis warning signs. Perceptions of the crisis management module and its placement within the course on ethical decision-making were positive. Research limitations/implications – Although the sample size was relatively small, small samples are associated with a greater risk of failing to detect an effect that is present, rather than the greater predicament of erroneously concluding that an absent effect is actually present. This information, coupled with the fact that the results demonstrated not only statistical significance but also large effect sizes using Cohen’s d, inspires confidence. Nonetheless, additional assessment with larger samples would allow for the possibility of convergent evidence. Similarly, additional assessment within different organizational contexts, including applications in human resource training and development is warranted. Future research should also include assessment of specific underlying teaching strategies and evaluation of whether certain models are associated with greater learning on a broader range of crisis management skills. Practical implications – Programs in business ethics education and training comprise one useful context in which to teach corporate crisis management. The program specified here addresses two training needs previously specified in the human resource development (HRD) literature on crisis management, including identifying specific methods of enhancing recognition or detection of crisis warning signs and also of providing tools and enhancing skills for assessing and containing crisis. Originality/value – Despite the centrality of both ethics and HRD to crisis management, there has been a dearth of research on whether ethics education is a useful context through which to teach this topic. This research addresses this dearth and suggests new avenues for HRD in this respect.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.002

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 head0.420
GPT teacher head0.409
Teacher spread0.010 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations52
Published2014
Admission routes1
Has abstractyes

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