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Record W2946961355 · doi:10.1108/ijdrbe-11-2018-0046

Indicators to assess organizational resilience – a review of empirical literature

2019· review· en· W2946961355 on OpenAlexaff
Khalil Rahi

Bibliographic record

VenueInternational Journal of Disaster Resilience in the Built Environment · 2019
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain Resilience and Risk Management
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsResilience (materials science)CredibilityEmpirical researchAdaptive capacityOriginalityKnowledge managementProcess managementBusinessEnvironmental resource managementComputer sciencePsychologyPolitical scienceSocial psychologyEconomics

Abstract

fetched live from OpenAlex

Purpose This paper aims to explore the empirical literature on organizational resilience. The goal consists of identifying and understanding the indicators used to evaluate organizational resilience and instigating the development of indicators to assess resilience in other areas, such as project management and critical infrastructure. Design/methodology/approach A review of recent empirical studies is conducted to collect information on the indicators used to assess organizational resilience. Findings A range of interrelated indicators aiming to measure organizational resilience in two dimensions is shown in this literature review: awareness and adaptive capacity. Awareness is the ability of an organization to assess its environment and interpret the changes in its surroundings, both now and in the future, to be proactive and better manage possible disruptive events. On the other hand, adaptive capacity is the organization’s capacity to transform its structure, processes, culture, etc. for recovering once faced with a disruptive event. Awareness forms the main base of the organization’s adaptive capacity. Originality/value Organizational resilience contributes to the safe development of the built environment. This concept helps organizations to cope with disruptions. However, little research has been conducted on the indicators to assess organizational resilience, in different fields. Moreover, these indicators’ credibility is based on empirical studies.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.892
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.352
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations95
Published2019
Admission routes1
Has abstractyes

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