Organizational Resilience: 30 years of intellectual structure and future perspectives
Bibliographic record
Abstract
Objective. The knowledge structure was analyzed, during the period 1991-2021, on the factors that influenced organizational resilience to distinguish possible synergies, interactions, and new research lines. Design/Methodology/Approach. Using a performance analysis and scientific mapping approach, a bibliometric methodology was used to discover and represent conceptual subdomains and thematic development. This methodology consisted of four phases: (1) detection of research topics, (2) visualization of research topics and the thematic network, (3) discovery of thematic areas, and (4) performance analysis. Results/Discussion. Of the 869 publications on organizational resilience indexed in Scopus, the ones that had the most significant impact on the development of the topic were: Resilience; the concept, a literature review and future directions (2011), Developing a capacity for organizational resilience through strategic human resource management (2011), Developing a tool to measure and compare organizations' resilience (2013), Organizational resilience: Development of a conceptual framework for organizational responses (2011), and Facilitated process for improving organizational resilience (2008). The most important authors were Bhamra, R.; Burnard, K.; Seville, E.; Vargo, J. and Beck, T.E. The driving issues that over time have been closely related to the resilience of organizations were: risk management, standardization and regulation, psychological resilience, ICT resilience, protection and security, health personnel, and reliable organization. Conclusions. In recent years, when the subject has been more developed, it became clear that it is essential to observe risk management, health personnel, reliable organization, and decision-making to manage organizational resilience. Regarding possible future lines of research, the following was found: resilience of security networks, cybersecurity, cyber resilience, disaster management, organizational innovation, sustainable development, and sustainability management.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.003 | 0.012 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".