Strategic adaptation to environmental jolts: an analysis of corporate resilience in the property development sector in Dubai
Bibliographic record
Abstract
This paper contributes to the literature on the contingent nature of strategic adaptation to environmental jolts in the context of the real estate industry in UAE. We selected the representative case of Emaar Properties to estimate how the evolving dynamics in the UAE real estate sector over the 2000-2015 period affect the exercise of managerial discretion and the development of corporate resilience. The emphasis was placed on two external discontinuities, namely the 2008-2009 financial crisis and the 2013 announcement of Dubai as the host city of World Expo 2020. By altering its portfolio of investments across countries and industry segments, the company mitigated the impact of the global recession and benefited from the market improvement triggered by the World Expo 2020 news. The strategic choices of the top management reflect how, in times of environmental turbulence, Emaar was geared toward achieving tighter external alignment to balance its risks and opportunities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".