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Record W2070618073 · doi:10.1108/00251741111143649

Against all odds: a strategic analysis of the fall of Hong Kong, 1941

2011· article· en· W2070618073 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueManagement Decision · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement Theory and Practice
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBattleSection (typography)SurrenderStrategic planningOperations researchMilitary strategyCompetitive advantageExtant taxonMarketingComputer scienceSociologyBusinessPolitical scienceLawHistoryEngineering

Abstract

fetched live from OpenAlex

Purpose The paper seeks to build on a model from extant literature which utilized a similar historical analysis approach in a study of strategic decision making. Using the (unsuccessful) defence of Hong Kong in World War II as the historical case, the paper seeks first to apply Chung and McLarney's model in the analysis, and then extend the model so as to better handle the unique sequence of events that took place in 1941. Design/methodology/approach The paper employs a historical case event in an analysis of competitive strategies. The first section provides a descriptive historical account of the battle of Hong Kong. The second section describes the decision‐making model, while the third section applies the model to explain three sets of decisions: the decision to defend the colony, decisions made during the battle and the decision to surrender. The fourth section draws implications for strategic decision making in organizations, while the last section presents conclusions. Findings Organization theorists seem to be fascinated with planning and strategy formulation, at the expense of strategy implementation. While designing organizational strategy is often more glamorous than execution, it is the execution of strategy that ultimately determines an organization's competitive advantage. Clearly, the strategy of the Allied Forces in Hong Kong was not hard to figure out (Mintzberg). However, there is growing research on how lower organizational levels have a tremendous contribution in fundamentally changing, formulating organizational strategy and sometimes even obstructing strategy formulated at the top. The decision to defend Hong Kong in the face of the Japanese invasion, decisions made during the battle and the decision to surrender were all major, critical decisions, especially susceptible to such biases as overconfidence, problem framing, availability heuristics and confirming‐evidence. Overconfidence is particularly dangerous. Originality/value The study not only modifies and extends the model, but also contributes to the literature by augmenting the validity of previous case research.

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.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.063
GPT teacher head0.250
Teacher spread0.188 · 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