Sainsbury's in Egypt: the strange case of Dr Jekyll and Mr Hyde?
Bibliographic record
Abstract
Purpose The purpose of this paper is first, to explore the role of institutional theory constructs in a case of international retail divestment. Second, to examine the potential of constructed metaphors as a means of analyzing and communicating the findings of managerial research. Design/methodology/approach The data were generated from participant observations and interactions with stakeholder groups during a three‐month ethnographic study based in a Sainsbury store in Egypt. Data were analysed and presented via a constructed metaphor – namely Robert Louis Stevenson's story of Dr Jekyll and Mr Hyde. Findings The case illustrated an apparent paradox between Sainsbury's technical superiority as a retail operator in the Egyptian market, and its social inferiority in its interactions with a variety of stakeholders, primarily customers and employees. The use of the metaphor to organize, analyse and present the findings proves to be a fruitful way to illustrate this issue, and parallels between the two “stories” provide further insights into behaviour – the denial of responsibility for (and the existence of) social inadequacies; and the implicit (and inevitable) existence of the capacity for social inadequacy in any business organization. Practical implications The potential to communicate managerial lessons by telling “stories” (the case) through well‐known “stories” (the novel) is highlighted. Originality/value The use of the constructed metaphor to analyse a case of international retail divestment is, to the authors' knowledge, unique and enhances the understanding of the legitimisation process and the role of socio‐moral codes in this process.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".