Anglo-American Multinationals in Europe: The Curious Case of Hudson’s Bay Company Taking over Galeria Kaufhof
Bibliographic record
Abstract
Multinational corporations are undeniably the driving force of globalization and regional economic integration. A convenient institutional framework (Hall and Soskice, 2001) to apply when comparing multinationals from different host countries is the well-travelled road of dividing capitalist economies into coordinated market economies (CMEs) and liberal market economies (LMEs). This article aims to elucidate the tensions between centralized human resources practices and labour union avoidance usually exhibited by multinationals from so-called Liberal Market Economies (LMEs) when they expand into coordinated ones (CMEs). Specifically, it examines the recent acquisition of the German retail giantGaleria Kaufhofby the Canadian multinational Hudson’s Bay Company (HBC). The article shows that HBC has settled into an uneasy acceptance of the CME institutions, while its investment motives vacillate between a long-term, market-enlargement strategy and a short- to medium-term one, based on the rapidly increasing real estate value of its downtown flagship stores. The article encourages researchers in IR to retain three principal conclusions for the literature and for further study. First, without predetermining outcomes by looking at host-country or home-country effects alone, institutionalist frameworks do present a convenient backdrop for conceptualizing movements of multinationals across jurisdictions. Secondly, concepts such as bricolage, recombining of institutional elements and institutional entrepreneurship, stemming from the institutional change literature, should routinely figure in one’s analytical toolbox, in any attempt at non-deterministic institutional analysis. Finally, sector-level actors, such as trade unions and employers’ associations, can play an essential role in any successful adaptation of collective bargaining institutions in the context of globalization by developing, maintaining and carefully utilizing their repertoire of strategic capabilities.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.008 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 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".