Three Organizational Challenges for Multinational Enterprises
Bibliographic record
Abstract
The rapidly changing and volatile institutional environments, within which Multinational Enterprises (MNEs) must operate, have put traditional organisational forms under pressure. Globalization and regionalism develop at the same time, whereas regulation facilitating Foreign Direct Investment (FDI) runs parallel to ‘reverse measures’ frustrating FDI (PIBR #7 – Van Tulder et al. 2012 provides an overview of mixed institutional pressures on the MNE). The leading question that this volume addresses is therefore whether there are adequate organizational responses that the MNEs can develop to these mixed pressures. How to internalize external inefficiencies, inter alia in the broader stakeholder sphere? MNEs have been responding along a variety of paths. One path has been to redraft relationships between headquarters and existing subsidiaries. Another path has been to adopt new organisational forms, both internally (team-based approaches and asymmetrical networks) and externally, (advanced management of value chains and stakeholder ecosystems). As a result, new organizational arrangements have appeared, including micro-multinationals, ‘born globals’, springboard multinationals, as well as other types of international new ventures. Taking stock of the present discourse in International Business (IB) we divide this chapter, and the contributions in this volume, along three organizational challenges. 1) Changing hierarchies: considers the shifting roles of headquarters and subsidiaries in MNEs, and explores the question whether headquarters still matter from various angles. 2) New organizational forms: considers new forms of organizing internationalization and international activities, including new roles of teams in multinational organizations. This part explores the question whether size still matters for MNEs. 3) Reorganizing the value chain: which gathers novel ideas about how multinational firms use external partners and parties in the organization of their international activities. The leading question here is whether the position of the MNE in the (international) value chain still matters. This chapter elaborates these three themes and provides a short account of each of the contributions that are selected for this volume in parts II, III and IV. These contributions include research-oriented papers, panel discussions and case studies.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.022 | 0.015 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".