Cross-Border M&A Motives and Home Country Institutions: Role of Regulatory Quality and Dynamics in the Asia-Pacific Region
Bibliographic record
Abstract
The purpose of this paper is to analyze the relationship between home country institutions and cross-border merger and acquisition (M&A) motives of MNEs from the Asia-Pacific region, with a focus on the role of regulatory quality and dynamics. We empirically examine how M&A motives are affected by elements related to risk of the institutional environment of the acquiring firm’s home country regulatory quality over time. The study is grounded in the general theory of springboard MNEs, and the institutional views of cross-border operations, namely the institutional escapism and institutional fostering perspectives. Using data on over 700 cross-border M&As of European firms by Asia-Pacific MNEs in 2007–2017, we analyze the rationales for these deals and their relationship to the institutional characteristics of the buyers’ home countries including regulatory quality and voice and accountability. We found that the quality of home country regulatory environment is significantly related to domestic firms’ motivation for international M&As. However, the significance and sign of the effects differ for different types of motives and over time. Our findings contribute to the literature on general versus emerging MNE-specific internationalization theories (particularly the theory of springboard MNEs) by expounding on the types and dynamics of cross-border M&A motives.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".