The Level of Digital Development in the Host Country and M&A Performance
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.
Bibliographic record
Abstract
Economic globalization is increasing, and an aspect of this trend is the increasing frequency of cross‐border mergers and acquisitions (M&As). As the world has entered the era of digital development, the efficiency of information communication has doubled. However, whether digital development can help improve the performance of cross‐border M&A remains to be verified. Based on the entropy method, we constructed an index system for national digital development and analyzed the cross‐border M&A events of Chinese listed companies from 2010 to 2019. Through empirical analysis, the study finds that digital development in the host country improves the performance of cross‐border M&A. This effect is especially pronounced when the knowledge complexity of the M&A is inferior, or the M&A occurs in the same industry. We then analyze the mechanism of the impact of the host country’s level of digital development on improving firms’ M&A performance under Dunning’s OLI framework and the M&A transaction cost perspective, respectively. These findings enrich the theory of international investment and offer practical value to enterprises engaged in cross‐border M&A.
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 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 | 0.000 | 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 | 0.000 |
| 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 it