Corporate political connections in global strategy
Bibliographic record
Abstract
Research Summary: The role of corporate political connections (CPC) in global strategy has been examined in a variety of institutional contexts and analyzed from different theoretical perspectives. This literature, along with the articles in this special issue, demonstrate the importance of contextualization in understanding the motivations, processes, and outcomes of firms developing and utilizing CPC in global strategy. We argue that context‐specific aspects of CPC, such as the political system in which the firm is operating, need to be incorporated more systematically to advance theory development globally. Future studies on CPC can advance this agenda through cross‐country comparative research, deeper engagement with political science literature, linking CPC with other nonmarket strategies, and configurational analysis of the multidimensional context of CPC. Managerial Summary: Multinational companies not only compete in a market environment, they engage with political actors in both their home and host societies. This special issue brings together research that explores how companies use their corporate political connections (CPC) to achieve firm objectives. Each study takes a different approach to studying the phenomenon, informed by the national context of their empirical data. Together, these studies highlight the importance of CPC around the world. However, the variation in research approaches also highlights that the “how and why” of companies' development and utilization of CPC vary across cultures and political systems. In consequence, the development of managerial recommendations always needs to carefully consider the pertinent political context of the available empirical evidence.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".