The determinants of strategic partnerships in research and development (R&D) - a regional comparison among the German federal states
Bibliographic record
Abstract
The systematic co-operation in R&D involving two or more enterprises or companies working with research organisations, suppliers, customers or even competitors has become a popular instrument of strategic management. As new empirical results from the IfM Bonn show, more than a quarter of all enterprises in the industrial sector and the industry-related services in Germany are participating in strategic partnerships of this kind. Strategic partnerships in R&D, which lead to new products or process innovations, have positive effects on a firm´s competitive position. Governmental policy in Germany has recognized its importance for the economy and therefore provides financial aid for R&D-active enterprises. From the perspective of regional science the question is whether R&D co-operations have gained equal popularity all over the country or whether significant regional differences have to be taken into account. This paper examines determinants on enterprises participating in R&D co-operations with particular emphasis on regional influences. Data from a postal questionnaire was taken to form a sample of approx. 950 enterprises located all over the country. To establish the determinants and their relative influence a logistic regression is estimated. Further regional comparisons in R&D activities are carried out by chi-square-tests. The results of the bivariate analyses highlight regional differences in partnerships between enterprises and research organisations. It is remarkable that enterprises in the federal states which have the biggest problems in coping with structural changes, the East-German states, participate significantly more frequently in these partnerships than their West-German counterparts. However, the results of the logistic regression provide no evidence for regional differences concerning R&D co-operations on the whole. Not the location but structural features of the enterprises matter. For instance, plant size is positively associated with R&D co-operation: larger enterprises are more cooperation-oriented than smaller enterprises. Furthermore, the analysis identifies company-specific conditions that enable them to join R&D co-operations. Besides that, emphasis is put, for example, on experiences with other forms of strategic partnerships. The presence of company-owned R&D facilities is another requirement to find a chance to co-operate in most of the cases. Other variables such as the degree of monopoly power or the market structure do not influence the plant´s capacity to join R&D partnerships.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".