An Empirical Research on the Relationship Between Firm Ownership Structure and Technical Innovation: Taking Manager Features as Mediums 1 UNE RECHERCHE EMPIRIQUE SUR LA RELATION ENTRE LA STRUCTURE DE PROPRIETE D'ENTREPRISE ET L'INNOVATION TECHNOLOGIQUE : PRENDRE LES CARACTERISTIQUES DES MANAGERS COMME MEDIAS
Bibliographic record
Abstract
Abstract: The empirical research on the relationship between firm ownership structure and technical innovation is weak in existing research. Based on existing research result, this article empirically studies the influence of manager on relationship between firm ownership structure and technical innovation, by analysing a large sample database. It proves that firm manager is the important link between firm ownership structure and technical innovation. Keywords: ownership structure; attitude of manager; talent of manager; firm technical innovation Resume: La recherche empirique sur la relation entre la structure de propriete d'entreprise et l'innovation technologique est faible dans les recherches existantes. Basee sur le resultat de recherches existantes, cette these fait une recherche empirique sur les influences des managers sur la relation entre la structure proprietaires d'entreprises et l'innovation technologique en analysant une donnee exemplaire immense. Elle prouve que les managers des entreprises sont les liaisons importantes entre la structure de propriete d'entreprise et l'innovation technologique. Mots-cles: Structure proprietaire, attitudes des managers, talents des managers, l'innovation des entreprises technologiques Both firm ownership structure and technical innovation can influence firm achievement. But, research on the relationship between ownership structure and technical innovation of a firm (for example, which factor can influence the relationship) is rare [1] [2]. In this article, basing on existing research result, the author will empirically studies the influence of managers on relationship between ownership structure and technical innovation by analyzing Chinese firms. Particularly, the paper will prove that managers' features can both strengthen the relationship between ownership shares of managers and firm technical innovation, and the relationship between ownership shares of government and firm technical innovation. Therefore, the paper will prove that the managers' features (in this paper, it means managers' care to owners benefit, and the managers' talent) can be regarded as important mediums between ownership structure and firm technical innovation. The following is the methods and the process for proving these points. 1. METHODS We use the widely approved method provided by Baron and Kenny (1986) to test the influence of manager features on the relationship between firm ownership structure and technical innovation. In their paper, Baron and Kenny argued that the mediums will strengthen the relationship between independent variables(IV) and dependent variables(DV) if the following four conditions are met[3] (Figure 1): (1) Independent variables (IV) influence the mediums in (a); (2) Independent variables (IV) influence dependent variables (DV) in (b); (3) Mediums influence dependent variables (DV) in (c); (4) Lastly, the influence of IV on DV in (c) is smaller than that in (b), which means the influence of IV on DV declines when we take mediums into account. In this paper, firm ownership structure is independent variable (IV), firm technical innovation is dependent variable (DV), and manager features are mediums. Besides, firm ownership structure is expressed by the ownership shares of managers(Sm), of government(Sg),and of the public(Spu); and the managers' features include the extent of managers' care to owners' benefit(Emc) and the managers' talent (Ta). Using statistic software (SPSS) and taking technical innovation as DV, we will test if above four conditions are met by regression analyzing. First of all, we now describe the relative data and the measure of variables. DATA SOURCE AND VARIABLE MEASURE 2.1 Data Source Data used in this paper come from an investigation on running circumstances of Chinese enterprises from 1997 to 2001. The investigation involves enterprises from Guangdong, Liaoning, Shandong, Shannxi, Shanxi, and Sichuan province. …
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".