An Empirical Study on the Mechanism of Corporate Relational Embeddedness Impacts on the Supply Chain Cooperative Performance
Bibliographic record
Abstract
The geographical proximity is neither a necessary condition nor sufficient condition to realize advantages of industrial clusters.On the contrary,relationship closeness is much more important for enterprises within industrial clusters to obtain the benefits of industrial clusters.In practice,enterprises' stable cooperation relationship among the inter-regional cluster enterprises as well as cross-regional partners is an important way for cluster enterprises to obtain firm-specific knowledge.Geographical proximity only increases the chance of contact between the enterprises,while relationship closeness enable cluster enterprises to take good advantage of low-cost suppliers,obtain benefits of local knowledge spillovers and collective learning effect in spite of geographical distances.As a result,for business growth of industrial cluster enterprises,relationship space should be more concerned about,not just geographic space.Every relationship or link in the network of industrial clusters represents exchange of resources or knowledge between both sides,and therefore,how to use this network interaction to obtain the necessary resources and knowledge becomes a vital source of innovation performance.Enterprises embeddedness in industrial clusters provides a critical bridge for individual relationship building,also provides a platform for cooperative relationship development between enterprises,as well as forming a stable supply chain community of interests. In this paper,relational embeddedness refers to an informal organization networks in which enterprises within industrial clusters interact with local suppliers,customers and partners,focusing on social relations link.The relational embeddedness stressed on the cohesion link utility in continuing cooperation activities between members,and the strength of the relationship will affect the level of knowledge sharing.The previously cohesive link between two organizations may offer a pipeline for both of them to learn from each other and make sure if the partner is trustworthy. At the interpersonal level,in the face of challenge and support,the active participation of others is an important factor to motivate a team,called action learning(McGill Warner,1989).Bessant Tsekouras(2001) believe that there is a similar phenomenon between enterprises,and commercial relationship is an important source of corporate learning(Hult and Ferrel,1997).The specific relationship between organizations is a premise condition for organization parties learn from each other,by strengthening cooperation,and taking advantage of the knowledge of the partner companies,it can accelerate upgrading of the organizational capacity,reduce technology risk of R D and better respond to environmental uncertainty.And the concept of the formation of relationship between the organizations through close partnership is relationship learning.Recently research shows that commercial relationship will provide a platform for relational learning,stimulate the knowledge sharing and enhance problem-solving ability,enable the partnership interaction continue,finally improve the organization's relationship learning ability significantly. In order to examine the relationship between enterprises' relational embeddedness and supply chain cooperative performance,the sample data of manufacturing enterprises in the industrial clusters within the Pearl River Delta region was collected.The result shows that relational embeddedness has a significant positive direct influence on relationship learning and knowledge innovation ability,while relational embeddedness has no significant direct effect on supply chain cooperative performance but via an indirect mediation effect of relationship learning and knowledge innovation ability.In other words,corporate relational embeddedness within industrial clusters do strongly impacts on supply chain cooperative performance,but this effect is indirect.Specifically,enterprises can take advantage of knowledge of the industrial cluster partners,and obtain local knowledge spillovers and the benefits of collective learning,thus enhance organizational knowledge innovation capability,as well as reduce the technical risk and uncertainty.However,relational embeddedness only provides a platform for exchanging of knowledge and resources between enterprises,their effect should not be exaggerated.Due to big difference in their skills and abilities to deal with external network relationship,companies need to focus on the effect of relationship learning and high-level relationship interaction in relational embeddedness,so as to improve supply chain cooperative performance.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".