Structural and social dimensions of an international joint venture
Bibliographic record
Abstract
Purpose The purpose of this paper is to advance knowledge in the area of international joint ventures, more specifically in China. Design/methodology/approach The analysis considers events prior to 26 April 2006, when the joint venture was announced. Organizations involved are considered as units of analysis for the current study. Using Yin's methodology for exploratory theory development, this study builds on existing theories through a case study that explores the execution of international joint ventures. This study analyzes holistic data in relation to Hypor Canada, Sichuan South Hope Company Ltd, and Shangdong Liu He Group Ltd. Findings The findings suggest that strategic intents and resources need to be aligned between parties involved, and that foreign‐based North American firms should cultivate both the structural and social dimensions of a relationship with a Chinese‐based company. Research limitations/implications The sample was limited to one case in swine genetics. The findings of this research may only be fully applicable for explaining joint venture operations in this particular area. Practical implications The Hypor and New Hope agreement shows that a project needs to address both structural and social dimensions at once. Managers and marketers need to be aware of this and to consider both dimensions when assessing situations that may lead to a new joint venture. Originality/value For various reasons, many joint ventures between North American and Chinese companies fail. On 26 April 2006, however, Hypor Canada, a leader in swine genetics headquartered in Regina, Saskatchewan, signed what would prove to be a successful joint venture with China‐based New Hope (Sichuan South Hope Company Ltd). The agreements with Sichuan South Hope Company Ltd (New Hope) and Shandong Liu He Group Company Ltd (Liu He) were at the production and distribution of breeding pigs in China.
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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 | 0.000 | 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 | 0.001 |
| 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 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".