Survival strategy of OEM companies: a case study of the Chinese toy industry
Bibliographic record
Abstract
Purpose Although there have been many discussions on the status and development of original equipment manufacturers (OEMs), theory on how they survive is minimal. Little is known about how OEMs survive and upgrade to other business models, such as original design manufacturers (ODMs) and original brand manufacturers (OBMs), in emerging economies. The purpose of this paper is to extend the theory on the survival path of OEMs from the perspective of emerging countries by examining how OEMs survive cost pressures and upgrade to ODMs or OBMs. Design/methodology/approach Using a multi-case study method, this study analyzes the survival path employed by OEMs by examining eight firms in the Chinese toy industry. Findings This study shows that OEMs remain weak in the global toy industry chain due to labor costs. While some OEMs move to low-cost regions, others turn to OBM management, after transitioning through an ODM model, by investing in research and development and marketing. Originality/value This study explores the survival paths of OEM enterprises, showing that OEMs can first upgrade to ODMs and then to OBMs, or they can directly upgrade to OBMs. Shifting from OEM to ODM is an important step in the transition process, although the contract that OEMs have with their foreign partners does not change significantly.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".