Effects of Brand Portfolio and Product Line Strategy on Brand Market Share: Evidence from Chinese Cellphone Market
Bibliographic record
Abstract
This paper investigates the effects of brand portfolio and product line strategy of cellphone brands’ market share in China. Based on the 15-month data of Chinese cellphone markets, the authors conducted the empirical analysis using a two-way fixed effect model. The results show that foreign cellphone brands and Chinese local cellphone brands market share response differently to price level, product line level, and geographic level variables. Increasing segment coverage and widening product line enhances both foreign and local brands’ market share. However, price-level factors have opposite influence on foreign and local brands in that price negatively relates to foreign brands’ market share but positively relates to local brands’ market share. Similarly, price concentration shows a negative impact on foreign brands but positive impact on local brands’ market share. Finally, longer brand history positively relates to foreign brands’ market share but negatively relates to local brands’ market share. This research provides useful guidelines and telecommunication implications in the context of Chinese market.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".