Strategic Interactions in Mobile Services of The Malaysian Telecommunication Industry
Bibliographic record
Abstract
The mobile telecommunication landscape in Malaysia has gone through some rapid changes in recent years due to the infusion of new technologies and industry deregulation, forcing local players to change the rules of the game. Although only two service providers were currently allowed to operate 3G licenses followed with the consolidation of five players into three in the industry, the conditions did not seem to result in higher entry barrier. The reason is because MCMC has allowed a new group of mobile virtual network operators (MVNOs) to compete in the mobile telecommunication market. With a penetration rate of 63.3% as of the second quarter of 2005, the market has become increasing saturated. As a result, the existing players have engaged in an ongoing price war to retain existing subscribers, if not to increase their market share. The study revealed that though the price war is unlikely to be sustainable, it will likely persist for the near future. The rationale is because the government has initiated that all prepaid mobile subscribers must be registered by the first quarter of 2006. Industry players believe that the initiative would result in a one-time mass exodus of subscribers. Hence, price war would continue in a last attempt to induce defections before the end of the registration period. Advertising was also found to play an important role in the industry. The analysis showed that each player tried to outspend one another in their advertising campaigns and played a dual role of information and persuasion which were used to compliment the other strategies. In addition, it is believed that R&D and innovation will play an increasingly important role specially after the rollout of 3G earlier this year. The convergence of the telecommunication, multimedia and online services would see increasing strategic alliance between the different service providers and create new growth opportunities in the industry.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".