As the two, next-largest handset vendors fling themselves at the dual prospects of entry-level phones in emerging markets and upgrade cycles in mature markets, all in an effort to compete with Nokia Corp.’s breakaway, a few rivets are coming loose.
Motorola Inc.’s historic stumble has enabled Samsung Electronics Co. Ltd. to seize, by a hair, the global, second-place ranking in market share.
Samsung churned out 37.4 million handsets in the second quarter, compared with Motorola’s self-projected volume of 35 million to 36 million. Samsung’s unit volume is up nearly 50% over the year-ago quarter. Analysts said that the vendor’s efforts in emerging markets are finding a degree of success and, like Sony Ericsson Mobile Communications, it has capitalized on Motorola’s weakness in the European market to gain share.
Samsung’s financial results on its massive second-quarter volume play are another matter. The overall company earned revenue of $16 billion for the second quarter, a 4% nudge up from the year-ago quarter. Net income in the quarter was $1.5 billion, down 5% from the year-ago quarter.
Samsung’s average selling price, as in Sony Ericsson’s case, has eroded with a push for market share. Samsung’s ASP in the quarter was $148, a 5% drop from the previous quarter.
The company attributed its performance to its Ultra Edition line of handsets in mature markets and its increased volume of entry-tier handsets in emerging markets.
Samsung passes Motorola, nabs No. 2 market-share ranking
ABOUT AUTHOR
Jump to Article
What infra upgrades are needed to handle AI energy spikes?
AI infra brief: Power struggles behind AI growth
The IEA report predicts that AI processing in the U.S. will need more electricity than all heavy industries combined, such as steel, cement and chemicals
Energy demand for AI data centers in the U.S. is expected to grow about 50 gigawatt each year for the coming years, according to Aman Khan, CEO of International Business Consultants
AI infra brief: Power struggles behind AI growth
The IEA report predicts that AI processing in the U.S. will need more electricity than all heavy industries combined, such as steel, cement and chemicals
Energy demand for AI data centers in the U.S. is expected to grow about 50 gigawatt each year for the coming years, according to Aman Khan, CEO of International Business Consultants