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Record W2290943870 · doi:10.5937/industrija43-8163

Lenovo acquires IBM's x86 low-end server business

2015· article· en· W2290943870 on OpenAlexaboutno aff
Pal Singh

Bibliographic record

VenueIndustrija · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFirm Innovation and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsIBMx86Competition (biology)BusinessDatabaseGovernment (linguistics)Computer scienceIndustrial organizationCommerceOperating systemSoftware

Abstract

fetched live from OpenAlex

This paper presents an analysis of the key events, impacts and issues of Lenovo buying IBM's x86 low-end server business. The analysis include (i) approval of the deal by regulatory bodies in the United States, Canada, India and China, (ii) security concerns of US government departments, (iii) pricing of the deals, (iv) possible impact on IBM in future, and (v) possibilities of Lenovo making it repeat of acquiring ThinkPad business of IBM. The paper presents analysis of qualitative and time series quantitative data. The qualitative data are mainly consists of different events before and after the acquisition of x86 server IBM business by Lenovo. The quantitative data are analyzed with respect to growth parameters of overall server business and Lenovo server business. Research paper also attempts to find out answer to specific 9 research questions with respect to impact on eco-systems of IBM and Lenovo. Based on analysis, it is inferred that IBM is not able to manage its traditional & well accepted products business in the face of fierce competition & low demand but Lenovo will manage. The deal was a financial necessity for IBM and strategic expansion in to new markets strategy for Lenovo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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.

Opus teacher head0.111
GPT teacher head0.233
Teacher spread0.122 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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