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Record W2889128942 · doi:10.5539/ibr.v11n9p108

The Impact of Applying the Blue Ocean Strategy on the Achievement of a Competitive Advantage: A Field Study Conducted in the Jordanian Telecommunication Companies

2018· article· en· W2889128942 on OpenAlexvenueno aff
Mohammad Ali Al Qudah, Tareq N. Hashem

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsCompetitive advantageSample (material)Competition (biology)Order (exchange)Process (computing)BusinessSample size determinationDescriptive statisticsMarketingService (business)Computer scienceStatisticsMathematics

Abstract

fetched live from OpenAlex

The present study aimed to identify the impact of applying the blue ocean strategy on the achievement of a competitive advantage in the Jordanian telecommunication companies. In order to achieve the study’s objectives, the descriptive analytical approach was adopted and a questionnaire was developed. After that, the questionnaire forms were distributed to the selected sample. The sample consists of one hundred (100) administrators working in Jordanian telecommunication companies. The researchers used descriptive statistical methods, as well as, linear regression analysis, that were done to test the study’s hypotheses and analyze the collected data. Several results were concluded. For instance, it was concluded that the blue ocean strategy dimensions are highly applied. It was also found that the elimination process significantly affects the achievement of a competitive advantage. It was also found that the reduction process significantly affects the achievement of a competitive advantage. In addition, it was found that the increasing process significantly affects the achievement of a competitive advantage. It was found that the innovation process significantly affects the achievement of a competitive advantage. In the light of the aforementioned results, several recommendations were suggested by the researchers. For instance, the researchers recommend providing customers with service guarantees by the Jordanian telecommunication companies. In addition, the researchers recommend overcoming the obstacles that hinder the application of the blue ocean strategy by the senior management. The researchers recommend utilizing the blue ocean strategy by companies and avoiding negative competition. The researchers also recommend making significant strategic changes in an ongoing manner. Such changes should be provided with support by the board of directors.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.076
GPT teacher head0.397
Teacher spread0.321 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2018
Admission routes1
Has abstractyes

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