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Record W2147565862 · doi:10.5539/ibr.v5n2p179

Gaining Competitive Advantage through Marketing Strategies in Container Terminal: A Case Study on Shahid Rajaee Port in Iran

2012· article· en· W2147565862 on OpenAlexvenueno aff
Hossein Cheraghi, Alireza Khaligh, Abbass Naderi, Alireza Miremadi

Bibliographic record

VenueInternational Business Research · 2012
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)BusinessCompetitive advantageContainer (type theory)Service (business)Default gatewayMarketingIndustrial organizationOperations managementComputer scienceEngineeringComputer network

Abstract

fetched live from OpenAlex

Shahid Rajaee port complex at Bandar Abbas is the country’s principal gateway for containerized cargo. It has emerged as a leading regional commercial center and a world class business environment. It has now become the logical place to do business in the Middle East, providing investors with a unique value added platform. Ports have a significant role in today’s networked business environment. They are being regarded as hubs that are part of various logistics systems. The very essence of seaport is to link maritime networks and land network. These networks for the port are means of analyzing its competitiveness. The objective of this study is to find out the main factors which impact on competitiveness of container port in Shaied Rajaee. Port and enable it to suggest and apply the profound marketing strategy to get the huge load in this port. Based on our findings by employing the factor analysis is to reveal the vital competitiveness of the port. It reveal that that port strategy and policy, port logistics, hinterland condition, availability, shipping maritime service, port Regional center, shipping agreement and port service and connectivity are determining factors in the shahid Rajee port in Iran.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.133
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.105
GPT teacher head0.406
Teacher spread0.301 · 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 teacher head, 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

Citations7
Published2012
Admission routes1
Has abstractyes

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