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Record W3170741612 · doi:10.5267/j.ac.2021.5.014

The effect of stakeholder's commitment and government regulations on dry port firm performance

2021· article· en· W3170741612 on OpenAlexvenueno aff
Engkos Achmad Kuncoro, Dicky Hida Syahchari, Hardijanto Saroso, Darjat Sudrajat, Henny K W Jordaan

Bibliographic record

VenueAccounting · 2021
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)BusinessGovernment (linguistics)StakeholderSupply chainService (business)Stakeholder engagementIndustrial organizationMarketingEconomicsManagementPublic relationsEngineeringPolitical science

Abstract

fetched live from OpenAlex

The dry port (or land port) is an inland area or an intermodal port directly connected to a seaport. Cikarang Dry Port, as one of the best performing dry ports among other dry ports in Indonesia, only contributes 18% of the loading and unloading volume at Tanjung Priok port. This study examines the effect of supply chain collaboration and service stakeholder engagement on Dry Port Company's performance. The data collected from a questionnaire. The 55 responses from employees of Cikarang dry port and a logistics company in Jakarta. The hypothesis was tested by multiple regression. This study confirms that government regulation and Stakeholder Commitment positively impact the performance of port companies. The study inspires managers to recognize the positive results of government regulation practice among stakeholder engagement organizations to improve port performance in port supply chains.

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)0.019
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 score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.196
Teacher spread0.185 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

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