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Record W2117804213 · doi:10.1002/atr.116

Effects of regulation changes in seoul bus system: private bus operation under non‐competitive fixed price contract

2010· article· en· W2117804213 on OpenAlexvenueno aff
Songju Kim, Euiyoung Shon

Bibliographic record

VenueJournal of Advanced Transportation · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessAutomotive engineeringTransport engineeringFinanceIndustrial organizationEngineering

Abstract

fetched live from OpenAlex

Abstract One of crucial measures introduced under Seoul Public Transport Reforms 2004 was the regulatory framework change of intra‐urban bus from the poorly regulated private operations with operating subsidy, towards the highly regulated one via fixed price contracts. The focus of this paper is placed on (1) addressing the challenges newly faced after Seoul Bus Reform 2004, and (2) proposing some strategies in order to ensure better bus operation overall the reforms was a success in many aspects, resulting in the increase of patronage of urban transit, the dramatic drop of bus accidents, and introducing exclusive median lanes. Unfortunately, the previously small, family‐owned, inefficient bus companies were transferred to monopoly franchises under the reforms, thus institutionalizing a non‐competitive supply situation. The exclusive operating right‐of‐way is still protected as a judicial precedent set by the Korean Supreme Court. The current non‐competitive bus contracts such as a sole‐source negotiation procurement must be modified into competitive tendering in the long run, and the major obstacles to this strategy and the detailed scheme are reviewed. Further, the short‐term strategies was proposed including (a) the development of more sophisticated standard cost model incorporating a route structure and/or the patronage change; (b) the introduction of yardstick regulation; and (c) extended incentives and penalties. Copyright © 2010 John Wiley & Sons, Ltd.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.484

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.255
Teacher spread0.250 · 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
Published2010
Admission routes1
Has abstractyes

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