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Record W4255241136 · doi:10.1177/0361198106198600114

Carsharing and Station Cars in Asia

2006· article· en· W4255241136 on OpenAlexaboutno aff
Matthew Barth, Susan Shaheen, Tuenjai Fukuda, Atsushi Fukuda

Bibliographic record

VenueTransportation Research Record Journal of the Transportation Research Board · 2006
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsnot available
FundersUniversity of California, DavisNational University of Singapore
KeywordsKuala lumpurPublic transportBusinessCar ownershipTransport engineeringGeographyEngineeringEconomic growthMarketingEconomics

Abstract

fetched live from OpenAlex

In recent years, there has been significant worldwide activity in shared-use vehicle systems (i.e., carsharing and station cars). Much of this activity is taking place in Europe and North America; however, there has also been significant activity in Asia, primarily in Japan and Singapore, with some planned activity in Malaysia. The latest shared-use vehicle system activities in Japan and Singapore are examined, beginning with a historical review followed by an evaluation of their current systems. Overall, there are several well-established systems in Japan (18 systems having approximately 176 vehicles and 3,500 members) and Singapore (four systems having approximately 432 vehicles and 12,200 members). A new program was planned to launch in spring 2006 in Kuala Lumpur, Malaysia, with 10 vehicles. In contrast to most European and North American cities, Japan and Singapore already have a wide range of viable public transportation modes. The primary carsharing focus in Japan is on business use, and in Singapore, on residential–neighborhood use. This likely is because of limited vehicle licensing and high car-ownership costs in Singapore. Further, systems in Japan and Singapore have a high degree of advanced technology in their systems, making the systems easy to use and to manage. The member–vehicle ratios in Asia appear to be approximately the same as in Europe and Canada and less than in the United States. It is expected that Asian shared-use vehicle systems will continue to have steady growth in number of organizations, vehicles, and users.

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 score0.212
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.055
GPT teacher head0.345
Teacher spread0.289 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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