Automated Author ProfileChu, Singfat
Chu, Singfat
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 7.5 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Objective is to infer if the expansion of public transportation provision (bus and Rapid Transit System) associate with a reduction for the competition of scarce car licenses in Singapore. Pertinent variables are adjusted for changes in population and inflation rates during the 2002-2018 study period.
Authors
- Chu, Singfat
Objective is to infer if the expansion of public transportation provision (bus and Rapid Transit System) associate with a reduction for the competition of scarce car licenses in Singapore. Pertinent variables are adjusted for changes in population and inflation rates during the 2002-2018 study period.
Authors
- Chu, Singfat
The research investigates if the demand for vehicle licenses in Singapore which is availed via bimonthly auctions in defined categories catering to cars and motorcycles has been influenced by two extensions of public transportation: (1) Increase in track length of the Rapid Transit System comprising MRT and LRT and (2) Bus Service Enhancement Programme wherein the government provided $1b between 2012 and 2017 to increase the fleet size by 1,000 (about +20%) , open up new routes and improve general standards. All the data were collected from public sources e.g. (1) https://www.singstat.gov.sg/find-data/search-by-theme/population/population-and-population-structure/latest-data (2) https://data.gov.sg/dataset/rail-length (3) https://www.lta.gov.sg/content/ltaweb/en/publications-and-research.html The regression model applied in the 4 vehicle categories was: BidRatio ~ a0 + a1SpilloverRate + a2lnCOEQuota + a3lnCOEPremium + a4RTSLength + a5*BSEPdummy where BidRatio is the ratio of bids to quota in each auction and which is further adjusted for population growth versus base year=2002. SpilloverRate is the ratio of unsuccessful bids in the preceding auction to the current quota and which is further adjusted for population growth versus base year=2002. lnCOEQuota is the logged quota of licenses in each auction. Log transformation is applied in view of wide quota variability. lnCOEPremium is the logged premium or uniform price arrived at in each auction. Log transformation is applied in view of wide premium variability. RTSLength is the sum of the MRT and LRT track lengths at the end of each year. An alternative is the number of RTS stations. Regression findings results would have remained the same. BSEPdummy is defined as 0 prior to Sep 2012 and 1 thereafter with the progressive addition of 1,000 new buses to open up new routes and improve service standards. Any statistical software can be used for the regression analyses. The author used StatsTools. Findings: The regression analyses indicate that the increase in RTS track length corelated with a decrease in the demand for car and motorcycle licenses while BSEP only cut down the demand for motorcycle licenses.
Authors
- Chu, Singfat
The research investigates if the demand for vehicle licenses in Singapore which is availed via bimonthly auctions in defined categories catering to cars and motorcycles has been influenced by two extensions of public transportation: (1) Increase in track length of the Rapid Transit System comprising MRT and LRT and (2) Bus Service Enhancement Programme wherein the government provided $1b between 2012 and 2017 to increase the fleet size by 1,000 (about +20%) , open up new routes and improve general standards. All the data were collected from public sources e.g. (1) https://www.singstat.gov.sg/find-data/search-by-theme/population/population-and-population-structure/latest-data (2) https://data.gov.sg/dataset/rail-length (3) https://www.lta.gov.sg/content/ltaweb/en/publications-and-research.html The regression model applied in the 4 vehicle categories was: BidRatio ~ a0 + a1SpilloverRate + a2lnCOEQuota + a3lnCOEPremium + a4RTSLength + a5*BSEPdummy where BidRatio is the ratio of bids to quota in each auction and which is further adjusted for population growth versus base year=2002. SpilloverRate is the ratio of unsuccessful bids in the preceding auction to the current quota and which is further adjusted for population growth versus base year=2002. lnCOEQuota is the logged quota of licenses in each auction. Log transformation is applied in view of wide quota variability. lnCOEPremium is the logged premium or uniform price arrived at in each auction. Log transformation is applied in view of wide premium variability. RTSLength is the sum of the MRT and LRT track lengths at the end of each year. An alternative is the number of RTS stations. Regression findings results would have remained the same. BSEPdummy is defined as 0 prior to Sep 2012 and 1 thereafter with the progressive addition of 1,000 new buses to open up new routes and improve service standards. Any statistical software can be used for the regression analyses. The author used StatsTools. Findings: The regression analyses indicate that the increase in RTS track length corelated with a decrease in the demand for car and motorcycle licenses while BSEP only cut down the demand for motorcycle licenses.
Authors
- Chu, Singfat
The data was used to illustrate how the endogenously related per capita RTS and bus riderships between 1994 and 2017 in Singapore have been influenced by a combination of carrot policies promoting increased affordability, reach, capacity and stick policies such as the Vehicle Quota System which has led to the world's most expensive cars.
Authors
- Chu, Singfat