| Title |
A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance
|
|---|---|
| Published in |
Financial Innovation, November 2015
|
| DOI | 10.1186/s40854-015-0014-5 |
| Authors |
Lang Zhang, Haiqing Hu, Dan Zhang |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Pakistan | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 167 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | <1% |
| Unknown | 166 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 22 | 13% |
| Student > Ph. D. Student | 20 | 12% |
| Lecturer | 9 | 5% |
| Student > Bachelor | 9 | 5% |
| Researcher | 8 | 5% |
| Other | 25 | 15% |
| Unknown | 74 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 41 | 25% |
| Economics, Econometrics and Finance | 15 | 9% |
| Engineering | 13 | 8% |
| Computer Science | 6 | 4% |
| Mathematics | 3 | 2% |
| Other | 14 | 8% |
| Unknown | 75 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2017.
All research outputs
#18,572,844
of 23,003,906 outputs
Outputs from Financial Innovation
#138
of 158 outputs
Outputs of similar age
#280,073
of 387,726 outputs
Outputs of similar age from Financial Innovation
#2
of 2 outputs
Altmetric has tracked 23,003,906 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 158 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 387,726 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.