| Title |
Driving innovation through big open linked data (BOLD): Exploring antecedents using interpretive structural modelling
|
|---|---|
| Published in |
Information Systems Frontiers, July 2016
|
| DOI | 10.1007/s10796-016-9675-5 |
| Authors |
Yogesh K. Dwivedi, Marijn Janssen, Emma L. Slade, Nripendra P. Rana, Vishanth Weerakkody, Jeremy Millard, Jan Hidders, Dhoya Snijders |
X Demographics
The data shown below were collected from the profiles of 22 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 14% |
| Netherlands | 3 | 14% |
| United States | 3 | 14% |
| Belgium | 2 | 9% |
| Chile | 1 | 5% |
| Spain | 1 | 5% |
| India | 1 | 5% |
| France | 1 | 5% |
| Portugal | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 3 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 73% |
| Scientists | 6 | 27% |
Mendeley readers
The data shown below were compiled from readership statistics for 362 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 360 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 63 | 17% |
| Student > Master | 54 | 15% |
| Student > Doctoral Student | 38 | 10% |
| Researcher | 29 | 8% |
| Professor > Associate Professor | 14 | 4% |
| Other | 57 | 16% |
| Unknown | 107 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 72 | 20% |
| Computer Science | 71 | 20% |
| Social Sciences | 47 | 13% |
| Engineering | 18 | 5% |
| Economics, Econometrics and Finance | 5 | 1% |
| Other | 27 | 7% |
| Unknown | 122 | 34% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 02 August 2017.
All research outputs
#2,524,562
of 24,500,598 outputs
Outputs from Information Systems Frontiers
#31
of 334 outputs
Outputs of similar age
#45,382
of 362,126 outputs
Outputs of similar age from Information Systems Frontiers
#2
of 10 outputs
Altmetric has tracked 24,500,598 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 334 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.8. This one has done particularly well, scoring higher than 91% of its peers.
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 362,126 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.