Title |
A dynamic computational model of employees goal transformation: Using self-determination theory
|
---|---|
Published in |
Motivation and Emotion, February 2019
|
DOI | 10.1007/s11031-019-09753-1 |
Authors |
Ying Zhang, Jian Zhang, Jacques Forest, Zhihua Chen |
X Demographics
The data shown below were collected from the profiles of 3 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 States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 67% |
Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 5 | 14% |
Student > Master | 5 | 14% |
Student > Postgraduate | 4 | 11% |
Student > Bachelor | 3 | 8% |
Student > Doctoral Student | 3 | 8% |
Other | 5 | 14% |
Unknown | 12 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 11 | 30% |
Business, Management and Accounting | 7 | 19% |
Social Sciences | 2 | 5% |
Linguistics | 1 | 3% |
Economics, Econometrics and Finance | 1 | 3% |
Other | 3 | 8% |
Unknown | 12 | 32% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 11 February 2021.
All research outputs
#3,392,371
of 23,906,448 outputs
Outputs from Motivation and Emotion
#220
of 792 outputs
Outputs of similar age
#81,904
of 451,617 outputs
Outputs of similar age from Motivation and Emotion
#6
of 16 outputs
Altmetric has tracked 23,906,448 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 792 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.7. This one has gotten more attention than average, scoring higher than 72% 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 451,617 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 81% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.