Understanding the Motivation of Participants in Innovation Open Data Contests: A Task Presentation Affordance Perspective

ABSTRACT Innovation Open Data Contest (IODC) is an effective way to take advantage of public efforts to realize the great potential value of open data in the field of digital humanities. Previous literature focusses more on the challenge open data contest rather than innovation open data contest. Gi...

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Veröffentlicht in:Proceedings of the ASIST Annual Meeting 2023-10, Vol.60 (1), p.1218-1220
Hauptverfasser: Zhang, Yan, Liu, Zhouying, Zhao, Yuxiang (Chris), Wu, Dawei
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Sprache:eng
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Zusammenfassung:ABSTRACT Innovation Open Data Contest (IODC) is an effective way to take advantage of public efforts to realize the great potential value of open data in the field of digital humanities. Previous literature focusses more on the challenge open data contest rather than innovation open data contest. Given this, understanding the underlying factors motivating participants to actively engage in the contest is necessary. Based on the task affordance theory and self‐determination theory (SDT), this study aims to identify and examine how task presentation affordances of IODC influence participants' motivations and thereby shape their level of effort. We employ partial least squares structural equation modeling (PLS‐SEM) techniques to analyze the responses from 215 individuals who have previously participated in the IODC. The findings indicate that participants' level of effort in the IODC is contingent upon their perception of relatedness and competence. Moreover, hedonic affordance and connective affordance positively influence participants' perceptions of relatedness and competence. Our findings contribute to the extant literature by proposing a theoretical model to understand the participants' motivation and have practical implications for IODC's organizers.
ISSN:2373-9231
2373-9231
1550-8390
DOI:10.1002/pra2.997