Abstract
Data-driven decision-making (DDDM) is said to have huge benefits for organizations. Data are generally kept in IS, and humans use these data for informed decision-making. Therefore, DDDM is fundamentally related to the adoption and use of IS by individuals. IT adoption and use is influenced by personality and cognitive style, but not much is known on how personality and cognitive style influence the adoption and use of data-driven decision support systems. Our study aims to further our understanding of this influence. Through a structured literature review of IS literature, 55 papers were found and analyzed, resulting in 14 relevant topics and 7 key papers. Our findings indicate that personality and cognitive style may influence the adoption and use of data-driven decision support systems. We provide implications for future research to obtain a better understanding of DDDM, and practitioners can use our results to realize more successful DDDM.
| Original language | English |
|---|---|
| Title of host publication | AMCIS 2017 - America's Conference on Information Systems |
| Subtitle of host publication | A Tradition of Innovation |
| Publisher | Americas Conference on Information Systems |
| Volume | 2017-August |
| ISBN (Electronic) | 9780996683142 |
| Publication status | Published - 1 Jan 2017 |
| Event | America�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 - Boston, United States Duration: 10 Aug 2017 → 12 Aug 2017 |
Conference
| Conference | America�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 |
|---|---|
| Country | United States |
| City | Boston |
| Period | 10/08/17 → 12/08/17 |
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Keywords
- Business analytics
- Cognitive style
- Data-driven decision-making
- Decision support systems
- Personality
Cite this
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Data-driven decision-making and the role of personality and cognitive style : A systematic literature review. / Wiedenhof, Tertia M.; Plomp, Marijn G.A.
AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation. Vol. 2017-August Americas Conference on Information Systems, 2017.Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - Data-driven decision-making and the role of personality and cognitive style
T2 - A systematic literature review
AU - Wiedenhof, Tertia M.
AU - Plomp, Marijn G.A.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Data-driven decision-making (DDDM) is said to have huge benefits for organizations. Data are generally kept in IS, and humans use these data for informed decision-making. Therefore, DDDM is fundamentally related to the adoption and use of IS by individuals. IT adoption and use is influenced by personality and cognitive style, but not much is known on how personality and cognitive style influence the adoption and use of data-driven decision support systems. Our study aims to further our understanding of this influence. Through a structured literature review of IS literature, 55 papers were found and analyzed, resulting in 14 relevant topics and 7 key papers. Our findings indicate that personality and cognitive style may influence the adoption and use of data-driven decision support systems. We provide implications for future research to obtain a better understanding of DDDM, and practitioners can use our results to realize more successful DDDM.
AB - Data-driven decision-making (DDDM) is said to have huge benefits for organizations. Data are generally kept in IS, and humans use these data for informed decision-making. Therefore, DDDM is fundamentally related to the adoption and use of IS by individuals. IT adoption and use is influenced by personality and cognitive style, but not much is known on how personality and cognitive style influence the adoption and use of data-driven decision support systems. Our study aims to further our understanding of this influence. Through a structured literature review of IS literature, 55 papers were found and analyzed, resulting in 14 relevant topics and 7 key papers. Our findings indicate that personality and cognitive style may influence the adoption and use of data-driven decision support systems. We provide implications for future research to obtain a better understanding of DDDM, and practitioners can use our results to realize more successful DDDM.
KW - Business analytics
KW - Cognitive style
KW - Data-driven decision-making
KW - Decision support systems
KW - Personality
UR - http://www.scopus.com/inward/record.url?scp=85048357264&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048357264&partnerID=8YFLogxK
M3 - Conference contribution
VL - 2017-August
BT - AMCIS 2017 - America's Conference on Information Systems
PB - Americas Conference on Information Systems
ER -