Data-driven decision-making and the role of personality and cognitive style: A systematic literature review

Tertia M. Wiedenhof, Marijn G.A. Plomp

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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 languageEnglish
Title of host publicationAMCIS 2017 - America's Conference on Information Systems
Subtitle of host publicationA Tradition of Innovation
PublisherAmericas Conference on Information Systems
Volume2017-August
ISBN (Electronic)9780996683142
Publication statusPublished - 1 Jan 2017
EventAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 - Boston, United States
Duration: 10 Aug 201712 Aug 2017

Conference

ConferenceAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017
CountryUnited States
CityBoston
Period10/08/1712/08/17

Keywords

  • Business analytics
  • Cognitive style
  • Data-driven decision-making
  • Decision support systems
  • Personality

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