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Neural Correlates of Human Decision Making in Recommendation Systems: A Research Proposal

In: Information Systems and Neuroscience

Author

Listed:
  • Naveen Zehra Quazilbash

    (Institute of Business Administration)

  • Zaheeruddin Asif

    (Institute of Business Administration)

  • Syed Asil Ali Naqvi

    (Institute of Business Administration)

Abstract

Significant research has been conducted on human decision making behavior in recommendation systems during the past decade, yet it remains a challenge to design effective and efficient recommendation systems so that they not only produce useful suggestions and ease the decision making task but also turn it into a pleasurable experience. Algorithms have been designed based on research that highlight individual theoretical constructs yet there is an absence of a comprehensive model of human decision-making. This research offers an insight into the core of this issue by examining the neural correlates of human decision-making using Electroencephalography (EEG). The insights generated maybe used to construct a comprehensive model of human decision making in recommendation systems and generate new design principles for the same.

Suggested Citation

  • Naveen Zehra Quazilbash & Zaheeruddin Asif & Syed Asil Ali Naqvi, 2019. "Neural Correlates of Human Decision Making in Recommendation Systems: A Research Proposal," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph (ed.), Information Systems and Neuroscience, pages 139-145, Springer.
    • Handle: RePEc:spr:lnichp:978-3-030-01087-4_17
    DOI: 10.1007/978-3-030-01087-4_17
    as

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