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

Naveen Zehra Quazilbash (), Zaheeruddin Asif () and Syed Asil Ali Naqvi
Additional contact information
Naveen Zehra Quazilbash: Institute of Business Administration
Zaheeruddin Asif: Institute of Business Administration
Syed Asil Ali Naqvi: Institute of Business Administration

A chapter in Information Systems and Neuroscience, 2019, pp 139-145 from Springer

Abstract: 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.

Keywords: Decision making; Recommendation systems; EEG; Source localization (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-030-01087-4_17

Ordering information: This item can be ordered from
http://www.springer.com/9783030010874

DOI: 10.1007/978-3-030-01087-4_17

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().