Navigating behavioral biases in job search: overview and digital solutions

Michèle Belot, Philipp Kircher and Paul Muller

Chapter 8 in Handbook on Labour Markets in Transition, 2024, pp 163-175 from Edward Elgar Publishing

Abstract: This chapter reviews common behavioral biases in job search behavior and reviews recent literature that studies their consequences for job search effectiveness. We focus on time preferences (present bias), biased beliefs about labour market prospects, and psychological barriers such as discouragement. Next we describe how recent technological advances have opened up opportunities to overcome these biases and enhance job search effectiveness. Online platforms can offer low-cost and personalized support in the form of goal-setting assistance, improved information provision about institutional features, or tailored job search recommendations. We review the recent empirical evidence from field experiments with such tools and link the diverse results to a discussion of the challenges in designing effective recommendation systems. These include ensuring accurate information about current labour demand, the risk of increasing congestion, and offering recommendations to those sub-populations that benefit most.

Keywords: Economics and Finance; Sociology and Social Policy (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.elgaronline.com/doi/10.4337/9781839106958.00014 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Temporarily Unavailable

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:elg:eechap:19758_8

Ordering information: This item can be ordered from
http://www.e-elgar.com

Access Statistics for this chapter

More chapters in Chapters from Edward Elgar Publishing
Bibliographic data for series maintained by Darrel McCalla ().