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Information Systems Research 2023

Effect of Online Professional Network Recommendations on the Likelihood of an Interview: A Field Study

Rohit Aggarwal1; Vishal Midha2; Nicholas Sullivan3

1 University of Utah · 2 Illinois State University · 3 University of Dayton

Abstract

Online professional networks (OPNs) are an increasingly common tool used by recruiters to find and vet qualified job candidates for open positions. These sites allow users to publish recommendations given by other users to supplement their profile information and add credibility to the information provided. OPN recommendations offer a rich source of information to recruiters. Unlike recommendations shared in other ways (non-OPN recommendations), OPN recommendations are publicly accessible, and candidates have complete control over which recommendations they show to others. In this study, we investigate how recommendations may have a different effect when presented as an OPN recommendation versus a non-OPN recommendation. Furthermore, we explore how to improve the effectiveness of recommendations. We conducted a field study where we leveraged the candidate tracking system of a large recruitment firm to measure the varying impact recommendations have on recruiters’ decisions. Our findings show that OPN and non-OPN recommendations that discuss an expected weakness positively affect a candidate’s likelihood of being interviewed. In contrast, recommendations that discuss an unexpected weakness have a negative effect. Furthermore, we find that non-OPN recommendations with no discussion of weakness are significantly more effective than OPN recommendations with no discussion of weakness. We then show that the potential benefits of discussing an expected weakness are more pronounced for OPN recommendations, whereas the potential harm of discussing an unexpected weakness is more severe for non-OPN recommendations.

DOI
10.1287/isre.2021.1053
Sources
openalex

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