Does More Informative Job Title Lead to More Successful Hirings? A Randomized Field Experiment on an Online Labor Market Platform
Files
Date
2025-01-07
Authors
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
3874
Ending Page
Alternative Title
Abstract
Online labor market platforms have rapidly developed over the past few years. The job title, as a crucial piece of observable information, research about its impact on job-related behaviors is lack. In this study, we selected one of the largest blue-collar online labor market platforms in China, constructing a large-scale field experiment on job titles with different degrees of information disclosure depth and breadth generated by the proposed model based on Large language model (LLM), involving more than 50,000 job listings and more than 800,000 users in the platform, to investigate whether the information disclosed in the job title affects the likelihood of the job being viewed and successfully matched. Findings claim the compared with the central route (processing depth information), peripheral route information processing (processing breadth information) is the dominant method on online labor market platforms. Additionally, sufficient processing of breadth information significantly impacts subsequent behaviors.
Description
Keywords
Crowd-based Platforms, elaboration likelihood model, field experiment, job title, large language model (llm), online labor market
Citation
Extent
10
Format
Geographic Location
Time Period
Related To
Proceedings of the 58th Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Collections
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.