Utilizing short version big five traits on crowdsouring release_pz4u4kkmkff4bcafeqodgfakwm

by Kousaku Igawa, Kunihiko Higa, Tsutomu Takamiya

Published in International Journal of Crowd Science by Emerald.

2020   Volume ahead-of-print, Issue ahead-of-print

Abstract

<jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> The purpose of this paper is to examine the efficacy of the Japanese ten-item personality inventory (TIPI-J), a short version of the big five (BF) questionnaire, on crowdsourcing. The BF traits are indicators of personality and are said to be an effective predictor of study performance in various occupations. BF can be used in crowdsourcing to predict crowd workers' performance; however, it will be difficult to use in practice for two reasons like the time-and-effort issue and the bias issue. In this study, an empirical analysis is conducted on crowdsourcing to examine if TIPI-J can solve those issues. </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> To investigate the issues, two tasks are posted on a crowdsourcing provider. Both TIPI-J and full version BF are conducted before and after selecting crowd workers. Structural validity and convergence validity are tested with correlation analysis between before (TIPI-J) and after (full version BF) data to examine the bias issue. Additionally, those correlations are compared with previous study and significances are examined. </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> The correlations in "conscientiousness" is 0.45-0.50, respectively, compared with a previous study, those two correlations did not show significance. This indicates that no clear bias exists. </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> This is the first research to investigate the efficacy of TIPI-J on crowdsourcing and showed that TIPI-J can be a useful tool for predicting crowd workers' performance and thus it can help to select appropriate crowd workers. </jats:sec>
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