Premium
Your words reveal your thoughts: A two‐wave study of assessing language dimensions in predicting employee turnover intention
Author(s) -
Seih YiTai,
Lepicovsky Marketa,
Chang YiYing
Publication year - 2020
Publication title -
international journal of selection and assessment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.812
H-Index - 61
eISSN - 1468-2389
pISSN - 0965-075X
DOI - 10.1111/ijsa.12302
Subject(s) - psychology , variance (accounting) , impression management , turnover , social desirability , social psychology , turnover intention , explained variation , applied psychology , statistics , organizational commitment , mathematics , accounting , management , economics , business
Assessing turnover intention with explicit approaches (self‐report scales) contains several measurement limitations, including social desirability, impression management, and self‐defense, potentially resulting in reduced accuracy. To improve the accuracy of assessment, the current research conducted a two‐wave study to examine whether implicit variables provide incremental effect in predicting turnover intention, after controlling for explicit variables. A computerized text analysis program, Linguistic Inquiry and Word Count, was used to identify language dimensions in participants' writing samples, and these exported scores serve as implicit language variables. Results demonstrate that language variables provide significant incremental effect (9% of explained variance) in predicting turnover intention, and this effect lasted at a one‐month follow‐up. The language dimensions signal topics of concern associated with turnover intention.