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A meta‐analysis of the interrelationships between employee lateness, absenteeism, and turnover: Implications for models of withdrawal behavior
Author(s) -
Berry Christopher M.,
Lelchook Ariel M.,
Clark Malissa A.
Publication year - 2012
Publication title -
journal of organizational behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.938
H-Index - 177
eISSN - 1099-1379
pISSN - 0894-3796
DOI - 10.1002/job.778
Subject(s) - absenteeism , psychology , turnover , spillover effect , meta analysis , construct (python library) , path analysis (statistics) , social psychology , statistics , economics , management , mathematics , microeconomics , medicine , computer science , programming language
Summary We meta‐analyzed the correlations between voluntary employee lateness, absenteeism, and turnover to (i) provide the most comprehensive estimates to date of the interrelationships between these withdrawal behaviors; (ii) test the viability of a withdrawal construct; and (iii) evaluate the evidence for competing models of the relationships between withdrawal behaviors (i.e., alternate forms, compensatory forms, independent forms, progression of withdrawal, and spillover model). Corrected correlations were .26 between lateness and absenteeism, .25 between absenteeism and turnover, and .01 between lateness and turnover. These correlations were even smaller in recent studies that had been carried out since the previous meta‐analyses of these relationships 15–20 years ago. The small‐to‐moderate intercorrelations are not supportive of a withdrawal construct that includes lateness, absenteeism, and turnover. These intercorrelations also rule out many of the competing models of the relationships between withdrawal behaviors, as many of the models assume all relationships will be positive, null, or negative. On the basis of path analyses using meta‐analytic data, the progression of withdrawal model garnered the most support. This suggests that lateness may moderately predict absenteeism and absenteeism may moderately predict turnover. Copyright © 2011 John Wiley & Sons, Ltd.