Civility, Job Satisfaction, and Intentions to Quit

Civility is an important research topic in today’s work environment, especially given concerns about retaining employees in the increasingly mobile labor market (Pearson & Porath, 2005). Although much of the research on civil work behaviors focuses on the negative impact of incivility, ongoing research at the Veterans Administration (VA) utilizes a strengths-based approach that identifies ways to increase civility rather than to decrease incivility (Osatuke, Moore, Ward, Dyrenforth, & Belton, 2009). VA’s civility research had found that workplace civility predicts organizational performance (Moore, Osatuke, & Howe, 2008), and that it exerts a positive influence on patient satisfaction (Osatuke et al., 2009) and employee job satisfaction (Moore, et al. 2008). While job satisfaction is important to consider, previous research suggests that employee intention to quit is the best leading indicator of actual employee turnover (Griffeth, Hom, & Gaertner, 2000), an important cost-related outcome for organizations. The current study examined the relationship between civility, job satisfaction, and intentions to quit using longitudinal techniques which accounted for the contextual effects of workgroups nested within facilities. All previous multi-level or contextual conceptualizations of incivility have involved cross-sectional data. The only study to examine civility, job satisfaction, and turnover intentions longitudinally was Moore et al. (2008), and those authors did not use intention to quit in their analysis, nor did they adjust their models for the multilevel nature of the data. Our approach also extended current research methodologically through consideration of the nested structure of the data and accounting for dependencies which could have led to misleadingly small standard error estimates and biased decision making regarding the significance of path coefficients. The study used archival de-identified data from 160 Veterans Health Administration (VHA) facilities (N ˜ 85,000 employees employees, and 5,883 workgroups per year) from 2009-2011. The data had workgroup and facility identifiers, permitting the contextual analyses. The primary aim of the study was to determine the causal impact of civility on job satisfaction and intentions to quit. Given the nested structure of the data, I was also interested in using contextual modeling techniques to account for the clustering of workgroups within facilities. The modeling process resulted in two panel models, one cross-lagged and the other a non-recursive simultaneous influence model where at Times 2 and 3 there were reciprocal effects present. The purpose of the cross-lagged models was to examine the influence of the three variables on one another over a one year lag, whereas the simultaneous influence model was meant to test the possibility that reciprocal contemporary influences coupled with stability paths between the same measures from time i to time i + 1 could account for the observed covariance structure. Findings suggested that within a given year, civility and job satisfaction may be more likely to influence each other equally; but from one year to the next, civility is a stronger driver of job satisfaction than vice versa. With respect to intentions to quit, both models supported the notion that civility is a stronger driver of intentions to quit than the converse.

Name thesis:degree_name

PhD

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Arts and Sciences: Psychology

Grantor dc:publisher

University of Cincinnati

Year dc:date

2012

Author dc:creator

• Brown, Andrew B.

Contributors dc:contributor

• Howe, Steven

• Psychology
• Civility
• Job Satisfaction
• Intentions to Quit

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=ucin1346170898

OAI identifier oai:identifier

oai:etd.ohiolink.edu:ucin1346170898