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Work-family conflict and job turnover

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1 Work-family conflict and job turnover
Emily Hughes Department of Experimental Psychology, University of Oxford Introduction Both work-family interference (WIF) and family-work interference (FIW) have been theorised to predict job turnover. One view is that FIW will lead to absenteeism, whilst WIF will cause turnover (Frone, 2003). In contrast, Frone et al.’s (1997) ‘Integrative model of the work-family interface’ hypothesised that FIW precedes turnover intent and behaviour, whilst WIF predicts marital separation; Frone et al. did not test this model with turnover data. The current study sought to clarify the relationship between work-family conflict (WFC) and turnover intention and behaviour. It has been suggested that ‘intention to leave’ acts an intervening variable between job-related variables and turnover (Sjoberg & Sverke, 2000). Greenhaus et al., (1997) found that ‘intent’ mediated the effect of WFC (combined measure) on turnover; these authors urged future researchers to distinguish between WIF and FIW to determine differential effects on turnover. Past WFC research has largely used ‘intention to leave’ as a proxy for actual turnover. However, predictors of ‘intent’ and actual turnover can differ. There have been calls for research using actual turnover data (Nohe & Sonntag, 2014). Objective: This study assesses the relative influence of WIF and FIW on intention to leave and actual turnover 12 months later. It tests a mediated pathway and assesses intention to leave as a proxy variable for turnover (see Fig. 1). Table 1: Hierarchical multiple regression predicting ‘intention to leave’ Results Antecedents of intention to leave (Table 1) Significant antecedents of intention to leave were younger age, lower job satisfaction and organisational commitment, and higher WIF WFC accounted for 4.5% of the variance in turnover intention; only WIF was significant Antecedents of actual turnover (Table 2) Significant antecedents of actual turnover were younger age, lower job satisfaction, higher FIW, and prior intention to leave After controlling for the effects of demographic and work variables, the WFC variables only accounted for an additional 1.5% of the variance in turnover FIW was the only significant work-family predictor of turnover Mediation effects The role of ‘intent to leave’ as a mediator between WFC and turnover was tested; there was no evidence of a mediated effect for FIW (see Table 2) Intention as proxy for turnover The two regression analysis models showed a different pattern of results (Fig. 2). The model predicting ‘Intention’ (Table 1) accounted for 41% of the variance and was significant F(8, 348) = 30.33, p < .001 In the model predicting actual turnover, the same variables (steps 1-3 of the model) accounted for 7.3% of the variance. The addition of ‘intention to leave’ as an independent variable, at step 4, increased the total variance explained in actual turnover to 20%; the model was significant F(9, 347) = 9.68, p < .001 Fig. 2. Percentage of variance explained in the two models Fig. 1. Relationships tested in this study WIF FIW Intent to leave Turnover Conclusions This study tested conflicting hypotheses, proposed by Frone and colleagues, regarding the relationship between WFC and turnover. It also established whether ‘intention to leave’ is a useful proxy for ‘actual turnover’ in WFC research. WIF preceded ‘intention’, whilst FIW predicted turnover, lending support to Frone et al.’s (1997) integrative model Prior authors have proposed that spillover of family demands into the work role may precipitate job turnover in an attempt to reduce strain and better meet family needs (Boyar et al., 2003) ‘Intention to leave’ may produce misleading results if used as a proxy for turnover behaviour The present study highlights the need for employers to assist employees in dealing with family demands, for instance by introducing more flexible hours and support for childcare Table 2: Hierarchical multiple regression predicting turnover, testing for mediation by ‘intention to leave’ Method Sample Data were collected by questionnaire from 2 public sector organisations in the UK (N=357). Twelve months later, staff lists showed that 59 (16%) of participants had left their organisation. The sample included administrative staff, general managers, health workers, and professional/technical workers (84% female); age years (M = 42 years). Measures Demographics: Age, gender, no. of children under 18 years, organisation type Work variables: Job satisfaction, organisational commitment Work-family conflict: WIF, FIW Outcome measures: Intention to leave, job turnover This work formed part of the author’s DPhil research, supervised by Dr K.R. Parkes, University of Oxford, and funded by the Newton Abraham studentship.. Contact:


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