| Literature DB >> 31284604 |
Guohua He1,2, Ran An3,4, Feng Zhang1.
Abstract
This study aims to explore the influence mechanism of cultural intelligence on work-family conflict for Chinese expatriates in cross-cultural non-profit organizations. Drawing on conservation of resources theory, this longitudinal study (six-month time lag) is the first to examine cultural intelligence as an antecedent of work-family conflict. The study also examines the mediating role of work engagement and the moderating role of leader-member exchange (LMX) in the cultural intelligence and work-family conflict relationship. The sample comprises 206 expatriate Chinese language teachers working at 45 Confucius Institutes in the US, Canada, and Russia. Results show that cultural intelligence not only reduces work-family conflict but also promotes expatriates' work engagement. The higher the work engagement, the higher the work-family conflict experienced by expatriates. LMX moderates not only the positive relationship between work engagement and work-family conflict but also the indirect effect of cultural intelligence on work-family conflict through work engagement. Thus, the indirect effect of cultural intelligence on work-family conflict through work engagement is stronger with low (compared to high) LMX. This study's findings provide implications for managers of cross-cultural non-profit organizations to better understand and solve expatriates' work-family conflict problem.Entities:
Keywords: Chinese expatriates; Confucius Institute; conservation of resources; cultural intelligence; work–family conflict
Mesh:
Year: 2019 PMID: 31284604 PMCID: PMC6651476 DOI: 10.3390/ijerph16132406
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Theoretical model.
Descriptive statistics and correlations among study variables.
| Variables | Mean | SD | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1. Gender | 0.31 | 0.462 | 1 | ||||||||
| 2. Age | 2.95 | 1.818 | 0.064 | 1 | |||||||
| 3. Education level | 2.25 | 0.563 | −0.111 | 0.051 * | 1 | ||||||
| 4. Tenure | 3.16 | 1.302 | 0.072 | −0.012 | 0.002 * | 1 | |||||
| 5. Country | 0.797 | 0.46 | 0.032 | 0.041 | 0.013 | 0.067 | 1 | ||||
| 6. CQ | 3.546 | 0.982 | −0.12 | −0.006 | 0.208 * | 0.067 | 0.078 | (0.91) | |||
| 7. WFC | 3.213 | 0.97 | −0.07 ** | 0.03 ** | 0.114 ** | −0.025 ** | 0.019 | −0.450 ** | (0.83) | ||
| 8. WE | 3.122 | 0.767 | −0.12 | −0.014 | 0.200 * | 0.058 ** | 0.072 * | 0.337 ** | 0.295 ** | (0.85) | |
| 9. LMX | 3.658 | 0.598 | −0.107 | 0.011 | 0.208 | 0.11 | 0.092 | 0.225 ** | −0.298 * | 0.312 ** | (0.94) |
Note. N = 206; CQ = cultural intelligence, WFC = work–family conflict, WE = work engagement, LMX = leader–member exchange. Gender is coded as 0 = female, 1 = male. Age is coded as 1 = 18–25 years, 2 = 26–30 years, 3 = 31–35 years, 4 = 36–40 years, 5 = 41–45 years, 6 = 46 years and above. Education level is coded as 1 = bachelor’s degree, 2 = master’s student/graduate, 3 = Ph.D. student/graduate. Tenure is coded as 1 = 0–3 months, 2 = 3 months–1 year, 3 = 1–2 year(s), 4 = 2–4 years, 5 = 5 years and above. Country is coded as 1 = America, 2 = Canada, 3 = Russia. * p < 0.05, ** p < 0.01.
Results of confirmatory factor analysis.
| Measurement Models |
|
| CFI | TLI | IFI | RMSEA | |
|---|---|---|---|---|---|---|---|
| Baseline model | 876.528 | 318 | 2.756 | 0.914 | 0.905 | 0.914 | 0.078 |
| Unmeasured latent factor model | 728.358 | 298 | 2.444 | 0.921 | 0.909 | 0.922 | 0.072 |
| Three-factor model | 1479.501 | 321 | 4.609 | 0.821 | 0.804 | 0.822 | 0.112 |
| Two-factor model | 2030.720 | 323 | 6.287 | 0.736 | 0.714 | 0.738 | 0.136 |
| One factor model | 2613.072 | 324 | 8.065 | 0.647 | 0.617 | 0.648 | 0.157 |
Note. The baseline model includes the study’s four variables (cultural intelligence, work-engagement, work–family conflict, and LMX); the unmeasured latent factor model includes another common variance factor based on the baseline model; the three-factor model is cultural intelligence + work-engagement, work–family conflict, LMX; the two-factor model is cultural intelligence + work-engagement, work–family conflict + LMX; the one factor model is cultural intelligence + work-engagement + work–family conflict + LMX, “+” indicates that variables are combined into a single model.
Results of multiple regression analysis.
| Variables | Work–Family Conflict | Work Engagement | ||||||
|---|---|---|---|---|---|---|---|---|
| Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 | Model 8 | |
| Control | ||||||||
| Gender | −0.058 * | 0.01 | 0.015 ** | 0.013 * | 0.014 | 0.027 | −0.103 * | −0.002 |
| Age | 0.028 | 0.036 | 0.041 | 0.045 * | 0.059 ** | 0.066 ** | −0.018 | −0.007 |
| Education level | 0.107 | −0.024 | −0.027 * | −0.02 | −0.006 * | −0.008 * | 0.19 | −0.003 |
| Tenure | −0.021 * | −0.071 | −0.067 | −0.061 | −0.022 | −0.019 | 0.066 * | −0.008 |
| Country | 0.024 | 0.021 | 0.023 | 0.018 | 0.019 | 0.022 | −0.068 | −0.034 |
| Independent variable | ||||||||
| CQ | −0.560 *** | −0.434 * | −0.040 | −0.052 | 0.488 *** | |||
| Mediator and moderator | ||||||||
| WE | 0.506 *** | 0.423 *** | 0.572 *** | 0.541 *** | ||||
| LMX | −0.414 *** | −0.308 *** | ||||||
| WE x LMX | −0.152 ** | |||||||
|
| 0.022 | 0.410 | 0.472 | 0.486 | 0.552 | 0.567 | 0.056 | 0.392 |
|
| 0.022 | 0.388 | 0.450 | 0.076 | 0.530 | 0.015 | 0.056 | 0.336 |
| F | 0.883 * | 25.050 *** | 32.073 *** | 28.965 *** | 36.710 *** | 34.574 *** | 3.020 * | 54.737 *** |
| 0.883 * | 142.758 *** | 183.985 *** | 20.312 *** | 94.361 *** | 7.619 ** | 3.020 * | 307.318 *** | |
Note. N = 206. Standardized coefficients are reported. CQ = cultural intelligence, WE = work engagement, LMX = leader–member exchange. *** p < 0.001, ** p < 0.01, * p < 0.05 (two-tailed).
Figure 2Interactive effects of work engagement and LMX on work–family conflict.
Results of the moderated path analysis.
| Moderator | CQ (X)→WE (M)→WFC (Y) | ||||
|---|---|---|---|---|---|
| Stage | Effect | ||||
| First | Second | Direct | Indirect | Total | |
| PMX | PYM | PYX | PYM × PMX | PYX + PYM × PMX | |
| Low-level LMX (−1SD) | 0.622 ** | 0.591 ** | 0.352 ** | 0.367 ** | 0.719 ** |
| High-level LMX (+1SD) | 0.541 ** | 0.287 ** | 0.366 ** | 0.156 ** | 0.522 ** |
| Difference | −0.081 | −0.304 * | 0.014 | −0.211 * | −0.197 ** |
Note. N = 206. LMX = leader–member exchange, CQ = cultural intelligence, WE = work engagement, WFC = work–family conflict; “→”refers to the path of effect from one variable to another; PMX: Path from cultural intelligence to work engagement; PYM: Path from work engagement to work–family conflict; PYX: Path from cultural intelligence to work–family conflict. Low-level LMX refers to one standard deviation below the LMX mean; high-level LMX refers to one standard deviation above the LMX mean. ** p < 0.01, * p < 0.05 (two-tailed).