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Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies

Business

Detecting causal relationships between work motivation and job performance: a meta-analytic review of cross-lagged studies

N. Wang, Y. Luan, et al.

Explore the groundbreaking findings of a meta-analytic study that reveals how work motivation significantly boosts job performance. Conducted by Nan Wang, Yuxiang Luan, and Rui Ma, this research demonstrates that motivating employees leads to better performance outcomes, while the reverse is not true. Dive into the insights that could enhance workplace dynamics and productivity.

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~3 min • Beginner • English
Abstract
Given that competing hypotheses about the causal relationship between work motivation and job performance exist, the current research utilized meta-analytic structural equation modeling (MASEM) methodology to detect the causal relationships between work motivation and job performance. In particular, completing hypotheses were checked by applying longitudinal data that include 84 correlations (n = 4389) from 11 independent studies measuring both work motivation and job performance over two waves. We find that the effect of motivation (T1) on performance (T2), with performance (T1) controlled, was positive and significant (β = 0.143). However, the effect of performance (T1) on motivation (T2), with motivation (T1) controlled, was not significant. These findings remain stable and robust across different measures of job performance (task performance versus organizational citizenship behavior), different measures of work motivation (engagement versus other motivations), and different time lags (1–6 months versus 7–12 months), suggesting that work motivation is more likely to cause job performance than vice versa. Practical and theoretical contributions are discussed.
Publisher
Humanities and Social Sciences Communications
Published On
May 09, 2024
Authors
Nan Wang, Yuxiang Luan, Rui Ma
Tags
work motivation
job performance
meta-analysis
causal relationship
longitudinal data
structural equation modeling
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