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How Does the Absence of Job Embeddedness Contribute to Nurses' Turnover Intention? A Fuzzy-Set Qualitative

Xin Wang¹, Ming Liu², Jun-E Zhang³

¹Faculty of Health Sciences and Sports, Macao Polytechnic University, Macao, China, mpu.edu.mo.

Journal of Nursing Management

|June 20, 2026

Summary

This summary is machine-generated.

Nurse turnover intention is complex, influenced by combined job embeddedness dimensions. Lack of organizational fit and sacrifice are key drivers, while collaboration and competition can prevent nurses from leaving.

Keywords:

job embeddedness nurses qualitative comparative analysis turnover intention

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Area of Science:

Nursing
Healthcare Management
Organizational Psychology

Background:

Nurse turnover significantly contributes to the global nursing shortage.
Job embeddedness is a critical factor influencing nurses' turnover intentions.
Previous research overlooked the combined effects of job embeddedness dimensions on turnover intention.

Purpose of the Study:

To explore how job embeddedness dimensions interact to form configurations leading to nurses' turnover intention or retention.
To identify specific patterns of job embeddedness that predict nurses' decisions to leave or stay.

Main Methods:

Cross-sectional study utilizing fuzzy-set qualitative comparative analysis (fsQCA).
Data collected from 232 nurses across six medical institutions in Hong Kong.
fsQCA analyzed set relationships between six job embeddedness dimensions and turnover intention, with robustness checks and ordered logit regression.

Main Results:

Multiple configurations of job embeddedness dimensions predict nurses' turnover intention.
No single job embeddedness dimension is a necessary condition for turnover or retention.
Five configurations were identified that contribute to turnover intention, and six configurations contributed to no turnover intention.

Conclusions:

The absence of organizational fit and sacrifice emerged as a core condition for nurses' turnover intention.
Interplay between job embeddedness dimensions creates configurations that can prevent nurses from leaving.
Findings offer targeted intervention strategies for managers to reduce nurse turnover.