Leader-member Exchange Social Comparison and Employee Voice Behavior: An Empirical Study based on Multiple Linear Regression Model

Zhiling Wang, Mingjian Zhou

2021

Abstract

In the context of Chinese culture, employee voice behavior is confronted with the awkward situation of the contradiction between individual interests and organizational interests. This paper used SPSS and AMOS to process the questionnaire data, and explored the relationship between leader-member exchange social comparison and employee voice behavior by establishing multiple regression model and structural equation model. The results show that leader-member exchange social comparison is positively correlated with employee voice behavior. This study enriches the leader-member exchange theory and provides theoretical support for the enterprise management mode reform in the modern market environmen.

Paper Citation

in Harvard Style

Wang Z. and Zhou M. (2021). Leader-member Exchange Social Comparison and Employee Voice Behavior: An Empirical Study based on Multiple Linear Regression Model. In Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA, ISBN 978-989-758-589-0, pages 152-157. DOI: 10.5220/0011344300003437

in Bibtex Style

@conference{pmbda21,
author={Zhiling Wang and Mingjian Zhou},
title={Leader-member Exchange Social Comparison and Employee Voice Behavior: An Empirical Study based on Multiple Linear Regression Model},
booktitle={Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,},
year={2021},
pages={152-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011344300003437},
isbn={978-989-758-589-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management and Big Data Analysis - Volume 1: PMBDA,
TI - Leader-member Exchange Social Comparison and Employee Voice Behavior: An Empirical Study based on Multiple Linear Regression Model
SN - 978-989-758-589-0
AU - Wang Z.
AU - Zhou M.
PY - 2021
SP - 152
EP - 157
DO - 10.5220/0011344300003437