Research on manufacturing enterprises employees CWB based on combining BN with computational experiment

doi:10.16265/j.cnki.issn1003-3033.2017.08.005

Abstract

Abstract: In order to avoid negative effects of the manufacturing enterprise employees counterproductive work behavior on organizational safety and performance, this paper studies a new way of combing BN with computational experimental method to build on evolution model for CWB. First, based onthe individual behavior mechanism of CWB and real data on Chinese manufacturing enterprises, a BN structural model for CWB can be acquired by parameter learning. And then interactive rules are designed for employees group behaviors on the basis of the BN model, social network theory and social exchange theory, which are embedded in the computational experiment model to simulate the CWB evolution process. The research shows that the growth of employees will not lead to the diffusion of CWB, the employees conscientiousness and distributing fairly have a significant influence on CWB, that both the scope of communication and the geographical relationship between employees will lead to deterioration of CWB, but the key to control is preventing initial polarization public opinion, and that while parallel management and organic organization can control group CWB, there are risks in implementation.

Key words: counterproductive work behaviors(CWB), Bayesian network(BN), computational experiment, control strategy, manufacturing enterprise

CLC Number:

X912

ZHAO Xu, TIAN Ye, HU Bin. Research on manufacturing enterprises employees CWB based on combining BN with computational experiment[J]. China Safety Science Journal, 2017, 27(8): 25-31.

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