Using Artificial Neural Networks To Model Nonlinearity: The Case Of The Job Satisfaction_Job Performance Relationship  

Oleh:

Somers, Mark John ; Casal, Jose C.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Organizational Research Methods vol. 12 no. 3 (Jul. 2009), page 403-417.
Topik: job performance; job satisfaction; multiple regression; neural networks
Fulltext: 403.pdf (254.18KB)

Isi artikel

Neural networks are advanced pattern recognition algorithms capable of extracting complex, nonlinear relationships among variables. This study examines those capabilities by modeling nonlinearities in the job satisfaction–job performance relationship with multilayer perceptron and radial basis function neural networks. A framework for studying nonlinear relationships with neural networks is offered. It is implemented using the job satisfaction–job performance relationship with results indicative of pervasive patterns of nonlinearity.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali