Comparison of the Artificial Neural Network Method and Structural Equation Method for Designing Employee's Justice Perception Model

Message:
Abstract:
Comparing the validity and the fitness power of two methods of structural equations (SEM), and artificial neural network (ANN) in the field of human resource studies represents the main goal of this article. A conceptual model was examined by both SEM and ANN, including all functions of HRM, individual culture, organizational culture and characteristics of accountability system as independent variables and the employee's justice perception as dependent variable. This survey research was implemented within three Iranian Banks (Mellat, Tejarat and keshvarzi) by random sampling of 325 employees. The researchers used the R² value as the metric of comparison that comes up with these
Findings
1- There was not significant difference between the performance of SEM and ANN when we had a few number of independent variables. When the number of independent variables increased, we found strong support for ANN having better result than SEM, with regards to R². The outcomes of this research were partially similar to the same studies and provide useful insight into capabilities of ANN and SEM used in HRM researches.
Language:
Persian
Published:
Human Resource Management Researches, Volume:2 Issue: 3, 2011
Page:
81
magiran.com/p929288  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!