Linking Human Resource Management Practices and Firms' Performance Using Neural Networks

Abstract

This paper investigates relationship between human resource management practices (HRM) and performance. This paper demonstrates how analysis to reveal relationship among dependent and independent variables in HRM-performance link can be done using artificial neural networks (ANN). Statistical package for the social sciences (SPSS) was used to produce ANN. It argues that HRM research should utilize the breadth of statistics available including data science statistics. This study utilizes positivist paradigmatic stance, descripto-explanatory research design, and survey methodology. Questionnaires were used in data collection. The study found that HRM practices are important in predicting financial and non-financial performance. Synergetic relationship among HRM practices was also found to predict financial and non-financial performance of financial cooperatives in Kenya. Apart from exploring HRM independent variables, their interrelationships must be explored and reported in literature.