TY - JOUR
T1 - Using an HRM pattern approach to examine the productivity of manufacturing firms - An empirical study
AU - Chen, Liang-Hsuan
AU - Liaw, Shu Yi
AU - Lee, Tzai Zang
PY - 2003/10/7
Y1 - 2003/10/7
N2 - Manufacturing firms are always faced with the problem of promoting operational performance and labor-force management. The utilization of human resources is closely correlated with operations and production performance. This study investigates the correlation between human resource management (HRM) and business performance of large-scale manufacturing firms in Taiwan. First, 16 subjects of HRM are designed to survey the importance level and achievement level of HRM by the sample firms. Productivity indices are also defined to measure business performance. Based on the survey, four critical HRM factors including 12 subjects are extracted by factor analysis. The difference between importance level and achievement level of subjects contained in each factor is examined. Furthermore, considering importance and achievement levels of HRM as features, fuzzy clustering analysis is employed to categorize the firms into four patterns. With various HRM characteristics, each pattern has different business performance in terms of productivity. Using a pattern approach, these findings can aid the firms in each pattern to improve their productivity by improving their HRM strategies.
AB - Manufacturing firms are always faced with the problem of promoting operational performance and labor-force management. The utilization of human resources is closely correlated with operations and production performance. This study investigates the correlation between human resource management (HRM) and business performance of large-scale manufacturing firms in Taiwan. First, 16 subjects of HRM are designed to survey the importance level and achievement level of HRM by the sample firms. Productivity indices are also defined to measure business performance. Based on the survey, four critical HRM factors including 12 subjects are extracted by factor analysis. The difference between importance level and achievement level of subjects contained in each factor is examined. Furthermore, considering importance and achievement levels of HRM as features, fuzzy clustering analysis is employed to categorize the firms into four patterns. With various HRM characteristics, each pattern has different business performance in terms of productivity. Using a pattern approach, these findings can aid the firms in each pattern to improve their productivity by improving their HRM strategies.
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U2 - 10.1108/01437720310479750
DO - 10.1108/01437720310479750
M3 - Article
AN - SCOPUS:0141755157
SN - 0143-7720
VL - 24
SP - 299
EP - 320
JO - International Journal of Manpower
JF - International Journal of Manpower
IS - 3
ER -