A network bounded adjusted measure for dealing with dual-role factors and undesirable outputs in multi-stage systems

Abstract

ABSTRACT Dual-role factors and undesirable outputs are two factors that are often present in multi-stage production. There are two shortcomings in existing methods for evaluating production efficiency. The first is that they only study single process and ignore the internal structure of decision making units (DMUs). The second is that they ignore the impact of dual-role factors and undesirable outputs. To address the deficiencies, this paper proposes a network bounded adjusted measure (BAM) method that considers both dual-role factors and undesirable outputs. The 0–1 programming and slack based measure are respectively utilised to handle dual-role factors and undesirable outputs. Production data from 10 automotive supply chains are collected to test the validity of this method. To verify the impact of dual-role factors, we calculate the efficiency under the condition of weak disposability (WD) and the condition of ignoring dual-role factors (IDF). The results show that the efficiency under WD is generally higher than the efficiency under SD, and the efficiency under IDF is generally lower than the efficiency under WD and SD. We also compare BAM with range adjust measure (RAM). The results show that BAM has a greater capability to identify DMUs.