چکیده:
Managers tend to improve resource (input) utilization in organizations to obtain the highest level of productivity. Additionally, many industrial units have multi-stage structure in which the output of one stage is the input of the next one. This paper, for the first time, presents data envelopment analysis (DEA) approaches to achieve the most productivity in two-stage decision making units (DMUs). By considering internal activities in system, radial and non-radial models are proposed to evaluate network DMUs and radial model is developed to identify the most productive scale size (MPSS) pattern. Proposed models are applied to optimize the performance of bank branches as units with two-stage structure. Results show that efficiency scores and improvements needed in costs and paid interests (inputs) to get more incomes and facilities (outputs). This study provides managers with information to propose better strategies to improve not only the overall performance but also the efficiency of each stage.
خلاصه ماشینی:
com An important issue here is the identification of MPSS pattern for each stage and for overall DMU that can help managers to improve the scale size of inputs and outputs values to obtain the highest level of productivity.
(Banker, Cooper, Seiford & Zhu (2004)) In this paper, for the first time, models are proposed to identify MPSS pattern for two-stage-structure DMUs. Setting scale efficient target to a system aids managers in optimal use of existing resources and gives information about whether increments in resources are profitable or not.
By considering the intermediate products Wang, Gopal & Zionts (1997) proposed a DEA model to measure the efficiency score of two-stage structure DMUs, then Seiford and Zhu (1999) extended their approach.
Yang, Wu, Liang, Bi & Wu (2011) presented a non-linear model in order to measure the efficiency of two-member supply chains, as two-stage DMUs. Paradi, Rouatt & Zhu (2011) developed a two-stage DEA approach by consideration geographic location and market size and applied it to assess bank branches.
A stochastic two-stage network DEA model was introduced by Zhou, Lin, Xiao, Ma & Wu (2017) as a deterministic linear programming model under the assumption that components of inputs, outputs and intermediate products are related with some basic stochastic factors ,and was applied to evaluate 16 commercial banks in China.
Galagedera, Roshdi, Fukuyama & Zhu (2018) developed a network DEA model to assess overall and stage-level performance of fund management function as a three-stage production process.