Estimating and decomposing most productive scale size in parallel DEA networks with shared inputs: A case of China's Five-Year Plans
Saeed Assani, Jianlin Jiang, Ahmad Assani, Feng Yang

TL;DR
This paper introduces a novel DEA-based model to estimate and decompose the most productive scale size in parallel production systems with shared inputs, demonstrated through China's Five-Year Plans.
Contribution
It proposes a relational model for measuring MPSS in parallel systems and proves its decomposability into subsystem MPSS, aiding targeted improvements.
Findings
Industry sector had better economic scale than Agriculture.
Last two FYPs were the most effective.
MPSS decomposition helps identify subsystem inefficiencies.
Abstract
Attaining the optimal scale size of production systems is an issue frequently found in the priority questions on management agendas of various types of organizations. Determining the most productive scale size (MPSS) allows the decision makers not only to know the best scale size that their systems can achieve but also to tell the decision makers how to move the inefficient systems onto the MPSS region. This paper investigates the MPSS concept for production systems consisting of multiple subsystems connected in parallel. First, we propose a relational model where the MPSS of the whole system and the internal subsystems are measured in a single DEA implementation. Then, it is proved that the MPSS of the system can be decomposed as the weighted sum of the MPSS of the individual subsystems. The main result is that the system is overall MPSS if and only if it is MPSS in each subsystem.…
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Taxonomy
TopicsEfficiency Analysis Using DEA · Environmental Impact and Sustainability · Energy, Environment, Economic Growth
