Issue |
RAIRO-Oper. Res.
Volume 58, Number 5, September-October 2024
|
|
---|---|---|
Page(s) | 3871 - 3893 | |
DOI | https://doi.org/10.1051/ro/2024080 | |
Published online | 24 September 2024 |
Allocating the fixed cost as a complementary input in two-stage system: a DEA approach
1
School of Management, University of Science and Technology of China, Hefei, Anhui 230026, P.R. China
2
School of Business Administration, Southwestern University of Finance and Economics, Chengdu, Sichuan 611130, P.R. China
3
School of Economics and Management, Beijing University of Technology, Beijing 100124, P.R. China
* Corresponding author: lionli@ustc.edu.cn
Received:
13
September
2023
Accepted:
2
April
2024
The existing research on fixed cost allocation (FCA) in two-stage system data envelopment analysis (DEA) models typically regards the fixed cost as an additional input for each decision-making unit (DMU). However, these models overlook the prevalent real-world scenario where fixed costs act as complementary inputs in production processes. This study proposes a general two-stage network DEA model that incorporates the fixed cost as a complementary input to optimize the allocation scheme. First, we construct a functional relationship between the efficiency scores of DMUs and their allocated fixed costs using a modified super-efficiency DEA model, which effectively classifies DMUs and solves infeasible solutions within the variable returns to scale (VRS) framework. Then, we propose a fair and unique allocation model based on fairness and efficiency maximization principles. Specifically, we allocate fixed costs based on the operational scale for inelastic DMUs while equitably increasing the efficiency scores for elastic DMUs. Finally, a numerical example and an empirical study on subsidy allocation among 30 provinces demonstrate the rationality and acceptability of our approach.
Mathematics Subject Classification: 90B30
Key words: Data envelopment analysis / fixed cost allocation / two-stage network structures / complementary input
© The authors. Published by EDP Sciences, ROADEF, SMAI 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.