Development of a Multi-Period Network Data Envelopment Analysis Model under Uncertainty for Measuring the Relative Efficiency of the Operational Budget in Iran’s ICT Sector
Subject Areas : Research in operation and optimization of systems and processesAlireza Torky 1 , kaveh khalili damghani 2 , Farhad Mehmanpazir 3 , امیر عباس شجاعی 4 , Hamid Tohidi 5
1 - Department of Industrial Engineering, ST., C, Islamic Azad University, Tehran, Iran
2 - Department of Industrial Engineering, ST., C, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Engineering, ST.,C, Islamic Azad University, Tehran, Iran
4 - دانشگاه تهران جنوب
5 - Department of Industrial Engineering, ST.,C, Islamic Azad University, Tehran, Iran
Keywords: National budget efficiency measurement, ICT budget performance, network DEA, multi-period efficiency evaluation, efficiency measurement under uncertainty,
Abstract :
Measuring the efficiency of national budget allocations has consistently posed challenges for policymakers, particularly in sectors that are both strategically important and resource-intensive. The communications and information technology (ICT) sector in Iran exemplifies such complexity, given its rapid technological evolution, high investment demands, and interconnected subunits. This study introduces a multi-period network data envelopment analysis (DEA) model under uncertainty to evaluate the relative efficiency of the operational budget in this sector. Unlike conventional DEA approaches that treat organizations as single units, the network DEA framework explicitly models internal structures, intermediate outputs, and feedback loops, thereby offering a more nuanced view of performance.
A distinctive feature of the proposed model is the integration of fuzzy sets to capture uncertainty in budgetary parameters. Since many financial indicators are subject to imprecision or incomplete information, the fuzzy extension of network DEA provides a more realistic representation of actual decision-making environments. The model is applied to real budget data from Iran’s ICT sector over a four-year horizon, with annual granularity, under both deterministic and uncertain conditions.
The findings reveal that the proposed framework can calculate annual relative efficiency scores, decompose overall efficiency into departmental contributions, and identify inefficiencies across different subunits. This decomposition enables policymakers to distinguish between inefficiencies arising from resource allocation, process management, or structural bottlenecks. Moreover, the results highlight how uncertainty influences efficiency rankings and resource utilization patterns, offering valuable insights for strategic planning.
In conclusion, this research contributes a methodological advancement by combining multi-period analysis, network structures, and uncertainty modeling. The proposed framework not only enriches academic discourse on efficiency measurement but also provides practical guidance for policymakers seeking to optimize financial resource allocation in Iran’s ICT sector.
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