An AHP-ME-IOWA Model for Assessing National Space Technology Scientific and Technological Strength: A Case Study of the United States

Space technology, a frontier of global scientific innovation, is crucial for competitive edges and national tech innovation. Amid intensified international competition and rapid technological change, scientifically evaluating a country's Scientific and Technological Strength in Space Technology (STSST) is vital. A model is innovatively proposed in this study called "Analytic Hierarchy Process-Maximum Entropy-Induced Ordered Weighted Average (AHP-ME-IOWA)" for the assessment of STSST. First, an STSST assessment indicator system is developed with four sub-dimensions: scientific research, industrial operation, innovation output, and policy resources. Second, the AHP model is used to convert experts' qualitative judgments on indicator importance into initial individual weight vectors. Subsequently, the IOWA operator is employed to aggregate these individual weight vectors, thereby mitigating the impact of outliers and enhancing the robustness of the weights. Specifically, the weights are reordered using the cosine similarity between each expert's weight vector and the temporary group mean as the induced value. Position weights are then determined via the ME method, and consensus weights are derived through re-aggregation. A systematic evaluation of the United States' STSST was conducted using this method. The results show that the United States achieved a comprehensive STSST score of 8.73 (out of 10), which is in line with the actual situation, thereby providing empirical validation for the proposed method.

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Journal
Entropy
Published
2025-11-06
DOI
https://doi.org/10.3390/e27111141
Primary Topic
Efficiency Analysis Using DEA
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article
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article

An AHP-ME-IOWA Model for Assessing National Space Technology Scientific and Technological Strength: A Case Study of the United States

Zhenqiang Qi, Yingying Chen, J Li, Yuting Zhu
Entropy
Efficiency Analysis Using DEA
article

An AHP-ME-IOWA Model for Assessing National Space Technology Scientific and Technological Strength: A Case Study of the United States

Zhenqiang Qi, Yingying Chen, J Li, Yuting Zhu
article en

Abstract

Space technology, a frontier of global scientific innovation, is crucial for competitive edges and national tech innovation. Amid intensified international competition and rapid technological change, scientifically evaluating a country's Scientific and Technological Strength in Space Technology (STSST) is vital. A model is innovatively proposed in this study called "Analytic Hierarchy Process-Maximum Entropy-Induced Ordered Weighted Average (AHP-ME-IOWA)" for the assessment of STSST. First, an STSST assessment indicator system is developed with four sub-dimensions: scientific research, industrial operation, innovation output, and policy resources. Second, the AHP model is used to convert experts' qualitative judgments on indicator importance into initial individual weight vectors. Subsequently, the IOWA operator is employed to aggregate these individual weight vectors, thereby mitigating the impact of outliers and enhancing the robustness of the weights. Specifically, the weights are reordered using the cosine similarity between each expert's weight vector and the temporary group mean as the induced value. Position weights are then determined via the ME method, and consensus weights are derived through re-aggregation. A systematic evaluation of the United States' STSST was conducted using this method. The results show that the United States achieved a comprehensive STSST score of 8.73 (out of 10), which is in line with the actual situation, thereby providing empirical validation for the proposed method.

EntropyVol. 27(11)
China Aerospace Science and Technology Corporation (CN), China Academy of Launch Vehicle Technology (CN)
Openalex Percentile: Top 61%
Efficiency Analysis Using DEA
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An AHP-ME-IOWA Model for Assessing National Space Technology Scientific and Technological Strength: A Case Study of the United States — Zhenqiang Qi, Yingying Chen, et al. · Entropy (2025) | TGRS Research Map | TGRS