中国の低炭素農村電子商取引への公共投資の優先順位付け：所得成長と環境パフォーマンスを結ぶAHP–TOPSISフレームワーク

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AHP-TOPSISの適用例として、多基準下での投資優先順位付けの方法論を学べる。

🏢実務担当者:物流・サプライチェーン部門で低炭素投資の優先順位付けに活用可能。

🏛政策担当者:農村開発政策で所得成長と環境目標を統合する際の参考になる。

Introduction Rural e commerce is widely promoted in China to expand market access and increase rural incomes. However, its rapid development also creates environmental pressures through logistics related emissions and packaging waste. This study aims to identify and prioritize public investment packages that can support rural income growth while promoting low carbon development. Methods An integrated Analytic Hierarchy Process and Technique for Order Preference by Similarity to Ideal Solution (AHP TOPSIS) framework is developed to evaluate and rank public investment options for rural e commerce development. Pairwise comparison questionnaires from 60 experts are aggregated using the geometric mean to derive criterion weights. Six main criteria and 20 indicators are considered, covering digital infrastructure, logistics capability, human capital, market linkage, inclusive economic impact, and environmental outcomes. Five alternative public investment packages are evaluated using TOPSIS based on their distances from the positive and negative ideal solutions. Sensitivity analysis with ±30% weight perturbations and scenario analysis under inclusion, growth, and environmental priorities are also conducted to assess ranking robustness. Results The baseline TOPSIS results show that A4 ranks first with a closeness coefficient of 0.630, followed by A2 with 0.593. A5 and A1 form a middle tier with coefficients of 0.556 and 0.534, respectively, whereas A3 ranks last with 0.489. The sensitivity analysis shows limited rank reversals, mainly among the middle ranked alternatives. Across the inclusion, growth, and environmental scenarios, A4 and A2 consistently remain the two highest ranked alternatives. Discussion The results indicate that skills and entrepreneurship support (A4) and low carbon logistics investment (A2) provide the most robust performance across different policy priorities. These findings suggest that rural development policies should combine human capital development with low carbon logistics infrastructure rather than focus on income growth alone. The proposed AHP-TOPSIS framework provides a transparent and robust decision support tool for prioritizing rural e commerce investments under multiple economic, social, logistical, and environmental objectives.

• openalex https://doi.org/10.3389/fenvs.2026.1803763first seen 2026-08-20 04:42:41