禽肉市場與冷凍禽肉供需的增長，給全球的永續議題帶來了新挑戰，禽肉供應鏈的永續性表現亦成為管理者持續關注的指標。相較於養殖與配銷，禽肉生產階段對環境的影響更加顯著，因此，如何透過充足的證據及嚴謹的分析改善禽肉生產過程的永續性就成了當今研究的重要議題。本研究旨在透過環境、經濟和社會等三個面向評估冷凍雞肉生產階段的永續性，研究中結合了德爾菲法、決策實驗室分析法（Decision Making Trial and Evaluation Laboratory, DEMATEL）和貝氏網路分析。其中，德爾菲方法用於獲得專家共識，確定應使用於永續性評估的重要指標，DEMATEL方法用於框架指標之間因果關係，這些因果關係最後再納入貝氏網路結構以進行最終的永續性評估。研究中除使用14個指標評估冷凍雞肉生產階段的永續性、採貝氏網路評估量化其不確定性，亦將模型實際應用於評估印尼一家大型冷凍雞肉生產設施的永續性。本研究提出的方法除可以幫助管理者在農產品供應鏈的永續性評估得到更多洞察，也突顯了在決策過程中考慮不確定性的重要性。

The growing market for poultry meat, mainly frozen meat, poses significant challenges to global sustainability. Furthermore, supply chain sustainability performance in developing countries still requires further investigation. The chicken meat production stage has the most environmental impact compared to the farming and distribution stages. As a result, improving the sustainability of the meat production process is critical. The purpose of this study is to assess the sustainability status of the frozen chicken meat production stage through environmental, economic, and social sustainability. This study combines the Delphi technique, Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Bayesian network. The Delphi method was implemented to obtain expert consensus on the sustainability indicators that should be used. The DEMATEL method elicited multiple expert judgments on the causal relationships between indicators. The study suggests incorporating DEMATEL to aid in the construction of the Bayesian network structure. A total of 14 indicators were used to assess the sustainability status of the frozen chicken meat production stage. The Bayesian network evaluates the state of sustainability and quantifies uncertainties. The method was implemented to assess the sustainability status of a large frozen chicken meat production facility in Indonesia. Sensitivity and propagation analysis are employed to validate the model and gain more insights from the Bayesian network model. This study provides insight into sustainability assessment in the agri-food supply chain and highlights the importance of considering uncertainty and integrated approaches in decision-making processes.

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