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Two-stage solution approach for supplier selection: A case study in a Taiwan automotive industry

机译:供应商选择的两阶段解决方案方法:以台湾汽车业为例

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Taiwan's automotive industry has undergone tremendous changes during the past decades as a result of joining the World Trade Organization (WTO) in 2002. After entering the WTO, Taiwanese automotive industries are facing the impact of tariff reduction, open import and the cancellation of self-made rate and taxation preferential, they are also encountering global competitive environmental threats, hence a reduction in operation costs and reinforcement of competitive advantage of the enterprise are required to embrace WTO's impact. A key strategy to reinforce competitiveness is effectively selecting the best supplier for operation cost reduction. The supplier selection is a multi-criterion decision making problem which includes both qualitative and quantitative criteria. Many criteria may conflict with each other which makes the decision making process complicated. In this paper, we propose to develop a systematic process for automotive industry supplier selection: a two-stage solution approach for supplier selection using Fuzzy Analytic Network Process-Goal Programming (FANP-GP) and De Novo Programming (DNP). The first stage is the FANP method integrated with the GP model to select the best supplier and to decide the optimal order quantity. In the second stage, the selected suppliers are evaluated based on the DNP method by adjusting their resource constraints and increase their capacity to achieve the minimum total procurement budget. Furthermore, a case study is conducted to illustrate the stages in the supplier selection for the lead industry-automotive industry. The result provides the idealised supplier selection model for automotive industry by the systematic process to facilitate in the decision making activity and helps to effectively select the best supplier significantly reduces purchasing costs and improves corporate competitiveness.
机译:由于2002年加入世界贸易组织(WTO),台湾汽车业在过去的几十年中发生了翻天覆地的变化。加入WTO后,台湾汽车业正面临关税降低,开放进口和取消自实行税率和税收优惠后,它们还面临着全球竞争性环境威胁,因此需要降低运营成本并增强企业的竞争优势,以适应WTO的影响。增强竞争力的关键策略是有效选择最佳供应商以降低运营成本。供应商的选择是一个多标准的决策问题,包括定性和定量标准。许多标准可能会相互冲突,这会使决策过程变得复杂。在本文中,我们建议开发一个用于汽车行业供应商选择的系统过程:使用模糊分析网络过程目标编程(FANP-GP)和De Novo编程(DNP)的供应商选择的两阶段解决方案。第一阶段是与GP模型集成的FANP方法,以选择最佳供应商并确定最佳订单数量。在第二阶段,通过调整供应商的资源限制并提高其实现最低总采购预算的能力,根据DNP方法对选定的供应商进行评估。此外,还进行了案例研究,以说明铅行业-汽车行业的供应商选择阶段。结果通过系统化的过程为汽车行业提供了理想的供应商选择模型,以促进决策活动,并有助于有效地选择最佳供应商,从而大大降低了采购成本并提高了企业竞争力。

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