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汽車產銷運籌服務管理分析與顧客偏好區隔 -以分群方法為基礎
Thesis

汽車產銷運籌服務管理分析與顧客偏好區隔 -以分群方法為基礎

黃雅莉
Masters, 國立清華大學, 工業工程與工程管理學系
2008

Abstract

汽車產業 第三方物流 供應鏈管理 顧客關係管理 K-means分群 Automobile Industry Third-Party Logistics Provider Supply Chain Management Customer Relationship Menagement K-means Clustering
Taiwan automobile industry has been influenced financial crisis, which caused the vehicle productivity and profit earing to decrease year after year. Therefore Taiwan automobile industry has been facing the unprecedented challenge. However the automobile 3PLs take on the automobile production and marketing physical distribution a quite important link, also deeply are affected. Thus the automobile logistics entrepreneur will aim at distinctive coustomer segments to better provide more customized logistics services category positively, strengthen the 3PL's market competitiveness, and increase 3PL’s trading profit. At present the domestic automobile industry's logistics and distribution cost approximately composes 10%~15% generally. Facing the energy price to rise under unceasingly the adverse effect which as well as the production cost enhances unceasingly, it must implement the 3PL mechanism to reduces the automobile physical distribution cost and enhance the automobile production and marketing chain physical distribution efficiency. This research analyses supply chain characteristic of Taiwanese automobile industry and proposes comprehensive logistics business and operations models to better understand operational processes of supply entity flows. Moreover, the study analyzes logistics transportation, selling, business and operation processes and develops optimized reference models for improving performances for Taiwan automobile logistics industries. Given the growing complexity of consumer preferences and the underlying market advantages of addressing these preferences, manufacturers and logistic service providers constantly monitor supply chain efficiency and quality requirements. Third-party logistic services are offered as a means to attract customers and enhance competitiveness as long as these services are effectively integrated into the order fullfilment processes. This research uses customer preference attributes to define distinctive customers. The clustering methods using customers’ demand attributes provide decision support capabilities to logistics providers so that they can adapt processes to satisfy specific customer preferences. As demonstrated by the case study that importance of customers’ preference service value of third party logistics provider and customer satisfaction revealed significant correlation. Given these results, the 3PLs provides customized logistics services for each customer based on their previous preferences and order requirement behaviors. The study demonstrates an effective means to better manage and promote complex logistics activities in automobile industry supply chain.

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