| Summary: | 碩士 === 南華大學 === 管理科學研究所 === 95 === The industry of the agricultural machinery is competitive in the global market environment as shortened products life cycle and customer-oriented marketing nowadays. A well designed collaborative forecasting process will reduce the inventory, shorten the production lead time and improve the cooperation among the participating partners. The critical components in the industry are typically expensive and with long order lead time. Moreover, the customers usually ask for short delivery time. This forces the manufacturer to put large quantities of inventory at hand, resulting in costly and less efficient supply chain. It’s of importance to develop an adequate collaborative forecasting process for the partners in the supply chain.
In this study, literature was investigated related to collaborative forecasting. The characteristics of agricultural machine industry and supply chain management was analyzed, and an in-depth interview of personnel in six companies was conducted. As a result, we constructed a hierarchy of factors that was crucial to the forecasting process in the agricultural machine industry. The hierarchy of factors consists of six main forecasting factors and 14 sub-factors. We finally applied the Analytical Hierarchical Process to rank the importance of these factors. The result showed that historical sale amount, capacity utilization rate and inventory turn-over days are three major factors for collaborative forecasting process in the agricultural machine industry.
In addition, this paper developed a structure of collaborative forecasting process for agricultural machine industry, and verified this structure by interviewing managers in agricultural machine enterprises. To be brief, the structure of collaborative forecasting process developed in this study is suitable for agricultural machine industry, and could be a reference model for further researches.
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