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研究生:黃仲達
研究生(外文):Huang, Chung-Tai
論文名稱:灰色理論在農產銷售預測及其供銷關係探討之應用
論文名稱(外文):An Application to Investigate Sales Forecast of Agricultural Products & its Supply and Sales Relationships-Using Grey Theory
指導教授:柯建全柯建全引用關係
指導教授(外文):Ko, Chien-Chuan
學位類別:碩士
校院名稱:國立嘉義大學
系所名稱:運輸與物流工程研究所
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2003
畢業學年度:91
語文別:中文
論文頁數:83
中文關鍵詞:銷售預測灰預測灰關聯分析供貨商評鑑
外文關鍵詞:Sales ForecastGrey PredictionGrey Relational AnalysisSupplier Selection
相關次數:
  • 被引用被引用:48
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  • 下載下載:175
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摘 要
國內農漁產品的產銷競爭自加入WTO後,在關稅降低及市場開放下,已邁入國際化,除了原有的供需失衡問題,其傳統的產銷體系已遭遇嚴苛的挑戰;尤其近年來更受到經濟不景氣、消費型態轉變等因素影響,原本平穩的產品銷售量亦隨之產生波動;然而傳統農業經營者往往憑經驗法則預測其銷售量,此種經營策略若在以往銷售量穩定的狀況下或許可行,但面臨上述因素導致銷售量波動超乎預期時,則必須透過一些預測工具的輔助,方能得到較令人滿意的結果。不幸的,就面臨經常性短期變化的狀況而言,這些方法並不全然非常適合進行各種預測。因此本研究主要目的在於嘗試利用灰色理論中灰預測的簡易、少數據之特性,來預測農產銷售量,並藉由與迴歸分析、時間序列分析的比較,探討灰預測應用於農產銷售預測之適用性。
有鑑於目前「供應鏈管理(Supply Chain Management, SCM)」觀念盛行,農產運銷體系中之供銷合作關係將愈形緊密且重要,與穩定的供貨商合作更是攫取利益的關鍵,因此本研究另一個目的即是運用灰關聯分析,構建供貨商評鑑模式及探討影響農產供銷合作關係因子的關聯性,希望讓市場通路中生產者、大盤商、中盤商、零售商等能藉此結合互惠,以期達到作業上的經濟效益及共同承受市場風險。
本研究實證對象為供應桶筍及魷魚的南部某中盤商,由預測精確度實證分析中,灰預測從預測精確度、模型的等級評定及使用的樣本數等多方面來看,其整體表現優於時間序列分析及統計的線性迴歸分析,證實了此模式之適用性。在供銷因子關聯性的探討方面,發現「願意為此供貨商做出讓步與犧牲」為供銷合作關係因子中表現最差者,而與之關聯度最高的前三名因子則為:「供貨商之配合度」、「供貨商提供的產品品質能滿足要求」及「供貨商的商譽評價」。
Abstract
Ever since Taiwan has been a member of the World Trade Organization (WTO). It makes a great impact on domestic traditional sales infrastructure, and also causes an imbalance problem between the supply site and demand site in agricultural products. Therefore, it is necessary to forecast the manufacturing and sales of the agricultural products beforehand to reduce costs and increase benefits using prediction tools. However, most of managers in the agricultural industry usually rely on old experiences to predict their sales volume. Theoretically, this will be feasible if the sales environments are stable. Once sales environments have become unstable and worse, using reliable prediction tools to maintain benefits and reduce costs is necessary for the agricultural industry. Although various prediction models for long-term or short-term prediction have been widely used in many businesses, these models often require a large amount of data to predict accurately. Most of these models may not be suitable for the forecasting of agricultural products, because its’ short-term variations caused by seasons or natural damages often will affect the prediction accuracy. The main goal of this thesis is to apply some approaches based on “Grey Theory", which have advantages such as simplicity and fewer data to predict sales and make sales decisions. Compared the results to two other traditional methods, such as Regression Model and Time-Series Analysis, it can produce better performance.
“Supply Chain Management” (SCM) is increasingly important in global logistics. The cooperation relationship between the agricultural suppliers and distributors has become more important. Cooperating with stable suppliers has becomes one key factor to achieve profit for business. Therefore, the other goal of this thesis is to exploit the “Gray Relational Analysis“ in order to determine “How to select a good supplier“, and evaluate the factors that affect the cooperation relationship between the agricultural suppliers and distributors. We hoped that the manufacturers, the upper distributors, the middle distributors, and the retailers share all the profits from one another, the economic benefit among their cooperation, and management risks.
The entire experiment is performed using one middle distributor in southern Taiwan who supplies bamboo shoots and squids. Based on the accuracy of the predictions, and from the evaluations of model’s grade as well as the amount of samples used, “Gray Prediction“ obtains the best performance among different comparisons using different prediction models, and thus also proves its feasibility simultaneously. Based on the investigation of the correlation factors between the suppliers and distributors. We found the factor, “willing to step back or sacrifices for certain supplier,” shows the worst performance in the proposed correlation factors. And, the top three highest correlation factors are “the flexibility of the supplier”, “whether the quality of the products from the supplier satisfies the needs”, and “the supplier’s reputation”.
目 錄
中文摘要......................................................i
英文摘要....................................................iii
誌謝..........................................................v
目錄.........................................................vi
表目錄.....................................................viii
圖目錄.......................................................ix
第一章 緒論...................................................1
1.1 研究背景..................................................1
1.2 研究緣起..................................................3
1.3 研究目的..................................................5
1.4 研究限制..................................................8
1.5 研究流程..................................................9
第二章 文獻探討..............................................11
2.1 農產銷售量預測...........................................11
2.1.1 傳統銷售預測法.........................................12
2.1.2 灰預測相關研究.........................................16
2.1.3 灰預測與傳統預測方法之比較.............................17
2.2 農產供銷關係探討.........................................18
2.2.1 供貨商評選準則的選取...................................19
2.2.2 供貨商評選準則架構的建立...............................23
2.2.3 供貨商評選資料的處理...................................24
2.2.4 供貨商績效表現之計算與排序.............................24
2.2.5 灰關聯相關研究.........................................25
第三章 研究方法..............................................26
3.1 研究架構.................................................26
3.2 灰色理論簡介.............................................27
3.3 灰預測...................................................28
3.3.1 數列灰預測.............................................29
3.3.2 誤差分析...............................................31
3.4 灰關聯...................................................32
3.4.1 灰關聯生成.............................................32
3.4.2 灰關聯度之計算.........................................34
第四章 個案研究..............................................35
4.1 個案簡介與資料蒐集.......................................35
4.2 個案分析I-銷售量預測....................................38
4.2.1 灰色理論-灰預測.......................................39
4.2.2 統計-迴歸分析.........................................40
4.2.3 時間序列分析...........................................49
4.2.4 最佳預測模式...........................................62
4.3 個案分析II-供貨商評選及供銷合作因子關聯度分析...........63
4.3.1 供貨商評選因子之調查...................................64
4.3.2 以灰關聯分析進行供貨商評選作業.........................65
4.3.3 以灰關聯分析進行供銷因子關聯度排序.....................72
第五章 結論與建議............................................77
5.1 研究結論.................................................77
5.2 對本產業及後續研究的建議.................................78
參考文獻.....................................................81
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