Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 黃皇程 | zh_TW |
dc.contributor.author | 巫木誠 | zh_TW |
dc.contributor.author | 洪暉智 | zh_TW |
dc.contributor.author | Huang, Huang-cheng | en_US |
dc.contributor.author | Wu, Muh-Cherng | en_US |
dc.contributor.author | Hung, Hui-Chih Hung | en_US |
dc.date.accessioned | 2018-01-24T07:41:08Z | - |
dc.date.available | 2018-01-24T07:41:08Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.uri | http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT079633805 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/141558 | - |
dc.description.abstract | 本篇論文開發一種新的預測方法,可以用來分析及預測兩種零售模式的競爭關係,進行這種預測的傳統預測方法是基於Lotka-Volterra model(以下簡稱LV模型)。 LV模型假設每個物種的族群數量受到自身生長,物種內部交互作用及其他物種的外部交互作用所影響。大多數商業應用研究直接使用銷售數據輸入LV模型。當銷售數據受到季節性變化影響的時候,先前的方法可能會導致錯誤的結論,因為原始的LV模型的並未考慮到季節性變化的影響。因此,本篇論文提出了一個預測方法(LV模型的增強應用)。每個零售模式的銷售數據被視為複合數據,並將複合數據分解為三個單獨的部分:(1)總計(2)競爭和(3)季節成分。LV模型用於預測競爭關係;其他兩個組件由典型的時間序列方法預測;並將三個部分數據最終組合成一個。實證研究表明,新的預測方法在預測預測誤差方面,基本上優於傳統預測方法(新方法便利導向預測誤差為4.4%、傳統預測方法為16.7%;新方法預算導向預測誤差為5.8%、傳統預測方法為16.2%)。 此外,新的預測方法所揭示的競爭模式是更有說服力的捕食者 -獵物關係,其結論是便利導向的零售模式是捕食者。相反地,傳統預測方法的結論是預算導向的零售模式是捕食者,是相當令人懷疑的,因為隨著時間的推移,便利導向的零售模式將隨著GDP的增長相較於預算導向的零售模式會有較快的成長。本篇論文為如何適當應用LV模型預測銷售數據和分析兩種商業模式的競爭關係做出了貢獻。 關鍵詞:Lotka–Volterra 模型,預測,零售模式 | zh_TW |
dc.description.abstract | his research develops a sales forecasting model that can analyze the interaction effects of two retail competing formats (Convenience-oriented vs. Budget-oriented formats). A traditional approach to making such a forecast is based on the Lotka–Volterra equations (also called the LV-model). The LV-model assumes that the population of each species is affected by its self-growth, internal interaction within the species, and external interaction with other species. Most prior studies in business applications directly use sales data as input to the LV-model. The prior approach may result in misleading conclusions when sales data are embedded with seasonal variation, because this variation is not addressed in the original development of the LV-model. Therefore, this study proposes a forecasting framework (an enhanced application of the LV-model). The sales data of each retail format is considered as a compound data, which is decomposed into three individual components: (1) aggregate, (2) competition, and (3) seasonal components. The LV-model is used to forecast the competition component;the other two components are forecasted by typical time series methods;and the data of three components are finally combined into one. Empirical study indicates that the proposed method substantially outperforms the prior approach in terms of forecasting errors (4.4% vs.16.7% for Convenience-oriented and 5.8% vs. 16.2% for Budget-oriented). In addition, the proposed method reveals a more convincing predator-prey relationship between the two retail formats, which concludes that the Convenience-oriented is the predator. To the opposite, the prior approach, concluding that the Budget-oriented is the predator, is quite doubtful because the Convenience-oriented shall be preferred while the GDP grows over time. This research makes a contribution in how to appropriately apply the LV-model in forecasting revenue and analyzing the interaction effects of two competing business species. Keywords : Lotka–Volterra model ; Forecasting ; Retail formats | en_US |
dc.language.iso | zh_TW | en_US |
dc.subject | Lotka–Volterra 模型 | zh_TW |
dc.subject | 預測 | zh_TW |
dc.subject | 零售模式 | zh_TW |
dc.subject | Lotka–Volterra equations | en_US |
dc.subject | Forecasting | en_US |
dc.subject | Retail formats | en_US |
dc.title | 以增強 Lotka–Volterra model預測具競爭關係的零售模式 | zh_TW |
dc.title | An enhanced application of Lotka–Volterra modelto forecast competing retail formats | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 工業工程與管理系所 | zh_TW |
Appears in Collections: | Thesis |