Full metadata record
DC FieldValueLanguage
dc.contributor.author王志軒zh_TW
dc.contributor.author王蓉萱zh_TW
dc.contributor.authorChih-Hsuan Wangen_US
dc.contributor.authorRong-Hsuan Wangen_US
dc.date.accessioned2022-12-19T08:08:10Z-
dc.date.available2022-12-19T08:08:10Z-
dc.date.issued2022-04-01en_US
dc.identifier.issn1023-9863en_US
dc.identifier.urihttp://dx.doi.org/10.29416/JMS.202204_29(2).0006en_US
dc.identifier.urihttp://hdl.handle.net/11536/159692-
dc.description.abstract本研究提出一個整合性的架構幫助服務商預測營收,並達成以下目標:(1)辨識影響3C零售通路(燦坤、全國電子、順發)與線上電商通路(富邦、網家、東森)營收的顯著性經濟指標(預測動態)、(2)具體納入廠商間的互動關係於營收預測(競爭動態)、(3)讓實務從業者與學術研究者能更清楚釐清經濟指標與競爭動態的管理意涵。研究結果顯示,失業率、零售指標、躉售指標同時影響3C零售通路與線上電商的營收。在預測動態中,以支援向量迴歸(SVR)的表現最佳,而在競爭動態中,則三次指數平滑法(HWS)與向量自回歸(VAR)表現較好。在管理意涵部分,研究顯示零售通路燦坤(#1)受到全國電子(#2)的威脅片害而順發(#3)卻從兩家零售商獲得片利;電商部分則由網家(#2)補食富邦購物(#1),東森則與其他電商維持互利狀態。最後,研究也顯示實體通路商持續遭受線上電商的片害侵蝕而讓營收獲利停滯不前。從市場競爭強度來看,不論實體3C通路(飽和市場)或線上電商通路(成長市場),前兩名廠商間的競爭不但激烈且對市場領導者不利,第三名的廠商只要差異化定位於利基市場,反而能持續生存且獲利。zh_TW
dc.description.abstractTo help service companies better forecast sales revenues, this study presents an integrated framework to help firms achieve the following goals: (1) representative and significant economic indicators are identified to predict sales revenues of retailing stores and online e-commerce platforms (predictive dynamics), (2) mutual interactions between a firm and its rivals are captured and incorporated to reveal managerial insights (competitive dynamics), and (3) the impacts of economic indicators and channel competition (retailing vs. online) are provided for industrial practitioners and academic researchers. Experimental results show that three economic indicators, such as unemployment rate, retail index, and wholesale index, are concurrently significant for both retailing stores and online platforms. In particular, support vector regression (SVR) performs the best in predictive dynamics while and vector autoregression (VAR) and Holt-Winters smoothing (HWS) perform the best in competitive dynamics. Managerial insights show the degree of competition between the top two firms is intense: #1 retailer (Tkec) or platform (Momoshop) tend to suffer from the existence of #2 firms (Elife or PChome). In contrast, #3 firms (Sunfar or ETmall) can benefit from the big-scale firms in both 3C retailing (commensalism) or online e-commerce (mutualism). By targeting the niche segments, the small-scale retailer or platform can earn sufficient profit to survive in the market. Not surprisingly, 3C retailing stores (a saturated or declined market) continue to suffer from the existence of online platforms (a growing market).en_US
dc.language.isoen_USen_US
dc.publisher國立陽明交通大學經營管理研究所zh_TW
dc.publisherInstitute of Business and Magement, National Yang Ming Chiao Tung Universityen_US
dc.subject經濟指標zh_TW
dc.subject通路競爭zh_TW
dc.subject銷售預測zh_TW
dc.subjectEconomic Indicatorsen_US
dc.subjectChannel Competitionen_US
dc.subjectSales Forecastingen_US
dc.title整合經濟指標與競爭動態預測3C零售通路與線上電商的營收zh_TW
dc.titleIncorporating Economic Indicators and Competitive Dynamics into the Prediction of 3C Retailing Stores and Online E-Commerce Platformsen_US
dc.typeCampus Publicationsen_US
dc.identifier.doi10.29416/JMS.202204_29(2).0006en_US
dc.identifier.journal管理與系統zh_TW
dc.identifier.journalJournal of Management and Systemsen_US
dc.citation.volume29en_US
dc.citation.issue2en_US
dc.citation.spage281en_US
dc.citation.epage302en_US
Appears in Collections:Journal of Management and System