臺灣博碩士論文加值系統

2008 年在美國出現了第一個網路團購平台 Groupon，由於其營收成長速度相當快，自此網路團購類似型態的網站紛紛出現，台灣也趕上這股熱潮，開始出現許多網路團購相關網站，搶食團購這塊市場大餅，資料顯示在 2010 年時台灣網路團購的市場規模已達到 71.6 億元，市場規模更隨著時間逐年擴大。

對於網路團購平台製造商業者而言，了解消費者對網路團購此一新形態商業模式之心理感受實屬必要，而本研究將進一步藉由量化模式的建立以進行數據資料的分析，使得有志於透過網路團購平台行銷之業者在經營及規劃平台商品配置時有一個決策的準則可參考。透過樣本觀察，本研究發現在網路團購市場中當存貨減少此一訊息的揭露會使得後續需求速率增加，本研究運用存貨與需求兩者之間具關聯性之特性，推導出一個網路團購的決策模型。現今網路團購製造商業者或可運用此模型以作為評估商品販售的參考依據。

本研究構建一網路團購決策模型，目的是讓網路團購製造商業者可以利用模型做初步的決策分析，當業者在規劃平台上各項商品販售期間時，應慮及商品在架上販售的時間，同時亦須知曉準備貨量多寡，運用上述在架上販售的時間以及備貨的數量以推估銷貨收入，扣除進貨成本與上架費用等開支，即可得知商品之最佳利潤。本研究以販售期間與進貨數量作為決策變數，寄望求解最佳決策組合，以達成網路團購製造商業者之目標，亦即利潤之極大化。此外，本研究運用數值分析以及敏感度分析的方式，以了解在網路團購決策模型中各參數對模型的影響程度，分析結果得知市場需求率之上限對於模型的影響最大，當商品的市場需求率越大，網路團購製造商業者可以多備貨，使得其在團購平台架上販售的時間拉長，賺取更高的營業額。

In 2008, the first group-buying website-Groupon comes out in the U.S. Because this kind of business model grows really fast, more and more similar group-buying websites start to sell group-buying products to share this market. Latter Taiwan followed the U.S to establish group-buying business company immediately. The market analysis data shows that in Taiwan 2010 the group-buying market size had already reached NT$ 7 billion and 160 million dollars, and market size continues expanding over time.

For a seller using the group-buying website as a sales channel, it is important to figure out consumers’ inner feelings about group-buying. In our research, we will construct a mathematical model and use data analysis to suggest the optimal decision policy. We can offer group-buying company’s manager the decision-making criteria to manage products operation. Through some empirical observation, we found that in group-buying market demand will increase while inventory decreased. According to the characteristic of connection between demand and inventory, we derive online group-buying decision model to help group-buying company’s manager to run their business better.

Formulating an online group-buying decision model can help group-buying companies’ managers to setup a better policy for products management. They can use this model to calculate the optimal sales horizon and stocking quantity as products control policy in order to achieve the maximum profit. Following that we use numerical analysis and sensitivity analysis to see how each parameter affects group-buying decision model. Analysis results show that the parameterdemand rate has the greatest effect on model. Group-buying company can stock more goods when market demand rate was greater, so that selling products on the group-buying website longer can gain higher revenue.

摘要...............i
Abstract ...............ii
目錄...............iv
表目錄...............v
圖目錄...............vi
第一章 緒論...............1
第一節 研究背景...............1
第二節 研究動機...............4
第三節 研究目的...............6
第四節 研究流程...............7
第二章 文獻探討...............8
第一節 團購議題相關研究...............8
第二節 需求與存貨呈正相關之研究...............10
第三節 需求及存貨呈現負相關的研究...............11
第三章 建構模型...............13
第一節 理論模式的建立...............13
第四章 網路團購上架期間之最適解分析...............18
第一節 網路團購利潤模型之最適化分析...............18
第五章 數值分析...............23
第一節 網路團購模型之數值分析...............23
第六章 結論與未來研究限制...............33
第一節 結論...............33
第二節 未來研究方向...............35
參考文獻...............36

中文文獻
張允曦（民102），7秒一筆交易！團購網賣餐券年營收12億，TVBS新聞。http://news.tvbs.com.tw/entry/506495
梁信翔（民95）「考慮需求與存貨水準有關且自有貨架空間容量有限存貨模型，之研究」，長庚大學企業管理研究所碩士論文。
陳炫凱（民96）「需求與存貨水準相依下損耗性產品的最佳補貨政策」，，國立中央大學工業工程與管理研究所碩士論文。
陳欽雨、王國光、張書豪（民102）「平台品質,網站知名度與網路口碑對品牌，評價之影響-以網路團購為例」。ElectronicCommerceStudies，11(1)，53-78
曾翌萍（民103），瘋團購！GOMAJI年營收翻倍達31億，TVBS新聞。http://news.tvbs.com.tw/entry/518039
華舜嘉（民103）「限時搶購+下殺」團購行銷手法公開！，TVBS新聞。http://news.tvbs.com.tw/entry/520936
翟翾（民103）不被電腦綁住手機｢行動敗家｣取代PC，TVBS新聞。http://news.tvbs.com.tw/entry/523308
劉致昕（民100）。台灣團購網大戰，本夠粗才能活命，商業周刊，第1231期，70-71頁。
歐陽良裕、吳坤山、楊志德（民97）「考慮數量折扣下需求與存貨水準有關且，隨機欠撥率之非即時退化性物品的存貨模式」。工業工程學刊，第二十五卷第一期，62-72頁。
魏國忠（民97），｢需求與存貨相依且具貨架空間限制之寄銷存貨模式｣，長庚大學企業管理研究所碩士論文。
羅之盈（民102），GOMAJI三周年，2014年挑戰交易額60億元，數位時代網站。http://www.bnext.com.tw/article/view/id/29633

英文期刊
Ahn, T., Ryu, S., & Han, I. (2005). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405-420.
Anand, K. S., & Aron, R. (2003). Group buying on the web: A comparison of price-discovery mechanisms. Management Science, 49(11), 1546-1562.
Baker, R. C., & Urban, T. L. (1988). A Deterministic Inventory System with an Inventory-Level-Dependent Demand Rate. Journal of Operational Research Society, Vol. 39, No. 9, pp. 823-831.
Chung, K. J., Chu, P. & Lan, S. P. (2000). A note on EOQ models for deteriorating items under stock dependent selling rate. European Journal of Operational Research, 124 (3), pp. 550–559.
Cox, D. F. (1967). Risk handling in consumer behavior–an intensive study of two cases. Risk taking and information handling in consumer behavior, pp. 34-81.
Das, K., & Maiti, M. (2003). Inventory of a differential item sold from two shops under single management with shortages and variable demand. Applied Mathematical Modelling, 27(7), pp. 535-549.
Datta, T. K., & Pal, A. K. (1990). A note on an inventory model with inventory-level-dependent demand rate. Journal of the Operational Research Society, pp. 971-975.
Donthu, N., & Garcia, A. (1999). The Internet shopper, Journal of Advertising Research, 39(3), pp. 52-58
Erdoğmuş, İ.E., & Çiçek, M. (2011). Online group buying: what is there for the consumers? Procedia-Social and Behavioral Sciences, 24, pp. 308–316.
Garretson, J. A., & Clow, K. E. (1999). The influence of coupon face value on service quality expectations, risk perceptions and purchase intentions in the dental industry. The Journal of Services Marketing, 13(1), pp. 59-72.
Johnson, E. L. (1968). On (s,S) policies, Management Science, 15 (1), pp. 80–101.
Kauffman, R. J., & Wang, B. (2001).New Buyers'' Arrival Under Dynamic Pricing Market Microstructure: The Case of Group-Buying Discounts on The Internet. Journal of Management Information Systems, 18(2), pp. 157-188.
Kauffman, R. J., & Wang, B. (2002). Bid together, buy together: On the efficacy of group-buying business models in Internet-based selling. The E-Business Handbook: pp. 99-137.
Lascu, D. N., & Zinkhan, G. (1999). Consumer conformity: review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, pp.1-12.
OuYang, L. Y., Hsieh, T. P., Dye, C. Y., & Chang, H. C. (2003). An inventory model for deteriorating items with stock-dependent demand under the conditions of inflation and time-value of money. The Engineering Economist, 48(1), pp. 52-68.
Padmanabhan, G., & Vrat, P. (1995). EOQ models for perishable items under stock dependent selling rate. European Journal of Operational Research, 86 (2), pp. 281–292.
Sarker, B.R., Mukherjee, S., & Balan, C. V. (1997).An order-level lot size inventory model with inventory-level dependent demand and deterioration. International Journal of Production Economics, 48 (3), pp. 227–236
Urban, T. L. (2005). Inventory Models with Inventory-Level-Dependent Demand: A Comprehensive Review and Unifying Theory. European Journal of Operational Research, Vol. 162, pp. 792-804.
Whitin, T. M. (1957). The Theory of Inventory Management, Princeton: Princeton University Press.
Wolfe, H. B. (1968). A Model for Control of Style Merchandise,” Industrial Management Review, Vol. 9, No. 2, pp. 69-82.
Xu, T., Zuo, S., Ning, H., Xu, J., & Ma, H. (2011). Group buying development model based on social networking site in china, Energy Procedia, 13, pp. 9719–9725.