網路消費市場存有許多促銷事件的發生，零售商為了增加其競爭力，通常藉由促銷行為以刺激額外消費金量，然而，對此也必須考慮因促銷行為的發生所造成的利益折損部分。零售商所面臨最重要的議題，就必須權衡因促銷事件所創造的額外利潤以及同時所衍伸出的成本，同時得善用所使用促銷工具的特性才能做出最當的決策。本研究主要探討的促銷工具為條件式免運費、價格促銷與積點制，條件式免運費旨在說明當消費者滿足特定消費門檻即可享有免運費；價格促銷說明消費者其消費量達某特定額度時即可享有折扣之優惠；而積點制則是說明消費金額可以轉換為特定點數，透過點數的累積可兌換相當金錢價值之贈品等。根據不同促銷形式之特性建立數學模式，並分析獨立促銷模式與三者共同作用之促銷模式對於零售商潤所造成的影響。
在零售商所預期達到的促銷幅度下，可得到零售商利潤最大化下的不同促銷模式最適門檻值以及最佳商品利潤佔成本之百分比，根據敏感度分析，整體來說，無論在何種促銷情境之下，商品利潤對從事購買行為轉換率敏感係數與從事購買行為轉換率常數均會造成零售商利潤有較大幅度的改變。而消費者的敏感程度不同也將影響零售商最適門檻值的設定，根據求解結果，在個別獨立促銷模式中，當消費者敏感程度適中時，所求解之最佳門檻值會較低；當消費者敏感程度較高或較低時，所求解之最佳門檻值會較高。此外，針對合併促銷模式受促銷影響之增額機率函數型態分別為指數函數與線性函數時加以做探討，前者之增額機率受目前消費金額與門檻間的差值影響的變動程度較大，可區分出較明顯的消費區間；後者之增額機率受差值影響的變動程度較小，將會構成消費區間萎縮的局面。

Online-retailers use various promotion methods such as contingent free-shipping, price discounts, and gift cards to increase their profits in the E-market. At the same time, the retailers concern the decision on how to increase their profit margin and set promotion thresholds on different activities. In this research, we develop three models for determining the threshold values in three different individual promotion events and an integrated model to derive the optimal threshold values for different promotion activities under the objective of maximizing retailer’s profit. These models provide an efficient procedure to set up their different threshold values if these promotion events are held at the same time. In the numerical analysis, we find that the appropriate threshold values can be obtained if the order of the threshold values are pre-determined by the decision makers. In addition, the sensitivity on the probability of additional purchasing affected by a promotion activity plays an important role in setting the threshold value of that promotion activities. For online-retailers, the best threshold value with sensitivity of the probability equals to 0.01 is lower than the ones with sensitivity of the probability equals to 0.005 and 0.02 in order to avoid losing the potential consumers, focus on high purchasing power consumers and earn much more profits. Finally, we perform a sensitivity analysis of the parameters related to conversion rate and the parameters related to discount methods to examine their impact on the retailer’s decisions.

Aaker, D. A. (1973). Toward a normative model of promotional decision making. Management Science, 19, 593-603.
Alba, J. W., Mela, C. F., Shimp, T. A., & Urbany, J. E. (1999). The effect of discount and depth on consumer price judgments. Journal of Consumer Research, 26, 99-114.
Banks, J., & Moorthy, S. (1999). A model of price promotions with consumer search. International Journal of Industrial Organization, 17, 371-398.
Barsh, J., Crawford, B., & Grosso, C. (2000). How e-tailing can rise from the ashes. The Mckinsey Quarterly, 3, 98-109.
Becerril-Arreola, R., Leng, M., & Parlar, M. (2013). Online retailers' promotional pricing, free-shipping threshold, and inventory decisions: A simulation-based analysis. European Journal of Operational Research, 230, 272-283.
Bell, D. R., Chiang, J., & Padmanabhan, V. (1999). The decomposition of promotional response: An empirical generalization. Marketing Science, 18, 504–526.
Biswas, A., Bhowmick, S., Guha, A., & Grewal, D. (2013). Consumer evaluations of sale price role of the subtraction principle. Journal of Marketing, 77, 49-66.
Boone, T., & Ganeshan, R. (2013). Exploratory analysis of free shipping policies of online retailers. International Journal of Production Economics, 143, 627-632.
Briesch, R. A., Chintagunta, P. K., & Matzkin, R. L. (2002). Semiparametric estimation of brand choice behavior. Journal of the American Statistical Association, 97, 973-982.
Campbell, L., & Diamond, W. D. (1990). Framing and sales promotions: The characteristics of a good deal? Journal of Consumer Marketing, 7, 25-31.
Chandon, P., Wansink, B., & Laurent, G. (2000). A benefit congruency framework of sales promotion effectiveness. Journal of Marketing, 64, 65-81.
Diamond, W. D. (1992). Just what is a ‘dollar’s worth’? Consumer reactions to price discounts vs. extra product promotions. Journal of Retailing, 68, 254-270.
Grewal, D., Krishnan, R., Baker, J., & Borin, N. (1998). The effect of store name, brand name and price discounts on consumers' evaluations and purchase intentions. Journal of Retailing, 74, 331-352.
Grewala, D., Ailawadi, K. L., Gauri, D., Hall, K., Kopalle, P., & Robertson, J. R. (2011). Innovations in retail pricing and promotions. Journal of Retailing, 87S, S43-S52.
Guadagni, P. M., & Little, J. D. C. (1983). A logit model of brand choice calibrated on scanner data. Marketing Science, 2, 203-238.
Hardesty, D. M., & Bearden, W. O. (2003). Consumer evaluations of different promotion types and price presentations: The moderating role of promotional benefit level. Journal of Retailing, 79, 17-25.
Heerde, H. J. van, Leeflang, P. S. H., & Wittink, D. R. (2000). The estimation of pre- and postpromotion dips with store-level scanner data. Journal of Marketing Research, 37, 383-395.
Hua, G., Wang, S., & Cheng, T. C. E. (2012). Optimal order lot sizing and pricing with free shipping. European Journal of Operational Research, 218, 435-441.
Kalakota, R., & Whinston, A. B. (1997). Electronic Commerce: A Manager's Guide. Boston, MA: Addison-Wesley Longman Publishing Co., Inc.
Khouja, M., Pan, J., Ratchford, B. T., & Zhou, J. (2011). Analysis of free gift card program effectiveness. Journal of Retailing, 87, 444-461.
Khouja, M., Park, S., & Zhou, J. (2013). A free gift card alternative to price discounts in the news vendor problem. Omega, 41, 665-678.
Kopalle, P. K., & Lehmann, D. R. (2006). Setting quality expectations when entering a market: what should the promise be? Marketing Science, 25, 8–24.
Kotler, P. & Kevin, L. K. (2009). Marketing Management, 13th ed. Upper Saddle River, NJ: Pearson/ Prentice Hall.
Koukova, N. T., Srivastava, J., & Steul-Fischer, M. (2012). The effect of shipping fee structure on consumers' online evaluations and choice. Journal of the Academy of Marketing Science, 40, 759-770.
Levy, M., Grewal, D., Kopalle, P. K., & Hess, J. D. (2004). Emerging trends in retail pricing practice: Implications for research. Journal of Retailing, 80, 13-21.
Lewis, M. (2006). The effect of shipping fees on customer acquisition, customer retention, and purchase quantities. Journal of Retailing, 82, 13-23.
Lewis, M., Singh, V., & Fay, S. (2006). An empirical study of the impact of nonlinear shipping and handling fees on purchase incidence and expenditure decisions. Marketing Science, 25, 51-64.
Nijs, V. R., Dekimpe, M. G., Steenkamps, J. B., & Hanssens, D. M. (2001). The category-demand effects of price promotions. Marketing Science, 20, 1-22.
Raghubir, P., & Corfman, K. (1999). When do price promotions affect pretrial brand evaluations? Journal of Marketing Research, 36, 211-222.
Raju, J. S. (1992). The effect of price promotions on variability in product category sales. Marketing Science, 11, 207-220.
Rosen, K. T., & Howard, A. L. (2000). E-retail: gold rush or fool’s gold. California Management Review, 42(3), 72–100.
Turban, E., King, D., Lee, J., Liang, T.P., & Turban, D. (2012). Electronic Commerce 2012: A Managerial and Social Networks Perspective, 7th ed. Upper Saddle River, NJ: Pearson/ Prentice Hall.
Wilkinson, J. B., Mason, J. B., & Paksoy, C. H. (1982). Assessing the impact of short-term supermarket strategy variables. Journal of Marketing Research, 72-86.
資策會MIC (2012)。2012年中華民國電子商務年鑑：應用篇，196-276。經濟部商業司。取自http://ecommercetaiwan.blogspot.tw/
戴國良(2011)。促銷管理：實戰與本土案例(第二版)。台北市：五南圖書出版股份有限公司。
資策會MIC(2010)。2010台灣線上購物市場規模3,583億元。取自http://www.iii.org.tw/(X(1)S(ryslp5jhplgyyz55bzf3j5ig))/service/3_1_4_c.aspx?id=127&AspxAutoDetectCookieSupport=1#here