隨著網路使用率的提升以及手機等行動裝置的普及，消費者開始接觸並習慣在網路上進行消費，進而帶動電子商務（E-Commerce，以下簡稱為電商）的發展。而COVID-19的出現，更是加快了全球電商的成長速度與規模，企業應如何把握當下的機會持續發展，將成為一大課題。
本研究旨在探討台灣電子商務產業在這此趨勢下的經營績效表現。使用Two-stage Dynamic RDM DDF Model，針對2018年下半年至2021年上半年，共3年期間，台灣22家上市、上櫃及興櫃的電子商務公司進行分析研究。研究結果如下：
1.在2018年下半年至2021年上半年的研究期間，台灣電商公司的平均總效率為0.6895，生產效率為0.9614，而市場效率為0.4176。
2.相較於生產效率階段，各電商公司在市場效率階段的表現差異較大，而原因可能來自「每股盈餘」這項個別變數所造成的。
3.在研究期間，華義、鈊象、尚凡、數字及富邦媒等5家公司在各階段的效率值皆為1，顯示出這些公司資源配置良好，成為電商產業中效率前緣的公司。
4.在研究期間，岳豐、富爾特及宏正是平均總效率最低的三家公司。

With the increase of Internet usage and the popularization of mobile devices such as mobile phones, consumers start to try and get used to spending online, which in turn drives the development of E-Commerce. The emergence of COVID-19 has accelerated the growth rate and scale of global E-Commerce, and how companies should seize the current opportunities for sustainable development will become a major issue.
This study aims to explore the business performance of Taiwan's E-Commerce industry under this trend. Using the Two-stage Dynamic RDM DDF Model, the analysis and research were conducted on 22 listed, OTC and OTC E-Commerce companies in Taiwan during the three-year period from the second half of 2018 to the first half of 2021. The results of the study are as follows:
1.During the study period, the overall efficiency value of Taiwanese E-Commerce companies was 0.6895, the production stage efficiency value was 0.9614, and the market stage efficiency value was 0.4176.
2.Compared with the production efficiency stage, the performance of the E-Commerce companies in the market efficiency stage is quite different, and the reason may be caused by the "EPS."
3.The efficiency value of 5 companies including Wayi, IGS, Sunfun, addcn and momo, were all 1 at each stage, indicating that these companies have well-allocated resources and become companies at the forefront of efficiency in the E-Commerce industry.
4.YFC-BonEagle, Fullerton and ATEN are the three companies with the lowest overall efficiency value.

王炳元（2018）。台灣零售百貨業實體與電商結合之事前效率評估。。
王財驛、蔡采容（2020）。應用資料包絡分析法探討電子商務產業經營效益-以臺灣, 香港, 美國上市電商公司為例。當代商管論叢， 5（1），頁 89-109。
林君信、張名媗、林欣宜（2015）。電子商務公司之績效評估: 二階段差額式評量之應用。科際整合管理研討會，頁 533-546。
洪秀婉、林美惠、王安邦（2008）。全球網路零售公司經營績效之研究。電子商務學報， 10（2），頁 359-377。
倪貝宜（2015）。企業網站對經營效率之影響: 以臺灣上市食品公司為例。
張雅珍（2016）。台灣百貨業效率評估-動態 DEA。張雅珍。
蔡聖涵（2018）。台灣網路公司經營效率與獲利能力關聯性之研究。國立中興大學應用經濟學系所，台中市。
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092.
Cao, X., & Yang, F. (2011). Measuring the performance of Internet companies using a two-stage data envelopment analysis model. Enterprise Information Systems, 5(2), 207-217.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
Chen, Y., Motiwalla, L., & Riaz Khan, M. (2004). Using super-efficiency DEA to evaluate financial performance of e-business initiative in the retail industry. International Journal of Information Technology & Decision Making, 3(02), 337-351.
Chung, Y. H., Färe, R., & Grosskopf, S. (1997). Productivity and undesirable outputs: a directional distance function approach. journal of Environmental Management, 51(3), 229-240.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
Färe, R., & Grosskopf, S. (1996). Productivity and intermediate products: A frontier approach. Economics letters, 50(1), 65-70.
Färe, R., & Grosskopf, S. (2004). Efficiency and productivity: New directions. In: Boston, MA: Kluwer Academic Publishers.
Färe, R., & Grosskopf, S. (2010). Directional distance functions and slacks-based measures of efficiency. European journal of operational research, 200(1), 320-322.
Färe, R., Grosskopf, S., & Whittaker, G. (2007). Network dea. In modeling data irregularities and structural complexities in data envelopment analysis (pp. 209–240). In: Boston, MA: Springer.
Klopp, G. A. (1985). The analysis of the efficiency of productive systems with multiple inputs and outputs. University of Illinois at Chicago.
Koopmans, T. i. C. (1957). Three Essays on the State of Economic Science. New York: McGraw-Hil1 Book Company. In: Inc.
Lin, R., & Chen, Z. (2015). Super-efficiency measurement under variable return to scale: an approach based on a new directional distance function. Journal of the Operational Research Society, 66(9), 1506-1510.
Lu, W.-M., & Hung, S.-W. (2011). Exploring the efficiency and effectiveness in global e-retailing companies. Computers & Operations Research, 38(9), 1351-1360.
Portela, M. S., Thanassoulis, E., & Simpson, G. (2004). Negative data in DEA: A directional distance approach applied to bank branches. Journal of the Operational Research Society, 55(10), 1111-1121.
Seiford, L. M., & Zhu, J. (2005). A response to comments on modeling undesirable factors in efficiency evaluation. European journal of operational research, 161(2), 579-581.
Serrano-Cinca, C., Fuertes-Callén, Y., & Mar-Molinero, C. (2005). Measuring DEA efficiency in Internet companies. Decision Support Systems, 38(4), 557-573.
Sueyoshi, T., & Sekitani, K. (2005). Returns to scale in dynamic DEA. European journal of operational research, 161(2), 536-544.
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. European journal of operational research, 197(1), 243-252.
Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145-156.
Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124-131.
Wang, C.-N., Dang, T.-T., Nguyen, N.-A.-T., & Le, T.-T.-H. (2020). Supporting better decision-making: A combined grey model and data envelopment analysis for efficiency evaluation in e-commerce marketplaces. Sustainability, 12(24), 10385.
Yang, Z., Shi, Y., Wang, B., & Yan, H. (2014). Website quality and profitability evaluation in ecommerce firms using two-stage DEA model. Procedia Computer Science, 30, 4-13.
Yang, Z., Shi, Y., & Yan, H. (2016). Scale, congestion, efficiency and effectiveness in e-commerce firms. Electronic Commerce Research and Applications, 20, 171-182.
Yu, M.-M. (2004). Measuring physical efficiency of domestic airports in Taiwan with undesirable outputs and environmental factors. Journal of Air Transport Management, 10(5), 295-303.