动态市场竞争环境下电子商务企业盈利能力的影响因素研究

doi:10.16381/j.cnki.issn1003-207x.2016.08.003

中国管理科学 ›› 2016, Vol. 24 ›› Issue (8): 18-27.doi: 10.16381/j.cnki.issn1003-207x.2016.08.003

动态市场竞争环境下电子商务企业盈利能力的影响因素研究

杨卓凡^1,2, 石勇^1,2,3

1. 中国科学院大学管理学院, 北京 100190;
2. 中国科学院虚拟经济与数据科学研究中心, 北京 100190;
3. 中国科学院大数据挖掘与知识管理重点实验室, 北京 100190

收稿日期:2015-05-04 修回日期:2015-07-09 出版日期:2016-08-20 发布日期:2016-08-24
通讯作者: 石勇(1956-),男(苗族),四川成都人,中国科学院大数据挖掘与知识管理重点实验室主任,中国科学院大学经济与管理学院副院长,教授,研究方向:大数据挖掘与知识管理、信用评分、决策分析,E-mail:yshi@ucas.ac.cn. E-mail:yshi@ucas.ac.cn
基金资助:
国家自然科学基金重点资助项目（71331005）；国际（地区）合作与交流项目（71110107026）

Study on E-commerce Profitability Determinant Under Dynamic Competitive Market Environment

YANG Zhuo-fan^1,2, SHI Yong^1,2,3

1. Management of School, University of Chinese Academy Sciences, Beijing 100190, China;
2. Research Center on Fictitious Economy & Data Science, Chinese Academy Sciences, Beijing 100190;
3. Key Research Lab on Big Data Mining and Knowledge Management, Chinese Academy Sciences, Beijing 100190

Received:2015-05-04 Revised:2015-07-09 Online:2016-08-20 Published:2016-08-24

摘要/Abstract

摘要： 为找到电子商务企业高投入、低投资回报现象存在的原因，本文首先运用数据包络分析（DEA）模型计算了电子商务企业投入对产出的过度效应，即投入拥挤，然后将之与行业内的市场竞争程度和移动电子商务的发展相结合，通过构建面板数据回归模型，详细探讨了动态市场竞争环境下电子商务企业盈利能力的影响因素。研究结果证实了资产规模过大对传统电子商务企业盈利能力具有削弱作用，而市场集中度和移动电子商务的发展则对传统电子商务企业盈利能力具有推动作用。这些发现启示企业经营管理者应聚焦于移动电子商务发展带来的新机遇，消除投入拥挤，通过调适生产规模和新业务模式的创新，开辟新的营销渠道和盈利模式。

关键词: 电子商务, DEA, 投入拥挤, 盈利能力, 市场集中度

Abstract: A major current focus in e-commerce study is to explore why there are high inputs but low profits in e-commerce. Focusing on the excessive effect of inputs on outputs, market competition rate and mobile e-commerce development, input congestion amount is firstly calculated using data envelopment analysis models, and then e-commerce firm profitability determinants are explored by constructing the panel data regression model. Thirty five pure e-commerce websites from the stock markets of Shanghai, Shenzhen, Hong Kong and NASDAQ are considered, all of which utilize at least one of the two e-business models, namely business-to-business (B2B) and business-to-customer (B2C). The results of DEA models identify that e-commerce suffers from congestion, and the regression shows that asset input congestion has a negative effect on e-commerce firm profitability while market concentration rate and the development of mobile e-commerce can strengthen e-commerce firm profitability. These findings indicate that it is input congestion that leads to low profits. It also enlightens decision makers to strengthen their profitability by eliminating congestion resources and adding new marketing channels such as mobile e-commerce.

Key words: e-commerce, DEA model, congestion, profitability, market concentration

中图分类号:

F224

杨卓凡, 石勇. 动态市场竞争环境下电子商务企业盈利能力的影响因素研究[J]. 中国管理科学, 2016, 24(8): 18-27.

YANG Zhuo-fan, SHI Yong. Study on E-commerce Profitability Determinant Under Dynamic Competitive Market Environment[J]. Chinese Journal of Management Science, 2016, 24(8): 18-27.

参考文献

[1] Bremser W G, Chung Q B. A framework for performance measurement in the e-business environment [J]. Electronic Commerce Research and Applications,2005,4(4):395-412.

[2] Ellickson P B, Market structure and performance [M]// Wright J D. International Encyclopedia of the Social & Behavioral Sciences (Second Edition), Oxford: Elsevier, 2015: 549-554.

[3] 王斌,田志龙, 动态竞争战略中的企业环境分析 [J]. 研究与发展管理,2005,17(3):39-58.

[4] Penrose E T. The theory of the growth of the firm [M]. New York: Oxford university press,1995.

[5] 黎传国,陈收,毛超,等, 资源配置视角下战略调整测度及其对绩效的影响 [J]. 中国管理科学,2014,22(11), 19-26.

[6] Schumpeter J A. Capitalism, socialism, and democracy [M]. New York: Harper Torchbooks, 1942,

[7] Kamien M I, Schwartz N L. Market structure and innovation [M]. Cambridge: Cambridge University Press,1982.

[8] Raider H J. Market structure and innovation [J]. Social Science Research,1998,27(1):1-21.

[9] Grifell-Tatjé E, Lovell C A K. Profits and productivity [J]. Management Science,1999,45(9):1177-1193.

[10] Garrigosa E G, Tatjé E G. Profits and total factor productivity: A comparative analysis [J]. Omega,1992,20(5-6):553-568.

[11] Gold B. Technology, productivity and economic analysis [J]. Omega,1973,1(1):5-24.

[12] Serrano-Cinca C, Fuertes-Callén Y, Mar-Molinero C. Measuring DEA efficiency in Internet companies [J]. Decision Support Systems,2005,38(4):557-573.

[13] Min S, Wolfinbarger M. Market share, profit margin, and marketing efficiency of early movers, bricks and clicks, and specialists in e-commerce [J]. Journal of Business Research,2005,58(8):1030-1039.

[14] Dehning B, Richardson V J. Returns on investments in information technology: A research synthesis [J]. Journal of Information Systems,2002,16(1):7-30.

[15] Porter M E. Competitive advantage: Creating and sustaining superior performance [M].Hong Kong:Free Press,1985.

[16] 戴维·贝赞可,戴维·德雷诺夫,马克·尚利,等. 战略经济学 [M]. 詹正茂,冯梅红等,译.3版,北京:中国人民大学出版社, 2006:346-351.

[17] Coase R H. The nature of the firm [J]. Economica,1937,4(16):386-405.

[18] Färe R, Svensson L. Congestion of production factors [J]. Econometrica,1980,48(7):1745-1753.

[19] Odeck J. Congestion, ownership, region of operation, and scale: Their impact on bus operator performance in Norway [J]. Socio-Economic Planning Sciences,2006,40(1):52-69.

[20] Khodabakhshi M. A one-model approach based on relaxed combinations of inputs for evaluating input congestion in DEA [J]. Journal of Computational and Applied Mathematics,2009,23(0):443-450.

[21] Khodabakhshi M, Lotfi F H, Aryavash K. Review of input congestion estimating methods in DEA [J]. Journal of Applied Mathematics,2014:1-9.

[22] Marques R C, Simões P. Measuring the influence of congestion on efficiency in worldwide airports [J]. Journal of Air Transport Management,2010,16(6):334-336.

[23] Chen Y. Congestion in commodity trading advisors [J]. INFOR,2011,49(1), 63-74.

[24] Flegg A T, Allen D O. Congestion in the Chinese automobile and textile industries revisited [J]. Socio-Economic Planning Sciences,2009,43(3):177-191.

[25] Brockett P L, Cooper W W, Wang Yuying,et al. Inefficiency and congestion in Chinese production before and after the 1978 economic reforms [J]. Socio-Economic Planning Sciences,1998,32(1):1-20.

[26] Zarate J M, Boksa P, Baptista T, et al. Using DEA to identify and manage congestion [J]. Journal of Productivity Analysis,2004,22(3):207-226.

[27] Cooper W W, Thompson R G, Thrall R M.Chapter 1 Introduction: Extensions and new developments in DEA [J]. Annals of Operations Research,1996,66(1):1-45.

[28] Banker R D, Charnes A, Cooper W W. Some models for estimating technical and scale inefficiencies in data envelopment analysis [J]. Management science,1984,30(9):1078-1092.

[29] Cooper W W, Seiford L M, Zhu J. A unified additive model approach for evaluating inefficiency and congestion with associated measures in DEA [J]. Socio-Economic Planning Sciences,2000,34(1):1-25.

动态市场竞争环境下电子商务企业盈利能力的影响因素研究

Study on E-commerce Profitability Determinant Under Dynamic Competitive Market Environment

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