Evaluating Model for B2C E- commerce Enterprise Development Based on DEA

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1 , pp Evaluatig Model for B2C E- commerce Eterprise Developmet Based o DEA Weli Geg, Jig Ta Computer ad iformatio egieerig Istitute, Harbi Uiversity of Commerce Harbi, , Chia Abstract. With the rapid developmet of etwork, e-commerce is the mai way for B2C eterprise to get competitiveess. A import problem i the developmet of B2C eterprises is that with the icreasig of the ivestmet, the efficiecy of eterprises is ot icrease i the same pace. The reaso is that the efficiecy betwee iput ad output ca t be evaluated exactly. So, i order to solve this problem with quatitative methods, a DEA model is established based o iput data ad output data of 7 B2C e- commerce eterprises from 2011 to Iput data icludes marketig costs ad the total assets. Output data icludes the umber of etwork member ad operatig icomes. BCC model is established based o VRS. The developmet status of each eterprise i three years ad the overall developmet treds of all eterprise are aalyzed. Fially, i view of the chage tred of differet eterprises i three years, developig shortcomigs are poited out, reaso are aalyzed, further eterprise developmet strategy ad methods are put forward. Keywords: B2C, E-commerce, Relative efficiecy, Data evelopmet aalysis 1 Itroductio I recet years, with the rapid developmet of etwork, such as Iteret, more ad more eterprises wat to get icome o Iteret [1]. So, B2C e-commerce became the mai way for small eterprises to sell their goods. At the same time, e-commerce eterprises met with the problem, such as, iput costs which ivest to the computer ad etwork cotiued icreasig but the profits ca t icreased at the same time [2]. So How to improve the operatig efficiecy of e-commerce eterprises is a importat issue. Idetify relative efficiet busiess by aalyzig the eterprise's operatig efficiecy. This ot oly allows eterprises to fid themselves' iadequate to promptly improve it, but also ca provide a referece sample for other eterprise whe they make decisios. 2 Mai Model of DEA-BCC ISSN: ASTL Copyright 2014 SERSC

2 I 1984, Baker, Chares ad Cooper coducted a BCC model [3]. Based o the CCR model, addig a assumptio terms which is model is show as follows: max st, j 1 j 1 j 1 λ jx λ jy rj ij λ j 1 X αy ijo rjo j 0, i 1,, m, r 1,, s, j 1, j 1 j 1 [4] Output-Orietated X ij ( x 1 j, x 2 j,, x mj ) T Y rj ( y 1 j, y 2 j,, y sj ) T j is a N 1 vector of costats Assumptio of BCC model is chaged from costat returs to scale to variable returs to scale [5]. So "pure" techical efficiecy(pte) ca be calculated by BCC. May studies decomposed the techical efficiecy (TE) obtaied from a CCR ito two compoets, oe is the scale efficiecy (SE) ad aother oe is PTE [6]. The differece betwee these two TE is that TE i BCC is put dow the scale efficiecy. That is TE=PTE SE [7]. 3 Case Aalysis Based o DEA 3.1 Idicators ad data selectio 7 B2C e-commerce eterprises are selected, they are Suig, Guomei, Amazo, Jigdog, Vipshop, Dagdag, Mcox. All selected eterprises are the performed better, which basically represet the developmet of B2C e-commerce idustry. Combies the characteristics of B2C e-commerce busiesses [8], " turover " ( thousad) ad " member " ( oe hudred thousad ) are selected as output idicators ad " Marketig costs " (thousad), "Techology ad cotet " (thousad), are selected as the iputs of the model. The members meas registered member, their data comes from the 7 listed eterprises i aual report from Baidu,Google ad other search egies. Copyright 2014 SERSC 181

3 3.2 Efficiecy Aalysis Calculated Result by DEA Software: With DEAP 2.1 software tool, the BCC(VRS) model based o output (uder the same circumstaces, how to expad output ad maximize the output) is selected to obtai the efficiecy of specific circumstaces of seve B2C e-commerce eterprises i [9]. Model results are show i Table Aalysis Process: some efficiecy chages will be foud i Table 1. I 2011, the efficiecy of four eterprises busiess is effective; they are Suig, Amazo, Vips ad Dagdag. The efficiecy declie mostly because the lower efficiecy of eterprise scale. I 2012, the busiess efficiecy of four eterprises is effective; they are Suig, Vips, Dagdag ad Mcox. Remaiig the efficiecy of three eterpirses is ivalid, amog these 7 eterprises, all eterprises are keepig techical valid, ad the scale of four eterprise is effective. Therefore, we ca see that the scale efficiecy is a importat factor for the efficiecy of eterprises. Similarly, i 2013, four eterprises are effective, all eterprises are i techology effective ad four eterprises are i scale effective. From above, we ca see that techical efficiecy ad scale efficiecy were risig from 2011 to Overall average efficiecy rise from to ad scale efficiecy rise from to 0.847, while the pure techical efficiecy icreases rapidly from to 1. From these data, we ca see that from 2011 to 2012, E- commerce is developig rapidly. More ad more customers wat to buy goods from the etwork, so it s the chace for B2C e-commerce eterprises expad market share to absorb customers ad expad market share with profits. But we also ca see that from 2012 to 2013, the overall average efficiecy ad scale efficiecy all decreased from to ad vrste is remaiig 1. The reaso is that with the expasio of e-commerce, more ad more eterprises became B2C eterprise ad market competitio icreasig, most eterprise put lots of advertisig for publicity ad they use lower prices for price competitio, all these result the iefficiecy of eterprise. I shortly, there are Suig, VIPS ad Dag three eterprises remai overall efficiecy effective. The reaso is that these B2C eterprises efficiecy scale ca keep pace with the developmet of e-commerce. But there are four eterprise ca t have a steady efficiecy, the reaso is that with E-commerce trasactio scale expaded, e- commerce eterprises wat to expad the scale ad achieve icreased busiess efficiecy, but due to the developmet of the eterprise scale is ot match the busiess facilities, the larger the scale, the more cost i ivestmet, ad without correspodig output, which leads to the curret status of e-commerce busiesses overall efficiecy is ot high. 182 Copyright 2014 SERSC

4 Table 1. Aalysis data by deap Developmet Strategy From IResearch orgaizatios, trade volume from 2011 s 7 trillio to 2013 s 9.9 trillio, ad the average aual growth rate reaches 31.8% [10]. Olie shoppig market share has cotiued to climb. So B2C eterprises should adjust strategy, occupy the market, ad icrease the size of the eterprise effectively. Guomei, Amazo ad Jigdog should adjust the size of the costructio. The preset model does ot match the e-commerce market. They have bee i a state of dimiishig returs, because they have lower efficiecy; the direct reaso is the low scale efficiecy. Because of B2C eterprises ca't moopoly markets, all eterprises ca completed the trasformatio scale ad diversify expasio. The eterprises should restructure, upgrade, maitai the origial market positio, ad develop ew models ad improve market share based o existig core stregths of busiess to chage this status. 4 Coclusio Seve B2C e-commerce eterprises were selected as DUM ad data of them was selected as iput ad output variables, with deap software, a BCC model is established to get aalysis of the operatioal efficiecy of B2C e-commerce eterprises. Aalysis shows that, B2C eterprises "crste" is ot high the reaso is that overall "scale" is ot high. B2C busiesses overall "scale" grows for these three years but the efficiecy of scale is ot always icrease, because of with cotiued icreasig "vrste", the cost which used to remai the icreased scale is more ad more, the icreased "scale" has bee hampered. So if eterprise wat to ehace B2C Copyright 2014 SERSC 183

5 busiesses "scale efficiecy", eterprises should ot expad blidly, they should adjust the size of the eterprise to match the eterprise's stregth ad market, besides, they should make ratioal use of existig resources, make use of advaced maagemet ad operatig model, develop iovative models ad the vertical category ad acillary services, develop core competitiveess, expad product categories, rich product lie ad stregthe the supply chai, improve logistics ad distributio system, ad cotiuously improve operatioal efficiecy, overcome the bottleeck of e-commerce. Fially, the steady developmet of e-busiess eterprises ca come true. Refereces 1. Baker R D, Chares A, ad Cooper WW. Some Models for Estimatig Techical ad Scale Iefficiecies i Data Evelopmet Aalysis, Maagemet Sciece, Issue9, pp , Qualig Wei, Data Evelopmet Aalysis, Sciece Publisher, Beijig, Li Guohog ad Ni Megxue, A Empirical Aalysis of Efficiecy Evaluatio of Maufacturer Logistics System Based o DEA, Logistics techology, volume 31, Issue 5,pp , Geg Weli ad Hu Yigsog, Performace Evaluatio of Robot Desig Based O AHP, Iteratioal Joural of Database Theory ad Applicatio, volume 6, Issue 2, pp.79-88, Feg Yig ad Hog Liag, Research o Implemetatio Performace Evaluatio of Small ad Medium-sized Electroic Commerce Eterprise, Commercial Research, Issue9,pp , Zhao Shukua, Yu Haiqig ad Gog Shulog, The Iovatio Efficiecy of Hi - tech Eterprises i Jili Provice based o DEA Method, Sciece Research Maagemet, volume34,issue 2,pp.36-43, Geg Weli ad Hu Yigsog, Selectio of Data Process Outsourcig Provider Based o AHP, Proceedigs of 2012 Iteratioal Coferece o Measuremet Iformatio ad Cotrol, pp , Xiaoyu Li ad Ximi Tia, Dyamic Vedor Selectio Based o Fuzzy AHP, E-busiess, Issue 13, pp.34-35, IResearch Co, IResearch E-commerce Market i Chia Idustry Developmet Report 10. Chia Electroic Commerce Research Ceter,2013 Chiese E-commerce Market Data Moitorig Report 184 Copyright 2014 SERSC

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