Evaluation of E-commerce Performance in SMEs based on Vector Auto Regression Model

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1 Inernaional Journal of u-and e-service, Science and Technolog, pp.5-60 hp://dx.doi.org/0.4257/unness Evaluaion of E-commerce Performance in SMEs based on Vecor Auo Regression Model Li Zhou and Qing-i Chen 2* School of Managemen, MinzuUniversi of China,Being, China 2 School of Business, RenminUniversi of China,Being, China 2 Absrac Wih he developmen of informaion echnolog, E-business becomes he core compeiion of small and medium enerprises in recen ears. In his paper, we make an empirical es o analze how he applicaion of E-business will effec on he business performance. The resul shows ha he E-business applicaion index increased percenage can drive sales volume increased b 0.22 percenages, so he effec of E-business o SMEs' business performance is obvious. From Johnson co-inegraion es, he resul shows ha here exis a leas one direc co-inegraion relaionship beween E-business applicaion and sales volume, which means ha here exis a long-erm equilibrium relaionship beween E-business applicaion and sales volume in SMEs. Kewords: E-commerce, business performance, small and medium enerprises (SMEs), vecor auo regression model. Inroducion Wih he developmen of informaion echnolog, E-business becomes he core compeiion of Small and medium enerprises in recen ears. E-business provides a new sales channel ha can no consider business ime and locaion, also online shopping will reduce he cos compared wih radiional business[]. Elecronic business is an inerne business, ma be defined as he applicaion of informaion and communicaion echnologies (ICT) in suppor of all he aciviies of business. E-commerce focuses on he use of ICT o enable he exernal aciviies and relaionships of he business wih individuals, groups and oher businesses[2]. E-business also promoes he developmen in small and medium enerprise (SMEs), as SMEs didn have he scale compeiion advanage, E-business will become he core compeiion ha can help SMEs ge several advanages as lowes cos, differeniaed services, and more convenien and efficien service[3]. According o he China saisical daa he E-commerce marke overall rade scale is 8. rillion RMB ($.3 rillion) in 202, up 27.9%. E-commerce has a huge poenial in he reail marke, also more small and medium enerprises begin o build heir own online sales websie. The legal definiion of SMEs varies b counr and b indusr, SMEs means a small business ha having fewer han 500 emploees for manufacuring businesses and less han $7 million in annual receips for mos non manufacuring businesses. Hans Jansson (202) poined ha he small business has several advanages as low cos and can be sared on a par-ime basis, small business is also well suied o inerne markeing because i can easil serve specialized niches, independence is anoher advanage of owning a small business, as E- business can furher srenghen he advanages of small business, so ha i would be imporan for SMEs o adop E-business sraeg[4]. ISSN: IJUNESST Coprigh c 204 SERSC

2 Inernaional Journal of u-and e-services, Science and Technolog E-business sofware soluions allow he inegraion of inra and iner firm business processes; i involves business processes spanning he enire value chain: elecronic purchasing and suppl chain managemen, processing orders elecronicall, handling cusomer service, and cooperaing wih business parners. Murra E.Jennex (2004) research he ke infrasrucure facors affecing he success of small companies in developing economies, he resul shows ha workers' skills, clien inerface, and echnical infrasrucure are he mos imporan facors o he success of a B2B E-commerce relaionship[5]. Chrisina A. Fader (2002) provided a model ha idenifies a number of unique facors ha should be considered when esimaing he opimal level of invesmen ino an e-commerce iniiaive, and poined ou here are several consrains for SMEs o adop E-commerce such as lack experise in digial markeing and sales, insufficien resources required for ideal levels of invesmen and oher creaive cos and risk[6]. ElieElia and Louis-A (2007) presened empirical daa from an elecronic surve conduced among 96 manufacuring SMEs o invesigae e-commerce iniiaives and heir relaed benefis. The research findings poin o four main profiles of manufacuring SMEs wih differen e-commerce focuses[7]. As he E-business is becoming more and more imporan o small and medium sized enerprises (SMEs), man researchers focused on he markeing sraeg of E-commerce and give ou some suggesions in using e-business echnolog. PariziaFariselli (999) explored hree issues as globalisaion; SMEs and e-commerce, hen poined ha here are imporan snergies beween e-commerce (virual) neworks and (real) producion neworks[8]. A. J. Davies, A. J. Garcia-Sierra (999) poined ou ha elecronic commerce has been acceped as a bona fide business pracice in he commercial world, and moniored and researched he usage paerns and find ou he effec of hese echnologies no onl on he smaller companies independenl, bu also on heir cusomers, suppliers and collaboraors[9]. Erik Wiersra, Gabriele Kulenkampff (200) assessed he impacs of basic elemens of business sraegies on he relaive compeiive posiion of seleced pes of ISPs, and find ou ha he incumben elcos have a relaivel srong saring poin in he ISP marke, while small regional ISPs have a weak saring poin[0]. In recen ears, e-commerce echnolog used more widel in SMEs. David A. Johnson, Lorna Wrigh (2004) poined ou ha over 60% of Small and Medium Enerprises (SMEs) in he USA and Canada have adoped some form of business process hrough a compuer mediaed nework, such as he Inerne[]. Also, here are man researchers use enerprise models and empirical sud o measure he impac of e-business o small business in emerging economics[2-4]. As he E-commerce developed fas in China, using E-commerce becomes more and more imporan o small and medium enerprise (SMEs). The small business has several advanages as low cos and can be sared on a par-ime basis, and E-business echnolog can srenghen hese advanages. In his paper, we r o analze how E-commerce applicaion will affec he business performance in emerging counries as China and hen give ou some suggesions. 2. Model Analsis 2.. VAR Model Vecor auo regression (VAR) is a saisical model used o capure he linear inerdependencies among muliple ime series. An esimaed VAR model can be used for forecasing, and he quali of he forecass can be judged, in was ha are compleel analogous o he mehods used in unvaried auoregressive modeling.var model is he simulaneous form of auoregressive model, A VAR (p) model of a ime series () has he form as: 52 Coprigh c 204 SERSC

3 Inernaional Journal of u-and e-services, Science and Technolog A A A 0 ( ) ( ) p ( p ) () The srucure of VAR model is decided onl b he number of variables and he lag lengh. For example, if a VAR model has wo variables as and 2, as:, 2, c c 2. 2.,, , 2, 2 (2) Then we change his formula ino marix form, as: 2 c c , 2, 2 (3) Assume ha Y 2 So ha, formula (3) can be wrien as: c.., c, 2, c Y (4) c Y (5) This is he basic model of VAR, as he formula onl has lagged endogenous variables, so ha hese lagged endogenous variables are asmpoic unrelaed wih. Then we can use OLS mehod o esimae each VAR formula, and he parameer esimaors ha we ga will be consisen Sabili Condiions The sabili of he VAR model means ha when we pu an impulse o he innovaion of on formula in he VAR mode,he impac of he effec will graduall reduce.the basic condiion of sabili is ha: all he eigenvalue of should be locaed wihin he uni circle. According o he formula 5, when =, i should be: And when =2, we calculae he formula wih ieraive mehod, as: So ha, when =, i could be wrien as: Y (6) c Y 0 2 Y c Y c Y (7) Y 2 c Y 0 i (8) i 0 i From he formula above, we can ge ha Y becomes a funcion o he vecor, Y 0 and afer he formula ransformaion. So we can analsis he impac resul of hese vecors o find ou wheher he VAR model is sable. If he VAR model is sable, i will saisf he condiions as: Coprigh c 204 SERSC 53

4 Inernaional Journal of u-and e-services, Science and Technolog ) If give one uni impulse o c a =, when,he effec will have a Limi value as (I- ) - 2) If give one uni impulse o Y 0, he effec will be when = and will be graduall disappeared wih ime has been increased. From he analsis abou VAR model, we can ge ha if he VAR model has he uni roo, i will have he memor abou impulse impac for a long ime, so his VAR model is no sable. Also, he response ofendogenous variables will no reduce wih ime increased in his case. 3. Empirical Analsis 3.. Daa Collecion and Evaluaion Index In order o analze how he applicaion of E-business effec on he business performance, we use STATA 2.0 sofware and make a saisical analsis of E-business applicaion index (EB) and sales volume (SV) in SMEs from Being. The E-business applicaion index is ver comprehensive, so ha we use analic hierarch process (AHP) in order o consruc his index. Afer he measuremen and selecion, we consruced he evaluaion index of e-commerce developmen level in SMEs. This evaluaion ssem mainl includes hree class as e-commerce ransacions Index, Informaizaion developmen Index and human capial Index. This E-business applicaion index can be used o analze he level of E-business applicaion in SMEs, he conen of hese hree indicaors as shown below. a) E-commerce ransacions Index (X): Share of e-commerce ransacions, ha is, he raio of e-commerce ransacions o he oal urnover. b) Informaizaion developmen Index(X2): mainl include he informaizaion invesmen raio, he average dail efficienc of compuer and he average his raio of enerprise websie. The informaizaion invesmen raio means he proporion of informaizaion invesmen o oal invesmen. c) Human capial Index(X3): saff raio of he elecronic commerce enerprise and he populari of he Inerne level. The E-business applicaion index can be calculaed b using linear weighed mehod. According o he index ssem, we used comprehensive evaluaion mehod o measure he E- business applicaion index (EAI), he calculaion formula is: EAI m n i j P W W (9) x P 00 (0) max x In his formula, EAI represens he score of E-business applicaion in SMEs, P is he calculaed value of he indicaors, and W is he corresponding weigh.the weigh of ever indicaor is calculaed b AHP mehod, he weigh is deermined b he influence of each index o he upper level index, and we use -9 o rank he influence level.means he influence level is same and 9 means he influence level is highes, he influence level is increased from o 9. B calculaing he weigh, we ge ha he weighs of hree indicaors as W=0.3, W2=0.49 and W3= Coprigh c 204 SERSC

5 Inernaional Journal of u-and e-services, Science and Technolog So ha we can ge he E-business applicaion index based on his mehod. The daa of sales volume is colleced from Being saisic ear book and Caixin daabase, period from 200 o 20. We also underake log processing o daa, noed as LnEB and LnSV ADF Uni Roo Tes The uni roo es was firs pu forward b David Dicke & Wane Fuller, so i is also called DF es. DF es is a basic mehod in saionari es, if we have a model as: Y () Y DF es is he significance es o he coefficien. If, when T, T, ha means he impulse will be reduced when he ime is increased. However, if, he impulse will no be reduced wih he ime, so ha his ime-series daa is no sable. The basic DF es model can be wrien as: Y (2) 2 Y If we add he lagged variable of in formula 0, hen i will be called he augmened Dicke-Fuller es, so ha ADF es model can be wrien as: Y m Y Y (3) 2 i i i Daa sable is he premise of esablishing VAR model, an augmened Dicke Fuller es (ADF) is a es for a uni roo in a ime series sample. We use ADF uni roo es o inspec LnEB and LnSV, he resul as is shown in Table. Through he es resuls we can see ha LnEB and LnSV are non-saionar,hen we es on d.lneb and d.lnsv and demonsrae ha d.lneb and d.lnsv are sable, so we can build he VAR model and use granger es and coinegraion es. Table. Augmened Dicke Fuller Tes (ADF) Variable Tes Saisic % Criical Value 5% Criical Value 0% Criical Value Resul LnEB Unsable LnSV Unsable D. LnEB Sable D. LnSV Sable 3.3. VAR Model Vecor auo regression (VAR) is a saisical model used o capure he linear inerdependencies among muliple ime series. An esimaed VAR model can be used for forecasing, and he quali of he forecass can be judged.var model is he simulaneous form of auoregressive model, A VAR (p) model of a ime series () has he form: A A A 0 ( ) ( ) p ( p ) (4) Coprigh c 204 SERSC 55

6 Inernaional Journal of u-and e-services, Science and Technolog In his paper, I use AIC, SC crierion o idenif he lag lengh. From he resul, we can ge ha he minimum AIC is in lag 2, so I choose lag 2 as he lag lengh. Then, we bulid he VAR model of LnEB and LnSV as: Ln S V LnEB LnSV (5) 0.28 LnEB 0.45 LnSV According o his formula, we can ge ha he applicaion of E-business will promoe sales volume increase. LnEB a lag period increased one percenage can drive LnSV increased b 0.22 percenages, so he effec of E-business o SMEs business performance is obvious. In order o analze he relaions beween E-business applicaion and sales volume, we use granger causali es o analze his VAR model, he resul is shown in able 2.From Table 2, we can ge ha LnEB is he reason o LnSV, which means E-business applicaion is he reason o sales volume increase. However, LnSV is no he reason for LnEB, so ha sales volume increase is no he reason o E-business; his is also same o he conclusion above. Table 2. Granger Causali Tes Equaion Excluded chi2 df Prob> chi2 LnEB LnSV LnSV LnEB A he same ime, we ake Johnson co-inegraion es o analze he long-erm relaions beween E-business applicaion and sales volume increase, he resuls is shown in able 3 Co inegraion is a saisical proper of ime series variables. Two or more ime series are co inegraed if he share a common sochasic drif, if wo or more series are individuall inegraed bu some linear combinaion of hem has a lower order of inegraion, hen he series are said o be co inegraed. Table 3. Johnson Co-inegraion Tes Rank Parms LL Characerisic Value Saisic 5% Significan level * According o he resuls, here exis a leas one direc co-inegraion relaionship beween E-business applicaion and sales volume, which means ha here exis a long-erm equilibrium relaionship beween E-business applicaion and small business sales volume Impulse-response Analsis According o he resuls above, we can ge ha here exis a long-erm equilibrium relaionship beween E-business applicaion and small business sales volume, and E-business is he reason o business sales volume increase, also he VAR model is sable. In order o analze he VAR model, I use Impulse-response funcion and cholesk variance decomposiion, he resuls is shown in Figure and Figure 2. From Figure, we can ge ha when LnEB received one uni impac, i will lead LnSV increase currenl, LnSV will reach he max a =4 period and begin o be sable hen. I illusraes here is long-erm effec beween E-business applicaion and small business sales volume. According o he impulse analsis resuls, we can ge ha E-business applicaion will 2 56 Coprigh c 204 SERSC

7 Inernaional Journal of u-and e-services, Science and Technolog significan influence business sales volume increase, so ha i is imporan o appl E-business in SMEs. The cholesk variance decomposiion also shows he same resul, he conribuion degree of LnSV o LnSV is graduall reduced and he conribuion degree of LnEB o LnSV is graduall increased. From figure 2, we find he conribuion degree of LnSV o LnSV a = period is almos 00%, and hen reduced graduall from sep 2, finall reduced o 67.2% in =8 period. A he same ime, he conribuion degree of LnEB o LnSV is 25% a = period, hen increased and become sable from sep 2, he conribuion degree in =8 period is 62%.This means ha E-business applicaion has a imporan conribuion degree o sales volume increase, and can be used o explain he business performance in SMEs b using E-business echnolog. Figure. Impulse-response Analsis 4. Conclusion Figure 2.Cholesk Variance Decomposiion In his paper, we firs inroduce he ECRM and E-business sraeg in enerprise, and use VAR model o analze how E-commerce affec he business performance in emerging counries as China. The resul shows ha E-business applicaion can improve he sales performance of small business obviousl, here exis a long-erm equilibrium relaionship beween E-business applicaion and small business sales volume. E-business would be he mos imporan facors for SMEs o success. The advanage of using E-business in SMEs basicall has he following aspecs: Firs, elecronic commerce has been he marke developmen ools, he nework markeing aciviies of enerprises can improve markeing efficienc and reduce he cos of sales. For example, inerne adverising can increase he sales Coprigh c 204 SERSC 57

8 Inernaional Journal of u-and e-services, Science and Technolog abou 0 imes compared wih he radiional adverising, bu he cos is onl /0 of radiional adverising; Second, he elecronic commerce can reduce procuremen coss because he enerprise can seek he mos preferenial prices in he global marke suppliers, and reduce he loss of inermediae links due o inaccurae informaion; Third, Elecronic commerce as a markeing plaform, he nework ransacion does no need an inermediar par, and can improve efficienc. B using he nework informaion echnolog, cusomers order can be received direcl hrough he nework, so ha he producs do no need o be sored o he warehouse bu can be shipped direcl o he cusomers. In addiion, reling on he Inerne echnolog like MSN, and oher business real-ime sofware dialog, i can srenghen he communicaion. However, here are sill some inhibiors of using e-commerce in SMEs, such as: The high cos of implemenaion Lack of organizaional readiness wih man SMEs having limied exising IT resources There are sill some complex echnologies like EDI which could require new skills Difficul o achieve imel nework updae The differen percepion beween webpage descripion and he reali of goods Securi, including confideniali and fraud Thus, a range of issues ma affec SMEs decisions o inves in e-business and o ake advanage of fuure opporuniies. These inhibiors of using e-commerce in SMEs sill need o analze and research. Wih he change of marke environmen, enerprises have realized he imporance of cusomer resource. E-CRM is a new managemen mechanism ha aims o improve he relaionship beween enerprises and cusomers, i provides comprehensive, personalized cusomer informaion o sales and service personnel, i also srenghen he racking service, informaion analsis capabiliies, enabling hem o build and mainain he one-o-one relaionship" beween cusomers and enerprise. Wih he exensive applicaion of managemen informaion ssem, small business will face more cusomer daa, using a reasonable CRM sraeg and informaion echnolog will help SMEs esablish a long-erm cusomer relaionship and improve he business performance. References [] H.Jinghua and J.Ximin, An e-commerceperformance assessmen model: Is developmen andan iniial es on e-commerce applicaions in he reailsecor of China, Informaion & Managemen,vol.46,(2009),pp [2] G. C.Juan, J.Daniel and M. Eusebio, Implemeninge-business hrough organizaional learning:an empirical invesigaion in SMEs,InernaionalJournal of Informaion Managemen, vol.27,(2007), pp [3] F.Parizia, O.Chrisinea and P. Chrisian, Elecronic commerce and he fuure for SMEsin a global markeplace: Neworking and publicpolicies, Small Business Economics, vol.2,(999), pp [4] M.Hilmersson,H.Jansson, Inernaional nework exension processes o insiuionall differen markes: Enr nodes and processes of exporing SMEs,Inernaional Business Review,vol.2,(202), pp [5] M.E. Jennex, D. Amoroso and O.Adelakun, E-Commerce Infrasrucure Success Facors for Small Companies in Developing Economies, Elecronic Commerce Research,vol.4, (2004), pp [6] C.A. Fader, Opimizing sunk invesmens in e-commerce: a quali assurance challenge for small businesses,inernaional Journal on Digial Libraries,vol.3,(2002), pp [7] E.Elie and A. L.Louis, Focus of B-o-Be-commerce iniiaives and relaed benefis inmanufacuring smalland medium-sized enerprises,informaion Ssems and e-business Managemen, vol.5,(2007), pp.-23. [8] F.Parizia, O.Chrisine and P. Chrisian, Elecronic commerce and he fuure for SMEsin a global markeplace: Neworking and publicpolicies,small Business Economics, vol.2,(999),pp Coprigh c 204 SERSC

9 Inernaional Journal of u-and e-services, Science and Technolog [9] A.J. Davies and G.Sierra, Implemeningelecronic commerce in SMEs--Three casesudies, BT Technolog Journal, vol.7,(999),pp.97-. [0] W.Erik, K.Gabriele, A frameworkforanalsing sraegies of Inerne ServiceProviders,NETNOMICS: Economic Researchand Elecronic Neworking,vol.3,(200), pp [] A. J.DavidandW. Lorna, The e-businesscapabili of small and medium sized firms in inernaionalsuppl chains, Informaion Ssems ande-business Managemen, vol.2,(2004), pp [2] S.Phavaphan andk.donaprueh, Effecsof e-crm on cusomer bank relaionship qualiand oucomes: The case of Thailand,TheJournalof High Technolog Managemen Research, vol.22,(20),pp [3] F. Slvie andj.judih, Idenifingsuccess facors for rapid growh in SME e-commerce, Small Business Economics, vol.9,(2002),pp [4] P. Lucia ands.francesca, Globalisaion, EBusinessand SMEs: Evidence from he Ialian disricof Prao, Small Business Economics, vol.22,(2004), pp [5] H.T.JamesandW.Richard, A model ofe-commerce use b inernaionalizing SMEs,Journalof Inernaional Managemen, vol.7, (200), pp [6] W.Ing-Long, H.Ching-Yi, A sraeg-based process for effecivel deermining ssemrequiremens in ecrm developmen, Informaionand Sofware Technolog, vol.5,(2009), pp Coprigh c 204 SERSC 59

10 Inernaional Journal of u-and e-services, Science and Technolog 60 Coprigh c 204 SERSC

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