Internal and external value evaluation of E-business strategy in enterprise

Transcription

1 Available online Journal of Chemical and Pharmaceuical Research, 2014, 6(6): Research Aricle ISSN : CODEN(USA) : JCPRC5 Inernal and exernal value evaluaion of E-business sraegy in enerprise Li Zhou School of Managemen, Minzu Universiy of China, Being, China ABSTRACT 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 supply chain managemen, processing orders elecronically, handling cusomer service, and cooperaing wih business parners.according o he empirical analysis, 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. Key words: E-commerce, Sofware, Enerprises Sraegy, Analyic Hierarchy Process (AHP) INTRODUCTION 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. Wih he developmen of informaion echnology, E-business becomes he core compeiion of Small and medium enerprises in recen years [1]. Elecronic business is an inerne business, may be defined as he applicaion of informaion and communicaion echnologies 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. E-business also promoes he developmen in small and medium enerprise, 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 [2]. According o he China saisical daa he E-commerce marke overall rade scale is 8.1 rillion RMB ($1.3 rillion) in 2012, 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 by counry and by indusry, SMEs means a small business ha having fewer han 500 employees for manufacuring businesses and less han $7 million in annual receips for mos non manufacuring businesses. Hans Jansson (2012) 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 easily 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 sraegy [3]. 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 supply chain managemen, processing orders elecronically, handling cusomer service, and cooperaing wih business parners. Murray E.Jennex (2004) research he key 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 [4]. 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 693

2 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 [5]. Elie Elia and Louis-A (2007) presened empirical daa from an elecronic survey conduced among 96 manufacuring SMEs o invesigae e-commerce iniiaives and heir relaed benefis [6]. The research findings poin o four main profiles of manufacuring SMEs wih differen e-commerce focuses. As he E-business is becoming more and more imporan o small and medium sized enerprises (SMEs), many researchers focused on he markeing sraegy of E-commerce and give ou some suggesions in using e-business echnology. Parizia Fariselli (1999) explored hree issues as globalisaion; SMEs and e-commerce, hen poined ha here are imporan synergies beween e-commerce (virual) neworks and (real) producion neworks [7]. A. J. Davies, A. J. Garcia-Sierra (1999) 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 only on he smaller companies independenly, bu also on heir cusomers, suppliers and collaboraors [8]. Erik Wiersra, Gabriele Kulenkampff (2001) assessed he impacs of basic elemens of business sraegies on he relaive compeiive posiion of seleced ypes of ISPs, and find ou ha he incumben elcos have a relaively srong saring poin in he ISP marke, while small regional ISPs have a weak saring poin [9]. In recen years, e-commerce echnology used more widely 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 [10]. Also, here are many researchers use enerprise models and empirical sudy o measure he impac of e-business o small business in emerging economics [11]. 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 echnology can srenghen hese advanages. In his paper, we ry o analyze how E-commerce applicaion will affec he business performance in emerging counries as China and hen give ou some suggesions. EXPERIMENTAL SECTION 2.1 Daa collecion and evaluaion index In order o analyze how he applicaion of E-business effec on he business performance, we use STATA 12.0 sofware and make a saisical analysis of E-business applicaion index (EB) and sales volume (SV) in SMEs from Being.The E-business applicaion index is very comprehensive, so ha we use analyic hierarchy 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 sysem mainly includes hree class as e-commerce ransacions Index, Informaizaion developmen Index and human capial Index. This E-business applicaion index can be used o analyze he level of E-business applicaion in SMEs, he conen of hese hree indicaors as shown below. a) E-commerce ransacions Index (X1): Share of e-commerce ransacions, ha is, he raio of e-commerce ransacions o he oal urnover. b) Informaizaion developmen Index(X2): mainly include he informaizaion invesmen raio, he average daily efficiency 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 populariy of he Inerne level. The E-business applicaion index can be calculaed by using linear weighed mehod. According o he index sysem, we used comprehensive evaluaion mehod o measure he E-business applicaion index (EAI), he calculaion formula is: m n EAI = P W W (1) i= 1 j= 1 x P max 100 (2) 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 every indicaor is calculaed by AHP mehod, he weigh is deermined by he influence of each index o he upper level index, and we use 1-9 o rank he influence level.1means he influence level is same and 9 means he influence level is highes, he influence level is increased from 1 o 9. By calculaing he weigh, we ge ha he weighs of hree indicaors as W1=0.31, W2=0.49 and W3=

3 So ha we can ge he E-business applicaion index based on his mehod. The daa of sales volume is colleced from Being saisic year book and Caixin daabase, period from 2001 o We also underake log processing o daa, noed as LnEB and LnSV. 2.2 ADF uni roo es The uni roo es was firs pu forward by David Dickey & Wayne Fuller, so i is also called DF es. DF es is a basic mehod in saionariy es, if we have a model as: Y ρ + µ = 1 (3) Y DF es is he significance es o he coefficien. If ρ<1, when T, ρ T 0, ha means he impulse will be reduced when he ime is increased. However, if ρ 1, 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: ( + δ ) Y β + µ = + β 2 + Y (4) If we add he lagged variable of Υ in formula 10, hen i will be called he augmened Dickey-Fuller es, so ha ADF es model can be wrien as: Y = β + β + δy + α Y + ε m i i (5) i= 1 Daa sable is he premise of esablishing VAR model, an augmened Dickey 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 able 1. Through he es resuls we can see ha LnEB and LnSV are non-saionary,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 1: Augmened Dickey Fuller es (ADF) Variable Tes Saisic 1% Criical Value 5% Criical Value 10% Criical Value Resul LnEB Unsable LnSV Unsable D. LnEB Sable D. LnSV Sable 2.3 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 qualiy of he forecass can be judged.var model is he simulaneous form of auoregressive model, A VAR (p) model of a ime series y () has he form: A y = A y + + A y + ε 0 ( ) 1 ( 1) p ( p) ( ) (6) In his paper, I use AIC, SC crierion o idenify 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 SV (7) = LnEB LnEB LnSV LnSV 2 According o his formula, we can ge ha he applicaion of E-business will promoe sales volume increase. LnEB a lag 1 period increased one percenage can drive LnSV increased by 0.22 percenages, so he effec of E-business o SMEs business performance is obvious. In order o analyze he relaions beween E-business applicaion and sales volume, we use granger causaliy es o analyze 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. 695

4 Table 2: Granger causaliy es Equaion Excluded chi2 df Prob > chi2 LnEB LnSV LnSV LnEB A he same ime, we ake Johnson co-inegraion es o analyze he long-erm relaions beween E-business applicaion and sales volume increase, he resuls is shown in able 3 Co inegraion is a saisical propery of ime series variables. Two or more ime series are co inegraed if hey share a common sochasic drif, if wo or more series are individually 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 es 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. 2.4 Impulse-response analysis and variance decomposiion 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 analyze he VAR model, I use Impulse-response funcion and cholesky variance decomposiion, he resuls is shown in figure 1 and figure 2. Figure 1. Impulse-response analysis Figure 2. Cholesky variance decomposiion From figure 1, we can ge ha when LnEB received one uni impac, i will lead LnSV increase currenly, 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 analysis resuls, we can ge ha E-business applicaion will significan influence business sales volume increase, so ha i is imporan o apply E-business in SMEs. 696

5 The cholesky variance decomposiion also shows he same resul, he conribuion degree of LnSV o LnSV is gradually reduced and he conribuion degree of LnEB o LnSV is gradually increased. From figure 2, we find he conribuion degree of LnSV o LnSV a =1 period is almos 100%, and hen reduced gradually from sep 2, finally reduced o 67.2% in =8 period. A he same ime, he conribuion degree of LnEB o LnSV is 25% a =1 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 by using E-business echnology. DISCUSSION However, here are sill some inhibiors of using e-commerce in SMEs, such as: The high cos of implemenaion Lack of organizaional readiness wih many SMEs having limied exising IT resources There are sill some complex echnologies like EDI which could require new skills Difficul o achieve imely nework updae The differen percepion beween webpage descripion and he realiy of goods Securiy, including confidenialiy and fraud Thus, a range of issues may 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 analyze 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 analysis capabiliies, enabling hem o build and mainain he one-o-one relaionship" beween cusomers and enerprise. Wih he exensive applicaion of managemen informaion sysem, small business will face more cusomer daa, using a reasonable CRM sraegy and informaion echnology will help SMEs esablish a long-erm cusomer relaionship and improve he business performance. CONCLUSION In his paper, we firs inroduce he ECRM and E-business sraegy in enerprise, and use VAR model o analyze 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 obviously, 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 basically has he following aspecs: Firs, elecronic commerce has been he marke developmen ools, he nework markeing aciviies of enerprises can improve markeing efficiency and reduce he cos of sales. For example, inerne adverising can increase he sales abou 10 imes compared wih he radiional adverising, bu he cos is only 1/10 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 inermediary pary, and can improve efficiency. By using he nework informaion echnology, cusomers order can be received direcly hrough he nework, so ha he producs do no need o be sored o he warehouse bu can be shipped direcly o he cusomers. In addiion, relying on he Inerne echnology like MSN, and oher business real-ime sofware dialog, i can srenghen he communicaion. REFERENCES [1] JG Cegarra-Navarroa ; DJ Jiménezb ; EÁM Conesac,Inernaional Journal of Informaion Managemen, 2007,27, [2] S Drew,European Managemen Journal, 2003,21,79 88 [3] T Koninen ; A Ojala1,Inernaional Business Review, 2011,20, [4] ME Jennex ; D Amoroso,Elecronic Commerce Research, 2004,4, [5] CA Fader,Inernaional Journal on Digial Libraries, 2002, 3, [6] E Elia, LA Lefebvre,Informaion Sysems and e-business Managemen, 2007,5, 1-23 [7] P Fariselli ; C Oughon ; C Picory ; R Sugden,Small Business Economics, 1999,12, [8] AJ Davies, AJ Garcia-Sierra,BT Technology Journal, 1999,17, [9] E Wiersra ; G Kulenkampff ; H Schaffers,Nenomics, 2001,3,35-65 [10]KA Qureshia,Inernaional Journal of Informaion Managemen, 2008, 28, [11] H Weigand,Schoop,M., Moor,A.d., Group Decision and Negoiaion, 2003,12,