The Fuzzy Evaluation of E-Commerce Customer Satisfaction

Transcription

1 World Alied Scieces Jourl 4 (): 64-68, 008 ISSN IDOSI Publictios, 008 The Fuzzy Evlutio of E-Commerce Customer Stisfctio Mehdi Fsghri d Frzd Hbibiour Roudsri Fculty of Iformtio Techology, Ir Telecommuictio Reserch Ceter (ITRC), Tehr, Ir Istitute of Iformtio Techology, Trbit Modres Uiversity, Tehr, Ir Abstrct: Effective customer stisfctio ivestigtio is very imortt recoditio for e-commerce re to wi i the mret cometitio. It is the roblems eed to be solved for e-commerce customer stisfctio d how to use dvced methods to evlute the customer stisfctio d how to use the evlutio result to imrove their services. This er estblishes customer stisfctio evlutio method bsed o combitio of liguistic vribles, fuzzy trigulr umbers, fuzzy etroy, d lso do some emle reserch. The results of demostrted emle show tht the desiged evlutio method cretes suitble results d the evlutio could be doe s well s ossible. Key words: liguistic Vrible Fuzzy Trigulr Numbers Fuzzy Etroy INTRODUCTION Thus, the idees of e-commerce customer stisfctio hve bee obtied bsed o literture review so tht E-commerce eterrises hve uderstood risig suort ll of the customer stisfctio re for e- the customer stisfctio degree i the ey fctor which commerce. c survive them. Thus, customer stisfctio is the I this er i the et sectio, fuzzy set theory d most imortt criteri of eterrise. Nowdys, the ricils of trigulr fuzzy umber hve bee more d more commercil orgiztios te customer reseted. The, the model for e-commerce customer stisfctio s their mi strtegy obect []. stisfctio hs bee illustrted. A cse study hve bee To evlute the e-commerce customer stisfctio doe, s vlidtio of our method, filly, coclusio qutittively, My coutries estblished their ow hve bee reseted. ide of customer stisfctio degree, mely customer stisfctory Ide, which is ew set of idees Fuzzy set theory: Fuzzy set theory rovides frmewor evlutig eterrise, trde or idustry comletely for hdlig the ucertities. Zdeh iitited the fuzzy from customer s gle []. Amog them hvig much set theory [7]. Bellm reseted some lictios of ifluece re Americ ACSI [3], Swedish SCSI, fuzzy theories to the vrious decisio-mig rocesses Euroe ECSI d Kore KCSI etc. Chiese Customer i fuzzy eviromet [8]. I o-fuzzy set every obect stisfctio Ide (CCSI) strted i 998, re still o the is either member of the set or it is ot member of the stge of elortio d lerig [4]. set but i fuzzy sets every obect is to some etet The e-commerce customer stisfctio rmeters member of set d to some etet it is member of should be visible for customers. The more imortt other set. Thus, ulie the cris sets membershi is rmeters hve bee chose bsed o the literture cotiuous cocet i fuzzy sets. Fuzzy is used i review: ideedecy, comrble d fesibility [-3,5,6]. suort of liguistic vribles d there is ucertiess Ech ide should ideedetly rereset the i the roblem. Fuzzy theory is widely licble i service qulity stisfctio from some sect. To clrify, iformtio gtherig, modelig, lysis, otimiztio, idees should be comrble, s the model should cotrol, decisio mig d suervisio. evlute the differet customer iuts, which eress the Secil cses of fuzzy umbers iclude cris rel stisfctio vlue for e-commerce; cosequetly, while umber d itervls of rel umbers. Although there re they rereset their stisfctio vlue of e-commerce, the my shes of fuzzy umbers, the trigulr d idees should be comrble for differet customer. trezoidl shes re used most ofte for reresetig Corresodig Author: Mehdi Fsghri, Fculty of Iformtio Techology, Ir Telecommuictio Reserch Ceter (ITRC), P.O.B , Tehr, Ir 64

2 World Al. Sci. J., 4 (): 64-68, 008 fuzzy umbers. The followig describes d defiitios I this er, the trigulr fuzzy umber is used for show tht membershi fuctio of trigulr d mesurig Itellectul Citls. More detils bout trezoidl fuzzy umber d its oertios. rithmetic oertios lws of trezoidl fuzzy umber c A fuzzy umber à is cove, if be see i [3]. Cosiderig eerts E i rovide the ossible [ + ( ) ] mi[ ( ), ( )] reliztio rtig of certi Itellectul Citl. The, X, [0,] () evlutio vlue give by ech eert E i re reseted i the form of trigulr fuzzy umber Altertively, fuzzy set is cove if ll -level sets re cove. () () () () i = ( i, i, i 3 ), where i =,,..., (5) A fuzzy set à i the uiverse of discourse X is A () i orml if [9, 0] The verge of ll m A is comuted usig verge mes su ( ) () A oemty fuzzy set à c lwys be ormlized by () i () i () i m ( m, m, 3) ( m,, 3 ) i= i= i= (6) ( ) /su ( ). A fuzzy umber is fuzzy subset i the uiverse of The Model for E-commerce Customer Stisfctio discourse X tht is both cove d orml. Evlutio: The idees of customer stisfctio hve Oe of the most imortt cocets of fuzzy sets is bee costructed bsed o bsed o cosumer's the cocet of -cut d its vrit. It is bridge from cocer, website desig, sfety of website ficil well-defied structure to fuzzy eviromet. iterctio, customer service iformtio, iformtio A trigulr fuzzy umber c be defied by ccurcy, itegrity, system ridity, service resod i qudrulet A = (,, 3), where, its member time, gurtee service, erformce of system, relibility 3 fuctio rereseted s follows. d roduct strtegy [, 4-8]. All of the idees i figure hve bee obtied 0 < through literture review d the oiio of the ( ) Iri eerts i e-commerce re (esecilly i BC ( ) e-commerce). As this idees re esecilly for direct = ( 3) cosumer of e-commerce, this evlutio could be useful ( 3 3) for ll of the busiess to cosumer (BC) e-commerce. 0 > 3 (3) Some reserchers hve bee used fuzzy methods for their evlutio methods [,4,5], but i this er, we costruct customer stisfctio ide of BC e-commerce Let à d be two fuzzy umbers rmeterized by eterrise, which is illustrted i figure d evlutes the qudrulet (,,) 3 d (b,b,b), 3 resectively. customer stisfctio of BC e-commerce eterrise by The the oertios of trigulr fuzzy umbers re dotig Liguistic Vribles d Fuzzy Trigulr eressed s []: Numbers. I dditio, we will evlute it by fuzzy etroy method. ( + ) B = (,, 3) + ( b, b, b3) = ( + b, + b, 3 + b3) Evlutio system hve bee desiged to coform ( ) B to the systemic riciles, scietific d dvced = (,, 3) ( b, b, b3) = ( b, b, 3 b3) riciles, hierrchy riciles, Meuverbility ( ) B = (,, 3) ( b, b, b3) = ( b, b, 3 b3) riciles d Comrbility riciles [7,9]. ( ) B = (,, 3) ( b, b, b3) = ( b3, b, 3 b) (4) Evlutio system hve bee desiged to coform to the systemic riciles, scietific d dvced Trigulr fuzzy umbers re rorite for riciles, hierrchy riciles, Meuverbility qutifyig the vgue iformtio bout most decisio riciles d Comrbility riciles [7,9,0]. roblems []. Ad the rimry reso for usig trigulr The etroy method is obective, for the weight of fuzzy umbers c be stted s their ituitive d ide is lrger whe the vlue of the sme ide o comuttiol-efficiet reresettio. differet obects vries gretly [0,]. It is becuse such 65

3 World Al. Sci. J., 4 (): 64-68, 008 Product Product customiztio Product vlue Product iformtio Product scoe Accurcy of roduct qulity Product gurty E-commerce customer stisfctio idees Service Networ System Service ttitude Service iformtio Distributio Resose d feedbc Cll ceter Service qulity Service mgemet Sfety Relibility Oerbility System ccessibility System humiztio Pymet Accurcy of fee clcultio Accurcy of fee collectio Pymet method Pymet fcilities Fig. : idees of e-commerce customer stisfctio evlutio ide is high i resolutio d thus reflects more 3) The etroy of ide i is iformtio, which mes it is more helful i distiguishig the obects. The stes of fuzzy etroy e = b l b, =,,3 method re: (9) ) Sme tredig: Whe reversl idees d ordil idees coeist, the reversl idees should be trsformed ito ordil idees. ) Covert the ctul ide vlue ito evlutio vlue 3 i = ( i, i, i) i i i l i= e 0 4) The ide weight vector is which 3 w= ( w, w,..., w ) w = w w w i= (,, ) i w =, =,,3 ( e ) (7) (0) 5) The fil vlue for w c be obti by defuzzifictio of w i, which is illustrted i equtio. bi =, =,,3 i 3 (8) w i= + w + w w = 4 () where i deotes the vlue of ide o obect i th for the vlue of trigulr fuzzy umber sice ech The g betwee customer stisfctio d customer resets his oiio i trigulr fuzzy eecttio cosisted of the clcultio stes s below. umbers. is the totl umber of obects d i =,,...,. - Collect customer evlutio d eecttio of is the totl umber of idees d =,,...,. ech ide of electricity suly service qulity. Suose 66

4 { } World Al. Sci. J., 4 (): 64-68, 008 the set of customers is =,,..., d the both their stisfctio degree d eected degree. evlutio d eecttio of ide u, is z d h, Stisfctio of e-commerce customer stisfctio d the resectively, ccordig to customer. Therefore, the g betwee stisfctio d eecttio c be derived evlutio d eecttio of ide u, is l i tble. From the clcultio below (tble ), the geerl z l = z stisfctio evlutio vlue is low d further efforts = should be doe to romote the service qulity. I ll the l d h l = h, resectively, ccordig to ll customers. sects ivolved, rosecute disosl, where the = eecttio d stisfctio yield the lrgest g, is seriously i eed of imrovemet, while ymet brigs - Derive the customer stisfctio of service qulity obviously higher stisfctio with smll g. Furthermore, the model i this er derives geerl service qulity for e-commerce suliers d the g zw = zw () betwee customer eecttio d service erformce = for differet service ctegory (tble ). Such fuctio 3- Clculte the g betwee customer stisfctio hels the comy fid those idees where the g d eecttio of electricity suly service qulity eists d the size of g s well, which oits the brethrough for service qulity imrovemet. For e- commerce suliers, differet ids of customers, e.g. SQ = ( z e ) w (3) idustril, commercil d residul cll for differet weight = distributios. The model is lso suitble for vrious ids Cse study: Accordig to the gthered idees i of customer stisfctio evlutio d thus hels the Error! Referece source ot foud., questioire sulier romotig the service qulity stisfctio, by hs bee rered d five customers, who do their rovidig services for ech id of customers urchses through e-commerce, fill i the questioire i ccordigly. Tble : Clcultio of e-commerce customer stisfctio vlue d the g betwee stisfctio d eecttio Obective Obective weight Ide Ide weight Eected vlue Actul vlue Customer stisfctio G Product (.,3.,4.) Product customiztio (.3,5.,6.4) (6,7,8) (4,5.,6.7) Product vlue (3,3.8,4.7) (5,6.,6.9) (5,5.8,7.) Product iformtio (.,3.6,3.9) (7,8.,9) (3.4,5.,7) Product scoe (.5,.6,.9) (4,4.5,5.3) (,3.4,5.7) Accurcy of roduct qulity (6.6,7.8,8.) (7.8,8.8,9.) (6,7.,8.4) Product gurty (5.6,5.7,6.8) (5.8,7.5,8.9) (4,6.,7.) Service (3.,3.5,4.3) Service ttitude (3,5,4.6,5.4) (5.6,6.4,6.9) (,3,3.5) 6..7 Service iformtio (4.6,5.6,7) (6.,7.6,8.8) (4,4.,4.8) Distributio (3,4,6) (7.5,8.8,9.7) (.,3.,3.6) Resose d feedbc (.,.,.5) (5.6,7.,7.3) (4,4.5,6) Cll ceter (0.,0.9,.7) (5.9,6.8,9) (,3,3.9) Service qulity (.4,.4,3) (7,8,0) (5,7.,9) Service mgemet (.,3.,3.6) (5.6,6.4,7.8) (3,5.6,7.4,) Networ system (.,3,5.) Sfety (.,3,3.4) (6,7.,8.4) (5,6.4,7.6) Relibility (3,4,6) (8.8,9.,0) (7,8.8,0) Oerbility (.8,3.,4.) (5.,5.8,6.7) (3,4.,4.8) System ccessibility (,3.,4.6) (5,6.,6.8) (5,6.7,8.7) System humiztio (4,5.6,6.8) (5.5,6.,8.) (3,5.,6.7) Pymet (4,5.,6.4) Accurcy of fee clcultio (4.,4.9,5.6) (6.,7.8,9.8) (5,6,7.6) Accurcy of fee collectio (3.6,5.,7) (5.,6.,7.) (5,6,8.) Pymet method (.3,.8,3) (6.,8.,9.4) (5,6.,6.8) Pymet fcilities (3.,4.7,5.) (4.,6.,7) (5,5.8,6.9) 67

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