G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 ONLINE CONSUMER BEHAVIOR: AN EXPLORATORY STUDY Namita Bhandari* & Prti Kaushal** *Panjab Univrsity, Chandigarh, India **Chitkara Univrsity, Punjab, India Abstract Onlin shopping is gaining momntum in India. With intrnt pntration improving in th country, smart phons bcoming affordabl and lifstyls bcoming hctic, th way popl usd to shop ar changing. Also with a hug chunk of young and working population, Indian dmographics ar a dlight for -commrc rtailrs. But to gain th trust and attntion of Indian consumrs in this virtual shopping world thr ar many aspcts of consumr bhavior which nd to b xplord. What xactly is Indian consumr thinking whn h is buying onlin, what ar his xpctations, apprhnsions, anxitis and phobias which -rtailrs nd to ovrcom. Is an Indian onlin consumr comfortabl with th click-of-th mous buying, any improvmnts or aras which h thinks nd to gt addrssd, any spcific part of onlin buying which dlights him. To answr such quris th prsnt study givs an insight. This study aims to idntify th main factors which an onlin buyr considrs whil making onlin purchass by using factor analysis. Th rsults hav shown various rasons lik trust, information, convninc, xprinc, ffortlss shopping and bargain bcaus of which consumrs do onlin shopping. Kywords: Onlin Shopping, E-commrc, Consumrs, onlin buyrs. Introduction Onlin shopping, commrc, -tailing or any othr way in which you addrss it, but sal and purchas of rtail goods and srvics via wb has bcom an important part of shopping phnomna. It all startd in 1997, whn worth multi-billion dollar ordrs wr placd through th wbsit of Dll Computrs. Aftr that Amazon and Bay furthr popularizd it. And now thr is a hug dlug of wbsits slling varity of products. Indian intrnt shopping story is still unfolding with approximatly 15 million intrnt usrs and that too only at an intrnt pntration of around 12%. So thr lis a hug unxplord potntial for this trnd to rid th wav of Indian dmographic story. To undrstand what Indian consumr is buying onlin and what is coming in his/hr mind whil xploring th aisls of onlin stors, this study is bing undrtakn. Anothr point worth noticing is th gratr involvmnt of Tir-II citis in this activity. In fact in a study conductd by th nam of Grat Onlin Shopping Fstival has found that mor than 5% of onlin buying is contributd by non-mtros (Googl India, 213). That s why this study is bing conductd in and around Chandigarh. In fact to highlight th incrasing popularity of -rtailing th sam study (Googl India, 213) has found that 212 has bn a phnomnal growth yar in th chaptrs of Indian onlin shopping story as it has witnssd 128% incras in consumr intrst in th yar 211-12. Furthr with incrasing usag of smart phons and bttr broadband connctivity, th onlin shopping trnd will furthr gt a boost. Also th kind of convninc attachd by doing shopping with th click of th mous this trnd is furthr going to gt boost. Living pac is gtting fastr, our daily schduls ar gtting mor hctic and furthr with incrasing ful xpnss, trip to our favorit rtail stors has bcom costlir. In such a scnario consumrs hav startd apprciating th hassl fr onlin shopping mod. Ys, visiting your favorit stor has a factor of hdonic plasur attachd to it, but as of saving tim, ful and fforts has startd taking prcdnc. In som countris -rtailing has alrady bcom quit popular whras in fw countris lik India it is at volving stag, with cosystm componnts lik, broadband pntration and smart phon ownrship not fully dvlopd. All ths things takn togthr ar going to giv a nw twist to th businsss happning so far and disruptiv businss modls ar going to happn through -commrc mod. Rviw of Litratur Thr ar many factors which draw a consumr towards onlin purchas with fw lik accss to lots of information, comptitiv prics, grat choic, convninc tc. (Zhou, Dai & Zhang, 27). Various studis hav trid to undrstand intrnt buying phnomnon from diffrnt angls. It has also bn obsrvd that cultural dimnsions of a nation lik bing individualistic or collctivist and masculin or fminin too ffcts th tndncy to buy onlin (Chau t al., 22). Onlin shopping has also bn found to hav som pculiar influnc of rfrnc groups, prs, family mmbrs and thir rcommndations (Foucault & Schufl, 22). Th onlin shopping xprinc can furthr b improvd if onlin vndors ngag with buyrs mor through social mdia, blogs, chat rooms tc. and thus gnrating mor onlin rfrrals (Zhou t al., 27).Th studis also rval that to undrstand th consumr psychology rgarding onlin purchas cannot b dirctly takn from normal rtail purchas, thr is a nd to sparatly undrstand this (Chung t al., 23). To undrstand onlin shopping bhavior various thortical modls lik Tchnology Accptanc Modl, Thory of Rasond Action or Innovativ Diffusion Thory hav also bn usd (Chung t al., 23). Intrnt shopping and intractiv hom shopping will b prfrrd ovr traditional rtail formats du to tchnological advancmnts bcaus 98
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 wb givs a consumr lots of as to find and compar suitabl products, thus hlps him to mak mor informd buying dcision (Alba t al., 1997). Furthr onlin sarch rducs a buyr s sarch cost du asy and accssibl availability of information, rviws and onlin databass and consumrs us diffrnt stratgis whil sarching information on wb lik, choic of sarch ngin, information filtring tc. (Kumar, Lang & Png, 25). Th litratur also has vidnc of rlation bing xamind btwn CRM practics and onlin rtailing. Thr has bn obsrvd positiv ffct on customr satisfaction by using CRM practics at right tim of onlin markting growth stag (Srinivisan & Moorman, 25).Th intrnt basd diffusion of tchnology has also bn hraldd as an important gam changr in th rlation btwn producr and consumr, if w s how historically changs hav com in th bhavior of consumrs ovr tim ld by cultural, social, political or tchnological dynamics and it has also changd th way comptitors gain advantag by looking for bst bargains in supply chain (Dickson, 2). Thn thr is also found to b diffrncs on th basis of gndr that information tchnology diffusion in shopping bhavior is obsrvd, with mal and fmals having variation in th way thy us and adopt tchnology (Slyk t al., 25). So it is also rquird to undrstand such gndr-basd diffrncs in contxt to wb-basd shopping. To undrstand that what kind of ky points should b kpt in mind whil dvloping wbsits for onlin shopping thortical modls lik Expctation Confirmation modl or Information Systm Continuanc thory, this can hlp in drafting stratgis to bring customrs back to th wbsits for shopping, hnc incrasing customrs lif tim valu (Chang & Chou, 211). Furthr, in th sam study it has bn obsrvd that whn consumrs dvlop an association with a brand on wb community thy tnd to shar thir positiv xprinc and knowldg about th wbsits with othr prospctiv buyrs crating a strong positiv publicity for th -commrc sit. That is why som of th -commrc sits hav stratgizd to st up thir onlin virtual communitis, so that a platform is providd to th usrs to shar thir xprincs (Chang & Chou, 211). Out of altrnativ rtail formats a customr slcts his prfrnc on th basis of crtain dimnsions lik: how many catgoris ar providd, altrnativs providd for ach catgory, what kind of considration st can b formd, comparison of altrnativs on th basis of quality and quantity, transaction costs lik dlivry tim, dlivry costs, transaction costs, supplir facility, as of placing ordrs, prsonal information scurity, social communitis availabl for th wbsit tc. (Alba t al., 1997). To support th onlin shopping rcall, th traditional mods of advrtismnt by using xprinc association mssags instad of itm spcific mssags should b usd, also it dpnds on that how th intgration btwn spokn and writtn words is maintaind which ffcts that mmory would b rtaind b a customr for long for that brand (Tavassoli, 1998). Th factor of gaining trust of consumrs to go ahad with onlin dals without gtting jittry about thir confidntial financial and prsonal information is vry crucial (Schlossr t al., 26). Th incrasing importanc of intrnt basd shopping is actually ncouraging vndors to go for multi-channl stratgy and us of multipl rtail formats simultanously spcially post dot-com burst, whr companis ar optimizing thir markting xpnditur by using thir intrnt fforts to nhanc customr rlationship (Bart t al., 25). Furthr many charactristics of wb-sits and consumrs influnc wb-sit trust, lik: financial risk, information risk, consumr s dgr of involvmnt with products or srvic, dpth of information providd on a sit and dgr of information browsing rquird for a srvic or a product (Bart t al., 25). Nd of th Study With incrasing popularity of onlin shopping th comptition is gtting scalatd and thus it has bcom imprativ for -rtailrs to undrstand th motivators which bring consumrs to shop onlin (Zhou t al., 27). Morovr Indian markts ar still untappd in trms of onlin shopping phnomna and this trnd is still gaining popularity among consumrs. Also th rcntly don survys hav also indicatd th hug growth xpctd from nonmtros in th nar futur (Googl, 213). As th onlin buying trnd is gaining popularity in India and many companis aim to capitaliz on it, it bcoms significant to gt insight about th why, how and what of onlin consumr bhavior. So this study tris to undrstand th antcdnts bhind th onlin purchas that too in Indian contxt. Objctiv of th Study Th objctiv of th study is to undrstand and find th factors which influnc th consumrs whil buying onlin. Th Study To undrstand th dimnsions of consumr bhavior which doing onlin shopping, this study has bn conductd with following particulars: Rsarch Dsign: Th rsarch dsign is xploratory in natur as it just aims to figur out th main factors which a customr considrs whil buying a product from an -commrc wbsit. Data Collction and Qustionnair Dsign: To undrstand th construct of onlin shopping both primary as wll as scondary data has bn usd. To collct th primary data a qustionnair was dvlopd with qustions basd on dmographic profil of th rspondnts and 22 statmnts to masur th attitud of rspondnts on a fiv point likrt scal. Ths statmnts wr collctd by doing a group discussion in a group of tn popl blonging to managmnt ducation background. 99
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Sampl Siz and Sampling Mthod: To collct th data convninc sampling mthod was usd. 125 rspondnts wr contactd from th ara of Chandigarh, Panchkula and Mohali and w wr abl to gt 1 compltly filld qustionnairs; thus lading to a rspons rat of 8%. Statistical Analysis: To xplain th structur or dimnsions of various multidirctional factors which ar usful in studying th construct of onlin shopping bhavior, th data was statistically analyzd by using data rduction tchniqu i.. factor analysis. Rsults & Discussion (a.) Sampl Profil: From th blow tabl, th dmographic profil of th rspondnts can b sn, with sampl consisting of 6% of mal and 4% of fmal rspondnts. Majority of th rspondnts i.. 6% blongd to 22 to 34 yars ag group and blow 21 yars and from 35 to 44 yars numbr of rspondnts wr 17% ach. Tabl 1: Dmographic Profil ITEMS % ag Gndr: Mal 6 Fmal 4 Ag: Upto 21 Yars 1 7 22 to 34 Yars 6 35 to 44 Yars 1 7 45 to 54 Yars 6 Factor Analysis: To crat dimnsions or factors from th 22 itms on which attitud of rspondnts wr masurd on fiv point likrt scal wr factor analyzd on SPSS. Bfor going ahad with factor analysis th condition of data adquacy is chckd by sing th valu of Kaisr-Myr-Olkin Masur of Sampling Adquacy (KMO). Th Appndix1 shows a KMO of.653, which is considrd good for using factor analysis. To chck if thr xists sufficint rlation btwn th variabls to factor analyz thm, Bartltt s Tst valu is chckd from Appndix1 and it is coming significant. From th total varianc xplaind tabl in Appndix2 w can s that th numbrs of factors xtractd ar svn whos Eign valus ar mor than on. Th factors ar xtractd on Kaisr s Critrion of rtaining factors. Th cumulativ varianc xplaind by ths svn factors is coming out to b 63.6%, and th individual varianc xplaind by ach factor is vry balancd among th svn factors. Now to undrstand that undr which factor, th variabl blongs, Rotatd Componnt Matrix tabl in Appndix3 will b usd. Th rotation is don basd on Principal Componnt Analysis mthod. Hr a variabl s loading is shown only undr that factor against which it is highst. Furthr, only thos variabls ar rtaind whos loadings ar at last.4, as w had slctd this supprssion critrion whil running factor analysis on SPSS. Aftr intrprting th Rotatd Componnt Matrix tabl, which has craftd factors by using Varimax rotation by using Kaisr Normalization critrion, w hav com up with th following factors which contain crtain variabls groupd undr rspctiv hads: Factor 1 (Trustworthy Shopping): This factor includs fiv itms which ar majorly rlatd to confidntiality of prsonal information, rliabl product quality, scur financial transactions and also two itms as quick shopping and latst products availabl. Th litratur also has indicatd consumrs apprhnsion for thir prsonal and financial information scurity and wbsits ar also making fforts to nsur to provid such scurity by providing scur wb tchnology, but along with that, -commrc sits nd to invst in ovrcoming consumr s far prcption towards making onlin purchas (Schlossr t al., 26). Furthr an association has bn obsrvd btwn trust and onlin purchas intntions thus lading to considration for spdy shopping and latst products availability. Morovr studis hav found that such contmporary lctronic or intractiv shopping mods provid xtnsiv opportunitis to brows and compar products and thus go for th bst and latst ons (Alba t al., 1997). Furthr onlin trust is drivn by many sub-factors such as scurity, privacy, rror-fr transactions, fulfillmnt of ordr as consumr fls vulnrabl whil doing shopping transactions on intrnt (Bart t al., 25). In fact th lmnt of onlin trust includs prcption of consumrs rgarding that how an -commrc sit prform on xpctations rlatd to products, srvic, blivability and consistncy of information (Bart t al., 25). Factor 2 (Convnint Shopping): This factor contains fiv itms as: quick dlivry, anytim, anywhr shopping, trndy and glamorous shopping. Ths componnts provid a kind of xprinc to usrs of -commrc which lad to customr satisfaction and furthr act as a strong diffrntiator ovr traditional rtail formats. This prcption of as 1
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 which coms with th us of tchnology whil doing shopping is also an important antcdnt of customr satisfaction rgarding onlin shopping, which furthr lads to rpat purchas and visit to an -commrc sit (Alba t al., 1997). Factor 3 (Informd Shopping): Undr this dimnsion th thr itms which ar gtting clubbd ar as: convnint to shop, good amount of information availabl and larg varity to choos from whil shopping on nt. Th findings ar consistnt with th litratur which has placd hug mphasis on rducd sarch cost as an advantag associatd with intrnt basd shopping, as consumrs ar abl to srach products, compar rviws with grat sarch tools and that too fr of cost (Spann & Tllis, 26); (Kumar, Lang & Png, 25). With numbr of brands mushrooming up which provid dynamically changing stuff spcially rlatd to fashion and tchnology th sarch for varity holds a vry important position in th fild of onlin buying. Th dpth and dgr of information associatd with a product catgory is an important charactristic linkd with th wb-basd shopping and in fact purchass which ar information intnsiv nd to hav wbsit with usr frindly navigation facility (Bart t al., 25). Factor 4 (Effortlss Shopping): This factor includs two itms as in hassl fr shopping and savs travl tim. In today s nvironmnt of hctic routin, incrasing ful prics, parking problm and distanc wis widsprad markts, this factor maks hug sns in favor of onlin shopping. Factor 5(Exprintial Shopping): This dimnsion includs thr itms as: xprinc th fl of th product, complt family shopping xprinc and prsonal srvic. Th wb sit signals which convy mor information about th products and wbsit dsigns which ar mor usr frindly and bstow trust hav highr possibility of gtting wbsit visits convrtd into purchas intntions (Schlossr t al., 26). Th ffort has also bn mad to ovrcom th disincntivs associatd with lctronic shopping lik product fl by offring mor intractiv options on whil doing lctronic shopping (Alba t al., 1997). Also to nsur vibrancy in onlin shopping zon it is rquird that vndor s stratgis should focus on that th -commrc sits giv usrs a rliabl and njoyabl xprinc and consumrs also aim to do an informd and bargain drivn shopping (Dohrty & Chadwick, 21). Factor 6(Bargain Shopping): This includs two itms as good bargains and rviw product rcommndations. Th opportunity to gt to know rviws of usrs or visitors of an onlin commrc sit through chat rooms, blogs or othr onlin forums is a big drivr of trust and also works in favor of onlin purchas (Bart t al., 25). In fact Smith t al. (1999) hav concludd that du to sarch as brought by intrnt, markt fficincy whil doing wb basd shopping gos up du to incras in pric lasticity among consumrs. Considrd Whil Shopping Onlin Factor 1 : Trustworthy Shopping Confidntiality of prsonal information Rliabl product quality Scurity of Financial Transactions Quick Shopping Latst product availability Factor 2: Convnint Shopping Quick dlivry of products Anytim shopping Anywhr shopping Trndy shopping Glamorous shopping Factor 3: Informd Shopping Good amount of information Convnint to shop Larg varity to choos from Factor 4: Effortlss Shopping Hassl fr shopping Savs travl tim Factor 5: Exprintial Shopping Exprinc th fl of th product Complt family shopping xprinc Prsonal srvic Factor 6: Bargain Shopping Good bargains Rviw product rcommndations Tabl 2 Factors 11
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Rliability: Now to chck that how consistntly th abov cratd factors ar xplaind by th sub-itms includd undr ach dimnsion, th rliability of th factors with thir sub-itms has bn chckd. To chck th rliability th Cronbach alpha (α) has bn calculatd for ach factor. Th rsults ar as follows: Tabl 3: Cronbach Alpha (α) Valus hy Shopping nt Shopping Shopping Shopping ial Shopping Shopping Factors Trustwort Convni Informd Effortlss Exprint Bargain liability.645.74.593.726.583.526 R marks dquat ood dquat ood dquat dquat R td itms A G A G A A Dl Th rsults of rliability chck by using Cronbach alpha (α) show that all th factors hav mor than.5 of alpha valu with thir rspctiv sub-itms, hnc th factors cratd hav a good rliability scor. As Appndix 4 to 9 show that for th first factor of trustworthy shopping th rliability scor for fiv sub-itms is coming.645, which can b considrd adquat; for th scond factor of convnint shopping th fiv sub-itms hav alpha valu of.74 which can b considrd good; for th third factor of informd shopping th thr sub-itms hav alpha valu of.593 which can b considrd adquat; for th fourth factor of ffortlss shopping th two sub-itms hav alpha valu of.726 which can b considrd good; for th fifth factor of xprintial shopping th thr sub-itms hav alpha valu of.583 which can b considrd good and for th sixth factor of bargain shopping th two sub-itms hav alpha valu of.526 which can b considrd good. Limitations of th Study Th rsults of a study should always b sn in th light of its limitations. Lik, in this study th sampl siz is an issu, as to mak th findings mor gnralizd th sampl siz should hav bn largr. But th KMO valu of sampl adquacy has found th sampl siz adquat to us factor analysis. Morovr, to improv th findings th sampl should hav bn drawn by using probabilistic sampling tchniqu whr as in th prsnt study du to shortag of tim convninc sampling was usd. Managrial Implications of th Study Th abov rsults giv dirction to th managrs and vndors of -commrc wbsits as it hlps in framing stratgis to mak onlin shopping a mor usr frindly xprinc. Also as in India onlin shopping has not yt rachd its tipping point, so it givs an insight into that what th apprhnsions and xpctations of Indian wb shopprs ar. Morovr, many brick-mortar businsss ar planning to vntur into click-mod also, so for thm it is important to undrstand that why consumrs do onlin shopping, how thy viw various componnts of onlin shopping xprinc. Th issus lik scurity of financial information whil transacting on wbsits and confidntiality of thir prsonal information still bring anxity to th minds of Indian consumrs, hnc onlin vndors nd to bring that assuranc to thir minds by having robust back-nd tchnology as wll as right imag through thir wbsits faturs. Furthr, th factor of convninc also tops th mind of an onlin buyr, so ffort should b mad to dlight th consumr by giving xtrmly good buying xprinc by nsuring quick dlivry and hassl fr onlin transactions. Futur Scop of th Study Th thortical framwork concludd from th study in th form of six dimnsions or factors craftd out can b usd furthr to undrstand th of onlin consumr bhavior. Ths factors can b furthr rgrssd on th customr satisfaction scor of th usrs of onlin rtail srvics to bttr undrstand th significanc of ach factor to bring bttr usr xprinc to onlin shopprs. Diffrnt dimnsions in th form of six factors which hav com up through this study can b studid sparatly in dtail to furthr undrstand th construct of onlin shopping bhavior. Rfrncs Alba, J., Lynch, J., Witz, B., Janiszwski, C., Lutz, R., Sawyr, A., & Wood, S. (1997). Intractiv hom shopping: Consumr, rtailr, and manufacturr incntivs to participat in lctronic marktplacs. Journal of Markting, 61 (3), 38-53. Bart, Y., Shankar, V., Sultan, F., & Urban, G. L. (25). Ar th drivrs and rol of onlin trust th sam for all wb sits and consumrs? A larg-scal xploratory mpirical study. Journal of Markting,69 (4), 133-152. 12
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Chang, S., & Chou, C. (211). Factors affcting usr's onlin shopping bhavior: Intgrating th constraint-basd and ddication-basd rlationship prspctivs. African Journal of Businss Managmnt, 5(2), 37-382. Chau, P. Y. K., Col, M., 45, A. P. M., Montoya-Wiss, M., & O'kf, R. M. (22). Cultural diffrncs in th onlin bhavior of consumrs. Communications of th ACM, 45 (1), 138-143. Christy M. K. Chung, C. M. K., Zhu, L., Kwong, T., Chan, G. W. W., & Limaym, M. (23, Jun). Onlin consumr bhavior: A rviw and agnda for futur rsarch. 16th Bld Commrc Confrnc Transformation. Bld, Slovnia, 194-218. Dickson, P. R. (2). Undrstanding th trad winds: Th global volution of production, consumption, and th intrnt. Journal of Consumr Rsarch, 27 (1), 115-122. Dohrty, N. F., & Chadwick, F. E. (21). Intrnt rtailing: th past, th prsnt and th futur. Intrnational Journal of Rtail & Distribution Managmnt, 38(11/12). Foucault, B., & Schufl, D. (22). Wb vs. campus stor? Why studnts buy txtbooks onlin. Journal of Consumr Markting, 19 (4/5), 49-424. Googl India. (213). Rtrivd from: http://yourstory.in/213/1/googl-india-study-about-onlin-shopping/ Kumar, N., Lang, K. R., Png, Q. (25, January). Consumr sarch bhavior in onlin shopping nvironmnts. Procdings of th 38th Hawaii Intrnational Confrnc on Systm Scincs (HICSS-38), 87-12. Schlossr, A.E., Whit, T. B., & Lloyd, S. M. (26). Convrting wb sit visitors into buyrs: How wb sit invstmnt incrass consumr trusting blifs and onlin purchas intntions. Journal of Markting, 7 (2), 133-148. Slyk, C. V., Blangr, F., & Hightowr, R. (25). Undrstanding gndr-basd diffrncs in consumr commrc adoption. Procdings of th 25 Southrn Association of Information Systms Confrnc, 24-29. Smith, M., Baily, J., & Brynjofsson, E. (1999). Undrstanding digital markts: Rviw and assssmnt (Erik Brynjolfsson & Brian Kahin, ds.). MIT: MIT Prss. Spann, M., & Tllis, G. J. (26). Dos th intrnt promot bttr consumr dcisions? Th cas of nam-your-own-pric auctions. Journal of Markting,7 (1), 65-78. Srinivasan,R., & Moorman, C. (25). Stratgic firm commitmnts and rwards for customr rlationship managmnt in onlin rtailing. Journal of Markting, 69 (4),193-2. Tavassoli, N. T. (1998) Languag in multimdia: Intraction of spokn and writtn information. Journal of Consumr Rsarch, 25 (1), 26-37. Zhou, L., Dai, L., & Zhang, D. (27). Onlin shopping accptanc modl: A critical survy of consumr factors in onlin shopping. Journal of Elctronic Commrc Rsarch, 8 (1), 41-62. Appndix: Appndix 1: KMO and Bartltt's Tst Kaisr-Myr-Olkin Masur of Sampling Adquacy. Bartltt' s Tst of Sphricity Approx. Chi-Squar 653 37.326. 6 Df 2 31 Sig.. 13
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Appndix 2: Total Varianc Explaind Initial Eignvalus Extraction Sums of Squard Loadings Rotation Sums of Squard Loadings % of % of % of Componnt Total Varianc Cumulativ % Total Varianc Cumulativ % Total Varianc Cumulativ % 1 4.746 21.574 21.574 4.746 21.574 21.574 2.388 1.855 1.855 2 2.373 1.786 32.36 2.373 1.786 32.36 2.223 1.13 2.958 3 1.681 7.642 4.3 1.681 7.642 4.3 2.115 9.615 3.573 4 1.497 6.84 46.87 1.497 6.84 46.87 2.1 9.97 39.67 5 1.385 6.293 53.1 1.385 6.293 53.1 1.883 8.559 48.229 6 1.243 5.65 58.75 1.243 5.65 58.75 1.812 8.235 56.463 7 1.71 4.868 63.618 1.71 4.868 63.618 1.574 7.155 63.618 8.937 4.257 67.875 9.98 4.128 72.3 1.862 3.917 75.92 11.754 3.427 79.347 12.671 3.48 82.395 13.593 2.697 85.92 14.56 2.544 87.637 15.525 2.385 9.21 16.459 2.84 92.16 17.411 1.869 93.974 18.378 1.717 95.691 19.291 1.325 97.16 2.259 1.176 98.192 21.223 1.14 99.26 22.175.794 1. Extraction Mthod: Principal Componnt Analysis. 14
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Appndix 3: Rotatd Componnt Matrix a Componnt 1 2 3 4 5 6 7 Good Amount Of Information.471 Convnint To Shop.819 Enjoyabl Shopping Exprinc Confidntiality Of Prsonal Information.747 Good Intrn t Connction.751 Rliabl Product Quality.718 Good Bargains.473 Scurity Of Financial Transactions.52 Exprinc Th Fl Of Th Products.614 Quick Dlivry Of Products.88 Anytim Shopping.54 Any whr Shopping.578 Rviw Product Rcommndations.881 Hassl Fr Shopping.759 Savs Travl Tim.797 Trndy Shopping Exprinc.473 Complt family Shopping Exprinc.739 Larg varity to Choos From.675 Prsonal srvic.696 Quick shopping.496 Glamorous and Exciting Shopping Exprinc.557 latst Product Availability.443 Extraction Mthod: Principal Componnt Analysis. Rotation Mthod: Varimax with Kaisr Normalizatio n. Appndix 4: Appndix 5: bach's Alpha Rliability Statistics Cronbach's Alpha N of Itms.645 5 Rliability Statistics Cron N of Itms.74 5 15
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 Appndix 6: Cr onbach's Alpha 93 Appndix 7: Rliability Statistics.5 Cr onbach's Alpha 26 Appndix 8: N of Itms 3 Rliability Statistics.7 Cr onbach's Alpha 83 Appndix 9: N of Itms 2 Rliability Statistics.5 Cr onbach's Alpha 26 N of Itms 3 Rliability Statistics.5 N of Itms 2 Appndix 1: QUESTIONNAIRE 1. Indicat th xtnt of your agrmnt or disagrmnt with ach of th following statmnts by putting a tick mark undr th appropriat numbr. Th maning of th numbrs is as: 1 2 3 4 5 Strongly Disagr Modratly Disagr Nithr Disagr Nor Agr Modratly Agr Strongly Agr o. I buy onlin bcaus : N Statmnts 1 2 3 4 5 Good amount 1 of information Convnint 2 to shop Enjoyabl 3 shopping xprinc Confidntiality 4 of prsonal information Good 5 intrnt connction Rliabl 6 product quality Good 7 bargains(bst Prics/dals) Scurity 8 of financial transactions Exprinc 9 th fl of th product/trials Quick 1dlivry of th product 16
G.J. C.M.P., Vol. 2(4):98-17 July-August, 213 ISSN: 2319 7285 1 2 3 4 5 6 7 8 9 1 2 24*7(anytim) 1 shopping Anywhr 1 shopping Rviw 1 faturs of products and rcommndation Hassl 1 fr shopping Savs 1travl tim Trndy 1 shopping xprinc Complt 1 family shopping xprinc Larg 1varity to choos from Prsonal 1 srvics Quick 2shopping Glamorous 2 and xciting shopping xprinc Latst 2product availability 3. Hav you vr mad a purchas on intrnt? a. Ys b. No 4. Nam : 5. Ag : (Tick th corrct option) [ ] 21 and Undr [ ] 22 to 34 [ ] 35 to 44 [ ] 45 to 54 [ ] 55 to 64 [ ] 65 and Ovr 6. Monthly Incom : (a) Upto Rs. 2, (b) 2,1 to 4, (c) 4,1 to 6, (d) 6,1 to 8, () 8,1 to 1, (f) 1,1 and abov Nam: Addrss: Phon/E-mail: Thank you vry much for participating in this study. Your tim and opinions ar gratly and dply apprciatd. 17