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- Page 7 and 8: VIIWe wish to thank the reviewers o
- Page 9: IXContentsPrefaceV1. A Conceptual F
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- Page 22 and 23: 12E-CommerceThe Application Layer c
- Page 24 and 25: 14E-CommerceService description. Th
- Page 26 and 27: 16E-Commerceunderstanding about the
- Page 28 and 29: 18E-CommerceThis chapter contribute
- Page 30 and 31: 20E-CommercePorter M (2001). Strate
- Page 32 and 33: 22E-CommerceTo evaluate the e-comme
- Page 34 and 35: 24E-CommerceAa 2a a4m1 m 2 m 3m (
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- Page 38 and 39: 28E-CommerceIndexFuzzy numberAltern
- Page 40 and 41: 30E-CommerceS. Mabuchi (1988). An a
- Page 42 and 43: 32E-Commercetechnology implementati
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- Page 48 and 49: 38E-CommerceNITC (National Informat
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- Page 60 and 61: 50E-Commerce4.3.2 The architecture
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- Page 70 and 71: 60E-CommerceThe third level of inve
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- Page 80 and 81: 70E-CommerceAs a first step towards
- Page 82 and 83: 72E-Commerce5. Conclusion and Outlo
- Page 84 and 85: 74E-CommerceSchmid, B. F., Schroth,
- Page 86 and 87: 76E-CommerceThe following section p
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84E-CommerceThe resultant value som
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86E-CommerceG shareholdershareholdi
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88E-Commerce17: Murata Noda Screen
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90E-Commerceand testing data in the
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92E-Commerce(c) Centrality-based ra
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Ranking Companies Based on Multiple
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Ranking Companies Based on Multiple
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Considering Culture in Designing We
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Considering Culture in Designing We
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Considering Culture in Designing We
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Considering Culture in Designing We
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Considering Culture in Designing We
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Considering Culture in Designing We
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Consumer Responses to Colors of E-C
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Consumer Responses to Colors of E-C
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Consumer Responses to Colors of E-C
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120E-Commerce4. Research methodOur
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122E-Commerceavailable information
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124E-CommerceNewsvine Green. Starti
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126E-CommerceProcedureRespondents w
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128E-Commerce6. Data analysis and r
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130E-CommerceHue 1Newsvine Green (d
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132E-CommerceEffects of graphic cha
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134E-Commercethe consumer retains w
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136E-Commercemaintain, load more ra
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138E-CommerceBellizzi J. A. & Hite
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140E-CommerceHill A. & Scharff L. V
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142E-CommerceSpool J. M., Scanlon T
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144E-CommerceConsequently, we concl
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146E-CommerceDimensionsSystems qual
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148E-Commercefunction deployment (Q
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150E-CommerceUseful help serviceEle
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152E-Commerceplanning, enacting and
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154E-Commercecomplete and measurabl
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156E-Commerce There is "About us" s
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158E-Commerce Validation testing -
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160E-Commercefor the Websites (Lohs
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162E-CommerceSinnappan S., Carlson
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164E-Commercerecommendations of a t
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166E-Commerce3.1 Neighborhood Based
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168E-Commerce3.3 Significance Weigh
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170E-Commerce , u1 0,fR5fuR1 u2else
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172E-CommerceFigure 6 shows the ste
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174E-CommerceMAE0.750.740.730.720.7
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Improving performance in recommende
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Improving performance in recommende
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Attacks on Two Buyer-Seller Waterma
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Electronic Commerce Readinessin Dev
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Can a Recommender System induce ser
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A Mobile Commerce Model for Automob
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A Mobile Commerce Model for Automob
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The Automatic Attaching Function Ba
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