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An auction participants’ feedback rating is a quantitative score that is based on the feedback reviews received from other community members. Ebay suggests that it be treated as “a measure of an eBay user's reputation in the community.” A person’s feedback rating can be computed using the following procedures: a) +1 point is tallied for each member who has left a positive comment for that person; the sum of these tallies is commonly referred to as the (number of unique) “positives” and it is the number of positives listed in a person’s Feedback Profile as being “from unique users” (e.g., see Figure 1 - IBM’s number of unique positives is 2453); b) -1 point is tallied for each member who has left a negative comment for that person; the sum of these tallies is commonly referred to as the (number of unique) “negatives” and it is the number of negatives listed in a person’s Feedback Profile as being “from unique users” (e.g., see Figure 1 - IBM’s number of unique negatives is 106); and c) the (number of unique) negatives are subtracted from the (number of unique) positives to yield the feedback rating (e.g., see Figure 1 -IBM’s feedback rating is 2347 1 = 2453 - 106). Research into the impact of online-auction feedback on consumer/bidder behavior has considered only quantitative aggregate reputation measures, such as the feedback rating, the number of unique positives and the number of unique negatives. Evidence indicates that the feedback rating does not fully explain how bidders use feedback information, and that bidders place more weight on (the number of unique) negatives than on (the number of unique) positives (Ba and Pavlou 2002, Lucking-Reilly 2000, Melnik and Alm 2002). Assuming that negatives and positives communicate potential losses and gains for a future transaction, respectively, then these results are consistent with the asymmetric impact of gains and losses in accordance with prospect theory (Kahneman and Tversky 1981, Tversky and Kahneman 1992). 124
1 Note that eBay actually indicated a feedback rating of 2349 for IBM while reporting 2453 positives and 106 negatives; however, this is, obviously, in error. EBay acknowledges this problem in their discussion boards: for example, a May 26, 2003 post by an eBay staff member states, “Hi Folks, We are aware that some members' feedback scores and/or summaries are not showing correct numbers. We are currently investigating the situation and hope to have it resolved soon. Thank you for your patience in this matter as we work to correct this problem. Daphne Community Development A main limitation of these inquiries is that they do not consider many other Feedback Forum elements/details, such as individual-auction comments, which contain “much (service performance) information about sellers,” (Ba and Pavlou 2002, page 256). Research which delves below the surface of the aggregate feedback measures is important because it can provide greater insight into: a) how consumers process and use online auction word-of-web information, b) which feedback elements impact consumer/bidder perceptions and behavior, c) how practitioners should make online-auction reputation- or service-related decisions (e.g., being less concerned about not receiving positive feedback, but doing everything possible to minimize the likelihood of receiving negative feedback), and d) the role of word- of-web rating-and-review information in online auctions in order to replicate or transfer its effects to other online (or offline) contexts or applications. STUDY ONE: RATING-AND-REVIEW WOW 125
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Volume 2 Contents: A Global Examina
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A Global Examination Of Relationshi
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and to measure them simultaneously
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customers’ total consumption expe
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From product perceived quality towa
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cumulative, or a combination of the
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trust4 -.68 commit1 .59 commit2 .51
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we observed that the least correlat
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outside of the consumption experien
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REFERENCES Anderson Eugene W., Forn
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Holbrook Morris B. Consumer Value:
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APPENDIX 1. DESCRIPTION OF THE ITEM
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An Empirical Examination of Retail
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This paper is organized in the foll
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Human and cognitive effort has been
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Seiders, Berry, and Gresham (2000)
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The four dimensions of retail conve
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2000). In-store shoppers receive th
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process resulted in slightly differ
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examine the dimensionality of these
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Seiders, Berry, and Gresham’s (20
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used, and the respondents were all
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Enis BM, Roering KJ. Product classi
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Table 1 Dimensions of Convenience G
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Table 3 Retail Convenience Scale Re
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Table 5 Correlations, Means, and St
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Error! Figure 1 Retail Convenience
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and Novak, 1996; Hammond, McWilliam
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and Hirschman, 1982, p 132). These
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interpretations of, all factors par
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the hedonic aspects of the online s
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satisfaction (Oliver, 1980; Westbro
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H6). It involves performing a multi
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Differences between the “shopping
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(Hypothesis 5) and online shopping
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demonstrates the importance of meas
Page 74 and 75: Dabholkar, Pratibha A. Incorporatin
Page 76 and 77: Mano Haim Elliott Michael T. Smart
Page 78 and 79: Zeithaml V., Parasuraman A. Malhotr
Page 80 and 81: 1. Introduction Like inseparability
Page 82 and 83: specific attributes. Dealing with p
Page 84 and 85: 2.2. Perceived Difficulty of Evalua
Page 86 and 87: and mentally intangible a product/s
Page 88 and 89: 2.4.1. Knowledge and Intangibility
Page 90 and 91: category, we included both generic
Page 92 and 93: goods exhibit higher levels of phys
Page 94 and 95: 5.1. Intangibility: Brand and Gener
Page 96 and 97: greater involvement with the purcha
Page 98 and 99: with generality, may also affect co
Page 100 and 101: Berry LL, Clark T. Four ways to mak
Page 102 and 103: Laroche M, Bergeron J, Goutaland C.
Page 104 and 105: Questionnair es Questionnaire 1 Que
Page 106 and 107: Table 3 Results of factor analysis
Page 108 and 109: Table 4 Summary of results 108
Page 110 and 111: Table 5 Stepwise multiple regressio
Page 112 and 113: Table 8 Stepwise multiple regressio
Page 114 and 115: 114
Page 116 and 117: Intangibility Physical intangibilit
Page 118 and 119: net income of 94% and 119%, respect
Page 120 and 121: this, it is not surprising that eBa
Page 122 and 123: frequently referred to as feedback
Page 126 and 127: The objective of study one was to i
Page 128 and 129: excerpts that were selected and fus
Page 130 and 131: Consumers believed that sellers wit
Page 132 and 133: negative feedback could be me,” a
Page 134 and 135: idder should read the praises too b
Page 136 and 137: first study focused on one class of
Page 138 and 139: Rothkopf, Joydeep Srivastava, Rami
Page 140 and 141: Industrial Economics. 50:3. 337-349
Page 142 and 143: http://www.laxshopper.com/index.htm
Page 144 and 145: 144
Page 146 and 147: Firstly, the consumer is supposed t
Page 148 and 149: For the psycho-sociology of environ
Page 150 and 151: To analyse appropriation strategies
Page 152 and 153: The second strategy is the most ela
Page 154 and 155: From the appropriation perspective
Page 156 and 157: To test these hypotheses we selecte
Page 158 and 159: Glace Glace Chart 4. Spatial config
Page 160 and 161: Chart 5b. Spatial configuration of
Page 162 and 163: No differences between the three di
Page 164 and 165: appropriation strategies adopted by
Page 166 and 167: A matrix of space management can th
Page 168 and 169: Holbrook M.B. (1999), Introduction
Page 170 and 171: Asymmetric Quality Tier Competition
Page 172 and 173: Wisniewski (1989) proposed a theory
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alternatives prior to the choice de
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decrease in tradeoff when L reduces
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As Bronnenberg and Wathieu (1996) u
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Those conceptually based utility fu
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ecent existing research (Sivakumar
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increased by 10% (conceptually the
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REFERENCES Allenby GM. A unified ap
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Table 1. Estimation Results _______
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Q U A L I T a H H’ x b PRICE 190
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MODELING THE IMPACT OF INTERNET ATM
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Eroglu et al (2001) proposed a typo
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playfulness (enjoy visiting Web sit
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H2: When consumers surf the Web, th
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significantly explain attitude towa
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Involvement toward an ad based on v
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usefulness and the resourcefulness
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3.2.2.2. Involvement The final comp
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environmental cues on purchase beha
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6. Test of Hypotheses [Insert table
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Cacioppo, Schumann, 1983; Petty and
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Pelsmacker et al, 1998). ATTI is li
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improvements are brought into navig
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Cho, C.H.: How Advertising Works on
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Liu, C. and Arnett, K.P. Exploring
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Rose, G., Khoo, H. and Straub, D.W.
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Table 1: Results of Confirmatory Fa
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Table 2: Full Structural Model Fit
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EXPB� INV H7b NS 0.080 0.062 0.00
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230
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MAPPING RETAILING ENTREPRENEUR DECI
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Attempts to use a framework to find
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attempts resulting in failure are n
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included in this sentence would be
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Detailed causal maps are needed in
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Start-up. Details of the stream of
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more successful when they avoid big
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Axelrod, Robert (1976), "The Cognit
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1. Brian Shore starts several + 2.
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+ 1. B.S. ‘Maximizes use of fryin
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degree of importance consumers plac
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initial use of the word “convenie
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In the decision-making process, tim
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at home 24 hr/7 days a week (Hofack
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Figure 1 about here ---------------
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the organization and design of the
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ehavior courses participated as bot
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convenience is different for the tw
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should seek to establish a similar
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obtained a small sample size of onl
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Dunn DT, Thomas CA, Lubawski JL. Pi
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Table 1 Dimensions of Convenience G
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Table 3 Retail Convenience Scale Re
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Table 5 Correlations, Means, and St
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Error! Figure 1 Retail Convenience
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Customer-to-customer interaction is
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Second, we need to find out the opt
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esponse to the behavior of other cu
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ewards (Swinyard 1993). A customer
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Values may be defined as beliefs th
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find out the optimal combination of
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Taguchi recommends the use of signa
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epresent higher tolerance of incomp
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estaurant where they can escape inc
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Three significant interaction terms
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McGrath, Mary Ann, Otnes, Cele, (19
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Table…2 Tests of Between-Subjects
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Figure…2 (a) Combination of L4 Ta
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