Quality, value, satisfaction, trust, a

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H6). It involves performing a multi-group analysis with each sub-sample of the moderating variables (gender and shopping orientation). Two models are compared: one model in which the parameters are allowed to vary freely across groups (general model) and another model in which parameters are constrained to be equal across groups (restricted model). If there is a significant difference between the groups, the general model should fit better (χ²) than the restricted model. It is necessary to calculate the difference between the χ² of the general model and the χ² of the restricted model (dχ²). A significant dχ² suggest that the relationships are different between the groups and is consistent with moderation. Research results Confirmatory factor analysis (CFA) was conducted on all measures: online shopping values and consumer satisfaction with the electronic catalog visit. Two items had high modification indices and were dropped from the analysis. Another CFA was conducted. Fit indices are correct for each scenario: χ²=42.4. RMSEA=0.049, RMR=0.078, GFI=0.972, AGFI=0.947, TLI=0.985, CFI=0.990 for the “shopping as recreation” scenario and χ²=38.5, RMSEA=0.043, RMR=0.109, GFI=0.974, AGFI=0.950, TLI=0.988, CFI=0.992 for the “shopping as work” scenario. Correlations between constructs were examined to test discriminant validity. Some variables such as satisfaction and online shopping hedonic value are highly correlated in the “shopping as recreation” condition (see table 1). Table 1 – Correlation between variables in the “shopping as recreation” scenario Satisfaction Hedonic value Utilitarian value Satisfaction 1 0.828 0.660 Hedonic value 0.828 1 0.454 Utilitarian value 0.660 0.454 1 66
This pattern is consistent with our research hypotheses. Online shopping hedonic value was predicted to have a relatively stronger effect on consumer satisfaction in this condition. A procedure used by Dabholkar and Bagozzi (2002) which involves conducting a simple CFA with the two constructs as one was applied in this scenario to assess the degree of discriminability in light of the high correlations. In each case, the CFA with two constructs has better fit indices than the CFA with two constructs as one. Coefficient alphas are correct for each scale: 0.832 for online shopping hedonic value, 0.878 for online shopping utilitarian value and 0.907 for consumer satisfaction. Manipulation check A single item was used to assess manipulation success: : “How did you consider the visit before visiting the web site: as work � as recreation”. A paired sample t-test was realized to compare consumer responses to this question for each scenario. Results show a significant difference (t=4.714, p=0.000) between the “shopping as recreation” scenario (4.608) and for the “shopping as work” scenario (4.232). Moderating impact of shopping orientation Model fit is satisfying: χ²=80.862, RMSEA=0.033, RMR=0.095, GFI=0.973, AGFI=0.949, TLI=0.987, CFI=0.991. In the “shopping as recreation” condition (see figure 3), consumer satisfaction with the electronic catalog visit is determined mainly by online shopping hedonic value (0.666). The correlation between online shopping hedonic value and online shopping utilitarian value is 0.454. In the “shopping as work” condition (see figure 3), consumer satisfaction with the electronic catalog is determined by both visit hedonic (0.473) and utilitarian (0.469) value. The correlation between online shopping hedonic value and online shopping utilitarian value is 0.266 67
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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
Page 15 and 16: we observed that the least correlat
Page 17 and 18: outside of the consumption experien
Page 19 and 20: REFERENCES Anderson Eugene W., Forn
Page 21 and 22: Holbrook Morris B. Consumer Value:
Page 23 and 24: APPENDIX 1. DESCRIPTION OF THE ITEM
Page 25 and 26: An Empirical Examination of Retail
Page 27 and 28: This paper is organized in the foll
Page 29 and 30: Human and cognitive effort has been
Page 31 and 32: Seiders, Berry, and Gresham (2000)
Page 33 and 34: The four dimensions of retail conve
Page 35 and 36: 2000). In-store shoppers receive th
Page 37 and 38: process resulted in slightly differ
Page 39 and 40: examine the dimensionality of these
Page 41 and 42: Seiders, Berry, and Gresham’s (20
Page 43 and 44: used, and the respondents were all
Page 45 and 46: Enis BM, Roering KJ. Product classi
Page 47 and 48: Table 1 Dimensions of Convenience G
Page 49 and 50: Table 3 Retail Convenience Scale Re
Page 51 and 52: Table 5 Correlations, Means, and St
Page 53: Error! Figure 1 Retail Convenience
Page 56 and 57: and Novak, 1996; Hammond, McWilliam
Page 58 and 59: and Hirschman, 1982, p 132). These
Page 60 and 61: interpretations of, all factors par
Page 62 and 63: the hedonic aspects of the online s
Page 64 and 65: satisfaction (Oliver, 1980; Westbro
Page 68 and 69: Differences between the “shopping
Page 70 and 71: (Hypothesis 5) and online shopping
Page 72 and 73: 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
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Intangibility Physical intangibilit
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net income of 94% and 119%, respect
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this, it is not surprising that eBa
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frequently referred to as feedback
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An auction participants’ feedback
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The objective of study one was to i
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excerpts that were selected and fus
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Consumers believed that sellers wit
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negative feedback could be me,” a
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idder should read the praises too b
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first study focused on one class of
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Rothkopf, Joydeep Srivastava, Rami
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Industrial Economics. 50:3. 337-349
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http://www.laxshopper.com/index.htm
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144
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Firstly, the consumer is supposed t
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For the psycho-sociology of environ
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To analyse appropriation strategies
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The second strategy is the most ela
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From the appropriation perspective
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To test these hypotheses we selecte
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Glace Glace Chart 4. Spatial config
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Chart 5b. Spatial configuration of
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No differences between the three di
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appropriation strategies adopted by
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A matrix of space management can th
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Holbrook M.B. (1999), Introduction
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Asymmetric Quality Tier Competition
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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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