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convenience is different for the two different types of shopping formats. Evidence of discriminant validity is provided by the fact that these items did not want to load on other components with which they were not supposed to be associated. Further, evidence of convergent validity is provided by the high loadings of each item on their respective component. A more rigorous examination of the validity of these scales was conducted with confirmatory factor analysis using LISREL 8.3 for Windows. As can be seen in Tables 3 and 4, the statistically significant λ x parameter estimates provide evidence of convergent validity. Additionally, the majority of the squared multiple correlations (SMCs), defined as the percentage of variance in each item that is explained by the latent construct of interest, are above 50%, indicating that each item performed well in capturing its construct of interest. Modification indices associated with λ x and Θ δ reveal some problems with discriminant validity. Specifically, there were seven modification indices in the λ x matrix for in-store shoppers, indicating that items search2, help3, possess1, and possess2 wanted to be associated with other dimensions of convenience. Additionally, there were 13 modification indices in Θ δ that indicate some error terms wanted to correlate. These changes were not incorporated in the model, as theoretically it does not make sense to do so. These problematic modification indices explain the poor overall fit: chi-square=498.08, 198 df, p=0.00; RMSEA=0.08; RMR=0.06; GFI=0.85. Problematic modification indices also surfaced in the measurement model for online shoppers. Three items (access2, possess2, and possess4) wanted to be associated with other constructs, while 6 error terms wanted to correlate. Again, these changes were not implemented, resulting in poor overall model fit: chi-square=206.34, 97 df, p=0.00; RMSEA=0.13; RMR=0.09; GFI=0.71. The overall fit does substantially improve if paths are freed as suggested by the modification indices. Therefore, confirmatory factor analysis results are mixed; there is 266
strong evidence of reliability and convergent validity, but discriminant validity must be improved in further scale refinement attempts. For Hypotheses 2 through 4, analysis of variance (ANOVA) was performed in order to compare the mean scale scores for online and in-store shoppers. Hypothesis 2 states that online shoppers benefit more from access convenience than in-store shoppers. A comparison of scale means for these two groups yields an F statistic of 37.59 (p=0.000). Access convenience is more beneficial for online shoppers (scale mean=6.55) than in-store shoppers (scale mean=5.65), providing evidence of support for H2. Hypothesis 3 states that online shoppers benefit more from search convenience than do in-store shoppers; ANOVA here produces an F statistic of 8.57 (p=0.004). The scale mean of 5.88 for in-store shoppers is significantly less than the scale mean of 6.26 for online shoppers; thus, there is evidence of support for H3. Finally, hypothesis 4 predicts that in-store shoppers benefit from possession convenience more than online shoppers. The F statistic from this ANOVA is significant (F=11.07, p=0.001); however, the scale means indicate that the reverse is true. The possession scale mean for in-store shoppers is 5.60, while the scale mean for online shoppers is 6.23. This finding is quite counter-intuitive; possible reasons for this result are provided in the next section. Discussion This study provides an important contribution to the marketing convenience literature because it is the first of its kind to utilize the different dimensions of retail convenience to better understand customer needs. The support for Hypothesis 1 suggests that the dimensions of convenience are different for the two different types of shopping formats. The expansion of Seiders, Berry, and Gresham’s (2000) four dimensions of retail convenience to include “assisted search” is warranted. The five-component solution resulting from the principal components analysis is evidence of the existence of this newly proposed dimension. Further work in this area 267
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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
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Dabholkar, Pratibha A. Incorporatin
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Mano Haim Elliott Michael T. Smart
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Zeithaml V., Parasuraman A. Malhotr
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1. Introduction Like inseparability
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specific attributes. Dealing with p
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2.2. Perceived Difficulty of Evalua
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and mentally intangible a product/s
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2.4.1. Knowledge and Intangibility
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category, we included both generic
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goods exhibit higher levels of phys
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5.1. Intangibility: Brand and Gener
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greater involvement with the purcha
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with generality, may also affect co
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Berry LL, Clark T. Four ways to mak
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Laroche M, Bergeron J, Goutaland C.
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Questionnair es Questionnaire 1 Que
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Table 3 Results of factor analysis
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Table 4 Summary of results 108
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Table 5 Stepwise multiple regressio
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Table 8 Stepwise multiple regressio
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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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Page 218 and 219: Cho, C.H.: How Advertising Works on
Page 220 and 221: Liu, C. and Arnett, K.P. Exploring
Page 222 and 223: Rose, G., Khoo, H. and Straub, D.W.
Page 224 and 225: Table 1: Results of Confirmatory Fa
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Page 228 and 229: EXPB� INV H7b NS 0.080 0.062 0.00
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Page 232 and 233: MAPPING RETAILING ENTREPRENEUR DECI
Page 234 and 235: Attempts to use a framework to find
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Page 240 and 241: Detailed causal maps are needed in
Page 242 and 243: Start-up. Details of the stream of
Page 244 and 245: more successful when they avoid big
Page 246 and 247: Axelrod, Robert (1976), "The Cognit
Page 248 and 249: 1. Brian Shore starts several + 2.
Page 250 and 251: + 1. B.S. ‘Maximizes use of fryin
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Page 256 and 257: In the decision-making process, tim
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Page 260 and 261: Figure 1 about here ---------------
Page 262 and 263: the organization and design of the
Page 264 and 265: ehavior courses participated as bot
Page 268 and 269: should seek to establish a similar
Page 270 and 271: obtained a small sample size of onl
Page 272 and 273: Dunn DT, Thomas CA, Lubawski JL. Pi
Page 274 and 275: Table 1 Dimensions of Convenience G
Page 276 and 277: Table 3 Retail Convenience Scale Re
Page 278 and 279: Table 5 Correlations, Means, and St
Page 280 and 281: Error! Figure 1 Retail Convenience
Page 282 and 283: Customer-to-customer interaction is
Page 284 and 285: Second, we need to find out the opt
Page 286 and 287: esponse to the behavior of other cu
Page 288 and 289: ewards (Swinyard 1993). A customer
Page 290 and 291: Values may be defined as beliefs th
Page 292 and 293: find out the optimal combination of
Page 294 and 295: Taguchi recommends the use of signa
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Page 300 and 301: Three significant interaction terms
Page 302 and 303: McGrath, Mary Ann, Otnes, Cele, (19
Page 304 and 305: Table…2 Tests of Between-Subjects
Page 306 and 307: Figure…2 (a) Combination of L4 Ta
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