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Study 1: Sector-specific Antecedents of Retail Brand Equity

Study 1: Sector-specific Antecedents of Retail Brand Equity

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ns

***

*

**

**



.063

.148

.146

.096

.138



.580 ***

.776 ***



R² RBE

R² LOY



.186

.195

.123

.037

.055



.463

.057

-.045

.013

-.012

.511



.364

.382

.240

.072

.108



**

***

*

*

ns



***

ns

ns

ns

ns

***



**

***

**

*

*



.566 ***

.599 ***



.148

.178

.158

.052

.080



.368

.052

-.057

.019

-.017

.528



.280

.337

.299

.099

.152



2 – Fashion retailing

b

β

p



.037

.089

.057

.070

.104



.495

.104

.141

-.031

.005

.299



.125

.298

.190

.236

.347



.643

.706



.027

.056

.087

.109

.141



.359

.065

.216

-.048

.007

.384



.070

.146

.225

.283

.367



***

***



ns

*

**

***

***



***

ns

**

ns

ns

***



ns

**

***

***

***



3 – Electronics retailing

b

β

p



.056

.091

.045

.024

.088



.561

.137

.001

.027

.043

.263



.213

.344

.172

.091

.334



b



ns

**

*

*

***



***

ns

ns

ns

ns

***



ns

***

**

*

***



.623 ***

.718 ***



.044

.065

.075

.034

.124



.440

.098

.001

.040

.061

.343



.128

.189

.219

.101

.361



4 – DIY retailing

β

p



ns

ns

ns

ns

ns



ns

ns

ns

*

ns

ns



ns

ns

ns

ns

ns



1 vs. 2



ns

ns

ns

ns

ns



ns

ns

ns

ns

ns

*



ns

ns

ns

*

ns



ns

ns

ns

*

ns



ns

ns

ns

*

*

*



ns

ns

ns

ns

ns



ns

*

ns

ns

ns



ns

ns

*

ns

ns

*



ns

ns

ns

***

**



*

*

ns

ns

ns



ns

ns

ns

ns

ns

***



ns

ns

ns

ns

***



Difference test between retail sectors

1 vs. 3

1 vs. 4

2 vs. 3

2 vs. 4



ns

ns

ns

*

ns



ns

ns

*

ns

ns

ns



ns

ns

ns

***

ns



3 vs. 4



Rival model I - Direct and indirect effects of retail attributes on intentional loyalty



Own creation.



Table E-1:



Source:



Covariates

Gender

.109

.056 ns

.037

.021 ns

-.012

-.006 ns

.026

.015

ns

ns

ns

ns

ns

ns

ns

Age

-.039

-.066 *

.007

.013 ns

-.031

-.060 ns

-.048 -.085

**

ns

ns

ns

ns

*

ns

Familiarity

.269

.243 ***

.080

.052 ns

.021

.012 ns

-.014

.011

ns

***

***

***

ns

ns

ns

Structural model fit: CFI .915; TLI .906; RMSEA .055; SRMR .067; F²(1496) = 4088.006.

Note: ASS = Assortment; PRI = Price; LAY = Layout; COM = Communication; SER = Service; RBE = Retail brand equity; LOY = Intentional loyalty; b = unstandardized coefficient; β = standardized coefficients.

*** p < .001; ** p < .01; * p < .05; ns = not significant.



***

**

ns

*

*

***



.429

.134

.053

-.018

-.126

.558



ASS → LOY

.489

PRI → LOY

.148

LAY → LOY

.046

COM → LOY

-.076

SER → LOY

-.099

RBE → LOY

.492

Indirect effects via RBE

ASS → LOY

.071

PRI → LOY

.163

LAY → LOY

.126

COM → LOY

.067

SER → LOY

.109



ns

***

*

**

***



.112

.264

.262

.171

.247



1 – Grocery retailing

b

β

p



.145

.333

.257

.137

.222



(N = 2112)

Effects

Direct effects

ASS → RBE

PRI → RBE

LAY → RBE

COM → RBE

SER → RBE



158

Appendix



.135

.061

.137

.045

.074



.112

.051

.112

.035

.052

.069



.067

.038

.072

.025

.040



Direct effects

ASS → RBE

PRI → RBE

LAY → RBE

COM → RBE

SER → RBE



ASS → LOY

PRI → LOY

LAY → LOY

COM → LOY

SER → LOY

RBE → LOY



Indirect effects via RBE

ASS → LOY

PRI → LOY

LAY → LOY

COM → LOY

SER → LOY



.071

.163

.126

.067

.109



.489

.148

.046

-.076

-.099

.492



.145

.333

.257

.137

.222



-.038

.108

.018

.030

.047



.332

.062

-.152

-134

-.187

.385



-.077

.236

.037

.064

.098



.184

.232

.249

.112

.176



.697

.228

.216

-.021

-.015

.610



.373

.434

.487

212

.342



ns

***

*

**

**



***

**

ns

*

*

***



ns

***

*

**

***



1 – Grocery retailing

b Lower Upper p



.079

.050

.066

.019

.039



.463

.057

-.045

.013

-.012

.060



.141

.063

.115

.033

.070



S.E.



.186

.195

.123

.037

.055



.095

.144

.070

.102

.033

.511



.364

.382

.240

.072

.108



.071

.124

.032

.007

-.004



.243

-.060

-.220

-.043

-.116

.359



.147

.289

.066

.014

.009



.325

.287

.243

.069

.124



.711

.171

.115

.067

.080

.672



.608

.495

.436

.123

.222



**

***

*

*

ns



***

ns

ns

ns

ns

***



**

***

**

*

*



2 – Fashion retailing

b Lower Upper p



.035

.041

.024

.021

.028



.098

.096

.048

.032

.047

.069



.113

.109

.062

.039

.045



S.E.



.037

.089

.057

.070

.104



.495

.104

.141

-.031

.005

.299



.125

.298

.190

.236

.347



-.022

.033

.026

.039

.061



.347

-.059

.069

-.087

-.076

.188



-.069

.130

.101

.174

.272



.089

.166

.103

.108

.152



.667

.255

.223

.019

.078

.412



.297

.488

.303

.303

.418



ns

*

**

***

***



***

ns

**

ns

ns

***



ns

**

***

***

***



3 – Electronics retailing

b Lower Upper p



.038

.037

.023

.024

.088



.118

.080

.048

.032

.040

.061



.146

.105

.068

.043

.049



S.E.



.056

.091

.045

.024

.088



.561

.137

.001

.027

.043

.263



.213

.344

.172

.091

.334



-.007

.037

.014

.005

.049



.389

.009

-.079

-.025

-.025

.162



-.024

.174

.069

.020

.255



.118

.156

.087

.045

.131



778

.270

.075

.082

.108

.367



.452

.524

.291

.162

.415



ns

**

*

*

***



***

ns

ns

ns

ns

***



ns

***

**

*

***



4 – DIY retailing

b Lower Upper p



Rival model I – Test for direct and indirect effects using bootstrapping



Own creation.



Table E-2:



Source:



Covariates

.061 .109 -.010 .209 ns

.065 .037 -.072 .144 ns

.063 -.012 -.115 .091 ns

.057 .026 -.068 .120 ns

Gender

.021 -.039 -.073 -.005 *

.020 .007 -.026 .041 ns

.018 -.031 -.061 .002 ns

.018 -.048 -.077 -.019 **

Age

.039 .269 .205 .334 ***

.057 .080 -.012 .174 ns

.063 .021 -.083 .125 ns

.043 -.014 -.084 .056 ns

Familiarity

Note: ASS = Assortment. PRI = Price; LAY = Layout; COM = Communication; SER = Service; RBE = Retail brand equity; LOY = Intentional loyalty; S.E. = Standard error; b = Unstandardized coefficients;

Lower: Lower limit of confidence interval; Upper: Upper limit of confidence interval; 95% confidence interval limits are shown; bootstrap samples = 5.000.

*** p < .001; ** p < .01; * p < .05; ns = not significant:



S.E.



Effects



Appendix

159



1 – Grocery retailing

b

β

p

.593

.819 ***

.292

.347 ***

.771

.789 ***

.738

.558 ***

.822

.698 ***

.808

.603 ***

.223

.193 ***

.207

.208 **

-.038 -.051 ns

-.027 -.033 ns

.754 ***



2 – Fashion retailing

b

β

p

.807

.873 ***

.013

.013 ns

1.047 .858 ***

.478

.301 ***

1.328 .796 ***

.743

.591 ***

.219

.193 ***

.102

.107 ns

.041

.056 ns

.017

.025 ns

.545 ***



3 – Electronics retailing

b

β

p

.369

.639 ***

.270

.543 ***

.697

.724 ***

.657

.539 ***

.700

.652 ***

.546

.405 ***

.236

.151 **

.263

.325 ***

.031

.049 ns

.110

.151 **

.674 ***

b

.481

.369

.794

.506

.806

.633

.257

.088

.041

.110



4 – DIY retailing

β

p

.772 ***

.646 ***

.754 ***

.441 ***

.722 ***

.508 ***

.189 ***

.119 *

.061 ns

.158 **

.685 ***

1 vs. 2

**

***

**

**

***

ns

ns

ns

ns

ns



Difference test between retail sectors

1 vs. 3

1 vs. 4

2 vs. 3

2 vs. 4

***

*

***

***

ns

ns

***

***

ns

ns

***

**

ns

**

ns

ns

ns

ns

***

***

*

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

ns

*

ns

ns

*

*

ns

ns

3 vs. 4

**

**

ns

*

ns

ns

ns

**

ns

ns



Rival model II – Effects of retail brand equity on intentional loyalty via retail attributes



Own creation.



Table E-3:



Source:



Covariates

Gender

.135

.066 *

.056

.032 ns

.010

.006 ns

.017

.010 ns

ns

ns

ns

ns

ns

ns

Age

-.036 -.058 ns

-.015 -.040 ns

-.029

-.055 ns

-.032 -.058 ns

ns

ns

ns

ns

ns

ns

Familiarity

.281

.244 ***

.068

.044 ns

.039

.023 ns

-.019 -.015 ns

**

**

***

ns

ns

ns

Structural model fit: CFI .898; TLI .884; RMSEA .061; SRMR .068; F²(1528) = 4570.899.

Note: ASS = Assortment; PRI = Price; LAY = Layout; COM = Communication; SER = Service; RBE = Retail brand equity; LOY = Intentional loyalty; b = unstandardized coefficient; β = standardized coefficients.

*** p < .001; ** p < .01; * p < .05; ns = not significant.



(N = 2112)

Effects

RBE → ASS

RBE → PRI

RBE → LAY

RBE → COM

RBE → SER

ASS → LOY

PRI → LOY

LAY → LOY

COM → LOY

SER → LOY

R² LOY



160

Appendix



Appendix



2.



161



Study 2: Reciprocity between Perceived Value and Retail Brand

Equity



2.1.



Item Parceling for the Perceived Value Scale



Rather than using four latent constructs that represent the dimensions of perceived value, we used one item for each dimension, and this method yielded

one latent construct with four items. The item parceling was performed by averaging the item scores (Bandalos 2002) for each dimension of perceived value. Therefore, prior to testing the overall measurement model in conjunction

with perceived value in a confirmatory factor analysis using parcels, we tested

the original measurement scale of perceived value (i.e., the four dimensions)

for reliability and validity (see Table E-4 to Table E-9) for all of our six models.



Dimension Item

Fashion sector

QV1

QV2

Quality

QV3

value

QV4a

QV5a

QV6

PV1

Price

PV2

value

PV3

PV4

SV1

Social

SV2

value

SV3

SV4a

EV1

EV2a

Emotional

EV3

value

EV4

EV5a

Grocery sector

QV1

QV2

Quality

QV3

value

QV4a

QV5a

QV6



FL



.856

.787

.894

.666

.896

.904

.866

.771

.846

.920

.885

.936

.936

.883

-



.673

.750

.901

.557



MV/Std.



5.6/1.2

5.3/1.3

5.4/1.3

5.5/1.3

4.0/1.9

5.1/1.5

5.4/1.2

5.4/1.2

4.9/1.5

5.5/1.3

4.4/1.3

4.2/1.3

3.8/1.6

5.5/1.4

5.7/1.2

4.9/1.8

5.7/1.1

5.7/1.2

4.7/1.7



5.6/1.2

4.8/1.5

5.1/1.3

5.9/1.3

5.8/1.5

5.4/1.4



.725



.732



.703



.787



.719



.614

.645

.740

.517



.701

.604

.746

.477

.790

.802

.755

.630

.668

.806

.734

.846

.846

.751

-



.807



.906



.855



.879



.807



Time point 1

KMO ItTC

α



.815



.909



.864



.879



.817



CR



.658

.816

.872

.526



.805

.714

.895

.514

.896

.917

.776

.630

.754

.909

.811

.923

.912

.800

-



λ



5.5/1.2

4.9/1.4

5.1/1.3

5.9/1.1

5.8/1.3

5.4/1.3



5.6/1.1

5.3/1.2

5.4/1.2

5.4/1.3

4.0/1.9

5.2/1.4

5.5/1.1

5.4/1.2

5.2/1.3

5.5/1.2

4.6/1.2

4.4/1.3

4.0/1.6

5.6/1.3

5.7/1.1

5.1/1.6

5.7/1.1

5.7/1.2

4.8/1.7

.611

.775

.925

.486



.835

.744

.864

.647

.844

.878

.847

.757

.856

.928

.878

.888

.907

.877

-



MV/Std. FL



.663



.734



.696



.768



.647



.582

.628

.727

.471



.659

.536

.674

.443

.704

.751

.717

.600

.682

.822

.727

.743

.780

.726

-



.790



.868



.858



.850



.768



Time point 2

KMO ItTC

α



.770



.869



.868



.854



.781



CR



.596

.819

.894

.554



.556

.673

.835

.510

.809

.869

.766

.629

.777

.926

.790

.843

.838

.812

-



λ



5.5/1.1

5.0/1.3

5.2/1.2

5.8/1.1

5.7/1.3

5.5/1.2



5.6/1.1

5.2/1.2

5.4/1.2

5.4/1.3

4.2/1.8

5.2/1.4

5.5/1.1

5.4/1.2

5.1/1.3

5.4/1.2

4.7/1.2

4.4/1.3

4.2/1.5

5.5/1.2

5.7/1.1

5.0/1.5

5.7/1.1

5.6/1.2

4.8/1.6



MV/Std.



.588

.696

.802

.434



.821

.749

.866

.644

.842

.857

.869

.719

.861

.930

.859

.909

.891

.891

-



FL



.664



.741



.682



.785



.688



.878



.854



.838



.763



.878



.864



.843



.775



CR

.736

.669

.843

.503

.783

.819

.826

.598

.787

.923

.771

.874

.818

.831

-



λ



.561

.566

.540

.775

.607

.786

.737 .740

.415

.506

Table to be continued



.641

.531

.681

.435

.695

.711

.743

.550

.686

.822

.693

.788

.753

.753

-



Time point 3

KMO ItTC α



162

Appendix



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Study 1: Sector-specific Antecedents of Retail Brand Equity

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