S
A

Journal of Industrial P
sychology

http://www.sajip.co.za SA Tydskrif vir BedryfsielkundeVol. 34 No. 1 pp. 59 - 68

Theoretical Research

Store Image: Scale development
part 2

ABSTRACT
The aims of this article (the second in a three-part series) are threefold, namely to (1) develop a
scale for the measurement of the perceived importance of store image dimensions , (2) purify the
developed scale to illustrate acceptable reliability and (3) develop and refine this scale for practical
implementation in the apparel retail environment. A four-phase approach was documented for scale
development. The provisional scale was purified and tested by means of two pilot studies and the
data was subjected to Cronbach alpha and confirmatory factor analysis (CFA). A revised model of
apparel store image was proposed. Model fit results indicated that fit can still be improved. Results
culminated in a 55-item Apparel Store Image Scale that showed good reliability.

Keywords: store image, dimensions, apparel, conceptual model, multi-dimensional

Part 1 of this series of articles delineated the domain of store
image and described the dimensions and subdimensions. Two
models were proposed and a definition of store image was
formulated to serve as point of departure for the following
phase in scale development. The importance of this first
phase in scale development cannot be overstated, since it is a
prerequisite for determining the validity of a measurement
scale and, more specifically, content validity (Netemeyer,
Bearden & Sharma, 2003).

The development of measurement scales with desirable
reliability and validity properties is a critical element in the
evolution of a fundamental body of knowledge in a specific
field of study. Churchill (1979) proposed a framework that is
often employed as point of departure in measurement scale
development (Blankson & Kalafatis, 2004; Grace, 2005; Li,
Edwards & Lee, 2002; Parasuraman, Zeithaml & Berry, 1988;
Shimp & Sharma, 1987). Based on Churchill’s framework, as
well as drawing from recommendations made by DeVellis
(2003), Hair, Black, Babin, Anderson and Tatham (2006) and
Netemeyer et al. (2003), four broad phases were identified in the
scale development process (see Figure 1).

Part 1 of this series of articles discussed Phase 1. Phases 2 and
3 are reported in this paper while Phase 4 will be discussed in
Part 3 of this series.

The aims of this paper are threefold, namely to
• develop a scale for the measurement of the perceived

importance of the apparel store image dimensions;
• purify the developed scale to illustrate acceptable

reliability; and
• develop and refine this scale for practical implementation

in the apparel retail environment.

Generation and judging of measurement items (Phase 2)

The main objective of the second phase is the generation of
measurement items (based on the work reported in the first
article) that adequately represent the store image construct and
domain, as well as the consequent judging of measurement
items, as recommended by Churchill (1979), DeVellis (2003),
Hair et al. (2006) and Netemeyer et al. (2003). The appropriate

operationalisation of a construct is imperative for valid
empirical results and interpretation (Little, Lindenberger &
Nesselroade, 1999; MacCallum & Austin, 2000). Therefore, the
primary focus of this phase, in conjunction with the first phase,
was to establish content and face validity of the measurement
instrument (DeVellis, 2003; Netemeyer et al., 2003). This was
accomplished through initial item pool generation using
existing literature and review by both expert and sample
population judges. The domain sampling model was used as
a basis for generating measurement items, since consequent
reliability assessment reflects this model. Therefore, items
were generated systematically to sample all content areas of
store image as defined by the model.

Generation of measurement items

Scale development studies frequently report item generation
from a review of the literature (Bearden, 2001; Dabholkar,
Thorpe & Rentz, 1995; Grace, 2005; Lastovicka, Bettencourt,
Hughner & Kuntze, 1999; Li et al., 2002; Lichtenstein, Ridgeway
& Netemeyer, 1993; Little et al., 1999; Terblanché & Boshoff, 2004).
Some reported extensive qualitative procedures to generate
items used in empirical studies on store image (Amirani &
Gates, 1993; Birtwistle & Siddiqui, 1995; Janse van Noordwyk,
2002; Thompson & Chen, 1998; Zimmer & Golden, 1988). For
the purposes of this study, it was decided to rely heavily on
extant literature for generating the initial item pool. The
researcher, expert judges and sample population judges added
a few items.

A composite list of attributes, previously employed as items in
store image research, was compiled based on the model of store
image. The inclusion of items was based on criteria reported
in the reviewed store image studies, as well as guidelines from
scale development literature. These criteria are summarised in
Table 1.

Items generated from qualitative research were also reviewed
(Birtwistle & Siddiqui, 1995; Thompson & Chen, 1998), as well as
items with previous empirical support in store image literature
reported by Lindquist (1974–1975) and Martineau (1958). Items
that were not generated from the review of literature but
deemed relevant by the researcher were also included.

RONEL DU PREEZ
ELIZABETH VISSER

HESTER JANSE VAN NOORDWYK
Department of Industrial Psychology

Stellenbosch University
South Africa

Correspondence to: Ronel du Preez
e-mail: rdp@sun.ac.za

Theoretical Research Du Preez, Visser, Janse van Noordwyk

Vol. 34 No. 2 pp. 59 - 68SA Tydskrif vir Bedryfsielkunde

S
A

J
ou

rn
al

o
f I

nd
us

tr
ia

l P
sy

ch
ol

og
y

http://www.sajip.co.za60

The initial generation of items resulted in a composite list of 371
items. This was a cause for concern, but it was decided to retain
the item pool based on the following three considerations:
Firstly, in the early stage of the scale development process, it
was preferable to be over-inclusive. Secondly, the internal
consistency of a scale is a function of how strongly items
correlate with each other. At this stage of scale development,
however, the correlation between items was unknown. Lastly,
the scale was submitted for judging of the measurement
items, which would assist the process of refining the scale, as
recommended by DeVellis (2003) and Netemeyer et al. (2003).

Each item from the composite list was rewritten into a declarative
statement to which respondents have to indicate varying
degrees of endorsement of the statement (Likert-type scale).
Subsequently, each item was revised for clarity, ambiguity and
double-barrel statements. This procedure was in accordance
with recommendations in the literature (Brace, 2004; Bradburn,
Sudman & Wansink, 2004; Churchill & Iacobucci, 2005; DeVellis,
2003; Frazer & Lawley, 2000; Kerlinger & Lee, 2000; Netemeyer
et al., 2003; Oppenheim, 1992; Synodinos, 2003).

The 371 items were grouped within each dimension and
subdimension, as guided by the model of apparel store image
(see Figure 3, Part 1). The final item pool was reviewed to ensure
that a sufficient number of items were included to adequately
measure each dimension and subdimension, namely eight to
ten items for each dimension as recommended by Netemeyer
et al. (2003, p.147).

Judging of measurement items

Judging of the generated items served three distinct purposes,
namely to ensure relevancy of the items to measure perceptions
of the importance of store image, evaluate items for clarity
and conciseness and identify possible areas of the store image
domain that were not previously captured (DeVellis, 2003).
Two experts in the fields of consumer psychology and apparel
consumer behaviour conducted the first expert review. It
comprised an evaluation of the initial measurement items
(including format and layout of the scale) and the proposed
model of store image.

The store image scale consisted of three sections. Section A
covered the store image items categorised under the various
store image dimensions. In Section B, respondents were
requested to rate the individual dimensions on the same five-
point response format. A demographic section, Section C

Proposed conceptual theoretical model of store
image and related consumer behaviour variables

Expert judging

Generation of measurement items

Judging of measurement items

Expert judging Sample population judging

Pilot study 1 Sample population, sample
selection and sample description

Data gathering

Research method

Sample population and sample description

Sample selection

Measurement instrument

Fieldworker training

Data gathering

Statistical analysis

Proposed model of the underlying
structure of store image

Statistical analysis

Sample population, sample
selection and sample description

Statistical analysis

Pilot study 2

Phase 1: Construction of
definition and domain

Phase 2: generation and
judging of measurement

items

Phase 3: Purification of the
store image scale

Phase 4: Assessment of
store image scale –

reliability and validity

Literature review

Figure 1
Scale development process

(adapted from Schlechter, 2005, p. 148)

CriTeriA FOr iTeM iNCLuSiON

Coefficient alpha ≥ 0.7

Factor analysis Eigen value > 1
Factor loadings ≥ 0.4
Coefficient alpha ≥ 0.7

Mean importance scores Higher than average of
given scale

Number of citations Summed number higher than 90%

TABLe 1
Criteria for item inclusion from reviewed literature

Store Image: Part 2 Theoretical Research

S
A

Journal of Industrial P
sychology

http://www.sajip.co.za SA Tydskrif vir BedryfsielkundeVol. 34 No. 2 pp. 59 - 68

(e.g. gender, age, population group and home language), was
included at the end of the measurement scale to avoid alienating
respondents by asking for personal information at the outset
of the measurement scale (Synodinos, 2003). A cover letter
was compiled to convey important information regarding the
research and completion of the scale to the respondents.

During this review, the experts gave consideration to the sample
population of interest, namely the South African consumer.
Within the South African context, the literacy and educational
levels of consumers may vary significantly. English is not the
home language of all respondents and a more refined scale could
potentially result in inaccurate information given in response.
This review culminated in a reduced item pool of 284 items and
the retainment of the five-point Likert-type scale.

A panel of experts from different fields of study (apparel
consumer behaviour, consumer psychology and statistics)
undertook the second expert review. They were familiar with
the research problem and objectives as well as the proposed
store image model and scale. Based on their feedback, 57 items
were eliminated and a further three items were generated,
resulting in 230 items. Changes were made to the response
format and rating scale. A six-point scale was used instead of
the original five-point scale. Only the first and fifth point were
anchored, namely 1 = unimportant and 5 = very important due
to difficulties experienced with the inadequate description
of the five anchor points. A sixth point was added to allow
respondents a neutral response, namely 6 = unable to rate,
and a visual presentation was added to the rating scale to
aid responses, as recommended in the literature (Churchill &
Iacobucci, 2005; DeVellis, 2003; Netemeyer et al., 2003; Nunnally,
1978; Synodinos, 2003). The cover letter was adapted to reflect
these changes.

Sample population judging serves the purpose of assessing
the practical implementation of the scale with respondents
similar to those employed in the administration of the scale
in the subsequent phases of the scale development process.
Therefore, two student group sessions were conducted. Based
on the feedback of these group sessions, two more items were
added to the scale (resulting in a scale consisting of 232 items)
and smaller technical changes were made.

Purification of the measurement scale (phase 3)

Concerns regarding the length of the measurement scale had to
be addressed in this phase. However, reducing the scale length

ABSOLuTe FiT MeASureS

Minimum Fit Function of
Chi-Square

A non-significant result indicates model fit

Normal Theory Weighted
Least Chi-Square

A non-significant result indicates model fit

Root Mean Square Error
of Approx. (RMSEA)

Values between 0.08 or below indicate acceptable fit
Values below 0.05 indicate good fit
Values below 0.01 indicate outstanding fit

Standardised Root Mean
Residual (RMR)

Lower values indicate better fit with values below
0.05 indicating good fit

Goodness of Fit Index
(GFI)

Higher values indicate better fit with values > 0.9
indicating good fit

Adjusted Goodness of Fit
Index (AGFI)

Higher values indicate better fit with value > 0.9
indicating good fit

iNCreMeNTAL FiT MeASureS

Non-Normed Fit Index
(NNFI)

Higher values indicate better fit with values > 0.9
indicating good fit

Comparative Fit Index
(CFI)

Values closer to 1 indicate better fit with values > 0.9
indicating good fit

TABLe 2
Summary of goodness-of-fit-indices*

CONSTruCT DiMeNSiONS SuBDiMeNSiONS
NO. OF
iTeMS

COeFFiCieNT
ALPHA

Store image 232 0.90

Atmosphere 15 0.57

Store interior 11 0.75

Store atmosphere 4 0.50

Convenience 42 0.61

Transportation 3 0.59

Location 11 0.76

Parking 6 0.75

Shopping ease 18 0.82

Store hours 4 0.87

Facilities 41 0.78

Store appearance 7 0.71

Store layout 4 0.76

Fixtures 14 0.84

Fitting rooms 8 0.81

Convenience of
facilities

8 0.77

Institutional 19 0.76

Store reputation 9 0.73

Clientele 10 0.75

Merchandise 28 0.85

Assortment 14 0.86

Style 7 0.79

Price 4 0.63

Quality 3 0.60

Promotion 33 0.81

Advertising 17 0.89

Displays 6 0.82

Sales incentives 10 0.85

Sales
personnel 18 0.56

Appearance 9 0.82

Interaction 9 0.80

Service 36 0.78

In-store service 17 0.86

Payment options 7 0.79

Delivery options 5 0.90

After-sales service 7 0.83

TABLe 3
Reliability - pilot study 1

had to be done in conjunction with reliability, as reliability is a
function of the number of items included in a scale (Churchill
& Iacobucci, 2005; DeVellis, 2003; Netemeyer et al., 2003). The
purification phase included two separate pilot studies.

MeThodoloGy

The methodology for each pilot study will be discussed
followed by a discussion of the results thereof.

Pilot study 1

The aim of the first pilot study was to obtain initial estimates
of reliability as a basis for scale purification, as well as to aid in
optimising scale length. A student sample population (n = 89)
was deemed appropriate, since this study is concerned with
the apparel consumer’s perception of store image. Students
were not considered entirely nonrepresentative, since they
qualify as apparel consumers and form part of apparel market
segments. This phase was concerned with providing evidence
of internal consistency of the store image scale for which the
sample was appropriate in terms of providing accurate results.
Student samples are frequently employed in scale development
research, which further serves to justify the student sample

*Adapted from Schlechter, 2005, p. 148

Theoretical Research Du Preez, Visser, Janse van Noordwyk

Vol. 34 No. 2 pp. 59 - 68SA Tydskrif vir Bedryfsielkunde

S
A

J
ou

rn
al

o
f I

nd
us

tr
ia

l P
sy

ch
ol

og
y

http://www.sajip.co.za62

(Bearden, 2001; Grace, 2005; Li et al., 2002). The sample size
was deemed adequate for this stage of the scale development
process based on recommendations from literature (Blankson
& Kalafatis, 2004; Dhurup, Venter & Oosthuyzen, 2005; Venter
& Dhurup, 2005).

Statistical analysis

Statistica (version 8) was used for the analyses (StatSoft Inc.,
2007). Coefficient alphas, item-total correlations and inter-item
correlations were calculated for all items included within each
subdimension. The cut-off value for coefficient alpha value
was set at 0.7. The acceptable benchmark level for item-total
correlations was set at above 0.3, with reports in the literature
ranging from higher than 0.3 to higher than 0.5. The criterion
for inter-item correlations was set at a range of 0.2–0.5 (Blankson
& Kalafatis, 2004; DeVellis, 2003; Dhurup et al., 2005; Grace, 2005;
Kerlinger & Lee, 2000; Netemeyer et al., 2003; Nunnally, 1978;
Terblanché & Boshoff, 2004). The internal consistency of the
subdimensions within each dimension was considered. Based
on the results, the items in Section A were reduced to 214. No
changes were made to sections B and C or the cover letter of the
questionnaire.

Pilot study 2

The aim of the second pilot study was to provide additional
evidence of scale reliability for scale purification, as well as to
further reduce the scale length. A similar methodology was
employed in the second pilot study. A convenience sample of
students was recruited (n = 176). The 214-item measurement
scale derived from the first pilot study was employed. A split-

CONSTruCT DiMeNSiONS NO. OF iTeMS
COeFFiCieNT
ALPHA

Store image 214 0.90

Atmosphere 11 0.84

Convenience 38 0.93

Facilities 37 0.93

Institutional 17 0.85

Merchandise 26 0.91

Promotion 33 0.94

Sales personnel 8 0.84

Service 44 0.95

TABLe 4
Reliability - pilot study 2 (training data set - 214-item store image scale)

Figure 2
Revised model of apparel store image (after pilot study 1)

sample approach was followed based on a 60:40 ratio, resulting
in a training data set (n = 110) and a test data set (n = 66). This
approach allowed for the purification of the scale based on the
statistical analysis of the training data set, to be cross-checked
by the statistical analysis from the test data set, as recommended
by De Vellis (2003).

However, a scale that was representative of all subdimensions
proposed in the model of apparel store image (refer to Figure 3
in Part 1) was still considered too long. In addition, to perform
confirmatory factor analysis, each individual subdimension had
to be represented by four items to allow for model identification
(Hair et al., 2006). For the 27 identified subdimensions, this
would result in, at least, a 108-item measurement scale, which
would still be considered too long for practical usability.
Therefore, the statistical analysis was only performed on

Store Image: Part 2 Theoretical Research

S
A

Journal of Industrial P
sychology

http://www.sajip.co.za SA Tydskrif vir BedryfsielkundeVol. 34 No. 2 pp. 59 - 68

DiMeNSiONS NO. OF iTeMS iTeMS
FACTOr
LOADiNgS

Atmosphere 6 Item 2 0.639

Item 3 0.647

Item 4 0.718

Item 5 0.685

Item 6 0.726

Item 11 0.565

Convenience 7 Item 12 0.613

Item 19 0.621

Item 22 0.613

Item 32 0.644

Item 38 0.664

Item 41 0.617

Item 46 0.607

Facilities 7 Item 53 0.689

Item 56 0.690

Item 57 0.701

Item 60 0.710

Item 75 0.634

Item 76 0.625

Item 80 0.620

Institutional 6 Item 95 0.649

Item 96 0.691

Item 98 0.673

Item 100 0.642

Item 101 0.698

Item 102 0.628

Merchandise 8 Item 104 0.685

Item 105 0.603

Item 107 0.643

Item 108 0.633

Item 111 0.582

Item 117 0.582

Item 122 0.585

Item 128 0.592

Promotion 8 Item 132 0.634

Item 143 0.603

Item 144 0.658

Item 148 0.667

Item 152 0.673

Item 153 0.644

Item 155 0.622

Item 156 0.613

Sales personnel 5 Item 165 0.800

Item 167 0.658

Item 168 0.817

Item 169 0.708

Item 170 0.713

Service 8 Item 173 0.659

Item 174 0.746

Item 180 0.634

Item 188 0.698

Item 189 0.654

Item 190 0.650

Item 204 0.649

Item 208 0.651

TABLe 5
Factor loadings (55 items) - pilot study 2 (training data set)

Figure 3
Simplified model of apparel store image – pilot study 2 (training data set)

each of the eight broad dimensions associated with the store
image construct. This was deemed acceptable to arrive at a
measurement scale with optimum length whilst maintaining
acceptable reliability.

Exploratory factor analysis (EFA): The training data set was
employed in this statistical analysis procedure. Literature
proposes that EFA and CFA be used in conjunction with one
another (Fabrigar, Wegener, MacCallum & Strahan, 1999;
Gorsuch, 1997). The model of apparel store image eliminated
the need for EFA to establish the dimensionality of store image
(refer to Figure 3 in Part 1). Therefore, the training data set was
submitted to the principal axis factoring procedure and the
analysis was constrained a priori to one factor for the separate
investigation of each dimension. This is in accordance with
previous studies employing this method for scale purification
and optimising scale length (Bearden, 2001; Lastovicka et al.,
1999; Parasuraman et al., 1988), as well as suggestions by
Churchill (1979) to employ EFA as a means to confirm the
number of conceptualised dimensions empirically after initial
item evaluation through coefficient alphas and item-total
correlations.

The cut-off value for factor loadings was set at a minimum of
> 0.5 based on recommendations in the literature (Bearden,
2001; Blankson & Kalafatis, 2002; Grace, 2005; Hair et al., 2006;
Lastovicka et al., 1999; Shrimp & Sharma, 1997; Tabachnick
& Fidell, 2007). The training data set was further analysed
through reliability measures and the criteria as per the previous
pilot study were maintained. The results of all the statistical
analyses were considered concurrently and concluded in a
shortened measurement scale consisting of 55 items (refer to
Appendix 1). A correlation analysis was done between the
214- item and the 55-item measurement scales.

Confirmatory factor analysis (CFA): Consequently, CFA was
done on the test data set, employing the shortened measurement
scale. For the purposes of this phase of the study, each dimension
was submitted to CFA separately to allow for the investigation
of individual items for further scale purification.

The measurement models for each dimension were tested
through CFA using LISREL (version 8.8) (Jöreskog & Sörbom,
2006). The method of estimation was diagonally weighted least
squares. This method was deemed appropriate for studies
employing a Likert-type rating scale (Diamantopoulos &
Sigauw, 2000; Steenkamp & Van Trijp, 1991). The CFA results

provided insight into model fit and evidence on items to be
considered for deletion. Firstly, model fit was assessed through
the examination of a combination of goodness-of-fit (GOF)
measures, i.e. absolute and incremental fit indices. Table 2
provides a summary of these fit indices and also indicates
the acceptable values used as guidelines for assessing GOF
(adapted from Schlechter, 2005, p. 148).

Theoretical Research Du Preez, Visser, Janse van Noordwyk

Vol. 34 No. 2 pp. 59 - 68SA Tydskrif vir Bedryfsielkunde

S
A

J
ou

rn
al

o
f I

nd
us

tr
ia

l P
sy

ch
ol

og
y

http://www.sajip.co.za64

It is critically important to examine parameter estimates in
conjunction with model fit (Kelloway, 1998; MacCallum &
Austin, 2000). Further scale purification was considered by
investigating path estimates and standardised residuals to
identify individual scale items for possible deletion. The cut-
off value for completely standardised loadings was set at a
minimum of > 0.5. The cut-off values for variance extracted
(VE) and construct reliability (CR) were set at > 0.5 and > 0.7
respectively. Those items with standardised residuals of
less than |2.5| were not considered for deletion. Where
standardised residuals were between |2.5| and |4|, items were
investigated but retained if there was no additional indication
that these items should be deleted. Items with associated
standardised residuals of higher than |4| were considered for
deletion. These criteria were developed in accordance with
recommendations by Diamantopoulos and Sigauw (2000) and
Hair et al. (2006).

ReSUlTS ANd dISCUSSIoN

Pilot study 1

Respondents (n = 89) were predominantly between 18 and
21 (82%). The majority belonged to the coloured population
group (51%), followed by the black population group, while 56%
indicated English as their home language, followed by isiXhosa
and Afrikaans. Respondents bought clothes when needed or
on a monthly basis, spending approximately R400 per month
on clothing.

An investigation of the coefficient alphas of the dimensions
revealed that Atmosphere (α = 0.57), Convenience (α = 0.61) and
Sales personnel (α = 0.56) fell outside the set criteria of > 0.7.
The subdimensions included in the Sales personnel dimension
had high coefficient alphas and no items were identified
for deletion. When considering the literature review, it is
evident that the two dimensions Sales personnel and Service
overlap with Employee service (Grace & O’Cass, 2005; Koo,
2003), Salespeople service (Kleinhans, 2003), Salesperson/
service (Manolis, Keep, Joyce & Lambert, 1994), Service – Sales
associates attributes (Lee & Johnson, 1997) and Service – Store
associates attributes (Lee & Johnson, 1997). Subsequently, it
was decided to include the Interaction subdimension within
the In-store service subdimension, since it could be justified as
being conceptually related, as per literature recommendations
(Blankson & Kalafatis, 2004; Parasuraman et al., 1988).

The changes to the theoretical structure of the model of apparel
store image (refer to Figure 3 Part 1) suggested by the statistical
analysis were effected and are presented in Figure 2 (two
subdimensions namely Transportation and Interaction were
omitted from the Convenience and Sales personnel dimensions
respectively). A 214-item store image scale was derived from
the statistical analysis in the first pilot study. This scale was
employed in the second pilot study.

CONSTRUCT DIMENSIONS IT
E

M
S

N
O

. O
F

IT
E

M
S

C
O

E
F

F
IC

IE
N

A
LP

H
A

A
LP

H
A

D
E

LE
T

E
D

IT
E

M
-T

O
TA

L
C

O
R

R
E

L
A

T
IO

N
S

Store image 55 0.83
Atmosphere 6 0.72

2 0.68 0.48
3 0.67 0.49
4 0.68 0.46
5 0.67 0.51
6 0.68 0.45
11 0.71 0.37

Convenience 7 0.62
12 0.57 0.37
19 0.56 0.40
22 0.57 0.38
32 0.57 0.40
38 0.58 0.35
41 0.58 0.37
46 0.66 0.09

Facilities 7 0.61
53 0.59 0.26
56 0.54 0.43
57 0.49 0.62
60 0.52 0.48
75 0.57 0.32
76 0.61 0.21
80 0.66 0.09

Institutional 6 0.69
95 0.66 0.42
96 0.67 0.37
98 0.64 0.47
100 0.59 0.62
101 0.66 0.41
102 0.70 0.29

Merchandise 8 0.64
104 0.64 0.18
105 0.65 0.18
107 0.57 0.45
108 0.52 0.59
111 0.60 0.37
117 0.58 0.47
122 0.62 0.28
128 0.65 0.15

Promotion 8 0.68
132 0.65 0.40
143 0.71 0.14
144 0.64 0.45
148 0.66 0.39
152 0.66 0.36
153 0.65 0.41
155 0.62 0.53
156 0.64 0.44

Sales personnel 5 0.79
165 0.80 0.41
167 0.80 0.40
168 0.70 0.72
169 0.73 0.65
170 0.71 0.70

Service 8 0.59
173 0.55 0.32
174 0.51 0.46
180 0.59 0.18
188 0.51 0.41
189 0.56 0.26
190 0.52 0.41
204 0.56 0.27
208 0.61 0.12

TABLe 7
Reliability and item-total correlations - pilot study 2 (test data set)

CONSTruCT DiMeNSiONS NO. OF iTeMS COeFFiCieNT ALPHA

Store image 55 0.89

Atmosphere 6 0.83

Convenience 7 0.80

Facilities 7 0.86

Institutional 6 0.84

Merchandise 8 0.83

Promotion 8 0.84

Sales personnel 5 0.88

Service 8 0.86

TABLe 6
Reliability - pilot study 2 (training data set - 55-item store image scale)

Store Image: Part 2 Theoretical Research

S
A

Journal of Industrial P
sychology

http://www.sajip.co.za SA Tydskrif vir BedryfsielkundeVol. 34 No. 2 pp. 59 - 68

Pilot study 2

The sample profile (n = 176) was similar to that of pilot study 1.
Most of the respondents (93%) were in the age group 18 to 21.
The majority (81%) belonged to the white population group and
indicated Afrikaans as their home language.

The data obtained were split into a training data set (n = 110) and
a test data set (n = 66). Once again, the statistical analysis was
only performed on each dimension associated with the store
image construct. Therefore, the model was adapted to exclude
all the subdimensions that focus on the broad dimensions of
store image. This model is represented in Figure 3 and was
employed in all further statistical analysis.

Training data set (n = 110)

Coefficient alphas for each dimension and the total scale are
presented in Table 4. All item-total correlations met the adopted
criteria of > 0.3. Inter-item correlations were within the set
criteria of 0.2-0.5, except for the Sales personnel dimension at
0.62.

EFA was performed employing the principal axis factoring
procedure and constraining the analysis to a priori one factor
for each dimension. The factor loadings for items in the
214- item scale ranged from 0.41 to 0.72 for Atmosphere, 0.36
to 0.66 for Convenience, 0.28 to 0.71 for Facilities, 0.20 to 0.69
for Institutional, 0.36 to 0.68 for Merchandise, 0.43 to 0.67 for
Promotion, 0.44 to 0.81 for Sales personnel and 0.39 to 0.74 for
Service. Given that the cut-off value for factor loadings was set
at a minimum of > 0.5, the results highlighted that individual
items required closer scrutiny.

Item reduction was undertaken by considering item factor
loadings in conjunction with item-total correlations. Aiming
at scale purification and optimal scale length, items with the
highest factor loadings and corresponding high item-total
correlations were retained. This resulted in the deletion of
159 items across all dimensions and 55 items being retained.
Table 5 presents the factor loadings of the individual items
retained in the 55-item scale.

Coefficient alphas, inter-item correlations and item-total
correlations were again calculated for the 55-item scale.
Coefficient alpha for the total scale was recorded at 0.89 and
ranged from 0.80 to 0.88 for the individual dimensions, thus
exceeding the cut-off value of > 0.7, as presented in Table 6.
All alpha values were lower for the shortened scale compared
to the 214-item scale, except for Sales personnel. This is to
be expected, since alpha increases with the number of items
(Netemeyer et al., 2003). The inter-item correlations were all

MODeL FiT iNDiCeS ATMOSPHere CONVeNieNCe FACiLiTieS iNSTiTuTiONAL MerCHANDiSe PrOMOTiON
SALeS
PerSONNeL SerViCe

Absolute Fit Measure

Degrees of Freedom 9 14 14 9 20 20 5 20

Normal Theory Weighted Least Squares Chi-
Square

40.02
p < 0.01

23.87
p < 0.05

53.20
p < 0.01

23.35
p < 0.01

99.72
p < 0.01

41.04
p < 0.01

24.12
p < 0.01

96.17
p < 0.01

Root Mean Square Error of Approximation
(RMSEA)

0.096 0.0 0.12 0.054 0.16 0.034 0.12 0.16

Standardised Root Mean Square Residual (RMR) 0.10 0.078 0.12 0.093 0.16 0.093 0.084 0.15

Goodness of Fit Index (GFI) 0.97 0.97 0.95 0.97 0.92 0.96 0.99 0.90

Adjusted Goodness of Fit Index (AGFI) 0.92 0.95 0.90 0.93 0.85 0.93 0.97 0.81

incremental Fit Measures

Non-Normed Fit Index (NNFI) 0.93 1.00 0.86 0.97 0.68 0.99 0.94 0.65

Comparative Fit Index (CFI) 0.96 1.00 0.91 0.98 0.77 0.99 0.97 0.75

TABLe 8
Model fit indices of CFA on individual dimensions - pilot study 2 (test data set)

within the adopted criterion ranging from 0.2–0.5 and the item-
total correlations were all above the cut-off value of > 0.3.

A correlation analysis was performed between the 214-item
and the 55-item store image scales. The correlations between
the various dimensions indicated satisfactory values, namely
Atmosphere (r = 0.94), Convenience (r = 0.90), Facilities
(r = 0.90), Institutional (r = 0.87), Merchandise (r = 0.90),
Promotion (r = .90), Sales personnel (r = 0.94) and Service
(r = 0.92) (see Section 3.4.2.3). The 214-item store image scale
was representative of all the subdimensions initially proposed
in the revised model of apparel store image (Figure 2). The
55- item scale did not represent all of these subdimensions but
only the broad dimensions of store image. The high correlations
between the longer and shorter store image scales provide
support for the shortened version and confirm that the 55-item
scale performs satisfactorily.

Test data set (n = 66)

Coefficient alphas for the 55-item scale were recorded at 0.83 for
the total scale and ranged from 0.59 to 0.79 for the individual
dimensions with only Atmosphere (α = 0.72) and Sales personnel
(α = 0.79) satisfying the accepted cut-off value of > 0.7 (refer to
Table 7).

The inter-item correlations of Convenience (0.192), Merchandise
(0.192) and Service (0.170) fell outside the set criterion ranging
from 0.2 to 0.5 with 14 individual items not achieving the set
cut-off value of > 0.3, namely Convenience (item 46), Facilities
(items 53, 76 and 80), Institutional (item 102), Merchandise
(items 104, 105, 122 and 128), Promotion (item 143) and Service
(items 180, 189, 204 and 208).

CFA was performed for each dimension of the test data set
using diagonally weighted least squares as the method of
estimation. Table 8 summarises the indices of model fit for each
of the dimensions. Root mean square error of approximation
(RMSEA) for Convenience (0.0) and Promotion (0.034)
demonstrates good fit, whilst Institutional (0.054) meets the set
criteria for acceptable fit. The RMSEA values for Atmosphere
(0.096), Facilities (0.12), Merchandise (0.16), Sales personnel (0.12)
and Service (0.16) fall outside of the set criteria for acceptable
fit. The Standardised root mean residual (RMR) value for all
dimensions exceeded 0.05, indicating poor fit. The Goodness-
of-fit index (GFI) value for all the dimensions exceeded the cut-
off value of 0.9, suggesting good model fit. The GFI value for
all the dimensions exceeded the cut-off value of 0.9, suggesting
good model fit. The Adjusted goodness-of-fit index (AGFI)
criteria of > 0.9 for all the dimensions were met except for
Merchandise (0.85) and Service (0.81). All the dimensions met

Theoretical Research Du Preez, Visser, Janse van Noordwyk

Vol. 34 No. 2 pp. 59 - 68SA Tydskrif vir Bedryfsielkunde

S
A

J
ou

rn
al

o
f I

nd
us

tr
ia

l P
sy

ch
ol

og
y

http://www.sajip.co.za66

a standardised residual of > |2.5| with item 111, this item
should be considered for deletion.

the cut-off value of 0.9 on the Non-normed fit index (NNFI)
except for Facilities (0.86), Merchandise (0.68) and Service (0.65).
The Comparitive fit index (CFI) values for all dimensions exceed
0.9 and demonstrate good fit. The set criterion of > 0.9 for the
CFI measure was met by all dimensions except for Merchandise
(0.77) and Service (0.75).

Results from the absolute fit measures indicated that the model
did not adequately reproduce the observed data. None of the
dimensions met the set criteria for the normal theory weighted
least chi-square statistic or the standardised RMR. Only the
Convenience, Promotion and Institutional dimensions indicated
acceptable fit based on the RMSEA measure. All dimensions
met the set criteria for the GFI and AGFI measure, except for
Merchandise and Service, which did not meet the set parameter
for the AGFI index. All the dimensions met the set criteria for
the incremental fit measures except for Facilities, Merchandise
and Service. By implication, the specified models for all
dimensions apart from Facilities, Merchandise and Service
provided a better fit than the null model. Overall, however, the
CFA results do not support adequate model fit.

Subsequently, the path estimates and standardised residuals
of individual items were considered to identify those items
contributing to the poor model fit. These items should be
considered for deletion to further purify the store image
scale. The cut-off values are indicated in Table 9 based on
recommendations by Hair et al., (2006). The parameter for item
deletion based on the standardised residuals was set at higher
than |4|. Items with standardised residuals between |2.5| and
|4| were considered for deletion only if there was additional
support for their deletion.

Atmosphere: Item 11 should be considered for deletion. The
standardised residual between items 5 and 6 (3.44) exceeded the
cut-off value of > |2.5|. However, no further support for the
deletion of these items was recorded and since these items did
not exceed the cut-off value of > |4|, they should be retained.

Convenience: The deletion of item 46 is supported by its item-
total correlation not meeting the set criterion of > 0.3 (refer to
Table 7). None of the standardised residuals exceeded the cut-
off value of > |2.5|.

Facilities: Four of the eight items (53, 75, 76 and 80) should be
considered for deletion. The item-total correlations for items
53, 76 and 80 did not meet the set criterion of > 0.3 and provide
further support for their deletion. The standardised residual
between items 75 and 76 was 3.25. This exceeded the cut-off
value of > |2.5|. Although this standardised residual did not
exceed the higher cut-off value of > |4|, the deletion of this item
was supported by additional evidence from the completely
standardised loadings and inter-item correlations.

Institutional: Completely standardised loadings for items 96
and 102 can be deleted. Additional support for the deletion of
item 102 is provided by the item-total correlation not meeting
the set criterion of > 0.3. The standardised residual between
items 95 and 96 (2.58) exceeded the cut-off value of > |2.5|. This
provides further support for the deletion of item 96.

Merchandise: The deletion of items 104, 105, 122 and 128 is
supported by their item-total correlations not meeting the set
criterion of > 0.3. The standardised residuals between items
108 and 111 (3.53) and items 117 and 128 (2.61) exceed the cut-
off value of > |2.5|. The deletion of items 108 and 111 is not
supported by any other results, and therefore these items should
be retained. However, item 128 is not only associated with a
high standardised residual but its completely standardised
loading and item-total correlation further support its deletion.
The standardised residual between items 107 and 108 (4.92)
exceeded the adopted criterion of > |4|, suggesting that either
one of these items should be deleted. Since item 108 also shares

DiMeNSiON CriTeriA FOr DeLeTiON OF iTeMS AND eVALuATiON
OF DiMeNSiONS

item
number

Completely
standardised
loading

Variance
extracted
(Ve)

Construct
reliability
(Cr)

< 0.5 < 0.5 < 0.7
Atmosphere 2 0.63 0.39 0.79

3 0.66

4 0.64

5 0.68

6 0.64

11 0.46

Convenience 12 0.54 0.28 0.71

19 0.67

22 0.50

32 0.56

38 0.53

41 0.60

46 0.14

Facilities 53 0.42 0.34 0.75

56 0.75

57 0.83

60 0.72

75 0.47

76 0.36

80 0.22

Institutional 95 0.52 0.36 0.76

96 0.46

98 0.67

100 0.81

101 0.60

102 0.43

Merchandise 104 0.26 0.33 0.79

105 0.28

107 0.71

108 0.94

111 0.62

117 0.52

122 0.35

128 0.23

Promotion 132 0.56 0.33 0.78

143 0.20

144 0.49

148 0.52

152 0.53

153 0.69

155 0.76

156 0.66

Sales personnel 165 0.46 0.52 0.83

167 0.44

168 0.93

169 0.85

170 0.78

Service 173 0.61 0.26 0.70

174 0.81

180 0.47

188 0.54

189 0.30

190 0.59

204 0.26

208 0.12

TABLe 9
Summary: completely standardised loadings, VE and CR –

pilot study 2 (test data set)

Values not meeting the criteria are highlighted

Store Image: Part 2 Theoretical Research

S
A

Journal of Industrial P
sychology

http://www.sajip.co.za SA Tydskrif vir BedryfsielkundeVol. 34 No. 2 pp. 59 - 68

Promotion: Items 143 and 144 should therefore be considered
for deletion. Item 143 also had an item-total correlation that
did not exceed the cut-off value of > 0.3, thus providing further
support for its deletion. None of the standardised residuals
exceeded the cut-off value of > |2.5|.

Sales personnel: Two of the five items for this dimension (165
and 167) did not meet the > 0.5 cut-off value and should be
considered for deletion. None of the standardised residuals
exceeded the criterion of > |2.5|.

Service: Four items namely 180, 189, 204 and 208 should be
deleted based on the completely standardised loadings. This
is supported by their item-total correlations not meeting the set
criterion of > 0.3.

CoNClUdING ReMARKS

The results from the item-total correlations, path estimates and
standardised residuals provided support for the deletion of
20 items. In addition, the VE for all dimensions did not meet
the set criterion. By implication, a higher amount of variance
in the items was captured by measurement error compared
to the underlying dimension. This result further supports
the deletion of these items. However, all dimensions met the
cut-off value for CR. This indicated that the items provide a
reliable measurement of each dimension. The deletion of the
suggested items should improve the model fit of the individual
dimensions and further purify the store image scale.

However, the CFA results raised concerns that needed to
be addressed before the next phase in the study. Firstly, the
deletion of the items would lead to the Facilities, Merchandise
and Sales personnel dimensions being under-identified, i.e.
there would be less than four measurement items associated
with these dimensions to allow for model identification.
Secondly, the small sample size (n = 66) cast doubt on the
CFA results, since the literature recommends sample sizes of
100 and more (Hair et al., 2006). Therefore, the decision was
made to retain the 55- item scale for the next phase in the scale
development process.

In the following article, Phase 4 of this study will be presented.
The 55-item Apparel Store Image Scale derived from the
two pilot studies will be employed in the fourth phase. The
reliability and validity of the Apparel Store Image Scale will be
assessed through practical implementation in an apparel retail
environment.

REFERENCES

Amirani, S. & Gates, R. (1993). An attribute-anchored conjoint
approach to measuring store image. International Journal of
Retail and Distribution Management, 21(5), 30–39.

Bearden, W.O. (2001). Consumer self-confidence: refinements
in conceptualization and measurement. Journal of Consumer
Research, 28(1), 121–135.

Birtwistle, G. & Siddiqui, N. (1995). Store image – characteristics
for menswear fashion retailers. The Home Economist, 14(6),
20–22.

Blankson, C. & Kalafatis, S.P. (2004). The development and
validation of a scale measuring consumer/customer-
derived generic typology of positioning strategies. Journal
of Marketing Management, 20, 5–43.

Bradburn, N., Sudman, S. & Wansink, B. (2004). Asking questions:
the definitive guide to questionnaire design – for market research,
political polls, and social and health questionnaires. San
Francisco: Jossey-Bass.

Brace, I. (2004). Questionnaire design: how to plan, structure and
write survey material for effective market research. London:
Kogan Page.

Churchill, G.A. Jr. (1979). A paradigm for developing better
measures of marketing construct. Journal of Marketing
Research, 16, 64–73.

Churchill, G.A. Jr. & Iacobucci, D. (2005). Marketing research:
methodological foundations (9th Ed.). Mason:Thomson
Southwestern.

Dabholkar, P.A., Thorpe, D.I. & Rentz, J.O. (1995). A measure
of service quality for retail stores: scale development and
validation. Journal of the Academy of Marketing Science, 24(1),
3–16.

DeVellis, R.F. (2003). Scale development: theory and applications
(2nd Ed.). Thousand Oaks: Sage Publications.

Dhurup, M., Venter, P.F. & Oosthuyzen, A. (2005). A factor
analytical service quality measurement scale for
supermarkets in South Africa. South African Journal of
Economic and Management Science, 8(2), 140–153.

Diamantopoulos, A. & Sigauw, J.A. (2000). Introducing LISREL: a
guide for the uninitiated. London: Sage Publications.

Fabrigar, L.R., Wegener, D.T., MacCallum, R.C. & Strahan, E.J.
(1999). Evaluating the use of exploratory factor analysis in
psychological research. Psychological Methods, 4(3), 272–299.

Frazer, L. & Lawley, M. (2002). Questionnaire design and
administration. Brisbane: John Wiley.

Gorsuch, R.L. (1997). Exploratory factor analysis: its role in item
analysis. Journal of Personality Assessment, 67, 532–560.

Grace, D. (2005). Consumer disposition toward satisfaction
(CDS): scale development and validation. Journal of Marketing
Theory and Practice, 13(2), 20–31.

Grace, D. & O’Cass, A. (2005). An examination of the antecedents
of repatronage intentions across different store formats.
Journal of Retailing and Consumer Services, 12(4), 227–243.

Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. & Tatham, R.L.
(2006). Multivariate data analysis. (6th Ed.). Upper Saddle
River: Pearson/Prentice Hall.

Janse van Noordwyk, H.S. (2002). Perceived importance of
retail store image attributes to the female large-size apparel
consumer in a multicultural society. Unpublished master’s
thesis. Stellenbosch: Stellenbosch University.

Jöreskog, K. & Sörbom, D. (2006). LISREL 8.8. Chicago, IL:
Scientific Software International Inc.

Kelloway, E.K. (1998). Using LISREL for structural equation
modelling: a researcher’s guide. Thousand Oaks: Sage
Publications.

Kerlinger, F.N. & Lee, H.B. (2000). Foundations of behavioural
research (4th Ed.). United States, Wadsworth.

Kleinhans, E.H. (2003). Black female student consumers’
perception of clothing store image attributes. Unpublished
masters thesis. Stellenbosch: Stellenbosch University.

Koo, D. (2003). Inter-relationships among store images, store
satisfaction, and store loyalty among Korea Discount Retail
patrons. Asia Pacific Journal of Marketing and Logistics, 15(4),
42–71.

Lastovicka, J.L., Bettencourt, L.A., Hughner, R.S. & Kuntze,
R.J. (1999). Lifestyle of the tight and frugal: theory and
measurement. Journal of Consumer Research, 26, 85–98.

Lee, M., & Johnson, K.K.P. (1997). Customer expectations
for service at apparel retail outlets. Journal of Family and
Consumer Sciences, Winter, 26–30.

Li, H., Edwards, S.M. & Lee, J. (2002). Measuring the
intrusiveness of advertisements: scale development and
validation. Journal of Advertising, 31(2), 37–47.

Lichtenstein, D.R., Ridgway, N.M. & Netemeyer, G. (1993). Price
perceptions and consumer shopping behaviour: a field
study. Journal of Marketing Research, 30(2), 234–245.

Lindquist, J.D. (1974–1975). Meaning of image. Journal of Retailing,
50(4), 29–38.

Little, T.D., Lindenberger, U. & Nesselroade, J.R. (1999). On
selecting indicators for multivariate measurement and
modelling with latent variables: when “good” indicators are
bad and “bad” indicators are good. Psychological Methods,
4(2), 192–211.

Theoretical Research Du Preez, Visser, Janse van Noordwyk

Vol. 34 No. 2 pp. 59 - 68SA Tydskrif vir Bedryfsielkunde

S
A

J
ou

rn
al

o
f I

nd
us

tr
ia

l P
sy

ch
ol

og
y

http://www.sajip.co.za

MacCallum, R.C. & Austin, J.T. (2000). Applications of structural
equation modelling in psychological research. Annual
Review of Psychology, 51, 201–226.

Manolis, C., Keep, W.W., Joyce, M.L. & Lambert, D.R. (1994).
Testing the underlying structure of store image scale.
Educational and Psychological Measurement, 54(3), 628–645.

Martineau, P. (1958). The personality of the retail store. Harvard
Business Review, 36, 47–55.

Netemeyer, R.G., Bearden, W.O. & Sharma, S. (2003). Scaling
procedures: issues and applications. Thousand Oaks: Sage
Publications.

Nunnally, J.C. (1978). Psychometric theory. London: McGraw-Hill
Book Company.

Oppenheim, A.N. (1992). Questionnaire design, interviewing and
attitude measurement. London: Continuum.

Parasuraman, A., Zeithaml, V.A. & Berry, L.L. (1988). SERVQUAL:
a multi-item scale for measure consumer perceptions of
service quality. Journal of Retailing, 64(1), 12–37.

Schlechter, A.F. (2005). The influence of transformational
leadership, emotional intelligence, trust, meaning and
intention to quit on organisational citizenship behaviour.
Unpublished doctoral thesis. Stellenbosch: Stellenbosch
University.

Shimp, T.A. & Sharma, S. (1987). Consumer ethnocentrism:
construction and validation of the CETSCALE. Journal of
Marketing Research, 24(3), 280–289.

StatSoft Inc. (2007). STATISTICA 8.0. [computer software].
www.statsoft.com.

Steenkamp, J.E.M. & Van Trijp, H.C.M. (1991). The use of LISREL
in validating marketing constructs. International Journal of
Research in Marketing, 8, 283–299.

Synodinos, N.E. (2003). The “art” of questionnaire construction:
some important considerations for manufacturing studies.
Integrated Manufacturing Systems, 14(3), 221–237.

Tabachnick, B.G. & Fidell, L.S. (2007). Using multivariate statistics
(5th Ed.). United States of America: Pearson Allyn and
Bacon.

Terblanché, N.S. & Boshoff, C. (2004). The in-store shopping
experience: a comparative study of supermarket and

clothing store customers. South African Journal of Business
Management, 35(4), 1–9.

Thompson, K.E. & Chen, Y.L. (1998). Retail store image: a means-
end approach. Journal of Marketing Practice, 4(6), 161–173.

Venter, P.F. & Dhurup, M. (2005). Consumer perceptions of
supermarket service quality: scale development and
validation. South African Journal of Economic and Management
Sciences, 4, 424–436.

Zimmer, M.R. & Golden, L.L. (1988). Impressions of retail stores:
a content analysis of consumer images. Journal of Retailing,
64(3), 265–293.

ATMOSPHERE
1. fashionability of store interior
3. attractiveness of décor in store

CONVENIENCE
9. accessibility of store (e.g. location within mall)
12. ease of finding merchandise items

FACILITIES
14. accessibility of store entrance/exit
20. ease of shopping with family in mall where store is situated

INSTITUTIONAL
22. store’s appeal to my friends
25. similarity between store image and self image

MERCHANDISE
28. availability of imported merchandise
33. availability of styles suitable to my age

PROMOTION
38. spaciousness of in-store displays
40. sales with marked-down prices

SALES PERSONNEL
43. fashionability of sales personnel
46. similarity in age between sales personnel and myself

SERVICE
49. courteousness of sales personnel
54. availability of mail-order service

APPeNDix 1
Examples of items: apparel store image scale