Simulating Attachment to Pure-Play Fashion Retailers - Academy of ...

Abstract
Purpose
Simulating Attachment to Pure-Play Fashion Retailers
This paper aims to identify how pure-play fashion retailers can simulate attachment to their
websites (through trust, loyalty and purchase intentions) by using different communication
mediums (static image, moving image, and text/image combination) to overcome the
intangible nature of the online environment.
Method
A purely quantitative methodology is adopted, using self-administered and online
questionnaires to gain a data set (n=688) appropriate for hypothesis testing. 22 items are
developed to measure 6 constructs. A two-step approach to data analysis is taken, using
confirmatory factor analysis and then structural equation modelling.
Results
There is a difference in the build-up of attachment when products are communicated via a
static or moving image. Static images have direct relationships with trust and purchase
intention, whereas moving images are related to loyalty. Analysis shows that product
recommendations (text and image) are found to be directly related to developing consumer
trust and loyalty towards a pure-play fashion retailer.
Conclusions
Marketing communications mediums serve different functions, and if used astutely could
maximise a pure-play fashion retailers online offering as part of their strategic direction.
Capturing the creation of loyal and trusting relationships should be seen as valuable and could
begin to mitigate the disadvantage of no physical contact with a consumer.
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Introduction:
Clothing is an experience product, with features that can only be evaluated by trying on or
inspection, dependent on an individual and their own personal requirements (Nelson, 1974).
For those selling clothing online, technology and communications techniques are therefore
instrumental in encouraging consumers to buy goods before they carry out their own physical
evaluations. For multichannel retailers, consumers have the option of visiting a physical store
whereby they can engage with the brand, the quality of the products and the sizing of the
goods on offer. For pure-play fashion retailers this is not possible, and therein lays their
biggest disadvantage. This study attempts to go some way to answering the question; how can
pure-play fashion retailers stimulate attachment to their website when they cannot offer
physical interaction from the shopping experience?
A pure-play retailer has no traditional storefront and can be found solely in the online
marketplace (Ashworth, Schmidt, Pioch & Hallsworth, 2006a). To date there is little research
on pure-play retailers, with previous studies concentrating on their definition (Marciniak &
Bruce, 2004), pricing strategies (Yan, 2008) and profitability (Goldsmith & Flynn, 2005;
Ashworth, Schmidt, Pioch & Hallsworth, 2006b). With some retailers beginning to move
towards category killer status (ASOS.com now claims to be the ‘world’s biggest wardrobe’) it
is imperative that there is an increased understanding of this retail format.
One fundamental disadvantage of pure-play fashion retailing is the lack of tactility and
experience a consumer can have with a product prior to purchase. Moreover, no human
interactions with store personnel can be made, and visual merchandising cannot be carried out
easily. In order to compete with offline stores a pure-play fashion retailer’s communication of
its products to consumers must be faultless. Understanding the effect that different
communications media have on consumer shopping experiences could go some way to
reaching this goal. This study models the effects of different mediums of communication and
how these tools relate to aspects of consumer attachment.
Shopping Motivations:
In modelling the effects that pure-play communication mediums have on attachment,
understanding of the pure-play consumer will increase and links can be made with consumer
shopping motivations. Understanding shopping motivations can help indicate what the pureplay
interface needs to deliver to stay competitive. Shopping motivations can be utilitarian or
hedonic (Wagner, 2007). Recognized hedonic shopping motivations include enjoyment,
whereas utilitarian motives are ease of use and usefulness (Monsuwe, Dellaert & Ruyter,
2004). Hedonic motivations to shop include adventure, social, gratification, idea, role and
value shopping (Arnold & Reynolds, 2003). Consumers with high levels of fashion
innovativeness are driven by adventure and idea motives and less concerned with value (Kang
& Park-Poaps, 2010). Motivations are also linked to customer’s evaluation of online store
elements such as visual design, product assortment and information quality (Koo, Kim & Lee
2008). This study attempts to increase understanding of the links between how consumers
process different communications mediums, the effects on their resulting levels of attachment
and the reasons why they choose the shop via a pure-play format.
Theoretical Framework - Communications Theory:
Finding its theoretical origin in cybernetics, long standing communications theory models the
journey between a source and a receiver (Shannon & Weaver, 1949; Lasswell, 1948; Craig,
1999). This journey includes a message, a medium and a resulting effect (Shannon & Weaver,
1949). Communication will be at its most effective when the source (pure-play fashion
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etailer) has understood the needs (motivations) of the receiver (consumer) (Danaher &
Rossiter, 2011). Clothing consumption is inherently linked to one’s self-image, thus websites
which build relationships through targeted communications are more likely to have loyal
followers and potentially higher sales (Kim & Jin, 2006). This study attempts to understand
how to maximise the effectiveness the medium of the message has on the receiver, in a
channel where there are no direct points of human to human contact.
Figure I shows where this study sits in terms of the model of communication (Shannon &
Weaver, 1949). The source in this study is considered the pure-play fashion retailer and the
message is their products. The mediums which this study measures includes images (static),
video (moving image) and text, and the effects which are explored include trust, loyalty and
purchase intentions. By looking at which effects are linked with which mediums, pure-play
fashion retailers can begin to see where their resources should be invested to ensure rewarding
marketing communications.
Figure I: A Communications Model
Source: Adapted From Lasswell (1948) and Shannon and Weaver (1949).
The medium element of the communications model is the focus for this study. Most retailers
will use a mix of mediums but some are more widespread than others and fulfil varying
consumer needs. Specifically this study will look at the effectiveness of videos, images and
text. The effectiveness of these mediums is pragmatically measured as static images, videos
of a product and expert recommender systems present on a pure-play fashion website. The
next section of the literature review will discuss these mediums and hypotheses are proposed
based on their links to trust, loyalty and purchase intentions.
Existing Literature -Static Product Presentation:
Static product presentation includes elements such as 2D or 3D view, back view, viewing a
product on a model, a mannequin and zoom capabilities. Product presentation contributes to a
consumer’s online information gathering (Flavian, Gurrea & Orus, 2009). The
communication of information via product presentation must be comprehensible and efficient
as it is the sole interaction a consumer will have with a product prior to purchase (Flavian et
al., 2009).
Moving Product Presentation:
Moving product presentation methods (such as video) are not as widely used as static
presentation methods. In a recent content analysis of 97 women’s apparel websites, video
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presentation was only available in 5.2% of cases (Kim, Kim & Lennon, 2011). However,
studies show that video can improve the attractiveness of products, build brand awareness
(Pentina, Amialchuk & Taylor, 2011), and improve the mood of consumers (Park, Lennon &
Stoel, 2005). Product movement can also help to overcome the limited physical experience
consumers are able to have shopping online by evoking product functionality (Li, Daugherty
& Biocca, 2002). Moreover, simulating touch and experience with product videos can evoke
cognitive, affective and conative responses (Park et al., 2005).
Product Recommendations:
One method of offering an individualized service is through product recommendations (Cho
& Fiorito, 2009). Recommendations can be communicated through a text based suggestion
coupled with an image. Recommendations have been defined as the extent to which a website
“gives suggestions, ideas or options to enable further examination of a specific product or to
trigger the inspection of further products” (Demangeot & Broderick, 2007, p. 885). Senecal
and Nantel (2004, p.160) posit that “online recommendation sources can be sorted into three
categories including other consumers (friends, relatives, and acquaintances), human experts
(salespersons, independent experts) and expert systems (such as recommender systems)”.
This study will focus on expert systems, which have been found to be the most influential
recommender source (Senecal & Nantel, 2004).
Trust, Loyalty and Purchase Intentions:
An increased need for the role of trust is covariant with increasing amounts of information
and alternatives presented to sovereign consumers (Chung & Shin, 2010). Trust has been
found to determine loyalty to a website (Ridings, Gefen & Arinze, 2002; Gefen, 2002) and
can be a crucial factor for consumers to make a purchase decision (Winch & Joyce, 2006;
Bart, Shankar, Sultan & Urban, 2005). Loyal customers are prepared to spend more, buy more,
are easy to reach, repeatedly return and are positive promoters of a company (Harris & Goode,
2004). Loyalty intention is the consumer’s positive attitude towards the retailer that results in
repeat purchase behaviour (Yen & Lu, 2008). Purchase intention has been defined as a mental
state which results in the consumer’s choice to buy a product or service in the immediate
future (Bigne-Alcaniz, Ruiz-Mafe, Aldas-Manzano & Sanz-Blas, 2008).
Conceptual Model:
Research hypotheses have been developed based on the existing literature (see Table I, in
Appendix A), and are shown in Table II, in Appendix B.
Methodology
This study is focused on ASOS, the largest independent fashion retailer. ASOS is a pure-play
fashion retailer and an industry high standard with 41% profit increase in 2011 to £26.8
million (IMRG, 2011). ASOS will be familiar to the target respondents of this study, their
target audience being 16-34 year old fashion-conscious consumers (Mintel, 2011). The
sample comprised of young female fashion consumers (specifically fashion retail students, in
accordance with Kim and Park (2005) and Kim and Forsythe (2009)). Fashion students are
likely to be more innovative than a sample from other disciplines (Workman & Caldwell,
2007).
A cross sectional approach to this study was taken using self administered and online surveys.
The survey questionnaire was composed of two sections; demographic and shopping
frequency questions and attitude scales. The shopping frequency questions were used as a
filter; respondents had to have visited the ASOS online store in the last six months and be
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female. The second section of the questionnaire used scaled responses to a seven-point likert
scale (Goldsmith & Flynn, 2005; Kim et al., 2009) (Strongly Agree- Strongly Disagree). A
‘No Opinion’ box was included (Collins-Dodd & Lindley, 2003) so as respondents who did
not use or had not heard of an item would not affect the analysis. 22 items were developed to
measure 6 constructs. Items which explicitly measure fashion website variables are limited,
and therefore some development and adaptation was needed. However, items originated from
academically validated sources. A review of all the item measures used in this study is shown
in Table III in Appendix C.
Empirical Results:
A total sample of 688 was collected for this study, 331 were completed in paper format and
357 were completed online. The average age of respondents is 21 with a range between 16
and 43. 87.9% of the sample is under 24, making this data more applicable to young
consumers.
Data Analysis:
This study uses both confirmatory factor analysis (CFA) and structural equation modelling
(SEM). The measurement model tested in confirmatory factor analysis provided satisfactory
evidence to accept the six factor model. Fit statistics indicated a good fit (χ² = 436.066, df =
194, p = .000, CMIN/DF = 2.248, GFI = .947, AGFI = .931, RMSEA = .043, NFI = .942, CFI
= .967). Factor loadings including all six factors are sufficient with values exceeding .60 apart
from one item in the static product presentation construct. Data was checked for reliability,
convergent and discriminant validity, which were all found to be present.
The data set for structural equation modelling contains 22 observed variables representing 6
latent factors. All latent factors have at least three observed variables. Overall, the fit statistics
indicate a relatively good fit (CMIN/DF = 2.388, GFI = .943, AGFI = .927, RMSEA = .045,
CFI = .962, NFI = .937). All of the fit statistics exceed their accepted thresholds. A summary
of the structural paths and their p-values is shown in Table IV in Appendix D. The
confirmation or rejection of the hypotheses can be evaluated by looking at the standardized
regression weights and the p-values. Nine out of the twelve hypotheses are statistically
significant.
Discussion- Static versus Movement on pure-play fashion websites:
In this study, static images are found to be more strongly related to directly building
consumers purchase intentions (γ=0.17) than moving images (γ=0.03). This finding is at odds
with previous research by Park et al., (2005) who found that the evaluation of images
involving movement had a greater effect on purchase intentions than static images. However,
moving images are more likely to relate to consumer loyalty (γ=0.23) compared with static
images (γ=0.02). Moving images have increased vividness, and have been found to induce
stronger enduring attitudes than images with moderate/low vividness (static) (Coyle &
Thorson, 2001). Trust can be developed by using static (γ=0.26) and moving images (γ=0.19)
in pure-play fashion websites, although there is a slightly stronger relationship between static
images and trust.
Expert Product Recommendations:
Analysis shows that product recommendations generated by an expert source (such as a
retailer) are found to directly relate to developing consumer trust and loyalty towards a pureplay
fashion retailer. Studies have found links between product recommendations and trust
(Hsaio, Lin, Wang, Lu & Yu, 2010; Pu & Chen, 2006; Gershoff, Mukherjee, &
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Mukhopadhyay, 2003). Expert product recommendations may generate perceptions of
increased choice for consumers, and lead to a quicker match of consumer and product
(Srinivasan, Anderson & Ponnavolu, 2002). Moreover, if there is a positive match between
recommendations and consumers, they may be more likely to re-patronise that retailer in their
next instance of online shopping. Successful evaluation of expert based product
recommendations can therefore increase customer loyalty towards a website.
Trust, Loyalty and Purchase Intentions:
Results show strong positive results for the three hypothesized relationships concerning these
latent constructs. Those consumers who are trusting of a pure-play fashion retailer are more
likely to be loyal, and have higher purchase intentions towards the website. Moreover, loyal
consumers are more likely to have higher purchase intentions towards a pure-play fashion
retailer. These findings support previous works by Harris and Goode (2010; 2004), Mukherjee
and Nath (2007), Novak, Hoffman and Peralta (1999) and Srinivasan et al., (2002),
contributing to further deepening of knowledge regarding the online environment.
Conclusion
Each of the marketing communication elements studied in this paper clearly serve different
functions, and if used strategically could maximise a pure-play fashion retailers online
offering as an element of their overall strategic direction. Pure-play fashion retailers should
try to appeal to those consumers willing to spend time on a website by providing product
videos which generate consumer loyalty and increase vividness and telepresence. Pure-play
fashion retailers can use movement to immerse and involve consumers in the online
experience. However, for those who do not wish to spend time and are more motivated by
evaluating the product through static images, high resolution images with multiple viewing
options should be provided to fulfil product evaluation, gratification or impulse leading to
trust and purchase intentions. When providing product recommendations a mixture of both
visual and verbal information can have a potent effect, but in the future movement could be
combined with this to create more persuasive and dynamic presentation of recommendations.
In answer to the question posed at the start of this paper, simulating attachment to a website
without physical interaction can be carried out by using multiple static viewing options of
products, moving product videos and expert driven product recommendations as facets of an
overall online strategy. Fashion retailers should attempt to fulfil a multiplicity of different
consumer motivations to shop online by maximising the communication mediums to
communicate products. For those looking for a quicker fashion fix, high resolution images
can provide sufficient information to consumers to make an informed purchase decision and
simulate attachment towards a retailer in the form of trust. For consumers who want to be
more involved with a website and spend more time, videos can offer higher levels of
vividness and telepresence. Those consumers who wish to dwell, seek fantasy or want to view
a product in more detail may develop more loyalty towards a website if product movement
communications are offered. Capturing the creation of these loyal relationships should be
seen as valuable and could go some way to mitigating the disadvantage of no physical contact
with a retailer. Moreover, these findings could translate to an in-store environment. In-store
retailers could provide points of technological interaction involving video to boost their
physical offering or to add cohesion to their multi-channel strategy.
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Appendix
Appendix A
Table I: Hypothesis Development Literature Summary
Construct Connections with Trust Connections with Loyalty Connections with Purchase Intentions
Static Product
Presentation
Moving Product
Presentation
Expert Driven Product
Recommendations
H2
McKnight et al., 2004, 2002;
Chang and Chen, 2008;
Flavian et al., 2009
H4
Exploratory hypothesis
H7
Urban, Sultan and Qualls, 1999;
Senecal and Nantel, 2004
H3
Flavian et al., 2009;
Goode and Harris, 2007
H6
Exploratory Hypothesis
H9
Srinivasan et al., 2002;
Kim et al., 2009
Trust N/A H10
Harris and Goode, 2010;
Stewart, 2003;
Yen and Gwinner, 2003;
Ridings, Gefen and Arinze,2002;
Gefen, 2002
13
H1
Then and Delong, 1999;
Kim and Lennon, 2000;
Park et al., 2005;
Kim et al., 2009
H5
Park et al, 2005;
Song, Fiore and Park, 2007;
Sharples, 1999
H8
Ha, Kwon and Lennon, 2007;
LaRose, 2001;
Hsiao, Lin, Wang, Lu and Yu, 2010
H11
Mukherjee and Nath, 2007;
Javenpaa, Tractinsky and Saarinen,
1999;
Novak, Hoffman and Peralta, 1999;
Gefen and Straub, 2001;
Cho and Lee, 2006;
Rosseau, Sitkin, Burt and Camerer,
1998;
Chau, Hu, Lee and Au, 2007;
Chen and Barnes, 2007;
Lim, 2003
Loyalty N/A N/A H12
Assael, 1992;
Keller, 1993;
Srinivasan et al., 2002;
Yen and Lu, 2008;
Tsai, Juang, Jaw and Cheng, 2006
Purchase Intentions N/A N/A N/A

Appendix B
Table II: Hypothesis Summary for Study
Hypothesis
Number
Hypothesis
H1 Positive evaluations of static product presentation variables will have a positive relationship with consumer purchase
intentions
H2 Positive evaluations of static product presentation variables will have a positive relationship with consumer trust
H3 Positive evaluations of static product presentation variables will have a positive relationship with consumer loyalty
H4 Positive evaluations of moving product presentation methods will have a positive effect on consumer trust.
H5 Positive evaluations of moving product presentation methods will have a positive effect on consumer purchase
intentions.
H6 Positive evaluations of moving product presentation methods will have a positive effect on consumer loyalty.
H7 Positive evaluations of product recommendations provided by an expert system will have a positive relationship with
trust
H8 Positive evaluations of product recommendations provided by an expert system will have a positive relationship with
purchase intentions
H9 Positive evaluations of product recommendations provided by an expert system will have a positive relationship with
loyalty
H10 Online trust of a website is positively related to loyalty
H11 Online trust of a website is positively related to purchase intentions
H12 Online loyalty towards a website is positively related to purchase intentions
14

Appendix C
Table III: Measurement Scales
Construct Item Source (Adapted from)
Product Presentation Back view on ASOS provides in-depth information
Zoom feature on ASOS provides in-depth information
Detailed view on ASOS provides in-depth information
3D Rotation view/Model on ASOS provides in-depth
information
Video ASOS has visually appealing catwalk videos
The catwalk video on ASOS is beneficial
The product videos on ASOS are lifelike
Suggestions Offering ASOS recommended relevant products to me which I had not
thought of or did not know
ASOS makes purchase recommendations which match my
needs
‘We Recommend’ feature on ASOS makes purchase
recommendations which match my needs
Trust ASOS represents a company or organisation that will deliver
on promises made
ASOS can be counted on to do what they say they will do
ASOS is reliable
ASOS puts the customer’s interest first
Loyalty When I need to make a purchase, ASOS is my first choice
I have repeatedly found ASOS better than others
I would classify myself as a loyal customer of ASOS
I will visit ASOS first when I buy fashion
Purchase Intention I would purchase an item from ASOS
I intend to continue using ASOS in the future
I would recommend ASOS to a friend
In the future I intend to use ASOS for fashion purchases
15
Wolfinbarger and Gilly (2003)
Wolfinbarger and Gilly (2003)
Wolfinbarger and Gilly (2003)
Wolfinbarger and Gilly (2003)
Kim, Kim and Kandampully (2009)
Mukherjee and Nath (2007)
Schlosser (2003)
Demangeot and Broderick (2007)
Srinivasan, Anderson and Ponnavolu (2002)
Srinivasan, Anderson and Ponnavolu (2002)
Bart, Shankar, Sultan and Urban (2005)
Mukherjee and Nath (2007)
Aaker, Fournier and Brasel (2004)
Verhoef, Franses and Hoekstra (2002)
Srinivasan, Anderson and Ponnavolu (2002)
Harris and Goode (2004)
Brady, Knight, Cronin, Tomas, Hult and
Keillor (2005)
Demangeot and Broderick (2007)
Bart, Shankar, Sultan and Urban (2005)
Demangeot and Broderick (2007)
Bart, Shankar, Sultan and Urban (2005)
Maxham and Netemayer (2003)

Appendix D
Table IV: Structural Path Estimates
Hypothesis
Number
Structural Path Standardized
Regression
Weights
16
P-Value T-value Support For
Hypothesis?
H1 Static Product Presentation > Purchase 0.171 *** 4.619 Yes
H2
Intention
Static Product Presentation > Trust 0.260 *** 5.723 Yes
H3 Static Product Presentation > Loyalty 0.020 0.635 .475 No
H4 Moving Product Presentation > Trust 0.189 *** 4.599 Yes
H5 Moving Product Presentation > Purchase
Intention
0.028 0.418 .810 No
H6 Moving Product Presentation > Loyalty 0.235 *** 5.656 Yes
H7 Product Recommendations> Trust 0.305 *** 6.761 Yes
H8 Product
Intention
Recommendations > Purchase -0.027 0.470 -.722 No
H9 Product Recommendations > Loyalty 0.147 *** 3.303 Yes
H10 Trust > Loyalty 0.389 *** 8.143 Yes
H11 Trust > Purchase Intentions 0.272 *** 6.503 Yes
H12 Loyalty > Purchase Intention
Note: *** = p