Content uploaded by Rosy Boardman
Author content
All content in this area was uploaded by Rosy Boardman on Jan 18, 2022
Content may be subject to copyright.
1
Citation: Boardman, R. and Mccormick, H. (2021), "Attention and behaviour on fashion retail
websites: an eye-tracking study", Information Technology & People, Vol. ahead-of-print No. ahead-of-
print. https://doi.org/10.1108/ITP-08-2020-0580
Attention and Behaviour on Fashion Retail Websites: An Eye-
Tracking Study
Dr Rosy Boardman, Department of Materials, University of Manchester
Dr Helen McCormick, Manchester Fashion Institute, Manchester Metropolitan
University
Abstract
Purpose
The purpose of this paper is to identify attention, cognitive and affective responses
towards a fashion retailer’s website and the behavioural outcomes when shopping
online.
Design/Methodology/Approach
52 eye-tracking tests and 52 qualitative semi-structured interviews were conducted.
Findings
Consumer attention and behaviour differs across web pages throughout the shopping
journey depending on its content, function and consumers’ goal. Top-down attention
is more dominant than bottom-up attention when consumers are shopping online for
fashion items. The product listings page was the most frequented and had the most
time spent on it. Consumers enjoy browsing for products and adding them to their
basket to evaluate them together later. Customisation and personalisation features
are the most valued due to their ability to make the experience more convenient and
enjoyable.
Originality/Value
This article contributes novel findings that the content and design of the website affects
attention in different ways. It demonstrates that research cannot simplify viewing
2
patterns for fashion shopping online. The study extends the SOR framework, showing
that top-down attention, when provided with personalisation and customisation
features, results in approach behaviour. A lack of personalisation or customisation
features results in avoidance behaviour. The complex nature of consumer attention
and behaviour during their holistic shopping journey advocates the need for eye-
tracking research to be conducted on a live website for ecological validity, providing a
methodological contribution which can be used for future research.
Key Words: Website Design, Attention, Eye tracking, Fashion Retail, Ecommerce,
Browsing, Consumer Behaviour, Personalisation, SOR Framework
Article Classification: Research Paper
3
Introduction
This research contributes to knowledge by investigating consumer attention and
responses to a holistic fashion retail website throughout their typical online shopping
journey. Online sales have been rising steadily over the last two decades, and its
importance as a retail channel has increased dramatically due to Covid-19, with people
unable to buy non-essential items in stores during global lockdowns. Although the
reliance has lessened due to stores reopening, Covid-19 has accelerated the shift to
shopping for fashion online and this heightened online demand will remain a legacy of
the pandemic (Mintel, 2020). This highlights the need for fashion retailers to invest in
e-commerce and the importance of effective website design.
However, consumers may have different responses to websites based on the product
that they are shopping for. Marketers classify products as ‘search’, ‘experience’ or
‘credence’ products (SEC classification). ‘Search’ products have features that are
easily evaluated before purchasing (e.g. price), meaning there is little product
uncertainty when purchasing (Hassanein and Head, 2005; Micu and Pentina 2015;
Rutgers, 2019). ‘Experience’ products have attributes that are unknown until
purchase, such as quality or fit, and whose characteristics can only be evaluated fully
when a consumer comes into direct contact with them (Hassanein and Head, 2005;
Micu and Pentina 2015). ‘Credence’ products are those which, even after purchase,
customers may still be unable to assess their quality, such as legal services (Rutgers,
2019). Hence, ‘search’ and ‘experience’ products are differentiated by the consumer’s
ability to evaluate quality before or after purchase (Darby and Karni, 1973; Gupta et
al., 2004).
This study classifies clothes as ‘experience’ products when bought online because
they can only be evaluated accurately after purchase and wear, the fit and quality is
not clear. Hong and Pavlou (2014) found that product fit and quality are experience
attributes. Moreover, Gupta and Harris (2010) state that experience products need to
be seen and tried on before purchasing in order for consumers to successfully
evaluate them. Indeed, consumer satisfaction depends upon how the clothes fit, how
they feel, how they look and how long they last, making the decision-making process
more experiential (Vahie and Paswan, 2006). This classification of clothes as an
‘experience’ product is aligned with existing literature (Ekelund et al., 1995; Citrin et
4
al., 2003; Vahie and Paswan, 2006; Grant et al., 2007; Bock et al., 2012; Jai et al.,
2014; Micu and Pentina, 2015; Pålsson et al., 2017; Boardman and McCormick, 2019;
Sun et al., 2019; Naegelein et al., 2019).
Hence, clothing is difficult to buy online compared to ‘search’ products as experience
attributes such as the feel, texture and fit are hard to communicate through websites,
creating a higher degree of uncertainty (Naegelein et al., 2019). This tactile interaction
is very difficult to replicate online but it is essential to provide for ‘experience’ products
such as clothing, as people want to touch the fabric to gain additional information about
its properties (Li et al., 2001; Citrin et al., 2003). Furthermore, clothing is associated
with higher social risk due to its potential to expose the consumer to ridicule from
peers, and thus, social and symbolic meaning also play significant roles in clothing
purchases (Batra and Sinha, 2000; Vahie and Paswan, 2006). This makes clothing
one of the most complex products to buy and sell online. Yet, fashion remains the
biggest category purchased online (Hootsuite, 2021). Therefore, fashion retailers must
ensure that their website presents items effectively, detailing style and fit accurately,
to encourage purchasing.
In order to design websites effectively, retailers must first understand how consumers
behave on them and what stimuli capture attention. Chang et al. (2016) called for
future research to investigate how website design effects consumers’ cognitive
attitudes. One way in which consumers cognitive processing can be measured is
through eye-tracking. Consumers are not often consciously aware of their decision-
making processes on websites and so traditional research methods such as surveys
are limited in terms of reliability (Wang et al., 2020). Eye-tracking enables researchers
to capture behaviour that consumers may be unaware of, or unwilling to admit,
showing how consumers view websites in real-time (Djamasbi, 2014). Therefore, eye-
tracking enables researchers to study the behavioural-environmental processes
behind consumers’ shopping journeys, providing real-time information on their
fixations and gaze patterns, thereby generating a greater understanding of online
shopping behaviour (Menon et al., 2016). Hence, by using eye-tracking, researchers
are able to measure peoples’ behaviour and cognitive processing objectively,
counteracting the limitations of traditional methods. Yet, peer-reviewed eye-tracking
5
papers relating to consumer research remain scare (Huddleston et al., 2018). Thus,
there is a need for more eye-tracking studies to gain a comprehensive understanding
of how consumers respond to fashion retail websites. The present study will fill this
gap in the literature.
Most eye-tracking studies are based on ‘search’ product websites, with ones based
on fashion retail websites scarce. Yet, as discussed, results may differ from studies
based on ‘search’ products due to the nature of clothing as an ‘experience’ product.
Furthermore, the majority of eye-tracking website studies are based on static
screenshots (Djamasbi et al., 2010) or partial/manipulated websites (Cyr and Head,
2013; Shi et al., 2013; Cortinas et al., 2019). Yet, studies using simulated websites
limit the possibility of analysing consumers’ actual experiences when shopping
(Tupikovskaja-Omovie and Tyler, 2020). Therefore, Huddleston et al. (2015) called for
future eye-tracking studies to be conducted in a real-time shopping environment as
consumers might respond differently in this context as opposed to when viewing static
images. Furthermore, Brunner-Sperdin et al. (2014) argue that it is imperative that
websites are evaluated holistically in order to understand consumers full perception of
the website. Thus, extant literature does not explain how consumers respond to a
fashion retailer’s website and how their attention varies (bottom-up vs top-down)
throughout their shopping journey. The present study will fill this gap in the literature
using the Stimulus-Organism-Response model to explore consumers’ attention and
behaviour throughout their shopping journey. Therefore, this article contributes to
knowledge by answering the following research questions:
RQ1. What do consumers think and feel when shopping on a live fashion retail website
in real-time?
RQ2. What design stimuli do consumers pay attention to when shopping on a fashion
retail website and why?
RQ3. How does consumers’ attention, cognitive and affective responses to the
website design influence their behaviour?
Literature Review
Retail Websites
6
Fashion consumers frequently switch channels and retailers when deciding on a
purchase (Patten et al., 2020). Thus, fashion retailers’ websites need to create exciting
shopping experiences, as consumers can switch to competitors’ websites with minimal
effort (Pham and Ahammad, 2017). Retail websites should also be easy to use in order
to be useful and generate feelings of pleasure (Espigares-Jurado et al., 2020).
Website stimuli can affect a consumer’s mood and buying behaviour, determining how
long a user engages with a website and whether they make a purchase (Loureiro and
Breazeale, 2016). Poor visual, navigational and informational website design results
in users being irritated (Hasan, 2016). Therefore, good website design and usability
are vital as they can foster longer user engagement, increasing satisfaction and
creating loyal customers (Djamasbi et al., 2010; Brunner-Sperdin et al., 2014). When
consumers are satisfied with the information provided by fashion websites, it
generates consumer trust in that brand (Loureiro et al., 2018). Indeed, research shows
that a retailer’s website design has an even greater impact on purchasing than
customer service does in stores (Hasan, 2016). Therefore, existing research
demonstrates the importance of effective website design in retaining and satisfying
consumers. However, no research to date has uncovered what website design stimuli
capture consumers’ attention across the holistic website when shopping online, why
they capture attention and how consumers actually use the website. The majority of
website design studies are based on quantitative surveys which do not explain how
consumers feel about the website in-depth, nor do they allow us to see consumers’
natural behaviour on holistic websites. The present study will fill this gap.
Existing eye-tracking studies use screenshots to represent websites (e.g. Djamasbi et
al., 2010) or simulations showing one page or section (e.g. Cyr and Head, 2013;
Cortinas et al., 2019) rather than live websites. Websites are interactive and much
more complex than static images. Thus, the same findings cannot be applied when
people look at a picture to when they look at a website. It is important to investigate
consumers’ whole website experience as design stimuli are not perceived as isolated
features, but as a combination of stimuli that contribute to the online shopping
experience (Pentina et al., 2011). As consumers view the website as part of a
continuous, integrated experience, the shopping experience should be researched
from a holistic perspective (Ballantine et al., 2015). However, there is a lack of
research investigating consumers’ perceptions of online environments holistically
7
(Brunner-Sperdin et al., 2014). Extant research has not considered consumers total
shopping experience online (Pham and Ahammad, 2017). The majority of eye-tracking
research on retailers’ websites have focused on the homepage (e.g. Djamasbi et al.,
2011; Huddleston et al., 2015; Espigares-Jurado et al., 2020). However, if a consumer
is directed to the website via a search engine or another site they may not see the
homepage, landing straight on a product page (Demangeot and Broderick, 2010).
Therefore, it is more appropriate to investigate the website as a whole, as opposed to
just the homepage, to achieve more realistic findings showing how websites are
navigated and experienced (Demangeot and Broderick, 2010). Cortinas et al. (2019)
call for future research to explore how consumers’ attention on text and images differs
throughout the different stages of the shopping process. By analysing consumers’
behaviour from their first fixation on the homepage all the way to the checkout,
researchers can investigate stimuli that help or hinder the shopper journey (Wong et
al., 2014). The present study researches how consumers behave during their whole
shopping journey, tracking participants’ eye movements whilst they are browsing in
real-time, thus, taking a holistic approach, filling this gap in the literature.
Furthermore, retail website designs may not necessarily produce the same responses
or provide the same experiences for consumers when they are shopping for ‘search’
or ‘experience’ products. ‘Experience’ products are evaluated on affective criteria that
are subjective or emotional, whereas ‘search’ products are evaluated on cognitive
criteria that are objective or rational (Jourdan, 2001). Thus, ‘experience’ products,
such as clothing, may generate a different type of shopper journey than ‘search’
products due to their complexity. Therefore, e-commerce studies based on ‘search’
products cannot necessarily be generalised to fashion retail websites. For example,
Vahie and Paswan (2006) state that their findings on grocery stores may not be
applicable to clothing stores because the value and importance of clothes is different
from the value and importance of grocery items. Furthermore, Hassanein and Head
(2005) found that websites selling clothes benefit from higher levels of social presence,
and that socially rich design created positive feelings. However, websites selling
headphones did not facilitate a positive response as the socially rich presentations did
not match the information requirements, making them seem forced and inappropriate
(ibid). Yet, many eye-tracking studies focus on ‘search’ products, such as plants
8
(Huddleston et al., 2015), highlighting the need for more eye-tracking studies on
‘experience’ product websites.
Studies that have investigated fashion retail websites using eye-tracking have
compared user responses to hedonic and utilitarian zones of product pages (Cyr and
Head, 2013) and how consumers interact with product presentation features
(Boardman and McCormick, 2019). Yet Cyr and Head, (2013) focused on the product
information page and Boardman and McCormick (2019) just on product presentation
features such as product images, videos and the zoom function, as opposed to the
holistic website. Eye-tracking has been used to investigate how consumers use
smartphones for fashion shopping (Tupikovskaja-Omovie and Tyler, 2020). However,
Tupikovskaja-Omovie and Tyler (2020) focused on a mobile site, on which consumers
shop and view items differently due to the size and nature of the device, and they were
interested in mapping the consumer journey rather than exploring consumers’
responses to the website design. Tupikovskaja-Omovie and Tyler (2020)
acknowledged their small sample (14 and 16 participants), calling for future research
to be conducted with a larger sample. The present study will build on this to provide
an understanding about why consumer attention is placed on certain design stimuli
and how they feel about the holistic website design when shopping on a
laptop/desktop. As laptops are the main device used when shopping for fashion online
(68% of people use laptops, only 41% use smartphones) this study is warranted
(Mintel, 2020).
Cortinas et al., (2019) used eye-tracking and a survey to investigate how attention can
vary on retail web pages according to different purchasing tasks. However, they
focused on how the attention differed on simulated websites according to the task.
This provides interesting insights but, again, does not provide an understanding about
why consumers behave this way and their attention during a more exploratory
shopping session on a real live website. Hence, no study has researched consumer
behaviour across a fashion retail website holistically. This rich set of qualitative data
is missing from the extant literature. Indeed, Tupikovskaja-Omovie and Tyler (2021)
call for future research to provide qualitative insights into consumers responses to
fashion retailers’ websites, especially when combined with eye-tracking data. Extant
literature details causal relationships between attitudes, satisfaction and purchase
9
intention on website design, but there is a lack of research regarding attention and
consumers’ cognitive and affective responses to fashion retailers’ website design and
their holistic online shopping experience. The present study will fill this gap.
Attention
Attention implies that a user focuses their thoughts on a particular stimulus (Wedel
and Pieters, 2008b). Thus, it is only if a user applies their mind to a stimulus that it
captures their attention. Visual attention is important as it represents information
processing (Wedel and Pieters, 2008b). Users’ attention is prioritised to areas of
information that are considered relevant to their goals and help them complete their
task (Wedel and Pieters, 2008a). Therefore, the amount of attention received indicates
the amount of cognitive processing required, with more complex items receiving more
attention (Scott and Hand, 2016).
Eye-tracking measures people’s viewing patterns and can be used to determine
consumer attention and subsequent cognitive activities when interacting with a
website (Wong et al., 2014). This facilitates a better understanding about which design
stimuli attract attention and those which are not seen. Consumers’ attention is useful
for practitioners to help them understand and manage the complicated consumer
shopping journey (Cortinas et al., 2019). It is essential for retailers to capture
consumer attention via their website design in order to direct them to information or
cues that will lead to a purchase (Huddleston et al., 2018). If products and information
are not obviously displayed, users may abandon their shopping baskets as the website
design does not capture their attention (Wong et al., 2014).
According to the visual marketing attention theory, attention can be allocated as a
result of either ‘bottom-up’ or ‘top-down’ factors (Wedel and Pieters, 2008a). Bottom-
up factors are visual characteristics, such as a stimuli’s size or shape (Orquin &
Mueller Loose, 2013; Meißner & Oll, 2019). Top-down factors are goal-driven and
relate to that person’s expectations, objectives and emotions rather than the layout of
the webpage (Scott & Hand, 2016; Imamoglu et al., 2018; Cortinas et al., 2019).
Fixations represent the type of information sought by users and its relevance to the
task at hand (Huddleston et al., 2018). Therefore, eye-tracking can be used to
measure both bottom-up and top-down attention. Yet, there is a paucity of research
10
focusing on bottom-up factors and their role in capturing attention, an aspect that eye-
tracking research enables us to explore further (Huddleston et al., 2015). The present
study will investigate both bottom-up and top-down attention through the triangulation
of eye-tracking and interviews, gathering a rich set of data. This will provide a novel
contribution to the literature as the interplay of both bottom-up and top-down attention
on a holistic website has not yet been explored.
Earlier eye-tracking studies advocated that users view websites in the shape of a letter
‘F’ (e.g. Buscher et al. 2009). However, later studies found that it was text-based web
pages that were more likely to receive an F-shaped viewing pattern (Sutcliffe and
Namoun, 2012). More recently, Scott and Hand (2016) found that users tend to view
Facebook profiles in a ‘Z’ or an ‘L’ pattern. Whilst this is interesting, social media sites
have very different layouts and purposes to retail websites and so these findings may
not be generalisable. No study has investigated consumers’ attention across a holistic
fashion retail website and how that attention may vary on the different types of web
pages or whether it is more formulaic as prior research suggests. The majority of eye-
tracking research is focused on a micro level, investigating very specific aspects such
as product packaging, price or sign information (Huddleston et al., 2018). In their
literature review of eye-tracking and retail marketing studies Huddleston et al., (2018)
identified a lack of eye-tracking research focusing on the wider picture, and therefore
called for future eye-tracking research to consider the whole shopping experience.
The present study contributes to knowledge by filling this gap in the literature.
Theoretical Framework: S-O-R Model
This study explored attention, cognitive and affective responses towards a fashion
retailer’s website when shopping online as well as the behavioural outcomes through
the theoretical lens of the Stimulus-Organism-Response (S-O-R) model. The S-O-R
paradigm stems from environmental psychology and advocates that the environment
affects the emotional state of the individual, which impacts their behaviour (Mehrabian
and Russell, 1974). The S-O-R framework has been used in many website design
studies to gain an understanding of how online environmental cues affect consumers’
responses, and by several eye-tracking website design studies in particular (e.g. Cyr
and Head, 2013; Jai et al., 2014; Cortinas et al., 2019). Thus, it is a reliable model to
use in this research and methodological context. Furthermore, Huddleston et al.,
11
(2018) call for future eye-tracking research to use the S-O-R model as a theoretical
frame to investigate attention in different retail contexts as well as the
mediating/moderating role of top-down and bottom-up factors when consumers are
shopping. The present study fills this gap in the literature, extending existing research
by examining how the holistic website design (Stimulus) affects consumers’ internal
states (Organism: visual, cognitive and affective), and how that affects their
behavioural outcomes (Response: approach/avoidance behaviour) using eye-tracking
and qualitative interviews to gain these insights.
Method
This research pursued a multi-method approach consisting of eye-tracking and
qualitative semi-structured interviews to investigate consumer behaviour on a fashion
retail website. Eye-tracking provides an objective measure of consumers’ reactions to
a website through their eye movements (Djamasbi et al., 2010). This facilitates an in-
depth analysis of their shopping journey, as unconscious actions and aspects that they
may not be able to describe are recorded and analysed. The analysis of observational
data is very valuable but a second method should be used alongside it in order to
ensure that other information and the effects of the online experience are captured too
(Cortinas et al., 2019). Therefore, qualitative semi-structured interviews were
conducted to gather rich data on consumers’ thoughts and feelings towards the
website. 6 pilot studies were performed to test the reliability and validity of the
research, as well as the research design and procedure. Ethical approval was granted
by the university ethics committee. Participants were given full disclosure of the
purpose of the study beforehand and signed informed consent forms. Participants
were told that they could withdraw from the study at any time. All participant data was
collected and stored anonymously on a password protected file.
Sample
A non-probability purposive sample of 52 regular users of the website (aged 20-70,
mean age=46), was selected to provide a representative reflection of the retailer’s
target demographic. The sample size is comparable to other eye-tracking studies on
websites (Cyr and Head, 2013; Cortinas et al., 2019; Wang et al., 2020; Deng and Gu,
2021) and ensured that saturation point was reached in the interviews. An all-female
sample was chosen as this was who the retailer targeted, justified by the fact that more
12
women (64%) than men (56%) purchase clothes online (Statista, 2019). A Love2Shop
voucher was provided as an incentive. Participants were required to have purchased
from the website within the last 3 months to ensure that they were familiar with the
design. Using real customers enabled the researchers to uncover any frustrations that
they experienced with the website design, providing the best basis for improvement
for retailers (Tupikovskaja-Omovie and Tyler, 2020), adding ecological validity,
increasing data validity and differentiating it from other eye-tracking studies with
student samples (Djamasbi et al., 2010; Scott and Hand, 2016; Cortinas et al., 2019;
Deng and Gu, 2021).
1. Eye-tracking Study
Eye-tracking technology was used to track consumers’ online shopping journey by
recording eye fixations and cognitive processing in real-time. A video-based infrared
eye-tracker, Tobii TX 300, with a 300Hz sampling rate, was used. The eye-tracker
records users’ fixations in an unobtrusive manner, operating remotely, not requiring
participants to take off glasses, making the experiment more natural, increasing
validity. Participants were positioned approximately 60-65cm away from the screen
and calibrated to ensure that their gaze and fixations were accurately recorded. After
calibration, participants read the on-screen instructions telling them to simply shop on
the retailer’s website as they would do normally, looking at items that interested them.
Participants pressed the space bar to launch the website and stopped when they felt
like they had finished shopping. The rationale behind this was that literature suggests
that eye-tracking experiments need to be designed in a natural way with minimal
interruptions when the participant is on the website (Tupikovskaja-Omovie and Tyler,
2021). The eye-tracking lasted a minimum of 5 and maximum of 25 minutes.
This study uses the eye-mind hypothesis, which suggests that what people look at is
the same as what they think about (Just and Carpenter, 1980). This implies that eye
fixations are equated to attention and cognitive processing. Users’ fixations were
analysed to ascertain where participants looked, with a fixation defined as 250
milliseconds (Guo et al., 2013). Fixations are an important indicator of decision-making
(Deng and Gu, 2021). Users’ fixation count and durations were analysed through the
generation of gaze replay videos (screen recordings containing the participant’s gaze
behaviour overlaid on the video), which illustrate the user’s sequence of fixations and
13
provides an insight into the user’s visual behaviour on dynamic content, such as
across several web pages (Wong et al., 2014). In order to visualise the results, heat
maps were created, which show the distribution and concentration of participants’
attention through different colours. Heat maps operate on a traffic light system, with
red areas those that gained the most attention and green areas which received the
least attention, whereas areas with no colour received no attention.
2. Qualitative Semi-Structured Interviews
The eye-tracking test was followed by a semi-structured interview to gain further
insights into the online shopping experience and participants responses to the website
design. The website was open with different pages being shown whilst the interview
was conducted and used as a prompt to discuss participant’s regular shopping
journey, allowing them to click on anything to illustrate their point. The rich qualitative
data sets allowed for patterns and clusters regarding the website design and
consumers shopping journey to emerge organically. The interview guide was
structured according to main, probes, and follow-up questions based on the holistic
website, the main web pages (homepage, trends sections, product listing page,
product information page) and the participant’s online shopping journey. Interviews
lasted on average 30-50 minutes. Once the interviews had been conducted all were
transcribed verbatim and data analysis began by reading and re-reading the
transcripts to identify the preliminary codes (Licsandru and Cui, 2019). The web pages
visited by participants were used as the main themes as well as anything that emerged
regarding the holistic website, such as customisation. The codes were then organised
into sub-codes to further analyse the data and understand the key findings for all the
website design stimuli (Saunders et al., 2015). The researchers conducted multiple
coding cycles, first individually, before discussing any discrepancies of emerging
themes and patterns, which were then carefully looked at. All codes were evaluated
and compared across all interviews (Licsandru and Cui, 2019).
Results
This study investigated consumers’ attention, cognitive and affective responses as
well as their behaviour on a fashion retail website. The eye-tracking and interview data
are analysed below. The interview quotes presented are the ones that typified
participants responses, the ‘power quotes’, which are the most compelling data that
14
effectively illustrate the main point and are, therefore, the most appropriate ones to
use in the main body of the paper (Pratt, 2009).
Figure 1 illustrates the number of times different web pages were visited overall
throughout all participants’ shopping journeys:
Figure 1 Number of Times Each Type of Web Page Visited
Figure 2 depicts the amount of time spent on average by each participant on the
different types of web pages throughout participants’ shopping journeys:
15
Figure 2 Average Amount of Time Spent on Each Web Page
Figures 1 and 2 demonstrate that the product listings page was the most frequented,
totalling 356 visits, with an average time spent of 28 seconds. This was followed by
the product information page, visited 246 times with an average time spent of 20
seconds. Only two other types of pages were visited; the features page (109 times,
average time spent: 8 seconds) and the homepage (visited 55 times, only 3
revisited it after initially landing on it, average time spent: 6 seconds). Therefore,
across the whole website, participants spent the least amount of time on the
homepage. Eye-tracking and interview data revealed that when landing on the
homepage consumers go straight to the top left-hand drop-down menu to access the
category that they want, exemplified by P.9:
“I wouldn’t spend that long on the homepage, I would just go off it pretty
quickly... I know what I want and I just go straight to the top… I’d just get on with
it” (P.9).
This shows that the homepage is just seen as a landing page, not much attention is
paid to the features on it. Data revealed that consumers felt it did not warrant further
exploration as it was not directly related to their shopping goal. Consumer attention
16
(or lack of) on the homepage is therefore primarily influenced by top-down factors as
they go straight to the navigation stimuli in order to access the part of the website that
is useful for their shopping goal.
Inspirational Features
Eye-tracking data show that 12% of participants visited the trend/style feature pages,
such as ‘Get The Look’ or ‘Designers and Brands’. Interviews revealed that
participants did so to get inspiration as a starting point for their shopping journey:
“I like outfits… if there was something for a night out there then you might like
it straight away and then just go for it, you don’t even need to look through…”
(P.42)
Thus, having products and outfits encompassing the latest trend or tailored towards
an occasion (e.g. a wedding) collated together was helpful it saved consumers time,
provided them with ideas and enabled them to browse products that were relevant to
their shopping goal. This is an example of top-down attention as they view inspirational
features to fulfil their shopping goal when shopping for a specific event. With so many
items on fashion websites, some consumers found it preferable to have a selection
already tailored to their needs, rather than having to filter the items down themselves.
Product Listings Page
Eye-tracking data show that the product listings page was the most frequented and
viewed for the longest time. Interviews revealed that this was because consumers
enjoyed browsing products and selecting those that appealed. Figure 3 depicts the
heat map of participants’ attention on the product listings page:
17
Figure 3 Heat Map of All Participants on The Product Listings Page
Figure 3 shows most attention was on the top-centre thumbnail images and the left
side of the page where the filter menu bar resides. When looking at the thumbnails,
18
participants’ fixations focused on the centre of the page. This suggests that products
on the edges are more likely to get missed as consumers keep their eyes focused in
the middle when scrolling as opposed to looking from side-to-side.
Figure 3 shows that the left-hand filter menu received a high amount of attention and
the gaze replays revealed that 77% of participants used it. Interviews revealed that
participants found the large product selection overwhelming and so narrowed it down
when they landed on the page to make it more manageable. As such, consumers are
creating a personalised website:
“It’s just quicker for me, less time for me, and less frustration so I’m more likely
to be happier and buy stuff” (P.38).
Therefore, having customisation features results in less frustration and a better
shopping experience for consumers. Interviews revealed that consumers enjoyed the
process of narrowing their search down to create their own personalised product
selection. This supports the eye-tracking data which showed that participants spent
the majority of their time on the website engaging in this behaviour.
Eye-tracking revealed that style, length and size, followed by colour, were the options
that received the most attention. This is reinforced by the number of participants that
used each option during the eye-tracking task (Table 1).
Option
Used
Most/
Least
Percentage of
Participants That
Used This Option
Reason Why According to the Semi-
Structured interviews
Size
1st
52%
• Easy
• Confirming Availability
• Time Saving
• Less Frustrating shopping Experience
Style
2nd
48%
• Quicker
• Personalise search
Colour
3rd
32%
• Personalise search
• Saves Time
• Easier shopping experience
19
Length
4th
26%
• Quicker
• Helpful
• Personalise search
Price
=5th
4%
• Would sort by price instead
• Would not use as the search would be too
narrow
Brand
=5th
4%
• Prefer to see all brands
• Would not use as the search would be too
narrow
Design
feature
=5th
4%
• Would not consider at this stage in the
shopping journey (consider on product
information page instead)
New in
6th
2%
• Would not consider at this stage in the
shopping journey (consider on homepage
instead)
Table 1 Eye Tracking & Interview Findings For Filter Menu
Interviews revealed that size was the most popular option because consumers wanted
to avoid the disappointment of seeing unavailable items:
“Just in case I saw something that I really liked and then it wasn’t in my size, I’d
be really annoyed… It makes it a lot quicker and more enjoyable because I’m
not seeing things that won’t fit me and getting upset about it” (P.47)
Thus, as well as avoiding disappointment, being able to narrow their search down by
size made consumers feel that their shopping journey was easier, which in turn made
their shopping experience more enjoyable.
‘Style’ was used for particular occasions:
“…If I wanted something because I was going out, or if it was coming up to
Christmas, or I was going away… I would click on there and then I know that I’m
going to get the sort of thing that I’m looking for…” (P.9).
20
This enabled consumers to “find what (they) want quicker” (P.17), making their
shopping journey more efficient and enjoyable. Similarly, colour was used when
consumers were looking for an item to match something that they already had, or if
they already knew what they wanted to buy (goal-directed shopping). Hence,
narrowing down their search by size, style and colour made the shopping experience
easier and quicker for consumers. This in turn made consumers feel like their shopping
journey was personalised, leading to feelings of enjoyment, which, in turn, resulted in
them having a better shopping experience and more likely to purchase items.
The gaze replay videos demonstrated that ‘design feature’, ‘price’, ‘brand’ and ‘new in’
were rarely used. Interviews revealed that consumers had already made the decision
whether or not they wanted to see the new products prior to landing on this page, and
‘brand’ or ‘design feature’ were things that they would consider later on, explained by
P.39:
“...if I was looking for a brand then I would have already specifically gone to Joe
Browns.... I’m not sure I’d use this design feature… those kinds of things are
not what I’m thinking about before I’ve started looking at dresses… it’s only
after I’ve got an idea would I start thinking about whether it’s going to have
secret support…” (P.39)
Therefore, fashion retailers need to ensure that they are selective in what they include
on the filter options and make sure that they are relevant to that stage in the shopping
journey.
15% of participants used the ‘sort by’ option to organise products from lowest to
highest price, discussed by P.39:
“…I always go straight to price from lowest to highest… so that I’m not over
spending, I am sticking to the minimum budget that I’m allowing myself and it
makes me feel good about not having to spend a fortune to get what I want”
(P.39)
21
Thus, the ‘sort by’ drop-down menu enabled consumers to personalise their search
further, making them feel in control, resulting in a more enjoyable shopping
experience.
Product Information Page
Most attention on the product information page was on the colour and size drop-down
menus (right side), followed by the product image (left side). This is illustrated in the
heat map of all participants (Figure 4). The mouse clicks have been included to show
that people zoomed-in and looked at alternative images, as well as clicked on the size
and colour drop-down menus.
Figure 4 Heat Map of All Participants on Product Information Page
These findings are reinforced by the gaze replay videos as participants spent the
majority of their time looking at and zooming-in on the product images and at the
alternative colours available. Figure 5 portrays the eye-tracking total visit duration
statistics, demonstrating the amount of attention spent on the product images in
particular.
22
Figure 5 Total Visit Duration on The Product Information Page Design Stimuli
Figure 5 shows that participants spent an average of 30 seconds looking at and
interacting with the product images and 12 seconds using the size and colour drop-
down menus. This is supported by the interviews, with the typical product information
page experience summarised by P.11:
“…what I do straight away is go to my size and see if they’ve got it in my size…
It… tells you what the material is… I would then just zoom it in and then go up
and down on it…” (P.11)
This reinforces the eye-tracking data which showed that the first thing that participants
did was check the size availability in order to pre-empt disappointment if their size was
not in stock. This demonstrates top-down attention as the size drop-down menus
fulfilled participants objectives. Yet, eye-tracking data show that participants’ first
fixation was on the product image, taking an average of 1 second for
participants to fixate on it. This is a clear example of bottom-up factors influencing
attention as participants wanted to check their size first but got distracted by the image.
The size drop-down menu received participants’ average second fixation (3.6
23
seconds to fixate on). Participants divided their attention between the two design
stimuli, clearly demonstrating the interplay between bottom-up and top-down attention.
Having different colourways presented for each garment was important to consumers.
They liked how the image changed when they clicked on different colours as it enabled
them to facilitate comparisons, often resulting in alternative or additional purchases.
However, the heatmap (Figure 4) shows that minimal attention was paid to the product
description and product detail. The interviews revealed that consumers only looked at
the practical information (material, length, care instructions) quickly and the product
description (sentences describing the style and trend) was perceived to be
unnecessary. For example:
“…there’s too much information… they don’t need the fashiony bit… I wouldn’t
even read that… I’m more interested in what length is it, is it washable, what
sizes have you got” (P.20)
Interviews revealed that product descriptions were not perceived as helpful because
consumers were already attracted to the product and wanted to know the practical
details to assess its suitability. This highlights a sustainability issue as the flexibility of
free returns has resulted in consumers not spending long on their decision-making
process and sending for items to try-on and decide at home, hugely increasing
retailers’ carbon footprint.
Nevertheless, consumers wanted more information about the fit of the garment:
“I need a really real description… it’s explaining here about the neckline, the
fact that it pulls in at the middle with an elasticated waist, where it falls to, those
are really important… It helps me to know what I’m getting…” (P.39)
Thus, to help consumers in their evaluation of clothes online, retailers should provide
details of how the garment fits, presented concisely. Consumers want fabric
information (e.g. stretchy, sheer), length and significant details (e.g. exposed zip).
Including this information will increase consumer confidence about their purchase.
24
Eye-tracking showed that 85% of participants looked at the product recommendations
but only 29% clicked on them. Interviews revealed that participants liked product
recommendations because they provide ideas and inspiration:
“…I’m like what l am I going to accessorise it with, so having some suggestions
on that would be really useful… That might encourage me to spend more money
if I find things that go with it, and get it all in one go, that would be brilliant…”
(P.39)
If an item was unavailable, participants looked at the product recommendations for
anything similar. Having complementary or similar items suggested was helpful,
resulting in consumer satisfaction and the likelihood of purchasing additional items.
Yet, the participants that fixated on product recommendations only did so briefly, with
minimal cognitive processing occurring. This may be because the items suggested
were not accurate matches for the item being viewed, as P.23 illustrates:
“…the things that are on there are so random, there’s no relation to the item that
you’re looking at… it’s horrendous… (I want them to be) Linked to the actual
outfit that they’re wearing. Or similar items… more thought put into it…” (P.23).
Therefore, fashion retailers must provide accurate product recommendations.
Presenting items that are unrelated produce feelings of annoyance and frustration,
resulting in avoidance behaviour. Interviews revealed that participants did not like the
terminology, ‘people who viewed this item also viewed’ as “it’s kind of a really
obvious attempt to get you to buy more…” (P.27). They were not interested in what
other people liked, preferring the website to be personalised, with items recommended
based on their browsing and purchasing history.
Holistic Website Behaviour
Eye-tracking showed that participants added items to their basket whilst browsing,
replicating an offline shopping experience, selecting anything of interest, then
evaluating at the end. Participants made a curated wish list and then went through
25
products in detail afterwards, thereby splitting their shopping journey into two stages.
As such, consumers use the basket as a “storage area” (P.35) and found it helpful
seeing items grouped together for evaluation:
“...when you actually see them summarised close together, you can see that
that’s actually a bit close to that so I can take that one out” (P.7)
Consumers enjoyed this process and found that “time flies” (P.52) when scrolling.
Participants wanted this process to uninterrupted so being able to add items directly
to their bag/wish list on the product listings page was preferable.
Eye-tracking revealed that the main menu bar was primarily used to navigate the
website but 20% of participants used the search bar. Gaze replay videos show that
participants did not use the search bar if they were simply browsing but may use it if
they were looking for a particular item. Words typed were product category (e.g.
jeans), product description (e.g. peplum top) and brand (e.g. UGG). Interviews
revealed that the search bar was used for convenience because it was “simpler” and
“quicker”. Hence, the search bar facilitates an easy shopping experience and saves
time when consumers are goal-directed shopping.
Discussion & Conclusion
This study contributes to knowledge by providing an in-depth understanding of
consumers’ attention and behaviour on a holistic fashion retailer’s website, thereby
addressing a gap in the literature. The study aimed to answer the following research
questions:
RQ1. What do consumers think and feel when shopping on a live fashion retail website
in real-time?
RQ2. What design stimuli do consumers pay attention to when shopping on a fashion
retail website and why?
RQ3. How does consumers’ attention, cognitive and affective responses to the
website design influence their behaviour?
Findings demonstrate that consumers have different viewing patterns on web pages
throughout the shopping journey. For instance, attention is placed towards the top-left
26
of the homepage (to click off it quickly), the top-left and centre of the product listings
page and the centre and centre-left of the product information page. This contradicts
prior literature as participants did not have F-shaped, Z-shaped, or L-shaped viewing
patterns (Buscher et al., 2009; Scott and Hand, 2016). Instead, the present study
shows that attention is influenced by both top-down and bottom-up factors. Thus,
research cannot generalise holistic website viewing behaviour into one formulaic
pattern, it depends on the design stimuli and consumers’ goal/objectives on that page.
The interplay between bottom-up and top-down attention is illustrated clearly on the
product information page, with the image naturally drawing participants’ attention,
receiving their first fixation (bottom-up attention), but their second fixation is directed
to where they want it to go, the size/colour drop down menus, in order to check
availability (top-down attention). Overall, the present study found that top-down
attention is more dominant than bottom-up attention when consumers are shopping
online for fashion items. Consumers are very focused when shopping for fashion, so
although stimuli, such as images, are distracting (bottom-up factors), consumers will
consciously focus their attention on the stimuli that they need to fulfil their objectives,
such as menus, filtering systems and colour/size options (top-down factors).
The study indicates that ‘experience’ product websites may produce different
responses to ‘search’ product websites due to the complexity of the decision-making
and evaluation stages involved. This is particularly evident on the product information
page where the images, sizes and colourways are focused on extensively in order to
evaluate the fit and quality of items, something that would not occur for ‘search’
products. Hence, this research contributes to the literature by demonstrating that
consumers may have different responses to different types of retail websites and may
want different experiences based on the products that they are shopping for. Future
research could explore this further.
The present study also provides a methodological contribution, demonstrating the
need for research to examine how users behave on a live website to observe their
natural behaviour and not just what they self-report. Studies that advocate F-shaped,
Z-shaped and L-shaped viewing patterns, alongside the majority of eye-tracking
studies, are based on static screenshots or simulation websites and, therefore, are not
realistic representations of users’ interaction with websites. For instance, the present
27
study found that consumers’ fixations remained quite central on the product listings
page when scrolling. This contradicts Guo et al. (2013) who found that on a product
listings page, eye movements started in the top left-hand corner and moved down the
page row by row. However, Guo et al. (2013) asked participants to view a static
screenshot, which is not an accurate representation of how consumers interact with a
website. Thus, using a live website has arguably made the results more reliable and
ecologically valid as it objectively captures consumers’ real-time behaviour.
Furthermore, the triangulation of eye-tracking and qualitative methods ensured that
participants’ attention and cognitive processing was interpreted accurately, providing
a rich data set. The value of a multi-methods approach is highlighted here as mono-
methods do not allow for a holistic picture to emerge and may result in misleading
conclusions/assumptions. This demonstrates a valuable methodological contribution
which can be utilised by future research.
Huddleston et al., (2018) call for future eye-tracking research to use the S-O-R
framework to explore the mediating/moderating role of top-down factors and bottom-
up stimuli when consumers are shopping. The present study fills this gap by examining
how the holistic website design (Stimulus) affects consumers’ internal states
(Organism: visual, cognitive and affective), which, in turn, affects their shopping
outcomes (Response: approach/avoidance behaviour) using eye-tracking and
qualitative interviews to gain these insights. The study extends the S-O-R framework,
showing that top-down attention, when provided with personalisation and
customisation features, results in approach behaviour. For example, being able to
narrow their search down by size made consumers feel that their shopping journey
was easier, which in turn made their shopping experience more enjoyable,
encouraging them to spend longer on the site and increase the number of items
purchased. Similarly, having personalised product recommendations resulted in
increased attention and feelings of enjoyment, leading to increased consumer
satisfaction and the likelihood of purchasing a higher number of items. If product
recommendations were not personalised, this resulted in avoidance behaviour.
Tupikovskaja-Omovie and Tyler (2021) found that only 2 out of 7 participants clicked
on the product recommendations and so call for future qualitative research to
investigate how well fashion retailers’ product recommendations meet the
28
requirements of consumers. The present study fills this gap by finding that consumers
wanted personalised product recommendations.
Similarly, customisation features resulted in approach behaviour, as they enabled
consumers to find items efficiently, aiding decision-making. This is surprising as
fashion retail websites contain a lot of dynamic content such as trends pages, but it is
the functional menus that enable consumers to navigate through the website and
customise their search that are the most important. This contradicts Cyr and Head
(2013), who found that participants spent more time looking at the hedonic sections of
a fashion retailer’s website than the utilitarian sections. This study focused on the
product information page and so is not generalisable to the whole website. These
results also contradict survey results from Kaushik et al. (2020) that ‘the latest trends’,
‘style guides’, and ‘celebrity endorsement’ were really important to consumers and
essential for fashion websites to have. Nevertheless, Kaushik et al.’s (2020) study was
based on Indian shoppers’ preferences and highlights there may be differences
between countries and cultures, an aspect that future research could investigate. This
also highlights the advantage of using eye-tracking as a method as consumers may
report that they want/do one thing in surveys but in reality, their behaviour suggests
otherwise. The present study found that consumers’ valued features that made their
shopping experience easier, more convenient and quicker. They wanted minimal
clicking and the ability to create a customised product selection to suit their
requirements, creating a more enjoyable shopping experience. Hence, the concept of
convenience was enjoyable, and thus, a trait which has been traditionally viewed as
utilitarian now appears to contain hedonic value. Further investigation of this is
warranted.
The study contributes further novel findings to literature, namely that the product
listings and product information pages were the most important pages, due to the
amount of time spent and the frequency of visits. Although research has found that
the product listings page can impact consumers’ decision-making and purchase
intention (Schmutz et al., 2010), no studies have explored consumers’ thoughts and
feelings towards the product listings page in-depth. The present study fills this gap.
This study disagrees with previous research that the homepage is the most important
page on a retailer’s website (Nielsen and Tahir, 2001; Tzanidou et al., 2006). This
29
suggests that consumer behaviour has changed as e-commerce has developed and
the homepage is now just perceived as a landing page. Further research could
investigate how retailers could encourage consumers to explore the homepage
further.
Nowadays, with information being presented in bitesize chunks on social media,
consumers do not want to spend time reading. The present study found that fashion
descriptions were not perceived as helpful, consumers just wanted the key practical
information to be presented clearly and concisely in order to acquire it in a glance.
These findings contradict previous research that high-quality product descriptions
have a positive effect on cognitive product involvement (Mou et al., 2019) and the call
to provide higher quantity product information in the form of text descriptions (Chang
et al., 2016). The findings highlight a shift in consumer behaviour so further research
could investigate different forms of information provision on fashion retail websites.
The depth of understanding provided into consumer attention and behaviour on a
fashion retail website in this article is of value to marketers and academics studying
website design, as the findings and conclusions drawn can be understood in the wider
context of shopping online for experience products, filling a gap in the literature.
Managerial Contributions
The study provides fashion retailers with the knowledge of how consumers behave on
their website and what attracts their attention, which they can use to inform their
website design. For instance, on the product listings page, attention focused on
products towards the centre of the page. This suggests that products on the edges
are more likely to get missed. Therefore, fashion retailers could provide rows of two
products to ensure that they are seen. Consumers added items to their basket as they
were browsing, creating a curated wish list. Consumers want this process to be as
smooth as possible so being able to add items directly to their bag/wish list on the
product listings page would be effective.
The product listings page is the most important, followed by the product information
page, in terms of time spent and frequented, and so these are the pages that fashion
retailers should invest in to maximise sales and the customer experience. In particular,
30
retailers should invest in features that enable consumers to customise their search.
Consumers found the large product selection overwhelming and so narrow it down to
make it more manageable. Fashion retailers need to ensure that they are selective in
what they include on the filter options and make sure that they are relevant, primarily
size, style and colour. ‘Design feature’, ‘price’ and ‘brand’ were not considered helpful
at this stage.
Using blocks of text to provide fashion information is not reflective of the modern
consumer. Consumers want to see key practical details presented concisely and more
information about how the garment fits, as well as fabric information (e.g. stretchy,
sheer), length and significant details (e.g. exposed zip). Including this information will
increase consumer confidence about their purchase. Having alternative colour options
on the product information page would also encourage alternative or additional
purchases.
Fashion retailers should also invest in making the website personalised for each
consumer. Consumers want accurate personalised product recommendations in the
form of ‘Similar Items’ or ‘Outfit Suggestions’ based on their own style, browsing and
purchasing history. Having personalised product recommendations resulted in
consumer satisfaction and the likelihood of purchasing a higher number of items.
Retailers could investigate how to enhance personalisation using Artificial Intelligence.
Fashion retailers should provide product listings pages for products dedicated to the
latest trend or tailored towards an occasion (e.g. a wedding). With so many items on
fashion websites, some consumers found it preferable to have a selection already
tailored to their needs, rather than having to filter items themselves. Including this
provides consumers with ideas and makes the goal-directed shopping experience
more enjoyable.
The practical implications of this study have been realised as the findings were
presented to the fashion retailer and recommendations made based on the results,
which have since been implemented, and further research is being conducted by the
retailer on how to create more personalised experiences for consumers based on
31
these findings. This emphasises the knowledge exchange and impact that the results
have already had and the managerial contribution made by this study.
Research Limitations and Future Research
This study was conducted in the UK and so used a UK-based sample, but the results
may be different for other areas of the world. Future studies could investigate if there
are cultural differences in responses to holistic fashion retail websites. An all-female
sample was used due to the website that the study was based on. Nevertheless, this
was representative of a wide demographic and was appropriate as the study aimed to
explore how regular consumers behaved. Future research could investigate if there
are any differences between men and women, or between age groups, in attention
and behaviour when shopping online.
As this study found that the product listings page and the product information page
were the more important pages, future research could be conducted to investigate
different designs of these pages. The study shows that consumers are not reading
product descriptions in the form of blocks of text so further research could explore
whether it would be more effective to show product information visually as opposed to
verbally.
Findings demonstrates that customisation and personalisation were very important to
consumers. Therefore, future research could be conducted to investigate how
websites can be designed to better suit contemporary consumers, maximising
customisation and personalisation features, and see how new technologies, such as
AI, could enhance the shopping experience.
References
Ballantine, P., Parsons, A. and Comeskey, K. (2015), “A Conceptual Model of the
Holistic Effects of Atmospheric Cues in Fashion Retailing”, International
Journal of Retail & Distribution Management, Vol. 43 No. 6, pp.503-517.
Batra, R. and Sinha, I. (2000), “Consumer
‐
level factors moderating the success of
private label brands”, Journal of Retailing, Vol. 76 No. 2, pp.175‐91.
32
Boardman, R. and McCormick, H. (2019), “The Impact of Product Presentation on
Decision Making and Purchasing”, Qualitative Market Research: An
International Journal, Vol. 22 No. 3, pp.365-380.
Bock, G., Lee, J., Kuan, H., and Kim, J., (2012), “The progression of online trust in the
multi-channel retailer context and the role of product uncertainty”, Decision
Support Systems, Vol. 53, Issue 1, pp.97-107,
Brunner-Sperdin, A., Scholl-Grissemann, U.S. and Stokburger-Sauer, N.E. (2014),
“The relevance of holistic website perception. How sense-making and
exploration cues guide consumers’ emotions and behaviors”, Journal of
Business Research, Vol. 67, pp.2515-2522.
Buscher, G., Cutrell, E. and Morris, M., (2009), “What Do you See When You’re
Surfing? Using Eye Tracking to Predict Salient Regions of Web Pages”, CHI,
ACM Press, New York, April 4-9 2009, pp.21-30.
Chang, S., Chih, W., Liou, D. and Yang, Y., (2016), “The Mediation of Cognitive
Attitude for Online Shopping”, Information Technology & People, Vol. 29 No. 3,
pp.618-646.
Chen, Y., Lu, Y., Gupta, S. and Pan, Z. (2019), “Understanding “Window” Shopping
and Browsing Experience on Social Shopping Website: An Empirical
Investigation”, Information Technology & People, Vol. 33 No. 4, pp.1124-1148.
Cian, L., Krishna, A., and Elder, R. (2014), “This logo moves me: dynamic imagery
from static images”, Journal of Marketing Research, Vol.51 No.2, pp. 184-197.
Citrin, A.V., Stem, D.E., Spangenberg, E.R., and Clark, M.J., (2003), “Consumer need
for tactile input: An internet retailing challenge”, Journal of Business Research,
Vol. 56 No. 11, pp.915-922.
Cortinas, M., Cabeza, R., Chocarro, R. and Villanueva, A. (2019), “Attention to online
channels across the path to purchase: an eye-tracking study”, Electronic
Commerce Research and Applications, Vol. 36, p.100864.
Cyr, D., and Head, M., (2013), “The Impact of Task Framing And Viewing Timing on
User Website Perceptions and Viewing Behaviour”, International Journal of
Human-Computer Studies, Vol. 71 No. 12, pp.1089-1102.
Darby, M.R., and Karni, E. (1973), “Free Competition and the Optimal Amount of
Fraud”, Journal of Law and Economics, Vol. 16 No. 1 pp.67–88.
33
Demangeot, C., and Broderick, A., (2010), “Consumer Perceptions of Online Shopping
Environments: A Gestalt Approach”, Psychology & Marketing, Vol. 27 No. 2,
pp.117–140.
Deng, M., and Gu, X., (2021), “Information acquisition, emotion experience and
behaviour intention during online shopping: an eye-tracking study”, Behaviour
& Information Technology, Vol. 40 No.7, pp.635-645.
Djamasbi, S., Siegel, M. and Tullis, T. (2010), “Generation Y, Web Design, And
Eyetracking”, International Journal of Human-Computer Studies, Vol. 68 No.
5, pp.307–323.
Djamasbi, S., Siegel M. and Tullis T. (2011), “Visual Hierarchy and Viewing Behavior:
An Eye Tracking Study”, Human-Computer Interaction. Design and
Development Approaches, Lecture Notes in Computer Science, Vol. 67 No.
61, pp.331-340.
Djamasbi, S. (2014), “Eye Tracking and Web Experience”, AIS Transactions on
Human-Computer Interaction, Vol. 6 No. 2, pp.37-54.
Ekelund, R.B.,Jr., Mixon, F.G.,Jr., and Ressler, R.W., (1995), “Advertising and
Information: An Empirical Study of Search, Experience and Credence Goods”,
Journal of Economic Studies, Vol. 22, pp.33-43.
Espigares-Jurado, F. Muñoz-Leiva, F., Correia, M.B., Sousa, C.M.R., Ramos, C.M.Q.,
and Faísca, L., (2020), “Visual Attention to the Main Image of a Hotel Website
Based on its Position, Type of Navigation and Belonging to Millennial
Generation: An Eye Tracking Study”, Journal of Retailing and Consumer
Services, Vol. 52, pp.101906.
Grant, R., Clarke, R.J., and Kyriazis, E., (2007). “A Review of Factors Affecting Online
Consumer Search Behaviour from an Information Value Perspective”, Journal
of Marketing Management, Vol. 23 No. 5-6, pp.519-533.
Guo, X., Gao, J., Zeng, Y. and Zhang, Z., (2013), “Exploring Offline Browsing Patterns
to Enhance the Online Environment”, A. Marcus (Ed.): DUXU/HCII 2013, Part
IV, LNCS 8015, pp.183–192, Springer-Verlag: Berlin Heidelberg.
Gupta, A., Su, B. and Walter, Z., (2004), An Empirical Study
of Consumer Switching from Traditional to Electronic Channels: A Purchase-
Decision Process Perspective, International Journal of Electronic Commerce,
Vol. 8 No.3, pp.131-161.
34
Gupta, P., Harris, J., (2010), “How e-WOM recommendations influence product
consideration and quality of choice: A motivation to process information
perspective”, Journal of Business Research, Vol. 63 No. 9-10, pp.1041-1049.
Hasan, B. (2016), “Perceived Irritation in Online Shopping: The Impact of Website
Design Characteristics”, Computers in Human Behavior, Vol. 54, pp.224-230.
Hassanein, K., and Head, M., (2005). “The Impact of Infusing Social Presence in the
Web Interface: An Investigation Across Product Types”, International Journal
of Electronic Commerce, Vol. 10 No. 2, pp.31-5.
Hong, Y.(K). and Pavlou, P.A., (2014), “Product Fit Uncertainty in Online Markets:
Nature, Effects, and Antecedents”, Information Systems Research, Vol. 25
No. 2, pp.328-344.
Hootsuite (2021), We are social “Digital 2021”, available at:
https://wearesocial.com/digital-2021
Huddleston, P., Behe, B.K., Minahan, S. and Fernandez, R.T. (2015), “Seeking
attention: An eye tracking study of in‐store merchandise displays”,
International Journal of Retail and Distribution Management, Vol. 43 No. 6,
pp.561‐574.
Huddleston, P.T., Behe, B.K., Driesener, C, Minahan, S., (2018), “Inside-outside:
Using Eye-Tracking to Investigate Search-Choice Processes in the Retail
Environment”, Journal of Retailing and Consumer Services, Vol. 43, pp.85-93.
Imamoglu, N., Shimoda, W., Zhang, C., Fang, Y., Kanezaki, A., Yanai, K., and Nishida,
Y., (2018), “An Integration of Bottom-Up and Top-Down Salient Cues on RGB-
D Data. Signal, Image And Video Processing”, Vol. 12 No. 2, pp.307-314.
Jai, T., O’Boyle, M., and Fang, D., (2014), “Neural Correlates of Sensory-Enabling
Presentation: An Fmri Study of Image Zooming and Rotation Video Effects on
Online Apparel Shopping”, Journal of Consumer Behaviour, Vol. 13, pp.342–
350.
Jourdan, P., (2001), "Search or Experience Products: an Empirical Investigation of
Services, Durable and Non-Durable Goods", in AP - Asia Pacific Advances in
Consumer Research Volume 4, eds. Paula M. Tidwell and Thomas E. Muller,
Provo, UT: Association for Consumer Research, pp.167-174.
Just, M.A. and Carpenter, P.A. (1980), “A theory of reading: From eye fixations to
comprehension”, Psychological Review, Vol. 87 No. 4, pp.329-354.
35
Kaushik, V., Khare, A., Boardman, R. and Blazquez, M. (2020), “Why Do Online
Retailers Succeed? The Identification and Prioritization of Success Factors for
Indian Fashion Retailers”, Electronic Commerce Research and Applications,
Vol. 39, p.100906.
Kim, J. and Lennon, S. (2010), “Information available on a web site: effect on
consumers’ shopping outcomes”, Journal of Fashion Marketing and
Management: An International Journal, Vol. 14 No. 2, pp.247-262.
Li, H., Daugherty, T., Biocca, F., (2001), “Characteristics of virtual experience in
electronic commerce: A protocol analysis”, Journal of Interactive Marketing,
Vol.15 No. 3, pp.13-30.
Licsandru, T.C. and Cui, C.C. (2019), “Ethnic marketing to the global millennial
consumers: Challenges and Opportunities”, Journal of Business Research,
Vol. 103, pp.261-274.
Loureiro, S.M.C. and Breazeale, M. (2016), “Pressing the buy button: Generation Y’s
online clothing shopping orientation and its impact on purchase”, Clothing and
Textiles Research Journal, Vol. 34 No. 3, pp.163-178.
Loureiro, S.M.C., Cavallero, L. and Miranda, F.J. (2018), “Fashion brands on retail
websites: customer performance expectancy and e-word-of-mouth”, Journal
of Retailing and Consumer Services, Vol. 41, pp.131-141.
Mehrabian, A. and Russell, J.A. (1974). An Approach to Environmental Psychology,
MIT Press, Cambridge, MA.
Meißner, M., Oll., J. 2019. The Promise of Eye-Tracking Methodology In
Organizational Research: A Taxonomy, Review, And Future Avenues,
Organizational Research Methods, 22(2), 590-617.
Menon, R.G., Sigurdsson, V., Larsen, N., Fagerstrøm, A. and Foxall, G. (2016),
“Consumer Attention to Price in Social Commerce: Eye Tracking Patterns in
Retail Clothing”, Journal of Business Research, Vol. 69, pp.5008-5013.
Micu, A.C. and Pentina, I. (2015), "Examining search as opposed to experience goods
when investigating synergies of internet news articles and banner ads",
Internet Research, Vol. 25 No. 3, pp.378-398.
Mintel (2020), “Fashion Online: Inc Impact Covid-19”, UK, November 2020, Available
at:
file:///Users/user/Downloads/Fashion%20Online%20Inc%20Impact%20of%2
36
0COVID-19%20-%20UK%20-%20November%202020%20-
%20Executive%20Summary.pdf
Mou, J., Zhu, W., and Benyoucef, M. (2019), “Impact of Product Description and
Involvement on Purchase Intention in Cross-Border E-Commerce”, Industrial
Management & Data Systems, Vol. 120 No. 3, pp.567-586.
Naegelein, P., Spann, M., and Molitor, D. (2019), “The value of product presentation
technologies on mobile vs. non-mobile devices: A randomized field
experiment”, Decision Support Systems, Vol. 121, pp.109-120.
Nielsen, J. and Tahir, M., (2001), Homepage Usability: 50 Websites Deconstructed,
New Riders, Indianapolis.
Orquin, J. L., and Mueller Loose, S., (2013), “Attention and Choice: A Review on Eye
Movements in Decision Making”, Acta Psychologica, Vol. 144 No.1, pp.190-
206.
Pålsson, H., Pettersson, F., and Winslott Hiselius, L., (2017), “Energy consumption in
e-commerce versus conventional trade channels - Insights into packaging, the
last mile, unsold products and product returns”, Journal of Cleaner Production,
Vol. 164, pp.765-778.
Patten, E., Ozuem, W. and Howell, K. (2020), “Service Quality in Multichannel Fashion
Retailing: An Exploratory Study”, Information Technology & People, Vol. 33
No. 4, pp.1327-1356.
Pentina, I., Amialchuk, A. and Taylor, D. (2011), “Exploring effects of online shopping
experiences on browser satisfaction and e‐tail performance”, International
Journal of Retail & Distribution Management, Vol. 39 No. 10, pp.742-758.
Pham, T.S.H. and Ahammad M.F. (2017), “Antecedents and consequences of online
customer satisfaction: a holistic process perspective”, Technological
Forecasting and Social Change, Vol. 124, pp.332-342.
Pratt, M.G., (2009), “From the Editors for the Lack of a Boilerplate: Tips on Writing Up
(and Reviewing) Qualitative Research”, The Academy of Management
Journal, Vol. 52 No. 5, pp.856-862.
Rutgers (2019). “Customer strategy foundation: Search, Experience and Credence
(SEC) analysis determines how customers buy”, Dave Wieneke, Tuesday 29th
January 2019, Available at: https://www.business.rutgers.edu/business-
insights/customer-strategy-foundation-search-experience-and-credence-sec-
analysis
37
Saunders, M, Lewis, P, & Thornhill, A., (2015), Research Methods for Business
Students PDF EBook, Pearson Education, Limited, Harlow. Available from:
ProQuest Ebook Central.
Scott, G.G. and Hand, C.J. (2016), “Motivation Determines Facebook Viewing
Strategy: An Eye Movement Analysis”, Computers in Human Behavior, Vol. 56,
pp.267-280.
Shi, S.W., Wedel, M., and Pieters, F.G.M., (2013). “Information Acquisition During
Online Decision Making: A Model-Based Exploration Using Eye-Tracking
Data.” Management Science, Vol. 59, No.5, pp.1009–1026.
Statista, (2019), “Share of Individuals Who Purchased Clothes and Sports Goods
Online in Great Britain in 2019, by age and gender”. Available at:
https://www.statista.com/statistics/286096/clothes-and-sports-goods-online-
purchasing-in-great-britain-by-demographic/
Schmutz, P., Roth, S., Seckler, M. and Opwis, K. (2010), “Designing product listing
pages – Effects on sales and users’ cognitive workload”, International Journal
of Human– Computer Studies, Vol. 68 No. 7, pp.423–431.
Sun, X., Han, M., Feng, J., (2019), “Helpfulness of online reviews: Examining review
informativeness and classification thresholds by search products and
experience products”, Decision Support Systems, Vol. 124, pp.113099.
Sutcliffe, A. and Namoun A. (2012), “Predicting User Attention in Complex Web
Pages”, Behaviour & Information Technology, Vol. 31 No. 7, pp.679-695.
Tzanidou, E., Minocha, S., Petre, M. and Grayson, A. (2006), “Revisiting Web Design
Guidelines by Exploring Users' Expectations Preferences and Visual Search
Behaviour”, People and Computers XIX — The Bigger Picture, Proceedings
of HCI 2005, pp.421-438.
Tupikovskaja-Omovie, Z. and Tyler, Z. (2020), “Clustering Consumers' Shopping
Journeys: Eye Tracking Fashion M-Retail”, Journal of Fashion Marketing and
Management, Vol. 24 No. 3, pp.381-398.
Tupikovskaja-Omovie, Z., and Tyler, D., (2021), “Eye Tracking Technology to Audit
Google Analytics: Analysing Digital Consumer Shopping Journey in Fashion
M-Retail”, International Journal of Information Management, Vol. 59,102294.
Vahie, A. and Paswan, A. (2006), "Private label Brand Image: Its Relationship With
Store Image And National Brand", International Journal of Retail & Distribution
Management, Vol. 34 No. 1, pp.67-84.
38
Wang, Q., Ma, D., Chen, H., Ye, X. and Xu, Q. (2020), “Effects of Background
Complexity on Consumer Visual Processing: An Eye-Tracking Study”, Journal
of Business Research, Vol. 11, pp.270-280.
Wedel, M. and Pieters, R. (2006), Eye Tracking for Visual Marketing, Foundations and
Trends, in Marketing, Vol. 1, No. 4, pp. 231-320.
Wedel, M. and Pieters, R. (2008b), “A Review of Eye-Tracking Research in Marketing”,
N.K. Malhotra (Ed.), Review of Marketing Research, Emerald Group, Bingley,
West Yorkshire, UK, pp.123-147.
Wong, W., Bartels, M. and Chrobot, N. (2014), “Practical Eye Trackingof the
Ecommerce Website User Experience”, C. Stephanidis and M. Antona (Eds.):
UAHCI/HCII 2014, Part IV, LNCS 8516, pp.109–118, Springer International
Publishing: Switzerland.
