This document provides a literature review on social media advertising strategies employed by fast fashion brands like H&M and Zara and their impact on customer purchase intentions and brand loyalty. It identifies several theories that explain how social media advertising can influence consumer behavior, such as the 4C framework and Hierarchy of Effects model. Popular social media strategies used by fast fashion brands, including display ads, photo and video posting, are also examined. While social media advertising is found to be generally more effective than traditional methods, more research is still needed to understand its effects according to different theories. The review informs the study's methodology to analyze the link between H&M's and Zara's social media strategies and customer outcomes in the UK.
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Abstract
This dissertation analyses the effect of the social media advertising strategies employed by Zara
and H&M on customer reactions such as purchase intention and brand loyalty. Three social
networking services, namely Facebook, Twitter and Instagram have been selected for the
purpose of this study. Primary data was collected from 100 customers of Zara and 100 customers
of H&M by means of self-administered questionnaires. In turn, secondary data was obtained
from websites, empirical articles and journals. The research findings suggest that social media
advertising strategies have a more considerable impact on customer loyalty and attitudes
comparing to traditional media. There is a strong correlation between Zara’s and H&M’s social
media strategies such as display ads on Facebook and photo posting on Instagram and
consumers’ intention to buy. Furthermore, consumers’ loyalty to the fashion brands is predicted
by video posting on Instagram and Twitter. The lack of generalisability is the key limitation of
this project since its outcomes are only relevant to Zara and H&M. The researchers who
investigate social media advertising and its impact on consumer behaviour may be interested in
this dissertation.
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Table of Contents
Chapter 1: Introduction.......................................................................................................................6
1.1. Problem Statement and Research Rationale...............................................................................6
1.2. Study Background.....................................................................................................................6
1.3. Research Aim, Objectives and Questions....................................................................................7
1.4. Significance and Potential Contribution .....................................................................................8
1.5. Research Methods....................................................................................................................8
1.6. Research Limitations.................................................................................................................9
1.7. Structure of the Dissertation.....................................................................................................9
Chapter 2: Literature Review.............................................................................................................10
2.1. Introduction...........................................................................................................................10
2.2. Theories of Customer Behaviour on Social Media.....................................................................10
2.3. Social Media Advertising Strategies Employed by Fashion Retail Brands ....................................13
2.4. Effectiveness of Social Media Advertising in Fashion Retail Industry..........................................17
2.5. Chapter Summary and Conceptual Framework.........................................................................19
Chapter 3: Research Methodology.....................................................................................................22
3.1. Introduction...........................................................................................................................22
3.2. Methodological Framework ....................................................................................................22
3.3. Research Strategies................................................................................................................23
3.4. Data Collection Instruments and Analysis Methods ..................................................................25
3.5. Research Ethics ......................................................................................................................29
3.6. Chapter Summary...................................................................................................................30
Chapter 4: Data Analysis and Findings................................................................................................31
4.1. Introduction...........................................................................................................................31
4.2. Background Data Analysis.......................................................................................................31
4.3. The Effectiveness of Social Media and Traditional Advertising...................................................34
4.4. The Link between Social Media Advertising Strategies and Customer Outcomes........................38
4.5. Summary ...............................................................................................................................46
Chapter 5: Conclusions and Recommendations ..................................................................................47
5.1. Introduction...........................................................................................................................47
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5.2. Concluding the Main Findings .................................................................................................47
5.3. Research Limitations...............................................................................................................50
5.4. Recommendations..................................................................................................................51
References.......................................................................................................................................53
Appendix..........................................................................................................................................61
List of Figures
Figure 1: The Meta-Theoretic Model of Motivation and Personality (3M).............................................12
Figure 2: Conceptual Framework of the Social Media Advertising in the Fashion Retail Context ............20
Figure 3: How OldAre You?(%).........................................................................................................31
Figure 4: What Is You Gender? (%).....................................................................................................32
Figure 5: How Often Do You Purchase Goods Either from Zara or from H&M? (%)................................33
Figure 6: I Am FullyAware of Zara'sand/or H&M's AdvertisingInitiativesonthe MostPopularSocial
Networking Services such as Facebook, Instagram and Twitter (%)......................................................34
Figure 7: The Attractiveness of Zara's and H&M's Online and Traditional Advertising (%)......................35
Figure 8: The Impact of Zara's and H&M's Online and Traditional Advertising on Buying Intentions(%) .37
Figure 9: Photo Posting (%) ...............................................................................................................39
Figure 10: Video Posting (%)..............................................................................................................40
Figure 11: Sponsored Stories (%) .......................................................................................................41
Figure 12: Companies’ Intention to Invest in Social Media Advertising (%) ...........................................42
List of Tables
Table 1: A Summary of Social Media Strategies Employed by Fashion Retail Brands..............................16
Table 2: The Variable Definitions .......................................................................................................27
Table 3: Social MediaAdvertisingStrategiesonFacebookandCustomerPurchase Intentions(Linear
Regression) ......................................................................................................................................43
Table 4: Social MediaAdvertisingStrategiesonInstagramandCustomerPurchase Intentions(Linear
Regression) ......................................................................................................................................44
Table 5: Social Media Advertising Strategies on Instagram and Brand Loyalty (Linear Regression) .........44
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Table 6: Social MediaAdvertisingStrategiesonTwitterandCustomerPurchase Intentions(Linear
Regression) ......................................................................................................................................45
Table 7: Social Media Advertising Strategies on Twitter and Brand Loyalty (Linear Regression)..............46
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Chapter 1: Introduction
1.1. ProblemStatement and Research Rationale
Social media have long been recognised as an effective advertising vehicle in a variety of
industries, including fashion retail (Goh et al., 2013; Park and Cho, 2012; Schultz, 2016). Today,
the integration between social networking sites (SNSs) and retailer websites is developing to
achieve the previously unwitnessed degree. For example, Soldsie, a service for Facebook and
Instagram, allows retailers to post their products and available quantities on these websites and
customers to make a one-click purchase (Cohen, 2014). Facebook Messenger can now be used to
place supplementary orders and ask for more information directly from the retailer (Tsukayama,
2015). Finally, Facebook has added the “buy” buttons that enabled to order the products within
Facebook ads themselves and pay with the linked credit card (Koh, 2015). These important
changes in the online retail landscape call for more up-to-date research on which advertising
strategies should be employed by companies on social media to maximise consumer outcomes.
Now that the customer can order the product directly within a Facebook ad, effective social
media advertising has an even greater potential to build sales and brand loyalty (Tweney, 2014).
This project aims at addressing this new research problem by establishing the impact of the
social media advertising practices adopted by Zara and H&M on customer purchase intention
and brand loyalty. The results of this research can enhance the current knowledge of the ways in
which social media advertising can influence consumer behaviour in the fashion retail context.
1.2. Study Background
H&M and Zara are two of the largest brands in the global fast fashion industry. Zara belongs to
the Inditex Group along with a range of other famous brands, such as Massimo Dutti, Pull&Bear
and Bershka. Zara’s retail network includes 2,100 stores in 88 nations worldwide (Inditex, 2016).
Originating in Spain, Zara has developed into a truly global brand with a “responsible passion for
fashion across a broad spectrum of people, cultures and ages” (Inditex, 2016, p. 1). In 2014,
Zara’s global sales reached EUR10.8 billion (Schultz, 2016). The brand’s official Facebook page
has over 24 million fans (Zara, 2016).
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H&M positions itself as a provider of “fashion and quality at the best price in a sustainable way”
(H&M, 2016c, p. 1). Founded in Sweden, this company has evolved into a global fashion retailer
with over 4,000 stores in 61 countries around the globe (H&M, 2016a). The brand’s worldwide
sales were estimated at EUR16.8 billion in 2014 (Schultz, 2016). The UK is one of H&M’s
largest markets, ranking third after Germany and the US (H&M, 2015). H&M’s official
Facebook page is followed by over 27 million people (H&M, 2016b).
1.3. Research Aim, Objectives and Questions
The aim of this research project is to analyse the impact of the social media advertising strategies
employed by Zara and H&M on such customer reactions as purchase intention and brand loyalty.
This aim requires the attainment of the following objectives:
1. To examine the ways in which social media advertising can affect customer purchase
intention and brand loyalty in the fast fashion industry.
2. To identify the most popular social media advertising practices adopted by fast fashion
brands.
3. To compare the effectiveness of social media strategies and traditional advertising
employed by Zara and H&M in the UK market.
4. To develop recommendations concerning how the social media marketing strategies of
fast fashion brands can be enhanced to engage the UK audiences more effectively.
The major research question of this dissertation is:
What social media advertising strategies are the most effective for fast fashion brands to
promote purchase intention and loyalty in British customers?
The supportive research questions are:
Do social media advertising strategies have more influence on customer loyalty and
attitudes than traditional advertising?
How do Web 2.0 advertising practices affect consumer purchase intention as compared
with traditional methods of advertising?
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How do the UK customers respond to the social media advertising strategies employed
by H&M and Zara?
What social media strategies should fast fashion brands employ to maximise the positive
customer outcomes?
1.4. Significance and Potential Contribution
This project can contribute to the scientific knowledge on the impact of social media advertising
strategies on customer behaviour. From the practical viewpoint, the research findings can inform
the social media marketing strategies of fast fashion brands.
1.5. Research Methods
Standardised questionnaire forms are distributed among those customers of H&M and Zara who
tend to be active on such social media as Facebook, Instagram and Twitter. In particular, the
researcher attempts to approach people who have made comments on H&M’s and Zara’s social
media accounts assuming that this target population is customers. The total population sample is
200 customers, including 100 customers of H&M and 100 customers of Zara. The human
participants are approached online and contacted via their social media accounts. This
questionnaire survey is limited geographically to the UK. The obtained quantitative evidence is
analysed statistically using the SPSS software package. Specifically, the brands’ social media
advertising practices are used as independent variables, while customer perceptions and purchase
responses are chosen as dependent variables to determine the effectiveness of Web 2.0
advertising. In addition, secondary data is collected online to enable triangulation and data
comparison (Saunders et al., 2009).
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1.6. Research Limitations
The findings of this research are only relevant to H&M and Zara, which are the focus brands of
this study. Because of a non-random sampling method employed, the identified opinions and
views cannot be extrapolated to all customers of these brands. The findings are limited to the UK
context as participants are recruited only in this country. A more detailed set of limitations can
be found the conclusions and recommendations chapter.
1.7. Structureof the Dissertation
This paper is organised in five chapters. The first chapter presents the problem statement, the
research context, aim, objectives and questions, outlines the significance and potential
contribution of this study, its methods and limitations. The second chapter critically evaluates the
past research literature in the field. The third chapter details and justifies the research
methodology. The fourth chapter reports, analyses and discusses the primary findings. The fifth
chapter culminates with a conclusion and recommendations for industry practitioners and future
researchers.
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Chapter 2: Literature Review
2.1. Introduction
This chapter identifies the ways in which social media advertising can affect customer purchase
intention and brand loyalty through the review of previous literature in the field. In addition, the
social media advertising practices currently employed by Zara, H&M and other fast fashion
brands are identified. Thus, this chapter attains the first and the second objectives of this
dissertation and answers the first and the second research questions.
This chapter includes five sections. The next section identifies the impacts of social media
advertising on consumer behaviour from the perspective of major theoretical frameworks. The
third section identifies the social media advertising strategies employed by fast fashion brands on
Facebook, Instagram and Twitter. The fourth section critically evaluates the effectiveness of the
most popular social media advertising strategies. The final section summarises the secondary
research findings and develops the conceptual framework.
2.2. Theories of Customer Behaviour on Social Media
One of the recent theories of online customer behaviour, with a particular focus on social media,
was suggested by Hoffman and Fodor (2010). The scholars distinguished between four key
customer motivations, or 4C’s, that guide their behaviour on social media, namely consumption,
connection, creation and control (Hoffman and Fodor, 2010). The consumption motivation drives
customers into reading online advertisements or clicking on them to get more information about
the product, find a good deal and make a purchase (Hoffman and Novak, 2012). The connection
motivation makes users subscribe to the brand’s page and comment there in order to be part of a
group of people with similar interests (Hoffman and Novak, 2012). The creation motivation
drives customers into sharing and re-posting the content they liked, or suggesting their own ideas
to the brand (Hoffman and Novak, 2012). Finally, the control motivation makes people add the
brand’s pages to favourites or leave bookmarks in order to be able to retrieve this information
whenever needed (Hoffman and Novak, 2012). The advantage of 4C theory is that it is rooted in
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the general theory of customer motivations (Wu and Lin, 2012) and, hence, has a strong
theoretical basis. The major problem with 4C is that, being a relatively new concept, it lacks
empirical support. In particular, the 4C identified by Hoffman and Fodor (2010) are different
from the four main customer online motives that were revealed by earlier researchers and
included shopping, communicating, surfing and researching (Stafford, 2008). Future research is
needed to find out which classification is more relevant to the present-day social media
environments.
The Behavioural Perspective Model assumes that online and offline consumers alike pursue two
main kinds of reinforcement, namely utilitarian or informational (Foxall, 1988). Besides,
customer actions might be driven by the avoidance of punishment, which can also be
informational or utilitarian. An example of a utilitarian punishment is paying more for a product
they could have bought cheaper in a different place. To pursue reinforcements and avoid
punishments, consumers would browse the information about brands and products online. The
Behavioural Perspective Model was used by Vishnu Menon and Sigurdsson (2016) in their
investigation of consumer responses to Facebook advertising of a large fashion retailer. The
major limitation of this model is that it is inductive and descriptive in nature, while its empirical
support is controversial (Vishnu Menon and Sigurdsson, 2016).
Another general customer behaviour theory that can be applied to social media contexts is the
Hierarchy of Effects that was pioneered by Lavdige and Steiner (1961). This model presents the
customer decision-making process as a three-stage sequence of cognition, affect and conation
(Hoyer et al., 2013). In other words, the customer first gets to know about the brand, e. g. from
social media advertising. The emotional appeal of the ad promotes affect, and in the next stage,
conation, the consumer develops an intention to buy this product (Smith et al., 2008). This model
is supported by a strong empirical basis as it has been frequently applied to understand consumer
behaviour on social media (Jung et al., 2011; Taylor et al., 2011). However, a number of studies
challenged the sequence of Lavdige and Steiner’s (1961) stages or even the very existence of the
Hierarchy of Effects. For example, Goodrich (2011) argued that thinking and feeling occur in
customers simultaneously as they are exposed to ads and, hence, cannot be separated into the
distinct stages of cognition and affect.
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The Meta-Theoretic Model of Motivation and Personality (3M) was suggested by Mowen
(2000). The scholar specified four groups of customer traits that affected their decision-making
process, namely elemental, compound, situational and surface traits (Mowen, 2000). The 3M
framework is graphically presented in the figure below.
Figure 1: The Meta-Theoretic Model of Motivation and Personality (3M)
Source: Adapted from Mowen (2000,p. 33)
As the figure above demonstrates, all four groups of traits act as inputs to the customer decision-
making process (Mowen, 2000). In combination with perceptual inputs, such as social media
advertising, these traits produce cognitive appraisal of the retailer’s offer and behavioural
outcomes. Mowen’s (2000) traits partly overlap with the online shopping motives identified by
Hoffman and Fodor (2010). In particular, situational traits incorporate socialising and
informational gratifications that are pursued by the customer (Kang and Johnson, 2015), which
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corresponds with Hoffman and Fodor’s (2010) connection and consumption motivations. Kang
and Johnson (2015) found 3M to be relevant to describe customer behaviour in the context of
apparel e-shopping on Facebook. The major drawback of 3M is that it is rather complicated and,
hence, might be impractical for use in some research studies and real-world business situations.
2.3. Social Media Advertising StrategiesEmployed by Fashion Retail
Brands
The social media advertising strategies might depend on the SNS type (e. g. Facebook, Twitter or
Instagram) or be universal across most types of social media. Zhang and Mao (2016) described
sponsored stories, display ads and reach generator as the three main forms of brand advertising
on social media. Sponsored stories are published by third parties for a reward from the company
and usually describe the author’s positive experience with the brand or product (Kulmala et al.,
2013). Display ads, also known as banners, are graphical elements that appear next to the content
on web pages, e-mails, messengers and other forms of web communication (Zhang and Mao,
2016). Reach generators are the pieces of content that are published by the company and that
encourage the users to share them (Kulmala et al., 2013). An example of a reach generator is the
company’s selecting a random owner of a valuable prize among those who shared the post about
this event. When used effectively, reach generators can result in 25-35% of the total social media
references to a particular brand being produced by highly engaged users (Geissinger and Laurel,
2016). The sponsored stories, display ads and reach generators are the examples of universal
strategies that can be employed across all most popular SNSs, including Facebook, Instagram
and Twitter (Zhang and Mao, 2016). However, there were few studies that compared their long-
term customer outcomes side by side. This dissertation bridges this research gap by investigating
the impact of various social media advertising strategies on purchase intention in the fashion
retail context.
Posting product advertisements with order information on the brand pages on Facebook, Twitter
or Instagram is a new trend in fashion retail that is gaining momentum since this feature became
available (Tweney, 2014). Vishnu Menon and Sigurdsson (2016) found that the attributes of such
advertisements could either increase or decrease the likelihood of the purchased. The highest
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customer utility was delivered by low price and return guarantee (Vishnu Menon and Sigurdsson,
2016). Considering attribute importance, the consumers rated price information the highest,
which was followed by guarantee and shipping information. The lowest importance ranking was
given to charity labels (Vishnu Menon and Sigurdsson, 2016). This study is especially relevant in
the context of this project because the focus company was a fashion retailer that used Facebook
as part of their marketing strategy (Vishnu Menon and Sigurdsson, 2016). The findings align
with the earlier results by Fagerstrom et al. (2011) and Sigurdsson et al. (2013). The major
limitation is that Vishnu Menon and Sigurdsson’s (2016) research sample only included
university students and was biased towards females, who constituted 81.9% of respondents.
Besides, the study only tested the consumer perception of Facebook ads. Future research is
needed to see whether these relative weights of ad attributes would be retained in other age and
occupational groups, as well as across other social networking sites such as Instagram or Twitter.
This dissertation partly addresses this research gap by comparing the effectiveness of posted
advertisements across Instagram, Facebook and Twitter. Another promising direction for future
research is to investigate what kinds of clothing annotations are likely to attract more customers
who use online automatic recognition and recommendation systems that are currently gaining
popularity on social media (Nogueira et al., 2016).
The engagement outcomes of four posting strategies on Facebook were compared by Taylor and
Alonso (2014). The scholars discovered that photos were strongly preferred by page visitors,
collecting over 10,000 ‘likes’ on average, while for other types of content this figure did not
exceed 2,000-2,500 (Taylor and Alonso, 2014). The number of ‘shares’ was notably smaller and
fluctuated around 200-300 for photos and videos (Taylor and Alonso, 2014). These results
indicate that posting predominantly image content can be the most effective strategy to engage
customers on Facebook and posting videos can be equally effective to promote sharing
behaviours and build the brand’s outreach. In general, photos accounted for 70% of the content
posted by brands on Facebook, which agrees with the findings by Touchette et al. (2015) on a
different brand sample. The major limitation of Taylor and Alonso’s (2014) work is that it only
measured engagement in the terms of immediate behavioural responses such as likes and shares.
The long-term outcomes, including purchase intention and brand loyalty, were not accounted for.
Moreover, the findings have limited practical value for the fashion retail industry because this
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study did not focus on fashion brands only. The research sample included the Top 100 brands
from the Interbrand 2012 rating. This project addresses the limitations of Taylor and Alonso’s
(2014) study by assessing the impact of Facebook strategies on customer loyalty and purchase
intention in fashion retail brands. Also, this dissertation examines the relative effectiveness of
photo and video posting on Instagram and Twitter.
The brands’ utilisation of sponsored stories in fashion blogs was investigated by Pihl (2013). The
scholar found both Zara and H&M to be among the top most referenced brands, with 1,265
references to H&M and 546 references to Zara encountered in fashion blogs (Pihl, 2013). These
findings indicate that both brands actively rely on this social media strategy. The major
limitation of Pihl’s (2013) work is that it did not measure customer outcomes, including purchase
intention and brand loyalty, that were generated by this marketing strategy. Another important
limitation is that Pihl’s (2013) study was limited to fashion bloggers based in Sweden. This
dissertation addresses these gaps by investigating the customer response to sponsored stories in
the UK context.
All three studies discussed above were focused on Facebook as the most popular SNS up to date.
However, other social media websites such as Instagram and Twitter can potentially be used by
fashion brands to leverage their sales and brand loyalty as well. Some advertising strategies,
including photo posting, video posting, sponsored stories and reach generation, can be used
across several social media platforms. This dissertation is testing the assumption that advertising
strategies on Instagram and Twitter can deliver customer outcomes that are comparable to those
of Facebook advertising. The tested advertising strategies are summarised in the table below.
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Table 1: A Summary of Social Media Strategies Employed by Fashion Retail Brands
SNS Strategy Source
Facebook
Photo/advertising posting
Taylor and Alonso (2014, p. 247); Vishnu Menon and
Sigurdsson (2016, p. 345)
Video posting Taylor and Alonso (2014, p. 247)
Display ads Zhang and Mao (2016, p. 156)
Sponsored stories Kulmala et al. (2013, p. 21); Pihl (2013, p. 3)
Instagram
Photo/advertising posting
Taylor and Alonso (2014, p. 247); Vishnu Menon and
Sigurdsson (2016, p. 345)
Video posting Taylor and Alonso (2014, p. 247)
Sponsored stories Kulmala et al. (2013, p. 21); Pihl (2013, p. 3)
Twitter
Photo/advertising posting
Taylor and Alonso (2014, p. 247); Vishnu Menon and
Sigurdsson (2016, p. 345)
Video posting Taylor and Alonso (2014, p. 247)
Sponsored stories Kulmala et al. (2013, p. 21); Pihl (2013, p. 3)
A comprehensive and critical summary of social media advertising advantages and
disadvantages was offered by Taylor (2013). The researcher noted that social media ads
contribute to customer engagement as they “grasp the attention of current and prospective clients
through the use of appropriate and exciting content” (Taylor, 2013, p. 41). The use of social
media advertising practices is also beneficial in terms of gaining customers’ trust, increasing the
overall cost-effectiveness of marketing and stimulating brand visibility. Oncel (2015) agreed that
social media advertising allows profit-making organisations to establish in-depth contract and
two-way communication with their target audience. On the downside, marketing activities on
social media require constant attention and management from organisations, which may consume
additional resources, time and energy. Finally, negative reviews are posted by customers more
frequently than positive feedback and such online behaviour can discourage other customers who
feel positive about the company (Taylor, 2013).
Discussing the critical success factors of social media advertising, McHale (2012) emphasised
that companies should avoid sharing false and misleading statements in the Web 2.0
environment. Another good practice is addressing the claims of customers and responding to
their concerns in the form of open discussions, personal messages and comments (McHale,
2012). It is essential for social media marketers to create unique and appealing content to be able
to retain customers’ attention for a continuous time period. However, Boateng and Okoe (2015)
argued that the effect of social media advertising is not straightforward and direct, but rather
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mediated by corporate reputation. In other words, corporate image that has been created offline is
transferred to the social media environment.
2.4. Effectivenessof Social Media Advertising in Fashion Retail Industry
Ad clicks are commonly used as a measure of social media advertising effectiveness in a variety
of sectors, including fashion retail (Fulgoni and Lipsman, 2014). The relevance of this measure
was supported by Zhang and Mao (2016) who found ad clicks to be a powerful predictor of
product evaluation, which, in turn, promoted purchase intention and positive word-of-mouth.
The regression model developed by the scholars explained 46.8% of variance in customer
purchase intention and 53.2% in electronic word-of-mouth (e-WOM) (Zhang and Mao, 2016).
This is consistent with the earlier conclusions by Haans et al. (2013) that the content of social
media ads can significantly shape customer behavioural responses. The major limitation of
Zhang and Mao’s (2016) study is that the research sample only included university students and
was biased towards Caucasians (71.1% of the total sample) and heavy Facebook users (64.2%).
The ratio of those who preferred Instagram was 31%, and heavy Twitter users constituted only
5.5% (Zhang and Mao, 2016). Thus, the established relationships are more relevant to Facebook
audiences than for those on other social networks. Besides, 93% of the samples were under 29
(Zhang and Mao, 2016), which means that the findings can only be generalised to this age group.
The posting and response strategies employed by Zara and H&M on Facebook were investigated
by Schultz (2016). The scholar found that both brands, as well as four of their major competitors,
produced more new posts on Tuesdays till Fridays and fewer during weekends. H&M stood out
strikingly for the number of new posts that reached 193 during the six weeks’ period of study
(Schultz, 2016). On the other hand, Zara made only 11 new posts within this period, while for
other brands this figure fluctuated between 34 and 68 (Schultz, 2016). In addition, H&M
responded to 40% of user posts in the community and Zara only responded to 6% (Schultz,
2016). Despite these strongly dissimilar social media policies, the development of fan base by
both brands over the studied period was roughly equal within 3-4% (Schultz, 2016). The fastest
development, by 9%, was achieved by Primark, a brand that was the second largest poster after
H&M and that did not respond to any user posts at all (Schultz, 2016). These findings challenge
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the widespread assumption that brands need to be actively engaged with their social media pages
in order to generate a greater brand value (Barnes, 2014; Kabadayi and Price, 2014; Wirtz et al.,
2013).
The major limitation of Schultz’s (2016) investigation is that it employed the growth of fan base
as the single measure of social media strategy effectiveness. Although the positive correlation
between fan base and sales growth was established in several past studies (Cao et al., 2014;
Lipsman et al., 2012), the number of followers is not suitable to measure the level of customer
satisfaction with their current relationship with the brand. Schultz (2016) cited the case of a surge
of negative comments on Zara’s Facebook page that continued for several days. Albeit not
causing a decrease in the number of fans, this negative message could still have done
considerable damage to the brand equity as it was allowed to spread through its network without
being properly addressed by the company (Schultz, 2016). This case indicates the potential
dangers of low-interaction strategies for fashion retail brands. However, future research is
needed to establish the relationship between the brand’s posting and response strategies and
direct customer outcomes such as brand loyalty or purchase intention.
The entertainment value of apparel brand social media pages was in the focus of Touchette’s et
al. (2015) study. The scholars investigated 50 top apparel brands, including manufacturers and
retailers, and found that the most commonly used type of entertainment on their Facebook pages
was advertisements and photos. They accounted for 55.4% of the total context, being followed
by online interactive (19.2%), sweepstakes (11%) and video/audio (7.6%) (Touchette et al.,
2015). Considering themes, 77.8% of posts presented no specific play theme and 7.9% used play
as frivolity (Touchette et al., 2015). The major limitation of this research is that it did not
evaluate customer response to various forms and themes in brand entertainment. Only content
analysis was conducted to identify the most frequently utilised themes. Future research is needed
to find out which types of entertainment on brand Facebook pages can deliver the best customer
outcomes.
The research study by Kang et al. (2013) identified three distinct clusters of customers according
to the primary purpose for which they seeking e-WOM on social media about apparel brands.
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Price-conscious customers were looking for the best price on the product they needed, which
corresponds with the consumption motive by Hoffman and Novak (2012) and with utilitarian
reinforcements by Foxall (1988). Fashion-conscious customers were looking for the trendiest
clothing, or seeking informational reinforcements in Foxall’s (1988) terminology. Brand-
conscious customers were exploring social media for more information about their favourite
brands, which corresponds with the connection motive by Hoffman and Novak (2012).
Therefore, the findings by Kang et al. (2013) are consistent with the major consumer behaviour
frameworks. The major limitation of Kang’s et al. (2013) work is that it did not measure the
effectiveness of various e-WOM strategies for engaging the identified types of customers. This
dissertation partly overcomes this limitation by comparing the impacts of e-WOM on Facebook,
Instagram and Twitter on British customers. However, future research is needed to establish the
relationship between e-WOM impacts and consumer types.
2.5. Chapter Summary and Conceptual Framework
Social media advertising can promote positive consumer responses by offering them utilitarian
and informational value (Foxall, 1988). Effective social media strategies address the customer
needs of price-conscious consumption, feeling connected to the brand and to customers with
similar interests, taking control over their relationship with the brand and co-creating valuable
content (Hoffman and Novak, 2012). One important difference of social media advertising from
traditional advertising is the interactivity of the former. For example, the customer can click on a
Facebook ad to order the product instantly and make an impulse purchase or share the
company’s tweet that they liked. Thus, engaging with the company’s content on social media
results in developed brand loyalty and greater purchase intentions.
Large fast fashion retailers such as Zara and H&M employ a variety of advertising strategies on
Facebook, Twitter and Instagram, including posting photo/advertising content, posting video
content, sponsoring stories and buying display ads (Zhang and Mao, 2016). The study by Taylor
and Alonso (2014) demonstrated that the photo content posted by brands was likely to attract
most ‘likes’, while the photo and video content were most likely to be shared. However, this
research work was limited to Facebook. This dissertation examines whether this relationship
20. 20
holds across other social media such as Twitter and Instagram. The dependent and independent
variables of this project are presented in the figure below.
Figure 2: Conceptual Framework of the Social Media Advertising in the Fashion Retail Context
As the chart above demonstrates, this dissertation tests the impact of social media advertising
strategies on two customer outcomes, namely purchase intention and brand loyalty, across three
SNSs, including Facebook, Instagram and Twitter. The impact of photo advertising, video
posting and sponsored stories is tested for each kind of social media since these strategies are
universal across platforms. The impact of display ads is only tested for Facebook because this
strategy is mostly employed on this platform (Zhang and Mao, 2016).
Facebook:
- Photoadvertising
- Videoposting
- Sponsoredstories
- Displayads
Instagram:
- Photoadvertising
- Videoposting
- Sponsoredstories
Twitter:
- Photoadvertising
- Videoposting
- Sponsoredstories
Customer outcomes:
- Purchase
intention
- Brand loyalty
21. 21
By the term ‘sponsored stories’, the researcher means any posts by third parties that are
sponsored by the company and that tell about personal experiences with the brand. An example
of a sponsored story on Instagram is the user’s photo in the brand’s clothes with a brief positive
comment.
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Chapter 3: Research Methodology
3.1. Introduction
This chapter explains the research methodology of this project. The next section justifies the
methodological framework. The third section presents the specific research strategies. The fourth
section outlines the data analysis methods. The fifth section discusses the involved ethical issues.
The sixth section summarises the contents of this chapter.
3.2. Methodological Framework
This project is guided by epistemological framework because the nature of knowledge to be
collected is determined by the research question (Saunders et al., 2007). Considering the research
philosophy, the combination of positivism and interpretivism is employed for this dissertation
(Saunders et al., 2007). Positivism enables the researcher to generalise on how a particular social
advertising practice is perceived by the customer audience (Remenyi et al., 1998). This
philosophy assumes that business and social situations develop according to certain laws. In
particular, the effectiveness of social media advertising practices can be evaluated by the impact
that they produce on customer perceptions and behaviours (Gill and Johnson, 2002,). This impact
can be measured quantitatively through customer survey, observation or sales data analysis. By
contrast, interpretivism is based on the assumption that each social situation is unique and can
only be understood through the perspectives of involved human actors (Richie et al., 2013). The
main limitation of positivism is that it might overlook the influence of factors that are difficult to
quantify, such as brand image or customer taste (Easterby-Smith et al., 2012). The main
limitation of interpretivism is that it is more vulnerable to the researcher bias as no rigorous
methodology is employed (Collis and Hussey, 2014). Using these two philosophies in
combination, the researcher can mitigate their drawbacks and fully utilise their strengths
(Tashakkori and Teddlie, 2003).
Deduction is selected as the main research approach for this project for several reasons. Firstly,
the field of social media marketing in fast fashion industry is overall well-investigated, with
23. 23
several major theories existing in this area. This situation favours the use of deductive approach,
while induction is preferable for underexplored or emerging fields (Creswell, 1994). Secondly,
deduction is more practicable for undergraduate researchers as the reliability and validity of
findings can be ensured by following a rigorous methodology (Gill and Johnson, 2002). In case
of induction, the researcher might lack the knowledge and skills to develop a completely new
theory. Thirdly, the use of deduction is consistent with the positivist research philosophy and
quantitative data being collected (Saunders et al., 2007). The major limitation of deduction is that
explaining any unexpected patterns that emerge from the data will be beyond the scope of this
study (Collis and Hussey, 2014). However, the researcher will be able to outline them as
directions for subsequent research. Another limitation is that the scientific contribution of
deductive projects is restricted to supporting or rejecting a particular hypothesis or set of
hypotheses (Saunders et al., 2007). Still, this potential contribution is sufficient to justify the
need of this study, especially considering that social media is a very dynamic field and the
current knowledge in this area needs to be constantly re-considered and updated.
3.3. Research Strategies
This dissertation combines case study and survey as the main primary research strategies. The
case study method is employed to gain a profound understanding of the context where the
research is set (Yin, 2003). The social media advertising practices of each focus company are
viewed in the broader context of its mission, business model and target audiences. This strategy
enables the researcher to evaluate the congruence and fit of H&M’s and Zara’s social media
advertising and the extent to which it helps the companies achieve their strategic goals (Morris
and Wood, 1991). The major limitation of case study research is that the findings cannot be
generalised to other organisational contexts since every organisation is viewed as a unique entity
(Saunders et al., 2007). Moreover, they cannot be extrapolated even to the same company in the
past or in the future because the combination of external and internal factors in this organisation
at the present moment is unique and subject to change over time (Robson, 2002). Nevertheless,
the research findings are useful to inform H&M’s and Zara’s social media marketing strategy for
the nearest future. Since social media is a very dynamic and fast-changing environment, the
diminishing value of findings over time is not a serious issue for this research.
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Survey is employed as a primary data collection method for several reasons. Firstly, surveys
allow to collect information directly from customers in a convenient and cost-effective way
(Ghauri and Gronhaug, 2005). Secondly, surveys yield quantitative data that is easier to interpret
and process. Besides, questionnaire data can be used for statistical inferences and establishing
quantified relationships between variables (Saunders et al., 2007). Thirdly, surveys minimise the
researcher bias because the analysis process is rather rigorous and straightforward (De Vaus,
2002). For this reason, surveys are generally more trusted by business practitioners than
alternative methods of primary research such as interviews or focus groups (Saunders et al.,
2007). On the other hand, surveys have a number of considerable limitations. The number of
questions to be included in the survey is limited and generally should not exceed 25-30,
otherwise the questionnaire might take too much time to complete (De Vaus, 2002). Being able
to obtain answers only to a narrow set of questions, the researcher should pay particular attention
to their selection. The reliability and validity of survey findings are determined by the fit
between included questions and research variables (Saunders et al., 2007). The researcher
addresses this issue by including at least two questions to measure each research variable. The
next limitation is that questionnaire responses are very brief and standardised and, hence, are
unlikely to provide any novel insights (Saunders et al., 2007). On the other hand, these responses
are a good fit to test a set of hypotheses, which is the purpose of this study.
This project uses self-nominated sampling. The researcher contacts the social media users who
commented on the recent posts by H&M and Zara on social media, assuming that they are the
engaged customers of these brands. Since this work is focused on the UK audience, only those
users who have specified Britain as their location are contacted. Each intended participant
receives a message that contains the invitation to take part in the study, the brief explanation of
its scope and purpose and the link to the online questionnaire. The online survey is available
until at least 100 responses from Zara’s implied customers and 100 responses from H&M’s
implied customers are collected. Therefore, the total number of survey respondents is 200
individuals. The advantage of this sampling method is that it enables the researcher to gather a
pre-determined number of responses that is large enough to make reliable statistical inferences
(De Vaus, 2002). One major drawback of self-nominated sampling is that it is a non-random
25. 25
method, so the results cannot be generalised to a broader population (Saunders et al., 2007).
Moreover, a self-nominated sample might be biased towards the customers who have stronger
emotions, either positive or negative, about the brand that they are willing to express, or against
those who have more free time to complete the questionnaire. Thus, the findings of this survey
should be interpreted with caution and not extrapolated to a potentially larger group of less
engaged customers.
3.4. Data Collection Instruments and AnalysisMethods
The questionnaire consists of six structured and logical sections, which are predominantly based
on the literature reviewed in the second chapter (Jung et al., 2011; Taylor et al., 2011; Nogueira
et al., 2016). These sections include background data, social media and traditional advertising,
advertising practices on Facebook, advertising practices on Instagram, advertising practices on
Twitter and customer outcomes. The first section (Q1 – Q4) offers research participants to report
their age, gender and awareness of Zara’s and H&M’s advertising initiatives on the most popular
social networking services. Although this data does not lead to the achievement of the main
dissertation aim, it allows the researcher to construct detailed respondent profiles and assess the
extent to which they are aware of the social media advertising strategies adopted by the fashion
brands on Facebook, Twitter and Instagram.
The next questionnaire section (Q5 – Q8) is focused on the comparison of social media and
traditional advertising in terms of its impact on consumer behaviour (Vishnu Menon and
Sigurdsson, 2016; Stafford, 2008). In turn, the third section (Q9 – Q12) offers research
participants to evaluate the extent to which Zara and H&M actively advertise their goods on
Facebook using various advertising strategies such as photo posting, video posting, sponsored
stories and display ads (Taylor and Alonso, 2014; Pihl, 2013). The fourth section (Q13 – Q15)
and the fifth section (Q16 –Q18) are focused on Zara’s and H&M’s social media advertising
strategies (i.e. photo advertising, video posting, sponsored stories) on Instagram and Twitter,
respectively. The final section of the questionnaire (Q19 – Q20) offers social media users to
report the extent to which they are willing to purchase from the fashion brands (purchase
intention) as well as the degree to which they are intended to buy from the companies in the
26. 26
future (brand loyalty) (Barnes, 2014; Wirtz et al., 2013; Kabadayi and Price, 2014). The
questionnaire sample can be found in Appendix.
As mentioned in the literature review chapter, this dissertation attempts to examine whether there
is a link between social media advertising strategies and the customer outcomes. Therefore, it is
important to define both dependent and independent variables used in the statistical analysis
(Saunders et al., 2007). The following table provides the reader with a summary of all the
variables employed in the statistical analysis section of this project.
27. 27
Table 2: The Variable Definitions
Questionnaire
Section
Question
No
Variable Definition Literature Source
III. Advertising
Practices on
Facebook
9 FPHO
Photo advertising on
Facebook
Taylor and Alonso (2014, p. 247);
Vishnu Menon and Sigurdsson
(2016, p. 345)
10 FVID
Video posting on
Facebook
Taylor and Alonso (2014, p. 247)
11 FSTO
Sponsored stories on
Facebook
Zhang and Mao (2016, p. 156)
12 FBAN
Display ads on
Facebook
Kulmala et al. (2013, p. 21); Pihl
(2013, p. 3)
IV. Advertising
Practices on
Instagram
13 IPHO
Photo advertising on
Instagram
Taylor and Alonso (2014, p. 247);
Vishnu Menon and Sigurdsson
(2016, p. 345)
14 IVID
Video posting on
Instagram
Taylor and Alonso (2014, p. 247)
15 ISTO
Sponsored stories on
Instagram
Kulmala et al. (2013, p. 21); Pihl
(2013, p. 3)
V. Advertising
Practices on
Twitter
16 TPHO
Photo advertising on
Twitter
Taylor and Alonso (2014, p. 247);
Vishnu Menon and Sigurdsson
(2016, p. 345)
17 TVID
Video posting on
Twitter
Taylor and Alonso (2014, p. 247)
18 TSTO
Sponsored stories on
Twitter
Kulmala et al. (2013, p. 21); Pihl
(2013, p. 3)
VI. Customer
Outcomes
19 WILL Purchase intention Taylor and Alonso (2014, p. 247)
20 LOYL Brand loyalty Tweney (2014, p. 1)
The relationship between the identified social media advertising strategies and customer
outcomes is established with the help of the linear regression function in SPSS. Given that this
project examines social media users’ purchase intention and brand loyalty on three different
social networking services, six regression models should be constructed.
𝑊𝐼𝐿𝐿 𝑖 = α0 + β1 𝐹𝑃𝐻𝑂i + β2 𝐹𝑉𝐼𝐷𝑖 + β3i + β4 𝐹𝐵𝐴𝑁i + εi, (1)
where, WILL is consumer purchase intention (a dependent variable), α0 is a constant, β1, 2, 3...4
are indicators impacting the independent variables, namely FPHO, FVID, FSTO and FBAN and
ε is residuals.
28. 28
𝐿𝑂𝑌𝐿𝑖 = α0 + β1 𝐹𝑃𝐻𝑂i + β2 𝐹𝑉𝐼𝐷𝑖 + β3i + β4 𝐹𝐵𝐴𝑁i + εi, (2)
where, LOYL is brand loyalty (a dependent variable), α0 is a constant, β1, 2, 3...4 are indicators
that affect the independent variables and ε is residuals.
𝑊𝐼𝐿𝐿 𝑖 = α0 + β1 𝐼𝑃𝐻𝑂i + β2 𝐼𝑉𝐼𝐷𝑖 + β3 𝐼𝑆𝑇𝑂 + εi, (3)
where, WILL is consumer purchase intention (a dependent variable), α0 is a constant, β1, 2, 3 are
indicators that influence the independent variables, namely IPHO, IVID and ISTO and ε is
residuals.
𝐿𝑂𝑌𝐿𝑖 = α0 + β1 𝐼𝑃𝐻𝑂i + β2 𝐼𝑉𝐼𝐷𝑖 + β3 𝐼𝑆𝑇𝑂 + εi, (4)
where, LOYL is brand loyalty (a dependent variable), α0 is a constant, β1, 2, 3 are indicators that
impact the predictors and ε is residuals.
𝑊𝐼𝐿𝐿 𝑖 = α0 + β1 𝑇𝑃𝐻𝑂i + β2 𝑇𝑉𝐼𝐷𝑖 + β3 𝑇𝑆𝑇𝑂 + εi, (5)
where, WILL is consumer purchase intention (a dependent variable), α0 is a constant, β1, 2, 3 are
indicators affecting the independent variables, namely TPHO, TVID and TSTO and ε is
residuals.
𝐿𝑂𝑌𝐿𝑖 = α0 + β1 𝑇𝑃𝐻𝑂i + β2 𝑇𝑉𝐼𝐷𝑖 + β3 𝑇𝑆𝑇𝑂 + εi, (6)
where, LOYL is brand loyalty (a dependent variable), α0 is a constant, β1, 2, 3 are indicators that
impact the predictors and ε is residuals.
As a first step in the analysis process, the correlations between variables are established to
control for the multicollinearity issue. As a second step, the multiple regression model is
developed to determine the quantified impacts of social media advertising practices on customer
purchase intention and brand loyalty. The findings of this quantitative analysis are triangulated
29. 29
against the conclusions by past researchers and the secondary evidence of the social media
advertising practices employed by the focus brands.
3.5. Research Ethics
As this project involves direct human participants, it is particularly important to maintain a high
standard of research ethics. To gain access to potential respondents, the researcher only uses their
contact data that is publicly available on social media. Each intended participant is informed on
the scope and purpose of this study so that they can provide a fully informed consent (Zikmund,
2000). Any refusal to take part in the survey is accepted by the researcher, and no pressure is
applied in the participant recruitment process. Besides, the researcher provides an estimate of the
questionnaire completion time, which is considered as a best practice in social and business
research (Blumberg et al., 2005).
Since the survey participants are recruited on social media, the researcher is able to access the
personal data that they have posted on their profiles, including their names, location and place of
work. However, this data is not collected, stored or processed for the purpose of this study. The
survey is anonymous and does not ask the participants for any personally identifiable
information. The researcher is not able to identify the participant by the completed questionnaire
and match it with their social media profile data. Thus, the anonymity and confidentiality of
respondents is maintained in the process of data collection and analysis (Saunders et al., 2007).
The researcher is committed to the accurate interpretation of the ideas and opinions expressed by
others, be it the survey respondents or the authors cited. Although no interpretation can be
completely free of the impact of the researcher’s personal values and perceptions, the author
relies on scientifically proven and rigorous methods of analysis, such as correlation and multiple
regressions, to minimise the possible bias (Sekaran, 2003).
30. 30
3.6. Chapter Summary
This project employs an epistemological mix of positivism and interpretivism to analyse both
tangible and intangible factors that might contribute to the established relationships. Deductive
approach is used to test the existing theory in the context of Zara’s and H&M’s social media
advertising. The methods of survey and case study are utilised to collect and process primary
quantitative data. The data is analysed using the SPSS software. The researcher is committed to
follow the appropriate ethical standards in the data collection and analysis process.
31. 31
Chapter 4: Data Analysis and Findings
4.1. Introduction
The fourth chapter analyses, reports and interprets the analysis findings. As mentioned in the
research methodology, primary data was collected from 100 customers of Zara and 100
customers of H&M. The data analysis and findings chapter consists of five subsections, namely
introduction, background data analysis, the effectiveness of social media and traditional
advertising, the link between social media advertising strategies and customer outcomes and
summary.
4.2. Background Data Analysis
In accordance with the research methodology chapter, this project is in keeping with self-
nominated sampling, meaning Zara’s and H&M’s customers of different age and gender
participated in the questionnaire survey. The background data analysis begins with the analysis
of the participants’ age, which is presented by means of the following chart.
Figure 3: How Old Are You? (%)
32. 32
More than one third or 37.5% of the participants indicated they were between 18 and 25 years.
The social media users who reported they belonged to the ’26-36’ age group accounted for 32%
of the sample. As much as 25.5% of those who returned their questionnaire reported they were
between 36 and 45 years. Only a minority or 4.5% of the respondents were between 46 and 55
years. Only one individual belonged to the ‘56-60’ age group. Hence, young social media users
between 18 and 35 years formed the overwhelming majority of the sample. The produced
analysis results are in keeping with Whiting and Williams (2013) who arrived at the conclusion
that individuals who belonged to a younger generation used social media more actively in
comparison with more mature persons. Nevertheless, according to Cao et al. (2014), social media
users are becoming older.
Although fashion brands such as Zara and H&M focus on women, both companies provide male
consumers with a wide range of fashion apparel and accessories (Inditex, 2016; H&M, 2015).
The following chart demonstrates the research participants’ gender.
Figure 4: What Is You Gender? (%)
The overwhelming majority or 76% of those who returned their questionnaire reported they were
women. On the contrary, the remaining 24% of the participants were males. These outcomes are
in keeping with Geissinger and Laurel (2016) who acknowledged that the fashion industry was
33. 33
more women-oriented. Nevertheless, the employment of the self-nominated sampling technique
does not allow for stating that the drawn sample is representative of the whole population of
Zara’s and H&M’s customers (Blumberg et al., 2005). According to the research methodology,
the survey participants are engaged customers of the fashion brands. The frequency of the
participants’ purchases from Zara and H&M is presented by means of the following chart.
Figure 5: How Often Do You Purchase Goods Either from Zara or from H&M? (%)
Almost two thirds or 60.5% of those surveyed indicated they purchased fashion goods and
accessories from the brands almost every month. In turn, the respondents who bought from Zara
and/or H&M almost every week accounted for 19% of the sample. As much as 18.5% of the
social media users reported they purchased fashion apparel and accessories from the companies
several times a year. Only a minority or 2% of the individuals buy fashion goods from Zara
and/or H&M almost every year. The produced results show that the sample of this project is
drawn from the engaged customers of the fashion brands. Therefore, it is relevant to assume that
the research participants are aware of the brands’ advertising and promotion campaigns on social
media.
34. 34
Figure 6: I Am Fully Aware of Zara's and/or H&M's Advertising Initiatives on the Most Popular Social Networking
Services such as Facebook, Instagram and Twitter (%)
The social media users who either agreed or strongly agreed they were fully aware of Zara’s
and/or H&M’s advertising initiatives on the most popular social networking services totalled
almost three fourths or 73% of the sample. On the contrary, in total, only a minority or 12.5% of
those who returned their questionnaire either disagreed or strongly disagreed with this statement.
The remaining 14.5% of the individuals provided the researcher with neutral responses to this
question. Therefore, the majority of the fashion consumers were aware of Zara’s and/or H&M’s
marketing campaigns and initiatives on social media. This fact contributes to the validity and
reliability of the research outcomes since the participants have a considerable knowledge of the
companies’ online marketing strategy.
4.3. The Effectiveness of Social Media and Traditional Advertising
This section is responsible for the examination of whether fashion consumers respond to social
media advertising more positively in comparison with traditional advertising methods and
practices. It is commonly accepted in the marketing literature that the emergence of Web 2.0 has
significantly changed the way organisations deliver their marketing messages to consumers
(McHale, 2012; Taylor and Alonso, 2014). For example, advertising on social media was
35. 35
reported by Kulmala et al. (2013) to facilitate two-way communication between the brand and
the customer, eliminating the factor of the time lag. At the same time, traditional marketing
communications channels such as TV, radio and printed materials are focused on one-way
communication, which can be viewed as a limitation (Zhang and Mao, 2016). The degree to
which both types of advertising are attractive to the research participants is presented as follows.
Figure 7: The Attractiveness of Zara's and H&M's Online and Traditional Advertising (%)
The questionnaire survey participants who either agreed or strongly agreed they were highly
attracted by Zara’s and/or H&M’s advertising campaigns and promotions on social media
totalled the overwhelming majority or 86% of the sample. By contrast, in total, only 13% of the
internet users either disagreed or strongly disagreed the effectiveness of the fashion brands’
online advertising and promotions initiatives was high. Only 1% of those surveyed provided the
researcher with neutral responses to this question.
Further analysis also indicates that in total, almost half or 44.5% of the social media users either
agreed or strongly agreed they were highly attracted by Zara’s and/or H&M’s advertising
campaigns and promotions communicated through TV, radio, billboards, journals and other
traditional ways of marketing communications. In turn, the individual who either disagreed or
strongly disagreed the attractiveness of the traditional advertising instruments employed by the
36. 36
fashion brands was totalled 46% of the sample. Only 9.5% of the internet users neither agreed
nor disagreed with their peers and responded neutrally to this statement.
The produced graphical analysis results demonstrate that online advertising campaigns and
initiatives are perceived by the social media users as more attractive in comparison with more
traditional ways of communicating marketing messages. Similarly to this dissertation, Hoffman
and Fodor (2010) were convinced that consumers were more responsive to advertising in the
online environment due to a higher level of interactivity comparing to offline advertising. This
statement is also in keeping with Touchette et al. (2015) who argued that interactive advertisings
provided consumers with easier and quicker access to product- and service-related information,
which in turn, stimulated their purchasing intention. Nevertheless, the attractiveness of offline
advertising instruments is still perceived as high (Taylor, 2013). It is possible to explain these
findings by the fact that traditional media are highly popular with more mature consumers
(Hoffman and Novak, 2012). In accordance with BLS (2015), consumers between 45 and 55
years spend the greatest amount of money on fashion in comparison with those fashion
consumers who belong to a younger generation. That is why fashion brands deliver their
marketing messages through traditional communications channels.
Pihl (2013) established a direct relationship between a firm’s marketing efforts and consumers’
willingness to purchase from this organisation. Nevertheless, the researcher failed to differentiate
between social media and traditional advertising. This dissertation attempts to bridge this gap by
comparing whether Zara’s and H&M’s online and traditional advertising has different impact on
their customers’ buying intentions. The analysis results are presented by means of the following
histogram.
37. 37
Figure 8: The Impact of Zara's and H&M's Online and Traditional Advertising on Buying Intentions (%)
In total, almost three fourths or 72% of the research participants either agreed or strongly agreed
Zara’s and/or H&M’s advertising campaigns and promotions on social media significantly
contributed to their willingness to purchase from the brands in the future. On the contrary, the
internet users who either disagreed or strongly disagreed with their peers totalled 21% of the
sample. The remaining 7% of those surveyed selected the ‘Neither’ response option. These
outcomes indicate that the impact of the fashion brands’ social media advertising on consumers’
purchase intentions is stronger comparing to traditional advertising.
The chart above also indicates that 43.5% of the individuals either agreed or strongly agreed
Zara’s and/or H&M’s advertising campaigns and promotions communicated through TV, radio,
billboards, journals and other printed materials added to their willingness to buy fashion apparel
and accessories from the brands in the future. At the same time, the survey participants who
either disagreed or strongly disagreed the companies’ traditional advertising had any positive
impact on their intention to purchase totalled 43.5% of the sample. Finally, neutral responses
were provided by the remaining 13% of the respondents.
The graphical analysis results indicate that online advertising and promotion campaigns have a
stronger impact on fashion consumers’ buying intentions in comparison with more traditional or
38. 38
offline methods of marketing communications. These findings correlate strongly with those
achieved by Taylor and Alonso (2014) according to whom online advertising is devoid of many
drawbacks, which are inherent in traditional advertising methods. As previously mentioned,
social media advertising allows for establishing two-way communication between the brand and
the consumer. Therefore, it is possible to collect feedback from consumers in a faster way
comparing to traditional marketing tools and instruments. It should be critically remarked,
however, that companies have limited control over their marketing mix activities in the online
environment (Taylor, 2013). This fact may pose a serious threat to their brand reputation. For
example, an advertising campaign that does not appeal to consumers’ needs and expectations
may trigger negative word of mouth (WOM) (Boateng and Okoe, 2015).
4.4. The Link between Social Media Advertising Strategiesand Customer
Outcomes
As mentioned in the introduction chapter, this dissertation attempts to identify what social media
advertising strategies are the most effective for fast fashion brands to promote purchase intention
and loyalty in British consumers. For this purpose, the most popular social networking services,
namely Facebook, Twitter and Instagram have been selected. In their study, Taylor and Alonso
(2014) found that photo posting on social media was an effective way to attract customer
attention to a firm’s goods and services. The following chart summarises and compares the
extent to which photo posting is perceived to be actively used by Zara and H&M on the
mentioned social media sites.
39. 39
Figure 9: Photo Posting (%)
Photo posting on Instagram was reported by the majority or in total, 87% of the respondents as
the most actively used social media advertising strategy by Zara and H&M. In turn, the extent to
which the brands actively posted photos on Facebook and Twitter was perceived by the research
participants as less significant. It is possible to explain these outcomes by the fact that
alternatively to Facebook and Twitter, Instagram is a photo and video sharing service. Overall,
Zara and H&M actively use all three social networking services to post photos.
Video positing on social media is another effective strategy that allows companies to attract
consumer attention and generate higher levels of engagement and loyalty (Taylor and Alonso,
2014; Vishnu Menon and Sigurdsson, 2016). The following chart compares the degree to which
the fashion brands are perceived to actively post videos on the social media sites.
40. 40
Figure 10: Video Posting (%)
The participants who either agreed or strongly agreed video posting on Instagram was the most
popular social media advertising strategy totalled 62.5% of the sample. The perceived popularity
of Facebook as a tool for posting videos was also evaluated by the respondents as high. In turn,
video posting on Twitter lags behind the remaining social networking services in terms of
perceived popularity. The produced outcomes are in line with those achieved by Vishnu Menon
and Sigurdsson (2016) who argued that Twitter was predominantly used to post short messages
rather than video content.
41. 41
Figure 11: Sponsored Stories (%)
As it can be observed from the chart above, the perceived popularity of sponsored stories as a
means of advertising is low across all three social networking services. A possible explanation of
these findings is that consumers tend to rely on independent information sources on third-party
web sites (McHale, 2012). At the same time, sponsored stories on Zara’s and H&M’s social
media pages may be perceived as not entirely honest (Fulgoni and Lipsman, 2014). Nevertheless,
Facebook, Twitter and Instagram still remain highly popular with companies as marketing tools.
This statement is also in keeping with Zhang and Mao’s (2016) findings, according to which a
great number of organisations are looking to increase their paid advertising on the mentioned
social networking services.
42. 42
Figure 12: Companies’ Intention to Invest in Social Media Advertising (%)
Source: Smart Insights (2014, p. 1)
According to the chart above, Facebook remains the most popular marketing tool with
companies. These results can be explained by the fact that this social networking service
provides business with a more flexible and effective ads system in comparison with its
alternatives (Schultz, 2016). At the same time, as demonstrated by the histogram, a great number
of organisations do not use social media to promote and advertise their goods (Smart Insights,
2014). Nevertheless, it is impossible to identify whether these findings are caused by the
perceived ineffectiveness of these marketing communications channels or firms’ focus on other
from social media users customer groups.
In accordance with the literature review, the most popular social networking services such as
Facebook, Twitter and Instagram are used in this project to establish the relationship between
social media advertising strategies and customer purchase intentions and brand loyalty. The
linear regression function is performed in the SPSS software package to identify how Zara’s and
H&M’s social media advertising strategies on Facebook predict consumer purchase intentions.
The outcomes of the statistical analysis are presented as follows.
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Table 3: Social Media Advertising Strategies on Facebook and Customer Purchase Intentions (Linear Regression)
Variable
Unstandardized Coefficients
t Sig.
Collinearity Statistics
B Std. Error Tolerance VIF
α 2.732 0.440 6.215 0.000
FPHO 0.012 0.066 0.185 0.853 0.965 1.036
FVID 0.104 0.063 1.652 0.100 0.988 1.012
FSTO 0.083 0.059 1.397 0.164 0.955 1.047
FBAN 0.139 0.059 2.366 0.019 0.996 1.004
The table above demonstrates that only one independent variable, namely FBAN has statistical
power over the independent variable. This statement is made since the Significance (Sig.) of the
predictor is equal to 0.019, which is much lower than the threshold value of 0.05. The statistical
outcomes also indicate that B coefficient of the independent variable is positive, meaning FBAN
is positively correlated with WILL. Hence, the established statistical relationship can be
interpreted as follows: the more actively Zara and/or H&M post stories about their customers’
positive experience with their products on Facebook, the more social media users are willing to
purchase fashion goods and accessories from the brands. The Variance Inflation Factor (VIF),
which is a means of validity and reliability, is within its normal range (n = 5), meaning the
statistical analysis results do not show collinearity. None of the predictors should be excluded
from the model.
Some scholars argue that variables, the Sig. of which is higher than 0.05 but lower than 0.15 are
statistically significant at least at 15% (Bryman and Cramar, 2011; Carver and Nash, 2011).
According to the table above, the Sig. of the FVID variable is equal to 0.10, which is lower than
0.15. Considering positive B coefficient of the predictor, it is possible to interpret the established
relationship as follows: the more actively Zara and/or H&M post videos of Facebook, the more
social media users are willing to buy fashion products and accessories from the brands. None of
the remaining variables have any statistically significant predicting power over the WILL
variable. According to the conceptual framework of this study, brand loyalty is another customer
outcome, which is used as a dependent variable. Nevertheless, this dissertation failed to establish
any statistically significant relationship between Zara’s and H&M’s social media advertising
strategies on Facebook and the research participants brand loyalty.
44. 44
Alternatively to Facebook, Instagram put a heavy emphasis on photo and video sharing.
Therefore, it is relevant to assume that the role of Zara’s and H&M’s video and photo sharing
activities on Instagram in consumers’ purchasing behaviour should be considerable. This
assumption is tested by means of the following table.
Table 4: Social Media Advertising Strategies on Instagram and Customer Purchase Intentions (Linear Regression)
Variable
Unstandardized
Coefficients t Sig.
Collinearity Statistics
B Std. Error Tolerance VIF
α 2.718 0.493 5.513 0.000
IPHO 0.205 0.097 2.109 0.036 0.997 1.003
IVID 0.050 0.059 0.858 0.392 0.993 1.007
ISTO 0.048 0.083 0.582 0.561 0.991 1.009
The statistical analysis results show that there is a significant correlation between the IPHO and
WILL variables. According to the table above, the Sig. of the predictor is lower than 0.05, which
is the threshold value. B coefficient of the predictor is positive, meaning the relationship between
the variables is also positive. Thus, the more actively Zara and H&M post photos on Instagram,
the more social media users are willing to purchase fashion apparel and accessories from the
brands. None of the remaining independent variables statistically predict the WILL variable. The
value of the VIF is lower than the threshold value, indicating all the variables are accessible and
none of them should be excluded from the constructed regression model. The following table
demonstrates the relationship between Zara’s and H&M’s social media advertising strategies on
Instagram and consumer brand loyalty.
Table 5: Social Media Advertising Strategies on Instagram and Brand Loyalty (Linear Regression)
Variable
Unstandardized
Coefficients t Sig.
Collinearity Statistics
B Std. Error Tolerance VIF
α 2.610 0.527 4.952 0.000
IPHO 0.101 0.104 0.978 0.329 0.997 1.003
IVID 0.245 0.063 3.897 0.000 0.993 1.007
ISTO -0.106 0.088 -1.202 0.231 0.991 1.009
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The linear regression analysis results indicate that the relationship between the IVID and LOYL
variables is statistically significant at least at 95% since the Sig. of the predictor is much lower
than the threshold value of 0.05. Considering positive B coefficient, it is possible to interpret the
link between the variables as follows: the more actively Zara and H&M post videos on
Instagram, the more social media users are intended to purchase fashion goods and accessories
from the brands in the future. The Sig. of the remaining variables is higher than the threshold
value, meaning they do not establish any statistically significant link with the dependent variable.
Twitter is another social networking services selected for the purpose of this dissertation. The
linear regression function is performed in the SPSS software package to identify whether or not
Zara’s and H&M’s social media advertising strategies on Twitter predict consumer purchase
intention.
Table 6: Social Media Advertising Strategies on Twitter and Customer Purchase Intentions (Linear Regression)
Variable
Unstandardized
Coefficients t Sig.
Collinearity Statistics
B Std. Error Tolerance VIF
α 3.362 0.371 9.050 0.000
TPHO 0.146 0.067 2.187 0.030 0.997 1.003
TVID -0.081 0.061 -1.331 0.185 0.995 1.005
TSTO 0.059 0.061 0.959 0.339 0.993 1.007
The Sig. of the TPHO variable is lower than 0.05, which is the threshold value. The table above
also indicates that the relationship between the variables is positive since B coefficient of the
predictor is positive. Therefore, the more actively Zara and/or H&M post photos on Twitter, the
more social media users are intended to purchase fashion products and accessories from the
companies. The remaining variables do not have any predicting power over the WILL variable
since their Sig. is higher than 0.05. The following table shows whether there is a correlation
between Zara’s and H&M’s social media advertising strategies on Twitter and brand loyalty.
46. 46
Table 7: Social Media Advertising Strategies on Twitter and Brand Loyalty (Linear Regression)
Variable
Unstandardized
Coefficients t Sig.
Collinearity Statistics
B Std. Error Tolerance VIF
α 2.640 0.408 6.471 0.000
TPHO 0.082 0.073 1.119 0.264 0.997 1.003
TVID 0.160 0.067 2.388 0.018 0.995 1.005
TSTO 0.115 0.068 1.700 0.091 0.993 1.007
Only one independent variable, namely TVID statistically predicts the LOYL variable at 95%
since its Sig. is equal to 0.18, which is much lower than the threshold value. Considering positive
B coefficient of the independent variable, it is possible to interpret the established relationship as
follows: the more actively Zara and H&M post videos on Twitter, the more social media users
are intended to purchase fashion products and accessories from the companies in the future. The
constructed regression model is reliable since the VIF is within its normal range (n =5).
4.5. Summary
It is relevant to summarise that social media advertising strategies have more influence on
customer loyalty and attitudes in comparison with traditional media. Furthermore, photo posting
and video posting have been discovered as the most popular social media advertising strategies
adopted by Zara and H&M. At the same time, the perceived popularity of sponsored stories is
not considerable. It can be summarised that there is a strong correlation between the brands’
social media strategies such as display ads on Facebook and photo posting on Instagram and
consumers’ intention to buy. In turn, consumers’ loyalty to Zara and H&M is predicted by video
posting on Instagram and video posting on Twitter.
47. 47
Chapter 5: Conclusions and Recommendations
5.1. Introduction
The purpose of the fifth chapter is to discuss the produced analysis outcomes in the light of the
previous researchers’ works (Kabadayi and Price, 2014; Barnes, 2014; Wirtz et al., 2013). On the
basis of this discussion, the final conclusions are drawn. The most important research limitations
are outlined and a set of practical recommendations as how fast fashion brands could enhance
their social media marketing strategies to engage the UK audiences in a more effective way are
formulated.
5.2. Concluding theMain Findings
The main aim of this dissertation was to analyse the impact of the social media advertising
strategies employed by Zara and H&M on such customer reactions as purchase intention and
brand loyalty. This aim has been achieved using both graphical and statistical analysis methods
applied to primary and secondary data. The methods of analysis employed in this project
included graphical representation and linear regression.
The first research objective was to examine the ways in which social media advertising can
affect customer purchase intention and brand loyalty in the fast fashion industry. This goal was
achieved in the literature review chapter. Using the findings from the second chapter, it is
relevant to conclude that there are numerous models and frameworks, which explain consumer
behaviour on the online environment. For instance, Hoffman and Fodor (2010) distinguished
between the four key elements of customer motivations, including consumption, creation,
connection and control. The Behavioural Perspective Model is another customer behaviour
theory applicable to the online environment (Foxall, 1988). In accordance with Vishnu Menon
and Sigurdsson (2016), all consumers pursue two types of reinforcements, namely informational
and utilitarian. The researchers reported that consumers who pursue reinforcements are more
likely to browse the information about products and brands online. Finally, the 3M model
implies that there are four groups of customer traits (i.e. elemental, situational, compound and
48. 48
surface traits), which impact the decision-making process (Mowen, 2000). However, 3M is
considered as excessively complicated and impractical for use (Kang and Johnson, 2015).
The next objective of this project was to identify the most popular social media advertising
practices adopted by fast fashion brands. In accordance with the literature review chapter,
sponsored stories, display ads and video and photo posting are the main forms of brand
advertising in the online environment (Zhang and Mao, 2016). The analysis results demonstrated
that photo positing was the most popular advertising strategy with both Zara and H&M. It can be
concluded that the brands actively use all three social networking services, namely Facebook,
Twitter and Instagram to post photos of their goods and services. These findings are in keeping
with Taylor and Alonso (2014) who also acknowledged that photos were strongly preferred by
the internet users who visited a brand’s social media web page.
Further analysis demonstrated that although video posting was perceived as less popular with
Zara and H&M, the popularity of this social media advertising strategy was still evaluated as
high. The perceived popularity of Facebook as a tool for posting videos was also evaluated as
high. In turn, the popularity of video posting on Twitter was not considerable in comparison with
the remaining social networking services. Similarly to this study, Vishnu Menon and Sigurdsson
(2016) reported that although Twitter supported the function of video sharing, this feature was
not highly popular with organisations comparing to alternative social networking services. It can
also be concluded that the extent to which Zara and H&M use sponsored stories as a means of
advertising is low across all three social networking services.
The third dissertation objective was to compare the effectiveness of social media strategies and
traditional advertising employed by Zara and H&M in the UK market. This objective was fully
attained in the data analysis and findings chapter. Using the results from the fourth dissertation
chapter, it is relevant to conclude that display ads on Facebook, photo posting on Instagram,
video posting on Instagram and video posting on Twitter are the most effective social media
advertising strategies for fast fashion brands to promote purchase intention and loyalty in British
customers.
49. 49
The impact of Web 2.0 advertising on consumers’ purchase intention was investigated by Hajili
(2014). Similarly to this dissertation, the researcher analysed primary data collected from social
media users and arrived at the conclusion that social media facilitated the social interaction of
consumers, which in turn, increased their intention to purchase (Hajili, 2014). As argued by
Schultz (2016), advertising on social media is more effective on social media due to the lack of
communication barriers. Nevertheless, Hajili (2014) did not differentiate between online and
offline advertising. This project attempted to overcome this limitation by examining whether
social media advertising strategies had more influence on consumer loyalty and attitudes in
comparison with traditional advertising. It is relevant to conclude that Zara’s and H&M’s social
media advertising is perceived by their consumers as more attractive comparing to traditional
advertising. Furthermore, the brands’ online advertising has stronger impact on consumers’
buying intentions.
In their empirical study, Taylor and Alonso (2014) arrived at the conclusion that photo posting
was an effective marketing initiative that allowed companies to attract consumers’ attention to
their goods and services on social media. Similarly to this project, the researchers investigated
the engagement outcomes of social media advertising strategies in the online environment. At the
same time, the most popular social networking services were reported by Fulgoni and Lipsman
(2014) to provide businesses with different approaches to advertising. Therefore, it is relevant to
study the impact of online advertising on consumer outcomes at the example of several social
networking services. Nevertheless, the scope of Taylor and Alonso’s (2014) was limited to
Facebook. This project attempted to overcome this limitation by examining how the UK
customers responded to the social media advertising strategies employed by H&M and Zara on
Facebook, Twitter and Instagram.
It is relevant to conclude that photo posting and video posting are the most popular social media
advertising strategies adopted by Zara and H&M. These findings are in keeping with Touchette
et al. (2015) who also reported that the extent to which video content attracted consumers in the
online environment was high. However, the perceived popularity of sponsored stories across the
social networking services was discovered as low. These results contradict Pihl (2013) who
found that both Zara and H&M actively relied on this advertising strategy. It should be critically
50. 50
remarked, however, that Pihl (2013) failed to measure customer outcomes such as purchase
intention and brand loyalty.
Alternatively to Pihl (2013), this dissertation addressed the identified gap and established the link
between Zara’s and H&M’s social media advertising strategies and consumers’ purchase
intention and brand loyalty. Using the findings from the data analysis and findings, it is relevant
to conclude that there is a strong correlation between the brands’ social media strategies,
including display ads on Facebook and photo posting on Instagram and consumers’ willingness
to purchase. At the same time, consumers’ loyalty to Zara and H&M is predicted by video
posting on Instagram and video posting on Twitter. Therefore, the fashion brands should put a
heavier emphasis on these social media advertising strategies in order to maximise the positive
customer outcomes (Kang et al., 2013).
5.3. Research Limitations
This dissertation is focused only on two fashion brands, namely Zara and H&M, which can be
viewed as a limitation to its generalisability (Saunders et al., 2007). The inclusion of the social
media users who prefer purchasing from alternative fashion brands such as L’Oréal, Chanel or
Louis Vuitton could have resulted in more comprehensive and generalisable research outcomes.
Another limitation concerns the use of a non-random sampling technique. The point is that it is
impossible to extrapolate the identified options and views to all fashion consumers using this
technique (Richie et al., 2013).
The number of customers who could be surveyed is another limitation. In accordance with
Ghauri and Gronhaug (2005), questionnaire surveys have a low response rate since only a
proportion of those who are invited to participate in a survey would actually take part. From the
700 potential respondents who had been invited, only 200 returned their questionnaires.
Therefore, the response rate is equal to 29%. This project has not been ensured against the social
media users’ bias and errors, which can be viewed as a limitation to the validity and reliability of
51. 51
the produced analysis findings (Blumberg et al., 2005). The use of the Likert scale methodology
is another potential limitation since the research participants could overreact or underreact to
certain questionnaire questions (Zikmund, 2000).
5.4. Recommendations
The fourth objective of this dissertation was to develop recommendations concerning how the
social media marketing strategies of fast fashion brands can be enhanced to engage the UK
audiences more effectively. It can be recommended that fashion brands should put a heavier
emphasis on display ads as a means of social media advertising. By adding attractive graphical
elements to the content of their web pages, e-mails and other forms of web communication,
fashion brands are capable of contributing to a higher level of customer interest in their brands
(Zhang and Mao, 2016). However, this recommendation applies only to Facebook since it is the
only social networking service that employs this strategy (Kabadayi and Price, 2014).
It is recommended that fashion brands should more actively post photos and videos on Instagram
and Twitter. According to the research outcomes, there is a strong positive correlation between
the frequency to which fashion brands post photo and video content on these social networking
services and consumer outcomes in terms of purchase intention and brand loyalty. Therefore, by
following this recommendation, fashion brands are able to promote social media users’ purchase
intention and loyalty (Touchette et al., 2015). It should be noted that this recommendation does
not apply to Facebook. This project failed to establish any statistical link between posting photos
and videos on Facebook and the consumer outcomes.
The future researchers should also be provided with a set of recommendations as how to
overcome the identified limitations. Thus, it is recommended that the future researchers should
gather primary data not only from Zara and H&M customers, but also from those social media
users who prefer purchasing fashion goods from L’Oréal, Chanel or Louis Vuitton. It is also
52. 52
recommended that the future researchers should introduce specific measures of consumers’
loyalty and willingness to purchase into the conceptual framework.
53. 53
References
Barnes, N. G., 2014. Social commerce emerges as big brands position themselves to turn
‘follows’, ‘likes’ and ‘pins’ into sales, American Journal of Management, 14 (4), pp. 11-18.
BLS, 2015. Consumer expenditures vary by age, [online] Available at:
http://www.bls.gov/opub/btn/volume-4/consumer-expenditures-vary-by-age.htm [Accessed on
27 August 2016].
Blumberg, B., Cooper, D.R. and Schindler, P.S., 2005. Business research methods, Maidenhead:
McGraw-Hill.
Boateng, H. and Okoe, A., 2015. Consumers’ attitude towards social media advertising and their
behavioural response: The moderating role of corporate reputation, Journal of Research in
Interactive Marketing, 9 (4), pp. 299-312.
Bryman, A. and Cramar, D., 2011. Quantitative data analysis with IBM SPSS 17, 18 and 19,
Hove: Routledge.
Cao, P., Meister, S. and Klante, O., 2014. How social media influence apparel purchasing
behaviour, Marketing Review St. Gallen, 31 (6), pp. 77-86.
Carver, R. and Nash, J., 2011. Doing data analysis with SPSS: version 18.0, Boston: Cengage
Learning.
Cohen, D., 2014. Facebook, Instagram social shopping service Soldsie integrates with Magento,
[online] Available at: http://www.adweek.com/socialtimes/soldsie-magento/437018 [Accessed
on 16 August 2016].
Collis, J. and Hussey, R., 2014. Business research: a practical guide for undergraduate and
postgraduate students, 4th ed., London: Palgrave MacMillan.
54. 54
Creswell, J., 1994. Research design: quantitative and qualitative approaches, Thousand Oaks:
Sage.
De Vaus, D. A., 2002. Surveys in social research, 5th ed., London: Routledge.
Easterby-Smith, M., Thorpe, R. and Jackson, P., 2012. Management research, 4th ed., Thousand
Oaks: Sage.
Fagerstrom, A., Arntzen, E. and Foxall, G. R., 2011. A study of preferences in a simulated online
shopping environment, The Service Industries Journal, 31 (1), pp. 2603-2615.
Foxall, G. R., 1988. Radical behaviourist interpretation: generating and evaluating an account of
consumer behaviour, The Behaviour Analyst, 21 (1), pp. 321-354.
Fulgoni, G. and Lipsman, A., 2014. Numbers, please. Digital game changers: how social media
will help usher in the ear of mobile and multi-platform campaign-effectiveness measurement,
Journal of Advertising Research, 54 (1), pp. 11-16.
Geissinger, A. and Laurel, C., 2016. User engagement in social media – an explorative study of
Swedish fashion brands, Journal of Fashion Marketing and Management, 20 (2), pp. 177-190.
Ghauri, P. and Gronhaug, K., 2005. Research methods in business studies: a practical guide, 3rd
ed., Harlow: Prentice Hall.
Gill, J. and Johnson, P., 2002. Research methods for managers, 3rd ed., London: Sage.
Goh, K.-Y., Heng, C.-S. and Lin, Z., 2013. Social media brand community and consumer
behaviour: quantifying the relative impact of user- and marketer-generated content, Information
Systems Research, 24 (1), pp. 88-107.
Goodrich, K., 2011. Anarchy of effects? Exploring attention to online advertising and multiple
outcomes, Psychology and Marketing, 28 (1), pp. 417-440.
55. 55
H&M, 2015. H&M worldwide, [online] Available at: http://about.hm.com/en/About/facts-about-
hm/fashion-for-all/sales-markets/hm-worldwide.html [Accessed on 12 August 2016].
H&M, 2016a. H&M worldwide, [online] Available at: http://about.hm.com/en/About/facts-
about-hm/fashion-for-all/sales-markets.html#cm-menu [Accessed on 12 August 2016].
H&M, 2016b. H&M: official Facebook page, [online] Available at:
https://www.facebook.com/hm/ [Accessed on 16 August 2016].
H&M, 2016c. Our business concept, [online] Available at: http://about.hm.com/en/About/facts-
about-hm/about-hm/business-concept.html [Accessed on 12 August 2016].
Haans, H., Raasens, N. and van Hout, R., 2013. Search engine advertisements: the impact of
advertising statements on click-through and conversion rates, Marketing Letters, 24 (1), pp. 151-
163.
Hajili, N., 2014. A study of the impact of social media on consumers, International Journal of
Market Research, 56 (3), pp. 387-404.
Hoffman, D. L. and Fodor, M., 2010. Can you measure the ROI of your social media marketing?,
MIT Sloan Management Review, 52 (1), pp. 41-49.
Hoffman, D. L. and Novak, T. P., 2012. Why do people use social media? Empirical findings
and a new theoretical framework for social media goal pursuit, [online] Available at:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1989586 [Accessed on 16 August 2016].
Hoyer, W. D., MacInnis, D. J. and Pieters, R., 2013. Consumer behaviour, 6th ed., Mason:
Cengage Learning.
Inditex, 2016. Zara, [online] Available at: http://www.inditex.com/en/brands/zara [Accessed on
12 August 2016].
56. 56
Jung, J. M., Min, K. S. and Kellaris, J. J., 2011. How the entertainment value of online ads helps
or harms persuasion, Psychology and Marketing, 28 (1), pp. 661-681.
Kabadayi, S. and Price, K., 2014. Consumer-brand engagement on Facebook: liking and
commenting behaviours, Journal of Research in Interactive Marketing, 8 (3), pp. 203-223.
Kang, J., Johnson, K. and Wu, J., 2013. Consumer style inventory and intent to social shop
online for apparel using social networking sites, Journal of Fashion Marketing and Management,
18 (3), pp. 301-320.
Kang, J.-Y. and Johnson, K., 2015. F-Commerce platform for apparel online social shopping:
testing a Mowen’s 3M model, International Journal of Information Management, 35 (6), pp.
691-701.
Koh, Y., 2015. Facebook acquires social shopping site TheFind, [online] Available at:
http://blogs.wsj.com/digits/2015/03/13/facebook-acquires-social-shopping-site-thefind/
[Accessed on 16 August 2016].
Kulmala, M., Mesiranta, N. and Tuominen, P., 2013. Organic and amplified e-WOM in
consumer fashion blogs, Journal of Fashion Marketing and Management, 17 (1), pp. 20-37.
Lavdige, R. J. and Steiner, G. A., 1961. A model for predictive measurements of advertising
effectiveness, Journal of Marketing, 25 (1), pp. 59-62.
Lipsman, A., Mud, G., Rich, M. and Bruich, S., 2012. The power of ‘like’: how brands reach
(and influence) fans through social-media marketing, Journal of Advertising Research, 52 (1),
pp. 40-52.
McHale, R., 2012. Navigating Social Media Legal Risks: Safeguarding Your Business, London:
Que Publishing.
57. 57
Morris, T. and Wood, S., 1991. Testing the survey method: continuity and change in British
industrial relations, Work, Employment and Society, 5 (2), pp. 259-282.
Mowen, J. C., 2000. The 3M model of motivation and personality, Boston: Kluwer Academic
Press.
Nogueira, K., Veloso, A. and Santos, J., 2016. Pointwise and pairwise clothing annotation:
combining features from social media, Multimedia Tools and Applications, 75 (7), pp. 4083-
4113.
Oncel, N., 2015. Handbook of Research on Effective Advertising Strategies in the Social Media
Age, New York: IGI Global.
Park, H. and Cho, H., 2012. Social network online communities: information sources for apparel
shopping, Journal of Consumer Marketing, 29 (6), pp. 400-411.
Pihl, C., 2013. Brands, community and style – exploring linking value in fashion blogging,
Journal of Fashion Marketing and Management, 18 (1), pp. 3-19.
Remenyi, D., Williams, B., Money, A. and Swartz, E., 1998. Doing research in business and
management: an introduction to process and method, London: Sage.
Richie, J., Lewis, J., McNaughton Nicholls, C. and Ormston, R., 2013. Qualitative research
practice: a guide for social science students and researchers, London: Sage.
Robson, C., 2002. Real world research, 2nd ed., Oxford: Blackwell.
Saunders, M., Lewis, P. and Thornhill, A., 2007. Research methods for business students,
London: Pearson Education.
Saunders, M., Lewis, P. and Thornhill, A., 2009. Research Methods for Business Students,
London: Pearson Education.