FINAL_Sermonti

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MSc Marketing
Masters Dissertation
SESSION 2015/16
TITLE
THE INFLUENCE OF STORE
ENVIRONMENT ON MALE IMPULSE
BUYING BEHAVIOUR: H&M CASE
STUDY
AUTHOR
GIORGIO SERMONTI
40217934
Supervisor: Ashleigh Logan

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Declaration
I declare that the work undertaken for this MSc Dissertation has been undertaken
by myself and the final Dissertation produced by me. The work has not been
submitted in part or in whole in regard to any other academic qualification.
Title of Dissertation:
The influence of store environment on male impulse buying behaviour:
H&M case study
Name (Print): Giorgio Sermonti
Signature: ______________________________________________
Date: ______________________________________________

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I. Abstract
Purpose/Aims/Objectives: The proposed aim of this research is investigating the
influence of store atmospherics (ambient, design and social factors) on male
shopping behaviour. In particular, it aims at highlighting how the store atmospherics
of H&M’s store in Princes Street, Edinburgh, influence the male shoppers’ impulsive
buying behaviour, in relation to their sense of urge to buy and positive and negative
affect perceived in the store. The specific objectives include reviewing the related
marketing literature and then elaborating a framework of hypotheses. In particular,
the study proposes four different hypotheses based on Mohan et al. (2013) and
adapted to the environment in which the research takes place, the local H&M store
in Edinburgh.
Methodology/Approach: The research involves a quantitative methodology,
elaborating a questionnaire based on the research of Mohan et al. (2013), for a data
collection involving more than 100 male costumers at the exit of H&M store in
Princes Street, Edinburgh. The questionnaire deeply investigates the impulse
buying behaviour of the customers, asking them questions about their shopping
experience, the store environment factors, the feelings perceived while shopping
and their sense of urge to buy. Moreover, few demographic questions are included
to analyse the collected sample.
Findings/Practical Implications: The paper confirms the relationship between the
evaluation of the store environmental factors and the urge to buy and positive and
negative affect. The study underlines the evaluation of the store environment as
positively correlated to the sense of urge to buy and positive affect, confirming
previous theories (Beatty and Ferrel, 1998; Sherman et al., 1997; Mattila and Wirtz,
2001; Badgaivan and Verma, 2015). Moreover, the research confirms the negative
correlation between store environment evaluation and negative affect. The study
does not find a relevant correlation between the sense of urge to buy and the actual
number of impulses purchases. Therefore, the study proves that in the fast fashion
sector, a greater sense of urge to buy does not always lead to an increased number
of impulsive purchases.

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II. Acknowledgements
I would like to express my appreciation to my family for always supporting me
throughout my degree. They always believed in my decisions, my potential, and in
me. Thanks Mamma, Papà and Bea.
Secondly, I would like to thank my supervisor, Ashleigh, for guiding me with a
helpful and positive attitude. She constantly helped me with detailed suggestions
that brought me to a final dissertation I am very proud of.
Finally yet importantly, I would like to say thank you to the dear friends that I met
during this year. Marta, Ana and Michele brought happiness to my experience
abroad, making it unforgettable and making every single day of studying
enjoyable.

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Table of contents
I. Abstract.............................................................................................................. 5
II. Acknowledgements.......................................................................................... 7
III. List of Tables ..................................................................................................11
IV. List of Figures ................................................................................................11
1. Introduction .....................................................................................................12
1.1 Aims and Objectives........................................................................................................ 15
1.2 Chapters Summary .......................................................................................................... 16
2. Key Literature Review.....................................................................................17
2.1 Key Words .......................................................................................................................... 17
2.2 Conceptual Framework and Hypotheses................................................................... 17
2.3 Store Environment ........................................................................................................... 18
2.3.1 Ambient Factors ........................................................................................................ 19
2.3.2 Design Factors........................................................................................................... 21
2.3.3 Social Factors............................................................................................................. 23
2.4 Positive and Negative Affect ......................................................................................... 23
2.4.1 Positive Affect and Store Environment............................................................... 24
2.4.2 Negative Affect and Store Environment.............................................................. 25
2.5 Impulse Buying Behaviour............................................................................................. 25
2.5.1 Urge and Store Environment.................................................................................. 26
2.5.2 Urge and Impulse Buying........................................................................................ 27
2.6 Female and Male Shopping Behaviour....................................................................... 28
2.6.1 Female Shopping Behaviour.................................................................................. 28
2.6.2 Male Shopping Behaviour....................................................................................... 29
2.7 Chapter Summary............................................................................................................. 31
3. Methodology....................................................................................................31
3.1 Research Philosophy....................................................................................................... 31
3.3 Research Design............................................................................................................... 32
3.4 The Reliability and Validity of the Survey Instrument............................................. 33
3.5 Sample................................................................................................................................. 34
3.6 Measures............................................................................................................................. 35
3.7 Procedure ........................................................................................................................... 36
3.8 Ethical Issues .................................................................................................................... 36
3.9 Data Analysis Method...................................................................................................... 37
3.10 Chapter Summary .......................................................................................................... 37
4. Data Analysis..................................................................................................37

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4.1 Data Description ............................................................................................................... 38
4.2 Preliminary Analysis........................................................................................................ 39
4.2.1 Checking the Reliability of the Scales................................................................. 39
4.3 Hypotheses Test ............................................................................................................... 40
4.4 Chapter Summary............................................................................................................. 41
5. Findings ...........................................................................................................42
5.1 Positive Affect and Store Environment ...................................................................... 43
5.2 Negative Affect and Store Environment..................................................................... 44
5.3 Urge and Store Environment......................................................................................... 45
5.4 Urge and impulsive Buying............................................................................................ 46
5.5 Male Shopping Behaviour .............................................................................................. 47
5.6 Chapter Summary............................................................................................................. 48
6. Conclusions and Recommendations.............................................................48
6.1 Research Aims and Objectives..................................................................................... 48
6.2 Theoretical Background and Research Approach .................................................. 50
6.3 Research Findings and Contribution .......................................................................... 50
6.3.1 Academic Contribution............................................................................................ 51
6.4 Research Limitation and Implication for Further Study......................................... 51
6.5 Managerial Contribution and Recommendations .................................................... 52
References...........................................................................................................54
Appendices..........................................................................................................62
Appendix 1 - Questionnaire ..................................................................................................... 62
Appendix 2 – Descriptive statistic on the sample................................................................. 65
Appendix 3 – Correlation matrixes.......................................................................................... 66
Appendix 3.1 – Correlation with Positive Affect.................................................................... 71
Appendix 3.2 – Correlation with Negative Affect .............................................................. 71
Appendix 3.3 – Correlation with Urge................................................................................. 72
Appendix 3.4 – Correlation Urge and Impulsive Buying.................................................. 72
Appendix 4 – Statistics Positive Affect................................................................................... 73
Appendix 5 – Statistics Negative Affect ................................................................................. 75
Appendix 6 –Statistics Urge..................................................................................................... 77
Appendix 7 – Descriptive Statistics Store Environment ...................................................... 79

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III. List of Tables
Table 3.6.1 – Table of variable………………………………………………………...35
Table 4.3.1 – The Results of Hypotheses Test……………………………………... 41
Table 4.3.2 – Correlations Matrix……………………………………………………...41
IV. List of Figures
Figure 2.5.1 – Hypotheses Model..........................................................................27
Figure 5.1 – Hypotheses Model after the Analysis……………………………….....42

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1. Introduction
Fashion is a sector experiencing an incredible growth. The past two decades have
seen the arousal of several international brands in an increasing and fierce
competitive scenario (McColl and Moore, 2010). Consequently, today fashion
companies possess the world’s most powerful and valuable brands, with twelve
fashion brands in the Top 100, according to Interbrand (Interbrand, 2015).
Simultaneously, the uncertainty of the fashion industry has made speed to market a
vital component of advantage on competition for short life cycle products such as
fashion (Hayes and Jones, 2006). The shops using this strategy have been called
‘fast fashion’: “a business strategy that aims to shrink the processes involved in the
buying cycle and lead times for getting new fashion products into stores, in order to
satisfy consumer demand at its peak” (Barnes & Lea-Greenwood, 2006, p. 259).
H&M was created in 1947 as a womenswear shop in Viisteras, a small Swedish
village. Then, Henners & Mauritz established it as a global retailer producing fashion
items for entire families and selling clothes, footwear, accessories, home furnishing
and cosmetics (H&M, 2014). The sales and profit of the company have been growing
in the last years thanks to its international expansion, even if the competition
especially from Zara was increasing. Between the strongest factors for the
company’s growth, one of the most important is its retail concept. Indeed, the
decision to enter in a store, to spend time inside, and if buying or not is strongly
affected by the store environment and its outcome on consumers’ feelings. Retailers
design their shops to attract consumers, sell quickly their products, generate
unplanned purchases and provide an enjoyable shopping experience (Levy & Weitz,
2009).
Today, fast fashion plays a very important role in the global fashion world.
Celebrities and fashion icons are increasingly adopting cheap outfits and developing
collaborations with fast fashion brands. An example comes from the ‘Kate Middleton
effect’, in which every single outfit wore by the Duchess of Cambridge sold out in
few minutes. More importantly, several of the outfits came from fast fashion stores
as Topshop or Zara, bringing revenues and a high fashion sensation to this category
of clothes (Graafland and Stacey, 2016). Moreover, another major trend consists in
collaboration between fast fashion retailer and high fashion brand. The collaboration

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between Balmain and H&M has been a huge success and KENZO just announced
an upcoming collection featuring H&M (Fieldsend, 2016).
Therefore, considering the increasing market share and value of fast fashion
retailers, this research aims at focusing on H&M, analysing the influence of the store
environment on male customers. Since H&M’s retail concept is one of the strongest
elements of the brand equity, the research aims at investigating it, especially in
relation to the male impulse buying behaviour. In addition, the different components
of the store environment (ambient, design and social factors) are going to be
analysed separately in order to understand how they are influencing the customers
in creating an urge to buy.
The marketing literature about atmospherics includes studies starting from the
1970s with Kotler and the Mehrabian-Russel Model (1974), applied to test the
customers’ response to the store environment. Baker (1987) analysed the store
environment of a store defining three different groups of factors: ambient, design
and social factors. Subsequently, several research focused on the different factors
highlighting their influence on the consumer behaviour. The behaviour of male
customers while shopping has been developed in marketing literature since the
1980s (Brosdahl and Carpenter, 2010). Before the 1980s, the studies were focused
on female shoppers or on a cross-genders comparison. Otnes & McGrath (2001)
underlines the lack of research on the male segment, while states the presence of
scientific articles analysing the gender differences.
Although several studies investigate the influence of atmospherics on consumer
behaviour, only recent studies have been analysing the impulse buying behaviour
in the retail environment. One of the most recent and significant research comes
from Mohan et al. (2013). In their analysis about Indian supermarkets and impulse
buying behaviour, they underlined the necessity of further research in the fashion
category. Their research focused on analysing how four environmental elements
(lights, music, layout and employees) and two individual characteristics (impulse
buying tendency and shopping enjoyment tendency) affects impulse buying through
urge to buy impulsively and positive and negative affect. The research involved
more than 700 hundreds participants with a various sample representing the Indian
population. The study underlined that store environment drives impulse buying

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through the urge and the positive affect. It resulted also that the personality variables
influenced impulsive buying through positive affect and urge.
Therefore, the research methodology adopted in this research will be adapted from
the one used by Mohan et al. and applied in the fast fashion retail environment. In
particular, the questionnaire involves a similar structure, decreasing the number of
questions to adapt them to a fashion retail and to focus on three environmental
factors (ambient, design and social) and their influence on positive and negative
affect and urge to buy. Moreover, the sample will be reduced according to the
resources available to the author.
Research about impulse buying behaviour is focused on different components of
buying impulses such as impulse buying tendency (Weun et al., 1998), product
category variables (Jones et al., 2003), situational factors (Beatty and Ferrell, 1998),
in-store advertisements (Zhou and Wong, 2003) or store display (Ghani and Kamal,
2010). In the marketing literature, there is a general lack of research discussing
about the gender influence on impulse buying behaviour. Tifferet and Herstein
(2012) investigated the gender differences in impulse buying, aiming at providing
suggestions to retailers on how to involve differently male and female customers.
They underlined the limitation of research about gender differences and consumer
behaviour, and suggested future research on particular topics such as the impulse
buying behaviour.
This study aims at filling the gap in the literature, investigating the impulse buying
behaviour of the male customers segment in the fast fashion context. From the
literature review, there are few models connecting situational variables and impulse
buying, and none of them is applied in the fast fashion retailers’ category. This
project is based upon a model elaborated by Mohan et al. (2013) that includes
situational variables, personality traits and impulse behaviours, following Russell
and Mehrabian (1976). Precisely, this research fills this gap in the existent literature
by studying the impact of three factors of the store environment (ambient, design
and social factors) on impulse buying behaviour. Basing the research methodology
on Mohan et al. (2013), the paper includes positive and negative affect (Beatty and
Ferrell, 1998), and the urge to buy impulsively (Dholakia, 2000) as mediators of the
influence of store environment on the impulse buying behaviour.

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1.1 Aims and Objectives
The proposed aim of this research is investigating the influence of store
atmospherics (ambient, design and social factors) on male shopping behaviour. In
particular, it aims at highlighting how the store atmospherics of H&M’s store in
Princes Street, Edinburgh, influence the male shoppers’ impulsive buying
behaviour, in relation to their sense of urge to buy and positive and negative affect
perceived in the store.
The specific objectives are:
1. To critically evaluate the marketing literature about the store
atmospherics, in particular regarding ambient (music and lights), design
and social factors. The mentioned store attributes will be considered in
relation to their ability to influence consumer behaviour and more
specifically their mood, sense of urge to buy and impulsive buying
behaviour. Moreover, the paper will summarize the relevant marketing
literature about cross-gender shopping behaviour, focusing on the most
recent findings about male shopping behaviour and their impulse buying
behaviour.
2. To create a framework of hypotheses related to the marketing literature
previously reviewed. In particular, the study will propose four different
hypotheses based on Mohan et al. (2013) and adapted to the environment
in which the research takes place, the local H&M store in Edinburgh. Four
hypotheses will be elaborated regarding the relation between the store
environmental factor and the urge to buy, the positive affect and negative
affect.
3. To elaborate a questionnaire for a quantitative research methodology
based on the research of Mohan et al. (2013), for a data collection
involving at least 100 male costumers at the exit of H&M store in Princes
Street, Edinburgh. The questionnaire will deeply investigate the impulse
buying behaviour of the customers, asking them questions about their
shopping experience, the store environment factors, the feelings

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perceived while shopping and their sense of urge to buy. Moreover, few
demographic questions will be included to analyse the collected sample.
4. To illustrate the results of the data analysis, using the statistical software
SPSS. Firstly, some preliminary tests will verify the validity and reliability
of the collected data. Secondly, the data analysis will verify the
hypotheses developed before, underlining if they are confirmed. Then, the
most relevant findings will be proposed and presented in relation to the
topics of the literature review. In conclusion, a summary of the findings
will be providing highlighting the gap filled by the paper and providing
recommendations to fast fashion retailers regarding how to involve male
customers through the store environment elements.
1.2 Chapters Summary
This paper consists of six chapters, starting from the first introduction chapter that
includes an overall summary of the content and the aim and objectives of the project.
The introduction gives an overview of the content of the paper, focusing on the
context of the study, the fast fashion industry. Moreover, this first section introduces
the main relevant theories regarding the store atmospherics, starting from Kotler.
Then, several other authors are introduced, in order to underline the main topics of
the paper, consisting in store environmental factors and male buying behaviour.
The second chapter reviews the relevant literature regarding the effect of store
environment on consumer behaviour. Firstly, it reviews the major theories regarding
store environment, and then it focuses on the three factors composing it: ambient,
design and social factors. Then, a summary regarding the main research about male
and female consumer behaviour is provided to highlight the gap filled by the study
and to explain why the paper is focusing on the male segment. Moreover, four
hypotheses are developed and included in this chapter. The four hypotheses
correlate the store environment with the urge of buying and with the positive and
negative emotions generated by the environmental factors. The third chapter
describes the research methodology, including the philosophical approach, the
research design and the entire research procedure. Moreover, the chapter

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discusses the validity and reliability of the questionnaire, in order to ensure that the
questionnaire is able to answer to the four hypotheses developed.
Chapter four regards the data analysis and hypotheses test. Firstly, the chapter
includes a description of the data collected using basic descriptive statistics. Then,
some preliminary test are included to validate the data collected and the overall
questionnaire design, testing the validity and reliability. After the preliminary tests,
the researcher verifies the hypotheses through a correlation analysis using SPSS.
After the hypotheses verification, a summary of the data analysis is provided. The
fifth chapter focuses on the findings generated by the data analysis. The findings
are analysed according to the different topics highlighted in the literature review.
The paper highlights in this section the most relevant findings and compares them
to the references implemented in the literature review and to additional academic
resources. Then, the sixth and last chapter gives a final summary to the paper. It
includes a review of the content, the contribution of the paper and the limitations and
suggestions for further studies.
2. Key Literature Review
2.1 Key Words
Store environment, atmospherics, servicescape, store attributes, ambient factors,
design factors, social factors, consumer behaviour, impulse buying behaviour,
urge to buy, male shoppers, fast fashion, retail environment, H&M
2.2 Conceptual Framework and Hypotheses
This section proposes a holistic model of impulse buying with three factors (ambient
factors, design factors and social factors) elements of store environment and two
dimension (positive affect and negative affect) as antecedents of impulse buying.
The first part of the literature review focuses on the relevant theories regarding the
store environment, in particular concerning the three factors analysed by Baker
(1987): ambient, design and social factors. Then, the paper introduces the two
different dimensions (positive and negative affect) and relates them to the store
environment factors, explaining how they interact with the two dimensions according
to the marketing literature. Afterwards, the focus moves on the impulse buying
behaviour and the urge to buy, deeply investigating on these two elements and

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regarding the three environmental factors. Four different hypotheses are developed,
based on the literature reviewed and on the paper by Mohan et al. (2013). Then, the
last part of the literature review summarizes the main findings regarding the different
shopping behaviours adopted by female and male customers, aiming to motivate
the choice of this specific target for the research.
2.3 Store Environment
Kotler (1973) was the first to refer at store atmospherics as “buying environments
[designed] to produce specific emotional effects in the buyer that enhance his
purchase probability” (Kotler, 1973, p.50). He underlined their influence on
consumer behaviour, including them as part of the store image, along with other
factors such as crowding and brightness. Today, most of the research about
atmospherics are related to the Mehrabian-Russel model (Mehrabian and Russell,
1974), applied by Donovan and Rossiter in 1982 for the first time in the retail
environment. Their research belongs to the ‘environmental psychology’ studies, in
which environmental cues are connected with consumer reactions. The model
states that the environment affects the emotional state of individuals on three
dimensions: pleasure, arousal and dominance. These emotional states can
generate two responses: approach or avoidance (Mehrabian and Russell, 1974).
Afterwards, the model has been applied extensively in several studies (Donovan
and Rossiter, 1982; Gardner 1985; Donovan et al. 1994; Koo & J.-H. Lee 2011).
In the service marketing field, a relevant innovation to the model was added by
Bitner (1990) that defined the atmospherics where services take place as
‘servicescapes’. ‘Servicescapes’ are “all of the objective physical factors that can be
controlled by the firm to enhance (or constrain) employee and customer actions”
(Bitner 1992, p.65). Therefore, atmospherics are including both customers and
employees, whose behaviour has effect on other people (Baker, Levy & Grewal
1992). The literature in this field is researching to comprehend which environmental
elements could be changed in a store to rise the revenues or affect the time spent
and other behaviours.
After Kotler (1973) introduced the store atmospherics into the marketing literature,
several authors have argued about the cues influencing customers in a shopping
environment. Authors studied stimuli such as colour, music and scent measuring

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their effect on shopping behaviour. Several studies suggested universal categories
to analyse the store atmospherics. Baker (1987) defined three different groups of
factors connected with the store environment: ambient, design and social factors.
According to her, ambient factors are elements such as music, scent and
temperature do not usually generate unplanned purchase if perceived as average.
Moreover, if they are extreme they could lead to an avoidance response. The
exceptions consist in very particular cases in which the ambient is attracting
customers and generating sales. Design factors can be functional or esthetical:
functional factors are the ones facilitating the behaviour of clients, such as the layout
and comfort. Aesthetic factors are the elements which consumers observe (colours,
architectures etc.), influencing the pleasure in the environment (Aubert-Gamet,
1997). Social Factors comprise the employees in a store environment, which
appearance and behaviour impact on consumers (Baker, Levy & Grewal, 1992).
Besides, the behaviour and amount of other customers strongly influence the
environment and the customers’ behaviour.
Concluding, this first section of the literature review underlined the historical
evolution of the theories regarding the store environment, highlighting how many
factors are involved in this field. Kotler was the first to introduce the exact
terminology in the literature, but then many authors started analysing the store
environment elaborating models and underlining the necessity of further research.
2.3.1 Ambient Factors
This section investigates deeper into the three factors composing the store
environment according to Baker (1987). Ambient, design and social factor are
analysed separately involving the most relevant findings related to the consumer
behaviour. Firstly, the ambient factors and their effects on the consumer purchasing
in a defined store environment are introduced.
Ambient factors include non-visual elements such as scent, music, temperature and
lighting. Music affects moods, feelings and behaviours and consequently, it is often
employed as a stimulus in retail atmospheres. Several authors analysed music in
stores. They demonstrated that music influences sales, purchase intentions, arousal
and time spent in a certain environment, the perception of the shopping length, and

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perception of store staff and evaluation of the product and service quality (Vaccaro
et al., 2008). Several research underlined how the effect of store music depends on
other atmospheric elements. The musical genre has to fit with the atmosphere of a
store to increase the duration of staying and purchasing, for example (Baker, Levy
& Grewal 1992). In addition, if consumers enjoy the music, they generally value
more positively the environment (Dubé & Morin 2001), and spending higher
amounts of money (Caldwell & Hibbert 2002). In addition, background music, could
reduce the negative consequences of waiting time in services, since it entertain the
customers and bring to a perceived shorter waiting time (Bailey & Areni 2006).
According to Bitner (1992), the evaluation of a service is strongly influenced by the
music, which presence is a key element to obtain positive feelings towards a specific
environment. Various research focused on the valence, type and tempo of music.
The volume and type of in-store music effects customers’ perception about the
product and the store. According to Levy and Weitz (2004), tempo and volume of
the music can influence the traffic in a store environment and generate attention in
the customers. Besides, in a store environment background music may generate
desire to collaborate between the sellers and the buyers, positively affecting the
interaction (Dube et al., 1995). The effect of music on customers is stronger for
product categories like jewellery or cosmetics, where they have an intense affective
involvement. Differently, music results as less effective for product categories such
as cars and insurances, when customers present high cognitive involvement
(Bruner, 1990).
Research confirms that the scent influence consumer behaviour. Bone and Ellen
(1999) recognised 34 studies demonstrating the results of scent presence on
consumers' response. In general, a likeable aroma positively influences customers,
even without them recognising the existence of the smell (Ward, Davies & Kooijman,
2007). Retailers are generally noticing how the scent of the environment can
influence the customer evaluation on the store (Spangenberg et al., 1996).
Moreover, personal factors as gender strongly influence the outcome. The scent
has to be associated with the environment in order to have beneficial effects,
although the incongruity between the products and the scent can lead to avoidance
(Parsons, 2009). Besides, customer could perceive waiting times and the general
time spent in the store as shorter if a scent is present (Spangenberg et al., 1996).

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Previous research underlined that the presence of a scent is more relevant than its
type. Thus, customers have better evaluation of environments where there is a light
and neutral scent, then of stores without any scent (Spangenberg et al., 1996).
Various studies found no relevant effect of ambient temperature on desire to remain
longer in a shopping environment (Wakefield & Baker, 1998). An average level of
temperature is usually ignored by customers, but extreme levels can generate an
avoidance behaviour (Baker, 1987).
Another ambient factor is the lighting. Research demonstrated that lightning impacts
store image, and the handling process of products (Baker, Levy & Grewal, 1992). It
has the ability of highlighting products and creating an overall improvement of the
store image. A suitable lighting system can influence the consumer behaviour in the
retail increasing the purchases and creating an exciting environment. Vaccaro et al.
(2008) demonstrated how the level of lighting could affect the store environment. A
lower lever usually increase the comfortability of the environment, while a brighter
lightning is connected to a higher evaluation of the store and a greater product
involvement. Moreover, lights can influence customers’ loyalty towards a specific
store. (Summers and Hebert, 2001).
In conclusion, several ambient factors are important for this research. In particular,
music and the illumination are two factors strongly influencing, positively or
negatively, the shopping experience. The questionnaire and data collection will test
the direct relation between ambient factors and unplanned purchases in the male
buying behaviour.
2.3.2 Design Factors
Design factors consist in both interior and external design of a store, including
elements such as colours, store layout and products display. The exterior design is
often judged by customers, and is composed by dimensions such as sign of the
store, entrances and window displays. They build the personality and identity of a
store and help in increasing the awareness attracting customers. By the same
standard, the interior design of a store plays an important role in attracting
customers. Interior design comprises elements such as flooring, facilities and all
those features that create a unique environment.

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Colours of interior store elements have an effect on shopping behaviour (Chebat &
Morrin, 2007). Research found that colour influences emotions and mood of the
customers, and can positively of negatively impact the shopping experience. In
particular, colours can generate more attraction, a higher time spent and number of
purchases (Bellizzi, Crowley and Hasty, 1983). Colours can be analysed on three
dimensions: intensity, hue and value. For example, colours like red and blue induce
completely different psychological reactions in connection to their hue, warm and
cool (Bellizi and Hite, 1992). Light and neutral colours such as certain shades of
green or blue, generate emotions connected with calm, relax and stability.
Differently, brighter colours induce more exciting and enthusiastic feelings (Bellizi
and Hite, 1992). In addition, personal characteristics such as gender, age or
ethnicity influence customers’ responses and reactions to colours. Consequently,
the colours present in a store atmosphere have to carefully be selected according
to the market of the store, since the wrong choice could lead to a negative overall
evaluation of the products displayed (Levy and Weitz, 2009).
The layout of the store layout and the product display are two other design factors
that influence customers’ buying behaviour. Store layout has be underlined as
influencing easier shopping, avoiding excessive crowding (Levy & Weitz 2009,),
increasing sales and perceived quality (Smith & Burns 1996). Product displays can
impact the store environment in different ways; for example, they can inform the
customers about the products features or even help the clients in making their
purchase decisions (Turley and Milliman, 2000).
Crowding is also part of the design factors, since the objects present in the
environment can be perceived as obstacles. Crowding in retail environment has two
different dimensions: spatial and human. The spatial crowding is a design factor,
while the human crowding is considered social. Consequently, objects, merchandise
and furniture in the store are included in the spatial crowding (Machleit et al., 2000).
Spatial crowding can generate lower satisfaction, decreased loyalty and influence
the purchasing experience. Moreover, Chebat and Michon (2003) state that
overcrowding can bring to confusion and lead the customer to avoid the store
environment.

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2.3.3 Social Factors
Social factors include both the influence on employees and of other customers’ on
the clients of a store. Employees remarkably affect customers’ satisfaction and
mood in a store environment. Retail staffs’ number, behaviour and appearance
influences customer’s insight of a company and affects behaviours (Bitner, 1992).
Too many employees could lead to human crowding and difficulty of interaction and
browsing in the environment. Nevertheless, having a very small staff could lead to
less support to the customers and a negative perception (Baker et al., 2002).
Moreover, the behaviour and look of the staff are directly connected with the
evaluation of a service; having well-dressed employees with a positive attitude helps
in creating a successful store atmosphere while the opposite could severely damage
it. Moreover, the friendliness of personnel positively generates arousal and
pleasure, resulting in positive purchasing intensions (Baker, Levy & Grewal 1992).
Several studies discuss the effect of other customers’ presence (Machleit, Eroglu &
Mantel 2000, Machleit & Mantel 2001). Crowding has a negative effect on a store
environment, leading to negative emotions and low satisfaction (Eroglu & Machleit
1990). A research realised in a service setting underlined that crowding decreases
customers’ satisfaction in utilitarian services but may lead to increased satisfaction
in hedonic services (Noone & Mattila, 2009). The second element that makes part
of the social environment are the customers. According to Bitner (1992), their
behaviour is influencing the surrounding environment. Sherman and Smith analysed
in a study from 1987 the mood of customers in fashion stores. They found out that
moods are connected with store image, purchases, amount and time spent in the
environment. Crowding is in addition more influential in certain types of stores. For
example, in high quality stores a reduced crowding is related to a perceived premium
positioning. Consequently, human crowding can lead to an increased satisfaction in
certain stores (Machleit et al., 2000). Consequently, this study aims at analysing the
social factors as a relevant component of the store environment. Through the
questionnaire, the paper investigates the relation between crowding and employees
with the impulse buying behaviour.
2.4 Positive and Negative Affect
According to Watson et al. (1998), affect is a feeling composed by two different and
opposite dimension: positive and negative. These two dimensions are going to be

24
involved in the research methodology, as done by Mohan et al. (2013). Several
authors suggest how the customers’ perception of a store environment is strongly
connected with positive affect and negative affect. The environmental factors can
either lead to positive or negative reactions in the customers, leading to different
behaviour and purchase decisions. Donovan et al. (1994) underlined how emotional
states are related in the store environment with unplanned and impulse buying
behaviours. Customers’ intentions are significantly affected by the feelings occurring
when entering the store (Machleit and Eroglu, 2000). Following Mohan et al. (2013)
this research considers only the affect generated inside the store, negative or
positive. The focus of the study is on the internal environment of the store since the
mentioned studies used for the hypotheses development regard ambient, design
and social factors inside different types of stores. Moreover, the shopping
experience is mainly related to the inside of a store, which makes this perspective
particularly relevant. Positive affect refers to enthusiasm and an active and energetic
feeling (Beatty and Ferrell, 1998). Differently, negative affect consists in aversive
emotional states, such as irritation, sadness, anger (Watson et al., 1988).
2.4.1 Positive Affect and Store Environment
As highlighted in the previous sections, there are multiple factors generating positive
affect in a store environment. Regarding the ambient factors, shoppers can
positively respond both to music and to lightning. Music is a very relevant factor that
influences the mood of costumers (Bruner, 1990). A pleasant music can easily
generate positive affect (Garlin and Owen, 2006). In addition, a functional lighting
system can add value to a store environment, creating an exciting atmosphere and
positive affect (Smith, 1989). Yoo et al. (1998) state that music and lighting induce
together positive affect (Yoo et al., 1998). Regarding design factors, an effective
layout creates a positive experience for the customers, providing the necessary
information and signage (Spies et al., 1997). Moreover, a worthy store layout
produce positive affect helping the customers in finding what they are looking for
(Spies et al., 1997) and reducing the stress during shopping (Baker et al., 2002).
Social factors may contribute in building positive affect, thanks to the store
experience created by the employees. Their behaviour can enhance the positive

25
feelings even through simple gestures such as a smile or being easy-going (Mattila
and Enz, 2002). In conclusion:
H1. A higher evaluation of store environment factors leads to a higher level of
positive affect.
2.4.2 Negative Affect and Store Environment
At the same time, the three factors of the store environment can negatively influence
customers and their mood. Music is the factor that negatively influence the most,
when too loud or improper, inducing discomfort and negative affect (Bitner, 1992).
Lighting could also create problems in exploring the merchandise, if too low or too
high, inducing negative affect (Areni and Kim, 1994). In terms of design, disorder
and a poor layout can bring to negative affect (Spies et al., 1997). Regarding the
social factors, the staff of a store (Yoo et al., 1998) could produce negative affect,
with his/her behaviours and actions. At the same time, the negative affect would be
reflected on the company the salesperson is representing (Crosby et al., 1990), for
either bad behaviours or absence of salespersons (Jones, 1999). The related
hypothesis is:
H2. A lower evaluation of store environment factors leads to a higher level of
negative affect.
2.5 Impulse Buying Behaviour
Noble et al. (2006) state that generally male shopper have a utilitarian orientation,
being satisfied when they use promotions or spend less. They claim that the most
frequent shopping motivations is just the need to purchase a specific product. This
research anyway, is limited to the old stereotypes of men that do not enjoy shopping.
Today, men are increasingly involved with shopping, so this study aims at analysing
their impulse buying behaviour in a fast fashion retail. The research about impulse
buying behaviour is focused on the analysis of different elements and personal
characteristics such as impulse buying tendency (Weun et al., 1998), product
category variables (Jones et al., 2003), situational factors (Beatty and Ferrell, 1998),

26
in-store advertisements (Zhou and Wong, 2003) or store display (Ghani and Kamal,
2010).
Mohan et al. (2013) discussed the impact of store environment on impulse buying
behaviour, in their study, they analyse the impact of store environment on the
impulse buying behaviour of the customers of an Indian supermarket. They
simultaneously explored four separate components of store environment (layout,
light, music and employee) and two individual tendencies (impulse buying and
shopping enjoyment) to understand their relation with the urge of buying. Their
research was the first to relate store elements, personality traits and impulse buying.
It was based upon several sources including Beatty and Ferrell (1998), the first to
propose a model about impulse buying using consumer traits and situational
variables, but without including store-level factors. Moreover, Mohan et al. (2013, p.
1727) underline that “future research may explore the influence of store environment
in other retail categories such as personal products, apparel, accessories, and
personal electronics”. Therefore, this research aims at adapting the methodology
used by Mohan et al. to analyse the male impulse buying behaviour in H&M. The
scope is significantly filling the gap in the marketing literature regarding male
customers and their impulse buying behaviour in the fast fashion industry.
2.5.1 Urge and Store Environment
While browsing products in a store environment, the urge to buy impulsively (urge)
is a sudden desire experienced towards a brand or specific model (Rook, 1987;
Dholakia, 2000). This urge happens spontaneously and precedes the following
impulsive buying behaviour (Beatty and Ferrell, 1998). During their shopping in a
store, customers are going to experience several urges, that will likely lead to a
purchase decision (Beatty and Ferrell, 1998). The store environment can help in
increasing the possibility to experience the urge. Music is usually used to improve
the store environment, but it can also lead to a greater urge to buy (Mattila and Wirtz,
2001). Good music can extend the shopping period, and consequently create new
urges to buy and occasions to have unplanned purchases. The ambient factors,
including music and lightning, have the ability to increase arousal (Sherman et al.,
1997) that can activate the urge of purchasing (Eroglu and Machleit, 1993). An ideal
layout ease the customers’ shopping decisions, inducing urge in buying impulsively.
A functional layout increase the urge especially in the utilitarian customers

27
(Sherman et al., 1997). In addition, salespersons can induce the urge by guiding the
customer through the product range. Consequently:
H3. A higher evaluation of store environment factors leads to a higher impulsive
urge to buy.
2.5.2 Urge and Impulse Buying
Research demonstrates that customers often have impulsive purchases behaviours
while they browse a store during shopping (Rook, 1987; Beatty and Ferrell, 1998),
and they apparently are unable to resist to the impulsive urge of buying, even if they
try to control it (Dholakia, 2000). So, the forth hypothesis, states that there is a
positive correlation between the urge to impulsively buy and the act of doing it.
H4. A higher degree of urge to buy impulsively leads to a higher degree of impulse
buying.
Figure 2.5.1 summarizes all the hypotheses.
Figure 2.5.1 – Hypotheses Model

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2.6 Female and Male Shopping Behaviour
This finale section of the literature review focuses on highlighting the main theories
and differences regarding the male and female shopping behaviours. In particular,
it aims at underlining the gap that the paper aims to fulfil regarding the male
shopping behaviour in a fast fashion context. The first part investigates into the
theories regarding female customers, to move later the focus on the target chosen
by this paper, male customers.
2.6.1 Female Shopping Behaviour
Marketers commonly target their customers based on gender, since is a division
“easy to identify, easy to access, and large enough to be profitable” (Putrevu, 2001,
p. 1). There is a large amount of literature regarding the psychologic differences
between genders, but there is still a lack of studies about consumer behaviour and
genders (Tifferet and Herstein, 2012).This lack is unexpected, considering the
growth of importance of the male role on shopping decisions today (Harnack et al.,
1998).
According to Michon et al. (2008), the 60% of stores in shopping centers sell
footwear, apparel or accessories, and three out of four target female customers.
Consequently, most of the literature in the field investigates about the female
consumer behaviour, while just a minor part regards the opposite gender.
Kwon (1987) examined the different shopping motivations among female and male
consumers, considering their clothing purchase decisions. In his study, he
underlined the connection between clothing choices and self-enhancement in the
female market, while male customers usually purchase according to the perceived
social status and hierarchy. Successively, Kwon (1991) discovered that females
purchase behaviour is more likely to be affected by the mood states. Otnes and
McGrath (2001) further suggest that many women "shop to love" whereas men
"shop to win."
The studies regarding male and female consumer behaviours have the limitation of
using mostly female samples, and of concentrating on just few aspects of the male
shopping behaviour (Tifferet and Herstein, 2012), although researchers suggest that
shopping is accomplished equally by men and women (Otnes and McGrath, 2001).
In addition, several authors suggest that gender is extremely important in predicting

29
purchasing behaviour, so this gap in the literature has to be implemented in the near
future. A study from Falk and Campbell (1997) found that usually women enjoy more
the shopping process, and like to spend time and energy on it, while men have an
opposite behaviour. Other studies from the same years underlined the “shopping as
leisure” for women (Jansen‐Verbeke, 1987) and that women usually prefer shopping
for a larger amount of time (Dholakia, 1999).
While a review from Gentry et al. (2003) underlines the minimal influence of gender,
other research found the opposite. For example, women usually enjoy shopping
more than men (Rook and Hoch, 1985) and moreover they analyse product
information in a deeper way (Kempf et al., 2006). They also are usually buying more
impulsively than men (Coley and Burgess, 2003; Rook and Hoch, 1985) and are
more rational in their purchases, scrutinizing the products, controlling the products
on sale and preferring to choose for a wide assortment (Kruger and Byker, 2009).
In their research, Tifferet and Herstein (2012) investigated the reasons why women
are more inclined to impulse buying. Firstly, since women are more used to hedonic
consumption than men are, they are more inclined to impulse buying. Secondly,
women are usually experience more anxiety than men. Therefore, women may be
closer to buying impulsively, considering the connection between impulse buying
and negative moods (Silvera et al., 2008). Thirdly, women have a stronger need of
experiencing products touching them, which could lead to a greater sensibility to
impulse behaviours (Peck and Childers, 2006).
2.6.2 Male Shopping Behaviour
Today, young males are increasingly interested in shopping (Dholokia, 1999) and
the number of product categories with a male target is continuously growing, from
cosmetic to fashion magazines. Simultaneously, there are several men that find
shopping unpleasant and spend an extremely short time on it, showing also an
inferior interest in fashion (Cox and Dittmar, 1995). Men are usually less sensitive
to their friends’ opinions (Shoaf et al., 1995), make decisions faster (Campbell,
1997), and are more confident, independent and risks takers (Areni and Kiecker,
1993; Prince, 1993). As underlined in the introduction, Otnes & McGrath (2001)
stated the general lack of research on the male segment, which this study is
targeting. Piper and Capella (1993) were between the firsts to analyse shopping

30
behaviour of men as a distinct market segment. They strictly related men shopping
with the cars, insurances and dwelling sectors. Moreover, they identified the need
of more research in the male fashion shopping, recognising it as an upcoming trend.
The studies connecting men and shopping behaviour before the 21st century were
mainly concerned about their demographics and social characteristics. For example,
Torres et al. (2001) discussed about the male satisfaction during shopping. In
particular, they underlined in which stores men prefer to go shopping for clothing,
identified the desired attributes of the stores environment and connected the link
among the attributes and the satisfaction. One of the main themes about main
shopping is the investigation about shopping orientation. Zietsman (2006)
developed a framework relating shopping orientation and store attributes, aiming to
forecast shopping behaviour. Several studies includes shopping orientation in the
online environment. For example, Hansens and Jensen (2008) analysed shopping
orientation and online behaviour, identifying three different behaviours according to
the utilitarian or hedonistic behaviour. Research considers shopping orientation as
one of the most influential elements influencing shopping behaviour, but they
generally just highlight the differences in male and female behaviours. Therefore,
there is a need of more research concerning the male shopping behaviour, in
particular regarding their reaction to the environmental and external cues. Broasdahl
and Carpenter (2012) analysed the desired store attributes by men, their favourite
retail format and satisfaction. This study is although limited to an analysis of USA
male shoppers, defining their differences among separate generations. According
to the same authors (2010), the desired attributes and shopping behaviours are
determining the favourite retail format. They determined six types of male shoppers
characterized by similar desired store attributes, shopping orientation and preferred
retail format, underlining how a store could be designed in relation to the features of
the target market.
In the less recent researches, male shoppers were defined as customers spending
small amount of time in shopping, not taking regular responsibility for the family
purchase in clothing or grocery. Today, men’s shopping behaviour is evolving,
resulting in further studies concerning their role. These new studies implies
researches about several different topics, including: the shopping responsibilities
(Mortimer, 2012), the shopping process (Noble et al, 2006; Bakewell and Mitchell,

31
2004), the emerging motives (Seock and Sauls, 2008), the search for information
(Bakshi, 2012). Considering all the mentioned research, this study aims at
discussing the male shopping behaviour in a fast fashion store, in order to fill the
gap in the literature about this growing market segment in the retail environment.
2.7 Chapter Summary
This chapter critically reviewed the relevant marketing literature regarding consumer
behaviour and store environment. Summarising the key issues of past research, the
chapter underlined the gap in the literature. As discussed, many research focused
on the female consumers or in general on group of customers without focusing on
the male segment. Moreover, there is a general lack of investigation in the fashion
retail sector, even if generally there is a remarkable amount of literature in the store
environment field. Therefore, this study developed hypotheses to investigate the
effect of the store environment in a fast fashion context, in particular involving male
customers.
3. Methodology
3.1 Research Philosophy
Research philosophy regards “the issue of the development of knowledge and the
nature of that knowledge” (Saunders et al., 2006). Research philosophy explains
the way the researcher examines the world and reflects the research strategy and
the method used. The major philosophies described by Saunders et al. (2006) are
four: positivism, realism, interpretivism and pragmatism. The research methodology
adopted in this paper follows a positivist epistemological approach (Crotty, 1998).
Flowers (2009, p.163) stated that positivism is: “The positivist position is derived
from that of natural science and is characterised by the testing of hypotheses
developed from existing theory (hence deductive or theory testing) through
measurement of observable social realities”. Positivist philosophy thinks that the
world involves social facts and that an objective reality exists (Firestone, 1987).
Therefore, this methodology is based upon data collection of an observable reality
to develop an investigation searching for regularities and relationships to create law-
like generalisation (Gill and Johnson, 2010). The researcher generates credible data

32
observing real phenomena, consistent factor rather than impressions. The research
strategy involved may develop hypotheses with existing theory. The hypotheses
will be tested and verified or refuted, leading to further theory. In this approach, the
researcher collects data from an external position, being neutral without altering the
collection (Saunders et al., 2009). Furthermore, positivist researchers usually adopt
a highly structured method in order to be easily replicated (Gill and Johnson, 2010).
Therefore, they focus on quantifiable data to analyse them statistically. The intention
of this study is to identify, through literature review, the key theories on impulsive
consumer behaviour related to the store environment. Then, the scope of the
research is to investigate the effectiveness of the theories in the fashion retail
context, specifically regarding H&M male customers.
3.2 Research Approach
Two different approaches could be involved in a research: deductive and inductive
(Saunders et al., 2006). According to the philosophy adopted, the research
approach includes a deductive reasoning. Deduction is “an approach to the
relationship between theory and research in which the latter is conducted with
reference to hypotheses and ideas inferred from the former” (Bryman and Bell,
2011). This approach occurs when the conclusion is logically derived from the
premises, and the conclusion is true if all the hypotheses are (Ketoviki and Mantere,
2010). The main features of the deductive approach include a structured
methodology and facts that can be measured, often quantitatively. Moreover, the
deduction follows a generalisation strategy, involving a sample with a size sufficient
to generalise the findings (Saunders et al., 2009).
3.3 Research Design
The research design is developed to answer the research questions and objectives
(Saunders et al., 2006). Regarding the research method utilised, a quantitative
approach has been employed. Creswell (1994) defined the quantitative method as
“a survey design provides a quantitative or numeric description of some fraction of
the population - the sample - through the data collection process of asking questions
of people”. Quantitative methods usually comprise a structural approach for the data
collection and data analysis with statistical techniques involving numerical data
(Wilson 2003). Therefore, quantitative methods need a large amount of data in order

33
to reach a relevant validity. The main advantage of quantitative methods is the ability
of illustrating the trends of attitude and behaviour of the sample studied. This
research aim at analysing the consumer behaviour of fast fashion users, so a
quantitative method meet this objective. Moreover, a quantitative method is also
coherent with the research philosophy and approach. According to Adams et al.
(2007), quantitative methods are based on the positivism principle and involves a
deductive approach. The research method employed will be a questionnaire. The
questionnaire allows the collection of standardised data allowing comparison and
statistical analysis. Data collected through a survey can be used to suggest
relationships and produce new models. Moreover, this method ensures an impartial
approach thanks to the absence of interviewer and the fact that the question are
selected before the data collection (Crotty, 1998).
3.4 The Reliability and Validity of the Survey Instrument
Reliability concerns the robustness of the questionnaire, its ability to produce
consistent findings and the consistency of measures (Saunders et al, 2009). In
particular, the scales adopted in the questionnaire are adapted from previous
papers, so other authors ensure the reliability. However, the internal reliability of the
indicators involved will be inspected throughout the preliminary analysis. Cronbach’s
alpha coefficient is a useful tool to measure internal reliability and it should be above
.7 (Pallant, 2010). However, Cronbach’s alpha value is very sensitive to the quantity
of items in the scale, so it is appropriate for scales with more than 10 items (Pallant,
2010). Consequently, with scales including few items, the best option is the mean
inter-item correlation.
The internal validity and reliability of collected data depend largely to the questions
design, questionnaire’s structure and the strictness applied throughout the pilot
testing (Saunders et al, 2009). Validity means having measures that represents the
concept studied by the research (Bryman and Bell, 2011). The internal validity of the
research instrument is ensured linking logically the measures with an objective and
with the literature reviewed (Kumar, 2005). So, according to the research objectives,
the scales in each of the dimensions have a clear logical link. Moreover, the external
validity will be obtained selecting an effective sample, as the next section highlights.

34
3.5 Sample
Sampling methods are divided into two subcategories: probability sampling and non-
probability sampling. In probability sampling each member of the population has the
same possibility to be chosen. Otherwise, non-probability sampling consists in
select a sample following the researcher’s personal judgement (Zikmund, 1994).
This research follows a non-probability sampling in order to achieve a higher
efficiency with the reduced time and resources of the research. Non-probability
sampling includes three types: convenience, judgement and quota sampling.
Convenience sampling means that the researcher is selecting the participants
based on the proximity and accessibility of the sample (Krishnaiah and Rao, 1988).
Judgement sampling means that the author uses his/her own judgement to choose
the sampling that fits the best the features of the research. Quota sampling means
that the research involves a determined population in order to cover several
subgroups (Zikmund, 1994). Therefore, this research includes a convenience
sample, in order to collect quickly a high number of participants. In particular, the
participant have been approached at the exit of the selected store, in order to
conveniently find a population able to answer to the specific store environment
questions.
The questionnaire is based upon the work of Mohan et al. (2013), which underlined
the possibility to extend the same research methodology to the apparel retail format.
The number of customers involved is chosen according to the personal limitations
of time and resources of the researcher, and it differs from the study of Mohan et al.
since it involved more than 40 interviewers in the project. The project used a single-
stage survey method to collect data using a process similar to previous studies (e.g.
Beatty and Ferrell, 1998; Sharma et al., 2010a) in Edinburgh, United Kingdom. The
data collection involved 112 male participants to the questionnaire, randomly
approached between the customers at the exit of H&M’s store in Princes Street,
Edinburgh. Being the approach positivist, the researcher had a minimum and neutral
contact with the participants in order not to influence the result of the data collection.
In particular, the questionnaire (see Appendix 1) has been designed to include the
number of unplanned items purchased, to consider as valid only the participants
who bought without planning. In total, the valid participants were 112, while 8 were
excluded since they didn’t purchase any item. The sample is composed by 73% of

35
participants between 18 and 24 years old, with 77% old students and 89% single
men (see Appendix 2). The valid participants to the survey were 112, 9
questionnaires were excluded because the participants reported 0 unplanned
purchases, and the paper is interested in analysing just the consumer who purchase
impulsively.
3.6 Measures
The research measured all the independent and mediator variables with multiple-
item scales used in past research. The following table I shows all the scale items
and their sources. First, the researcher measured the dependent variable, impulse
purchases always. Then, he measured the store related variables, the mediators
(positive and negative affect and urge) and then the demographics. After measuring
the dependent variable, impulse purchases, he counterbalanced questions within
each category (e.g. questions pertaining to the store environment, mediators).
Table 3.6.1 – Table of variables
Ambient factors: Music (Morin and Chebat, 2005) and Light (Smith, 1989;
Areni and Kim, 1994; Summers and Hebert, 2001)
1. The store had appropriate music
2. The store had terrible music*
3. The store was correctly illuminated
4. Lighting in the store is pleasant
Design factors (Dickson and Albaum, 1977)
1. It was easy to move about in the store
2. It was easy to locate products/merchandise in the store
3. The store had attractive displays
Social factors (Dickson and Albaum, 1977; Eroglu & Machleit, 1990)
1. The store had the right number of employees
2. The store had friendly employees
3. The store was overcrowded *
Positive affect (Watson et al., 1988)
1. I felt enthusiastic while shopping today
2. I felt happy during this shopping trip
Negative affect (Watson et al., 1988)
1. I felt bored on this shopping trip
2. I felt upset during this shopping trip
Urge (Beatty and Ferrell, 1998)
1. I experienced many sudden urges to buy unplanned items
2. I experienced no sudden urges to buy unplanned items*

36
3.7 Procedure
The interviewer intercepted the shoppers upon their exit from the store and
requested their participation in the survey. Being the sample quite small, there could
have been the possibility of having a judgemental sampling. The researcher
interacted with casual customers going out from the store, not judging them on their
possible reaction to the questionnaire. Therefore, the casual choice of respondents
will lead to a representative sample. The researcher collected the questionnaire on
the different days of the week (Wednesday, Friday, Sunday) and in three different
time schedules (morning, lunch time and afternoon) in order to achieve a sample as
mixed as possible. Following Mohan et al.’s methodology (2013), the researcher
counted as valid just participants that had at least one unplanned purchase in H&M,
including in the questionnaire a question regarding their impulsive and unplanned
purchases. The questionnaire included closed rating questions to avoid coding a
large number of open question responses and simultaneously to ensure the
participants that the research methodology will involve them for a reasonable
amount of time (Saunders et al, 2009). The questionnaire (see Appendix 1) is
divided with heading in clear sections, regarding personal information, personality
traits connected with the impulse buying behaviour and questions about the store
elements (ambient, design and social factors).
3.8 Ethical Issues
In the context of research, the word “ethics” refers to the standards guiding the
conduct of the researcher behaviour during the analysis (McMillan and Weyers,
2007). The research comprises collecting data and going through a data analysis,
so both confidentiality and accuracy have been observed during the whole process.
The author considers the University’s guidelines and the Research Integrity
Approval Form of Edinburgh Napier University. The respondents of the survey have
as possibility the anonymity during the research process. The responses have been
collected from voluntaries and they did not receive rewards or incentives. They had
the opportunity to stop the questionnaire at any time; all their rights and the ethical
issues are summarised in the first paragraph of the questionnaire (see Appendix 1).
During the whole process, the relevant UK legislation has been followed. Moreover,
regarding plagiarism, any research or study helping the project will be cited in the
text and in the references.

37
3.9 Data Analysis Method
The data analysis method is based upon the use of SPSS in order to verify the
hypotheses and analyse the collected data and the variables. Firstly, SPSS will be
used to execute some basic descriptive statistic to describe the collected data.
Secondly, some preliminary tests will be used to verify the validity of the
questionnaire. Thirdly, the correlations between the variables will be analysed to
verify the hypotheses and evaluate possible trends and interesting findings.
Correlation analysis has both advantages and disadvantages. The advantage
comes from being easily able to relate different variables and to apply the same
method to future studies. It allows researchers to define the strength and direction
of a relationship so that later studies can narrow the findings down. The
disadvantages are not providing clear reasons why some variables are correlated.
A correlative finding does not reveal which variable influences the other. Therefore,
the author has to underline and discover the findings of the data analysis.
3.10 Chapter Summary
The chapter underlined the reasons why the research approached used is positivist,
and discussed about the research philosophy of the paper. Moreover, it underlined
how a quantitative method can elaborate useful data to satisfy the research
objectives. The research sample, measures and procedures are introduced. The
last part of the chapter explained the ethics of the methodology. The results and
finding following the data collection will be presented in the next chapter.
4. Data Analysis
The data were collected in the center of Edinburgh, in front of the local H&M store
in Princes Street. The total respondents were 121, of which 112 valid (92,6%),
containing a mixed sample of male participants (see Appendix 2). In this chapter,
firstly the data will be presented with a detailed description of the sample. Then, the
preliminary analysis, including checking the reliability of the scales will be
conducted. Later, using the correlation matrix from SPSS, the hypotheses
generated previously will be tested. In conclusion, a summary of the results from the
statistical analysis will be provided.

38
4.1 Data Description
The data were collected in front of the H&M on Princes Street, in Edinburgh city
centre. The research is focused upon the male buying behaviour, so all the 112 valid
respondents were men. The questionnaire included three final demographic
questions, in order to understand the basic personal features of the respondents. In
particular, the three demographic factors included were age, occupation and marital
status.
The questionnaire included four different age ranges: 18-24, 25-29, 30-34 and over
35. The data collection resulted in 73,2% of respondents between 18 and 24 years
old, with 21,4 between 25 and 29 years old and 5,4% in the other two categories
(see Appendix 2). The sample represents correctly the target market of H&M, since
the main target of the company includes teenagers and men under 30 years old
(H&M, 2015). Secondly, the questionnaire investigated the occupation of the
customers. 76,8% of the participants resulted as students, while the 23,2% defined
themselves as employed. This data is a consequence of the young average age of
the target market, which is mostly composed by high school or university attendants
(H&M, 2015). The third and last demographic factor included in the research was
the marital status. Most of the participants, 89,3%, is single, while a minor part is
married (3,6%), Divorced (1,8%) or in a civil partnership (5,4%).
When compared to the demographics of the research by Mohan et al. (2013), the
participants of this research result as sharply different. The main reason is the
different geographic location and store environment, which brought in the previous
study a more mixed sample with a remarkably higher average age. Therefore, a
sample composed by a precise target group could lead to reliable and consistent
results, and gives the possibility of further research in different store environments
and geographic locations.
Lastly, the data collection included the number of impulsive purchases experienced
during the shopping trip. From the final data analysis, nine participants were
excluded since they did not purchase any item impulsively. Out of the 112 valid
participants, 50 had just one impulsive purchase, while 60 experienced between 2
and 4 impulsive purchases and just 2 more than 5 (see Appendix 2). This value was
remarkably different from the one revealed in the study from Mohan et al. (2013),
where 58.5 participants did not present impulsive purchases. The explanation

39
comes from the different environment, since the previous study has been developed
in a supermarket, where the costumers usually buy using a shopping list (ibid).
4.2 Preliminary Analysis
The preliminary analysis is a fundamental process to inspect the validity and
reliability of the collected data. Firstly, the reliability of the scales will be analysed,
as introduced in the previous chapter. In this research, the questions is likert scale
questions from 1 to 5. Even though the scales are adapted from other academic
articles and their reliability has been tested, the reliability of the current research will
be checked to guarantee that the indicators that compose the scale are consistent.
Even if the significance tests of correlation are based on the multivariate normal
distribution, the normality will not be checked because the questionnaire is
structured with Likert scale questions (Pallant, 2010).
4.2.1 Checking the Reliability of the Scales
In the following, the reliability of the scales for the groups of variables in this research
were statistically checked, including the three factors (design, social and ambient
divided into music and light), the affects and the urge of buying (see Appendix 3 for
results). According to Pallant (2010), the range for the reliability for the mean inter-
item correlation is higher than .2, which indicates the reliability of the scales.
The mean inter-item correlation for items measuring the ambient factors and design
factors are reliable, being higher than .29 (Appendix 2). Differently, the social factors
includes very different questions that range from the employees to the other
customers, so the reliability is lower. Moreover, the urge scale is reliable with over
0,56.
The second test for the reliability was the Chronbach’s alpha. In general it is 0,6,
while deleting the negative affect is over 0,8 and highly reliable. The total reliability
is influenced by the ‘negative affect’ variable, since it is composed by two questions
regarding negative feelings. Consequently, the other values are generally not
related to the negative affect, and the reliability is confirmed even using this second
statistical instrument.

40
4.3 Hypotheses Test
This section focuses on the analysis of the data and on testing the hypotheses
developed in the literature review. The four hypotheses will be analysed separately
highlighting the influence of the three factors of the store environment. Then, a
summary will be provided and the next chapter will present a discussion on the
findings.
The first hypothesis stated that:
H1. A higher evaluation of store environment factors leads to a higher level of
positive affect.
In order to test the relation between the environment factors and the positive affect,
the Pearson correlation coefficient was used. There is a positive correlation, as
shown in the Table 4.3.2, between all the environmental factors and the positive
affect, so the hypothesis is verified, with an overall Pearson coefficient of ,51**.
Nonetheless, the correlation between the social factors and the positive affect (see
Appendix 3.1) is slightly lower, with just 0,22*, meaning that this factors has a less
relevant correlation when compared to the others.
The second hypothesis is:
H2. A lower evaluation of store environment factors leads to a higher level of
negative affect.
This hypothesis is verified, with a very high correlation, and the Pearson coefficient
of ,69** (See appendix 3.2). The correlation is negative, meaning that when the
environmental factors are better perceived, the negative affect is lower. The stronger
correlation comes from the design factors (,56**), meaning that these factors are the
ones generating less negative emotions when liked.
The third hypothesis is:
H3. A higher evaluation of store environment factors leads to a higher impulsive
urge to buy.
The third hypothesis is confirmed thanks to a high Pearson correlation coefficient of
,45**. The lower coefficient comes from the music, but it still proves a positive
correlation (See Appendix 3.3).

41
The fourth hypothesis is:
H4. A higher degree of urge to buy impulsively leads to a higher degree of impulse
buying.
This is the only hypothesis not confirmed. The correlation is positive, but not strong
enough to be relevant. As highlighted in Appendix 3.4, the Pearson Correlation
coefficient is just ,17.
Number Hypothesis content Result
H1 A higher evaluation of store environment factors lead
to a higher level of positive affect
Confirmed
H2 A lower evaluation of store environment factors lead
to a higher level of negative affect
Confirmed
H3 A higher evaluation of store environment factors leads
to a higher impulsive urge to buy
Confirmed
H4 A higher degree of urge to buy impulsively leads to a
higher degree of impulse buying
Rejected
Table 4.3.1 – The Results of Hypotheses Test
Positive affect Negative affect Urge
LIGHT ,27** -,40** ,44**
MUSIC ,53** -,48** ,23*
SOCIAL ,22* -,51** ,30**
DESIGN ,45** -,56** ,36**
Table 4.3.2 – Correlations Matrix
4.4 Chapter Summary
The fourth chapter started with the description of the data collected, analysing the
personal features of the respondent. Later, the preliminary analysis tested the
reliability and validity of the questionnaires. The main part of this chapter was the
hypotheses test, which confirmed three of the four hypotheses. The next chapter
will highlight the most important findings of this data analysis.

42
5. Findings
The data analysis found an overall good fit for the model used, with 3 of the 4
hypotheses confirmed. Specifically, it was found that the three environmental factors
analysed strongly contribute to the creation of positive/negative affect and to the
urge of buying. However, the paper did not find a strong correlation between the
urge of buying and the quantity of impulse purchases executed.
Figure 5.1 summarizes the hypotheses test.
Figure 5.1 – Hypotheses Model after the Analysis
Sherman et al. (1997) studied the influence of the store environment factors on
unplanned buying, not focusing particularly on impulse buying. Differently, Beatty
and Ferrell (1998) created a model regarding impulsive buying, but did not evaluate
the variables of the store environment. Several studies show how shopping
decisions are commonly taken inside the store environment, so it is a relevant factor
to analyse (Peck and Childers, 2006; Underhill, 1999; Zhou and Wong, 2003).
Therefore, the data analysis and findings of this paper aim at filling the gap of
marketing literature in the sector, extending Beatty and Ferrell (1998) and basing
the methodology on Mohan et al. (2013). The model of impulse buying behaviour
elaborated included the three environmental factors and the two different affects
generated by them. The model followed Jarvis et al. (2003) and Baker et al. (2002),
since the store environment is used as formative construct and is related not only
with the store patronage but also with impulse buying. Although, the paper found a
lack of support for the connection between urge of buying impulsively and effective

43
purchases, studied by Donovan et al. (1994) and Spies et al. (1997). Differently from
these two authors, the paper counted as valid just participants presenting at least
one impulsive purchase. Consequently, the result differs and underlines a lack of
correlation between a higher number of purchases and an increased sense of urge.
This research contributes to the marketing literature regarding store environment
and impulsive buying. In particular, this chapter has been divided in different section
according to the themes involved with the hypotheses.
5.1 Positive Affect and Store Environment
The first hypothesis regarded the correlation between the evaluation of the store
environment factors and the positive affect perceived by the customers. The
hypothesis was confirmed, meaning that a good perception of the environmental
factors (ambient, social and design factors) lead into the male customers of H&M in
a higher level of positive emotions such as happiness and enthusiasm. The average
enthusiasm was 3,0 out of 5, while the average happiness was 3,3, with a lower
standard deviation. Consequently, the male customers of H&M can definitely be
described as happy during their shopping trips (see Appendix 4).
In particular, the correlation was more significant regarding the ambient and design
factors, while lower with the social factors. The literature review highlighted the
strong influence of music and lights on consumer behaviour. A pleasant and
appropriate music can remarkably influence customers, generating positive affect
(Garlin and Owen, 2006). In addition, the atmosphere created by an effective lighting
system can make the difference in the store environment, generating positive affect
(Smith, 1989). Out of all the ambient factors, the two questions regarding the store
music showed a very high correlation with positive feeling. Consequently, good and
appropriate music brings positive emotions in male customers in H&M. Differently,
the lights were less relevant, even if the use of a correct illumination remarkably
participated in the overall happiness of the consumers (see Appendix 4).
Concerning design factors, an effective layout creates a positive experience for the
customers (Spies et al., 1997), reducing the stress while shopping (Baker et al.,
2002). Between the design factors, the attractiveness of the layout was defined as
the most important factor in connection to positive affect. Nonetheless, it was
underlined how the ability of easily moving in the store was not related to happiness

44
or enthusiasm, so this factor is not relevant in the selected store environment (see
Appendix 4).
The social factors were the ones with the weakest level of positive correlation.
According to Mattila and Enz (2002), they can build positive affect, thanks to the
store experience created by the employees through their behaviour. The analysis
presents in Appendix 5 shows how the attitude of H&M’s staff did not remarkably
affect the positive affect. Moreover, the right amount of crowd in the store was more
related to the happiness of the customer. The explanation is the fact that the store
environment in fast fashion stores such as H&M or Zara is not trained to have a
strong interaction with the customers (Lopez and Fan, 2009). In addition, the low
correlation with the social factors confirms precedent theories. Jung Chang et al.
(2014) stated that the social characteristics of the store did not influence
positive emotional responses from the customers. In their research, they realised
how positive affect was not directly related to salepeople’s willingness to help. Even
if the social interaction between the staff and customer was considered very
influential by previous research, the research from Jung Chan et al. and this one
suggest that ambient and design factors are more influential than are social factors
in inducing consumers’ positive reactions in the store environment.
5.2 Negative Affect and Store Environment
The second hypothesis considered the relation between the store environment
factors and the level of negative affect. The researcher stated that a lower evaluation
of the three environmental factors leads to negative emotions, such as boredom and
anger. In particular, the questionnaire underlined how both the customers did not
feel upset or bored, with a mean between 2,2 and 2,5 (see Appendix 5).The
hypothesis was verified, with a very high correlation, meaning that when the
environmental factors are better perceived, the negative affect is lower.
The stronger correlation comes from the design factors, meaning that these factors
are the one generating stronger negative emotions if disliked. In particular, disorder
and a poor layout can produce negative affect (Spies et al., 1997). From the data
analysis, the strongest correlation comes from the likeability of the layout,
demonstrating how the appearance strongly influence the shopping experience in
H&M (see Appendix 5).

45
Regarding the ambient and social factors, they have a lower correlation, but they
are still strongly related with the negative affect. According to previous research,
music is a factor that could easily generate negative emotions such as discomfort,
when too loud or improper (Bitner, 1992). Moreover, from the data analysis the
likeability of the music stands out as a very relevant factor. The ambient could also
be negatively affected by too bright or an inefficient lighting system (Areni and Kim,
1994), as a very high Pearson coefficient underlines (see Appendix 5).
In the category of the social factors, the staff of a store (Yoo et al., 1998) could
produce negative affect, with his/her behaviour. Secondly, is proved that
overcrowding could lead to negative feelings like anger, and this is the factors that
affect the most the male customers of the study (See Appendix 5).
In the study from Mohan et al. (2013) from which this paper takes inspiration, this
hypothesis was not supported. The explanation comes from the different
environment, a big mall that probably lead to a pre-existing negative affect.
5.3 Urge and Store Environment
The third and fourth hypotheses relate the store environment factors with the urge
to buy, and with the impulsive purchases. The two questions regarding the urge to
buy have a similar distribution, with average 3,2 and variance around 1,0 (see
Appendix 6). Therefore, the urge is generally perceived by the customers, and is
differently influenced by the environmental factors. The third hypothesis, specifically,
stated that a higher evaluation of store environment factor leads to an increased
impulsive urge to purchase. This hypothesis is strongly verified, confirming several
previous researches mentioned in the marketing literature (Beatty and Ferrel, 1998;
Sherman et al., 1997). Mattila and Wirtz (2001) stated that consumers who rate the
environment more positively usually demonstrate higher levels of impulsive buying
behaviour. This theory is confirmed also by more recent studies, as the one from
Badgaivan and Verma (2015), which indicated the significant positive effect of the
store environment on impulsive buying behaviour, together with other situational
elements such as the money and time availability.
The customers of a store, during their shopping trips, are going to experience
several urges, which will likely lead to purchase decisions (Beatty and Ferrell, 1998).
As proved by this paper and by the data analysis, the store environment can help in

46
increasing the possibility to experience the urge. Music can also lead to a greater
urge to buy (Mattila and Wirtz, 2001). Good music can affect the shopping period
and create new urges to buy. In fact, a music liked by the customer of the store of
H&M in Princes Street strongly leads them to perceive urge of buying (see Appendix
6). The confirmation of the hypothesis agrees with previous theories stating that
ambient factors have the ability to increase arousal (Sherman et al., 1997) that can
activate the urge of purchasing.
The store can also generate urge to buy through its layout, especially targeting
utilitarian customers, as men have been often described (Sherman et al., 1997).
Urge appears also to be positively related with the social factors. This positive effect
of social factors on impulsive buying behaviour is similar to the findings of many
other studies (Mattila and Wirtz, 2008; Tendai and Crispen, 2009). Although, when
analysing individually the questions, the salepersons do not seem to be a relevant
factor. They usually increase the urge by guiding the customers, but this is not
apparently happening in H&M where they do not contribute to the sense of urge.
This finding agrees with the paper from Park et al. (2006) who reported a weak
interaction between employee assistance and the tendency to buy impulsively. The
explanation given by the authors was that sales people could sometimes induce a
sense of instigation towards purchasing.
5.4 Urge and impulsive Buying
The only hypothesis rejected, the fourth, considered the sense of urge as positively
related to the actual impulse purchases. The correlation was positive but not strong
enough to support the hypothesis. The reason could be the fact that the research
excluded all the participants who did not have any purchase in the shop. Therefore,
all the participants had at least one impulsive purchase, confirming the hypothesis.
Apparently, the number of impulsive purchases is not strictly related with the degree
of sense of urge to buy. A customer who perceived a very high urge to buy probably
bought less than one with a lower urge. The reasons could be for example the cost
of the items, or the personality, that sometimes leads to try controlling the sense of
urge (Dholakia, 2000).

47
5.5 Male Shopping Behaviour
The marketing literature underlined in the last decades an upcoming trend
connecting males and fashion, which started the discussion regarding the utilitarian
or hedonistic male shopping behaviour. Most of the studies from the late 20th
century, underlined the utilitarian male shopping behaviour, spending a restricted
amount of time in the store environment and generally a low interest in fashion and
tendency to experience negative affects while shopping (Cox and Dittmar, 1995).
Differently, this paper highlighted a positive attitude towards unplanned purchases,
which suggests a hedonistic behaviour adopted by male fashion customers. Coley
and Burgess (2003) stated that women tend to buy more impulsively than men, but
this study proved that male customers often experience urges to buy when shopping
in H&M in the analysed store, confirming more recent theories saying that gender is
not affecting impulsive buying (Badgaiyan and Verma, 2015). Moreover, Fitzmaurice
(2008) stated that female consumers are more likely to make impulse in the fashion
or apparel sector, especially to express their identity, but this paper showed how
even male customer have an impulsive behaviour.
From the last decades, the interested in shopping by male customers has increased
(Dholokia, 1999), and the creation of stores as H&M for men is the consequence.
Michon et al. (2008) stated that 75% of fashion stores target female customers, but
the number of stores for men is increasing, and according to the results of this
research, they are conditioned and appreciate the environment that have been
created. Specifically, the ambient factors showed a very high average rate, with 3,65
for music and 3,83 for the lighting system (see Appendix 7). Therefore, the male
customers enjoyed the environment created for them, and had a positive shopping
experience, proving that today men are not just utilitarian shoppers.
Researcher as Otnes & McGrath (2001), Piper and Capella (1993) and Harnack
(1998) underlined the need of more research in the male fashion shopping,
recognising it as an upcoming and growing trend. Several studies, before the 21st
century, where focused on the demographic features of male customers, and this
study adds interesting elements. Regarding the age, the two older age groups
present just few participants, so their results are not relevant. The younger age
group, 18-24, shows a very high evaluation of the ambient factors, while the social
factors have the lowest evaluation (see Appendix 7). Differently, the age group from

48
25 to 29 years old evaluates with the lowest score the design factors, demonstrating
a higher rationality and importance given to the layout of the store.
Concerning the marital status, 100 out of 112 participants described themselves as
singles, so the other categories have just few participants. It is interesting to
underline how the married and divorced customers gave higher evaluations of all
the environmental factors, when compared to the singles. Probably they were less
critical than the single group that is usually composed by younger customers. Lastly,
the analysis of the different occupations does not bring to relevant findings. The only
main gap between employed customers and students is about the evaluation of the
ambient factors. In particular, employed customers enjoyed more the ambient of the
store, which could be part of further research.
5.6 Chapter Summary
This chapter underlined the most relevant findings of the paper, generated by the
quantitative data analysis. The chapter was structured dividing the findings in the
same way of the literature review, in order to easily highlight whether the paper
confirmed the research from other authors. The next and conclusive chapter will
summarise the findings and provide the final conclusions and recommendations.
6. Conclusions and Recommendations
The last chapter of the research includes the conclusions and recommendations.
Firstly, it revisits the aims and objectives underlining how the paper answered to
them. Secondly, the findings are summarised and the contribution of the paper is
underlined. Lastly, the chapter provides the limitations of the study and investigates
regarding the further research that could be developed in the field, providing in
addition managerial recommendations.
6.1 Research Aims and Objectives
The proposed aim of this research was investigating the influence of store
atmospherics (ambient, design and social factors) on male shopping behaviour. This
aim was met by distributing a questionnaire to the customers of H&M’s store in
Princes Street, Edinburgh, and analysing the collected data.

49
The first and second objectives were achieved in the second chapter, thanks to a
throughout review of the marketing literature. Firstly, the paper underlined the
literature regarding the ambient, design and social factors of the store atmospherics.
Secondly, it reviewed the literature about cross-gender shopping behaviour,
focusing on the male shopping behaviour and their impulse buying behaviour. In
particular, the elements were related in order to highlight how every factor influences
the impulsive consumer behaviour, with a special focus on the fashion environment.
At the end of the literature review, four hypotheses have been developed according
to the major theories mentioned. The hypotheses were then included in the
questionnaire in order to be verified through data analysis. The objective of the
literature review was to underline the gap that this study meant to fill. In particular,
the gap the paper filled includes male consumer behaviour and impulsive buying in
the fast fashion environment, investigating the emotional and unplanned reaction
that the environmental factors generate on them. Previous studies in fact focused
mainly on female customer, underlining how male customers in the fashion
environment act generally in a utilitarian way (Piper and Capella, 1993; Michon et
al., 2008; Tifferet and Herstein, 2012).
The third objective regarded the elaboration of a questionnaire involving at least 100
participants. This objective was fulfilled with 112 valid participants, answering to
questions related to the marketing literature previously analysed in order to obtain
findings and conclusions that would fill the highlighted gap.
The fourth and last objective regarded the analysis of the data collected, by using a
statistical software, SPSS. The objective was obtained involving basic descriptive
statistics and more complex analysis such as the correlation matrix. The data were
firstly analysed using some preliminary test in order to ensure their validity and
reliability. In particular, the reliability was ensured by calculating the mean inter-item
correlation (Pallant, 2010). Then, the hypotheses were tested and the most relevant
findings were highlighted in the fifth chapter. In the next sections of the sixth and
conclusive chapter, the findings will be summarised to underline the most relevant
ones.

50
6.2 Theoretical Background and Research Approach
In order to achieve the above mentioned aims and objectives, the research
developed a theoretical background combining several marketing theories. Firstly,
the literature review included theories from Kotler (1973) and regarding the
Mehrabian-Russel model (Mehrabian and Russell, 1974), applied by Donovan and
Rossiter in 1982 for the first time in the retail environment. In this first part the paper
explained the origins of the studies about atmospherics, focusing on the model
elaborated by Mehrabian and Russell, used by several other authors (Donovan and
Rossiter, 1982; Gardner 1985; Donovan et al. 1994; Koo & J.-H. Lee 2011).
Secondly, the paper analysed the recent theories regarding the elements of the
store environment and environmental factors (Levy and Weitz, 2004; Ward, Davies
& Kooijman, 2007; Vaccaro et al., 2008; Levy and Weitz, 2009; Noone & Mattila,
2009). Then a model has been built, based on Mohan et al. (2013) and adapted to
the fast fashion environment, to include four hypotheses to be tested.
Based on this theoretical model, the research conducted a quantitative research to
investigate the relationship between the environmental factors and other elements,
such as the urge to buy and the positive and negative affect generated by the store
environment. Through delivering a questionnaire to more than 100 customers, the
paper investigated the evaluation of the local H&M customers on several
atmospheric elements. These data were later analysed through SPSS on two main
aspects. Firstly, whether the hypotheses and relationships among the variables
were verified. Secondly, the evaluation of the store environmental factors, the
personal affects and urge to buy were individually investigated.
6.3 Research Findings and Contribution
This research confirmed three of the four hypotheses developed. In particular, it
verified the relationship between the evaluation of the store environmental factors
and the urge to buy and positive and negative affect. The evaluation of the store
environment has been found as positively correlated to the sense of urge to buy and
positive affect, confirming previous theories (Beatty and Ferrel, 1998; Sherman et
al., 1997; Mattila and Wirtz, 2001; Badgaivan and Verma, 2015). The analysis of the
responses highlighted a general positive attitude towards the shopping trips in the

51
analysed environment, with a strong relation between the evaluation of ambient and
design factors and positive attitudes. Similarly, ambient and design factors are
strongly and positively correlated to the urge of buying. In addition, the examined
male customers demonstrated an averagely high sense of urge to buy, confirming
the marketing theories stating that the position of male customers is moving towards
a more hedonistic behaviour (Badgaiyan and Verma, 2015; Dholokia, 1999). The
third hypothesis confirmed regarded the negative correlation between store
environment evaluation and negative feelings such as boredom and anger.
Moreover, the study did not find a relevant correlation between the sense of urge to
buy and the actual number of impulses purchases. Therefore, the study proved that
in the fast fashion sector, a greater sense of urge to buy does not always lead to an
increased number of impulsive purchases.
6.3.1 Academic Contribution
This research provides a theoretical framework connecting a part of the marketing
literature including various atmospherics theories (see Table 1). The study is based
upon the framework elaborated by Mohan et al. (2013), but it is customised for the
specific environment, the fast fashion industry. In particular, it contributes to the
academic material in the consumer behaviour field, by combining relevant theories
regarding store atmospherics and male consumer behaviour theories. This
framework extended the studies that have been developed before, that were not
usually focused upon male consumers (Rook, 1987; Beatty and Ferrell, 1998;
Dholakia, 2000; Mohan et al., 2013). The data analysis highlighted the validity and
reliability of the data collection methodology that could be applied in different
situations. Even though the findings did not support all the hypotheses of the model,
this model may still be applicable to similar contexts, as the last section of the paper
will underline.
6.4 Research Limitation and Implication for Further Study
The research had few major limitations, linked to the situation in which it was
developed. The methodology was based upon the review of the marketing literature
in the field and according to the objectives of the paper. Nonetheless, the research
had the main limitation connected with the limited resources of the researcher.
Previous research, as the one from Mohan et al. (2013), were conducted by multiple

52
interviewers, which were able to collect easily a very high amount of participants.
With a quantitative research, the number of participants is strictly correlated with the
validity and relevance of a study, so the limited resources available afflict this paper.
A second limitation come from the statistical analysis of data with a restricted
number of participants. The consequence is an analysis with results that are not
strongly reliable and trustable. Therefore, the consequent data analysis and findings
could present a weak academic relevance.
In conclusion, it is suggested that further study might need to include an extended
quantitative research and a qualitative research to investigate in a more detailed
way in the thoughts of male customers. Moreover, the model could be applied in
other fast fashion environments to verify the same hypotheses, changing store or
geographic location. Future research could also focus on different demographic
groups of customers, in order to understand how and why the store environment
differently influences them. Having more resources, the framework could include
more elements, investigating more deeply into the components of the three
environmental factors. For example, further research could focus on using the same
methodology to gather information regarding the relation between lighting systems
or in store music with impulsive purchases in fast fashion environments. In addition,
further research could be developed on the online store of the company analysed in
the paper, H&M. Today, the e-commerce is a business fastly growing, and many
researches as the one from Floh and Madlberger (2013) are analysing the cues
affecting impulse online behaviour. Therefore, this type of research could extend the
understanding of the behaviour of the customer of H&M in the online environment.
6.5 Managerial Contribution and Recommendations
The current research found a relationship between store environment and urge to
buy, positive and negative affect. In addition, it highlighted how the different factors
composing the store environment influence the customers’ perception and filled the
gap about male customers in a fast fashion store environment.
These findings provide implications for the strategy of fast fashion stores similar to
H&M, in order to increase the impulsive buying for this specific target of customers.
On the one hand, marketers should realize the importance of the store elements,

53
knowing how they strongly influence the urge of buying and feelings perceived by
the customers. According to the results, they can easily create more urge of buying
and positive affect by improving the ambient and design factors. For example, they
could study the preferences of music, lights and layout of their customer to increase
remarkably the evaluation of their store environment. Moreover, the study suggests
how even for a male target, these elements are extremely relevant, so there should
be an equal focus on the environment of the male sector of a store than on the
female one.
In conclusion, this research underlined how the environmental elements have a
strong behavioural effect on the customer of a fast fashion store. Therefore, when
planning an environment, the managers have to consider carefully the elements
analysed throughout this paper.

54
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62
Appendices
Appendix 1 - Questionnaire
Consumer behaviour questionnaire
Your participation to the study is voluntary and greatly appreciated. The information that
you provide in this questionnaire will remain anonymous and strictly confidential in
compliance with the Data Protection Act and Edinburgh Napier University Ethical
Guidelines.
My name is Giorgio Sermonti and I am currently a student at Edinburgh Napier University
undertaking a research project to analyse impulse buying behaviour as a part of my
dissertation. -
_________________________________________________________________
_______
Part 1: Please read the questions and tick the answer that best
reflects your shopping experience in H&M
Q1 The store was overcrowded
Q2 The store had the right number of employees
Q3 The store was correctly illuminated
Q4 I felt upset during this shopping trip
Q5 I felt enthusiastic while shopping today
Q6 I experienced no sudden urges to buy unplanned items
1
Strongly
Disagree
2
Disagree
3
Undecided
4
Agree
5
Strongly
Agree

63
Q7 The store had appropriate music
Q8 The store had attractive displays
Q9 I felt happy during this shopping trip
Q10 I experienced many sudden urges to buy unplanned items
Q11 The store had terrible music
Q12 It was easy to move about in the store
Q13 The store had friendly employees
Q14 Lighting in the store is pleasant
Q15 It was easy to locate products/merchandise in the store
Q16 I felt bored on this shopping trip
1
Strongly
Disagree
2
Disagree
3
Undecided
4
Agree
5
Strongly
Agree

64
Part 2: Additional information
Number of purchases: 0 1 2-4 5+
Age: 18-24 25-29 30-34 35+
Occupation: Student Employed Self-Employed Retired
Marital status: Single Married Divorced Widowed Civil
partnership
_________________________________________________________________
Thank you for taking the time to complete the questionnaire. If you are interested in the
results or have any questions, please do not hesitate to contact me.
giorgio.semonti@gmail.com
Giorgio Sermonti - Edinburgh Napier University

65
Appendix 2 – Descriptive statistic on the sample
Purchases
Frequency Percentage Valid
Percentage
Cumulative
Percentage
Validi
1 50 44,6 44,6 44,6
2-4 60 53,6 53,6 98,2
5+ 2 1,8 1,8 100,0
Totale 112 100,0 100,0
Age
Frequency Percentage Percentuale
valida
Percentuale
cumulata
Validi
18-24 82 73,2 73,2 73,2
25-29 24 21,4 21,4 94,6
30-34 2 1,8 1,8 96,4
35+ 4 3,6 3,6 100,0
Totale 112 100,0 100,0
Occupation
Frequenza Percentuale Percentuale
valida
Percentuale
cumulata
Validi
Student 86 76,8 76,8 76,8
Employed 26 23,2 23,2 100,0
Totale 112 100,0 100,0
MaritalStatus
Frequenza Percentuale Percentuale
valida
Percentuale
cumulata
Validi
Single 100 89,3 89,3 89,3
Married 4 3,6 3,6 92,9
Divorced 2 1,8 1,8 94,6
Civil partneship 6 5,4 5,4 100,0
Totale 112 100,0 100,0

66
Appendix 3 – Correlation matrixes
Correlations
ENVIRONMEN
T
POSITIVE NEGATIVE URGE
ENVIRONMENT
Pearson Correlation 1 ,513**
-,690**
,451**
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
POSITIVE
Pearson Correlation ,513**
1 -,604**
,365**
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
NEGATIVE
Pearson Correlation -,690**
-,604**
1 -,410**
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
URGE
,365**
-,410**
1
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
**. Correlation is significant at the 0.01 level (2-tailed).
Correlations – Social Factors
The store had
the right
number of
employees
The store had
friendly
employees
The store was
overcrowded
The store had the right
number of employees
Pearson Correlation 1 ,187*
,329**
Sig. (2-tailed) ,048 ,000
N 112 112 112
The store had friendly
employees
Pearson Correlation ,187*
1 ,067
Sig. (2-tailed) ,048 ,483
N 112 112 112
The store was overcrowded
,067 1
Sig. (2-tailed) ,000 ,483
N 112 112 112
*. Correlation is significant at the 0.05 level (2-tailed).

67
Correlations – Music – Ambient Factors
The store had
appropriate
music
The store had
terrible music
The store had appropriate
music
Sig. (2-tailed) ,000
N 112 112
The store had terrible music
1
N 112 112
Correlations – Design Factors
The store had
attractive
displays
It was easy to
locate
products/merch
andise in the
store
It was easy to
move about in
the store
The store had attractive
displays
,346**
Sig. (2-tailed) ,002 ,000
N 112 112 112
It was easy to locate
products/merchandise in the
store
1 ,405**
Sig. (2-tailed) ,002 ,000
N 112 112 112
It was easy to move about in
the store
,405**
1
Sig. (2-tailed) ,000 ,000
N 112 112 112
Correlations – Light – Ambient Factors
Lighting in the
store is
pleasant
The store was
correctly
illuminated
Lighting in the store is
pleasant
N 112 112
The store was correctly
illuminated
1
N 112 112

68
Correlations
I experienced
no sudden
urges to buy
unplanned
items
I experienced
many sudden
urges to buy
unplanned
items
I experienced no sudden
urges to buy unplanned
items
N 112 112
I experienced many sudden
items
1
N 112 112
Reliability Statistics
Cronbach's
Alpha
N of Items
,664 16
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total
Correlation
Cronbach's
Alpha if Item
Deleted
MUSIC1: The store had
appropriate music
48,9732 30,567 ,400 ,631
MUSIC2R: The store had
terrible music
48,6339 29,189 ,560 ,609
SOCIAL2: The store had
the right number of
employees
49,2768 32,328 ,279 ,648
LIGHT1: The store was
correctly illuminated
48,5446 30,953 ,406 ,632
POS1: I felt enthusiastic
while shopping today
49,4196 29,867 ,518 ,617
DES1: The store had
attractive displays
48,9732 29,179 ,563 ,609

69
POS1: I felt happy during
this shopping trip
49,1696 31,169 ,419 ,632
URGE2: I experienced
many sudden urges to buy
unplanned items
49,3125 29,766 ,442 ,624
DES2: It was easy to move
about in the store
49,1875 28,460 ,481 ,614
friendly employees
48,9911 33,685 ,146 ,662
LIGHT2: Lighting in the
store is pleasant
48,7054 32,102 ,316 ,644
DES3: It was easy to locate
store
49,2232 30,247 ,389 ,631
SOCIAL1R: The store was
overcrowded
49,0714 31,166 ,360 ,637
URGE1R: I experienced no
sudden urges to buy
unplanned items
49,0804 28,561 ,491 ,613
NEG1: I felt upset during
this shopping trip
50,2232 41,941 -,562 ,755
NEG2: I felt bored on this
shopping trip
50,0446 41,917 -,693 ,744
Without negative affect
Reliability Statistics
Cronbach's
Alpha
N of Items
,818 14

70
Item-Total Statistics
Scale Mean if
Item Deleted
Scale Variance
if Item Deleted
Corrected Item-
Total
Correlation
Cronbach's
Alpha if Item
Deleted
MUSIC1: The store had
appropriate music
44,3304 43,196 ,412 ,810
MUSIC2R: The store had
terrible music
43,9911 41,198 ,603 ,795
the right number of
employees
44,6339 44,919 ,325 ,815
LIGHT1: The store was
43,9018 43,387 ,442 ,807
POS1: I felt enthusiastic
while shopping today
44,7768 41,995 ,563 ,799
DES1: The store had
attractive displays
44,3304 41,376 ,588 ,797
POS1: I felt happy during
this shopping trip
44,5268 43,333 ,487 ,805
URGE2: I experienced
many sudden urges to buy
unplanned items
44,6696 41,899 ,482 ,804
DES2: It was easy to move
about in the store
44,5446 40,647 ,497 ,803
friendly employees
44,3482 46,625 ,182 ,823
LIGHT2: Lighting in the
store is pleasant
44,0625 45,068 ,321 ,815
DES3: It was easy to locate
store
44,5804 42,480 ,428 ,809
SOCIAL1R: The store was
overcrowded
44,4286 43,598 ,398 ,810
URGE1R: I experienced no
sudden urges to buy
unplanned items
44,4375 41,149 ,477 ,805

71
Appendix 3.1 – Correlation with Positive Affect
Correlations
SOCIAL DESIGN MUSIC LIGHT POSITIVE
SOCIAL
,248**
,280**
,221*
Sig. (2-tailed) ,000 ,008 ,003 ,019
N 112 112 112 112 112
DESIGN
1 ,546**
,350**
,451**
Sig. (2-tailed) ,000 ,000 ,000 ,000
N 112 112 112 112 112
MUSIC
,546**
1 ,143 ,529**
Sig. (2-tailed) ,008 ,000 ,132 ,000
N 112 112 112 112 112
LIGHT
,350**
,143 1 ,269**
Sig. (2-tailed) ,003 ,000 ,132 ,004
N 112 112 112 112 112
POSITIVE
Pearson Correlation ,221*
,451**
,529**
,269**
1
Sig. (2-tailed) ,019 ,000 ,000 ,004
N 112 112 112 112 112
Appendix 3.2 – Correlation with Negative Affect
Correlations
NEGATIVE SOCIAL DESIGN MUSIC LIGHT
NEGATIVE
Pearson Correlation 1 -,509**
-,560**
-,478**
-,398**
Sig. (2-tailed) ,000 ,000 ,000 ,000
N 112 112 112 112 112
SOCIAL
1 ,376**
,248**
,280**
Sig. (2-tailed) ,000 ,000 ,008 ,003
N 112 112 112 112 112
DESIGN
,376**
1 ,546**
,350**
Sig. (2-tailed) ,000 ,000 ,000 ,000
N 112 112 112 112 112
MUSIC
,248**
,546**
1 ,143
Sig. (2-tailed) ,000 ,008 ,000 ,132
N 112 112 112 112 112
LIGHT
,280**
,350**
,143 1
Sig. (2-tailed) ,000 ,003 ,000 ,132
N 112 112 112 112 112

72
Appendix 3.3 – Correlation with Urge
Correlations
SOCIAL DESIGN MUSIC LIGHT URGE
SOCIAL
,248**
,280**
,300**
Sig. (2-tailed) ,000 ,008 ,003 ,001
N 112 112 112 112 112
DESIGN
1 ,546**
,350**
,358**
Sig. (2-tailed) ,000 ,000 ,000 ,000
N 112 112 112 112 112
MUSIC
,546**
1 ,143 ,226*
Sig. (2-tailed) ,008 ,000 ,132 ,016
N 112 112 112 112 112
LIGHT
,350**
,143 1 ,436**
Sig. (2-tailed) ,003 ,000 ,132 ,000
N 112 112 112 112 112
URGE
,358**
,226*
,436**
1
Sig. (2-tailed) ,001 ,000 ,016 ,000
N 112 112 112 112 112
Appendix 3.4 – Correlation Urge and Impulsive Buying
Correlations
URGE kk
URGE
Pearson Correlation 1 ,168
N 112 112
Purchas
es
Pearson Correlation ,168 1
N 112 112

73
Appendix 4 – Statistics Positive Affect
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
I felt enthusiastic while
shopping today
112 1,00 4,00 3,0357 ,86918
I felt happy during this
shopping trip
112 1,00 5,00 3,2857 ,79897
Valid N (listwise) 112
Correlations
POSITIVE The store
had terrible
music
The store
had
appropriate
music
Lighting in
the store is
pleasant
The store
was
correctly
illuminated
POSITIVE
Pearson
Correlation
1 ,495**
,448**
,193*
,250**
Sig. (2-tailed) ,000 ,000 ,042 ,008
N 112 112 112 112 112
The store had terrible
music
Pearson
Correlation
,495**
1 ,591**
,138 ,233*
Sig. (2-tailed) ,000 ,000 ,148 ,013
N 112 112 112 112 112
The store had
appropriate music
Pearson
Correlation
,448**
,591**
1 ,018 ,032
Sig. (2-tailed) ,000 ,000 ,847 ,738
N 112 112 112 112 112
Lighting in the store
is pleasant
Pearson
Correlation
,193*
,138 ,018 1 ,368**
Sig. (2-tailed) ,042 ,148 ,847 ,000
N 112 112 112 112 112
The store was
Pearson
Correlation
,250**
,233*
,032 ,368**
1
Sig. (2-tailed) ,008 ,013 ,738 ,000
N 112 112 112 112 112
Correlations

74
POSITI
VE
The
store
had
attracti
ve
display
s
It
was
eas
y to
mov
e
abo
ut in
the
stor
e
It was easy to
locate
products/merchan
dise in the store
The
store
had
friendly
employe
es
The
store
had the
right
number
of
employe
es
The store
was
overcrowd
ed
POSITIVE
Pearson
Correlati
on
1 ,591**
,174 ,300**
,106 ,117 ,219*
Sig. (2-
tailed)
,000 ,067 ,001 ,264 ,219 ,020
N 112 112 112 112 112 112 112
The store had
attractive displays
Pearson
Correlati
on
,591**
1
,346
**
,290**
,064 ,225*
,280**
Sig. (2-
tailed)
,000 ,000 ,002 ,501 ,017 ,003
N 112 112 112 112 112 112 112
It was easy to
move about in the
store
Pearson
Correlati
on
,174 ,346**
1 ,405**
,085 ,204*
,361**
Sig. (2-
tailed)
,067 ,000 ,000 ,374 ,031 ,000
N 112 112 112 112 112 112 112
It was easy to
locate
products/merchan
dise in the store
Pearson
Correlati
on
,300**
,290**
,405
**
1 ,236*
,148 ,101
Sig. (2-
tailed)
,001 ,002 ,000 ,012 ,119 ,291
N 112 112 112 112 112 112 112
The store had
friendly
employees
Pearson
Correlati
on
,106 ,064 ,085 ,236*
1 ,187*
,067
Sig. (2-
tailed)
,264 ,501 ,374 ,012 ,048 ,483
N 112 112 112 112 112 112 112

75
The store had the
right number of
employees
Pearson
Correlati
on
,117 ,225*
,204
*
,148 ,187*
1 ,329**
Sig. (2-
tailed)
,219 ,017 ,031 ,119 ,048 ,000
N 112 112 112 112 112 112 112
The store was
overcrowded
Pearson
Correlati
on
,219*
,280**
,361
**
,101 ,067 ,329**
1
Sig. (2-
tailed)
,020 ,003 ,000 ,291 ,483 ,000
N 112 112 112 112 112 112 112
Appendix 5 – Statistics Negative Affect
I felt bored on this shopping
trip
112 1,00 4,00 2,4107 ,77754
I felt upset during this
shopping trip
112 1,00 5,00 2,2321 1,02212
Correlations
It was easy to
move about in
the store
The store had
attractive
displays
It was easy to
locate
products/mercha
ndise in the
store
NEGATIVE
the store
,405**
-,385**
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
displays
1 ,290**
-,474**
Sig. (2-tailed) ,000 ,002 ,000
N 112 112 112 112
store
,290**
1 -,418**
Sig. (2-tailed) ,000 ,002 ,000
N 112 112 112 112
NEGATIVE Pearson Correlation -,385**
-,474**
-,418**
1

76
Sig. (2-tailed) ,000 ,000 ,000
N 112 112 112 112
Correlations
NEGATIVE The store
had
appropriate
music
Lighting in
the store is
pleasant
The store
was
correctly
illuminated
The store
had terrible
music
NEGATIVE
Pearson
Correlation
1 -,315**
-,235*
-,416**
-,539**
Sig. (2-tailed) ,001 ,013 ,000 ,000
N 112 112 112 112 112
The store had
appropriate music
Pearson
Correlation
-,315** 1 ,018 ,032 ,591**
Sig. (2-tailed) ,001 ,847 ,738 ,000
N 112 112 112 112 112
Lighting in the store
is pleasant
Pearson
Correlation
-,235*
,018 1 ,368**
,138
Sig. (2-tailed) ,013 ,847 ,000 ,148
N 112 112 112 112 112
The store was
Pearson
Correlation
-,416**
,032 ,368**
1 ,233*
Sig. (2-tailed) ,000 ,738 ,000 ,013
N 112 112 112 112 112
The store had
terrible music
Pearson
Correlation
-,539**
,591**
,138 ,233*
1
Sig. (2-tailed) ,000 ,000 ,148 ,013
N 112 112 112 112 112
Correlations
NEGATIVE The store had
the right number
of employees
The store had
friendly
employees
The store was
overcrowded
NEGATIVE
Pearson Correlation 1 -,378**
-,255**
-,399**
Sig. (2-tailed) ,000 ,007 ,000
N 112 112 112 112

77
The store had the right
number of employees
1 ,187*
,329**
Sig. (2-tailed) ,000 ,048 ,000
N 112 112 112 112
The store had friendly
employees
,187*
1 ,067
Sig. (2-tailed) ,007 ,048 ,483
N 112 112 112 112
The store was overcrowded
,329**
,067 1
Sig. (2-tailed) ,000 ,000 ,483
N 112 112 112 112
Appendix 6 –Statistics Urge
I experienced many sudden
items
112 1,00 5,00 3,1429 ,99419
I experienced no sudden
items
112 1,00 5,00 3,3750 1,09975
Correlations
URGE The store
had terrible
music
The store
had
appropriate
music
Lighting in
the store is
pleasant
The store
was
correctly
illuminated
URGE
Pearson
Correlation
1 ,247**
,157 ,238*
,474**
Sig. (2-tailed) ,009 ,098 ,012 ,000
N 112 112 112 112 112
The store had terrible
music
Pearson
Correlation
,247**
1 ,591**
,138 ,233*
Sig. (2-tailed) ,009 ,000 ,148 ,013
N 112 112 112 112 112
The store had
appropriate music
Pearson
Correlation
,157 ,591**
1 ,018 ,032

78
Sig. (2-tailed) ,098 ,000 ,847 ,738
N 112 112 112 112 112
Lighting in the store is
pleasant
Pearson
Correlation
,238*
,138 ,018 1 ,368**
Sig. (2-tailed) ,012 ,148 ,847 ,000
N 112 112 112 112 112
The store was
Pearson
Correlation
,474**
,233*
,032 ,368**
1
Sig. (2-tailed) ,000 ,013 ,738 ,000
N 112 112 112 112 112
Correlations
URGE It was easy to
move about in
the store
The store had
attractive
displays
It was easy to
locate
products/merch
andise in the
store
URGE
,278**
,245**
Sig. (2-tailed) ,002 ,003 ,009
N 112 112 112 112
the store
1 ,346**
,405**
Sig. (2-tailed) ,002 ,000 ,000
N 112 112 112 112
displays
,346**
1 ,290**
Sig. (2-tailed) ,003 ,000 ,002
N 112 112 112 112
store
,405**
,290**
1
Sig. (2-tailed) ,009 ,000 ,002
N 112 112 112 112

79
Appendix 7 – Descriptive Statistics Store Environment
SOCIAL 112 1,67 4,33 3,3423 ,55967
DESIGN 112 1,67 4,67 3,3274 ,76587
MUSIC 112 1,00 5,00 3,6518 ,82155
LIGHT 112 2,00 5,00 3,8304 ,67967
SOCIAL DESIGN MUSIC LIGHT * Age
Age SOCIAL DESIGN MUSIC LIGHT
18-24
Mean 3,3333 3,3496 3,6220 3,8537
N 82 82 82 82
Std. Deviation ,60632 ,72559 ,82985 ,68713
25-29
Mean 3,2917 3,1111 3,6667 3,6250
N 24 24 24 24
Std. Deviation ,39700 ,90445 ,81650 ,66349
30-34
Mean 3,3333 3,6667 3,0000 4,0000
N 2 2 2 2
Std. Deviation ,00000 ,00000 ,00000 ,00000
35+
Mean 3,8333 4,0000 4,5000 4,5000
N 4 4 4 4
Std. Deviation ,33333 ,38490 ,00000 ,00000
Total
Mean 3,3423 3,3274 3,6518 3,8304
N 112 112 112 112
Std. Deviation ,55967 ,76587 ,82155 ,67967
SOCIAL DESIGN MUSIC LIGHT * Occupation
Occupation SOCIAL DESIGN MUSIC LIGHT
Student
Mean 3,3333 3,3256 3,5814 3,8372
N 86 86 86 86
Std. Deviation ,56011 ,70289 ,72704 ,66616
Employed
Mean 3,3718 3,3333 3,8846 3,8077
N 26 26 26 26
Std. Deviation ,56825 ,96148 1,06120 ,73589
Total
Mean 3,3423 3,3274 3,6518 3,8304
N 112 112 112 112
Std. Deviation ,55967 ,76587 ,82155 ,67967

80
SOCIAL DESIGN MUSIC LIGHT * MaritalStatus
MaritalStatus SOCIAL DESIGN MUSIC LIGHT
Single
Mean 3,3500 3,2667 3,6200 3,8000
N 100 100 100 100
Std. Deviation ,56928 ,76688 ,78212 ,69631
Married
Mean 3,6667 4,5000 4,7500 4,0000
N 4 4 4 4
Std. Deviation ,47140 ,19245 ,28868 ,57735
Divorced
Mean 3,6667 3,6667 4,5000 4,5000
N 2 2 2 2
Std. Deviation ,00000 ,00000 ,00000 ,00000
Civil partneship
Mean 2,8889 3,4444 3,1667 4,0000
N 6 6 6 6
Std. Deviation ,17213 ,34427 1,12546 ,44721
Total
Mean 3,3423 3,3274 3,6518 3,8304
N 112 112 112 112
Std. Deviation ,55967 ,76587 ,82155 ,67967

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