Dessertation 3 research on factors influencing the level impulsive buying behavior in the chinese retail industry.edited (1)

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Research On Factors Influencing the Level Impulsive Buying Behaviour in the Chinese Retail
Industry
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Abstract
The impulsive buying behaviour is a common trend in today’s market environment. Impulsive
buying behaviour is an urge or temptation to purchase a product or service with no consideration
of the consequence of the purchase. Controlling impulsive buying behaviour is essential to
improving an individual's psychological well-being. On the other hand, stimulating impulse
buying is one of the key strategies employed by retailers to ensure that they increase their sales
revenue. The five key stimulators of impulsive buying behaviour includes impulse-buying
tendency, vicarious ownership, window displays, income levels, credit card usage. The impulsive
buying behaviour is common in many markets today, and the Chinese retail industry is not an
exception. This research aimed at investigating how window displays, income level and credit
card offers influence the level of impulse buying in the Chinese retail industry. The researcher
extensively reviewed the existing literature and was able to formulate three hypotheses that were
evaluated and examined to draw conclusions. The first hypothesis stated that window displays
have a significant influence in increasing the level of impulse buying in the Chinese retail
industry. The seconded hypothesis stated that Income level increases the level of impulse buying
in the Chinese retail industry. According to the third Hypothesis, high level of income increases
the level of impulse buying in the Chinese retail industry. The research adopted the use of
positivism philosophy, quantitative research approach, survey research strategy, descriptive
research design and the primary method of data collection. The respondents’ responses were
descriptively analysed to draw conclusions from the 490’s successfully returned questionnaires.
According to the research findings, window displays, income level and credit card usage
increases the level of impulsive buying behaviour in the Chinese retail industry. The researcher
provides key recommendation on how retailers can maximise on window displays, income level
and credit card usage to increase their sales revenue. Futures studies are also guided to maximise
on the weaknesses of this research. For instance, the futures studies can use larger samples and
investigate the impact of other variables such as customer loyalty and product quality on the
level of impulse buying.

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Contents
Chapter 1......................................................................................................................................... 4
Introduction..................................................................................................................................... 4
1. Research Background ................................................................................................................. 4
1.1 Research Rationale........................................................................................................... 6
1.1.1 Theoretical Rationale...................................................................................................... 6
1.1.2 Practical rationale ........................................................................................................... 7
1.2 Research Objectives .............................................................................................................. 7
1.3 Structure of the Dissertation.................................................................................................. 8
Chapter 2......................................................................................................................................... 8
Literature Review............................................................................................................................ 8
2. Introduction................................................................................................................................. 8
2.1 Impulsive Buying Behaviour ................................................................................................ 9
2.1.1 Factors Influencing Impulsive Buying Behaviour........................................................ 10
2.3 Theories on Customers Buying Behaviour ......................................................................... 12
2.3.1 The Generic Theory of Buying Behaviour ................................................................... 12
2.3.2 The Cultural Theory of Buying Behaviour................................................................... 12
2.3.3 The Internal Theory of Buying Behaviour ................................................................... 13
2.3.4 The Process Theory of Buyer Behaviour...................................................................... 14
2.4 Empirical Studies on Factors Influencing Impulsive Buying Behaviour............................ 15
2.4.1 Influence of window displays on impulsive buying behaviour .................................... 15
2.4.2 Influence of income level on impulsive buying behaviour .......................................... 16
2.4.3 Influence of credit card offers on impulsive buying behaviour.................................... 18
2.5 Summary ............................................................................................................................. 20
Chapter 3....................................................................................................................................... 20
Methodology................................................................................................................................. 20
3.1 Introduction......................................................................................................................... 20
3.2 The Formulation of Research Hypotheses .......................................................................... 21
3.3 Research Questions ............................................................................................................. 22

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3.5 Research Approach ............................................................................................................. 25
3.6 Research Strategy................................................................................................................ 26
3.7 Research Design.................................................................................................................. 26
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3.8 Methods of Data Collection ................................................................................................ 27
3.9 Description of Data ............................................................................................................. 28
3.10 Data Analysis .................................................................................................................... 29
3.11 Summary ........................................................................................................................... 29
Chapter 4....................................................................................................................................... 20
Research Findings and Analysis ................................................................................................... 30
4.1 Introduction......................................................................................................................... 30
4.2 Sample Description............................................................................................................. 30
4.3 Respondent’s Profile ........................................................................................................... 31
4.3.1 Gender........................................................................................................................... 31
4.3.2 Age................................................................................................................................ 32
4.3.3 Marital Status................................................................................................................ 33
4.3.4 Level of Education........................................................................................................ 34
4.3.5 Occupation Level.......................................................................................................... 35
4.3.6 Income Level ................................................................................................................ 36
4.4 Results ................................................................................................................................. 37
4.4.1 Review .......................................................................................................................... 37
4.4.2 The window displays have a significant influence in increasing the level of impulse
buying in the Chinese retail industry. .................................................................................... 38
4.4.3 The Income level increases the level of impulse buying in the Chinese retail industry.
............................................................................................................................................... 40
4.4.4 The usage of credit card offers increases the level of impulse buying in the Chinese
retail industry......................................................................................................................... 42
4.5 Summary ............................................................................................................................. 44
Chapter 5....................................................................................................................................... 45
Conclusion and Recommendations............................................................................................... 45
5.1 Introduction......................................................................................................................... 45
5.2 Conclusions ......................................................................................................................... 45

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5.2.1 The window displays have a significant influence in increasing the level of impulse
buying in the Chinese retail industry. .................................................................................... 45
The more income one earns, the more he is likely to engage in impulse buying.................. 46
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5.2.3 The usage of credit card offers increases the level of impulse buying in the Chinese
retail industry. ........................................................................................................................ 47
5.3 Recommendation................................................................................................................. 48
5.4 Direction for Future Studies................................................................................................ 48
5.5 Limitations .......................................................................................................................... 49
References..................................................................................................................................... 50
Appendix....................................................................................................................................... 55
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Chapter 1
Introduction
1. ResearchBackground
According to Ahmad &Vays (2011), impulsive buying behaviour is a common trend in today’s
market environment. Hadjali, Salimi&Ardestani (2012) define impulsive buying behaviour as an
urge or temptation to purchase a product or service with no consideration of the consequence of
the purchase. Further, as noted by Chang, Eckman& Yan (2011), controlling impulsive buying
behaviour is essential to improving an individual's psychological well-being. Hostler et al.
(2011) further note that impulsive buying behaviour has a close connection to unhappiness and
anxiety because in some situations it can lead to remorseful reactions. As argued by Kalla&
Arora (2011), understanding impulsive buying behaviour from the psychological perspective will
play a critical role in helping a consumer to make smarter and more rational buying decisions.
Karbasivar&Yarahmadi (2011) highlight five key motivators of impulsive buying behaviour,
which are closely connected to an individual’s psychology in the Chinese retail industry. The
first motivator of impulsive buying is the impulse-buying tendency, which is a personality trait
possessed by some individuals. The impulse buying tendency motivates an individual to form a

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habit of buying anything attractive to him. As expounded by Karbasivar&Yarahmadi (2011, the
impulse-buying tendency is connected to detrimental behaviours. For instance, individuals with
the impulse-buying tendency are status-conscious, image-concerned and socially active. This
category of persons participates in impulse buying to look better in the eyes of other buyers.
Similarly, Liang (2012) argues that impulse buying tendency creates anxiety that makes it
difficult to control impulse buying. People who have the habit of purchasing to improve their
social status experience difficulties in managing their emotional urges to spend. Ling, Chai
&Piew (2010) also note that individuals with personality traits of impulsive buying tendency
experience unhappiness, so they buy impulsively to improve their moods. Individuals who are
involved in impulsive purchasing in most cases fail to consider the consequences. The second
motivator of impulsive buying behaviour is fun and vicarious ownership. According the research
conducted by Maymand& Ahmadinejad (2011), some individuals want to experience pleasure
and own the products that please them. Further, Mihić&Kursan (2010) postulate that vicarious
ownership and fun are strongly related to brand and service reliability. When individuals have a
strong connection with certain products or services, Mihić&Kursan (2010) argue that the
perceived quality influences their buying behaviour. The three connections between the product
and the impulse buyer are the physical connection, temporal connection and the social
connection. Mohan, Sivakumaran & Sharma (2013) explain that a physical relationship with the
product is formed when an individual is closer to it and can touch it. A physical relationship
leads to a temporal relationship with the product when it is purchased. A social relationship with
the products is formed when an individual can compare himself with other people using similar
products. The social connection with a product tends to make some individuals think that they
are better off and happy when seen making expensive purchases (Muruganantham&Bhakat,
2013). Therefore, the feelings of happiness and respect will drive an impulsive buyer to buy
unbudgeted products without considering its consequences on spending.
According Nazir et al. (2012), the impulsive buying behaviour is common in many markets
today, and the Chinese retail industry is not an exception. This research project aimed at
investigating the factors that influence the level impulsive buying behaviour in the Chinese retail
industry. Despite the fact that many studies have been conducted in this area, more focus has
been diverted from the factors triggering impulsive behaviour in various markets. The specific
attributes that will be considered to achieve the core objectives of this study include the window

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displays, income levels and the availability of credit card offers. The current literature has not
put more focus on the mentioned attributes. Similarly, those studies that have tried to highlight
the impact of window displays, income level and credit card offers provide inconclusive or
inadequate findings. To address this existing gap, the researcher chose Chinese retail industry
that is one of the biggest global markets affected by impulsive purchasing behaviour.
1.1 ResearchRationale
1.1.1 Theoretical Rationale
Considering the previous and the current literature, much focus has been diverted on
investigating the factors triggering the impulsive buying behaviour Sharma, P., Sivakumaran &
Marshall, 2010). Additionally, as noted by Tinne (2011), the existing literature tends to explain
more on the impact of impulsive buying behaviour. However, thefactors that influence the level
impulsive buying behaviour in retail markets have been ignored. Based on the past literature
regarding impulsive buying behaviour, there are no conclusive findings on how window
displays, income level and credit card offers influence the level of impulsive buying in the retail
industry. To bridge the current gap, the researcher selected the Chinese retail industry to
investigate how window displays, income levels and credit card offers influence the level of
impulsive buying behaviour. According to Verhagen& van Dolen (2011), it is vital to investigate
the factors influencing the impulsive buying behaviour to help consumers control their
purchasing decisions. Regardless the fact that impulsive buying behaviour is beneficial to
retailers, it has remorse consequences on consumer spending Yang, Huang & Feng, 2011).
Further&Bastin (2010) note that it is critical to helping consumers develop mechanisms that can
help them resist the urge or motivation of purchasing unbudgeted products. As mentioned
earlier, some consumers may probably make impulse buying to please others but they do not
understand the remorse effects of such buying behaviour. Paradoxically as expounded by Zhang,
Winterich& Mittal (2010), the impulsive buying behaviour leads remorse and unhappiness in the
long-run. This implies that the feelings of fun, pleasure and social image are short-term as
opposed to guilt and sadness, which result from impulsive buying behaviour. A closer review of
the previous and the existing literature, most authors have concentrated on highlighting the
impacts of impulse buying and its motivators. However, these studies have not investigated how
window displays, income level and credit card offers influence the level of impulsive buying
behaviour in the retail industry (Lai, 2010). In the bid to address the identified gap, the
researcher assessed the contribution of window displays, income level and credit card offers in

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the impulsive buying behaviour in the Chinese retail industry. The Chinese retail market was
significant in this dissertation because it is one of the biggest global markets with higher
preferences of impulsive buying. The three variables namely window displays, income level and
credit card offers were distinctively selected because the previous researchers have widely
ignored them. Based on Kalla& Arora (2011)'s definitions, window displays are creative and
inspirational platforms created by retailers to attract the attentions of the passing customers. The
income level refers to the amount of money an individual can earn monthly in the form of wages.
The credit card offers have benefits such as redeemable points, which may influence the
consumer to engage in impulsive purchasing.
1.1.2 Practical rationale
Practically, impulsive buying behaviour is detrimental to the consumer because in the long-run it
brings remorse feelings, unhappiness and financial implications. However, in the short-run,
impulsive buying behaviour may create false feelings of pleasure, fun and improved social
status. Based on the long-term negative consequences of impulsive buying, this dissertation
seeks to investigate how window displays, income level and credit card offers influences the
degree of impulsive buying in the Chinese retail industry. The research findings will help in
enlightening the consumers to develop strategies that can help them control their urge and
motivation of buying the unbudgeted products or services. The results of this research will also
be critical in controlling the long-term consequences related to impulse buying such as remorse
and unhappiness.
1.2 ResearchObjectives
Based on the current literature, consumers are motivated to engage in impulse buying so that
they can improve their social status, have fun or experience pleasure (Niazi et al., 2012). Further,
the current studies note that the feelings of fun, social improvement and pleasure are short-run
compared to the long-term remorse feelings (Muruganantham&Bhakat, 2013). After conducting
an extensive review of the existing literature, the researcher identified that the attributing factors
influencing the level of impulse buying in the retail industry have been ignored. Some of the
factors that can affect the level of impulse buying in the retail industry includes packaging
attractiveness, product colour, product arrangement, window displays, income levels and credit
card offers. However, the researcher specifically identified window displays, income levels and
credit card offers as the three vital attributes that have been ignored in the existing literature. The
mentioned factors can significantly influence the level of impulsive buying behaviour in the

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Chinese retail industry. It is, therefore, evident that this dissertation will have a considerable
positive impact in helping consumers to develop strategies that will limit them from engaging in
impulse buying. Therefore, the three specific research objectives obtained by the researcher
include:
 To assess the influence of window displays on impulsive buying behavior in the Chinese
retail industry.
 To investigate how the income level influences impulsive buying behavior in the Chinese
Retail Industry.
 To examine the influence of credit card offers on impulsive buying behavior in the
Chinese retail industry.
1.3 Structure of the Dissertation
The researcher aimed at investing the factors that influence the level of impulse buying
behaviour in the Chinese retail industry. The researcher structured this dissertation into five
chapters. Chapter one provides an overall introduction to this research with a detailed research
background, research rationale, objectives and the research structure. An extensive review of the
previous literature concerning impulse buying is discussed in chapter two. The study
methodology is provided in the third chapter while the research findings and analysis are
presented in the fourth chapter. The last chapter makes recommendations and conclusion.
Chapter 2
Literature Review
2. Introduction
As noted by Ahmad &Vays (2011), the impulsive buying behaviour is a common trend in
today’s market environment. According to Abideen&Saleem (2011), various factors influence
people to engage in impulse buying. The impulse buying behaviour can have both short-term and
long-term consequences. Further, Amos, Holmes &Keneson (2014) argue that the uncontrolled
urge to consume is influenced by the mirror neurones, which trigger emotional responses in the
brain that result in impulsive buying without consideration of the aftermath consequences.
Similarly, Banerjee, Saha 2012) expound that impulsive buying is unintentional, unplanned and
unthoughtful purchasing, which results in remorseful feelings and unhappiness in the long-term.

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Based on the circumstances under which the impulsive buying occurs, it is inevitable to avoid
experiencing regretful feelings after the purchase. Many studies have investigated the factors
influencing impulsive buying behaviour. Similarly, many researchers have attempted to examine
the impact of impulsive behaviour both in the short-term and in the long-term. The previous
studies on the factors influencing the level of impulsive buying behaviour are reviewed in this
chapter. The researcher structured this chapter into five key sections. The first section is the
introduction, which provides an overview and the structure of this chapter. The second section
discusses the impulsive buying behaviour and factors influencing impulsive buying behaviour.
The theories on consumer buying behaviour are discussed in the third section. The fourth section
reviews the empirical studies on factors affecting the impulsive buying behaviour including
window displays, income level and credit card offers. The last section provides a comprehensive
summary of the chapter.
2.1 Impulsive Buying Behaviour
The impulsive buying behaviour is a study topic that has attracted various business researchers
since 1950s (Bashar & Ahmed, 2012). According to Chang, Eckman& Yan (2011), many
researchers agree that the impulsive buying behaviour is driven by emotions, hedonistic desires
and massive advertisements in the retail environment. Dawson & Kim (2010) note that many
companies facing stiff competition in the retail environment are applying stimuli marketing
techniques to encourage impulse buying as a way of gaining a competitive edge. Further, as
indicated by Dr Ahmed (2011), manipulative marketing stimuli techniques play a critical role in
influencing consumer’s emotions to trigger impulse buying. The impulsive buying behaviour is
categorised into four categories namely: pure impulse buying, suggestive impulse buying,
reminder impulse buying and the planned impulse buying. As defined by Floh&Madlberger
(2013), the pure impulse buying is a purchase behaviour that goes against the shopping
anticipated patterns. The level of impulsiveness in the pure impulse buying behaviour is very
high due to its connection to emotions (Floh&Madlberger, 2013). As indicated by Gajanayake,
Gajanayake and Surangi (2011), when a consumer is under the influence of pure impulse buying,
he develops a strong emotional connection to the product and which can only be satisfied if the
purchase is made. Further, Floh&Madlberger (2013) argue that the major factor triggering the
pure impulse buying behaviour in the retail market environment is the cheap product and service

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prices. The second category of impulse buying is the suggestive impulsive buying behaviour.
The key factor triggering suggestive impulsive buying behaviour is the retail store visualisation.
Under suggestive impulsive buying behaviour, the consumer develops and interest to purchase a
new product when he first comes into contact with it. The only way a shopper can be satisfied
after coming into contact with a new product that interests him is to purchase it. According to the
research conducted by Jain, Sharma &Narwal (2012), the purchasing decision under suggestive
impulsive buying behaviour is irrational, functional and unplanned. The consumer does not buy
the product because he had seen it before or heard of it but buys it because it interests him for the
first time. The third category of impulse buying is the reminder impulsive buying behaviour
(Jain, Sharma &Narwal, 2012). Unlike the suggestive and pure impulsive buying behaviours, in
this category, the customer has adequate knowledge about the product. The last category of
impulse buying is the planned impulsive buying behaviour. Under the planned impulsive buying
behaviour, the consumer already knows what to buy but the product choice, brand, size or price
are not predetermined (Kalla& Arora, 2011). Therefore, despite planning to make a purchase, the
consumer will end up impulsively purchasing unplanned sizes and brands with varying prices.
The planned impulsive buying behaviour differs from the planned purchase because, in the
former, the consumer makes the actual decision to purchase at the points of sale
(Karbasivar&Yarahmadi, 2011).
2.1.1 Factors Influencing Impulsive Buying Behaviour
Khandai, Agrawal Gulla (2012) categorise the factors influencing impulse buying behaviour into
personality traits factors and environmental stimuli. The Multidimensional Personality
Questionnaire (MPQ) developed by Khurram and Seemab (2013) categorises the three-
dimensional personality factors that influence impulse buying into the lack of control
(impulsivity), stress reaction and absorption. Control is a personality trait that can be used to
monitor the impulse activity. However, as noted by Khurram and Seemab (2013), an impulse-
driven person acts spontaneously, careless and reckless. Neurones trigger the emotional activities
of impulse-driven individuals only get satisfaction after acquiring something of interest (Kinley,
Josiam& Lockett, 2010). In the context of the retail environment, lack of control or impulsivity is
a significant personality trait that influences impulse buying (Kinley, Josiam& Lockett, 2010).
The second personality trait that influences the impulsive buying behaviour is the stress reaction.

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Based on the research conducted by Liu &Sutanto (2012), stress reactions represent systematic
personal deviations when responding to various situations linked to anxiety, guilt or distress.
People suffering from stress tend to make decisions catastrophically without considering the
accompanying repercussions. Further, Liu &Sutanto (2012) argue that stressful individuals are
very sensitive, nervous and can make any spontaneous decision to provide some form of relief.
In the context of the retail environment, people suffering from stress make impulsive purchasing
decisions as a way of relief. As noted by Maymand&Ahmedinejad (2011), some prior studies on
impulse buying have established that some individuals suffering from stress acknowledged that
they gained relief after impulse buying. Additionally, as expounded by Mehta & Chugan (2012),
the highly stress-reactive individuals get short-term gratification from impulsive buying. The last
personality trait that influences impulsive buying is absorption. The highly absorptive individuals
are likely to think unconventionally. The research conducted by Mehta & Chugan (2013),
absorption influences people on how they respond to stimuli and environmental cues linked to
purchasing and the consumption of products. Environmental factors related to stimuli that
influence the impulse buying behaviour include the store environment, window displays and the
visual merchandising. As argued by Mehta & Chugan (2012), the impulse buying behaviour is
created by stimuli. Therefore, the store set-up can influence consumers’ response when making
purchasing decisions. The store settings have also undergone tremendous changes to match
consumer choices, taste, preference and purchasing patterns. The window displays as explained
by Muruganantham&Bhakat (2013), have both charm and charisma to influencing consumer
choices. The visual merchandising (VM) is another environmental factor that influences
consumer buying behaviour (Park & Forney, 2011). VM entails the arrangement of retail
products in a way that clutches consumers' attention, thus influencing the buying behaviour.
However, the existing studies have not explicitly explored the impact of window displays,
income level and credit card offers on the level of impulsive buying in the retail industry. The
current research findings provide inconclusive and inadequate findings regarding how window
displays, income level and credit offers influence the level of impulse buying. Most studies have
put more emphasis on the impact of impulse buying on both the businesses and consumers. This
research, however, will fill this gap by exploring conclusively how the window displays, income
level and credit card offers influence the level of impulse buying in the Chinese retail industry.

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2.3 Theories on Customers Buying Behaviour
As noted earlier by Pentecost & Andrews (2010), the topic of impulse buying has attracted the
attention of many researchers since 1950's. Various theories have been formulated in an attempt
of explaining what triggers impulse buying. The five most prevalent theories of buyer behaviour
include the generic theory of buyer behaviour, cultural theory of buyer behaviour, internal theory
of buyer behaviour, rational actor theory and the process theory.
2.3.1 The Generic Theory of Buying Behaviour
According to the generic theory of buying behaviour, consumers are guided by the generic model
of decision-making process before making a buying decision. Pereira et al. (2010) argue that
based on the generic theory of buyer behaviour, before making a purchase, a consumer will
conduct research on the available products and their respective prices. Further, as postulated by
Podoshen & Andrzejewski (2012), under the generic theory of buyer behaviour, a consumer is
initiated to make a purchase by a need of either making replacement or acquiring a new planned
item. For instance, a consumer may make a decision to buy a new fridge because the older one is
worn out and cannot be repaired. Before making a purchase, the consumer will conduct research
on the available fridges in the market and their respective prices (Podoshen & Andrzejewski,
2012). Similarly, the consumer will investigate the product features, durability and other critical
aspects related to the product to be bought. After ensuring that the product meets the anticipated
expectations, the consumer will proceed to make the purchase.
2.3.2 The Cultural Theory of Buying Behaviour
According to the cultural theory of buying behaviour, the factors that influence buyer behaviour
include culture and societal environment, sub-cultures, social classes and the cultural trends. As
noted by Sharma, Sivakumaran & Marshall (2010), each consumer belongs to a particular culture
with distinct norms, values and beliefs. Further, Wells, Parboteeah&Valacich (2011) argue that a
business can only understand the consumer behaviour if it first analyses the culture to which the
consumer belongs. For instance, each belongs to a specific family and friends who influence his
thinking, preferences and choices. Based on Wells, Parboteeah&Valacich (2011)’s arguments,
the cultural attributes have a significant influence on the buying behaviour of an individual. For
instance, Xiao & Nicholson (2013) argue that the social class and family status can define the
consumption pattern of an individual. Based on the cultural theory of buyer behaviour, Ahmad
&Vays (2011) note that a consumer may make purchases distinctively based on family
preferences. Similarly, as indicated by Chang, Eckman& Yan (2011), the buying behaviour is

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closely linked to attitudes and beliefs based on specific cultural set-ups. An individual's lifestyle
is shaped by the shared experiences and values based on sub-cultures. Sub-cultures may entail
different ethnic groups, different age groups, religions and gender components that significantly
influence the decision to buy. Additionally, Hadjali, Salimi&Ardestani (2012) postulate that the
social hierarchy has a significant influence on the purchasing decisions. The different social
classes have differing tastes, preferences, lifestyles and interests (Kalla& Arora, 2011). The
social classes may be classified to lower, middle and upper classes. The consumption patterns
differ from one social class to the other due to different purchasing power capabilities. Similarly,
as explained by Karbasivar&Yarahmadi (2011), the upper social class may distinguish itself
from the rest based on the products they buy. Additionally, the culture theory of buying suggests
that when making purchasing decisions, the lower and middle classes may focus on product
prices, but upper classes may only focus on product attributes (Lai, 2010). The buyer behaviour
is also influenced by the social pressure resulting from the cultural trends. The cultural trends are
becoming dynamic due to increased technological innovations. The desire to belong to a
particular fashion trend as stimulated by the social media has greatly influenced the buyer
behaviour. Individuals are either consciously or unconsciously making purchase decisions to
below to a particular fashion trend. The pressure to belong to a particular fashion trend may not
only affect the buying behaviour but also can trigger impulse buying. Liang (2012) points out
that the social media such as Facebook and Tweeter have become social, cultural trends that are
exerting pressure on the purchase decisions. However, not much research has been done to
investigate the impact of window displays, income level and credit card offers on the level of
impulsive buying behaviour in the retail industry.
2.3.3 The Internal Theory of Buying Behaviour
According to the internal theory of buying behaviour, personality traits and social factors such as
lifestyle significantly influence the buying behaviour and impulsive buying (Mihić&Kursan,
2010). The internal theory of buyer behaviour categorises social factors influencing buyer
behaviour into reference groups, family roles and lifestyle status. Muruganantham&Bhakat
(2013) note that the reference groups are more often related to factors such as age, social origin,
residence, workplace among other factors. The consumption pattern in a reference group is
determined by the lifestyle, mindset and group's values. Further, Tinne (2011) argues that the
points of comparison among the reference group include consumer habits and lifestyle standards.

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The pressure to match up with the rest of the group members can significantly influence buying
decisions. For instance, if the group has a preference for driving high ranking vehicles, an
individual within the group will prefer to match the same standard. The internal theory of buyer
behaviour also identifies another group known as aspiration group (Verhagen& van Dolen,
2011). An individual might want to resemble members of a particular group and this will
influence his purchasing behaviour. The desire of belonging to a particular aspiration group may
not only influence consumer behaviour but can as well trigger impulse buying. Yu &Bastin
(2010) explain that the roles that affect the buying behaviour within a reference group are
categorised into initiator, influencer, decision maker and the buyer. The initiator is an individual
who initiates or suggests the purchase of products or services. The influencer is an individual
whose advice can impact on the purchase decision and in most cases, such an individual might
be celeb or role model to the group. The decision makers in the context of the reference group
are the consumers or buyers who make purchase decisions on the initiated products.
Further, the internal theory of buying behaviour identifies the family as a key influencer of the
buying decisions (Abideen&Saleem, 2011). The perception of brands and buying habits are
guided by the family beliefs and lifestyle. For instance, individuals may consider purchasing
similar products already possessed by the family members. The social roles and status also
influences the buying behaviour of an individual. The social status and roles may be associated
with the level of income earned, place of residence and the place of work. To keep up with the
standards of a particular social rank, individuals may tend to purchase products fit for their status
(Abideen&Saleem, 2011). Similarly, the urge of distinguishing oneself from other social classes
can encourage an individual to make impulsive purchases. Therefore, based on the internal
theory of buying behaviour, an individual's buying decisions can be significantly influenced by
the cultural trends, societal environment, sub-cultures, family and the social status.
2.3.4 The Process Theory of Buyer Behaviour
The process theory tries to explain what individuals would do theoretically and practically if they
were assumed to be rational economic actors (Banerjee &Saha, 2012). Based on the process
theory, the buyer decisions can be made from both opportunistic and self-defensive perspectives
reliant on the consumer's ultimate gains. For example, customers will take advantage of bulk
purchases to get discounts. However, the intention of utilising the bulk purchasing can lead to
impulsive buying because one will end up buying more products than budgeted due to the

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discount's attractiveness (Bashar & Ahmed, 2012). The opportunistic perspective of the buyer
behaviour can also be motivated by the use of credit card offers. According to Dawson & Kim
(2010), businesses are formulating creative strategies such as the use of credit card offers to
encourage consumers to make extra purchases. When using credit cards, consumers will make as
many purchases as they can and pay for the products at a future date (Floh&Madlberger, 2013).
The use of credit card offers is tremendously growing due to the parallel growth of other credit
card usages such as bank overdrafts and personal loans. Since the consumers are not pressured to
pay for the products instantly, they end up making unthoughtful and unplanned purchases.
2.4 Empirical Studies on Factors Influencing Impulsive Buying Behaviour
2.4.1 Influence of window displays on impulsive buying behaviour
According to Mehta & Chugan (2012), the level of impulse buying is tremendously increasing in
the retail industry. As expounded by Park & Forney (2011), window displaying is among the
principal stimulators of impulse buying in the retail industry. Window displays as explained by
Pereira et al., (2010) entails the effective presentation of products in large shop windows to
capture the attention of the passing consumers. The window displays, therefore, is the exterior
visual merchandising that attracts customers to interior stores (Khandai, Agrawal &Gulla, 2012).
The window displays have four key atmospheric dimensions that draw the attention of the
customers, which include visual, aural, smell and tactile. In the year 2012, Mehta and Chugan
did a researched to investigate the effects of visual merchandising on customer impulsive buying
behaviour in India. The study utilised a sample of 184 customers who regularly visit the Indian
retail stores. The study analysed the respondent's responses using SPSS software and the mean as
a measure of dispersion. The study findings showed that there is a direct relationship between
impulse buying with the visual merchandising. However, the study did not take a keen interest in
how the window displays influence the level of impulse buying in the retail industry. The study
only established that visual merchandising has a direct relation to impulse buying.
Another research was conducted by Bashar & Ahmed (2012) to investigate the influence of floor
merchandising and form displays on consumer's impulsive buying behaviour in the retail
industry. The research used a sample of 250 Indian customers. The researchers in this study
applied Pearson correlation technique to study how impulsive buying behaviour correlated with
floor merchandising, forum display and window displaying. The study's findings revealed that
the impulsive buying behaviour and the floor merchandising are positively correlated to window
displays. However, the study did not take a keen interest in investigating the effect of the

16
window display on the level of impulsive buying behaviour in the retail industry. Further,
another research was conducted by Sharma, Sivakumaran & Marshall (2010) which used floor
merchandising, forum displays and window displays as the independent variables. The study
utilised a sample of 45 respondents comprising of both males and females. Similarly, the Pearson
correlation techniques were used to analyse the data. The study's findings established that there is
a weak correlation between impulse buying and floor merchandising. However, there was a high
correlation between window display and the impulsive buying behaviour. Similarly, the study
failed to focus on how the window display influences the level of impulsive buying in the retail
industry.
In 2011, Dr Tausef found out that the impulsive buying behaviour was different between the
consumers of different genders, age-groups and education levels for the FMCG products in the
retail industry. The impulsive buying behaviour was used as a dependent variable while the
education level, gender and income levels were used as independent variables. The study used a
sample of 160 customer respondents. The data was analysed using the factor analysis tool (SPSS
16.0). Further, Mehta & Chugan (2013) investigated the triggers of impulsive buying in the
retail stores. The shopping frequency was used as an independent variable while the customer
gender was used as the interdependent variable. The study used a sample of 100 customers and
the data was analysed statistically using the Chi-square tool. The research findings established
that the shopping frequency is not associated with gender. As evidenced by the above reviews,
the current studies have not put more emphasis on how the window displays influence the level
of impulsive buying. To bridge this identified gap, the researcher will assess the impact of
window displays on the level of impulsive buying behaviour in the Chinese retail industry. This
will as well address the first objective of this study.
2.4.2 Influence of income level on impulsive buying behaviour
According to Xiao & Nicholson (2013), the income level is one of the key demographic factors
influencing the impulsive buying behaviour in retail markets. Further, Xiao & Nicholson (2013)
note that most of the contemporary studies in the past have concluded that the level of income is
a key influencer of the consumer behaviour. When reviewing various empirical studies, Wells,
Parboteeah&Valacich (2011) postulate that most of the consumer behavioural scientists have
come to a consensus that the social class is a key determinant of the buying behaviour. However,
as explained by Podoshen & Andrzejewski (2012), the social classes are distinguished based on

17
the level of income. The income level explicitly depends on the economic development of a
country. Various studies have been conducted to examine whether the income level has an
impact on the buying behaviour. The research conducted by Podoshen & Andrzejewski (2012)
established that those consumers with a higher level of income seemed more confident when
purchasing compared to those with low-income levels. The study utilised a sample of 175
participants in the Chinese electronic industry. The data was collected using the closed-ended
questionnaires and analysed using the descriptive statistics. The study showed a high correlation
between the frequencies of purchasing with the level of income. It, therefore, implies that those
individual with a higher level of income tend to buy more products compared to those with low
income. However, the key focus of this research was to determine whether the frequency of
purchasing correlated with the level of income. The impact of the income level of the impulsive
buying behaviour in the retail market environment was ignored. Additionally, the study
conducted by Park & Forney (2011) revealed that the income level was a key influencer of the
buyer behaviour in the Latvian tourism industry. The study used factor analysis as a statistical
tool to analyse the data that was collected from a sample of 145 tourists. The researcher in the
study wanted to establish how the level of income influenced the consumer's spending
behaviour. The study's findings confirmed that consumer spending had a strong relationship with
the level of income. Those tourists who had higher income levels tended to buy more compared
with those with lower income levels. Just like other contemporary studies on consumer's buying
behaviour, the researcher failed to focus on how income levels influence the level of impulse
buying.
Park & Forney (2011)’s assertions were supported by Karbasivar&Yarahmadi (2011) who argue
that economists predict consumer buying choices based on their level of income.
Karbasivar&Yarahmadi (2011) further conducted research to study the factors affecting buyer
behaviour. The income level was used as one of the key demographic factors influencing the
consumer buying behaviour. The other factors that were under investigation included age and
gender. The study utilised multiple linear regression analysis to analyse the data collected from
140 respondents. The research outcome established that the income level and the education level
were key determinants of the buyer behaviour. However, as evidenced by the current empirical
studies, there is little effort to investigate the influence of the level of income on the impulse
buying in the retail industry. As noted earlier, the social class is determined by the level of

18
income. Earlier studies indicated that the social status of an individual can trigger him to engage
in impulse buying (Kalla& Arora, 2011). The desire to look better in front of others encourages
people to engage in impulsive buying. The upper social classes tend to have higher levels of
income compared to middle and lower classes. However, this dissertation aimed at filling the
existing gap by studying the influence of income level on impulse buying in the Chinese retail
industry. The study will provide critical information that will help consumers monitor their level
of their impulse buying in the retail industry.
2.4.3 Influence of credit card offers on impulsive buying behaviour
As argued by Robb (2011), the credit card offers are one of the key factors influencing the
impulse buying behaviour in the retail market environment. Robb (2011) defines credit card
offers as a payment mode widely used in purchasing products and services on credit. The usage
of credit card offers has tremendously grown in the past decade. According to Thomas, Desai
&Seenivasan (2011), the growth of credit card usage in the retail industry has been influenced by
the parallel growth in other consumer credit cards such as higher purchase, bank overdrafts and
personal loans. Further, the increase in the usage of the credit card usage in the retail industry has
been greatly influenced by the dynamic developments of the global financial system that has
created confidence in their usage (Joireman, Kees&Sprott, 2010). However, Ahmed et al. (2010)
asserts that despite the benefits that stimulate consumers to use credit card offers, some setbacks
should be considered before making a purchase. Ahmed et al. (2010) also argues that consumers
who use credit card offers tend to make extra purchases than intended. The increased trend of
using credit card offers is overwhelming in the retail industry. Different scholars have conducted
empirical studies to investigate whether the credit cards have a significant impact on the impulse
buying. Ahmed et al. (2010)'s study aimed at investigating credit card misuse in the Malaysian
retail industry. The study utilised a sample of 230 respondents whose responses were analysed
using descriptive statistics. The study established three key findings regarding the credit card
usage. Firstly, the study proved that consumers will use their credit cards to buy more luxury
goods to satisfy their emotional desires. Secondly, the research findings indicated that people
with low self-esteem tend to overuse their credit cards in purchasing luxurious products to boost
their esteem and self-worth. Thirdly, the study concluded that credit card offers enticed buyers to
make impulsive purchases. However, the study did not take a keen interest in how credit card
offers influence the level of impulsive buying. Another study was conducted by Foscht et al.

19
(2010) who wanted to investigate the factors that affect the misuse of the credit card offers
among the working population. The factors under consideration included the budget constraints,
self-esteem and impulse buying. The researcher used 250 respondents from the Austria retail
industry. The research model applied by the researcher is illustrated in Figure 1.
Figure 1: Research Model
Source: Foscht et al. (2010)
The researcher successfully collected the empirical data from 230 respondents using the
questionnaire survey. The collected data was hypothetically tested and the researcher established
that materialism and impulsive buying contributed to the credit card misuse. Similarly, the study
established that consumers had an impulsive buying tendency of spending beyond their means.
These research findings are in line with the various reviewed literature that indicated that users
of credit card offers tend to overspend in different retail markets (Podoshen, & Andrzejewski,
2012). The various studies have also shown a strong relationship between credit card offers
usage and the indebtedness in consumer spending. However, the previous researches show
inconclusive and inadequate findings regarding the influence of the credit card offers on the level
of impulse buying in the retail industry. To address the current inconsistencies, this dissertation
aims at investigating how the credit card offers, income level and the window displays influence
the level of impulse buying in the Chinese retail industry. The research outcome will play a vital
role in helping the consumers in the Chinese retail industry to control their impulsive buying
desires.

20
2.5 Summary
The chapter explored and reviewed the previous literature concerning the impact of window
displays, income level and the credit card offers on the level of impulse buying. Based on the
existing literature, the impulsive buying is categorised into pure impulse purchase, suggestive
impulse buying, reminder impulse buying and the planned impulse buying. The pure impulse
buying is a purchase behaviour that goes against the shopping anticipated patterns. Under
suggestive impulsive buying behaviour, the consumer develops an interest to purchase a new
product when he first comes into contact with it. Under the impulsive reminder buying, a product
reminds the consumer that he needs it because it is out of stock in his home. In the planned
impulsive buying behaviour, the customer already knows what to buy but the product choice,
brand, size or price are not predetermined. The various theories that explain buyer behaviour
includes the internal theory of buyer behaviour, the generic theory of buyer behaviour, the
process theory of buyer behaviour and the cultural theory of buyer behaviour. The reviewed
literature, however, revealed that little has been done in investigating the impact of window
displays, income levels and credit card offers on the level of impulsive buying on the retail
industry. Therefore, this study aims to at investigating the influence of the mentioned factors in
the Chinese retail industry.
Chapter 3
Methodology
3.1 Introduction
As postulated by Coleman & Ringrose (2013), it is essential for the researcher to select an
appropriate methodology when conducting research to ensure validity and reliability of the
research findings. Further, Coleman & Ringrose (2013), argue that the appropriateness of the
selected methodology greatly depends on the research topic and its main objectives. This study
aimed at investigating how window displays, income level and credit card offers influence the
level of impulse buying in the Chinese retail market. This chapter, therefore, presents a detailed
methodology selected by the researcher in achieving the research objectives. The first section
provides the introduction and the structure of this chapter. The formulation of the research
hypotheses is discussed in the second section. The research questions are also formulated in the
third section. Similarly, other sections provide detailed information concerning the selected
philosophy, research approach, research strategy, research design and methods of data collection.

21
The chapter as well presents the method of data analysis used. The last section provides a
comprehensive summary of the entire chapter.
3.2 The Formulation of ResearchHypotheses
As defined by Bryman & Bell (2015), research hypotheses are statements created by a researcher
aimed at speculating the possible research outcomes, experiments or analysis. Additionally, as
noted by Bryman & Bell (2015), the research hypotheses are formulated from the existing
literature to test the research objectives. Hair et al. (2015) further note that research without
hypotheses is aimless because there will be no clear guideline on what is to be tested, supported
or disputed. There are four key reasons why the researcher of this study formulated hypotheses.
Firstly, the hypotheses formulated helped the research in determining research direction and
focus. Therefore, since the researcher knew what he wanted to achieve, it was easier for him to
dedicate his effort towards achieving the research objectives. Secondly, the development of the
hypotheses helped the researcher to state precisely the purpose of the study and the activities
involved in this research. Thirdly, hypotheses formulated provided clarity to this research
because the researcher was clear on what was anticipated. Fourthly, hypotheses formulation
equipped the researcher with the knowledge required to fill the existing gaps. As noted earlier,
hypotheses are formulated after a critical review of the current and existing literature to identify
the areas of weakness. After identifying limitations in the existing literature, the researcher
develops, new knowledge on such gaps should be filled (Wilson, 2014). This study aimed at
investigating how income level, window displays and the credit card offers influence the level of
impulse buying in the Chinese retail industry. The researcher explored and critically analysed the
existing literature on the impulse buying in the retail industry. After the extensive review of the
existing literature, the researcher established that consumers are influenced to engage in impulse
buying by the window displays. Merchandising plays a significant role in attracting the
consumers’ attentions in the retail industry. People are convinced to make purchasing decisions
from what they see on the window displays. The existing literature also indicated that the level of
income categorises people into social classes. Therefore, other individuals unconsciously
participate in impulse buying to maintain their social status. Similarly, various past researchers
agree that the usage of credit card offers stimulates impulse buying because customers tend to
make an extra purchase. Based on the existing literature establishments, the researcher was able
to formulate three hypotheses as mentioned below:

22
Hypothesis 1: The window displays have a significant influence on increasing the level of
impulse buying in the Chinese retail industry.
Hypothesis 2: The Income level increases the level of impulse buying in the Chinese retail
industry.
Hypothesis 3: The usage of credit card offers increases the level of impulse buying in the
Chinese retail industry.
3.3 ResearchQuestions
As expounded by Myers (2013), research questions guide the researcher on how the research
objectives can be achieved. However, Myers (2013) notes that the research questions used must
be precise and focused for the researcher to achieve the set objectives. Based on the objectives of
this study, the researcher was able to formulate three research questions:
1. How does the window displays influence the level of impulse buying in the Chinese retail
industry?
2. How does the level of income influence the level of impulse buying in the Chinese retail
industry?
3. How does the usage of credit card offers influence the level of impulse buying in the Chinese
retail industry?
3.4 ResearchPhilosophy
According to Bozeman & Melkers (2013), understanding the research philosophies and
approaches is critical in helping the researcher to determine the methods of data collection and
analysis. Further, as indicated by Creswell (2013), a research paradigm has three characteristics
namely ontology, epistemology and axiology. In ontology, researchers see nature from the reality
point of view taking into considerations the assumptions explaining how the world works. On the
other hand, in epistemology, a researcher views what entails the acceptable knowledge based on
his understanding of nature (Creswell, 2013). A researcher in this category also studies the
relationship between what he already knows and the assumptions constituting the acceptable
knowledge (Creswell, 2013). The research onion in Figure 2 provides a comprehensive overview
on how the understanding of various philosophical approaches guides the researcher in selecting
the appropriate methods of collecting data and analysis.

23
Figure 2: Research Onion.
Source: Creswell (2013).
As explained by Mertens (2014), research philosophy is made up of four pillars namely
positivism, realism, interpretivism and pragmatism. Table 1 provides the differences between
the four philosophical approaches.

24
Table 1: Differences in Philosophical Approaches
Positivism Realism Interpretivism Pragmatism
Ontology Objective,
independent
from social
actors and
external
Objective,
independent of
Human thoughts,
critical realist
Socially
constructed,
subjective, my
change and
multiple
Multiple and
external
Epistemology Observable
phenomenon
provides
credible data and
facts. Focuses on
causality
Observable,
credible data,
open to
misinterpretation
and focus on
explaining
contexts
Subjective
meanings, social
phenomena,
focus on
situation,
Observable
phenomena and
subjective
Axiology Value freeway,
the researcher is
independent of
data and
maintains
objectivity
Value-laden,
biased by world
views,
Value-bound,
researcher is part
of what is being
researched,
highly
subjective.
Value based,
both objective
and subjective
view are
incorporated
Data Collection
Method and the
Techniques
Adopted
Use of highly
structured large
samples,
quantitative
measurements
and use of
Statistical
Methods
Small samples,
can be
qualitative or
quantitative
Small samples,
qualitative
investigation
Mixed or
multiples
methods and can
be either
qualitative or
quantitative.
Source: Mertens (2014).
The research philosophy is chosen based on the research motives (Punch, 2013). Based on this
research, the researcher aimed at investigating the influence of window displays, income level
and credit card offers on the level of impulse buying in the Chinese retail industry. The
observable variables that were objectively measured by the researcher included window displays,
credit card offers and the level of income. The observable facts were measured using the ordinal
numbers that were scored on the five Likert scale. The scores were analysed descriptively using
the SPSS software in which the measure of dispersion (mean) was used. The researcher similarly
used a large sample of customers from the Chinese retail industry to ensure that the results
obtained were free from bias. Additionally, research findings in this study were purely tested
empirically. Based on the requirements of this research, the researcher adopted the positivist
philosophy. There are various reasons why the researcher preferred positivism as opposed to

25
other philosophical approaches. Firstly, positivism philosophy helped the researcher to test the
research findings empirically. Secondly, the positivism philosophy allowed the researcher to
collect a large sample using online survey questionnaires to ensure the reliability of the research
findings. Thirdly, by using positivism philosophy, the researcher was able to establish the causal
and effect relationships between the observable facts and the impulse buying in the Chinese retail
industry. Fourthly, since this research required a highly structured methodology, positivism
philosophy was the best as opposed to realism, interpretivism and pragmatism that do not require
a strict methodology. Similarly, unlike interpretivism, realism and pragmatism, the positivism
philosophy allowed the researcher to analyse the data descriptively using the SPSS software.
Interpretivism was not adopted because it emphasises on qualitative analysis. As indicated in
Table 2, interpretivism is highly subjective and that might have compromised the reliability of
the research findings. Table 2 also indicates that interpretivism, realism and pragmatism do not
allow the use of large samples, thus making them unsuitable for this study (Myers, 2013).
Therefore, based on the requirements of this study, the positivist philosophy was the most
appropriate as opposed to interpretivism, realism and pragmatism.
3.5 ResearchApproach
The two common research approaches are quantitative approach and qualitative approach
(Bowling, 2014). Bowling (2014) indicates that it is vital for the researcher to understand the
different research approaches to enable him to select the most appropriate approach. Further,
Bowling (2014) explains that the research approach selected is determined by the selected
philosophy. The quantitative approach is linked to positivist paradigm because it entails
deductive reasoning (Gray, 2013). Under the quantitative approach, the data collected is
converted into numerical figures so that it can be easily analysed using the statistical techniques
to draw conclusions. Further, as argued by Saunders & Lewis (2012), in quantitative studies,
researchers must formulate hypotheses to predict the possible outcome of the research findings
based on the variables under investigation. The data collected in quantitative research is analysed
statistically. The qualitative research approach is associated with social constructivism or
interpretivism paradigms and involves inductive reasoning (Saunders & Lewis, 2012). In
qualitative studies, research is not based on the formulation of hypotheses. Similarly, in
qualitative research, small samples are used when collecting data. Qualitative data is not
converted into a numerical form. Thus, statistical methods are not used in data analysis

26
(Saunders & Lewis, 2012). This research aimed at investigating how window displays, income
level and the credit card offers influence the level of impulse buying in the Chinese retail
industry. The data collected was scored in a five-Likert scale and analysed using descriptive
statistics. The research was also based on the pre-determined hypotheses. Therefore, based on the
requirements of this study, the researcher adopted the quantitative research approach. The
qualitative approach was unsuitable because it involves small samples and the research is not
based on pre-determined hypotheses. Similarly, a qualitative approach was not fit for this study
because it does not involve statistical analysis.
3.6 ResearchStrategy
The research strategy is another critical component that determines the success of the research
study. As notified by Saunders & Lewis (2012), the research strategy selected is associated with
both the research strategy and the research approach. The three common research strategies
include surveys, experiments and case studies (Zikmund et al., 2012). Experimental research
strategies aim at showing the link between the independent and dependent variables and are
commonly applicable in the exploratory studies (Zikmund et al., 2012). The survey strategy is
used when the researcher intends to use large samples when collecting data. One of the tools
used to collect data in the survey strategy is the questionnaires. The case studies are widely used
in traditional science studies (Punch, 2013). As indicated earlier, the researcher in this study
adopted the positivism philosophy, implying that this is quantitative research. The researcher
intended to use a large sample to ensure that his findings were reliable and unbiased. The data
collected was to be analysed quantitatively using the descriptive statistics. Therefore, the most
appropriate research strategy in this study was the survey strategy. The researcher intended to
investigate the impact of window displays, income level and credit card offers in the Chinese
retail industry. The researcher had to collect data from a large sample. The survey strategy
enabled the researcher to reach a large audience using the online survey questionnaire. The case
study strategy was not appropriate for this study because it is widely used in traditional sciences.
Similarly, the experimental strategy is widely applied in exploratory studies making it
inappropriate for this research.
3.7 ResearchDesign
According to Saunders & Lewis (2012), a research design can either be descriptive, exploratory
or casual depending on the requirements of the research study. Further, Coleman & Ringrose
(2013) note that it is essential for the researcher to have a good understanding of the various

27
research designs to enable him to achieve his research objectives. The core aim of this research
was to study the influence of window displays, income level and credit card offers in the Chinese
retail industry. To precisely select the research design, Bryman & Bell (2015) note that the
researcher must understand the research philosophy, research approach and the strategy selected.
The researcher in this study collected data using survey strategy. The data was quantitative and
analysed using statistical methods. Therefore, the most appropriate research design was
descriptive research design. The research design selected enabled the researcher to align his
study with his objectives. Similarly, the descriptive research design is associated with positivism
approach selected for this study. Therefore, the exploratory and causal research designs were not
appropriate in this study because they are associated with social constructs and interpretive
approaches. By using either exploratory or causal research designs, it could have been difficult
for the researcher to collect data from a large sample. Similarly, it could have been difficult for
the researcher to analyse data statistically.
3.8 Methods of Data Collection
The method used in collecting data is essential in determining the success of the research
findings. As argued by Saunders et al. (2011), inaccurate data collection methods can lead to
misleading research findings. Data can be collected using either primary or secondary methods.
The secondary data refers to the already existing research findings conducted in the past
(Saunders & Lewis, 2012). The secondary data is readily available and can be retrieved from
public libraries and online sources. The secondary data can be in the form of published books,
journals, periodicals, newspapers and articles (Saunders & Lewis, 2012). Similarly, the
secondary data can be readily available on soft copies. There are three key benefits of using the
secondary data. Firstly, it is faster to use secondary data because it can be readily available, thus,
reducing the amount of time taken to retrieve such information. Secondly, it is cheaper to collect
secondary data since it does not involve complicated procedures. Thirdly, collecting data using
secondary methods is less tedious since it does not involve field activities. However, Saunders et
al. (2011) note that the secondary sources have limitations. In some situations, it is difficult to
get appropriate data regarding a particular topic. Secondly, secondary data may not be adequate
thus making it difficult to attain research objectives. Thirdly, the secondary data may be outdated
and this may jeopardise the research findings. On the other hand, the primary data refers to first-
hand information collected from the field (Myers, 2013). The primary data can either be

28
qualitative or quantitative based on the research requirements. The primary data can be collected
using methods such as interviews, questionnaires and observation (Bryman & Bell, 2015). Based
on the requirements of this study, the researcher adopted the use of the online questionnaire that
is a primary source of data. The online questionnaire method was selected because the researcher
wanted to collect data from a large sample of customers to investigate the impact of window
displays, income level and credit card offers on the level of impulse buying in the Chinese retail
industry. The interviews and observation were not used because the researcher wanted to collect
quantitative data that was to be converted into a numerical form to make it easier for statistical
calculations. There are three key benefits the researcher obtained from the use of an online
questionnaire. Firstly, the online questionnaires are flexible and can be adjusted when the need
arises. Secondly, it is easier to reach a broad audience within the shortest time possible. Thirdly,
the closed-ended questions used allows standardisation of data which made it easier to analyse
the data statistically. Therefore, the online survey questionnaire was the most appropriate in this
study as compared to other methods of data collection.
3.9 Description of Data
The researcher targeted 500 customers who frequented the top five busiest shopping malls in
Beijing City. The top five retail shops in Beijing where customers frequent includes the Oriental
Plaza Malls, the Shin Kong Place Malls, the Beijing Yintai Center, Solana Beijing Shopping
Mall and the Place Retail Center. The Oriental Plaza Malls are the largest commercial retail
malls in Asia, located in the heart of Beijing. The Malls at Oriental receive many customers a
day. The Shin Kong Retail Place is another biggest shopping mall in China that attracts many
customers to a day due to its modern set up and displays. The Beijing Yintai Center is the third
largest shopping mall in China as well with a large following of customers. Similarly, the Solana
and Place shopping malls are also designed to attract customers. The researcher selected the
mentioned retail centres to represent impulse buying in the retail industry in China. The customer
respondents were randomly selected based on the retail mall they frequented. Therefore, the
researcher categorised customers according to the five retail malls to strike a balance in
investigating how window displays, income level and credit card offers influence the level of
impulse buying in the Chinese retail industry. Since it was not possible to strike the required
balance through hand-delivery of the designed questionnaires, the researcher adopted the online
survey. Customers were asked to indicate the mall they frequently go for shopping before

29
answering the impulse questions. Therefore, the researcher was able to categories responses
regarding the mentioned malls to avoid biased responses.
3.10 Data Analysis
Data analysis is a systematic application of statistical tools or other logical techniques to analyse
the collected data to draw conclusions (Bryman & Bell, 2015). The process of data analysis
entails condensing, recapping and evaluating data to draw meaningful conclusions. Bryman &
Bell (2015) argue that the type of analysis used depends on the research requirements, type of
philosophy adopted and the methods used to collect data. Further, Punch (2013) postulates that
three critical considerations must be made to ensure the credibility of the research findings after
data analysis. Firstly, the researcher must have the required skills to analyse the data. Having
appropriate skills on the method used will make it easier for the researcher to analyse the data.
The researcher also must be able to choose appropriate methods of data collection to make it
easy to analyse data. Thirdly, the researcher must follow the research acceptable norms. As noted
earlier, the method used to analyse data depends on the research requirements. Based on this
research, this study aimed at investigating how window displays, income level and the credit
card offers influence the level of impulse buying in Chinese retail industry. The data was
collected using online survey questionnaires and the responses were ranked on an ordinal scale
and the scores were recorded on a five Likert-scale. Therefore, based on the requirements this
study, the researcher adopted descriptive statistics. The mean was used as a measure of
dispersion. As noted by Creswell (2013), descriptive statistics provides information in a more
meaningful way. Additionally, the researcher of this study was well conversant with the usage of
statistical software (SPSS) which ensured the reliability of the Research Findings.
3.11 Summary
The chapter provided a detailed methodology adopted by the researcher in achieving the
objectives of this research. The three research hypotheses were formulated from an extensive
review of the current literature. The formulation of the hypotheses was critical because they
provided clarity, focus and direction for the study. Similarly, the three research questions were
formulated from the current literature to help the research focus on the main objectives of the
research. The research philosophy adopted by the researcher was positivism since this was
quantitative research. Since the study's data were to be analysed quantitatively, the research
employed deductive reasoning. The research aimed at investigating how the window displays,
income level and the credit card offers in the Chinese retail industry. To achieve this, the

30
researcher adopted the survey strategy to collect data from a large sample to ensure that the
research findings are reliable. Similarly, the researcher adopted the descriptive research design as
opposed to exploratory and case studies since the data was to be analysed using statistical
calculations. The primary data was utilised to achieve the core aims of this study. The online
questionnaire was used to collect the raw data that was analysed to draw the research findings.
The respondents were randomly selected from the top five retail stores in China. The
respondents’ answers were analysed using descriptive statistics to draw the research findings.
Chapter 4
Research Findings and Analysis
4.1 Introduction
A noted earlier by Bryman & Bell (2015), data analysis entails systematic recapping, condensing
and evaluating the collected data to draw conclusions. The collected data was analysed using
descriptive statistics to draw conclusions. The research paper aimed at investigating how window
displays, income level and the credit card offers influence the level of impulse buying in the
Chinese retail industry. The researcher ensured all the hypotheses formulated from the extensive
review of the existing literature were testable. The analysis was also aimed at uncovering any
unforeseen trends so that the researcher could establish the causal and statistical relationship that
could be interpreted in a more meaningful way. This chapter therefore, presents the data analysis
and research findings. The chapter is structured into four key sections. The first section
introduces this chapter and provides the structure of the chapter. The respondent's profile is
discussed in detail in the second section. Issues such as age, gender, marital status, occupations,
income level and the level of education are discussed in detail in the second section as well. The
main results of this research are discussed in the third section. The three hypotheses formulated
from the extensive review of the existing literature are tested comprehensively to draw
conclusions. The last section provides a comprehensive summary of the entire chapter.
4.2 Sample Description
The researcher focused his attention in the Chinese retail industry where he wanted to investigate
the influence of window displays, income level and the credit card offers on the level of impulse
buying. To achieve this, the research decided to select his sample from Beijing City where there
are many retail outlets and consumers. The top five retail shops in Beijing where large numbers

31
of people stream for shopping every day includes the Oriental Plaza Malls, the Shin Kong Place
Malls, the Beijing Yintai Center, Solana Beijing Shopping Mall and the Place Retail Center. The
five categories of the mentioned retail outlets in Beijing helped the researcher to categorise his
sample to attain a balance purposely to avoid biases. The targeted number of respondents was
500. Because it could not have been possible for the researcher to administer questionnaires on
hand-delivery, he opted to use the online survey questionnaire. Customers were asked to select
their best retail stores before answering the questions related to impulse buying. The researcher
also ensured that all participants were in possession of the credit card offers and had access to
monthly income. This helped the researcher to strike a balance when selecting the number of
respondents who visited various retail stores in Beijing China. More than 800 participants
showed interest in filling the questionnaires. However, the researcher had selected only those
respondents that met the research requirements. For instance, he ensured that they had credit
cards, he ensured that they had access to income and made sure that they frequented the
mentioned retail outlets in Beijing. After screening the 800 interested participants, the researcher
eliminated 300 participants to remain with 500 which was the targeted sample. All the five
hundred selected respondents met the requirements of this research. However, out of the 500
respondents, 490 successfully filled the questionnaires and returned them to the researcher after
two weeks. It, therefore, implies that 98% of electronically distributed questionnaires were
returned duly filled. The unreturned questionnaires only represented 2% that was insignificant
and could not influence the research outcome. The respondents were asked to fill voluntarily the
questionnaires implying that the responses were sincere and honest.
4.3 Respondent’s Profile
4.3.1 Gender
490 respondents successfully filled and returned the questionnaires. Out of the 490 respondents
who participated, 250 were males, and 240 were females. Regarding percentages, 51% of the
successful participants were males while 49% were females. The difference between the two
participating genders was only 2%, which was insignificant and did not have any profound
influence on the research outcome. The researcher also tried to achieve the gender balance based
on the country's total population in which 51.2% are male whiles the rest are female. The balance
between the genders was significant in eliminating any chances of biases in the research findings

32
because both genders are victims of impulse buying in the Chinese Retail Industry. Tables 2 and
Figure 3 provides the summary of the gender's profile who participated in this research.
Table 2: Respondents’ Profile
Gender Number of Participants Percentage
Female 240 51%
Male 250 49%
Source: Author
Figure 3: Gender Profile
Source: Author
4.3.2 Age
The participants who took part in this exercise were comprised of different age groups. The age
groups, which participated were 18-35, 36-56, 57-65 and above 66. The majority of the
respondents belonged to age groups 18-35 and 36-56. 250 respondents belonged to age group 18-
36, 150 belonged to age group 36-56, 50 belonged to age group 57-65 and the rest belonged to
those who were above age 66. Concerning percentages, 51% belonged to age group 18-36,
30.6% belonged to age group 36-56, 10.2% belonged to age group 57-65 while 8.2% had 66
years and above. As noted by the researcher, the majority of the buyers involve those who are
young, energetic, financially secure and full of lifestyle. Similarly, the researcher tried to strike a
balance by integrating other age groups as mentioned to ensure that the data collected was free of
biases. Table 3 and Figure 4 provides a summary of the respondents' age groups.
51%49%
0%0%
Gender
Male Female

33
Table 3: Respondent’s Age Groups
Age-Group Number of Participants Percentage
18-35 250 51%
36-56 150 30.6%
57-65 50 10.2%
66 and Above 40 8.2%
Source: Author
Figure 4: Respondent’s Age Groups
Source: Author.
4.3.3 Marital Status
Both married and unmarried respondents participated in this study. Out of the 490 participants,
300 were married, 186 were single, and 4 were divorced. Concerning percentages, 61.2% were
married, 38% were single while 0.8% were divorced. Based on the provided marital status's data,
the majority of the respondents comprised of the married people. The single individuals were the
second largest target population consisting of 38%. The single individuals starting life have a
higher affinity to purchasing various products in the retail industry. The researcher achieved the
marital status balance that helped in eliminating any chances of biases in the collected data.
Table 4 and Figure 5.
Table 4: Respondent’s Marital Status
Marital Status Number of Participants Percentage
Married 300 61.2%
Single 186 38%
Divorced 4 0.8%
Source: Author
51%
31%
10%
8%
Respondent's Age Groups
18-35 36-56 57-65 66+

34
Figure 5: Respondents’ Marital Status
Source: Author
4.3.4 Level of Education
The respondents had different levels of education background. It was essential to categorise the
respondents based on their education levels to avoid any bias in the research findings. The
education level was categorised into Secondary Level, Diploma Level and the University Level.
150 participants has secondary school education level, 200 participants were diploma graduates
while 140 had the university education and above. Regarding percentages, 30.6% were
secondary school graduates, 40.8% were diploma graduates while 28.6% had the university
education and above. Therefore, the majority of the respondents were diploma graduates
followed by secondary school graduates and university graduates respectively. Similarly, striking
a balance between education backgrounds of the respondents implies that the researcher aimed at
avoiding biases. Table 5 and Figure 6 illustrates the respondents' education level.
Table 5: Respondent's Education Background
Education Level Number of Participants Percentage
Secondary School 150 30.6
Diploma 200 40.8
University and Above 140 28.6
Source: Author
61%
38%
1%0%
Respondent's Marital Status
Married Single Divorced

35
Figure 6: Respondent’s Education Background
Source: Author
4.3.5 Occupation Level
The respondents were either employed, self-employed, unemployed or students. Out of the 490
respondents who participated in this study, 260 were employed, 150 were self-employed, 50
were unemployed, and 40 were students. Regarding percentages, 53% were employed, 30.6%
were self-employed, 10.2% were unemployed, and 8% were students. The majority of the
respondents composed of the employed and the unemployed. Since the income level was one of
the variables under investigation, it was essential for the researcher to take into consideration the
employed, self-employed, students and the unemployed. This balance was essential in ensuring
that the data was free from bias. It is also essential to note that those people who are engaged in
impulse buying must have a source of income. The unemployed comprised housewives who get
money from their spouses to do purchases. The students also get money from their parents and
sponsors some of which is used in making purchases. Therefore, the researcher considered
categorising the sample about the occupation level. Table 6 and figure 7 illustrates the
respondent's occupation level.
Table 6: Respondent’s Occupational Level
Occupation Level Number of Participants Percentage
Employed 260 53%
Self-Employed 150 30.6%
Unemployed 50 10.2%
Students 40
Source: Author
30%
41%
29%
0%
Respondents' Education Level
Secondary Education Diploma Education University Education and Above

36
Figure 7: Respondent’s Occupation Level
Source: Author
4.3.6 Income Level
The other essential component of categorising the participants was the income level. The
respondents who participated in this research had different levels of monthly income. The
income levels were significant in determining the respondents' purchasing power that also helped
in showing the level of impulse buying. The income levels were categorised into four key
categories namely below $1000, between $1001 and $2000, $2001-$2500 and above $2,600.
Out of the 490 participants, 90 earned below $1000, 90 earned $1001-$2000, 200 earned $2001-
$2,500 and 110 earned above $2,600 monthly. The income level was significant in measuring the
level of impulse buying in the Chinese retail industry. The majority of the respondents earned
between $2001-$2,500, followed by those earning above $2,600, $1000 and below $1000
respectively. Table 7 and Figure 8 illustrates the respondents' level of income.
Income Level Number of Participants Percentage
Below $1000 90 18.4%
Between $1001-$2000 90 18.4%
Between $2001-$2,500 200 40.8%
Above $2,600 110 22.4%
Source: Author
52%
30%
10%
8%
Respondent's Occipation Level
Employed Self-Employed Unemployed Students

37
Figure 8: Respondent’s Level of Income
Source: Author
4.4 Results
4.4.1 Review
The researcher's core aim was to investigate how window displays, income level and credit card
offers influence the level of impulse buying in the Chinese retail industry. It was, therefore,
critical to analyse the respondent's responses to draw conclusions. As noted earlier, the online
survey questionnaire was used to collect the primary data from the 490 successful respondents.
The Likert-scale was used in ranking the respondent's responses on a scale of 1-5. The Likert
scale was marked strongly disagree, disagree, neither agree nor disagree, agree and strongly
agree from 1 to 5 respectively. The measure of dispersion was used in the analysis in which a
mean score below 3.0 implied that respondents either disagreed or strongly disagreed with the
question's requirement. The mean score of exactly 3.0 implied impartiality while a mean score of
more than 3.0 suggested that the respondents either agreed or strongly agreed with the question's
requirement. All the three formulated hypotheses were tested by the researcher that included:
 The window displays have a significant influence on increasing the level of impulse
buying in the Chinese retail industry.
 The Income level increases the level of impulse buying in the Chinese retail industry. The
 The usage of credit card offers increases the level of impulse buying in the Chinese retail
industry.
19%
18%
41%
22%
Respondents'Income Level
Below $1000 Between $1001-$2000 Between $2001-$2,500 Above $2600

38
4.4.2 The window displays have a significant influence on increasing the level of impulse
buying in the Chinese retail industry.
The researcher evaluated the first hypothesis by asking various questions related to window
displaying and impulse buying. According to the first hypothesis, window displays can
significantly influence the level of impulse buying in the Chinese retail industry. Table 8 and
figure illustrates the descriptive statistical results regarding the participant’s responses.
Table 8: Descriptive Statistics (Window Displays)
Descriptive Statistics
Item N Minimum Maximum Mean
Std.
Deviation
Attracted to buy an attractively displayed
product the first time
490 1.00 5.00 3.8204 1.18287
Not influenced to purchase a displayed
product if you had not budgeted for it
490 1.00 5.00 2.3980 1.35317
Have the capacity to resist making an impulse
buying decision
490 1.00 5.00 2.5388 1.22663
The art of window displays makes you
develop an interest to buy
490 1.00 5.00 3.9327 1.18682
prone to making impulse buying decisions 490 1.00 12.00 3.8857 1.30094
Valid N (listwise) 490
Source: Author
Figure 8: Descriptive Statistics on Window Displays.
Source: Author.
0 0.5 1 1.5 2 2.5 3 3.5 4
ATTRACTED TO BUY AN ATTRACTIVE DISPLAYEDPRODUCT
THE FIRST TIME
NOT INFLUENCED TO PURCHASE A DISPLAYEDPRODUCT IF
YOU HAD NOT BUDGETED FOR IT
HAVE THE CAPACITY TO RESIST MAKINGAN IMPULSE BUYING
DECISION
THE ART OF WINDOW DISPLAYS MAKES YOU TO DEVELOPAN
INTEREST TO BUY
PRONE TO MAKING IMPULSE BUYING DECISIONS
Window Displays
Stadard Devistion Mean

39
The first question asked respondents to rank whether they are attracted to buy the window
displayed products the first time they see them. The participants' responses to this question
scored a mean score of 3.8204 which was above 3.00 implying that they agreed with the
question's requirement. Based on the respondent's answers to this question, customers in the
Chinese retail industry are attracted to make an impulse purchase whenever they come across
fascinating window displayed products. The higher score in this question as well implies that the
Chinese retailers have learnt how to capture consumers' attention when they pass by. The
indication that customers are attracted the first time they come into contact with a window
displayed product and makes an abrupt buying decision reveals that the level of impulse buying
in the Chinese retail market is very high.
Secondly, the participants were asked whether they are not influenced to purchase a displayed
products if they had not budgeted for them. The responses recorded a mean score of 2.3980
which is below 3.00 an indication that they either disagreed or strongly disagreed with the
question's requirement. The lower score in this question reveals that in the Chinese retail
industry, customers are influenced by the window displays to make unbudgeted purchases. The
unbudgeted purchases result in impulse buying which later on may be a source of remorse and
unhappiness. The fact that the customers in the Chinese retail industry make unbudgeted
purchases whenever they come across window displayed products shows that the level of
impulse buying is very high.
Thirdly, the respondents were asked whether they have the capacity to resist making an impulse
buying decision whenever they come into contact with a window displayed product. The
question was aimed at testing whether the customers had the capability to resist emotions that the
encouraged them to indulge in the impulse buying behaviour. Surprisingly, the customers'
responses revealed that the ability to resist emotions to make an abrupt purchase was hard. The
responses scored a mean score of 2.5388 which was below 3.00 implying that they either
disagreed or strongly disagreed with the questions requirement. The low mean score revealed
that the customers in the Chinese retail industry have no capability to resist the urge of making
unbudgeted window displayed product when they come into contact with it. The inability to
control emotions that trigger impulse buying shows that the level of impulse buying in the
Chinese retail industry is very high.

40
Fourthly, the respondents were asked whether the art of window displays makes them develop an
interest to buy a displayed product. The mean scored in this question was 3.9327 showing that
that the participants either agreed or strongly agreed with the requirement of the question. The art
of window displaying in the Chinese retail industry is irresistible, and it has the capability of
attracting the intentions of the passing consumers. This significantly contributes to influencing
consumers to make abrupt buying decisions. Thus, the art of window displays in the Chinese
industry results to a higher level of impulse buying.
Lastly, the respondents were asked whether they are are prone to making impulse buying
decisions whenever they are attracted to a product that is appealing to them. The responses
scored a mean score of 3.8857 showing that the respondents agreed with the question. The fact
that the customers are prone to making impulse buying when they see window displayed
products shows that the level of impulse buying in the Chinese retail industry is very high.
To evaluate and examine the second hypothesis, the researcher asked five questions related to the
influence of the income level of the impulse buying. According to the second hypothesis, the
higher the level of income, the higher the urge of making unplanned purchases that result in the
higher level of impulse buying in the Chinese retail industry. The participant's responses were
descriptively analysed, and the results are indicated in Table 9 and Figure 10 respectively.
Table 9: Descriptive Statistics (Level of Income)
Descriptive Statistics
N Minimum Maximum Mean
Std.
Deviation
The more money you have, the more products
you buy
490 1.00 5.00 3.8388 1.23866
You stick to your budget regardless of the
amount of income you have
490 1.00 5.00 2.5061 1.10630
Your income level dictates the amount of
products you purchase
490 1.00 5.00 4.0020 1.02823
You do not consider prices as long as you
enough money to buy products
490 1.00 5.00 3.9531 1.01514
You do not buy expensive products regardless
of the amount of money you have
490 1.00 5.00 2.4878 1.14619
Valid N (listwise) 490
Source: Author

41
Figure 10: Descriptive Statistics on Income Level
Source: Author
The first question required the respondents to rank whether when the have more money they
make unbudgeted purchases. The question was aimed at measuring the desire to buy extra
unbudgeted products if the consumers had more money. The responses to this question attracted
a mean score of 3.8388 which was above 3.00 implying that they either agreed or strongly agreed
with the question’s requirements. The urge of overspending when consumers have a lot of
money indicates that the level of impulse buying in the Chinese retail industry is very high. The
respondents were further asked whether they can stick to their budget regardless of the amount of
income they have whenever they make purchases. The question was intended to measure
whether consumers can control their urge to overspend regardless of the fact that they had
enough money to make extra purchases. The responses to this particular question attracted a
mean score of 2.5061 which was below 3.00 an indication that the respondents either disagreed
or strongly disagreed with the question's requirement. The respondents indicated that they can
hardly stick to their purchase whenever they have enough cash to buy additional products that
were appealing to them. The temptation of overspending when consumers have more money
implies that the level of impulse buying in the Chinese retail industry is very high.
The researcher also wanted to know whether the level of income dictated the customers when
making purchases. The respondents’ answers attracted a relatively high mean score of 4.0020.
The respondents either agreed or strongly agreed that the level of income was a significant
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
THE MORE MONEY YOU HAVE, THE MORE PRODUCTS YOU
BUY
YOU STICKTO YOUR BUDGET REGARDLESSOF THE AMOUNT
OF INCOME YOU HAVE
YOUR INCOME LEVEL DICTATES THE AMOUNT OF PRODUCTS
YOU PURCHASE
YOU DO NOT CONSIDER PRICES AS LONG AS YOU ENOUGH
MONEY TO BUY PRODUCTS
YOU DO NOT BUY EXPENSIVE PRODUCTS REGARDLESSOF
THE AMOUNT OF MONEY YOU HAVE
Income Level
Series 3 Standard Deviation Mean

Dessertation 3 research on factors influencing the level impulsive buying behavior in the chinese retail industry.edited (1)

Dessertation 3 research on factors influencing the level impulsive buying behavior in the chinese retail industry.edited (1)

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