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Essay: The Online Shopping Experience – literature review

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  • The Online Shopping Experience - literature review
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Shopping: ‘the new form of hunting’ (Genco et al. 2013)

Peterson (1997), has been quoted explaining that shopping ‘is a process, composed of a set of distinct components linked together in a particular sequence’ (Mokhtarian 2004; Hsiao 2009).

Characteristically, this process includes ‘desire, information gathering/receiving, trial/experience, evaluation, selection, transaction, delivery/possession, display/use, and return’ (Mokhtarian 2004, p. 264). In more simpler terms (1) need recognition; (2) information search; (3) evaluation; (4) purchase, and finally (5) post-purchase (Price et al. 2009).

This process, however, varies depending on the product being bought gender and location from where the product is being purchased (Kotler et al. 2005). This means that buying a product from a physical store and buying the same product from an online store can create a much different buying process (Constantinides 2004; Kau et al. 2003).

The level of satisfaction or dissatisfaction from a shopping experience depends on a multitude of factors. Some obvious factors include the actual product being bought; the shop or website the product is being purchased from and the service received from the company of the product, before, during and after the purchase (Kotler et al. 2005). Other important factors include age, gender and the overall attitude of a consumer towards shopping (Settle & Alreck 2002).

The difference between the two can be explained by the understanding the meaning of shopping environment and the evaluation of brand loyalty in two main shopping environments; the online and brick-and-mortar even if very little research has been yet conducted on the differences between these two environments (Hsiao 2009).

2.1 The Online Shopping Experience

With the increasing number of online sales and the rising number of shoppers utilizing online stores, it is imperative for businesses to develop a better understanding of the e-commerce users and ‘to better comprehend their attitudes, pattern of information acquisition and purchase decision-making process’ (Kau et al. 2003, p.140). Understanding this is a matter of understanding what motivates consumers to purchase online and what needs to be done to increase and maintain this motivation. CITE

2.1.1 The Online Shopping Environment

The level of satisfaction depends on the consumers’ impression of the website’s design, event, emotions and atmosphere created over a number of stages ‘ from searching to interacting and transacting. In other words, the online shopping experience is defined by the consumers’ exposure to the virtual marketing tools (Constantinides 2004).

However, besides trust and digital marketing tools, it is also important that the website must create and deliver a combination of ‘online functionality, information, emotions, cues, stimuli and products/service’ (Constandtinides 2004, p. 112). That is, a complex mix of elements that goes beyond the traditional marketing mix. In fact, as explained in Figure X these factors can be categorized into two sections; the Personal and Environmental Uncontrollable Factors and the Online Controllable Marketing Forces’.

Besides the use of marketing tools, trust, is also a vital factor that needs to be delivered on an e-commerce website (Kau et al. 2003), so much so that research has identified this as another step in the online buying decision process (Constantinides 2004). Figure X represents this online buying process.

Figure 1: Factors Affecting the Online Consumer’s Behaviour (Constantinides, 2004)

2.2.2 Online Shopping Motivation (38/200 words)

There may be various reasons why consumers would prefer to shop online rather than in brick-and-mortar stores, including time flexibility and the opportunity to engage in impulsive buying or directly responding to an advertisement (Kau et al. 2003).

2.1.3 Age and Gender Attitude towards Online Shopping

Males have been described as the first profile of a typical internet shopper (Sorce et al. 2005), but this has now changed. Studies show that there are no preferential differences between genders when shopping online (Settle & Alreck 2002).

When it comes to age differences, Sorce (2005) suggests that younger consumers agree that online shopping is more convenient, even if, as a group, they are more engaged in the search for different products rather than actually purchasing the product. The study continues by showing that, older consumers, on the other hand, tend to purchase more in relation to the amount of search they conduct for the different products.

There is, however, a substantial amount of research that focuses on who is the actual consumer of the internet. Some research suggest that the online consumer depends on demographics such as income, education and age (Sorce et al. 2005). Others suggest that age affects the level of pre-purchase search in manner that it is negatively correlated but positively correlated when online purchases (Sorce et al. 2005). This means that as age increases, the level of purchases increases but the level of pre-purchase research decreases.

2.2 The Brick-and-Mortar Shopping Experience

Brick-and-mortar is defined as ‘a traditional street-side business that deals with its customers face to face in an office or store that the business owns or rents’ (Investopedia n.d.). Even if this type of shopping medium does not offer the 24/7 convenience of an online shop, it offer consumers the ability to first hand interact with the environment and goods at hand (Mokhtarian 2004).

2.2.1 The Brick-and-Mortar Shopping Environment

Shopping can take various goals such as ‘doing shopping’ and ‘going shopping’ (Genco et al. 2013; Settle & Alreck 2002). Depending on these goals, the customers are able to make up an experience through their perception of the retail environment and the overall satisfaction of the experience (Price et al. 2009).

Predominately the more shopping is seen as a chore the less the consumer is consciously aware of the marketing efforts (Genco et al. 2013). These different types of goals explain why customers have different types of shopping behaviours which in turn show retailers the need to restructure or opening new stores based on these goals (Price et al. 2009).

A positive shopping experience in brick-and-mortar shopping environment is a result of the senses triggered while shopping (Mokhtarian 2004; Genco et al. 2013). This includes the ability for the consumers to physical go to a store (touch); the effect of light (sight); scents (smell) and music and/or noise (hearing) in a store CITE.

However, senses are just part of the influences consumers’ experience. In fact, the shopping experience can be also affected by the ‘impact of consumer personality, temperament, and behavioural style on shopping behaviour and outcome’ (Genco et al. 2013).

2.2.2 The Brick-and-Mortar Shopping Motivations

‘One of the earliest efforts to identify and classify the reasons people shop (Tauber 1972) suggests that personal and social needs motivate shopping, beyond the simple need to acquire some product’ (Price et al., 2009 p. 16).

Even if consumers are bound with limited opening hours, the main benefits of shopping from brick-and-mortar shops are tangibility (including the shopping environment in itself) and immediate possessions (Mokhtarian 2004) – since generally consumers receive the product immediately after they pay for the product (Hsiao 2009).

Other motivations for consumers to shop in brick-and-mortars are more psychological than the specific need for a good, including; social interaction (especially, but not limited to those that live alone), entertainment (levels of which varies from one person to another), recreation, trip changing or intellectual stimulation (Mokhtarian 2004; Price et al. 2009).

2.2.3 Age and Gender Attitude toward Brick-and-Mortar Shopping

Various characteristics distinguish males from female consumers; for instance, females rarely see shopping as a chore. In fact, these prefer to shop with other family members and friends to make an event out of it. This is in complete contrast to males, where these prefer that others do their shopping for them and when they actually shop, they seek to do so in the least possible time (Settle & Alreck 2002).
However this trend is changing and males, especially in the white collar class, are engaging in more shopping activities which could be attributed to the fact that now-a-days both males and females are in the workforce (Mortimer & Clarke 2011).

2.3 Brand Loyalty

Brand is defined as a ‘name, term, symbol, design or a combination of these, that identifies the maker or seller of the product or service’ (Kotler et al. 2005, p. 549). However, brands are not just the names and symbols but rather ‘everything that the product or service means to consumers’ (Kotler et al. 2005, p.555).

Kotler et al. (2005) continue to explain that having a strong brand means that a brand is capable to capture consumers’ preferences and brand loyalty which is measured through brand equity. This is defined as ‘the value of a brand, based on the extent to which it has high brand loyalty, name awareness, perceived associations, and other assets such as patents, trademarks and channel relationships’ (Kotler et al. 2005, p.556).

Other papers on brand equity ‘ Keller 1998; Aaker 1991, Barwise 1993 ‘ focus on components of brand equity.

However, for this particular study the focus will be on one of these components, mainly the brand experience. This is defined as ‘sensations, feelings, cognitions and behavioural responses evoked by brand-related stimuli that are part of a brand’s design and identity, packaging, communications, and environments’ (Brakus et al. 2009, p. 52). Brakus et al. (2009) further explain how brand experience is related to but at the same time different from other brand constructs such as brand attitudes, brand involvement, brand attachment, and brand personality. In fact, an experience may be the basis for more elaborative information processing and inference making that result in brand-related associations. In turn, these associations may affect satisfaction and loyalty. In other words, from the positive experience of a person with a brand leads to satisfaction which in turn leads to loyalty.

Brand loyalty is defined as a ‘repeated purchases of particular products and services during a certain period of time’ (Youjae & Hoseong 2003 p. 231). Kim et al. (2008) further explain that brand loyalty is ‘a construct that has both attitudinal and behavioural elements’ (p. 80) especially when defined as a non-random purchase ‘expressed over time by some decision-making units with respect to one or more alternative brands’ (p.80).

Various researches have been conducted on brand loyalty. Some research such as Ehrenber (1988); Jacoby and Chestnut (1978) and Oliver (1997) have focused on classifying the different loyalty. Other research examined the relationships between program loyalty and brand loyalty. Of particular importance even for this study, is the implication from the study of CITE. This study showed that loyalty programs should be different depending on the involvement on part of the customers, in fact the CITE concludes that ‘under high involvement, program loyalty is formed based on value perception, and the loyalty program affects brand loyalty via both direct and indirect routes.”
The implications of a good website and triggers of senses go beyond the actual product so much so that having a strong brand and a positive online experience go hand in hand (Constantinides 2004). In fact, Kau et al. (2003) explain how a strong offline brand, affected by well-exploited sense, will positively affect online shopping because it determines if the consumer will return or not; not only online but also in any brick-and-mortar stores the company might have.

2.4 Consumer Neuroscience

The field of neuromarketing is relatively new. According to Morin (2011) neuromarketing first appeared in 2002 by two companies offering neuromarketing research at the time: BrightHouse and SalesBrain.

According to this author, the first scholar paper on this field was later published by Read Montague, Professor of Neuroscience at Baylor College of Medicine in 2003 when he tested what the consumer preferred between Coca Cola and Pepsi through the use of the fMRI (Functional Magnetic Resonance Imagining) technique. This experiment triggered a number of criticisms towards this new field fearing that it will eventually find a way to manipulate the consumer purchases ‘ and therefore the consumers’ freedom of choice. However, this did not stop the field from evolving, and today, even if still in its infancy, neuromarketing is on a steady growing rate both academically and professionally.

2.4.1 Defining Consumer Neuroscience

Different definitions have been given to consumer neuroscience; also known as neuromarketing. One definition constructed by Nielsen (n.d.) defines consumer neuroscience as ‘the application of neuroscience (the study of the human brain and nervous system) to consumer research, in order to determine a consumer’s non-conscious response to brands, products, packaging, in-store marketing, advertising, and entertainment content.’

Another definition suggests that neuromarketing is ‘any marketing or market research activity that uses the methods and techniques of brain science or is informed by the findings or insights of brain science’ (Genco et al, 2013 p. 8). This highlights an important difference between marketing and neuromarketing; that is, that while marketing is to influence people to buy certain products, neuromarketing is ‘a new way to measure whether and how marketing is working’ (Genco et al, 2013 p. 8).

Therefore, neuromarketing according to Morin (2011) is a solution for companies who are, or have suffered in the past, from unsuccessful campaigns, only because they relied on consumers to tell them the truth of how they feel about a product, service or brand, but failed to do so for a number of reasons.

2.4.2 How does it Work?

Genco et al. (2013) explains how as opposed to traditional marketing research where consumers are said to be rational, neuromarketing creates another model; ‘the intuitive consumer model’ (p. 73). This, explains Genco et al. (2013), tells us that the consumer is not a ‘slow and careful deliberator’ to its choices of shopping but rather, a ‘cognitive miser’; that is, that the brain produces fast and efficient decisions and actions to reduce mental effort by means such as efficiency, novelty, familiarity and processing fluency. This demonstrates how consumers, more often than not, are not consciously aware to why they are purchasing a particular product or why they are switching brands.
One way to understand why consumers are not always consciously aware of their routine or switch in brands is because of the physiological senses; sight, smell, taste, hearing and touch. Zurawicki (2010) explains how, ‘Through the senses, the body perceives all the information arriving from the outside world; the brain interprets this information and produces chemical and physical responses which are translated into thoughts and behaviours.’ (p. 12) Therefore, according to this author, gaining insight on such subject and its effects on the consumers is of great benefit.

When a person is stimulated by one of the senses, it experiences an action potential (also known as an evoked potential). At this stage the ions in the resting potential are disturbed (through a sensory stimulus) creating an action potential. An action potential generated from a sensory stimulus take the form of Visual Evoked Potentials (from sight), Gustatory Evoked Potential (from tasting) and/or Olfactory Evoked Potential (from smell) (Zurawicki 2010).

From the different possible evoked potentials, the visual evoked potentials is the most important for the study and it is important to have a basic understanding of how a person sees an object; that is, the process of how human sees.

When a person is looking at an object, light rays enter the eye through the cornea ‘ which is a transparent layer of tissue. These rays pass through the iris (also known as the pupil), where the iris contracts in order to change the pupil’s dimension and regulates the light coming in the eye. Light is then passed through the lens and hits the photosensitive walls of the eye (also known as the retina). The photosensitive walls in the retina will transform light into impulses which are transmitted to the brain though the optic nerve. As depicted in Figure X.

Figure 2: Basic Anatomy of the Eye and the Process from the Cornea to the Optic Nerve

The optic nerve then transports the signals from the retina to the thalamus which in turn forward the signal to the visual cortex at the back of the occipital lobe (situated at the back of the head). As depicted by Figure X Here the processing of colour, shape and motion is done and sight is perceived.

Figure 3: Visual Process from the Retina to the Perception of Color, Shape and Motion

The thalamus is situated at the heart of the brain and it is the brain’s sensory switchboard located at the brainstem (responsible for automatic survival functions). It directs messages to the sensory receiving areas in the cortex and transmits replies to the cerebellum (that helps coordinate voluntary movement and balance) and the medulla (that controls the heartbeat and breathing).

Different tools captures different responses and most of the time combining more than one tool together will provide better and more insightful results. The following table analysis neuromarketing techniques. BLABLABLA GENCO. The two most relevant tools for this research are the EEG and Eye Tracking.

Electroencephalography (EEG) is a ‘noninvasive and silent technology that’s directly sensitive to neuronal activity’ (Genco et al. 2013, p. 263). It measures electrical activity in the localised areas of the brain where electrodes (i.e. a conductor through which electricity enters or leaves an object, substance, or region) are attached to the scalp.

One of the possible EEG’s analyses is the ‘brain-wave frequency analysis’ (Genco et al. 2013, p.263). The brain can detect such frequencies in cycles per second using the units’ hertz (Hz). The author explains that the most easily seen frequency is that of 10 Hz, that is, 10 cycles per second. Different unit hertz, indicate the state of mind and state of consciousness of the being, and can be classified into five main categories; alpha, beta, theta and delta (Zurawicki 2010; Genco et al. 2013). Figure X is a summary of each of these brain-waves.

Figure 4: Summary of Brain-Waves Properties based on Genco et al. (2013) and Zurawicki (2010)
Zurawicki (2010) explains how the ‘disadvantages of EEG is that the electric conductivity, and therefore the measured electrical potentials can vary widely from person to person and at different time frames.’ (p. 49). He explains that is due to the fact that tissues in the body such as brain matter, blood and bones have ‘different conductivities for electrical signals’ (p.49).
Eye tracking, on the other hand, is a powerful tool for analysing behaviour and cognition of a test participant during a research project by analysing a number of important features (Zurawicki 2010). Genco et al. (2013) explain how these include; (1) the speed of eye movement, (2) duration of fixation, (3) pattern and frequency of blinks and (4) patterns of searching behaviour.
Fixations occur when the eye movement stops the retina on a particular object; that is a person’s eye stops and look (fixate) in certain position (Duchowski 2007; Zurawicki 2010; Genco et al. 2013). Fixations duration varies from 150ms to 600ms (Duchowski 2007) and Zurawicki (2010), continue explaining that the ‘resulting series of fixations and saccades is called a scan path’, which are used to analyse ‘visual perception, cognitive intent, interest and salience (p.51).

Saccade are eye movements from one fixation to another (Zurawicki 2010), in more technical terms it is the repositioning of ‘the fovea to a new location in the visual environment’ (Duchowski 2007, p.42). Duchowski (2007) continue by explaining that these can be either voluntary or reflexive with duration between 10ms and 100ms. Saccades have been termed as ballistic; that is, with the assumption that after the decision of the next point have been made, the saccade cannot change during the movement (Duchowski 2007).
Eye tracking results are analysed through heat maps, which are characterized by the fixations and saccades discussed, which can be achieved using software such as MATLAB and XXX. Results are presented with visual image in which the path taken by the person’s eye is traced in a numerical sequence.

2.4.3 Limitations of Neuromarketing

2.5 Summary


Constantinides, E., 2004. Influencing the Online Consumer’s Behavior: the Web experience. Internet Research, 14(2), pp.111’126.

Duchowski, A.T., 2007. Eye Tracking Methdology: Theory and Practice Second Edi., London: Springer.

Genco, S., Pohlmann, A. & Steidl, P., 2013. Neuromarketing For Dummies First., John Wiley & Sons Canada, Ltd.

Hsiao, M.-H., 2009. Shopping mode choice: Physical store shopping versus e-shopping. Transportation Research Part E: Logistics and Transportation Review, 45(1), pp.86’95.

Investopedia, Brick And Mortar Definition | Investopedia. Available at: [Accessed April 16, 2014].

Kau, A.K., Tang, Y.E. & Ghose, S., 2003. Typology of Online Shoppers. Journal of Consumer Marketing, 20(2), pp.139’156.

Kotler, P. et al., 2005. Principles of Marketing Forth Euro., Essex: Pearson Education Ltd.

Mokhtarian, P.L., 2004. A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3), pp.257’284.

Mortimer, G. & Clarke, P., 2011. Supermarket Consumers and Gender Differences Relating to their Perceived Importance Levels of Store Characteristics. Journal of Retailing and Consumer Services, 18(6), pp.575’585.

Price, R. et al., 2009. Customer Experience Management in Retailing: Understanding the Buying Process. Journal of Retailing, 85(1), pp.15’30.

Settle, R.B. & Alreck, P., 2002. Gender effects on Internet, Catalogue and Store Shopping. Journal of Database Marketing, 9(2), pp.150’162.

Sorce, P., Perotti, V. & Widrick, S., 2005. Attitude and age differences in online buying. International Journal of Retail & Distribution Management, 33(2), pp.122’132.

Zurawicki, L., 2010. Neuromarketing: Exploring the Brain of the Consumer, London: Springer.

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