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Abstract
Online shopping becomes increasingly important for modern businesses, and there is a lack of research on the topic, which is why the present dissertation is dedicated to an analysis of the relationships between online shopping applications and impulse buying. To investigate the two phenomena, a mixed-methods study was designed. One thousand thirty shoppers were surveyed, and 20 people were interviewed.
In addition, 74 buyers who used exclusively online shopping applications or brick-and-mortar stores completed a survey which was employed to determine if any of the two groups were more likely to engage in impulse buying. A statistical analysis of this survey demonstrated that while online shoppers did seem to buy spontaneously more often, the difference was not statistically significant.
The analysis of the rest of the responses (both surveys and interviews) shows that for the time being, it is impossible to state if there is a relationship between online shopping applications and impulse buying, but online shopping applications have multiple opportunities for promoting the behaviour. In conclusion, the dissertation offers recommendations regarding the use of said opportunities.
Introduction
Nowadays, online shopping becomes increasingly important, which makes it a useful tool for modern businesses. In addition, the research on the topic is becoming more diverse as it explores the various aspects of online purchases. However, since online shopping is a relatively recent development, the research does not cover all its significant features (Badgaiyan & Verma 2014; Rezaei et al. 2016). One of the topics that are not studied very extensively is the relationship between online shopping applications and impulsive buying behaviour.
Impulsive buying behaviour or impulse buying can be identified as unplanned or spontaneous buying. It is a very important factor to consider for modern businesses, mostly because it is responsible for a large percentage of sales worldwide (Lin & Lo 2015; Thompson & Prendergast 2015). Impulse buying in online shops is not very extensively studied (Park, Jun & Lee 2015), but due to the development of online shopping applications, this topic becomes more and more important. As a result, the present dissertation aims to investigate it and contribute some data that can be used by modern businesses.
The research has several key objectives, which can be summarised as follows.
Objectives
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First, the dissertation aims to determine if there is any relationship between online shopping applications and impulse buying.
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Further, it intends to investigate this relationship. Specifically, a discussion of the possible reasons and outcomes of this relationship, as well as its implications for businesses, is planned.
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Eventually, the study intends to provide some advice that would guide the use of online applications for stimulating impulse buying.
These objectives can be transformed into the following research questions.
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Is there a relationship between online shopping applications and impulse buying?
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If they can be found or theorised, what are the possible reasons for this relationship?
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What effects could this relationship have? Specifically, in which ways could shopping applications affect impulse buying?
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What are the implications of the findings for businesses? Can any advice on the matter be provided?
Thus, the study was developed with the general aim of offering modern businesses some information on impulse buying that can be employed in practice. This dissertation will contribute some data to the research of impulse buying behaviours and investigate the possible relationships between online shopping implications and impulse buying. As a result, the study should have both theoretical and practical value which is explained by the importance of the chosen topics and their underrepresentation in recent research.
The rest of the dissertation will be structured as follows. First, a literature review on the topics of impulse buying and online shopping applications will be presented; offline (brick-and-mortar) stores will also be considered as a counterpoint to online ones. Further, the methodology of the study that was developed for this dissertation will be described, including the methods used, the sample recruited, and the ethical considerations reviewed. Then, the findings of the study will be presented, and their discussion will be carried out in the following chapter. Eventually, conclusions will be made regarding the coverage of the research questions, and recommendations will be offered.
Background and Literature Review
Impulse Buying Behaviour: The Terminology
Impulse buying behaviour has received some attention from modern researchers, including psychologists (Thompson & Prendergast 2015). However, it is also of importance to marketing and business research, and the specialists in these fields have dedicated some attention to the phenomenon as well (Chan, Cheung & Lee 2017). Simply put, impulse buying is characterised by being spontaneous; it is the buying that occurs without planning, and its antonym is rational, planned buying (Lin & Lo 2015).
It is important to differentiate impulse buying and compulsive buying; the former is a norm, a simple situation in which a person acquires things without planning. The latter is a disorder that is characterised by negative outcomes, causes severe distress and requires medical attention (Darrat, Darrat & Amyx 2016; Thompson & Prendergast 2015). This form of spontaneous buying is not the topic of the present research; most often, it is studied to develop interventions that can help compulsive buyers to resolve their problem.
Impulse buying, on the other hand, is not harmful to buyers, although it might cause regret in certain instances (Lee, Park & Jun 2014). Still, it has been defined as a behaviour resulting from the positive effect that a consumer spontaneously experiences when confronted with a product or service which is manifested in the wish to buy a thing spontaneously and instantly (Lin & Lo 2015, p. 39). In addition, it is very common; according to different studies, up to 90% of the population purchase things impulsively from time to time (Lin & Lo 2015; Thompson & Prendergast 2015).
Impulse buying is believed to be responsible for up to 50% of all sales in the world (Lin & Lo 2015), and 40% of online purchases are also estimated to be spontaneous (Chan, Cheung & Lee 2017; Chen & Yao 2018). In other words, impulse buying is significant for businesses, which is why stimulating it is rational. This fact explains the interest of the present dissertation on the topic: any factors that can potentially improve impulse buying are of importance to business research.
There are different types of impulse buying; at least four different forms of it have been identified in the literature on the topic (Chan, Cheung & Lee 2017). Pure impulse buying is a simple unplanned purchase that occurs accidentally. Reminder impulse buying happens when a person sees a product and is reminded of the fact that they need it.
This type of impulse buying is especially common with the things that are used regularly (for instance, food or drinks); if a person does not remember to buy such a thing before seeing the product, reminder impulse buying occurs. Suggestion impulse buying happens when a person encounters a brand-new product and decides that he or she needs or wants it. In addition, there are planned impulse buying; it happens when a person goes to a store with the plan of buying something unplanned (Bellini, Cardinali & Grandi 2017; Chen & Wang 2015; Zhang et al. 2018). In the present dissertation, the term impulse buying incorporates all these options.
Different approaches to explaining impulse buying have been developed. However, one of them is particularly common in business research: Stimulus-Organism-Response (S-O-R or SOR) (Chen & Yao 2018; Ju & Ahn 2016; Lin & Lo 2015; Parboteeah, Taylor & Barber 2016; Prashar, Vijay & Parsad 2017; Wu & Li 2018). SOR is a framework that explains impulse buying by considering the stimuli that can cause it, the organism or the person who processes the stimuli, and the response to the stimuli (Chan, Cheung & Lee 2017; Parboteeah, Taylor & Barber 2016).
The response element incorporates the reaction to the stimulus and its evaluation (that is, they wish to buy a product) and the action of impulse buying (Parboteeah, Taylor & Barber 2016). This framework incorporates both the individual and environmental factors that can influence impulse buying, which is especially helpful for this study since it is dedicated to investigating the relationship between impulse buying and the stimuli of online shopping applications.
The research on impulse buying is expanding and becoming more extensive, but there is still much to investigate. Some findings require checking, and some topics related to impulse buying have not been explored to the full extent (Chan, Cheung & Lee 2017; Thompson & Prendergast 2015). For instance, online impulse buying has not been studied very extensively (Chan, Cheung & Lee 2017; Chen, Su & Widjaja 2016). Given the fact that online shopping applications, as well as online marketing, are also not very well researched (Badgaiyan & Verma 2014; Rezaei et al. 2016), it becomes apparent that the consideration of impulse buying behaviour in online shopping applications and their comparison to offline stores may be very helpful. Thus, the present dissertation aims to cover a gap in modern research.
Factors Impacting Impulse Buying Behaviour
Given the pervasiveness of impulse buying, business studies look into the ways of promoting impulse buying, determining the factors which cause it and can be used by businesses. In SOR, the stimulus element incorporates the factors that can potentially trigger impulse buying (Chan, Cheung & Lee 2017). However, the studied behaviour is rather complex, which brings attention to the second element of the framework: the organism which signifies the person who can be engaged in impulse buying (Lee 2018).
Here, it should be pointed out that impulsivity is closely connected to psychological factors, which explains many of its predictors (Chen & Wang 2015; Husnain & Akhtar 2016; Lin & Lo 2015; Ozer & Gultekin 2015). Certain theorists argue that the actual cause of impulse buying consists of varying problems with self-regulation, which is especially prominent in compulsive buying (Thompson & Prendergast 2015). Therefore, individual factors are important to consider.
As shown by Thompson and Prendergast (2015) and Chung, Song and Lee (2017), the currently existing evidence suggests that certain character traits or skills can predict impulse buying. In fact, some people are believed to have an impulse buying tendency, which is defined as a particular proneness to buying impulsively (Badgaiyan, Verma & Dixit 2016). If the lack of self-regulation is the cause of impulse buying, the people who are worse at self-regulation are more prone to impulsive, spontaneous purchases and vice versa.
Self-regulation is generally comprised of skills and abilities like setting goals, monitoring oneself, and restraining ones impulses (Badgaiyan, Verma & Dixit 2016; Thompson & Prendergast 2015). Using this information, Thompson and Prendergast (2015) demonstrate that certain traits like neuroticism or extraversion can affect ones impulse buying.
The same study also indicates that a persons state of mind may contribute to impulse buying, and Ozer and Gultekin (2015) support the idea through their investigation of pre-purchase moods. Similarly, according to a study by Park, Jun and Lee (2015), the shoppers who feel smart (that is, feel that they can use mobile shopping to buy things cheaper) are more likely to buy impulsively.
Furthermore, the specific buying preferences and habits of a person may matter. For example, the people who shop in a particular store regularly are more likely to buy from it impulsively (Bhuvaneswari & Krishnan 2015). On the other hand, people who prefer to plan their purchases are less likely to buy impulsively; extensive pre-planning is associated with lower impulse buying rates (Bellini, Cardinali & Grandi 2017).
Finally, there are certain tendencies found in different groups of buyers. Thus, women and men tend to make impulsive purchases of different products as associated with their social roles, and younger people are more likely to buy spontaneously than older ones (Bhuvaneswari & Krishnan 2015). Overall, the personal traits, characteristics, moods and feelings of a shopper matter when impulse buying is concerned.
In addition to personal characteristics, other phenomena that promote or constrain impulse buying may be significant. Socio-cultural factors have been shown to have some importance; they can include the influence of other people like ones family or peers, the specifics of ones culture and subculture, as well as ones socioeconomic position (Bhuvaneswari & Krishnan 2015; Islam et al. 2018).
Further, the situation of purchase is noteworthy; aspects like the time of shopping or the amount of money available may be significant (Parboteeah, Taylor & Barber 2016). For example, according to Akram et al. (2018) and Bhuvaneswari and Krishnan (2015), credit cards promote impulse buying due to the opportunity of spending more money, and if a person has much time for browsing the goods, they are more likely to buy something impulsively.
In other words, some factors that cause impulse buying are either individual or situation-specific, which is why they are unlikely to be influenced by businesses. However, the literature on the topic also demonstrates that there are external stimuli, which can and have been used by stores to cause customers to buy impulsively. The strategies that are commonly used by both online and brick-and-mortar stores include discounts, special offers and limited-time offers (Lin & Lo 2015).
Further, the price of goods and quality of services is a factor (Bhuvaneswari & Krishnan 2015; Lin & Lo 2015). Recommendations are important, as well as advertising; all these stimuli can promote impulse buying (Bues et al. 2017; Lin & Lo 2015; Zhang et al. 2018; Wu & Lee 2015). Overall, different marketing approaches have an impact on impulse buying.
The product itself, as well as its presentation, can be significant. Specifically, its package, brand, visual appearance and guarantees associated with it (for instance, the possibility of a refund) can promote impulse buying (Bhuvaneswari & Krishnan 2015; Husnain & Akhtar 2016; Siahpush et al. 2015; Wu & Lee 2015). Moreover, seeing something new can become a factor; a new product may result in its spontaneous buying as shown by suggestion impulse buying (Bellini, Cardinali & Grandi 2017; Chan, Cheung & Lee 2017).
However, it is important to remember that all the above-described strategies affect different people in various ways depending on their preferences, worldviews and other factors that are united by the organism element of SOR (Parboteeah, Taylor & Barber 2016; Zhang et al. 2018). The specific strategies employed by online and offline stores will be discussed below.
In conclusion to this section, it should be mentioned that different types of shopping may be associated with different frequencies of impulse buying. For example, some evidence suggests that Internet buyers are more likely to buy impulsively when compared to those frequenting retail stores (Chan, Cheung & Lee 2017; Lin & Lo 2015). Also, Lee, Park and Jun (2014) and Park, Jun and Lee (2015) note that there is a tendency for increased impulse buying among online buyers, specifically those who use mobile phones. Thus, it is possible that the differences in online and offline strategies or opportunities for promoting impulse behaviour may potentially result in one of the two being more conducive to spontaneous purchases.
Offline Stores Affecting Impulse Buying Behaviour
In this dissertation, online shopping applications are compared to brick-and-mortar stores. In this paper, they are going to be termed as offline stores to highlight the fact that they are different from online ones. This comparison is introduced because it is relatively simple to contrast online and offline means of shopping. In addition, online methods of shopping are relatively new and still developing (Badgaiyan & Verma 2014; Rezaei et al. 2016), which is why comparing them to the more traditional methods may be helpful. As a result, in this section, the methods of affecting impulse buying in offline stores will be considered to compare them to those available for online shopping applications.
The general strategies that are described above, including various pricing policies, advertisements, and the product itself are applicable to offline stores. However, researchers point out that brick-and-mortar stores have a very important advantage when prompting impulse buying: their buyers are physically present in the store, which provides multiple opportunities for enhancing their buying experience (Bhuvaneswari & Krishnan 2015; Su & Lu 2018).
Lin and Lo (2015) comment on the way different senses of buyers can be affected: a store can be decorated and scented, and music can also be used. In addition, the layout and displays of goods can be made appealing and supportive of cross-selling, which cannot be achieved in online stores (Bhuvaneswari & Krishnan 2015).
The environment of a store is very important for impulse buying; sensory stimulation, especially overstimulation, can suppress ones self-regulation (Bhuvaneswari & Krishnan 2015; Lin & Lo 2015; Su & Lu 2018). The ability to touch a product was also described as helpful in promoting spontaneous purchases (Bhuvaneswari & Krishnan 2015). All these factors are not an option for online applications.
The location of a store can also be significant for impulse buying as one of the situational factors of a purchase. In other words, a convenient location makes a person more likely to enter a shop, browse the goods and decide to make a purchase. In addition, it should be noted that the use of technology in offline stores can be helpful; for example, it may be employed to facilitate transactions or provide entertainment (Bhuvaneswari & Krishnan 2015). Finally, the suggestions of salespeople can result in spontaneous buying (Bhuvaneswari & Krishnan 2015). To summarise, there is a number of impulse buying promotion strategies that are available for offline stores.
Online Stores Affecting Impulse Buying Behaviour
Having reviewed the methods employed by offline stores to promote impulse buying, it is necessary to consider online stores and their ability to achieve the same outcome. Here, it should be mentioned that online shopping applications do not receive much coverage in recent research.
However, mobile shopping, which includes shopping applications and e-commerce, which is a more general term, are sufficiently represented. In fact, there is some research dedicated to the comparison of online and offline stores and impulse buying in them, but it does not specifically focus on shopping applications (Bhuvaneswari & Krishnan 2015). Still, this information is mostly applicable and will be used for this section.
In general, the above-presented marketing approaches to impulse buying promotion are applicable to online shopping. In other words, factors like advertising or limited-time offers are important stimuli for online applications (Bues et al. 2017). However, several online-specific concerns should be reviewed. According to recent literature, the design of applications and websites appears to be of utmost importance.
For example, there is some evidence which indicates that the quality of the website and its ease of use (especially navigation) can contribute to impulse buying (Akram et al. 2018; Chen, Su & Widjaja 2016; Lin & Lo 2015; Rezaei et al. 2016; Turkyilmaz, Erdem & Uslu 2015; Wu, Chen & Chiu 2016). Perceived convenience, as well as control, in working with an online shop has been proven to have an impact on impulse buying (Lee, Park & Jun 2014), and this outcome can be achieved through careful design of an application.
Thus, as pointed out by Lin and Lo (2015), since online stores are unlikely to be able to affect any sense other than the visual one, it is particularly important to develop a pleasing website design with the help of pictures, colour, and fonts. The more vividly and interactively a product is presented, the greater the possibility of impulse buying becomes (Vonkeman, Verhagen & Dolen 2017). In summary, the visuals of online applications are a major tool in fostering impulse buying.
The quality of the information provided by a site is also important. It needs to be relevant, easy to understand, useful and complete (Chen, Su & Widjaja 2016; Lee 2018). Recommendation features should be considered, as well.
For instance, a study that was dedicated to Facebook and carried out by Chen, Su and Widjaja (2016) demonstrated that Likes may affect impulse buying. This finding can be extended to other forms of approval and recommendation since the latter tend to boost spontaneous purchasing as well (Husnain et al. 2016; Zhang et al. 2018). Other examples can include the opportunity to write reviews of bought products and rate them; also, the electronic word-of-mouth is an important stimulus.
While offline shops have the opportunity to modify their environment, online shops also have a feature that can potentially improve impulse buying. In particular, online stores are more convenient: online buyers do not spend any time to get to the shop, and they can make a purchase at any time of day and night, although, admittedly, the delivery will consume some time (Chan, Cheung & Lee 2017). Given that prolonged browsing results in increased chases of impulse buying (Zhang et al. 2018), this advantage is very important.
On the other hand, the literature suggests that in some instances, online stores can benefit from mimicking offline ones. For instance, Ju and Ahn (2016) and Xiang et al. (2016) demonstrate the fact that social commerce sites can become similar to offline stores due to social presence, which enables the feeling of shopping together that is beneficial for improved experience and impulse buying. Also, Ju and Ahn (2016) note that music can be used in online stores; this way, they will be able to affect more than just the visual sense of a buyer. To summarise, despite the lack of some opportunities that are available to offline stores, online ones have their own advantages.
Methodology
During the process of designing the study, the research questions were used as a guide for determining the methods that could potentially achieve the aims of this dissertation. Given the fact that the research was intended to both determine a relationship and investigate it, it was apparent that a mixed-methods approach would fit it best. The following sections will present the different aspects of the research and explain their connection to the research questions of this dissertation.
Research Paradigm
When establishing a research paradigm for the dissertation, a perspective that would be applicable to the studys aims was found. A critical realism paradigm is an approach that incorporates the general ideas of both positivism and constructionism, allowing for a middle-ground point between the two (Eriksson & Kovalainen 2016). According to positivism, objective reality does exist, and it can be both observed and measured, which fits this studys aim of investigating the relationship between online shopping and impulse buying.
However, positivism does not account for the subjective aspects of observation, which makes this approach rather one-sided. On the other hand, constructionism recognises the significance of the subjective perspective of humans and points out the fact that knowledge is socially constructed, which highlights the impact that subjectivity can have on our perceptions.
Critical realism unites the two ideas and postulates both the existence of objective reality and the impact that the social construction of reality has on human knowledge. The convenience of this middle-ground perspective is pointed out by Eriksson and Kovalainen (2016): the authors note that due to its duality, critical realism can support and guide mixed methods designs. As a result, the present dissertation uses this approach, and it will be applied to the methods described below.
A Summary of the Methodology: Data Collection, Sample and Analysis
The methods employed in this dissertation included surveys and interviews. The former was used to test the presence of a relationship between online shopping applications and impulse buying and to gather more data about the way impulse buying is influenced by online and offline shopping experiences. The latter were mostly used to explore the studied phenomena. The surveys were developed with the help of the Survey Monkey service, and the interviews were carried out in person with the interviewees determining the settings of the meetings.
Data analysis employed methods that fit the data studied. Thus, quantitative data were processed using statistical analyses, and qualitative data presupposed thematic analysis (Creswell & Creswell 2017; Hair et al. 2015; Heeringa, West & Berglund 2017). Specifically, to summarise the majority of the findings of the survey, the descriptive statistics produced by the Survey Monkey were included in the research.
However, the analysis of the first part of the survey required establishing the relationship between the two variables, which is why, for this task, the Mann-Whitney U test was used. Due to the specifics of the sample (which was rather small) and data (which was not normally distributed), as well as the goal of the analysis (which consisted of determining if there was a relationship between the two variables), the choice of the test was justified (Momeni, Pincus & Libien 2017). This part of the analysis used SPSS. In addition, some of the graphs were created with the help of MS Excel.
Recruitment methods can be defined as quota and convenience sampling. The recruitment was done using online methods: Survey Monkey and social media were employed to invite people to participate in the surveys. The researcher also visited some of the stores, the brick-and-mortar versions of which were located in close proximity, for interviews. The quotas were established for the interviews and eventually had to be used for the first part of the survey.
Admittedly, convenience sampling has its limitations; specifically, it is a nonprobability approach, which makes the sample less likely to be representative (Benzo, Mohsen & Fourali 2017; Creswell & Creswell 2017). However, the use of this method is explained by the studys time constraints, and this limitation will be taken into account when interpreting the results of the research.
Eventually, three different samples were recruited for the different parts of the study. The first survey (or the first part of the survey) needed the people who used only online applications or only brick-and-mortar stores for their purchases. As it was anticipated, it was not very easy to find the people who would only employ one of the two approaches. Eventually, 37 exclusively online shoppers filled out the surveys, and this number was used to determine the quota for the offline ones; only the first 37 offline buyers were included in the investigation.
For the second survey, only the time constraints determined the sample. At the end of the investigation (that is, by the time the data were extracted and analysed), 1030 people had completed the survey. Therefore, no specific quota was proposed for this part of the study. However, the interviews had a quota that was introduced to fit the time constraints of the research and ensure that enough time was available for completing data analysis. Specifically, 10 experts who were the first to respond to the researcher were recruited for the study as it was initially planned.
In addition, it was initially planned to recruit five online and five offline buyers for interviews, but only two offline and one online buyer agreed to participate. As a result, seven additional buyers were recruited who made their purchases both online and offline. To summarise, the present dissertation reports the results of a mixed-methods study that surveyed a total of 1104 participants and interviewed 20 more people.
First Part of the Survey: Quantitative Methods and Gathering the Data
The quantitative methods of research have multiple applications, but a very common one is the testing of the presence or absence of any relationships between variables (Creswell & Creswell 2017). Given the fact that the first question of this study consists of testing a relationship, this dissertation needs to use quantitative methods. Specifically, surveys were employed to this end. With the help of surveys, the study gathered quantitative data that could be used to answer the first research questions.
A survey is a self-report tool that offers respondents to consider a set of questions with responses (Eriksson & Kovalainen 2016; Hair et al. 2015). Surveys are a commonly used quantitative method of data collection (Creswell & Creswell 2017), which is typically employed to draw inferences from a population. Web-surveys are also becoming increasingly popular; they are more convenient than paper surveys from multiple perspectives, including relative accessibility and simplicity in conducting and data extracting (Bryman & Bell 2015). Thus, the use of this method in this dissertation is justified.
The survey that was used in this study can be found in Appendix A under the section Online/Offline Users. As can be seen from the data collection tool, in it, the independent variable consisted of using or not using online shopping applications.
The dependent variable (impulse buying) was measured with the help of frequency (from never to always using a 5-point Likert scale), which means that the tool employed an ordinal scale for it. Thus, this part of the research was based on the idea that objective reality can be measured (Eriksson & Kovalainen 2016). This way, the use of online applications and impulse buying was prepared for checking if a relationship between them could be found.
The primary limitation of this part of the research is its sample. The study found that it was difficult to recruit the people who were exclusive in their use of online shops. Apparently, this approach to shopping has not become sufficiently common to completely substitute brick-and-mortar stores for the population that the researcher could contact. As a result, the total sample of the survey amounts to 74 people.
Given that the data were tested for statistical differences in the means of the responses using a test that could be applied to small samples, the results should still be relevant. However, the sample is very small, which means that additional research with other samples that can be gathered from particular populations would be required for conclusive statements on the topic.
Second Part of the Survey: Additional Data
In addition to the data that were meant to test the relationship between the two variables, the survey sought
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