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Master thesis
Whether and how does customer behavior varies between
conventional online and mobile-online channels?
The effect of customer characteristics and expected benefit and cost on the usage of conventional online and mobile-online channels
Author: Elisa Tjan
Student number: 10677291
University of Amsterdam
Faculty of Economics and Business MSc. Business Studies – Marketing Track
Supervisor: Dr. U. Konuş Second assessor: E. Korkmaz Date of submission: June 27, 2014 Version: final version
- 2 - Abstract
Consumers nowadays are facing an expanding range of online shopping channels due to technological developments. Prior studies have mainly examined the variation in consumer behavior between using traditional offline and online channels. However, consumers can also show different behavior when using different online channels such as the computer, smart phone or tablet devices. Therefore, this study investigates whether and how customer behavior varies between using conventional online (i.e. computer) and mobile-online (i.e. mobile devices) channels by conducting a quantitative cross-sectional survey among 225 online consumers. The results reveal that online channel usage is affected by consumers’ demographic and psychographic characteristics and expected benefit and cost factors. More specifically, it was found that consumers show different shopping patterns when using computers, smart phones or tablets. Conventional online channel users are mostly young male and female consumers who are little influenced by their level of innovativeness, have moderate expectations of the computers’ information availability and are less concerned about security issues when using the conventional online channel. On the other hand, the results indicate that mobile-online channel users are generally middle-aged female consumers who are highly innovative, have high expectations of the information availability of mobile-online channels and are less influenced by security barriers of these channels. The current research has several managerial implications that are presented at the end of the research along with the limitations and suggestions for further research.
Keywords: online shopping, online channel usage, consumer behavior, conventional online channel, mobile-online channels.
3 TABLE OF CONTENTS
1. Introduction 5
2. Literature review 9
2.1 Online shopping and its development 9
2.2 Online shopping channels and its key differences 10
2.2.1 Conventional online channels 11
2.2.2 Mobile-online channels 11
2.2.2 Differences between conventional online and mobile-online channels 12
2.3 Online channel usage 15
2.4 Factors that influence the online channel usage 16
2.4.1 Demographic factors 16
2.4.2 Psychographic factors 19
2.4.3 Expected benefit and cost factors 22
2.5 Hypotheses 25 2.6 Conceptual framework 26 3. Research method 29 3.1 Research design 29 3.2 Data collection 30 3.2.1 Self-mediated questionnaire 30 3.2.2 Sample selection 31 3.2.3 Research sample 32 3.3 Variable measurements 33 4. Results 35
4.1 Quality of the data 35
4.2 Descriptive statistics 35 4.3 Reliability analysis 39 4.4 Hypotheses testing 40 4.4.1 Hypothesis 1 40 4.4.2 Hypothesis 2 42 4.4.3 Hypothesis 3 43
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4.4.4 Hypothesis 4 44
4.4.5 Hypothesis 5 45
4.4.6 Hypothesis 6 46
4.4.7 Hypothesis 7 48
5. Discussion and conclusions 50
5.1 Findings 50
5.2 Managerial implications 53
5.3 Limitations and further research 54
References 56
Appendices
I: Questionnaire items 65
II: Questionnaire survey 66
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1. INTRODUCTION
Over the past decade, the emergence of online shopping channels has increased tremendously, outperforming most traditional offline retail stores such as brick-and-mortar stores (ComScore, 2009; Frost & Sullivan, 2014). Electronic commerce sales have increased 16.9% in 2013 to reach $263.3 billion (see Figure 1.1) (eMarketer, 2014a). Since online shopping provides numerous advantages for consumers that are not quite available in offline shopping channels, more and more consumers are moving towards online platforms (Teo, 2006). This has led to greater interests among researchers and practitioners. Within the online shopping context, consumers are also facing an expanding range of shopping channels. One of the latest forms of online channel that has risen due to technological developments is the mobile-online channel, where consumers use their mobile devices (i.e., smart phone or tablet pc) to make purchases (San Martin-Gutierrez, 2012).
Mobile-online shopping has an increasing share of the online retail sales (eMarketer, 2014a). This is based on several facts. First, a study by ComScore (2012) reports that 4 out of 5 consumers use their smart phone for online shopping. Second, eMarketer (2014a) notes that mobile commerce sales increased 70% to hit $42.1 billion in 2013 (see Figure 1.2). It is also estimated that this growth will continue to increase in 2014 with another 37.2% to $57.8 billion (eMarketer, 2014a). Third, mobile commerce revenue grew 24% during the second quarter of 2013, while the electronic commerce grew only 16% (ComScore, 2013). Based on these numbers, it can be said that the usage of mobile-online channels is increasing and it is driving faster growth than conventional online channels where consumers purchase via their desktop or laptop computer.
Figure 1.1: US Retail Ecommerce Sales (2012-2018)
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Figure 1.2: US Retail Mcommerce Sales (2012-2018)
Source: eMarketer, 2014a.
Many online retailers are responding well to the mobile-online consumers (eMarketer, 2014b). For example, 74% of the retailers have mobile-optimized Web sites to increase the online shopping experience of customers (eMarketer, 2014b). In addition, retailers are also using mobile applications to personalize the consumer’s shopping experience by providing customized offers, product and price information, and discounts (Makwana and Rahaman, 2013).
In the marketing literature, many studies have been devoted to understanding the differences in customer behavior between offline and online shopping channels (Chiang and Dhokalia, 2003; Armesh et al., 2010; Zuroni and Goh, 2012). However, customers may also show different characteristics when using conventional online and mobile-online channels. For example, conventional online channel users are generally highly educated male consumers, while mobile-online channel users are young, and less educated (Bigne et al., 2007; Zhang and Yuan, 2002). Moreover, interactions with customers also vary between conventional online and mobile-online channels. For instance, retailers usually communicate with conventional online customers via Web sites, while mobile-online customers can be reached via multiple ways such as Web sites, mobile-optimized versions of the Web sites or mobile applications (Rishi, 2012).
It is particularly important for researchers and managers to understand the differences in customer behavior between using various online channels for several reasons. First, conventional online and mobile-online channels have unique characteristics and thus they cannot be considered from a general online channeling perspective. For example, ubiquity is a unique characteristic of mobile-online channels which conventional online channel does not necessarily have (Ozok and Wei, 2010). In addition, retailers need to address this carefully, since interactions with customers via mobile applications is different from interactions via Web sites. For instance, mobile applications generally provide more simple and short
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information to customers while Web sites provide rich information about products or services (Zhang and Yuan, 2002). Second, understanding the differences between using various online shopping channels will assist managers segmenting the conventional online and mobile-online customers based on their characteristics. By doing so, managers will be able to understand who the conventional online and mobile-online customers are in order to anticipate their needs in the best possible way. Third, recognizing these differences is essential in helping retailers to create and manage their online strategies better by improving their conventional online and mobile-online offerings to attract consumers (Teo and Young, 2003). For example, if male consumers tend to have a higher usage rate of mobile-online channels than female consumers, retailers will need to pay more attention on offering male-oriented products and services via mobile-online channels to target the segment of male online shoppers in order to realize a higher turnover and greater revenue. Last, managers should also consider how expected benefits and costs of using the online channels might vary. Understanding these benefits and costs is relevant because these factors may motivate or deter customers to shop via either conventional online or mobile-online channels. Moreover, it enables managers to focus on increasing the perceived benefits or minimizing the perceived costs in the online channels. Imagine that mobile-online consumers show a higher level of security concerns than conventional online consumers. Proof of such behavior would imply that managers should emphasize lowering the perceived security and risks concerns or increasing the benefits in a mobile-online channel.
Considering the aforementioned, this study focuses on gaining deeper insight into whether and how customer behavior varies between using conventional online (i.e., desktop or laptop computer) and mobile-online (i.e., smart phones and tablet devices) channels. The objective of this study is to investigate the effect of consumer characteristics and expected benefits and cost on the usage of conventional online and mobile-online shopping channels. In addition, it aims to extend the current knowledge of customer behavior in the online shopping context and therefore contribute to the field of the marketing literature.
The current research provides several theoretical and managerial contributions. First, it thoroughly investigates the relations of consumers’ demographic and psychographic characteristics and expected benefit and cost with the usage of conventional online as well as mobile-online channels. Prior research has considered the usage of conventional online shopping channel, but research on the influence of customer behavior on the usage of mobile-online channels remains scarce (Kushwaha and Shankar, 2013). Second, previous studies were also mainly concerned with how customer behavior differs between using offline and
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online shopping channels, while little research has been done about how customer behavior could vary between using various online shopping channels. The current study takes this into account. Third, the findings of this study can help online retailers to identify their conventional online and mobile-online customers based on demographic and psychographic characteristics and expected benefits and costs. Fourth, this study can assist retailers in better designing their online channeling strategies by showing which consumers’ attributes are important in the online channel environment. Retailers can thereby improve their conventional online and mobile-online offerings. To conclude, this study builds on previous research, adds new knowledge to the literature about online consumer behavior and fills a research gap in the online shopping context.
The remainder of this research is structured as follows. Chapter two provides the literature review on online shopping channels, online channel usage and factors that influence the online channel usage. The chapter ends with the conceptual framework. In chapter three the research methodology is explained. Subsequently, chapter four presents the results of this research. Finally, in chapter five the discussion and conclusions will be outlined, including the implications of the findings, limitations, and indications for further research.
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2. LITERATURE REVIEW
This chapter provides an overview of the existing literature on online shopping. First, current theory on online shopping and its development is explained. Second, the forms of online shopping channels and their key differences will be discussed. Third, the online channel usage by consumers is presented. Fourth, the factors that influence the online channel usage will be outlined. The chapter ends with presenting a table of the hypotheses and the conceptual framework.
2.1 Online shopping and its development
Historically, retailers have engaged with their customers exclusively through traditional offline channels, such as brick-and-mortar stores, television, radio, and print (Bradley et al., 2007). These offline, physical channels are not connected to the World Wide Web. Due to advances in technology, the traditional offline retail stores now have to compete with non-offline format retail stores. The Internet commerce has become one of the most powerful tools with which businesses and consumers to interact, since it provides numerous of benefits to both parties (Teo, 2006). It is an essential tool for businesses, as it can reduce supply chain costs, reach new potential customers in new segments, and allow companies to create unlimited store space virtually compared to traditional offline stores (Teo and Yeong, 2003). Additionally, the Internet offers many benefits to consumers in terms of time and costs efficiency, choices, price comparisons, and avoidance of queues (Teo, 2006). Thus, the Internet as a new medium for online shopping has gained increasing attention among researchers and practitioners (Bourlakis et al., 2008; Malik and Guptha, 2013).
Online shopping is defined as the process through which a customer purchases products or services over the Internet (Malik and Guptha, 2013; Monsuwé et al., 2004). Other studies have looked at online shopping from the perspective in which a computer (i.e., desktop or laptop) is used as a channel to purchase online (Zuroni and Goh, 2012; Suki, 2013). However, this is not necessarily always the case, as unprecedented technological development has enabled customers to purchase online using mobile devices, such as smart phones and tablets (Kumar and Mukherjee, 2013). Therefore within the context of this study, online shopping refers only to the process through which a customer purchases products or services over the Internet.
Over the past few years, online shopping has grown tremendously. In 2011, online retail sales in the United Kingdom increased 14% to over £50 billion, and this growth is expected to continue (The Guardian, 2012). eMarketer (2012) notes that online retail sales
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will increase from $225.5 billion in 2012 to $434.2 billion in 2017. Similarly, Forrester Research (2013) predicts that online sales will increase at an annual rate of 10% from 2012 to 2017. This rapid growth has had several consequences. First, it has attracted a lot of attention from researchers and practitioners due to the emergence of online shopping as a new marketing channel (Malik and Guptha, 2013). Second, it has led many retailers moving their traditional offline offerings to online platforms, making brick and mortar stores becoming obsolete (Frambach et al., 2007). Third, the growth of online retailing has enabled businesses to reach customers that otherwise could not be reached (Malik and Guptha, 2013).
While it is clear that online shopping shows great potential for businesses, it is necessary for managers to know their online customers well in order to anticipate their needs. Managers should understand who their potential customers are and how they purchase online. Therefore it is essential to first make a distinction between the different types of online shopping channels. The following paragraph will pay more attention to this matter.
2.2 Online shopping channels
Over the past few decades, the evolution of the Internet as a new marketing medium has become a worldwide phenomenon (Ganguly et al., 2010). The growing number of households that possess a computer and easy access to the Internet has made customers widely accept electronic commerce (Ganguly et al., 2010). Therefore, retailers have increasingly used it as a marketing tool to reach their customers through many different online shopping channels (Karim, 2011). Before discussing the online shopping channels, an overview of the channels is presented in table 2.1.
Table 2.1
Overview of the channels
Channels Definitions Examples
Traditional offline channels Physical channels that are not connected to the World Wide Web.
Brick-and-mortar, catalogs, brochures, flyers, radio, television.
Conventional online channel Channel used for purchasing products or services through the Internet using desktop or laptop computer.
Desktop computer, laptop computer.
Mobile-online channels Channel used for purchasing products or services through the Internet or mobile applications using wireless handheld devices.
Personal Digital Assistant Smart phones, tablet devices.
11 2.2.1 Conventional online channels
Customers have historically purchased online exclusively through conventional online
channels, where they use their desktop or laptop computers to shop online (Zuroni and Goh,
2012; Suki, 2013). Prior studies show that consumers use conventional online channel for different shopping purposes. They use it either for browsing information about products or services or for online transactions (Verhoef et al., 2007; Kumar and Venkatesan, 2005; Frambach et al., 2007; Mahmood et al., 2004).
Within the context of this research, conventional online channel will refer to the channel (i.e. desktop or laptop computer) used by customers to purchase products or services over the Internet.
2.2.2 Mobile-online channels
Due to the rapid growth of electronic commerce, customers are no longer restricted to shopping solely through conventional online channels. Technological emergence has enabled them to purchase via mobile-online channels. A mobile-online channel is defined as shopping for consumer goods and services using an Internet-enabled cell phone (i.e., smart phone), tablets or Personal Digital Assistant (PDA), independent of a desktop or laptop computer and a hard-wired Internet connection (Ozok and Wei, 2010; Kumar and Mukherjee, 2013; Tiwari et al., 2006; Thakur, 2013).
According to Bang et al. (2013), the mobile-online channel is increasing as a new electronic commerce venue. In 2011, 91% of the online retailers in the United States have developed a mobile strategy, compared to 74% in 2010 (Shop.org/Forrester Research, 2011). More specifically, 48% of the retailers have a mobile optimized website, 35% have developed an iPhone application, and respectively, 15% offer an Android application and an iPad application (Shop.org/Forrester Research, 2011). From the consumers’ perspective, Google Shopper Marketing Agency Council claims that 79% of the smart phone owners use their mobile phone for shopping (News 24, 2013). Internet retailer (2013) states that consumers spend more time using smart phones and tablet devices when interacting with online retailers than using desktop or laptop computers. Therefore, it can be said that the mobile-online commerce is rapidly emerging.
However, it must be noted that the mobile-online channel does not necessarily replace the conventional-online channel, Rather, it can be seen as a supplement to electronic commerce (Malik et al., 2013). For example, the mobile-online channel can increase the searching ability of consumers by providing them the possibility of having access to online
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stores anytime and anywhere they want. This may cause additional purchases on the online channels (Malik et al., 2013). On the other hand, the mobile-online channel can also be seen as a substitution of the conventional online channel (Bang et al., 2013). For instance, introducing the mobile-online channel may provide customers an alternative for purchasing products or services that they would normally purchase through the conventional online channel. This will lead to substitution of the conventional online channel.
2.2.2 Differences between conventional online and mobile-online channels
Although mobile-online channels can be seen as either supplements or substitutions of the conventional online channels, they have some fundamental differences. It is essential for managers to understand these differences between conventional online and mobile-online channels for several reasons. First, conventional online as well as mobile-online channels have unique, differentiating characteristics and functions, and thus it cannot be examined from a general online channeling perspective (Makwana and Rahaman, 2013). Second, consumers who shop online with their mobile phone do not shop in the same way as they do with their computer (Zhang and Yuan, 2002). They might show different behavior across different online channels. Third, distinguishing the online channels will help manager to develop their business strategies. Knowing these differences can help them to identify what is and is not suitable in a conventional online and mobile-online channel to target their customers (Zhang and Yuan, 2002). Fourth, it contributes to a deeper understanding of the drivers of adopting the conventional online and mobile-online shopping channels. Table 2.1 displays the key differences between conventional online and mobile-online channels that are identified in prior studies.
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Table 2.1
Key differences between conventional online channels and mobile-online channels
Dimension Conventional online channels
Mobile-online channels Sources
Mobility Not mobile, fixed location. Ubiquitous. Ozok and Wei, 2010; Makwana and Rahaman, 2013.
Personalization Limited: only inferences of consumer’s preferences
Widely: consumer’s revealed preferences and location-based services
Kats, 2012; eMarketer, 2014c.
Transactions Internet browsers and constraint to Internet connection
Internet browsers and mobile applications (wirelessly)
Rishi, 2012
Customer base Men and women, less income
Women, high income and education.
Smith, 2014; Farago, 2012.
Perceived usability High usability Low usability. Ozok and Wei, 2010.
Mobility. One of the greatest benefits of mobile-online channel over conventional
online channel is mobility (Ozok and Wei, 2010). Mobility is defined as the ability to initiate online transactions at any desired time (Ozok and Wei, 2010). The mobility of mobile-online channels enables retailers to reach their customers anywhere and anytime they want regardless of their locations. In addition, retailers can reach these customers even faster compared to conventional online channel users, since people might not always carry a computer with them, while they will most likely have their smart phones with them. Mobile-online consumers are also not constrained by their location to purchase products or services, whereas conventional online consumers are limited to make transactions from locations with Internet accessibility (Makwana and Rahaman, 2013). Therefore, mobility creates a certain value for time-critical and location sensitive situations for consumers (Makwana and Rahaman, 2013).
Personalization. Another advantage of mobile-online channels over conventional
online channel is personalization. Personalization is defined as creating services that customizes the consumer’s experience to his or her needs (Shi, 2004). Although personalization can be done in e-commerce, it goes further and deeper in m-commerce (Kats, 2012). For example, mobile-online retailers can use consumer’s revealed preferences and location-based services (LBS) to provide tailor-made offerings (eMarketer, 2014c). In addition, personalization is of great importance in the mobile-online environment, since
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providing consumers with a customized experience that gives them what they want and need is more important than getting them to purchase a product or service (Kats, 2012). Mobile-online consumers want relevant and targeted information (Kats, 2012). For this reason, retailers need to focus more on personalizing in order to better reach their audience.
Transactions. In the context of online shopping, purchases can be conducted via
several ways. Purchases made through conventional online channels are usually done via Internet browsers where consumers visit online web stores using their computer and are thus constrained to having Internet access. This often differs considerably from mobile-online channels, where purchases can be conducted wirelessly via Internet browsers (i.e., visiting a computer version of the online stores) or via mobile applications. Mobile applications or mobile apps are software applications specially designed for smart phones, tablets, or PDAs, since they use a lighter version of computer applications (Rishi, 2012). Mobile applications often require customers to have installed the software application before being able to purchase a product or service. Conventional online channels do not face these issues.
Customer base. Customers who use conventional online channels differ from the
customers who use mobile-online channels. A report by BI Intelligence examined the demographic characteristics of conventional online shoppers by their gender, age, and income (Smith, 2014). The findings of the report show that conventional online channel users are male as well as female consumers, aged between 18 and 34, with a lower level of income than older adults (Business Insider, 2014). On the other hand, mobile-online channel users are generally women, between the ages of 25 and 34 years old, with a higher level of income and education (Farago, 2012).
Perceived usability. The perceived usability of online shopping channels refers to
consumer perceptions of functions such as browsing processes and transaction procedures in terms of their convenience (Ozok and Wei, 2010). The perceived usability of consumers is essential for determining what consumers find important in a conventional online or mobile-online channel to create a more compelling mobile-online experience. The difference is that consumers perceive low usability in the usage of mobile-online channel compared to the usage of conventional online channel (Ozok and Wei, 2010). This might be due to interface limitations of the mobile-online channel, such as bandwidth allocations, limited regulation, and relatively high fees associated with the mobile Internet services (Ozok and Wei, 2010). Therefore retailers are challenged to investigate the cost and speed issues of mobile devices.
15 2.3 Online channel usage
As consumers have a variety of choices of using online shopping channels, the tendency increases to examine the differences in shopping usage between conventional online and mobile-online channels, since different channels most likely have specific characteristics. Although prior studies have examined how channel usage varies between traditional offline and online channels, little research has been done in investigating how channel usage varies between conventional online and mobile-online channels. It is crucial for managers to identify their customers’ shopping usage of the online channels for at least three reasons. First, understanding the online channel usage will provide retailers with extensive information to help them create and manage their channel strategy effectively (Verhoef et al., 2007). Second, identifying the online channel usage may develop and enhance customer relationship (Gensler et al., 2011). Third, it is also useful for predicting the future shopping behavior of consumers through the online channels (Seock and Yu, 2007).
Prior study shows that consumers generally purchase online using computer about once a month or less than once per month (Teo, 2006). The majority of consumers purchase about 1 to 3 items in six months (Teo, 2006). On the other hand, purchases through mobile-online channels are relatively frequent. About 40% of US and UK customers reveal that they purchase via their mobile phones on a monthly basis, and additionally about 40% of the customers make purchases at least once a week using their mobile device (MC Saatchi, 2013). The average purchase amount using mobile-online channels is about 10 items per year (Ipsos, 2011).
The findings from a Dutch market research by Thuiswinkel.org show that more and more consumers are using mobile-online channels for shopping purposes (Nu.nl, 2014). In 2013, consumers spent €1.3 billion on purchases using their mobile devices, while in 2012, they spent €560 million. In addition, most of these purchases were made using a tablet device (Nu.nl, 2014). Consumers are also spending a greater amount of money using mobile devices and it is expected that this will continue to grow (Nu.nl, 2014). In this sense, consumers are increasingly using mobile-online channels to purchase products and services. This might be due to the prevalence and ubiquity of mobile devices (Bang et al., 2013). Even though consumers are spending more money on mobile-online channels, it should be noted that mobile-online channels are associated with several constraints, such as small screen size, inconsistent Internet access, and slow and inconvenient mobile web stores (Kumar and Mukherjee, 2013). This can lead to opposite findings where consumers may favor using conventional online channel over using mobile-online channels.
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To conclude, the aforementioned findings indicate that online channel usage is greater for mobile-online than conventional online channels, in the sense that mobile-online consumers purchase relatively more frequently, a greater amount of products and services, and spending a larger amount of money than conventional online consumers.
2.4 Factors that influence the online channel usage
Prior studies pointed out that multiple factors play a role in influencing the online channel usage. For example, convenience compels consumers to shop online using computers because they find it essential to shop at home without having to spend time or energy traveling to brick-and-mortar stores (Chiang and Dhokalia, 2003). On the other hand, the compatibility of mobile-online channels has a significant influence on consumers’ usage of their mobile phones (Wu and Wang, 2005). This means that there are a variety of factors that influence the consumers’ online channel usage. However, little is known about whether or not and how these factors may differently influence the usage of conventional online and mobile-online channels. Consumers vary in their behaviors, preferences, and attitudes, and this may have different effects on their online channel usage (Neslin and Shankar, 2009; Ansari et al., 2008).
To examine whether and how different attributes of consumers influence their online channel usage, this study includes demographic and psychographic characteristics of consumers and expected benefit and cost that might lead to different patterns of the online channel usage. Segmenting the consumers based on these attributes is crucial for the success of electronic commerce in explaining the online shopping behavior of consumers (Berry, 1999). The following subparagraphs will provide a clearer explanation on the factors that influence the online channel usage.
2.4.1 Demographic factors
Consumer characteristics that are of great interest to researchers seeking to understand why consumers shop online include demographic factors (Monsuwe et al., 2004). The demographic factors of a customer may significantly influence his or her choice of channel (Kushwaha and Shankar, 2013). Prior studies have identified several demographic factors that are linked to the online shopping behavior of consumers (Bellman, 1999; Sin and Tse, 2008; Li and Zhang, 2002). More specifically, studies found that gender, age, level of education and income of customer determines his or her attitude towards online shopping (Hashim et al., 2009; Monsuwe et al., 2004; Sin and Tse, 2008).
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In contrast, the study by Bellman et al. (1999) stated that demographic factors do not seem to have a key influence on the online shopping behavior of consumers once they are familiar with using the Internet. Because the aforementioned study was conducted over ten years ago, this current study will incorporate the influence of gender and age on the usage of online shopping channels to see whether or not these factors have different effects on conventional online and mobile-online channels.
Gender
Many studies have been devoted to studying the relation between gender and online shopping behavior of consumers (Sin and Tse, 2008; Burkolter and Kluge, 2011; Bigne et al., 2005). Gender is overall used as a key variable for segmentation, and it is seen to have influence over the likelihood of consumers to purchase over the Internet. In this study, we expect that there is a difference in gender between using conventional online and mobile-online channels. A survey conducted on mobile-online shopping shows that conventional mobile-online channels are used almost equally by both males and females (Small Business Trends, 2013). 87% of male consumers, and respectively 82% of female consumers purchase via computer (Small Business Trends, 2013). However, prior studies reveal that men use conventional online channels for making purchases at a higher rate than women (Sin and Tse, 2008; Bigne et al., 2005). The study by Sin and Tse (2008) reveals that conventional online consumers consist of 66.7% male and 33.3% female consumers. This could be explained by the fact that female consumers perceive a higher level of risk in purchasing online and they are less interested in the Internet and thus spend less time online than male consumers do (Garbarino and Strahilevitz, 2004). Therefore, we expect that male consumers will have a higher usage rate of the conventional online channel than female consumers have.
On the other hand, when looking at the relation between gender and usage of mobile devices, findings are different from the conventional online channel usage. Women are inclined to spend more money on mobile apps that are not games compared to men (Lewis, 2013). Additionally, Marketing Charts (2013) states that women are more likely to purchase using tablet devices than men. There are numerous explanations for these findings. First, women are open to mobile marketing and eager to explore shopping using mobile devices (O’dell, 2010). Further, 85% of women use the mobile-online devices on a daily base and 70% of women expect to increase their mobile-online channel usage in the future (O’dell, 2010). Therefore, we assume that female consumers are more likely to use mobile-online channels than male consumers. Based on the aforementioned, it is expected that gender will
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differently affect the usage of conventional online and mobile-online channels, in the sense that men have a higher usage rate of conventional online channels than women, whereas women have a higher usage rate of mobile-online channels than men. Therefore, the following hypotheses are advanced:
H1a: Male consumers are more likely to use the conventional online channel than female consumers.
H1b: Female consumers are more likely to use the mobile-online channel than male consumers.
Age
The findings of prior studies regarding the relation between age and online shopping behavior have been inconsistent (Burkolter and Kluge, 2011; Cowart and Goldsmith, 2007; Zuroni and Goh, 2012). The study by Cowart and Goldsmith (2007) found that older consumers were more inclined to purchase online than younger consumers. Other research notes that there is a negative relation between age and online shopping behavior, which states that young consumers use the Internet more often to purchase online than middle-aged (40-64 years) consumers (Burkolter and Kluge, 2011). In addition, Joines et al. (2003) reveals that online shoppers are relatively young in age. This might be due to the fact that younger consumers generally have a more favorable attitude towards online shopping than middle-aged consumers (Cowart and Goldsmith, 2007). Thus, it is assumed that young consumers differ in their usage of conventional online channels from middle-aged consumers in the sense that they are more likely to use computers than middle-aged consumers.
In contrast, we expect that age will have a different impact on the mobile-online channel usage compared to conventional online channel usage. Several studies have been carried out to investigate the impact of age on consumers’ online shopping behavior via their mobile devices. It is found that middle-aged consumers are more prone to use mobile-online channels than young consumers. This is based on several findings. First, a survey among Swedish consumers by Payair reveals that mobile-online shopping seems to be more popular among middle-aged consumers than young consumers (Telecom paper, 2012). The age groups of 30 to 39 years and 40 to 49 years old have the highest interests in mobile-online shopping (Telecom paper, 2012). 28% of the 30 - 39 age group is interested in shopping with their mobile devices, followed by the age group of 40 - 49 years with 25% (Telecom paper, 2012). While on the other hand, only 22% of the people aged between 20 – 29 years and 3.5% of the people under 19 years old are interested in mobile-online shopping (Telecom
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paper, 2012). Second, mobile-online shopping is starting to play a bigger role in buying decisions of U.S. families (Barcode Discount, 2013). More specifically, middle-aged women are highly attracted to use mobile coupons for groceries which they can use in-stores (Barcode Discount, 2013). Third, a report by KPCB’s Partner reveals a surprising finding that middle-aged consumers are more likely to be mobile device addicts than teens (Khalaf, 2014). Therefore, it is expected that the age of consumers has a different impact on the usage of conventional online and mobile-online channels, in a way that young consumers have a higher usage rate of conventional online channel than middle-aged consumers, whereas middle-aged consumers have a higher usage rate of mobile-online channel than young consumers. The following hypotheses will be advanced:
H2a: Young consumers are more likely to use conventional online channels than middle-aged consumers.
H2b: Middle-aged consumers are more likely to use mobile-online channels than young consumers.
2.4.2 Psychographic factors
In the field of marketing, psychographic factors are attributes related to the personalities, values, attitudes, interests, opinions, or lifestyles of consumers (Ganguly et al., 2011). Prior studies have indicated that psychographic factors influence the shopping behavior of consumers and that consumers can be segmented based on these factors (Ziff, 1971; Tauber, 1972). Therefore, online retailers have used these attributes to communicate with their customers by developing customer profiles based on psychographic segmentation (Ganguly et al., 2011; Wu, 2003). This study focuses on three psychographic factors, namely shopping enjoyment, innovativeness and time consciousness of consumers.
Shopping enjoyment
According to Wong et al. (2012), shopping enjoyment is defined as consumer’s personality trait that finds shopping trips to be associated with great pleasure and enjoyable qualities. Shopping is a social process that is not only related to utilitarian shopping values, but also to hedonistic shopping values, such as fun, pleasure, and excitement (Liu and Forsythe, 2011). This study includes the psychographic factor of shopping enjoyment for several reasons. First, there is a lack of extant research on shopping enjoyment, and prior studies have examined this factor from a general shopping perspective and not from the online shopping point of view (Wong et al., 2012). Second, perceived shopping enjoyment is
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seen as a determinant contributing to the consumers’ loyalty and repurchase behavior (Wong et al., 2012). Third, hedonic shopping values (i.e. enjoyment) are more likely to contribute to online purchase intention than functional shopping values (i.e. usefulness) (Liu and Forsythe, 2011).
Prior studies find that shopping enjoyment is significantly and positively related to online shopping behavior (Liu and Forsythe, 2011; Seock and Bailey, 2008). In other words, consumers who perceive a high level of enjoyment when shopping online are more likely to purchase online. In the mobile-online context, perceived shopping enjoyment is the view that mobile technology offers fun and enjoyment to consumers when using mobile or tablet devices for shopping (Kumar and Mukherjee, 2013).
In the current study, we expect shopping enjoyment to be differently related to conventional online and mobile-online channel usage. It is assumed that shopping enjoyment is more positively associated with mobile-online channel usage than conventional online channel usage for several reasons. Smart phones and tablet devices have the ability to create a fun mobile atmosphere for consumers by using diverse media such as pictures, background music, and videos to create attractive and inventive mobile applications or web pages to reach them (Kumar and Mukherjee, 2013). When consumers perceive shopping through online channels as an enjoyable process, this will contribute to a higher usage rate of mobile-online channels. In addition, mobile-mobile-online channels have the advantage above conventional online channel of making mobile applications personal and convenient for consumers (Makwana and Rahaman, 2013). The ability to make personalized offerings is contributing to creating enjoyment for consumers (Pappas et al., 2011). With this said, personalized offerings in mobile-online channels have a positive influence on the degree of consumers’ shopping enjoyment and this in turn may lead to a higher usage rate of mobile-online channels. Therefore, we will advance the following hypothesis:
H3: Shopping enjoyment is more positively related to the usage of mobile-online channels than to the usage of conventional online channel.
Innovativeness
Innovativeness is defined as the degree to which a consumer prefers change, tries new and different products, and seeks new experiences (Hurt et al., 1977). Most studies view consumer innovativeness as a personality trait that differs among individuals (Khare et al., 2010; Goldsmith, 2002). Limited studies have examined the role of consumers’ innovativeness despite its importance, because it can influence the online purchase decisions
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of consumers (Limayem et al., 2000). Furthermore, prior studies have mainly examined the relation between consumer innovativeness and online shopping from a general perspective. They have not investigated whether consumer innovativeness is differently associated with the usage of conventional online and mobile-online channels.
The studies by Limayem et al. (2000) and Goldsmith (2002) investigated the influence of consumer innovativeness on online shopping behavior. The findings show that consumer innovativeness is positively related to the online shopping behavior of consumers through the Internet. This means that consumers with a high level of innovativeness have a higher tendency to purchase online than consumers with a low level of innovativeness. More specifically, innovative consumers purchase a greater amount of items than non-innovative consumers (Limayem et al., 2000). Additionally, in the current study we expect that consumer innovativeness is more positively related to mobile-online channel usage than to conventional online channel usage due to several reasons. First, in the context of business and marketing, consumer innovativeness is strongly related to adopting new technology, channels, products, or activities (Khare et al., 2010; Bigne-Alcaniz et al., 2008). Consumers with a high degree of innovation will most likely adopt new technologies (Bigne-Alcaniz et al., 2008). Given the fact that mobile-online shopping is a relatively new and innovative concept, it is expected to drive innovative consumers towards using mobile-online channels. While on the other hand, conventional online channel is not seen as a new technology, because it has been used as an online shopping channel for several years and thus it is unlikely that consumer innovativeness is highly positively related to conventional online channel. To conclude, building on previous studies, it is expected that consumer innovativeness is more positively associated with mobile-online channel usage than with conventional online channel usage. Therefore, the following hypothesis is advanced:
H4: Consumer innovativeness is more positively related to the usage of mobile-online channels than to the usage of conventional online channel.
Time consciousness
Time consciousness refers to the degree to which consumers are aware of the passing of time, and the tendency to perceive time as a scarce resource and therefore use it carefully (Kleijnen et al., 2007). Time consciousness is an important psychographic factor of consumers that needs to be considered when studying the online shopping context, because time is seen as the most precious and least replaceable asset of consumers and consumers have varying degrees of consciousness of how they spend their time (Kleijnen et al., 2007).
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The study by Chiang and Dholakia (2003) states that time consciousness is positively related to online shopping in the sense that time-conscious consumers are more likely to shop online than offline, due to its convenience of saving time spent at checkout lines and driving to stores. In contrast, another study found that online shopping is less associated with time consciousness of consumers than traditional offline shopping (Zhu et al., 2012). However this study has examined the time consciousness from another perspective; it saw time-consciousness as making shopping trips rapidly and not giving much thought before shopping, while the current study refers to time consciousness as using time wisely and seeing it as a scarce resource. This may have caused the inconsistency in the findings regarding time consciousness and online shopping.
In this study, it is expected that time consciousness has a different impact on mobile-online channel usage than on conventional mobile-online channel usage in the sense that time conscious consumers are more positively related to using mobile devices than computer. There are several reasons for this expectation. First, time conscious consumers will search for channels that offer them the opportunity to use their time efficiently (Kleijnen et al., 2007). Mobile-online channels offer this opportunity by enabling consumers to receive information and perform transactions anywhere and anytime regardless of their locations, which is not present in conventional online channels. Second, time-conscious consumers are more concerned with having the ability to control their time (Kleijnen et al., 2007). Mobile-online channels provide consumers the ability to control time by allowing them to have more flexibility when doing mobile transactions, while this is less present in conventional online channels (Kleijnen et al., 2007). Third, time-conscious consumers are more willing to consider or adopt “smarter” channels due to their service compatibility. Service compatibility in mobile-online channels may increase the productivity which might be important to time conscious consumers (Kleijnen et al., 2007). Based on these reasons, it is expected that time consciousness is more positively associated with the usage of mobile-online channels than with the usage of conventional online channels. Therefore, the hypothesis is as follows:
H5: Time consciousness of consumers is more positively related to the usage of mobile-online channels than to the usage of conventional online channel.
2.4.3 Expected benefit and cost factors
Online consumer behavior has been examined from the perspectives of consumer demographic and psychographic characteristics as mentioned above. Besides these consumer characteristics, this study also incorporates the expected benefit and cost factors of using
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online shopping channels, because they provide more diagnostic information about the consumers than the demographic and psychographic factors do, which is vital in understanding the behavior and needs of consumers in the online channel usage (Bhatnagar and Ghose, 2004a). The benefits of using the online shopping channels provide a certain degree of convenience to consumers that are not available in other channels, whereas costs are related to uncertainties that are involved in online shopping channels, such as perceived risks (Bhatnagar and Ghose, 2004b). These perceptions of expected benefits and costs about online shopping influence the consumers’ decision to use a particular online shopping channel (Zhou et al., 2007). For example, consumers may prefer to shop online using their mobile phones because it is expected to provide greater benefits than shopping online via computers due to its ubiquitous nature, or the ability to purchase products or services from anywhere desired. In this sense, the mobile-online channel has an essential characteristic that matches the personal needs of the consumer, which is ubiquity.
The current study focuses on the expected benefit of information availability and the expected cost of security concerns of the online channels, because these two factors are personally important to consumers when shopping online and thus, it may differently influence the online channel usage of consumers (Bhatnagar and Ghose, 2004a).
Information availability
Verhoef et al. (2007) defines information availability as the consumers’ perception of the quality, quantity, accessibility of information, and the ability to compare alternatives. Consumers perceive information availability as a functional benefit of online shopping channels for several reasons. First, the Internet is often considered a convenient platform for gathering information (Teo, 2006; Verhoef et al., 2007). Second, consumers expect the online shopping channels to offer them easy access and the ability to compare rich information about products and services with greater fluidity than traditional offline shopping channels (Lim and Dubinsky, 2004). This is because online shoppers are not physically restricted in the online shopping environment (Lim and Dubinsky, 2004). Third, information availability is an important determinant of customer satisfaction and the purchase intentions of customers (Thongpapanl and Ashraf, 2011). This means that the information availability of a Web store is of great importance for potential online consumers. For these reasons, this study includes the benefit factor information accessibility.
Although there are limited empirical studies about the relation between information availability and mobile-online channel usage, in this study we expect information availability
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to have a different impact on conventional online and mobile-online channel usage due to several reasons. First, mobile-online channels impose certain constraints on information accessibility and availability compared to conventional online channels (Bang et al., 2013). Mobile phones and tablet devices have smaller screens, lower usability, and lower bandwidth compared to desktop and laptop computers, which makes it less convenient to access the information that is available through the channel (Bang et al., 2013). Further, retailers communicate with their consumers via mobile-online channels in a relatively interactive and effective way by providing simple and short information through mobile applications or mobile-optimized Web sites (Lamarre et al., 2012). However, consumers who want to collect more detailed information or compare multiple products might be reluctant to do these tasks on mobile devices. While on the other hand, web browsing via conventional online channel provides easy access to rich information about products and services and facilitates product comparisons (Bang et al., 2013). In this way, consumers that use their computer to shop online have the ability to make more informed decisions. Accordingly, we propose that the consumers’ expected information availability of the online channel is more positively related to conventional online channel usage than to mobile-online channel usage. The following hypothesis will be advanced:
H6: Expected information availability of the online channel is more positively related to conventional online channel usage than to mobile-online channel usage.
Security concerns
In the context of online shopping, security refers to issues that are dealing with the payment of transactions, online credit card security, and alternative payment options (Mohanty et al., 2007; Miyazaki and Fernandez, 2000). Security is one of the largest barriers for consumers using online channels (Ahuja et al., 2003; Teo, 2006; Kumar and Mukherjee, 2013) for numerous reasons. First, consumers are dealing with a larger amount of uncertainty when shopping via online channels than via traditional offline channels (i.e., brick-and-mortar stores). Second, consumers are usually faced with exposing personal and credit card information when shopping online. For this reason, they tend to be more careful when shopping online, having to examine the credibility of the retailer before making a purchase, for instance (Lim and Dubinsky, 2004). Third, consumers have major security concerns due to credit card frauds, privacy, risks of non-delivery, and so on (Mohanty et al., 2007). Based on the aforementioned, the security factor is an important aspect to examine, because it is an
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expected prime determinant for consumers to not use the online shopping channels (Teo, 2006).
In this study, it is presumed that expected security concerns is more negatively related to the usage of mobile-online channels than to the usage of conventional online channel. This is based on numerous reasons. First, Makwana and Rahaman (2013) mention that 52% of the mobile users are concerned about their credit card security, which deterred them from using their mobile devices for online purchases. Second, a survey conducted by Tripwire notes that 91% of the respondents believed that shopping online using a computer provides more security than shopping online using a mobile device (Tripwire, 2013). Third, mobile devices may interchange information in the open area where everyone with technological skills can intercept it (Makwana and Rahaman, 2013). Last, consumers are more worried about losing their mobile phones or tablets with their personal information in it, which may deter them from using mobile-online channels (Makwana and Rahaman, 2013). Therefore, the following hypotheses will be advanced:
H7: Expected security concerns of the online channel is more negatively related to mobile-online channel usage than to conventional online channel usage.
2.5 Hypotheses
Based on the review of past literature, several hypotheses are formulated. Table 2.2 summarizes the hypotheses that are examined in this research.
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Table 2.2
Hypotheses in this research
Hypotheses Statements Results
H1a,b Male consumers are more likely to use the conventional online channel than female consumers.
Female consumers are more likely to use the mobile-online channels than male consumers.
Not confirmed Partially confirmed
H2a,b Young consumers are more likely to use conventional online channels than middle-aged consumers.
Middle-aged consumers are more likely to use mobile-online channels than young consumers.
Confirmed Confirmed
H3 Shopping enjoyment is more positively related to the usage of mobile-online channels than to the usage of conventional mobile-online channel.
Not confirmed
H4 Consumer innovativeness is more positively related to the usage of mobile-online channels than to the usage of conventional online channel.
Confirmed
H5 Time consciousness of consumers is more positively related to the usage of mobile-online channels than to the usage of conventional online channel.
Not confirmed
H6 Expected information availability of the online channel is more positively related to conventional online channel usage than to mobile-online channel usage.
Not confirmed
H7 Expected security concerns of the online channel is more negatively related to mobile-online channel usage than to conventional online channel usage.
Not confirmed
2.6 Conceptual framework
Prior research has provided useful insights into the usage of online shopping channels, but there are important research gaps. First, these studies mainly focused on the usage of online shopping in general, which most of the time refers to online shopping using desktop or laptop computer. They have left out the usage of mobile-online channels (i.e., mobile phones and tablet devices) as it is a relatively new and innovative concept. Second, previous research found that consumers’ shopping behavior in online channels differs from that in traditional
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offline retail channels (Alba et al., 1997), but they have not examined whether the shopping behavior of consumers differs when using conventional online in comparison with mobile-online channels. Third, one may also conclude that there is a need for more empirical research on mobile-online shopping, since the customer usage of mobile-online channels is growing rapidly (Kushwaha and Shankar, 2013). Therefore this research could contribute greatly to the scientific literature. To fill the research gaps mentioned above and to enrich the understanding of consumer shopping behavior when using conventional online and mobile-online channels, the following research question is addressed:
“Whether and how does customer behavior differs between the usage of conventional online channel (i.e., computer) and mobile-online channels (i.e., mobile and tablet devices)?”
The objective of this study is to examine the impact of several demographic and psychographic characteristics of consumers and expected benefit and cost factors on the usage of conventional online and mobile-online channels. This study builds on previous research by investigating the usage of online shopping channels and in addition, we aim to gain a deeper insight into the differences in the consumers’ characteristics when using different online shopping channels. To answer the research question, a conceptual framework of this research is presented in figure 1.
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The framework is based on prior literature on online shopping channel usage and consumer behavior. The framework proposes that the consumers’ characteristics and expectations differently influence the usage of the online channels, namely the computer, mobile phone and tablet. Additionally, in the proposed framework, the formulated hypotheses are visualized. The hypotheses attempt to answer the research question. It includes gender,
age, shopping enjoyment, innovativeness, time consciousness, information availability and security concerns as factors that influence the online channel usage. Further, we look at the
online channel usage from multiple activities, such as the percentage using the online channels and the number of items purchased through computers, mobile phones, and tablets. This will provide a richer understanding of whether and how consumer behavior varies in using online shopping channels.
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3. RESEARCH METHODS
This chapter presents the research methods that are used in order to answer the research question. First, the research design will be explained. In addition, the data collection procedure is described and the chapter ends with an explanation of the variable measurements.
3.1 Research design
According to Bryman and Bell (2011), a research design refers to a framework for collecting and analyzing data. When choosing a research design, there are a variety of issues to consider, such as the aim of the research, the research question, the medium and time frame for collecting data, and the priority and interests of the researcher (Bryman and Bell, 2011). In order to answer the research question of this study, a quantitative, exploratory research is most suitable to examine the differences in consumer behavior when using various online shopping channels, since a quantitative study generates highly structured data collection techniques, and thus it will most likely provide a large amount of data, which is necessary for this study (Saunders et al., 2009). In addition, this research is exploratory of nature since the given conclusions of the study are not explicit but needs to be examined further.
The research design is a cross-sectional survey design, which entails that data is collected at a single point in time from a sample of respondents that is drawn from the target population (Bryman and Bell, 2011). The cross-sectional survey design is considered to be the most appropriate research design for this study to gather information for numerous reasons. First, the survey design presents the possibility of collecting a large amount of data from a wide range of people in the population (Saunders and Lewis, 2011). To test the propositions of this study, a great amount of respondents is needed in order to make generalizable conclusions about consumer behavior in online channel usage. Second, the cross-sectional survey design enables the gathering of data on all variables at once and does not contain as many obstacles as other research designs related to finding and maintaining respondents (Saunders et al., 2009). Third, the survey design allows us to examine and compare multiple constructs at a single time, which is particularly important in this study, since we want to see how different consumer characteristics correspond to consumers’ online channel usage (Saunders et al., 2009). Fourth, this study aims to identify the actual online shopping behavior of consumers across different online channels. Therefore information is
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needed about the subjects without having to manipulate the study environment. Based on these reasons, a quantitative cross-sectional survey design is chosen for this research.
A potential limitation of the cross-sectional survey design is that it can be difficult to examine whether there is causation due to lack of randomized control group and time dimension, since data is gathered at only one point in time (Bryman and Bell, 2011). However, given the fact that this study is exploratory and particularly interested in the current practice of online shopping behavior and related issues, it is not necessary to examine changes over time or causal relationships.
3.2 Data collection
An important matter within the research design is the procedure of collecting data. This paragraph will explain the data collection method. First, the survey method used in this study to gather data, the self-mediated questionnaire, will be discussed. Second, the sampling technique for approaching the respondents is outlined. Last, the research sample will be presented.
3.2.1 Self-mediated questionnaire
When using the survey method, data collection can take several forms, such as questionnaires, structured observations, and structured interviews (Saunders and Lewis, 2011). The present study uses a self-mediated questionnaire through the Internet as the main data collection instrument. There are several reasons why this type of questionnaire is appropriate for this research. First, the questionnaire is distributed online with the idea that people who use the online medium are most likely the consumers making purchases using online channels (Kumar and Venkatesan, 2005). These people are part of the target population. Second, online surveys provide the quickest, cheapest, and most efficient way to gather data in the sense that it automatically puts data in a suitable file for the SPSS software (Albaum et al., 2010). This could reduce human error. Third, questionnaires are relatively simple to administer and the obtained data are consistent, since each respondent is exposed to the same set of questions. This will decrease the inconsistency in the outcomes, which can potentially result from interviewers’ interventions. Fourth, self-mediated questionnaires provide respondents enough time to fill in the questionnaire, which in turn reduces the sample error (Bryman and Bell, 2011).
Although a questionnaire provides a lot of advantages, it also has a few limitations. The questionnaire can only contain a limited number of questions to avoid inducing fatigue
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or boredom in its participants (Bryman and Bell, 2011). This problem can be foreseen by creating well-designed questions, so that a limited number of questions is needed to collect sufficient data. Therefore this study uses measurements of variables that have been used before in prior studies to create the questionnaire. This will maintain the reliability and validity of measuring the variables. Another limitation is the fact that there is no interviewer intervention to explain the survey, since it is a self-mediated questionnaire. However, pilot testing the survey can overcome this limitation. Revising questions will be done when needed in order for all respondents to interpret the questions in the same manner, where explanation will not be necessary.
Therefore prior to the actual research, a pilot test is conducted. The purpose of conducting the pilot test was to make sure the questions were clear and appropriate to ascertain the validity, reliability and consistency of the questions in order to answer the research objectives. Four persons conducted the pilot test, of which two of them have academic backgrounds. They were asked to fill in the questionnaire and review the questions by identifying complex or ambiguous questions. This has resulted into valuable opinions concerning additional factors and reformulation of some questions to make it more clearly. 3.2.2 Sample selection
The target population in this research consists of consumers aged between 16 and 65 that shop online. Normally any consumer could be a target sample in this study without age restrictions. However, based on the fact that the questionnaire is distributed via the Internet mainly through social networking sites, the target sample is set between 16 and 65 years old, since prior study shows that social network users are in this age category (Lenhart et al., 2010).
Due to the fact that it is not possible to examine the entire population, a sample needs to be chosen. In order to select the respondents, there are several types of sampling techniques (Bryman and Bell, 2011). The sampling technique used in this research is the purposive sampling technique, which entails that the sample is primarily drawn by the researcher’s subjective conviction that the sample will faithfully represent the population (Bryman and Bell, 2011). The reason for choosing this type of sampling technique is that in this study, the researcher attempts to address respondents who are most likely online shoppers by approaching them via social networking sites (i.e., Facebook, LinkedIn) and via emails to family members, friends, and acquaintances. Distributing the survey through social media and email will most likely provide data from respondents that have experience with
