Masterarbeit, 2013
39 Seiten, Note: 1,3
List of figures
List of tables
List of appendices
1 Introduction
2 Theoretical background of showrooming
2.1 Shopping trends and behaviors related to showrooming
2.1.1 Multi-channel shopping
2.1.2 Research shopping
2.1.3 Free riding
2.2 Findings about showrooming
3 Factors influencing showrooming
3.1 Literature review
3.2 Channel attributes
3.2.1 Enjoyment
3.2.2 Assortment
3.2.3 Purchase convenience
3.2.4 Service
3.2.5 After-sales service
3.2.6 Price
3.2.7 Risk
3.3 Customer characteristics
3.3.1 Attitude towards shopping
3.3.2 Internet experience
3.3.3 Price-consciousness
3.3.4 Attitude towards free riding
3.3.5 Retailer loyalty
3.4 Conceptual framework
4 Empirical study
4.1 Study design
4.2 Operationalization of variables
4.3 Sample
4.4 Reliability of construct
4.5 Logistic regression
5 Results
5.1 Testing of hypotheses
5.2 Additional analyzes
6 Conclusion
6.1 Summary of findings
6.2 Implications for retailers
6.2.1 Channel attributes
6.2.2 Customer characteristics
6.3 Limitations and future research
References
Appendix
Figure 1: Directions of the shopping process (source: author’s illustration)
Figure 2: Conceptual framework with overview of hypotheses
Figure 3: Products purchased within the study’s sample
Table 1: Directions of research shopping (source: Verhoef, Neslin, and Vroomen 2007, p. 130)
Table 2: Overview of variables used in previous multi-channel research
Table 3: Operationalization of channel attributes
Table 4: Operationalization of customer characteristics
Table 5: Age of study sample
Table 6: Education, occupation and income of study sample
Table 7: Results of logistic regression (Wald statistic)
Table 8: Evaluations of channel attributes
Table 9: Evaluations of customer characteristics
Table 10: Smartphone usage among showroomers and non-showroomers
Appendix A: German questionnaire
Appendix B: Output logistic regression
Appendix C: Demographic differences between showrooming and non- showrooming Please find the electronic appendix on the attached CD.
With the emergence of the internet as a shopping channel, consumers, retailers and manufacturers are facing a continuously changing shopping environment that opens various opportunities of changing shopping and selling behaviors and creates both chances and challenges for traditional shopping channels. In that context, one term is recently gaining rising attention – showrooming. Showrooming is a consumer behavior that is defined by a customer using a physical store to inform him- or herself about products or services and purchases in an online shop afterwards.
Latest studies and articles highlight that showrooming brings along opportunities and threads for retailers (ComScore 2012; IDC Retail Insights 2012; PwC 2012a; Roland Berger Strategy Consultants 2013; Zimmerman 2011). It is claimed that in the future, physical retail stores may only serve as showrooms where customers experience a unique shopping experience, receive inspiration and interaction with products, while purchases will be made online. Whether this is a positive or negative development depends on the retailers ability to attract customers from its physical retail store into its own online shop. By managing this consumer transfer, retailers can achieve cost efficiencies (Alba et al. 1997; Burke 1997; Roland Berger Strategy Consultants 2013). Losing the customer to a competitive online shop, on the other side, means uncompensated costs and lower profits (van Baal and Dach 2005).
Showrooming today is still in its first steps (Roland Berger Strategy Consultants 2013). But considering its heavy expansion in recent years, showrooming is prospected to gain very high importance in the near future (IDC Retail Insights 2012). Even today, physical stores tend to be harmed by showrooming consumers who purchase at competitive online shops. Zimmerman (2011) already claimed back then that showrooming hurts the bottom lines of traditional stores while benefiting online-only retailers such as Amazon. When consumers are only using physical stores to view products but do not create sales on-site, the further existence of these shops is critical as the retailers are faced with high establishment, personal and maintenance costs that pure online shops simply do not have.
Before determining the reasons of purchasing from a retailers own online shop or a competitive shop, it first needs to be understood why customers attend showrooming at all. In order to find possible drivers of that behavior one way is to compare showrooming customers with customers who purchased the product in-store after viewing, called non-showroomers in the following. In the course of this thesis both showroomers and non-showroomers start to view a product in a physical store but differ in their choice of channel for purchase. Showroomers therefore clearly distinguish from pure online shoppers. An empirical investigation on showroomers and non-showroomers regarding various channel attributes and customer characteristics is the focus of the conducted study. The findings are expected to give insights into what is influencing showrooming on the channel perspective and how showroomer characteristics differ from non-showroomers when purchasing products. The main research questions are therefore: a) What are the main channel attributes that encourage or deject showrooming and b) How do showrooming costumers differ from non-showrooming costumers?
Up to now, only very few empirical studies have investigated purely on the showrooming phenomenon. This study contributes to the marketing literature as the first empirical research that explores the impact of both channel attributes and customer characteristics on showrooming behavior.
The results help retailers to design channel attributes in order to avoid showrooming behavior of their customers in-store. Additionally, it will help retailers to identify whether their customer base is likely to attend showrooming or not and which customers they have to address when using showrooming on their behalf.
To answer the research questions, the thesis proceeds as follows: first, a theoretical background about relevant topics in the context of showrooming is given. Second, possible factors that may impact the showrooming decision are explained in detail, including the hypotheses and conceptual framework of the study. Third, the empirical study is described, followed by the presentation of the results. The thesis ends up with a summary of findings, implications for retailers and limitations of the study.
Although the term showrooming has entered marketing literature very recently, it is not a completely new phenomenon. Related trends and consumer behaviors have already been studied in previous academic research for many years. A summary of this research will help to give an upfront understanding of showrooming. The chapter will also explain showrooming in more detail.
Today, consumers shopping behaviors are constantly changing (Chiang and Dholakia 2003). Especially technology related developments such as internet, advanced mobile devices and social networks have changed the traditional shopping landscape and enabled marketers to reach shoppers through new touch points (Shankar et al. 2011). Consequently, consumers today can use a variety of channels to purchase. A large body of marketing literature deals with the explanation of a consumer’s channel choice. Within that research, some behaviors are closely related to showrooming:
Consumers today are not bond on using a certain purchase channel to acquire products and services, they can choose among a great variety of channels. Those consumer contact points can serve as instruments of communication, interaction, transaction and/or distribution (Neslin et al. 2006; Peterson, Balasubramanian, and Bronnenberg 1997). Examples for channels are physical stores, the internet, telephone orders or catalogues (Chiang and Dholakia 2003; Jindal et al. 2007; Konus, Verhoef, and Neslin 2008). Consumers who use various channels to purchase products and services are called multi-channel shoppers.
Multi-channel shopping is highly related to showrooming, as showroomers us both the offline and online channel for purchase. Thus, previous research about multi-channel shopping appears to be interesting for this thesis as it deals with the following questions: What are the determinants of using multiple channels for purchases? And, what determines a consumer’s choice to use a particular channel instead of another one? Although multi-channel shoppers can use many different channels, only two relevant channels are going to be extracted in this thesis: the online shop (online channel) and the physical store (offline channel).
As determinants of using multiple channels, Konus, Verhoef, and Neslin (2008) found that multi-channel consumers show a higher shopping enjoyment, higher price-consciousness and higher innovativeness than traditional customers who consistently use the same channel for purchase. Kumar and Venkatesan (2005) explain that cross-buying behavior and a higher frequency of shopping increases the likelihood of using multiple channels. Additionally, consumers who are purchasing various product categories will likely use multiple channels. As consequences of using multiple channels of the same retailer, consumers often spend more money and purchase more often than those who only use one channel (Double Click 2004; Kumar and Venkatesan 2005).
When using multiple channels for purchase, research has also analyzed why a consumer chooses the online or offline channel for a particular purchase. The decision might be influenced by the retail context utility (for example by the service and shopping atmosphere) and the perceived product risk, which depends on the type of product. For products with low perceived purchase risk, the online channel is more likely to be chosen (Lee and Tan 2003). Additionally, products whose attributes can be assessed easily before purchase, called search goods, are more amenable to online shopping. In contrast, products in the category of experience goods, that can only be evaluated by direct experience (for example touching, smelling and hearing) are less likely to be purchased online (Gupta, Su, and Walter 2004).
The online channel has gained rising popularity in the past decade (Chiang and Dholakia 2003; PwC 2012a). Gupta, Su, and Walter (2004) have found, that 52 percent of customers tend to switch from offline to online channels when buying certain products. Research reveals that consumers value the unlimited shopping time, perceived lower prices and the ease and speed of usage of the online shop (Ahuja, Gupta, and Raman 2003; Chiang and Dholakia 2003; PwC 2012b). A major reason for shopping online is also convenience, like shopping from home and avoiding the hassles of parking and checkout lines (Ahuja, Gupta, and Raman 2003; Chiang and Dholakia 2003; Gupta, Su, and Walter 2004). The availability of products, as well as the access to a broader product variety drives the decision to shop online instead of offline as well. On the other side, the perceived lack of service and personal assistance can detain people from shopping online (Ahuja, Gupta, and Raman 2003; Montoya-Weiss, Voss, and Grewal 2003) and so does the perceived higher risk of purchasing in this channel (Gupta, Su, and Walter 2004).
Although the online channel becomes a more accepted purchase channel, for most purchases the physical store remains the center of shopping (PwC 2012b; Roland Berger Strategy Consultants 2013). One determinant of using the offline store may simply be that online shops lack the opportunity to experience the products. Besides, offline stores are preferred for the personal service. After all, consumers may favor the physical store for social reasons, such as the experience to visit a shopping mall with friends (Ahuja, Gupta, and Raman 2003). These findings indicate that physical stores will still be of high relevance in future.
Next to the use of multiple channels for different purchases, the multi-channel environment enables customers to use different channels during one single purchase process (Nunes and Cespedes 2007).
Generally, while purchasing a product or service, a customer passes through three stages: pre-purchase stage, purchase stage and post-purchase stage (Balasubramanian, Raghunathan, and Mahajan 2005; Frambach, Roest, and Krishnan 2007; Gensler, Verhoef, and Böhm 2012; Shin 2007; Verhoef, Neslin, and Vroomen 2007). During the pre-purchase stage or information search stage, consumers are attempting to gather information about a product or service (Kucuk and Maddox 2010). In the purchase stage a decision is made and the actual purchase transaction takes place. The post-purchase phase is characterized by after-sales services, such as consulting, repair or repeat purchases (Frambach, Roest, and Krishnan 2007). In the pre- and post-purchase stage a consumer can use multiple channels, for example using both the internet and a catalogue for information search. The purchase itself can only be made in one channel.
Research has shown that customers often switch between online and offline channels when they move through the different stages of the purchase process (Ahuja, Gupta, and Raman 2003; Frambach, Roest, and Krishnan 2007; Gensler, Verhoef, Böhm 2012; Gupta, Su, and Walter 2004; Nunes and Cespedes 2007; Montoya-Weiss, Voss, and Grewal 2003; Verhoef, Neslin, and Vroomen 2007). When consumers switch the channels between different stages, respectively between the pre-purchase and purchase stage, it is called research shopping (Verhoef, Neslin, and Vroomen 2007). Showrooming can be assigned to research shopping because customers use the physical store in the pre-purchase stage and the internet for the actual purchase transaction. However, research shopping can have many different directions, depending on how many channels are used and showrooming is only one of them. Table 1 gives a simplified overview of the directions.
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Table 1: Directions of research shopping (source: Verhoef, Neslin, and Vroomen 2007, p. 130)
Internet search and offline purchase is the most popular direction of research shoppers (Double Click 2004; Verhoef, Neslin, and Vroomen 2007). A study by van Baal and Dach (2005) found that 30.8 percent of the respondents collect information on the internet before they made their latest offline purchase. In a study by PwC (2012b) more than 80 percent of the respondents admitted to conduct online research before purchasing electronics, computers, books, music and movies in a physical store.
The reasons why consumers attend research shopping lie in the different requirements of the three purchase stages and the channels ability to fulfill these requirements (Neslin et al. 2006; Verhoef, Neslin, and Vroomen 2007). Consumers can perceive the channels’ fulfillments of these requirements differently, depending at what stage of the purchase process they are (Gensler, Verhoef, and Böhm 2012).
In the search phase the channel attributes search convenience and search effort are highly significant drivers of channel choice (Verhoef, Neslin, and Vroomen 2007) and so are accessibility of the channel and social presence (Frambach, Roest, and Krishnan 2007). The attributes assortment, price promotion, enjoyment and consumer clientele are significant drivers for using the internet channel for information search (Verhoef, Neslin, and Vroomen 2007). It is claimed that the internet performs better in providing product information and the ability to compare products and prices easier than in traditional stores (Alba et al. 1997; Chiang and Dholakia 2003; Gupta, Su, and Walter 2004; Peterson, Balasubramanian, and Bronnenberg 1997). This can be explained by the more detailed, timely and customizable information, compared to the offline store (Morton, Zettelmeyer, and Silva-Rosso 2001). Consequently, consumers prefer to use the internet in the information search phase rather than the offline shop (Gupta, Su, and Walter 2004).
In the purchase phase, the decision of where to buy is significantly influenced by the channel attributes service, purchase effort, risk, privacy and enjoyment (Verhoef, Neslin, and Vroomen 2007) as well as ease of use (Frambach, Roest, and Krishnan 2007). Perceived price was found to not significantly affect consumers channel choice in this phase (Gensler, Verhoef, and Böhm 2012). In the purchase phase the offline channel is found to be preferred over the online shop, predominantly because of the internet’s higher shopping risk and the lack of viewing the product online (Ahuja, Gupta, and Raman 2003).
The consequences of research shopping are two fold. A distinction into loyal and competitive research shopping is made (Neslin and Shankar 2009). A loyal research shopper switches the channel during the purchase process but stays at the same retailer. This means that sales of these costumers are only shifted between the different channels of a company and do not become lost. In comparison, competitive research shoppers use a channel of a retailer to gather product information, but then switch to a channel of another retailer to purchase afterwards (Nunes and Cespedes 2003). The latter behavior is called free riding, which will be discussed in the following.
Free riding is a general behavior that can be summarized as someone or something who is receiving benefits of public goods without paying for it (Devlin-Foltz and Lim 2009). In the shopping context free riding describes the behavior of a consumer who uses one retailer only to view and evaluate the products or services and then purchases them at another retailer (Dulleck and Kerschbamer 2009; Kucuk and Maddux 2010; van Baal and Dach 2005). Therefore, the customer takes advantages of the services provided in other stores. The behavior also appears on the retailer side, when a low-service retailer takes advantage of full-service retailers to sell its merchandise (Carlton and Chevalier 2001). Consumer free riding does not necessarily imply a change of channel during the purchase process. For example a customer uses an online shop to inform him-/herself about the product (for example Adidas.com) and purchases at another online shop (for example a shop at Amazon.com).
Free riding occurs when retailers offer pre-purchase services, such as product trial or personal assistance, with no upfront charges (Carlton and Chevalier 2001). Receiving such pre-purchase services does not generally force someone to make a purchase (van Baal and Dach 2005). This opens the possibility for consumers to use these pre-purchase services but switch to other retailers for purchase afterwards (Dulleck and Kerschbamer 2009). Typically, consumers then switch to retailers where they get the same product for a lower price (Carlton and Chevalier 2001; Huang, Lurie, and Mitra 2009).
Free riding can also be influenced by the product itself. Offline retailers that offer experience products, products with a high technological change and products that are purchased less often suffer most from free riding, as these products demand an inspection and personal consultancy prior to purchase (van Baal and Dach 2005).
On the other side, Huang, Lurie, and Mitra (2009) found that free riding in the online context is more frequent for search goods. Attributes of search goods can be evaluated more easily and consumers rather browse quickly through many different websites for information search, which increases the likelihood of free riding. Experience goods on the other side demand greater effort to evaluate their attributes online and therefore consumers prefer to only use a few websites to internalize all product information (for example try simulation, read customers reviews and expert ratings). After spending a long time on one website the consumer increases trust in the website and becomes more prone to use this website for purchase and thus, is less likely to free ride.
The behavior of free riding in the shopping environment has found wide adoption. Van Baal and Dach (2005) report that 20.4 percent of all respondents were pure free riders. It is predicted that consumer free riding will increase in the future (Huang, Lurie, and Mitra 2009) and that the internet is a large driver of this growth (Carlton and Chevalier 2001; Morton, Zettelmeyer, and Silva-Rosso 2001). The rise of this behavior must be seen critically as free riding is a major concern for retailers and comes along with disadvantages, especially when consumers use the physical store for information search and purchase the product at a competitors channel, like it can be done during showrooming (Carlton and Chevalier 2001). Full-service physical stores are most vulnerable because more service is related to more costs and possibly higher prices of the products. Retailers who do not offer full-service can therefore sell their products for lower prices, which attracts purchasing consumers (Shin 2007). When offline stores provide full-service to consumers who then purchase the product at a cheaper discounter, the retailer incurs opportunity costs because the time a sales person spends with a free riding customers could have been spent with a possible buyer (van Baal and Dach 2005). The problem is that free riding customers cannot be differentiated straight away from potential customers. This means that a sales assistance has to spend equal effort with each customer, no matter whether he/she buys or not (Burns 2010). More common and less harmful are consumers who free ride on services provided on websites and online shops (van Baal and Dach 2005). The majority of research shoppers use the internet for information search and the offline store for purchase (Verhoef, Neslin, and Vroomen 2007). This can be viewed less critical because the costs of websites are lower and remain fixed (Carlton and Chevalier 2001).
Figure 1 shows a summary of the presented shopping behaviors which can all partly be assigned to multi-channel research. It also illustrates how research shopping and free riding are related to showrooming.
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Figure 1: Directions of the shopping process (source: author’s illustration)
The arrows 1, 2, 7 and 8 represent research shopping (switch of channel between information search and purchase), arrows 2, 4, 6 and 8 illustrate free riding (switch of retailer between information search and purchase), arrow 3 and 4 show pure online shopping, and arrows 5 and 6 show pure offline shopping. Arrows 7 and 8 illustrate showrooming (switch from offline information search to online purchase).
Pure showrooming appears very sparsely in academic literature, though in recent years it has caught the attention of market research institutions, consultancies and experts (for example ComScore 2012; PwC 2012a; Roland Berger Strategy Consultants 2013; Zimmerman 2011).
The dispersion of showrooming customers in previous studies is generally quite low. The ratios of showrooming consumers among all consumers are varying from 35 percent (ComScore 2012) over 26.4 percent (van Baal and Dach 2005) and 17 percent (Roland Berger Strategy Consultants 2013), 16 percent (Verhoef, Neslin, and Vroomen 2007) to 2 percent (PwC 2012b). However, it is claimed that showrooming will gain importance in the future and that the number of showroomers is expected to increase (IDC Retail Insights 2012).
The intentions of showrooming are differing: 6 in 10 showroomers claimed that they originally planned to purchase in a physical store but then changed their mind while being there and instead purchased online. The remaining part stated that they went to a physical store only to see the product but were always intending to buy the item online (ComScore 2012).
ComScore (2012) gives further insights into the phenomenon. When asked about showrooming, 12 percent of the study’s attendances claimed to have heard about showrooming before. Interestingly twice as many men than women did know the term. From the customers who engaged in showrooming, 50 percent were between 25-34 years old (oldest age group in the study). 72 percent stated that a reason for this behavior was a lower price online, 45 percent only wanted to view the product before buying it online. Other reasons were that the desired item was out of stock (24 percent) or that they preferred to get the items shipped home rather than taking them home immediately (18 percent). The most purchased items in showrooming were consumer electronics (63 percent), clothing and accessories (43 percent), books (29 percent), appliances (22 percent) followed by toys, jewelry/watches and others.
When evaluating showrooming and its meaning for retail stores, one can distinct between positive or negative showrooming in economic terms, here called loyal and competitive showrooming (adapted from Neslin and Shankar 2009).
Loyal showrooming (see figure 1, arrow 7) takes places when a physical retail store can attract customers in its offline shop and then makes them buy from its own online shop. This is not critical for retailers as it is only a shift of sales revenues from the offline to the online channel (Roland Berger Strategy Consultants 2013). Online shops in general provide lower costs for market entry and establishment of shops and allow retailers to benefit from a centralized distribution (Burke 1997; Peterson, Balasubramanian, and Bronnenberg 1997). By directing customers from the offline shop towards the own online shop, the retailer can use distribution efficiency, offer a complementary assortment to the physical shop, collect customer information more easily and furthermore can target customers more precisely (Alba et al. 1997; Burke 1997). Therefore, showrooming can be a chance for retailers. When a retailer successfully manages to direct its customers from its offline to its online store, it is imaginable that the retailer uses advantages from mobile shops or pop-up shops and thus, saves costs for rent, storage facilities and staff (Burke 1997). However, loyal showrooming was found to be very seldom (only 1.8 percent of showroomers) (van Baal and Dach 2005). Researchers further argue that the achievement of loyal showrooming can also be seen critically: when physical retailers try to attract consumers to their own online shop the possibility that consumers switch to a competitive online shop is very high because the consumers switching costs online are low (Ansari, Mela, and Neslin 2006).
Showrooming that includes a switch from the physical store to a competitive online shop is called competitive showrooming and has found a much wider adoption (see figure 1, arrow 8) (ComScore 2012; van Baal and Dach 2005). This free riding behavior has negative consequences for the retailer. Especially vulnerable are those retailers who are not able to direct their consumers to an own online shop, for example because they do not have an online shop. When showrooming increases, those retailers can face major problems as they generate less sales.
However, the following chapters of this thesis will focus less on the intention to attend loyal or competitive showrooming but on the general intention to showroom in the first place.
After reviewing the theoretical background the focus will now be set on understanding the possible reasons why consumers attend showrooming.
The previous chapter has shown that showrooming can be assigned to related consumer behaviors, which have been well studied. Research has identified possible influencing factors of multi-channel shopping, research shopping and free riding but showrooming is a specific combination of these behaviors and therefore demands an individual examination of its impacting factors. However, when analyzing the antecedents of showrooming, the before mentioned related research serves as a foundation of possible influencing factors.
This chapter first presents potential impacts based on previous research. Afterwards, each relevant factor will be explained, followed by a hypothesis of the possible impact on showrooming. The conceptual framework then illustrates the contributive factors as variables and summarizes the hypotheses of this study.
Literature about multi-channel shopping, channel choice, research shopping and free riding has determined various factors such as channel characteristics (for example Gensler, Verhoef, and Böhm 2012; Montoya-Weiss, Voss, and Grewal 2003; Verhoef, Neslin, and Vroomen 2007), consumer characteristics (for example Balasubramanian, Raghunathan, and Mahajan 2005; Jarvenpaa, Tractinsky, and Vitale 2000; Konus, Verhoef, and Neslin 2008) and a mix of them (for example Ahuja, Gupta, and Raman 2003; Burke 2002; Frambach, Roest, and Krishnan 2007; Gupta, Su, and Walter 2004; Kumar and Venkatesan 2005, Ratchford, Talukdar, and Lee 2001) to influence these related shopping behaviors. Table 2 shows an overview of variables that have been analyzed in previous multi-channel behavior, including research shopping and free riding.
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Table 2: Overview of variables used in previous multi-channel research
Channel attributes and customer characteristics are well analyzed in previous literature, proving that they are determining customer’s shopping behaviors to a great extent.
The effect of channel attributes on consumer behavior can be explained by various theoretical frameworks. One theoretical explanation is used by Ratchford, Talukdar, and Lee (2001). They argue with the benefit-cost-theory as economic explanation for the choice behavior during search phase. Channel attributes are perceived as either search benefits or search costs, respectively some attributes have a positive and some a negative impact on the attractiveness of a specific channel in the search phase. A consumer then is eager to minimize his/her search costs (maximize search benefits) by combining different channels, respectively he/she will chose the channel(s) that serve(s) her/his needs most cost-efficiently.
As another theoretical explanation, Verhoef, Neslin, and Vroomen (2007) analyzed the channel choice among the three stages of the purchase process. They underlie their study the theoretical framework of Fishbein and Ajzen’s Theory of Reasoned Action (TRA). TRA, in the context of multi-channel purchasing, claims that the attractiveness of using a channel in the search and purchase phase is based on the performance of a channel’s attributes in each stage (Verhoef, Neslin, and Vroomen 2007). For example, one channel is more attractive for search and another channel is more attractive for purchase, based on how well the channel attributes are perceived in each stage. The sum of the attribute evaluations in each stage will then form the overall attractiveness of one channel for search and purchase. This in turn will affect the consumers’ choice. It can also be described as attribute-driven decision making (attributes of channel → attractiveness of channel → channel choice).
Showrooming and non-showrooming customers both use the offline channel in the search phase but differ in their choice of purchase channel (in the means of this thesis). The purchase choice is influenced by purchase attributes such as price, as well as by general attributes of a channel such as enjoyment (Verhoef, Neslin, and Vroomen 2007). Therefore, both purchase and general attributes are included in the study.
Next to channel attributes, customer characteristics can play a vital role in the channel decision (Ailawadi, Neslin, and Gedenk 2001; Girard, Korgaonkar, and Silverblatt 2003; Konus, Verhoef, and Neslin 2008) and therefore determine a certain shopping behavior. Previous studies on multi-channel shopping have investigated on customer characteristics (for example Balasubramanian, Raghunathan, and Mahajan, 2005; Burke 2002; Burns 2010; Frambach, Roest, and Krishnan 2007; Schoenbachler and Gordon 2002; Gupta, Su, and Walter 2004; Jarvenpaa, Tractinsky, and Vitale 2000; Konus, Verhoef, and Neslin 2008) reporting significant impact of different customer characteristics and segments on the channel choice.
This study is going to analyze whether there are customer characteristics that act significantly to explain the showrooming behavior and in which direction they influence it.
For the study, both, channel attributes and consumer characteristics, are expected to have a simultaneous influence on showrooming and are therefore included in one model. They are assessed and detailed in the following.
This section of the thesis will focus on the role of channel attributes in the showrooming decision and provides a detailed explanation and expected impact of each channel attribute.
The selection of possible impacting channel attributes is based on a) the frequency in which the channel attribute has been studied in previous related research and b) on the significance of impact on related behavior. Thus, those attributes where chosen that have been studied most often and have shown a significant or inconsistent impact in previous research. As a dominant influence on the attribute choice in this study, the paper of Verhoef, Neslin, and Vroomen (2007) can be mentioned. Their paper about research shopping is most related to showrooming and their selection of variables includes most of the channel attributes that showed significant impact in other studies. Besides, the chosen attributes are proven to be the most important motives that influence the channel decision (Roland Berger Strategy Consultants 2013).
The channel attributes analyzed in this study are: enjoyment, assortment, purchase convenience, service, after-sales service, price and risk.
In contrast to other studies which show the impact of the evaluations of channel attributes on consumer behaviors, this study will focus on the perceived difference of a customers evaluation of channel attributes for the online, compared to the offline store. The difference in evaluations of channel attributes will be measured: Attribute evaluationonline – attribute evaluationoffline = difference score. If a consumer for example perceives the online shop much better than the offline shop in terms of one attribute then he/she will give a higher grading to the online shop (for example 5 points) and a lower grading for the offline shop (for example 2 points). This will lead to a high difference score (5-2=3 points). The better the consumer perceives the online shop compared to the offline shop, the higher will be the difference score. In the contrary case, the difference score would be low, respectively negative. In the following it will be examined which impact the values of these difference scores have on the showrooming likelihood. Each attribute is now discussed in detail.
3.2.1 Enjoyment
Enjoyment of a shopping channel is defined as “the perceived shopping experiences that reflects the hedonic value of shopping in a channel” (Verhoef, Neslin, and Vroomen 2007, p. 134). It can also be described as simply liking to do shopping in a particular channel (Babin, Darden, and Griffin 1994; Dawson, Bloch, and Ridgway 1990; Mathwick, Malhotra, and Rigdon 2001).
The perceived enjoyment of shopping in a channel can be seen as entertainment and emotional benefit (Babin, Darden, and Griffin 1994). It involves fun, adventure and excitement to try new items, customizing products and more (Forsythe et al. 2006). Offline stores have recognized the need to improve the shopping experience in their stores, for example through adding restaurants to shops or arranging events (Burke 1997). The offline shopping enjoyment is also influenced by social experiences. For instance, when a customer visits an outdoor equipment store not only to purchase hiking equipment but also to enjoy a conversation about hiking experiences with a salesperson or other customers (Dawson, Bloch, and Ridgway 1990). Offline enjoyment is also influenced by the store’s atmosphere (like music and light) (Baker et al. 2002) and the facility itself (like size and layout of the store) (Yoo, Park, and MacInnis 1998).
Enjoyment of the online channel is mainly driven by high flexibility in navigation, clarity, convenience and the level of ability to substitute the real viewing of the product (Childers et al. 2001). However, the online shop was found to be less joyful for shopping. It lacks on personal service, entertainment and social interaction (Burke 1997). But the internet has improved in its variety of entertainment opportunities, for example with integrated videos, music, customization possibilities or real time auctions. This was found to increase the attitude towards this media and thus drives its adoption and usage (Lee and Tan 2003). It is also reported that enjoyment is a significant driver of using the online channel for search and purchase and is influencing online purchase most (Verhoef, Neslin, and Vroomen 2007).
Previous research has found out that enjoyment of a channel has a significant influence for stage-channel-choice (Babin, Darden, and Griffin 1994; Verhoef, Neslin, and Vroomen 2007) and so it is also expected to influence the channel choice in the purchase phase (both, showroomers and non-showroomers, use the physical store in the pre-purchase stage). It is expected that people who perceive a higher enjoyment in one channel will also choose this channel in the purchase phase. Thus, consumers who search in offline stores but who perceive the online channel as more enjoyable for purchase than the offline channel are expected to be more likely to showroom, compared to people who perceive the offline channel as more enjoyable for purchase.
Hypothesis 1: The more enjoyable consumers evaluate the online shop compared to the offline store, the more likely is showrooming.
3.2.2 Assortment
Assortment is described as the perceived quality, quantity and availability of products in a channel (Verhoef, Neslin, and Vroomen 2007; Yoo, Park, and MacInnis 1998).
A wide assortment was found to make people feel excited, pleased, content and satisfied. Finding a desired product is arising the feeling of pride. These positive emotions caused by product assortment were shown to positively affect the attitude towards a retailer (Yoo, Park, and MacInnis 1998). The unavailability of products on the other side was found to create disappointment in consumers and may lead them to switch to other channels of a company or competitors (Bendoly et al. 2005). The lack of availability of a product or stock-outs can also cause the perception of risk purchasing in a channel, which may lead to consumers switching to other channels.
In a previous survey the assortment was stated as one of the most important reasons why people make channel decisions because generally consumers prefer to use the channel with a larger assortment (Roland Berger Strategy Consultants 2013). A larger assortment offers more alternatives for choice and therefore a higher likelihood that a consumer will find the optimal alternative and it also allows a higher flexibility when making a choice (for example an ice cream seller who offers 31 flavors offers more flexibility than one who is selling 3 flavors) (Kahn and Lehmann 1991). However, too much choice can be perceived negatively as the decision making takes too much time and increases the demand on the individual’s cognitive resources (Greenleaf and Lehmann 1995).
Verhoef, Neslin, and Vroomen (2007) found that assortment has a significant positive impact on the use of the online channel in the search and purchase phase. Ahuja, Gupta, and Raman (2003) showed that access to product variety is a significant reason why consumers use the online channel in the purchase phase. This is supported by the finding that consumers perceive a greater assortment and better availability of products in the online channel compared to the offline channel (Bendoly et al. 2005). The internet is able to offer a broader assortment because it is not limited in shelf and storage space (Srinivasan, Anderson, and Ponnavolu 2002).
In the offline channel assortment did not show significant impact, thus it is assumed that most of the consumers generally evaluate the offline shop worse in terms of assortment compared to the internet. When consumers use the physical store in the pre-purchase stage, one reason to leave the physical store for the purchase phase and therefore attend showrooming can be the better evaluation of the assortment online, for example a broader and more recent variety of products or less stock-outs. It is expected that those consumers who perceive the online shop much better in terms of assortment than the offline store are more likely to showroom, whereas consumers who only perceive a little difference between the online and offline assortment are less likely to attend showrooming.
Hypothesis 2: The better the perceived assortment of the online shop compared to the offline store, the more likely is showrooming.
Convenience relates to the ease or effort of using a channel (y Monsuwé, Dellaert, and de Ruyter 2004). General convenience attributes of a channel have been studied in previous literature and are found to be significant drivers of channel choice (Ahuja, Gupta, and Raman 2003; Chiang and Dholakia 2003; Frambach, Roest, and Krishnan 2007; Gupta, Su, and Walter 2004; Verhoef, Neslin, and Vroomen 2007). Convenience appears to be an important attribute for channel choice, especially in the purchase phase (Gensler, Verhoef, and Böhm 2012; Gupta, Su, and Walter 2004).
In the online shop convenience is connected to shopping from home and avoiding the hassles of parking, salespeople and checkout lines (Ahuja, Gupta, and Raman 2003; Girard, Korgaonkar, and Silverblatt 2003). The convenience perception of online retailers is also influenced by the website’s performance, product selection, ease of ordering and shipping (Smith, Bailey, and Brynjolfsson 1999). The ease of using a website was detected to increase the attitude towards the new media, which in turn drives website usage. Remote channels, such as the internet or mail-order, are additionally characterized by no travel cost and the unlimited accessibility, which leads to greater convenience and makes shopping online more useful, enjoyable and easy to use (Childers et al. 2001; y Monsuwé, Dellaert, and de Ruyter 2004). Moreover, the increased accessibility and simplicity of shopping can be an antecedent to complete purchase transactions online (Srinivasan, Anderson, and Ponnavolu 2002). Internet furthermore reduces the time needed for shopping, which is generally associated with higher convenience (Bhatnagar, Misra, and Raghav Rao 2000). On the other side, internet lacks the possibility to view the products and the delivery of products takes more time than just taking the product with you while in-store. This reduces the convenience of online channels (Alba et al. 1997; Vanketasan, Kumar, and Ravishanker 2007).
In the offline store environment, general convenience is associated with low driving time, parking space availability and short check-out lines (Childers et al. 2001; Samli, Kelly, and Hunt 1988). Moreover, it is influenced by the navigation through a physical store, which is enhanced by simplified floor plans, standardized store layouts and stability of store layouts over time (Childers et al. 2001).
In a more detailed evaluation channel convenience can be specified into search and purchase convenience. The latter is in focus of this study as showrooming in this thesis only affects the channel choice for purchase. Purchase convenience is mainly representing the efficiency, ease and speed of obtaining the product in a channel (Verhoef, Neslin, and Vroomen 2007), including delivery time (Gupta, Su, and Walter, 2004; Jiang and Rosenbloom 2004). When it comes to obtaining the product, online and offline channels differ to a great extent. While you can take the product with you straight away in the offline shop, one has to wait for delivery when purchasing in the online shop. This delay in obtaining causes perceived costs and inconvenience, like the late consumption of the product or the lack of hedonic pleasure of the purchasing process itself (Vanketasan, Kumar, and Ravishanker 2007). On the other side, people may prefer the delivery to their homes and do not mind the extra time it takes online. Roland Berger Strategy Consultants (2013) show that the way consumers obtain the product is a major driver of channel choice and that the majority of consumers prefers an instant obtaining.
While in this thesis showroomers and non-showroomers both start their purchase process in the physical store, some consumers might tend to purchase online as they are more satisfied with obtaining the product via the internet and they find it less timely and difficult to purchase online than non-showroomers do.
It is further expected that consumers chose that channel for purchase which they personally perceive as more convenient for obtaining the product, irrespective of how long it takes. Those customers who evaluate the online shop better in terms of purchase convenience than the offline store are expected to be more likely to showroom.
Hypothesis 3: The more convenient consumers perceive the online shop for purchase compared to the offline store, the more likely is showrooming.
Service can be defined as the perceived delivery of assistance and is determined by whether a consumer receives the quality of assistance and support he/she has expected in a channel to make a product choice (Grönroos 1984; Verhoef, Neslin, and Vroomen 2007). In this context it refers to retailers add-on to the actual product instead of selling a service as core offering (for example an insurance or language course) (Homburg, Hoyer, and Fassnacht 2002). Service and assistance (offline or online) are found to be important determinants in the purchase stage as here consumers need to find advice about products to find out whether products match their needs (Verhoef, Neslin, and Vroomen 2007).
The level of service in a channel can be perceived differently (Montoya-Weiss, Voss, and Grewal 2003), especially as the online and offline channel differ in this attribute. Whereas in offline stores, personal assistance can be consulted, this is not yet possible in online channels.
The quality of offered service and personal assistance is a major determinant of retailer differentiation in today’s competitive markets. A high level of service orientation of a retailer was found to affect the retailer’s performance and profitability on the market positively (Homburg, Hoyer, and Fassnacht 2002).
In the offline store the level of service can be influenced positively by the degree of consumer orientation and the number of sales persons on floor (Homburg, Hoyer, and Fassnacht 2002). In online shops, the service can be determined for example by the design of the website (Montoya-Weiss, Voss, and Grewal 2003). A user-friendly website improves the navigation through the website and the time needed to find the desired information and therefore has a positive impact on a customer’s perception of service (Yang and Jun 2002). In the online channel however, personal assistance is missing, which includes the inability to reach someone if the consumer has a problem while purchasing (Ahuja, Gupta, and Raman 2003; Yang and Jun 2002).
Depending on the service, consumers may feel ignored and angry when a lack of service occurs. These consumers can build negative attitudes towards a store. When the service is perceived good it makes customers feel excited, proud and pleased and therefore has a positive effect on the attitude towards a store, which in turn drives purchase intention (Yoo, Park, and MacInnis 1998).
The degree of perceived service might be a reason for consumers who search in the offline store to switch to the online channel for purchase, respectively not to switch to the online store. Since service in the online store is generally perceived lower than offline, it is expected, that both showroomers and non-showroomers evaluate the offline store better in terms of service. However, for consumers who do perceive a higher difference between service provision online and offline in favor of the online shop, the likelihood to showroom is expected to be higher than for consumers who perceive a low or negative difference.
Hypothesis 4: The better the perceived service of the online shop compared to the offline store, the more likely is showrooming.
After-sales service refers to the quality of service after the product has been purchased (Verhoef, Neslin, and Vroomen 2007). It includes for example the return of the product, installation, delivery and repairs or the support in usage and disposal of products (Gaiardelli, Saccani, and Songini 2007). The explanation of effects and impacts of after-sales service are similar to the before mentioned channel attribute service. In the context of channel choice it was found that after-sales service significantly influences the choice of channel in the purchase phase (Verhoef, Neslin, and Vroomen 2007).
The importance of after-sales service is growing today. For retailers it serves as one possibility to differentiate and gain competitive advantage as products become more homogeneous these days (Mittal, Kumar, and Tsiros 1999). It can even generate profits that are higher than the actual purchase price of the product (Gaiardelli, Saccani, and Songini 2007).
The online and offline store differ in the way they provide after-sales service. In the offline store after-sales service is personal whereas communication in the online shop works remotely. That means that in the case of product return or repair, the products needs to be sent back to the online retailer, which increases the time needed for the handling process. However, there can be many people who do not perceive this negatively. Today, online shops offer chats or hotlines for consulting and free returns. Additionally, the importance of after-sales service rises with complex products and services compared to regularly purchased products (van Kenhove, de Wulf, and van Waterschoot 1999).
After-sales services were found to impact consumers’ behavior, for example an exceptionally good after-sales service can influence a consumers satisfaction with a product and therefore increases purchase intention (Mittal, Kumar, and Tsiros 1999). A high satisfaction with after-sales service, together with pre-sales service, can also increase customer retention (Jiang and Rosenbloom 2004).
It is expected that after-sales service has an impact on the decision of the purchase channel. Consumers who start purchasing in a physical store might switch to the online channel because they perceive a better after-sales service compared to the offline shop. However, similar to the attribute service, it is expected that all consumers generally have a better evaluation of the after-sales service in the offline channel, compared to the online channel. Again, the higher the perceived differences between the two channels and therefore the better the evaluation of after-sales service in the online channel, the more likely showrooming is expected to occur.
Hypothesis 5: The better the perceived after-sales service of the online shop compared to the offline store, the more likely is showrooming.
The channel attribute price describes the consumer’s perception of price and the amount and heights of promotions or discounts of the retailer (Verhoef, Neslin, and Vroomen 2007).
A price is perceived as low if it is positioned under the consumer’s internal expectation of a price, also known as reference price. Prices that are lower than the reference price are perceived as a gain to the consumer (Kalyanaram and Winer 1995). Paying a lower price or discount price can be of utilitarian value for consumers as the saved money can be spent for other purposes. When consumers pay a higher price for an item it could make them feel angry and resentful. In order to find low prices some consumers engage in price search activities such as visiting multiple offline and online stores (Schindler 1989).
Price is assumed to be an important driver in the consumer’s decision-making process (Chiang and Dholakia 2003). In a study by Keaveney (1995) about the choice of retail stores for purchase, price is among the three most influencing reasons why consumers switch from one to another provider. Higher prices are found to influence purchase probability in a channel negatively (Lichtenstein, Ridgway, and Burton 1993). However, past research about the impact of price is controversial. Some findings show that the perceived price does not significantly affect channel choice in a certain purchase stage (Gensler, Verhoef, and Böhm 2012; Gupta, Su, and Walter 2004). On the other side Montoya-Weiss, Voss, and Grewal (2003) found a significant impact of price on channel choice in a way that consumers prefer channels where the desired product is lower-priced. Keen et al. (2004) show that the lowest price was the most important driver for channel choice (for higher priced products). And showrooming research further revealed that lower prices in the online shop are the most stated reason for showrooming (ComScore 2012).
The perceived better price in the online shop is expected to be a major reason why consumers who visit the physical store in the pre-purchase stage switch to the online channel in the purchase stage. Consumers generally perceive online prices to be lower than offline prices (Roland Berger Strategy Consultants 2013). And some studies show that they are in fact lower than in the physical store (Ancarani and Shankar 2004; Brynjolfsson and Smith 2000). Therefore, it is expected that both showroomers and non-showroomers evaluate the online shop better in terms of price. However, showroomers are assumed to perceive a higher difference in price between the online and offline shop and therefore experience it as more valuable to change the channel for purchase.
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