The influence of inspiration on unplanned purchases : a comparison between online and offline venues

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The Influence of Inspiration on Unplanned Purchases

A comparison between online and offline venues

B.I. de Brabander 10871020

11 July 2016

University of Amsterdam - Faculty of Economics & Business

Master’s thesis Behavioural Economics and Game Theory (15 ECTS) 1st supervisor: dr. J.J. (Joël) van der Weele

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Statement of Originality

This document is written by Brigitte de Brabander who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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ABSTRACT

This paper hypothesizes that online shoppers have a predetermined product in mind and purchase only that product. Likewise, we expect customers looking for inspiration to visit conventional retailers. We hypothesize that store atmosphere triggers needs or wants for products. These triggers motivate customers into purchasing more products than initially intended, which results in more unplanned purchases for offline consumers. Study 1 explores the likelihood of visiting venues in different situations. This is investigated with a sample of 156 respondents from an online survey. Results of study 1 show that the search for inspiration induces consumers to shop offline. Study 2 consists of a sample of customers from an online and physical store. Results of study 2 show that offline shopping accounts for a higher percentage of unplanned purchases per visit. In addition, customers who value store characteristics as more important show to purchase more products offline per year.

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LIST OF TABLES

Table 1: Sample characteristics online vignette survey 23

Table 2: Medians of answers to vignettes 24

Table 3: Wilcoxon Signed-Rank tests of vignettes with a high/low need for inspiration 24 Table 4: Wilcoxon Signed-Rank tests of importance of venues as a source of inspiration 26

Table 5: Sample characteristics online and offline bookstore survey 35

Table 6: Sample characteristics unplanned purchases as percentage of number of books bought 36

Table 7: Mann-Whitney U test, per physical store characteristic 37

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1. INTRODUCTION

The past years witnessed an explosive growth in electronic commerce worldwide. The Internet became an alternative to traditional retailers. This growth is reflected in the number of webshops in the Netherlands that increased from more than five thousand in early 2007 to nearly 30 thousand in early 2015 (CBS, 2016). A contrary development occurred for traditional retailers, particularly in the non-food sector. More than 80 thousand stores were present in 2010 as opposed to 74 thousand in 2015 (CBS, 2016). Thus, it appears that e-tailers acquire market power at the expense of retailers, especially for sectors like clothing, electronics and books (CBS, 2016). With the advent of multiple channels such as mobile commerce and e-commerce, and a corresponding increase in competition between channels, shopping environments are changing (Jo Black et al., 2002). With the increasing number of consumers who use the Internet for their purchases (Broekhuizen, 2006) we wonder if one day the conventional brick-and-mortar shopping context is replaced by the clickable online shopping context. To assess the likelihood of this replacement, it important to understand what motivates consumers in their choice to purchase products online and offline.

The phenomenon of retail sales migrating online, refers to the cannibalization of traditional retailers by webshops (Gupta et al., 2004). Cannibalization in the context of this study is the extent to which webshops take over (part of) the market from traditional retailers. Because of cannibalization, “the death of retail” or the extinction of traditional markets, is feared (Hortaçsu and Syverson, 2015). However, despite the emergence of online channels and the substantial changes the Internet has brought to markets, the supremacy of e-tail is questioned (Hortaçsu and Syverson, 2015; Lieber and Syverson, 2012). Though an increasing number of consumers use the Internet for shopping, reasons for consumers to shop at conventional retailers are plenty (e.g. Jo Black et al., 2002; Kolyesnikova et al., 2010; Levin et al., 2003; Hoch and Loewenstein, 1991; Arnold and Reynolds, 2003). Focusing upon these differences assists traditional retailers to maintain customers. Ultimately, this can put a hold to the cannibalization of retailers by e-tailers. We propose that the distinguishing feature between choosing an online or offline venue, lies within the (un)certainty of buying decisions. According to research by Wolfinbarger and Gilly (2001), most online shoppers have a predetermined product in mind. On the contrary, research

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8 by Arnold and Reynolds (2003) indicates that for offline shoppers the search for new ideas is sometimes even the main motive to shop. We argue that consumers certain of a purchase are goal-oriented and therefore have a low need for inspiration. We adopt the definition of customer inspiration from Böttger (2015) as a “cognitive and motivational state that is evoked by stimuli, incorporating the realization of new or enhanced consumption-related insights, and motivates customers to purchase products or services.” According to research by Broekhuizen (2006), consumers still in doubt of their purchase, are more likely to visit physical venues than online venues. Since research shows that individuals are easier inspired by physical proximity (Bell et al., 2011; Hoch and Loewenstein, 1991) this could be a main reason for consumers to choose conventional retailers. Physical proximity could be a key determinant for conventional retailers to attract consumers who are in search of inspiration. As online shopping venues lack physical proximity, complete cannibalization of traditional in-store shopping experiences seems a bridge to far. To test whether inspiration is an activator for consumers in deciding where to purchase products, we propose the following research question: does the search for inspiration induce consumers to shop at conventional retailers?

We expect offline shoppers to get inspiration from temporal proximity to products. Temporal proximity in the form of physically seeing, touching and examining products shows to increase desirability for products (Ainslie, 1975; Hoch and Loewenstein, 1991). Physical proximity as well as in-store stimuli show to indirectly encourage purchases because these act as reminders of shopping needs (Abratt and Goodey, 1990). Therefore, visiting physical venues and getting inspiration directly (e.g. from salespeople) or indirectly (e.g. by encountering in-store stimuli), increases chances of purchasing more products than intended. Temporal proximity not only increases desirability for products, but also increases impatience to buy products immediately, thereby increasing the need for physical ownership (Ainslie, 1975; Hoch and Loewenstein, 1991; Peck and Childers, 2003). As a consequence, we believe that offline shoppers buy more products than originally intended. These unintended, or unplanned purchases, are those purchases that are not planned before a customer enters a store (Abratt and Goodey, 1990; Bell et al., 2011; Park et al., 1989; Stilley et al., 2010). Since online venues lack physical presence and therefore may not excite our senses, we do not expect these venues to stimulate unplanned purchasing behaviour. To assess whether unplanned purchases are higher for offline shoppers we propose the following

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9 research question: is the number of unplanned purchases higher for offline shoppers compared to online shoppers?

Online and physical venues were once two separate worlds. However, with technological improvements and the rise of e-commerce, the differences between online and offline are blurring rapidly and channels become substitutes. Yet, physical proximity lacks for online shopping venues. Unique factors associated with physical stores are the possibility to experience store atmosphere, the ability to touch products, and possess products immediately after buying. We argue that these unique factors influence motivations of consumers in choosing shopping locations. We expect consumers who attach importance to these unique factors to prefer offline shopping. These offline visits result in more unplanned purchases because consumers are expected to get inspiration from the physical store experience. Indirectly, the importance consumers attach to store characteristics thus influences the number of products consumers buy. To test this, the final research question states: are store characteristics of influence on the number of products bought?

Despite the vast amount of literature focusing on online and offline venues, significant gaps remain. That is, research on unplanned purchases is largely applied to offline venues (Abratt and Goodey, 1990; Stilley et al., 2010; Park et al., 1989) and not to online venues. Recent research looked into budget deviation (Stilley et al, 2010), browsing and shopping behaviour (Hui et al., 2009), social influences (Zhang, et al., 2014) and factors influencing unplanned purchases (Bell

et al., 2011; Hui et al. 2013; Inman et al., 2009) where all studies focus upon retail store visits. What is new in this paper is that a) the influence of inspiration and b) unplanned purchases are explored for conventional and online channels. We argue that unplanned purchases are more likely for the offline environment than for the online environment. The difference in number of unplanned purchases is the result of the (un)recognized need for inspiration which motivates consumers to visit conventional retailers. Therefore, we argue that inspiration is the distinguishing factor for offline venues to compete online venues. A stronger focus on inspiration increases sales and helps retailers to differentiate from online competitors (Böttger, 2015). The contribution of this research is to show that differences remain between online and offline venues. Therefore, we expect traditional markets to stay in business in the future.

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10 The structure of this paper is as follows; the first section begins with a review of relevant literature. This literature review contributes to the design of two studies. Each study presents its own method, hypotheses, results, conclusion, discussion and limitations. The two studies are followed by a general discussion of findings, limitations and implications for future research. Study 1 aims at answering the question whether the search for inspiration induces consumers to shop offline. It tests the difference in perceived level of inspiration between online and offline venues by executing an online survey. Respondents of this survey were present in the network of the researcher, and voluntarily filled out the online survey. Study 2 aims at answering the second and third research question. Visitors of a physical and online store were asked to participate in a survey asking for actual (un)planned purchasing behaviour and motivations.

Results of study 1 show that the need for inspiration induces shoppers to visit offline venues. Furthermore, there is enough evidence that respondents do not value both venues equally as a source of inspiration. When there is no conscious need for inspiration or consumers already know what product to buy, the choice of venue is less evident. Results of study 2 indicate that offline shoppers show a higher percentage of unplanned purchases. In addition, outcomes confirm that the greater the importance attached to physical store characteristics, the higher the number of products bought per year offline is.

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2. THEORETICAL FRAMEWORK

To understand why consumers shop online or offline, requires to apprehend consumers’ motivations to choose shopping locations. Substantial research focuses on motivations to shop offline (for a review, see Baker et al., 2002), motivations to shop online (Lieber and Syverson, 2012) and comparing and contrasting both channels (e.g. Broekhuizen, 2006; Gupta et al., 2004; Kacen et al., 2012; Levin et al., 2005). The next section briefly reviews the existing literature on why consumers (not) shop online. This gives a better insight in shopping behaviour and exposes the gaps in the existing literature.

2.1 Why do consumers (not) shop online?

Researchers recognize that consumers shop differently depending primarily on experiential or goal-oriented shopping motivations (Babin et al., 1994; Broekhuizen, 2006). Experiential or hedonic shopping experiences are defined as fun, amusing, fantasy and sensory stimulating (Babin et al., 1994; Arnold and Reynolds, 2003). Conversely, utilitarian or goal-oriented shopping motivations are characterized as task-related and rational (Babin et al., 1994; Arnold and Reynolds, 2003). According to Wolfinbarger and Gilly (2001) 66 to 80 percent of online purchases are goal-oriented. This goal-oriented behaviour involves consumers considering and evaluating product-related information prior to purchase (Babin et al., 1994). Time-constrained consumers with a need for efficiency and a narrowly focused search explain the relatively high percentage of online goal-oriented purchases (Wolfinbarger and Gilly, 2001). Another advantage of shopping online is the convenience it gives from shopping anywhere, at any time. This convenience saves consumers time and money since no transport costs are involved (Chiang and Dholakia, 2003; Wolfinbarger and Gilly, 2001). Empirical findings show that consumers appreciate online shopping for their quick shopping as it is assessed faster than visiting a physical retailer (Levin et al., 2003). Among other advantages of online shopping are the rapid and extensive display of information (Szymanski and Hise, 2000; Wolfinbarger and Gilly, 2001), creating a convenient comparison of attributes of multiple brands (Levin et al., 2003), the possibility of locating hard-to-find items, the opportunity to make discrete purchases (Browne et al., 2004) and the wide selection of products (Srinivasan et al., 2002; Szymanski and Hise, 2000). Furthermore, search cost have decreased with the wide availability of information on the Internet (Lynch and Ariely, 2000), especially with the help of recommendation tools (Häubl and

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12 Trifts, 2000). These recommendation tools, such as reviews of other customers, “others have also bought” and top 10 most popular products, help consumers in their search for products online. However, consumers still have their reasons not to shop online. According to research by Jo Black et al. (2002) consumers want to talk to an employee when a product is bought. Moreover, customer service features such as helpful and knowledgeable staff and the ease of returning products, are important characteristics for conventional retailers (Kolyesnikova et al., 2010). Results of research by Levin et al. (2003) show that offline shopping scores higher on enjoyable shopping experience, personal service and easier exchange. Broekhuizen (2006) indicates that the online environment creates uncertainty because of the physical and temporal distance between consumers and retailers. This distance makes it more difficult to assess product characteristics and retailer identities. Furthermore, immediate possession can clarify why consumers rather buy offline than online (Levin et al., 2003; Lieber and Syverson, 2012) since consumers have to wait before online purchased products are delivered. This delivery lag weakens the power of immediate satisfaction and discourages impulse buying (Francis and White, 2004; Rohm and Swaminathan, 2004; Wolfinbarger and Gilly, 2001). Levin et al. (2003) and Li et al. (1999) argue that not being able to see, examine or experience products prior to purchase inhibits consumers to shop online.

In sum, online and offline channels have their advantages and disadvantages. To understand the substitutability of channels, it is necessary to comprehend motivations that induce consumers to make use of these channel advantages. Faster delivery and widely available information on products, ensure that online and offline channels are better substitutes. Virtual shopping experiences approximate the physical experience through interactive features such as search engines, (3D) photographs of products, online comparison and review services, virtual tours, full motion, close-up pictures, zoom-in functions, 3D virtual models and sound videos of products (Kim et al., 2007; Kolyesnikova et al., 2010). Though virtual shopping and physical shopping experiences are more equal, there are still distinct differences. The next section elaborates on three matters that we think are key factors for consumers in choosing an online or an offline venue for their purchases. First, this is the need for inspiration, which we think is valued as better for offline shopping because consumers get inspired from the physical store experience. Secondly, we expect customers who appreciate physical proximity to products to be more likely

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13 to visit offline venues. Lastly, we expect immediate possession to be of influence on venue choice. Immediate possession is possible for purchases made at offline venues, whereas shopping online always entails delivery time.

2.2 Distinct differences between venues

2.2.1 Customer inspiration

Inspiration is evoked by triggers (e.g. a person or idea) and targets the direction towards which the motivation is orientated (e.g. personal goal or purchase) (Thrash and Elliot, 2003). Shopping for inspiration therefore entails keeping up with trends and new fashions while at the same time seeing new products and innovations. By catering those needs and inspiring shoppers with new product ideas, retailers can attract customers and prevent them from visiting online competitors (Rudolph et al., 2013). Wolfinbarger and Gilly (2001) state that consumers buy online when they have a specific purchase in mind. This is confirmed by Broekhuizen (2006) who shows that 73.5% of respondents who bought their last book online knew exactly, prior to purchase, what book to buy, while only 49.4% of respondents who bought their last book offline had a predetermined book in mind. Moreover, research by Rudolph and Weber (2012) indicates that many consumers are open to new ideas while shopping offline, as about half of them have a specific product in mind. The search for new ideas might even be the main motive to shop offline (Arnold and Reynolds, 2003). Furthermore, results from Broekhuizen (2006) show that prior to offline purchases, 16% of respondents use the Internet to get inspiration, whereas 56% of respondents use the Internet to search for specific book content. This indicates that consumers engage in goal-oriented search behaviour while shopping online (Broekhuizen, 2006) which affirms our theory that shoppers have predetermined products in mind when they visit online stores. One explanation for this difference in goal-oriented behaviour could be the distance between consumers and retailers while shopping online, as opposed to physically encountering stimuli (triggers) that evoke inspiration when visiting offline venues. We expect offline consumers to be less goal-oriented, and therefore open to new ideas and products. Surprisingly, to our knowledge, there is no research that explicitly studies the causal relation of the search for inspiration and venue choice. Our paper extends prior research on inspiration and applies it to online and offline channels.

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14 Online and offline venues try to inspire customers by the use of recommendations. Recommendations are primarily conceived as information source (Senecal and Nantel, 2004). Andreasen (1968) proposes the following division of information sources: impersonal advocate (e.g. media), impersonal independent (e.g. recommendations by other consumers or consumer reports), personal advocate (e.g. salespeople) and personal independent (e.g. friends and family). Research by Grewal and Sharma (1991) shows that the interaction with salespeople positively affects the number of purchases. Likewise, Reynolds and Beatty (1999) and Beatty et al. (1996) show that salespeople who engage in well-established associations with consumers, enjoy a greater share of customer purchases. Findings from a study by Zhang et al. (2014) reveal that interactive social influences (e.g. salespeople contact, conversations with other customers) tend to encourage longer store visits, thereby increasing product interaction and purchases. Furthermore, customer-salespeople interaction shows to be of influence in increasing sales for traditional retailers (e.g. Bagozzi, 1978; Davis and Silk, 1972; Grewal and Sharma, 1991; Park and Lennon, 2006). Research by Stern (1962) confirms that unplanned purchasing occurs when consumers are motivated by salespeople who evaluate quality, functions and usefulness of products that consumers had no previous knowledge of. Thus, salespeople can directly stimulate purchases by helping customers or recommending them products when asked for.

Online venues recommend customers in a different way since face-to-face customer-salesperson interaction is not possible. Online recommendations are divided into three categories: other consumers (e.g. relatives, friends and other users), human experts (e.g. sales staff) and experts systems such as recommender systems (e.g. “others have also bought”) (Senecal and Nantel, 2004). Results of Senecal and Nantel (2004) and Häubl and Trifts (2000) show that all three online recommendation sources are of influence on online product choices. The recommender system is the most influential, even though it is perceived as possessing less expertise than human experts and less trustworthy than other consumers (Senecal and Nantel, 2004). Brown and Reingen (1987) argue that information received from sources that have specific knowledge about consumers is more influential than sources without any customer knowledge. This is an explanation as to why recommender systems, which analyse customer behaviour and antecedents, provide customers with better personalized information than recommendation sources (e.g. other customers).

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15 However, to receive direct recommendations from salespeople or recommender systems, pre-purchase information of customers is needed. Examples of prepre-purchase information are the type of product a consumer is looking for or information on previously bought products. However, conventional retailers not only influence consumers via direct recommendations. Conventional retailers indirectly influence consumers by exploiting store atmosphere experiences and in-store stimuli. In-store stimuli such as on-shelf positioning, sampling and in-store siting (Abratt and Goodey, 1990) stimulate the recognition of items needed or wanted. An advantage of in-store stimuli is that no individual customer prepurchase information is needed for designing recommendations. Thus, store recommendations show to be of influence on inspiring customers. Moreover, physical proximity to recommendations also improves its usefulness. The next section elaborates on the existing research on physical proximity.

2.2.2 Physical proximity

The possibility of touching products when shopping offline is another distinct difference between online and offline venues. We adopt the definition of touch from Peck and Childers (2003) as being “a form of direct experience with a product and examine product, individual, and situational factors that enhance or impair the use of touch information during product evaluation”. Research on the effect of people touching people proves to influence behaviour. An example is a study by Crusco and Wetzel (1984) which shows that waiters who briefly touch customers receive larger tips than waiters who do not touch customers. Briefly touched individuals are more willing to sign a petition (Willis and Hamm, 1980). Furthermore, Hornik and Ellis (1988) show that shoppers are more willing to participate in a mall intercept interview when they are touched. However, the literature on the effect of touch on purchasing behaviour is limited. Peck and Wiggins (2006) show that touching products has a persuasive influence on consumer behaviour. Whereas physically inspecting products is possible for in-store environments, are the possibilities for remote environments to examine representations of the actual product limited by means of pictures or written descriptions (McCabe and Nowlis, 2003; Wood, 2001). The sense of touch can add information to purchase decisions, and therefore customers visiting physical venues are more likely to do so (McCabe and Nowlis, 2003). Attitudes towards products show to increase from touching products and in addition promote purchase intentions towards the product (Peck and Childers, 2003). The need of direct product experience in product evaluation shows the be an inability for products that are sold online

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16 (Citrin et al., 2003; McCabe and Nowlis, 2003). Experiencing products by seeing and examining prior to purchases show to be inhibitors of online shopping (Levin et al., 2003, Li et al., 1999). Therefore, offline shopping is rated as better for attributes related to the experience and delivery processes such as “see-touch-and-handle-the-product” (Levin et al., 2003). Lastly, Peck and Childers (2003) conclude that there are individual differences in consumers’ “need for touch” (NFT), which means that there are differences in preferences and motivations for collecting information through touch. Therefore, in situations with a higher NFT we expect consumers to prefer shopping at conventional retailers.

Physical proximity not only enables touching and evaluating products, but also gives consumers the possibility of the direct ownership of products (Rohm and Swaminathan, 2004). Delivery lags are still present for online purchases (Levin et al., 2003; Lieber and Syverson, 2012) whereas immediate possession of products is possible for shopping at conventional retailers. Immediate possession is thus a distinct difference between online and offline venues. Results of a study by Levin et al. (2003) show that attributes related to the search process, such as quick shopping and large selections are rated better online than offline. Speedy delivery and no hassle exchange are rated better for offline shopping (Levin et al., 2003). According to results from a study by Kacen and Lee (2002), are highly impulsive buyers likely to have a subjective bias in favour of immediate possession. Immediate possession gives individuals immediate gratification and therefore influences the choice of purchasing venue (Hoch and Loewenstein, 1991). The desire for immediate gratification and the corresponding impatience is based on the economic concept of discounting (Hoch and Loewenstein, 1991). According to this view, individuals are disproportionately attracted to immediately available rewards. Hoch and Loewenstein (1991) argue that next to impatience and the importance of discounting, a shift in a consumer’s reference point can cause a sudden increase in desire for products. Reference points reflect the fact that individuals are less concerned with absolute attainments than with attainments relative to some relevant comparison point (Hoch and Loewenstein, 1991). Research by Kahneman and Tversky (1979), Thaler (1985) and Tversky and Kahneman (1991) shows that consumer decisions are made with regard to reference points and that expectations are the source of reference points. Thus, reference-point shifts influence the way consumers react to the notion of owning or consuming a product that has not been purchased yet. Perhaps the most powerful inducer of reference-point shifts is physical proximity (Hoch and Loewenstein, 1991). Mischel

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17 (1974) and Mischel and Grusec (1967) show that physical proximity to rewards shifts reference-points. These reference-point shifts make subjects less willing to delay their gratification. Moreover, increasing temporal proximity not only increases desirability but also impatience for owning the product (Hoch and Loewenstein, 1991; Ainslie and Haendel, 1983; Benzion et al., 1987). Online consumers can postpone purchase due to the ease of returning to websites later after further thought (Wolfinbarger and Gilly, 2001) whereas proximity to products increases the desirability for them, increasing the likelihood of purchase.

2.3 (Un)planned purchases

In sum; the current literature provides evidence that customer inspiration and physical proximity are of influence on the choice of purchasing venue. However, we find indications that customer inspiration and physical proximity are also of direct influence on the number of purchases. For instance, individuals with higher NFT are more likely to make unplanned purchases (Peck and Childers, 2006). We adopt the definition of unplanned purchases from the Popai/Du Pont study (1977) as being “all purchases where consumers buy an item that was not planned at all.” Unplanned purchases are not the same as impulsive purchases. Impulse buying is associated with the powerful urge to purchase products as opposed to a forgotten “need” or “want” which relates to unplanned purchases. Findings suggest that impulse buying can typically be categorized as unplanned, but unplanned purchases cannot always be categorized as impulse buying (eg. Kacen et al., 2012; Verhagen and van Dolen, 2011; Zhang et al., 2010). That is, unplanned purchases are not driven by an uncontrollable urge to buy products, but consumers end up with items other than those items that provided the initial rational to go shopping in the first place (Earl and Potts, 2000). The current literature fails to address the way inspiration and physical proximity influence the number of unplanned purchases for e-tailers and retailers. Particularly for offline settings, proper investigation of the effects of inspiration and proximity on unplanned purchases could help retailers to sustain their position in the market. This thesis investigates that. However, we first review the current state of literature on unplanned purchases.

Prior research by Kollat and Willet (1967) finds that unplanned purchasing is positively related to transaction size but negatively related to shopping lists. In addition, these researchers find that unplanned purchases are a response to out-of-stock products. According to research by Granbois (1968) unplanned purchases increase with the time spent in a store, the number of aisles shopped

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18 and the number of people shopping together. Results from Park et al., (1989) show that unplanned shopping is most likely when visiting unfamiliar stores and when no time pressure is perceived by consumers.Also, Bucklin and Lattin (1991) show that the probability of unplanned purchases is higher for low-loyalty stores and for households looking for deals. Furthermore, Beatty and Ferrell (1998) indicate that individual differences in the propensity for impulsiveness significantly influence unplanned purchasing. Drawing on the individual preferences literature, Rook and Fisher (1995) demonstrate that normative evaluations temper the acceptability of buying. This means that unplanned buying for oneself is not valued as appropriate but purchasing a gift on an impulse is. More recent studies looked into budget deviation and find that consumers have mental budgets for shopping trips which include room to make unplanned purchases (Stilley et al., 2010). Hui et al. (2009) find a positive effect of in-store travel distance on unplanned spending. Furthermore, recent research from Zhang et al., (2014) shows that social interactions with salespeople tend to slow shoppers down, consequently encouraging longer store visits, thereby increasing product interaction and purchases. Consumer in-store activities, such as the number of aisles shopped, also increase unplanned purchases, as research by Inman et al. (2009) demonstrates. Bell et al. (2011) show that unplanned purchasing increases monotonically with the abstractness of the shopping goal held by the buyer prior to entering the store. Respondents of a study by Wolfinbarger and Gilly (2001) state that their buying consists largely of planned purchases whereas their offline buying entail more unplanned purchases.

A common theme across these articles is the focus on offline venues, especially grocery stores, for unplanned purchases (e.g. Bell et al., 2011 Hui et al., 2009; Kollat and Willet, 1967; Park et al., 1989; Stilley et al. 2010). Since online grocery shopping is still quite small (Halzack, 2015), it is interesting to focus upon other product categories which are often bought online and offline. Despite the increase in the use of the Internet for shopping, the literature focusing upon both venues is limited. This thesis complements previous work by examining offline and online unplanned shopping behaviour for another product category than those found at grocery stores.

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3. STUDY 1

Study 1 answers the research question: does the search for inspiration induce consumers to shop at conventional retailers? To test this, data was collected by means of a survey. Collecting data via a survey is a quantitative method to generalize results from a sample to the population of interest. The population of interest in this case is consumers buying books online and offline. The survey that was used included vignettes. Vignettes are short stories or scenarios that describe hypothetical situations to which a respondent is asked for his or her reaction (Martin, 2004). The use of vignettes is primarily based on the assumption that this method yields incentive-compatible results (Cummings et al., 1995; Martin, 2004). In other words; answers given are assumed to hold when the hypothetical situations occur in real-life.

3.1 Method 3.1.1 Participants

Participants of this survey were 156 respondents from an online survey (58% women). The participants were on average 31 years of age (SD = 12.07).

3.1.2 Procedure

The data used in this study was collected via an online survey which focused on the product category books. The focus is on books because these are unique products, irrespective of the location where these are bought. Books can be identified by their title and specific ISBN number. Often, books are valued as ‘search goods’ (Nelson, 1970; Gupta et al., 2004; Girard et al., 2002; Levin et al., 2003). For search goods like books, quality is easier assessed prior to purchase than after purchase. Before purchasing search goods there may be the need to examine the good which makes offline shopping more straightforward since inspection is possible. Research shows that there is an equal preference for online and offline venues for searching and comparing books, although there is a strong preference for actual offline purchasing (Levin et al., 2003). Results from Gupta et al. (2004) indicate that there is a 52 percent tendency to switch between venues for purchasing books. Therefore, books are an interesting category since it concerns unique products, irrespective of the purchasing channel, for which research shows that searching, comparing and purchasing is done on an equal base for both venues.

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20 An online survey including vignettes was used to get more information on which situations encourage online shopping and which encourage offline shopping. Vignettes enable researchers to collect data that could not otherwise be collected at all, or only for a small number of cases (Martin, 2004). For this study, the efficiency of vignettes is that respondents did not need to experience a specific situation in order to interpret how they would react if they would experience it. Gathering data for all situations in which respondents had actually experienced them, would have delayed the process (Martin, 2004). The vignettes used in this study focus on the purchase of books in different kinds of situations. For online surveys, respondents have complete control with regard to how questions are read and comprehended (Gupta et al., 2004). Since we expect the questions and vignettes used in this survey not to be assessed as complex situations, nor situations that are very unlikely, we expect every respondent to understand the question or situation in the same way. The survey was posted online in July 2015, via the online survey program Qualtrics. Appendix 7.1 presents this survey. This survey was anonymous, demographics asked for were age and gender of the respondents. The link to this survey was posted on the social media website Facebook. Family, friends and acquaintances could click on the link and fill out the survey. However, there is one concern to this way of collecting data and that is that of nonresponse bias. Nonresponse bias arises when characteristics of the respondents are systematically different from characteristics of non-respondents (Hudson et al., 2004). That is, Facebook users present in the network of the researcher may not be representative of the target population since the variety in background (e.g. education, age and gender) can be limited. However, since 99.4% of respondents indicated that they had ever shopped online and 87.8% of respondents indicated they had shopped at an online bookstore, we expect answers to be representative of the non-respondents too. Furthermore, those individuals who did not have access to the Internet were not given the possibility to fill out this survey. However, research indicates that 97% of the Dutch population had Internet access in 2013 (CBS, 2016), which decreases the possibility that people did not fill out this survey because they had no Internet access.

3.1.3 Measures

The survey contained sixteen questions. The first two questions asked for online shopping behaviour, in particular shopping behaviour with respect to buying books online. Questions three and four asked for the number of hard copy books bought per year and how many of those were

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21 bought online. Questions five until nine contained vignettes, describing brief scenarios, measured the need for customer inspiration in combination with the choice of venue. The definition of customer inspiration is adopted from Böttger (2015) as a “cognitive and motivational state that is evoked by stimuli, incorporating the realization of new or enhanced consumption-related insights, and motivates customers to purchase products or services.” Respondents were asked to assess the likelihood in each situation that they were going to buy a book in an online bookstore and at a conventional bookstore. Answers were on a seven-point Likert scale, ranging from very unlikely (1) to very likely (7). To preserve realistic situations, vignettes were based on actual situations, and respondents were asked to project themselves into a vignette situation and rate the likelihood of choosing a venue (Martin, 2004). To understand which location would be chosen for buying products in certain situations, five scenarios were presented to respondents. Two scenarios in which the respondent did not know what product to buy, assuming a high need for inspiration, and three situations for which the respondent was already sure of what product to buy, assuming a low need for inspiration. To test whether there were significant differences in likelihood of visiting online and offline venues per scenario, a Wilcoxon Signed-Rank test was performed. This test was chosen because the data was ordinal, which made it possible to rank the observations. The Wilcoxon Signed Rank test tests that the median of the differences between answers to the likelihood of buying online and offline, equals zero.

In addition, questions 10 and 11 asked for more background on the importance respondents attached to the availability and characteristics of physical and online bookstores, again on a seven-point Likert scale, ranging from not at all important (1) to extremely important (7). Questions 12 and 13 requested reasons for buying books online or at physical venues, where multiple answers were possible. Question 14 asked for the gender and question 15 asked for age of the respondent. The final question gave the opportunity to leave a comment.

3.2 Hypotheses

Hypothesis 1: In situations assuming a higher need for inspiration, the likelihood of choosing an offline venue over an online venue for making purchases is higher.

The main hypothesis of this study is that the search for inspiration induces consumers to shop at offline venues. Research by Broekhuizen (2006) shows that from the respondents that bought their last book online nearly 50% had a predetermined book in mind. By using vignettes to

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22 hypothesize situations in which consumers are uncertain of what book to purchase, assuming there is a high need for inspiration, we expect respondents to be more likely to visit offline venues than online venues. Inspiration can also be searched for on the Internet but this usually requires consumers to have some idea or category for which they are looking for. When consumers have no idea what to buy, it will be difficult for online venues to adapt to the needs of consumers since usually some idea is needed to offer consumers alternatives or ‘others have also bought’. Furthermore, without webshops having any idea about who is visiting their website and what products the customer has bought before, it will be difficult to generate algorithms that calculate recommendations. For physical venues inspiring consumers is easier since these stores are often sorted per category e.g. travel books, thrillers, novels or literature. Presenting customers with ‘top 10’ books or with books that did not have much attention inspires customers without even actively searching for or noticing it. Thus, expectations are that the search for inspiration is appreciated more offline since in-store stimuli present the consumer with new ideas as opposed to actively searching for inspiration on the Internet.

For hypothetical situations assuming there is a low need for inspiration, we expect the opposite. Wolfinbarger and Gilly (2001) argued that more than 60 percent of online purchases were goal-oriented. Results from Broekhuizen (2006) likewise confirmed that online book purchases tended to be more goal-directed than offline book purchases; nearly 75% of the respondents exactly knew what book to buy prior to purchase. Furthermore, it is generally accepted that search costs are lower for online than for offline markets (Lieber and Syverson, 2012) because consumers do not have to travel to offline venues but rather order products from behind their computer. Therefore, we expect that in situations for which consumers know what product they want to purchase, no inspiration is needed and thus consumers will order these products online since this gives them more convenience and saves time.

Hypothesis 2: Physical stores are more important as a source of inspiration than online stores.

To capture the general thought on the perceived level of inspiration attached to stores, the importance respondents attach to stores as a source of inspiration was asked for. Hypothesis two assesses the difference in importance between physical and online stores as a source of inspiration. When physical stores are valued as more important as a source of inspiration, it will

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23 indirectly entail that consumers use the offline venue for inspiration, more than using the online venue.

3.3 Results

3.4.1 Descriptive statistics

Of the 156 respondents, 58% were female and 42% were male. The mean respondent age was 30.94 (SD = 12.07), the median and mode were both 25 for age. The youngest respondent was 19, the oldest was 64. Table 1 summarizes the sample characteristics.

Table 1 Sample characteristics online vignette survey

Sample Sample size (N) 156 Female (n) 91 Mean age 30.94 (SD = 12.07) Median age 25.00 Mode age 25 Minimum age 19 Maximum age 64 3.4.2 Hypotheses testing

Hypothesis 1: In situations assuming a higher need for inspiration, the likelihood of choosing an offline venue over an online venue for making purchases is higher.

Hypothesis 1 concerns the likelihood of choosing an offline venue over an online venue for making purchases in situations assuming a high and low need for inspiration. The design of the study asked respondents for both the likelihood of buying the product online and offline. Two vignettes concerned situations for which respondents had no idea what to buy prior to entering the store and three vignettes concerned situations for which respondents had a predetermined book in mind. The first vignette of the first category concerned a book for a vacation, the second vignette concerned a book for a friends’ birthday. In both situations it was clear that respondents did not know what book to buy. We expected that in these situations respondents would score higher on the likelihood for offline venues than online venues since visiting offline venues inspires buyers for their purchases. The first vignette of the second category concerned a book recommended by a friend, the second a book recommended by a television program and the third

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24 a book needed for a language course. In all three situations it was clear that respondents wanted or needed to buy the book. We expected that in these situations respondents would score higher on likelihood for online venues since the ease of ordering online would prevent people from going to physical venues. Table 2 presents the medians of answers to these vignettes.

Table 2 Medians of answers to vignettes

Likelihood visiting online bookstore Likelihood visiting physical bookstore

Holiday (high) 3.00 6.00

Friends’ birthday (high) 3.00 6.00

Recommendation friend (low) 6.00 5.00

Recommendation TV (low) 5.00 5.00

Language course (low) 7.00 3.00

Note: answers were on a 7-point Likert scale; (1) very unlikely (2) unlikely (3) somewhat unlikely (4) undecided (5) somewhat likely (6) likely (7) very likely.

Overall, there are differences in likelihood of visiting online and physical stores. Comparing medians for both venues indicates that the likelihood of visiting online bookstores is higher when we assume a low need for inspiration. Conversely, results show that the likelihood of visiting physical bookstores is higher when the need for inspiration is high. To assess whether these differences are significant, a Wilcoxon Signed-Rank test was performed. It compared answers for five vignettes asking for the likelihood of visiting online and offline venues. Results for the Wilcoxon Signed-Rank test are presented in table 3.

Table 3 Wilcoxon Signed-Rank tests of vignettes with a high/low need for inspiration

Holiday Friends’ birthday Recommended friend Recommended TV Language course Test statistic -6.57b (p < 0.001) -8.34b (p < 0.001) -1.564a (p = .118) -.465a (p = .642) -8.203a (p < .001) Sum ranks (negative) 1609.00 891.00 4428.00 4801.00 8640.00 Sum ranks (positive) 7571.00 8700.00 3198.00 4379.00 951.00

Notes: non-significant results are indicated by p-values. Exact significance used, 2-tailed. Test statistic is z-value and is negative as it is based on the smallest absolute value of ranks. Superscript ‘b’ indicates test-statistic is based on negative ranks, superscript ‘a’ indicates that it is based on positive ranks.

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25 For respondents, the likelihood of choosing physical bookstores (Mdn = 6.00) is higher than online bookstores (Mdn = 3.00), for finding a book for a holiday, assuming a high need for inspiration. Results of the Wilcoxon Signed-Rank test indicate that the positive sum of ranks is higher than the negative sum of ranks, z = -6.57, p < .001. This confirms that there is a significant difference in likelihood between venues. Furthermore, the average respondent shows to be more likely to visit a physical bookstore (Mdn = 6.00) to find a book for a friends’ birthday than an online bookstore (Mdn = 3.00), again assuming a high need for inspiration. Results from the Wilcoxon Signed-Rank test show that the positive sum of ranks is higher than the negative sum of ranks, with z = -8.34 and p < .001. Therefore, the likelihood of choosing the physical bookstore for purchasing a book for a friends’ birthday is significantly higher than choosing the online bookstore.

For respondents, the likelihood of choosing an online bookstore (Mdn = 6.00) is higher than for physical bookstores (Mdn = 5.00) for finding the book recommended by a friend, assuming a low need for inspiration. The Wilcoxon Signed-Rank test shows that the positive sum of ranks is lower than the negative sum of ranks. However, this result is not significant with z = -1.56 and p = .118. Answers to the second scenario assuming a low need of inspiration, show that the average respondent is just as likely to visit an online bookstore (Mdn = 5.00) to find the book recommended on the television program as visiting a physical bookstore (Mdn = 5.00), but this result is not significant with z = - .47 andp = .642. The Wilcoxon Signed-Rank test shows that the positive sum of ranks is lower than the negative sum of ranks. Answers to the fifth scenario show that the average respondent is more likely to visit an online bookstore (Mdn = 7.00) to find the book needed for the language course, than visiting a physical bookstore (Mdn = 3.00), which is significant with z = -8.20 and p < .001. The Wilcoxon Signed-Rank test shows that the negative sum of ranks is higher than the positive sum of ranks.

The above analyses presents mixed results. There is enough proof to reject the null hypothesis that in situations assuming a high need for inspiration, the likelihood of choosing an offline venue compared to an online venue for making purchases, is the same. However, since only one out of the three vignettes assuming a low need for inspiration rejects the null hypothesis, there are no strong arguments to presume that consumers choose online venues assuming a low need

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26 for inspiration. Other factors might influence the decision to buy online or offline when consumers know exactly what product to buy.

Hypothesis 2: Physical stores are more important as a source of inspiration than online stores.

The question to test hypothesis 2 asked for the importance respondents attach to online and offline bookstores as a source of inspiration. Answers were on a 7-point Likert scale, ranging from not at all important (1) tot extremely important (7). To assess whether there was a significant difference in importance between venues, a Wilcoxon Signed-Rank test was performed. Table 4 shows the results of this test.

Table 4 Wilcoxon Signed-Rank tests of importance of venues as a source of inspiration

Importance venue as source of inspiration

Test statistic -8.593a _{(p < 0.001)}

Sum ranks (negative) 8591.50 Sum ranks (positive) 724.50

Notes: Exact significance used, 2-tailed. Test statistic is z-value and is negative as it is based on the smallest absolute value of ranks. Superscript ‘b’ indicates test-statistic is based on negative ranks, superscript ‘a’ indicates that it is based on positive ranks.

The Wilcoxon Signed-Rank test indicates that offline venues were valued more important as a source of inspiration (Mdn = 6.00) than online venues (Mdn = 4.00), z = -8.59 and p < .001, and this difference is statistically significant. Concluding, there is enough evidence to reject the null hypothesis that the physical stores are just as important as a source of inspiration as online stores. 3.4 Conclusion, discussion and limitations

In sum, study 1 answers the research question whether the search for inspiration induces consumers to shop offline. Respondents are significantly more likely to visit offline venues assuming the search for inspiration is high (the respondent does not know what product to buy). As a respondent states: “for inspiration and advice I go to a bookshop, and I always enjoy going there”. Yet, results show that respondents are not significantly more likely to visit online venues assuming the search for inspiration is low (the respondent is already sure of what product to buy). This could result from the fact that consumers prefer to shop at offline venues, irrespective of the need for inspiration. Research by Babin et al. (1994) shows that shopping is often seen as an appreciation of the experience rather than simply completing a task. Results of the current

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27 study validate this with nearly 58% of respondents stating that they rather buy books at physical bookstores for the pleasurable experience. From the results of study 1 we find enough evidence that the search for inspiration induces consumers to shop offline. By focusing on inspiring customers, retailers strengthen their market position, making the complete cannibalization of retailers by e-tailers less likely. Online players may want to exploit ways to inspire customers, thereby competing conventional retailers.

Although this study has significant results, the study has some methodological drawbacks. First, it is well known that small changes in wording of questions can substantially affect responses (Schuman and Presser, 1981) presumably because it affects respondents’ interpretations of the meaning of questions (Martin, 2004). With this in mind, different framing of questions could have alternated results. However, we expect the scenarios easy to interpret and close to real life situations. The possibility of other results with a different framing is not considered very likely. Secondly, vignettes studies remain hypothetical. Thus, results can never fully meet results in non-hypothetical situations. However, the use of vignettes in this study is practical since it enables analysing data that otherwise would have taken more time to gather. Thirdly, we assumed situations for ‘high’ and ‘low’ needs of inspiration. These are very abstract assumptions and might not be the same for all consumers. Future research could evade this problem by presenting respondents situations and subsequently ask to rate the need of inspiration.

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4. STUDY 2

Results from study 1 show that the need for inspiration induces consumers to shop at offline venues, rather than visiting online venues. This is an indication that consumers perceive offline venues to be more inspiring than their online counterparts. Research shows that in-store stimuli are promotional techniques exploited to increase unplanned purchases of products (Abratt and Goodey, 1990). Even so, in-store stimuli trigger inspiration in the form of unrecognized needs and desires, or activate forgotten needs leading to more in store decision-making, or unplanned purchasing (Inman et al., 2009). This implies that unplanned purchases are higher for offline consumers than for online consumers since in-store stimuli are not fully replicable online. Thus, when offline shopping is valued as more inspiring, chances of buying more products than originally intended also increase. This section therefore investigates the second research question: is the number of unplanned purchases higher for offline shoppers compared to online shoppers?

When people in general value offline venues as more inspiring than online venues, we expect them to value characteristics stimulating inspiration as more important too. If consumers attach importance to these characteristics, especially those that are unique to physical venues and those that stimulate inspiration, these should be of influence on the number of unplanned purchases at physical venues too. When answers to the second research question confirm that unplanned purchases are higher for offline shoppers, the total number of products bought is also higher. Therefore, we expect consumers who value physical store characteristics as more important, to also buy more products offline per year. Consumers who attach less importance to these characteristics may be indifferent between online and offline buying. This section therefore also investigates the third research question: are store characteristics of influence on the number of products bought? Data for answering these questions was collected by conducting a survey at a local bookstore, and both online and offline consumers were asked to participate.

4.1 Method 4.1.1 Participants

Participants were 100 visitors of a physical bookstore (66% women) and 98 visitors of the online counterpart of this bookstore (59% women). The offline participants were on average 50 years of age (SD = 15.91) and the average age for the online participants was 49 (SD = 16.71).

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4.1.2 Procedure

A survey was used to collect data. The sample consists of customers of an online and physical bookstore. This sample enables comparing differences between these venues with respect to motivations and number of books bought. The same reasoning as in study 1 applies for investigating books; these are uniquely identified products, with an equal preference for searching and comparing online and offline. In addition, competition between and within channels is large since books are sold by numerous Internet and traditional retailers. Furthermore, research indicates that prices of books are the same on- and offline, and differentiation between books has little impact on prices (Clay et al., 2002), implying that prices are of little interest on the venue choice. Finally, Dutch regulation subjects publishers of books to fixed prices in the first year after publishing, therefore eliminating the possible influence of prices on venue choice.1 Thus, analysing the Dutch book market is an appropriate context since it involves homogeneous physical products with an approximate identical price, sold in a competitive market. This leaves room for exploring other influences of the decision making process in choosing an online or offline venue.

To explore actual (unplanned) purchasing behaviour and motivations, visitors of a bookstore with a webshop and two offline stores, were asked to participate in a survey. An advantage of exploring traditional bookstores above venues that offer other products next to books (e.g. department stores), is that consumer visits are solely aimed at buying books, not at other products. The bookstore is well-known in The Hague, and has 65 years of experience since its establishment in 1951. The knowledge, experience and wide variety of products attracts loyal customers, customers looking for specified products, and tourists. The physical stores are positioned in frequently visited shopping streets, and therefore the probability of interviewing a variety of shoppers with different backgrounds and intentions was large.

A survey was developed for the offline research sample. Appendix 7.2 presents this survey. This one-on-one survey of bookstore customers within the bricks-and-mortar setting was executed in June 2015. The methodology used is similar to those in studies conducted by Kollat and Willet

1_{The fixed book price is regulated by Dutch law since 2005 to prevent price competition and thus promote a broad}

availability and diverse range of books. The law obliges publishers to fix the retail price for a book, once it is published. This gives a book the same fixed price everywhere, at the bookstore, Internet retailer or supermarket. A publisher may adjust the price of a book after half a year, he may lift the fixed price of a book after one year (Wet op de vaste boekenprijs (Wvbp), 2015).

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30 (1967) and Abratt and Goodey (1990). Personal face-to-face interviews were conducted at the store check-out where buying intentions and actual purchases were recorded (Abratt and Goodey, 1990). It was essential that respondents had actually bought one or more books since actual purchasing behaviour was accounted for. Overall, 135 people were approached in the physical bookstores. Some customers did not want to participate in the survey for numerous reasons, such as no interest or no time. In three days’ time a final number of 100 respondents filled out the survey, resulting in a 74% response rate.

Like multiple studies (e.g. Kacen et al., 2012; Rohm and Swaminathan, 2004; Verhagen and van Dolen, 2011) an online survey, almost identical to the in-store survey, was used to collect the other half of the sample. Appendix 7.3 presents this online survey. Data was gathered from customers who completed an online transaction between May and June 2015 at the webshop of the same bookstore. An email was sent with an invitation to participate in this study. This invitation included a link to online survey program Qualtrics. The survey was anonymous, demographics asked for were age and gender of respondents. Of the 428 online customers who received an email with the invitation for filling in the survey, 98 responded. This gives a response rate of almost 23%. Approaching customers personally and not electronically could be a reason for the higher response rate in the offline sample. However, since the online and the offline sample exerted almost the same amount of respondents, the higher response rate for the offline sample is not expected to influence results.

4.1.3 Measures

The surveys contained eighteen questions in total, of which there were six on a seven-point Likert scale anchored by very unimportant and very important. The other questions were open-ended or in yes-no format. The last questions regarded gender and age. In both surveys, respondents had the possibility to leave a comment. To answer the second research question, whether the number of unplanned purchases is higher for offline shoppers compared to online shoppers, single purchase intentions were evaluated, procedures developed based upon prior research by Abratt and Goodey (1990) and Kollat and Willet (1967). We define unplanned purchases as all purchases that consumers forgot to put on their shopping list or which were not planned to buy before entering a store, including those purchases of which the consumer had a vague idea of, or which consumers did not know for sure that they were going to buy.

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31 The disparity between actual purchases and purchase intentions is used to determine the level of unplanned purchases. Unplanned purchases are calculated as a percentage of total purchases per visit. This is done to receive a relative percentage of unplanned purchases, which enables comparing online and offline venues. We want to determine whether there is a significant difference in percentages of unplanned purchases between online and offline shoppers. Regressing venue on the percentage of unplanned purchases should give an indication whether venue choice is of influence on unplanned purchases. We expect consumers who visit offline venues to make more unplanned purchases.

To answer the third research question, online and offline respondents were asked whether they used the information desks and recommendations while purchasing offline. Furthermore, the importance attached to the immediate possession of products, touching, seeing and examining products prior to purchase, and the store as an inspirational source, were asked for. In addition, respondents were asked for the number of books they buy per year and how many of those they buy online. Consequently, the number of books bought each year offline per individual was calculated. Subsequently, the total number of books bought offline per year was divided by the total number of books bought (offline and online) so to receive a percentage for the number of books bought offline each year. The use of information desks and recommendations, and the importance attached to possession, touch and the store as an inspirational source, are regressed on the number of books bought per year offline. We expect customers, who value physical bookstore characteristics as important, to show a higher percentage of books bought offline each year. If this expectation is confirmed by the results of the regression, maintaining and improving these characteristics could help physical retailers in attracting customers, thereby ensuring their market position.

4.2 Hypotheses

Hypothesis 1: Offline shoppers show a higher percentage of unplanned purchases per visit than online shoppers.

Several studies (e.g. Abbrat and Goodey, 1990; Böttger, 2015; Inman et al., 2009) argue that in-store stimuli may trigger in-in-store buying decisions. These in-in-store stimuli trigger unrecognized or forgotten needs and desires, which results in consumers purchasing more products than originally intended. Thus, in-store stimuli have the function of inspiring customers, with the aim

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32 of increasing the number of unplanned purchases. In addition, the study by Zhang et al. (2014) shows that social interaction increases product interaction and purchases. Since no in-store stimuli or social interaction applies to online venues and from study 1 we find that the search for inspiration induces shoppers to visit offline stores, we expect online shoppers solely buying the product aimed for. We propose that the difference in percentage of unplanned purchases is a result from in-store stimuli such as in-store siting, on-shelf positioning, promotions, sampling, point-of-purchase displays, coupons, and in-store demonstrations or readings (Abratt and Goodey, 1990). Even though interactive features of the Internet have improved in recent years, complete imitation of in-store stimuli is not possible for online retailers. Therefore, we expect a difference in the number of unplanned purchases for online and offline shoppers.

Hypothesis 2: The importance attached to physical store characteristics positively influences the number of products bought offline.

2a: The importance attached to physical stores as a source of inspiration positively influences the number of products bought offline.

From study 1 we find that the search for inspiration induces consumers to shop at physical venues. Hypothesis 2a tries to confirm this outcome by assessing the importance customers attach to physical stores as being a source of inspiration. When customers are looking for inspiration, we expect them to visit physical venues. When customers do not value physical bookstores as inspirational, we expect them to be indifferent between purchasing products online or offline.To test if offline shopping locations are valued as more inspiring than online venues, the importance respondents attach to the location as an inspirational source was asked for. With consumers appreciating the offline venue as a better source of inspiration we expect the number of products bought offline each year to increase too.

2b: The use of recommendations and/or information desks positively influences the number of products bought.

One of the reasons for consumers to shop at conventional retailers is the possibility of speaking to an employee prior to purchasing a product (Jo Black et al., 2002). This interaction between customer and salespeople is recognized as an important feature in augmenting sales in the traditional retail channel (Bagozzi, 1978; Davis and Silk, 1972; Grewal and Sharma, 1991; Park and Lennon, 2006). According to research by Stern (1962) unplanned buying happens when

The influence of inspiration on unplanned purchases : a comparison between online and offline venues