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An empirical investigation into e-shopping excitement: antecedents and effects Chanaka Jayawardhena Loughborough University Business School, Loughborough University, Loughborough, UK, and

Len Tiu Wright

E-shopping excitement

1171 Received April 2007 Revised January 2008 Accepted August 2008

Graduate Business School, De Montfort University, Leicester, UK Abstract Purpose – This paper seeks to examine the antecedents of online shopper excitement, its consequences for behavioural intentions as expressed by intent to return, and positive word-of-mouth communication. Design/methodology/approach – A conceptual model is developed based on the literature. Instrument item scales to measure all constructs in the model were as informed by the literature and adapted from prior studies. An online structured questionnaire survey was sent by e-mail to a UK consumer panel (n ¼ 626). The results were analysed using LISREL 8.7. Findings – Convenience, involvement, attributes of the web site and merchandising all collectively influence shopper excitement. The attributes of the web site and merchandising directly influence intent to return. E-shopper excitement leads to positive word-of-mouth (WOM) and increases the intent to return. Research limitations/implications – The study may be limited in that no differentiation is made between the types of goods that e-consumers purchased. A future extension of this work could be to investigate how the study can be applied to various products, including experience goods such as entertainment. Practical implications – It is shown that shopping excitement can increase intent to return and positive WOM. Understanding online shopper excitement can explain some of the reasons why consumers shop online, which in turn can help e-tailers improve their offerings to their consumers. Originality/value – The study presents a comprehensive model of online shopper excitement. This is the first study to validate such a model empirically, and therefore the study adds to the understanding of the antecedents and consequences of consumer excitement in the online shopping environment. Keywords Internet shopping, Consumer behaviour Paper type Research paper

Introduction Today’s e-commerce landscape is characterised by very high competition (Belanger et al., 2002) and a marketplace is changing at a very dynamic pace (Keen et al., 2004; Jayawardhena, 2004a). Practitioners and academics alike have argued that an essential strategy for success and in today’s marketplace is the creation and maintenance of satisfied and loyal customers (Arnold et al., 2005). Increasingly, e-shoppers are becoming more sophisticated and more experienced at shopping online. Online shoppers are looking for enjoyment (Koufaris et al., 2001/2002) and excitement (Jayawardhena, 2004b) in their shopping experience. Successful e-tailers have gone to

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great lengths to enhance shopper experience (Keen et al., 2004) and emphasis appears to be increasingly placed on the virtual environment in e-tailing and its effects on consumer evaluation of e-shopping web sites and shopping behaviour. There is a growing stream of research that examines the factors that influence e-shopper attitudes (Eroglu et al., 2001, 2003) and mood (Park et al., 2005), online service quality (e.g. Parasuraman et al., 2005), online satisfaction (Evanschitzky et al., 2004), intention to purchase (Loiacono et al., 2002), and intention to revisit sites (Rice, 2002). Nevertheless, this growing body of research still does not appear to address a question that e-tailers in this extremely competitive environment now face: how do e-tailers provide an enjoyable and exciting shopping experience for e-shoppers? What are the behavioural outcomes of excited e-shoppers? Despite the proliferation of research concerning online shopping, to the best of the authors’ knowledge, no single study has attempted to examine both the antecedents and consequences of online shopper excitement. The aim of this study is to fill this research gap by conducting an empirical study of e-shopper excitement. More specifically, the objectives of the study are twofold: (1) to examine four antecedent factors as determinants of excitement, namely convenience, attributes of the web site, merchandising and involvement; and (2) to assess the consequences of excitement on behavioural intentions, namely intent to return and word of mouth communications. The paper is organised as follows. First, the existing literature is discussed in order to develop the theoretical background and the conceptual framework to the study. In this section, factors having an influence on shopper excitement and its consequences are proposed. Thereafter, we describe the methodology used in the study, including the sample, measures and scales generated. We also present the subsequent analysis and results in this section. Next, we discuss the findings of the research in terms of both its theoretical and practical implications. Last but not least, we present directions for future researchers to consider along with limitations of this study. Theoretical context After a considerable period in which consumers were assumed to make largely “rational” decisions in purchase behaviour, marketing scholars are increasingly examining the influence of emotions evoked by marketing stimuli (Laros and Steenkamp, 2004). Emotions are responses to causal-specific stimuli that are generally intense and more enduring, especially if emotional traces are stored and retrieved (Cohen and Areni, 1991) and excitement is a specific positive emotional descriptor as illustrated by Richins (1997). Similarly, Russell (1980) describes excitement as a positive emotional state that consists of high levels of pleasure and arousal. The distinction between feelings and emotions is important since feelings are also responses to causal-specific stimuli, yet less intense and more fleeting as compared to emotions (Agarwal and Malhotra, 2005). Moods on the other hand are affective states (in the context of this paper we use the term “affective states” to reflect the emotional state induced rather than in the “attitude towards the ad” model). However, moods are non-object specific and may be quite transient and easily influenced by little things (Agarwal and Malhotra, 2005). The pervasive influence of emotional response has long been recognised by marketing researchers in various contexts, such as advertising, product consumption,

and shopping (Machleit and Eroglu, 2000; Wakefield and Baker, 1998; Westbrook, 1987; Batra and Holbrook, 1990; Cohen, 1990). Specifically, past retailing research has shown that store atmospherics can evoke emotional responses in shoppers (Wakefield and Baker, 1998; Donovan and Rossiter, 1982; Darden and Babin, 1994). In retail settings, design elements are construed to provide consumers with a satisfying shopping experience and to project a favourable retailer image. By manipulating all the available ambient factors, retailers strive to induce certain desirable emotions in their patrons (Wakefield and Baker, 1998). Similarly, it can be argued that upon entering (browsing) an e-tailer’s web site environment, an individual may experience emotions. An understanding of positive emotions (as represented by excitement) in the e-tailer’s environment can lead to a greater comprehension of the role that excitement play in influencing shopping behaviours and outcomes. The model shown in Figure 1 postulates that four variables (i.e. attributes of web site, merchandising, convenience and involvement) directly influence excitement, which in turn leads to two behavioural intentions: (1) intent to return; and (2) positive word-of-mouth communications.

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The conceptual foundations in the model are offered next. For some links specific conceptual evidence is not clear enough to warrant a formal hypothesis. Therefore, we defer from offering formal hypotheses and provide preliminary conceptual evidence. Consequences of e-shopper excitement Intent to return. Research indicates that consumers in all shopping mediums shop for both hedonic and utilitarian outcomes (Childers et al., 2001). Hedonic shopping value reflects an evaluation that interacting with an environment is rewarding for the sake of the experience itself (Babin et al., 1994). Emotional experience plays a primary role in creating this gratification. Excitement, a combination of pleasure and arousal (Russell, 1980), can create approach tendencies, unplanned purchases, and hedonic shopping value (Dawson et al., 1990). Approach tendencies or approach behaviours are seen as positive responses to an environment, such as a desire to stay in a particular facility and explore it, or intent to return to that facility. The association between approach

Figure 1. Conceptual model

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behaviours and pleasurable affective states have been reported by a number of researchers (Grewal et al., 2004; Raijas, 2002). Work by Donovan and Rossiter (1982) found that enjoyment of a retail experience results in more time being spent shopping and return patronage. Therefore, to the extent that a consumer associates excitement with an e-tailer, intent to return should increase. Intent to return fulfils two important goals: (1) increased intentions allow for greater shopping task fulfilment through the acquisition of goods, services and information, and through this fulfilment, utilitarian shopping value is increased; and (2) intent to return is associated with hedonic values through an increased desire to browse and continue gratification. Positive word-of-mouth (WOM). Positive WOM communication is defined as “oral, person-to-person communication between a receiver and a communicator whom the receiver perceives as non-commercial, regarding a brand, a product or a service” (Arndt, 1967; p. 5). Bringing the definition up to date might require reference to e-mail, online forums and virtual communities, but the non-commercial focus would remain (Gelb and Johnson, 1995). Kozinets (2002) defines types of virtual communities from their primary group focus and social structure, where loyalty and heavier usage of products and services could be developed and hence, reinforced in consumption. For example, members of a non-verbal virtual community site at www.travelwise.com share information about reviews and ratings of holidays, travel, accommodation and their consumer experiences. Emotions about these experiences trigger positive or negative WOM (Westbrook, 1987). Such reactions may range from joy to anger and increase WOM directly (Westbrook, 1987). Additionally, existing literature suggests that aspects of WOM communication may include favourableness (Arndt, 1967, 1968; Herr et al., 1991), enthusiasm (how often the individual engages in WOM and with how many people) (Anderson, 1998; File et al., 1994), and detail (how much is said) (Bone, 1992). In sum, the above statements and the existing literature uphold a general theme. That is, consumers’ excitement may have important implications for positive WOM. Antecedents of excitement Attributes of a web site. We define attributes of a web site as elements of a web site that that are visible to a customer and aid the shopping process. These elements include web site aesthetics, navigation, responsiveness, and secure purchase measures. Alba et al. (1997), in their seminal piece on interactive shopping, suggest that the effective design of these elements may lead to a competitive advantage for e-tailers. Many studies suggest that web attributes are akin to the physical environment of a store in a high street or a shopping mall (Childers et al., 2001). Research in traditional retailing suggests that the shopping environment is a significant determinant of consumers’ emotions (Machleit and Eroglu, 2000) and more specifically that visual excitement positively correlates with shopping frequency (Stoltman et al., 1991). Therefore, based on the above review we expect that positive perceptions of the attributes of a web site will lead to excitement. Involvement. Involvement is referred to as an individual’s perceived relevance of an object based on inherent needs, values and interests (Zaichkowsky, 1985). Involvement is said to be either situational (temporal) or enduring (lasting) (Richins and Bloch, 1986). Individuals with an enduring involvement with shopping may receive hedonic

pleasure directly from the time spent exploring the shopping environment, while others will embark on a purchase(s) with a shopping plan including an exit (Machleit and Eroglu, 2000; Wakefield and Baker, 1998). Researchers have also shown that higher involvement leads to heightened emotional arousal with the consumption experience (Wakefield and Blodgett, 1994). In summary, individuals tend to get more excited about things that they enjoy doing. Those who do not enjoy shopping are less excited about the experience and the environment within which they carry out the task. Merchandising. Merchandising is defined as factors associated with online offerings separate from the attributes of the web site and shopping convenience. This definition is in keeping with the definition adopted by Szymanski and Hise (2000). This includes both product offerings and product information available online (Szymanski and Hise, 2000; Evanschitzky et al., 2004). An e-tail offer composed of a superior assortment of products increases the probability that consumer needs will be met (Raijas, 2002). Similarly, a wider assortment of products that can include items of superior quality accessible at all hours online would appear attractive to e-shoppers (Dennis et al., 2004). Lower search costs of e-shopping are likely to result in consumers buying better quality items (Bakos, 1997). Buying better quality items can improve overall shopping outcomes by eliminating costs of failed products, an important motivational benefit. Similarly, an improved repository of information (both in terms of quality and quantity) available online leads to better buying decisions and higher levels of satisfaction (Grewal et al., 2004). Based on the reviewed literature, we can postulate that merchandising can enhance consumer shopping outcomes, and by extension such consumers are more likely to be excited. Convenience. One of the most significant attractions of e-shopping is perceptions of convenience (Szymanski and Hise, 2000; Evanschitzky et al., 2004). Bakos (1991) asserts that e-shopping can lower the costs of acquiring pre-purchase product information while at the same time increase search benefits by providing a broader array of product alternatives at a small incremental cost. These benefits in the reduction of search costs accrue particularly when the consumer is under time pressure (Beatty and Smith, 1987) making the accessibility advantage of interactive shopping especially advantageous to consumers. Convenience in e-shopping therefore increases search efficiency, by eliminating travel costs and associated frustrations (psychological costs). While e-shopping in general is more convenient to traditional shopping, e-tailers have gone to significant lengths to differentiate among themselves by emphasising convenience (Jayawardhena, 2004b). Therefore, it could be argued that perceptions of convenience of shopping with a specific e-tailer facilitates the accomplishment of the task and makes e-tailing more attractive. Furthermore, the reduction of psychological costs could make the e-shopping experience more enjoyable and therefore exciting. Research method Sampling and data collection A sample of 1,500 individuals was randomly selected from a consumer panel of online shoppers. Respondents were asked to respond to a questionnaire based on their last online shopping episode. In total, 644 completed questionnaires were received in total, of which 626 were usable. This is a response rate of 42.93 per cent, which is favourable by comparison with previous surveys examining similar topics (Shim and Eastlick, 1998; Shim et al., 2001). Characteristics of the respondents can be found in Table I.

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Sample demographics

Percentage

Age , 21 21-30 31-40 41-50 . 50

33.6 29.6 19.5 12.0 5.3

Gender Male Female

43.9 56.1

Measures An online questionnaire was developed to test the conceptual model. Instrument construct item scales were adapted from previous studies on traditional retailing and environmental variables, and emerging online retailing literature (see Table II for item measures). Items that measure attributes of the web site were adopted from Baker et al.(1992), Wakefield and Baker (1998) and Szymanski and Hise (2000). Item measurements for merchandising and convenience were adopted from Szymanski and Hise (2000). The involvement scale items were adopted from Zaichkowsky (1985), with the selected items reflecting the subscales of the “value” and “interest” of shopping (Mano and Oliver, 1993; Wakefield and Baker, 1998). Items that measure excitement were selected from work carried out by Russell (1980), Mano and Oliver (1993), and Wakefield and Baker (1998). Similarly, items measuring intent to return (Oliver and Swan, 1989) and positive WOM were adopted from McKee et al. (2006). Results We initially carried out an exploratory principal axis factoring of all constructs of interest. This resulted in the first deletions of poorly performing items from the scales based on weak or cross-loadings (see Table II for deleted items). Confirmatory factor analysis (CFA) was then run using LISREL 8.7. The final CFA fit indices were all found to be above recommended thresholds (x 2 ¼ 211:36; df ¼ 123; RMSEA ¼ 0:054; GFI ¼ 0:936; NNFI ¼ 0:934; CFI ¼ 0:991). These fit indices were chosen because a combination of such indices has been shown to achieve a good balance between Type I and Type II error rates when assessing model fit (Hu and Bentler, 1999). We assessed the discriminant validity of our measures using two approaches. First, we examined a series of x 2 difference tests by comparing the fit for pairs of constructs that were freely estimated with those that were constrained to unity (Anderson and Gerbing, 1988). The results reveal that in each comparison, the unconstrained models fit the data better than the constrained models. Second, we compared the average variance extracted (AVE) for each of our constructs with the squared correlation between construct pairs (Fornell and Larcker, 1981). The results show that the AVEs (smallest AVE ¼ 0:61; see Table III for construct correlations) exceed the squared correlations for all measures. In combination, these two tests provide evidence of the discriminant validity of our multi-item measures. Fornell and Larcker (1981) also consider a construct to display convergent validity if AVE is at least 0.50, and hence the measures also display convergent validity.

Standardised Composite factor loading reliability Attributes of the web site (1) ABC web site offers . . . . . . fast downloads . . . easy-to-follow search paths . . . attractive graphics * . . . uncluttered screens . . . a secure purchase Merchandising (1) ABC offers a high . . . . . . number of offerings . . . amount of product information . . . variety of offerings Involvement (2) In general, online shopping is . . . . . . unimportant-important . . . unexciting-exciting * . . . unappealing-appealing . . . means nothing to me-means a lot to me . . . doesn’t matter to me-matters to me . . . boring-interesting * Convenience (1) Shopping at ABC compared with other e-tailers . . . . . . in total shopping time . . . in ease of payment . . . in ease of gathering required info Excitement (2) Shopping at ABC is . . . . . . exciting-unexciting . . . dull-interesting . . . boring-stimulating . . . unappealing-appealing . . . monotonous-sensational * Intent to return (2) In future, shopping at ABC will be . . . . . . not at all-very frequent . . . unlikely-likely . . . not probable-very probable . . . impossible-very possible * WOM (1) In future . . . . . . likelihood of you spreading positive WOM about ABC is . . . I would recommend ABC to my friends . . . if my friends were shopping I would tell them to try ABC

0.79

Average variance extracted

E-shopping excitement

0.64

1177

0.79 0.78 0.72 0.75

0.61

0.85

0.68

0.78

0.68

0.90

0.70

0.75

0.61

0.69

0.62

0.73 0.74 0.71

0.76 0.72 0.74 0.71

0.85 0.84 0.83

0.76 0.77 0.73 0.77

0.74 0.71 0.70

0.62 0.71 0.78

Table II. Item measures, composite reliabilities and average variance extracted

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In testing the conceptual model, a structural model was run. The fit indices were as follows: x 2 ¼ 226:99; df ¼ 131; RMSEA ¼ 0:059; GFI ¼ 0:918; NNFI ¼ 0:967; CFI ¼ 0:979 (model 1 in Table IV). While all the conceptualised paths were significant, an examination of the predicted model’s modification indices showed there was room for improvement. As a result, three additional links were added, namely between attributes of the web site and intent to return, merchandising and intent to return, and between intent to return and positive WOM. It is, of course, never recommended to be data-driven in any model construction; however, it is common practice to add or delete structural paths to models based on empirical results (Kelloway, 1998). Furthermore, theoretical reasons for the addition of this link are discussed in our concluding remarks. The fit indices of the second structural model were: x 2 ¼ 219:68; df ¼ 131; RMSEA ¼ 0:054; GFI ¼ 0:922; NNFI ¼ 0:981; CFI ¼ 0:987 (model 2 in Table IV). Model 2 provides a slightly better fit to the data than Model 1, as evidenced by the reduction in the RMSEA and the slight increases in the GFI, NNFI and CFI. The results of Model 2 are presented in Table V. Table V reveals that involvement, merchandising, convenience and attributes of the web site all positively influence excitement (in that respective order of influence), whilst excitement in turn positively influences intent to return and positive WOM. Furthermore, it shows that both merchandising and attributes of web site positively influence intent to return, which in turn is positively related to positive WOM. Discussion and conclusions This study postulated that convenience, attributes of the web site, merchandising and involvement directly influence consumer excitement, and this in turn influences intent to return and positive WOM. The results support this general supposition of the study. It finds that involvement has the most significant influence on excitement (0.64) closely followed by merchandising (0.513). Convenience and attributes of the web site have a

Table III. Construct correlations

1. 2. 3. 4. 5. 6. 7.

Attributes of the web site Merchandising Involvement Convenience Excitement Intent to return Positive WOM

Model Model 1 Model 2

Table IV. Model fit measures

1

2

3

4

5

6

0.569 0.643 0.628 0.672 0.563 0.585

0.711 0.665 0.619 0.652 0.617

0.586 0.566 0.695 0.634

0.612 0.669 0.661

0.634 0.686

0.656

x 2 (df)

Dx 2 (df)

RMSEA

GFI

NNFI

CFI

226.99 (131) 219.68 (130)

35.6 (4) * * 28.3 (3) * *

0.059 0.054

0.918 0.922

0.967 0.981

0.979 0.987

Notes: Model 1: as per the conceptual model; Model 2: as above plus links between attributes of web site and intent to return, merchandising and intent to return, and between intent to return and positive WOM. RMSEA, root mean square error of approximation; GFI, goodness-of-fit index; NNFI, nonnormed fit index; CFI, comparative fit index. *Not significant; * *significant at 0.05

Path Convenience ! excitement Involvement ! excitement Attributes of web site ! excitement Merchandising ! excitement Attributes of web site ! intent to return Merchandising ! intent to return Excitement ! intent to return Excitement ! positive WOM Intent to return ! positive WOM

Coefficient

t value

0.314 0.540 0.308 0.413 0.349 0.363 0.449 0.412 0.310

6.64 10.75 4.53 4.99 6.66 9.98 4.99 3.35 4.11

Notes: Excitement R 2 ¼ 0:679; positive WOM R 2 ¼ 0:601; intent to return R 2 ¼ 0:569

somewhat less significant influence on excitement (0.414 and 0.408, respectively). The study also finds that, of these variables, attributes of the web site and merchandising directly influence the intent to return, which in turn influences positive WOM. In addition, the study shows that excited shoppers’ behaviours can be expressed in terms of intent to return and positive WOM. We will now examine both theoretical and practical implications of our findings in the following subsections. Involvement Marketers cannot control the extent to which consumers have an enduring involvement with shopping. However, marketers can cater to individuals with differing levels of involvement by presenting an e-tailing experience that consumers perceive are relevant to their needs, values and interests. More specifically e-tailers can adopt strategies that cater for customers’ involvement, and such strategies may help consumers to achieve an enduring level of involvement with shopping. For example, some e-tailers allow the opportunity for customers who purchase a particular product to write a review of the product. E-tailers can take this concept further to link the reviews to discussion forums, thereby enabling customers who bought the product and potential customers who may be thinking of buying the product to interact. Such forums may be particularly appealing to customers with high involvement, and therefore is perhaps an avenue that e-tailers should further develop. In this context, e-tailers can leverage the capabilities of Web 2.0 – i.e. the second generation of web-based communities and hosted services – and can use such forums as places to facilitate creativity, collaboration, and sharing between users with high levels of involvement. Therefore, such strategies allow e-tailers to retain both existing customer and also to attract potential customers. Web 2.0 enables people to collaborate by giving out their information and voluntarily exchanging details with others in online environments such as in blogs, podcasts, virtual worlds (e.g. Second Life) and social network sites such as Facebook. Some owners of sites such as Facebook have seen the potential of members as customers by adding commercial advertising on their sites. Typically, the growth of personal information gleaned through web sites and internet chatrooms or e-mail messages are encouraging the spread of viral marketing. Film clips, videos, games and jokes can also be forwarded electronically from recipient to recipient in an infectious form of discussion or chat, which can be termed viral marketing. E-tailers can use viral marketing in their strategies when customers are encouraged to create a buzz, thereby

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Table V. Structural model

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motivating them into passing on marketing messages to yet more people. Like viruses such strategies can induce multiplication in message exposure or explosion from one to many, for example to hundreds or thousands or millions of people. The e-potential for exponential growth in terms of social media research and marketing is therefore large. Merchandising We find that perceptions about superior merchandising have a positive impact on excitement (0.513) and intent to return (0.363). As such, our findings confirm the popular discussion in e-shopping: the perceived merchandising benefits (Grewal et al., 2004). These benefits are discussed often in the context of motivating people to shop online (Smith and Sivakumar, 2004). In practical terms this may indicate that it is very beneficial for e-tailers to broaden product and brand choice, the amount of product information, etc. This is perhaps one of the possible explanations of successful e-tailers (for example, Amazon.com) commencing operations as only as a single product (books) e-tailer but gradually expanding the product range with the passage of time. E-shoppers appear to prefer to shop with e-tailers that have a very large selection of goods (both in terms of breath and depth). Additionally, e-shoppers value the information provision element of merchandising, and in this context e-tailers can leverage the enhanced capabilities offered by Web 2.0 to present more customised information content that is both relevant and richer in its content. Convenience Shoppers who value convenience can often obtain the benefits of products and services with less time, effort and money expended and these benefits have a positive relationship with shopper excitement. For example the large supermarket UK retailer Tesco plc has taken advantage of the internet to provide the added convenience of home purchases and deliveries as well as its bundle of broadband services. Where such stimuli from “mouse to house” generate a convenient and pleasant atmosphere, a company can improve its competitive position in providing satisfaction and inducements to excite and prompt purchases (Wright et al., 2006). It is beneficial for e-tailers to employ strategies that can enhance the convenience of shopping online: speeding up payment systems, enhancing the information use within the e-tailing web site so that consumers may complete their shopping tasks more quickly. Additionally, convenience can be employed as a positioning strategy. Attributes of the web site Our study provides empirical evidence that the attributes of the web site contribute to e-tail shoppers’ self-reported affective states. This finding is in line with previous studies that suggest that using the internet may provoke enjoyable experiences through the flow state, which may in turn positively influence and affect psychological wellbeing (Chen et al., 2000) and a determinant of consumers’ emotions (Machleit and Eroglu, 2000). The implication for e-tailers, indicated by attributes of web site item measures, is that it is important to incorporate these aspects into their web sites, since they contribute to the positive e-shopping experience and by extension to consumer excitement. Excitement, intention to return and WOM That shopper excitement is directly related to repatronage intentions is in keeping with previous empirical research on retailing (Wakefield and Baker, 1998). Similarly, both

merchandising and attributes of the web site have significant influence on intent to return, which supports previous empirical and conceptual arguments (e.g. Bloch et al., 1994). Therefore to summarise in part, as described earlier, elements within the control of e-tailers (i.e. attributes of the web site, convenience and merchandising) and individual factors (as measured by involvement) have a direct influence on shopping excitement, which in turn has positive influences on intent to return and say good things about the e-tailer. The retailing literature suggests that consumers are apt to invest considerable search effort in comparison shopping at some point before settling into a shopping routine (Urbany et al., 1996). Therefore, as consumers expand their online shopping episodes and expand their online shopping volumes, they are likely to initially visit alternative e-tailers, frequent online discussion forums, etc. This research, then, may suggest that an e-shopping episode that leads to excitement is more likely to lead to intentions to return and thus become part of the consumer’s online shopping routine. Conversely, low excitement levels may lead to lower intentions to return and less likelihood that consumers will make the e-tailer part of their online shopping routine. A major managerial outcome is the understanding that customers who are excited by their shopping experience intend to return to the shopping area in future. This raises a number of issues relating to repatronage intentions. Our results indicate that customers derive enjoyment shopping experiences from their assessment of online e-tailing environment. This result is similar to that provided by Wakefield and Baker (1998) who found that excitement has a positive influence upon repatronage intentions in traditional retailing. Our findings indicate that excitement positively influences positive WOM. Additionally, intent to return also has a positive impact on WOM. Previous work (see Banerjee, 1992, 1993; Bikhchandani et al., 1992; Maxham, 2001) indicates that WOM is persuasive despite the fact that there might be some noise in the transmission process due to preference heterogeneity, or as in Banerjee (1993), uncertainty whether previous consumers acted on new information or were “herded”. Gelb and Johnson (1995) go on to conclude that positive WOM is more effective than advertising and although it persuades potential customers, it also leads to action. Therefore, creating conditions that lead to positive WOM is in the interest of the e-tailer. For example, it can be argued that by creating the necessary conditions for consumer excitement such e-tailers may also be in a position to make savings on advertising expenditure. WOM is ingrained in social behaviour and increases the strength of relationships ties when a consumer interacts with other consumers and with e-tailers. For example, virtual communities – or specifically, types of brand communities formed around cult brands such as the iPod, Harley-Davidson and Star Trek – work on a combination of content with communication that allows information exchange between consumers to meet their social and community needs, thereby enhancing relationship ties and increasing excitement. Brown and Reingen (1987) have described WOM as the intensity of the social relationship between consumers. Cova and Pace (2006) discuss further how consumers can become impassioned and empowered consumer collectives to assert more channel power, even to the extent of seeing brands as shared cultural property belonging to them rather than solely to the companies that own them. WOM can therefore be more effective than general advertising when it acts as a catalyst in harnessing emotions and generating excitement.

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Limitations and future research The results of this study provide a foundation to the understanding of the antecedents and consequences of positive emotion in general and, more specifically, online shopping excitement in particular. However, in considering any research, it is important to evaluate the limitations of the work. First, the study maybe limited in that no differentiation is made between the types of goods that e-consumers purchased. Future research should explore the types of media attributes and consumer characteristics that lead to shopping excitement for experience goods. Shim et al. (2001) state that a fundamental question facing e-tailers is whether the antecedents that predict the internet purchase of goods are different from those that predict the purchase of experience goods. A possible future extension of this work could be to investigate whether the results from this study can be applied to experience goods (such as entertainment). Second, this study is cross-sectional, measuring respondents’ excitement of the shopping experience based on their last shopping episode. As such, conclusions regarding the causal order amongst the variables of interest cannot be made, and care should be exercised when interpreting the findings. Third, although this study has confirmed a number of variables relating to online shopping excitement, it may be likely that certain of these variables will be more influential than others in affecting levels of excitement and its consequences. Further research could examine specific factors that customers use to judge their enjoyment of a shopping experience. Further research would also be valuable in identifying other consumer segments than the ones identified by gender in this study, and to segment, for example, according to respondents’ personal values. Fourth, it should be noted that there are differences between intentions to return and actual repatronage behaviours on the part of shoppers. Future work in the area could seek to examine whether intentions to return to an e-tailer translate into actual repatronage behaviours. Finally, we measured a limited number of variables in our work. There may be additional factors that could contribute towards shopping excitement. One such antecedent could be “flow”, since research indicates flow to influence hedonic and utilitarian shopping values (Se´ne´cal et al., 2002), and therefore shopper excitement. Additionally, there may be other consequences of excitement that we did not include in our study. For instance it may be that shopping excitement may influence the discretionary amount that shoppers are prepared to spend. The retailing literature has established that increased time spent in the retail environment results in higher spending (Donovan et al., 1994; Wakefield and Baker, 1998). Thus, shopping excitement may increase the duration of time spent on the shopping visit and spending potential. Willingness to spend more money is another potential outcome variable. A further possible consequence of excitement, and a possible influence on word of mouth, is “tenure”. For instance, East et al. (2001) found that new customers tend to engage in WOM more than loyal customers. It seems logical to postulate that an online shopper excited about the discovery of a new online shopping site would tell more people than someone who has been shopping with the same site for a long time. This study does, however, offer several directions for future research into e-consumer behaviour. The role of excitement in the proposed model in this study suggests that future research on e-consumer behaviour could usefully extend research into the antecedents and effects of positive emotion. Future research could explore other variables for their effects, if any, since this theoretical model may not have

incorporated all relevant variables, especially other salient internet attributes and consumer attitudes. Such study is of both theoretical and practical relevance. As highlighted by other authors examining traditional shopping media the results of this study underline the importance of including emotion as an important component when modelling consumer retail response. Future research is therefore recommended in order to make more precise measurements of these variables.

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1183 References Agarwal, J. and Malhotra, N.K. (2005), “An integrated model of attitude and affect: theoretical foundation and an empirical investigation”, Journal of Business Research, Vol. 58 No. 4, pp. 483-98. Alba, J., Lynch, J., Weitz, B. and Janiszewski, C. (1997), “Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces”, Journal of Marketing, Vol. 61 No. 3, pp. 38-53. Anderson, E.W. (1998), “Customer satisfaction and word-of mouth”, Journal of Service Research, Vol. 1 No. 1, pp. 5-17. Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modelling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103, pp. 411-23. Arndt, J.A. (1967), “Role of product-related conversations in the diffusion of a new product”, Journal of Marketing Research, Vol. 4 No. 3, pp. 291-5. Arndt, J.A. (1968), “Selective processes in word-of-mouth”, Journal of Advertising Research, Vol. 8, pp. 19-22. Arnold, M.J., Reynolds, K.E., Ponder, N. and Lueg, J.E. (2005), “Customer delight in a retail context: investigating delightful and terrible shopping experiences”, Journal of Business Research, Vol. 58 No. 6, pp. 1132-56. Babin, B.J., Darden, W.R. and Griffin, M. (1994), “Work and/or fun: measuring hedonic and utilitarian shopping value”, Journal of Consumer Research, Vol. 20 No. 4, pp. 644-56. Baker, J., Grewal, D. and Levy, M. (1992), “An experimental approach to making retail store environmental decisions”, Journal of Retailing, Vol. 68, Winter, pp. 445-60. Bakos, J.Y. (1991), “A strategic analysis of electronic marketplaces”, MIS Quarterly, Vol. 15, September, pp. 295-310. Bakos, J.Y. (1997), “Reducing buyer search costs: implications for electronic marketplaces”, Management Science, Vol. 43, December, pp. 1676-92. Banerjee, A. (1992), “A simple model of herd behaviour”, Quarterly Journal of Economics, Vol. 110, pp. 797-817. Banerjee, A. (1993), “The economics of rumours”, Review of Economic Studies, Vol. 60, pp. 309-27. Batra, R. and Holbrook, M.B. (1990), “Developing a typology of affective responses to advertising: a test of validity and reliability”, Psychology and Marketing, Vol. 7, Spring, pp. 11-25. Beatty, S.A. and Smith, S.M. (1987), “External search effort: an investigation across several product categories”, Journal of Consumer Research, Vol. 14, June, pp. 83-95. Belanger, F., Hiller, J.S. and Smith, W.J. (2002), “Trustworthiness in electronic commerce: the role of privacy, security, and site attributes”, The Journal of Strategic Information Systems, Vol. 11 No. 3/4, pp. 245-70. Bikhchandani, S.D., Hirshleifer, D. and Welch, I. (1992), “A theory of fads, fashions, custom and cultural change as information cascades”, Journal of Political Economy, Vol. 100, pp. 992-1026.

EJM 43,9/10

1184

Bloch, P.H., Ridgway, N.M. and Dawson, S.A. (1994), “The shopping mall as consumer habitat”, Journal of Retailing, Vol. 70 No. 1, pp. 23-42. Bone, P.F. (1992), “Determinants of word-of-mouth communications during consumption”, in Sherry, J. and Stemthal, B. (Eds), Advances in Consumer Research, Vol. 19, Association for Consumer Research, Provo, UT, pp. 579-83. Brown, J.J. and Reingen, P.H. (1987), “Social ties and word-of-mouth referral behaviour”, Journal of Consumer Research, Vol. 14 No. 3, pp. 50-62. Chen, H., Wigand, R.T. and Nilan, M. (2000), “Exploring web users’ optimal flow experiences”, Information Technology & People, Vol. 13 No. 4, pp. 267-79. Childers, T.L., Carr, C.L., Peck, J. and Carson, S. (2001), “Hedonic and utilitarian motivations for online retail shopping behaviour”, Journal of Retailing, Vol. 77 No. 4, pp. 511-39. Cohen, J.B. (1990), “Attitude, affect and consumer behaviour”, in Moore, B.S. and Isen, A.M. (Eds), Affect and Social Behavior, Cambridge University Press, New York, NY, pp. 152-206. Cohen, J.B. and Areni, C.S. (1991), “Affect and consumer behavior”, in Robertson, T.S. and Kassarjian, H.H. (Eds), Handbook of Consumer Behavior, Prentice-Hall, Englewood Cliffs, NJ, pp. 188-240. Cova, B. and Pace, S. (2006), “Brand community of convenience products: new forms of customer empowerment – the case of ‘My Nutella The Community’”, European Journal of Marketing, Vol. 40 No. 9/10, pp. 1087-105. Darden, W.R. and Babin, B.J. (1994), “Exploring the concept of affective quality: expanding the concept of retail personality”, Journal of Business Research, Vol. 29, pp. 101-9. Dawson, S., Bloch, P.H. and Ridgeway, N.M. (1990), “Shopping motives, emotional states, and retail outcomes”, Journal of Retailing, Vol. 66, Winter, pp. 408-27. Dennis, E., Fenech, T. and Merrilees, B. (2004), e-Retailing, Routledge, New York, NY. Donovan, R.J. and Rossiter, J.R. (1982), “Store atmosphere: an environmental psychology approach”, Journal of Retailing, Vol. 58, Spring, pp. 34-57. Donovan, R.J., Rossiter, J.R., Marcoolyn, G. and Nesdale, A. (1994), “Store atmosphere and purchasing behaviour”, Journal of Retailing, Vol. 70 No. 3, pp. 283-94. East, R., Lomax, W. and Narain, R. (2001), “Customer tenure, recommendation and switching”, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behaviour, Vol. 14 No. 1, pp. 46-54. Eroglu, S.A., Machleit, K.A. and Davis, L.M. (2001), “Atmospheric qualities of online retailing: a conceptual model and implications”, Journal of Business Research, Vol. 54, pp. 177-84. Eroglu, S.A., Machleit, K.A. and Davis, L.A. (2003), “Empirical testing of a model of online store atmospherics and shopper responses”, Psychology and Marketing, Vol. 20 No. 2, pp. 139-50. Evanschitzky, H., Iyer, G.R., Hesse, J. and Ahlert, D. (2004), “E-satisfaction: a re-examination”, Journal of Retailing, Vol. 80 No. 3, pp. 239-47. File, K.M., Cermak, D.S.P. and Prince, R.A. (1994), “Word-of-mouth effects in professional services buyer behaviour”, The Service Industries Journal, Vol. 14 No. 3, pp. 301-14. Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-51. Gelb, B. and Johnson, M. (1995), “Word-of-mouth communication: causes and consequences”, Journal of Health Care Marketing, Vol. 15 No. 3, pp. 54-8. Grewal, D., Iyer, G.R. and Levy, M. (2004), “Internet retailing: enablers, limiters and market consequences”, Journal of Business Research, Vol. 57 No. 7, p. 703.

Herr, P.M., Kardes, F.R. and Kim, J. (1991), “Effects of word-of-mouth and product attribute information on persuasion: an accessibility-diagnosticity perspective”, Journal of Consumer Research, Vol. 17, March, pp. 454-62. Hu, L.-T. and Bentler, P.M. (1999), “Cut-off criteria for fit indices in covariance structure analysis: conventional criteria versus new alternatives”, Structural Equation Modelling: A Multidisciplinary Journal, Vol. 6 No. 1, pp. 1-55. Jayawardhena, C. (2004a), “Measurement of service quality in internet delivered services: the development and validation of an instrument”, Journal of Marketing Management, Vol. 20 Nos 1/2, pp. 185-209. Jayawardhena, C. (2004b), “The hierarchical influence of personal values on e-shopping attitude and behaviour”, Internet Research: Electronic Networking Applications and Policy, Vol. 14 No. 2, pp. 127-42. Keen, C., Wetzelsb, M., de Ruyter, K. and Feinberg, R. (2004), “E-tailers versus retailers: which factors determine consumer preferences?”, Journal of Business Research, Vol. 57 No. 7, pp. 685-704. Kelloway, E.K. (1998), Using LISREL for Structural Equation Modeling: A Researcher’s Guide, Sage Publications, Thousand Oaks, CA. Koufaris, M., Kambil, A. and LaBarbera, P.A. (2001/2002), “Consumer behaviour in web-based commerce: an empirical study”, International Journal of Electronic Commerce, Vol. 6 No. 2, pp. 131-54. Kozinets, R.V. (2002), “The field behind the screen: using netnography for marketing research in online communities”, Journal of Marketing Research, Vol. 39 No. 1, pp. 61-71. Laros, F. and Steenkamp, J.-B. (2004), “Importance of fear in the case of genetically modified food”, Psychology and Marketing, Vol. 21 No. 11, pp. 889-908. Loiacono, E.T., Watson, R.T. and Goodhue, D.L. (2002), “WEBQUAL: a measure of web site quality”, in Evans, K. and Scheer, L. (Eds), 2002 Marketing Educators’ Conference: Marketing Theory and Applications, Vol. 13, pp. 432-7. McKee, D., Simmers, C.S. and Licata, J. (2006), “Customer self-efficacy and response to service”, Journal of Service Research, Vol. 8 No. 3, pp. 207-21. Machleit, K.A. and Eroglu, S.A. (2000), “Describing and measuring emotional response to shopping experience”, Journal of Business Research, Vol. 49, pp. 101-11. Mano, H. and Oliver, R.L. (1993), “Assessing the dimensionality and structure of the consumption experience: evaluation, feeling and satisfaction”, Journal of Consumer Research, Vol. 20, December, pp. 451-66. Maxham, J.G. III (2001), “Service recovery’s influence on consumer satisfaction, positive word-of-mouth, and purchase intentions”, Journal of Business Research, Vol. 54 No. 1, pp. 11-23. Oliver, R.L. and Swan, J.E. (1989), “Consumer perceptions of interpersonal equity and satisfaction in transactions: a field survey approach”, Journal of Marketing, Vol. 53, April, pp. 21-35. Parasuraman, A., Zeithaml, V.A. and Malhotra, A. (2005), “E-S-QUAL: a multiple item scale for assessing electronic service quality”, Journal of Service Research, Vol. 7 No. 3, pp. 213-33. Park, J., Lennon, S.J. and Stoel, L. (2005), “On-line product presentation: effects on mood, perceived risk, and purchase intention”, Psychology and Marketing, Vol. 22 No. 9, pp. 695-719. Raijas, A. (2002), “The consumer benefits and problems in the electronic grocery store”, Journal of Retailing and Consumer Services, Vol. 9 No. 2, pp. 107-13. Rice, M. (2002), “What makes users revisit a web site?”, Marketing News, Vol. 31 No. 6, p. 12.

E-shopping excitement

1185

EJM 43,9/10

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Richins, M.L. (1997), “Measuring emotions in the consumption experience”, Journal of Consumer Research, Vol. 24 No. 3, pp. 127-46. Richins, M.L. and Bloch, P.H. (1986), “After the new wears off: the temporal context of product involvement”, Journal of Consumer Research, Vol. 43, September, pp. 280-5. Russell, J.A. (1980), “A complex model of affect”, Journal of Personality and Social Psychology, Vol. 39, December, pp. 1161-78. Se´ne´cal, S., Gharbi, J.-E. and Nantel, J. (2002), “The influence of flow on hedonic and utilitarian shopping value”, Advances in Consumer Research, Vol. 29, pp. 483-4. Shim, S. and Eastlick, M.A. (1998), “The hierarchical influence of personal values on mall shopping attitude and behaviour”, Journal of Retailing, Vol. 74 No. 1, pp. 139-52. Shim, S., Eastlick, M.A., Lotz, S.L. and Warrington, P. (2001), “An online prepurchase intentions model: the role of intention to search”, Journal of Retailing, Vol. 77, pp. 397-416. Smith, D.N. and Sivakumar, K. (2004), “Flow and internet shopping behaviour: a conceptual model and research propositions”, Journal of Business Research, Vol. 57 No. 10, pp. 1199-215. Stoltman, J.J., Gentry, J.W. and Anglin, K.A. (1991), “Shopping choices: the case of mall choice”, in Holman, R. and Solomon, M. (Eds), Advances in Consumer Research, Vol. 18, Association for Consumer Research, Provo, UT, pp. 434-40. Szymanski, D.M. and Hise, R.T. (2000), “E-satisfaction: an initial examination”, Journal of Retailing, Vol. 76 No. 3, pp. 309-22. Urbany, J.E., Dickson, P. and Kalapurakal, R. (1996), “Price search in retail grocery markets”, Journal of Marketing, Vol. 60 No. 2, pp. 90-104. Wakefield, K.L. and Baker, J. (1998), “Excitement at the mall: determinants and effects on shopping response”, Journal of Retailing, Vol. 74 No. 4, pp. 515-31. Wakefield, K.L. and Blodgett, J.G. (1994), “The importance of servicescapes in leisure service settings”, Journal of Services Marketing, Vol. 8 No. 3, pp. 66-76. Westbrook, R.A. (1987), “Product/consumption-based affective response and postpurchase processes”, Journal of Marketing Research, Vol. 24, August, pp. 258-70. Wright, L.T., Newman, A. and Dennis, C. (2006), “Enhancing consumer empowerment”, European Journal of Marketing, Vol. 40 No. 9/10, pp. 925-35. Zaichkowsky, J.L. (1985), “Measuring the involvement construct”, Journal of Consumer Research, Vol. 12, pp. 341-52.

Further reading Babin, B.J. and Darden, W.R. (1996), “Good and bad shopping vibes: spending and patronage satisfaction”, Journal of Business Research, Vol. 35, pp. 201-6. Bakewell, C. and Mitchell, V.-W. (2004), “Male consumer decision-making styles”, International Review of Retail, Distribution and Consumer Research, Vol. 14 No. 2, pp. 223-40. Bone, P.F. (1995), “Word-of-mouth effects on short-term and long-term product judgments”, Journal of Business Research, Vol. 32, pp. 213-23. Burzynski, M.H. and Bayer, D.J. (1977), “The effect of positive and negative prior information on motion picture appreciation”, Journal of Social Psychology, Vol. 101, pp. 215-18. Dabholkar, P.A., Thorpe, D.I. and Rentz, J.O. (1996), “A measure of service quality for retail stores: scale development and validation”, Journal of the Academy of Marketing Science, Vol. 24 No. 1, pp. 3-16.

Holbrook, M.B., Chestnut, R.W., Oliva, T.A. and Greenleaf, E.A. (1984), “Play as a consumption experience: the role of emotions, performance and personality in enjoyment of games”, Journal of Consumer Research, Vol. 11, September, pp. 728-39. Ranchhod, A. and Zhou, F. (2001), “Comparing respondents of e-mail and mail surveys: understanding the implications of technology”, Marketing Intelligence & Planning, Vol. 19 No. 4, pp. 254-62. Ranganathan, C. and Ganapathy, S. (2002), “Key dimensions of business-to-consumer web sites”, Information & Management, Vol. 39 No. 6, pp. 457-65. Reingen, P.H. and Kernan, J.B. (1986), “Analysis of referral networks in marketing: methods and illustration”, Journal of Marketing Research, Vol. 23, November, pp. 370-8. Russell, J.A. and Pratt, G. (1980), “A description of the affective quality of environments”, Journal of Personality and Social Psychology, Vol. 38, pp. 311-26. Sivadas, E. and Baker-Prewitt, J.L. (2000), “An examination of the relationship between service quality, customer satisfaction and store loyalty”, International Journal of Retail & Distribution Management, Vol. 28 No. 2, pp. 73-82. Steenkamp, J.B.E.M. and Baumgartner, H. (1998), “Assessing measurement invariance in cross-national consumer research”, Journal of Consumer Research, Vol. 25 No. 1, pp. 78-91. Stern, B.B. (1999), “Gender and multicultural issues in advertising: stages on the research highway”, Journal of Advertising, Vol. 28 No. 1, pp. 1-9. Swan, J.E. and Oliver, R.L. (1989), “Postpurchase communications by consumers”, Journal of Retailing, Vol. 65, Winter, pp. 516-33. Tse, A.C.B. (1998), “Comparing the response rate, response speed and response quality of two methods of sending questionnaires: e-mail vs mail”, Journal of the Market Research Society, Vol. 40 No. 4, pp. 353-61. Vandenberg, R.J. and Lance, C.E. (2000), “A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research”, Organizational Research Methods, Vol. 2, pp. 4-69. Wolfinbarger, M. and Gilly, M.C. (2003), “eTailQ: dimensionalising, measuring and predicting etail quality”, Journal of Retailing, Vol. 79, pp. 183-98. About the authors Chanaka Jayawardhena is Lecturer in Marketing at Loughborough University Business School, UK. He has won numerous research awards including two Best Paper Awards at the Academy of Marketing Conference in 2003 and 2004. Previous publications have appeared (or are forthcoming) in Industrial Marketing Management, European Journal of Marketing, Journal of Marketing Management, Journal of General Management, Journal of Internet Research and European Business Review, among others. Chanaka Jayawardhena is the corresponding author and can be contacted at: [email protected] Len Tiu Wright is Professor of Marketing and Research Professor at De Montfort University, Leicester. She has held full time appointments and visiting appointments in the UK and overseas. Her writings have appeared in books, in American and European academic journals, and at conferences where some have gained best paper awards for overall best conference papers and best-in-track papers. She is on the editorial boards of a number of leading marketing journals and is Editor of Qualitative Market Research: An International Journal, an Emerald publication.

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