Given the review above of WOM stimulation techniques, it is argued here that there is a need for a new theoretical framework to predict and influence consumers’ behaviour of generating positive WOM. The aim of this section is to lay out the theoretical justifications for a new framework. To that end, three characteristics that the new framework will have are outlined and discussed. First, the framework will refine the concept of WOM further by splitting it into multiple sub-concepts or categories. Second, it will take into account the impact of product or consumption types on WOM dissemination. Third, it will be universal in terms of online and offline WOM. Subsequently in this section, it will be shown that these three characteristics are not reflected adequately in contemporary theoretical frameworks. Previous conceptualisations of WOM can be put into two groups. The first views the
phenomenon of WOM in general as an information exchange process. This process would simultaneously involve two activities; one is the provision of information and the other is the acquisition of information (King, Racherla, & Bush, 2014; Yang, Hu, Winer, Assael, & Chen, 2012). Differently, the second conceptualisation focuses on each activity separately. Thus, in
21
the first conceptualisation, predictors of WOM are supposed to explain the entire event of two people exchanging information. In the second conceptualisation however, there are different definitions of sending and requesting WOM and different sets of predictors for each activity. The current research advocates the second conceptualisation for two reasons. First, the conceptualisation of WOM provision and WOM acquisition as one phenomenon is lacking in terms of specificity. Following this conceptualisation, the ability to accurately predict WOM would be hindered because the concept is too broad. Second, there is already evidence in the literature suggesting that the two behaviours are driven by different
psychological processes (Nyilasy, 2006).
In addition to the distinction between generating and requesting WOM, the current research calls for further refinement of the concept of WOM dissemination. Very few studies have advocated a conceptualisation of WOM dissemination at a more refined and specific level. Nevertheless, scattered remarks and hints can be found in the literature which indicate that the concept of WOM dissemination can be broken down to more than one category. For example, Sundaram, Mitra, and Webster(1998) asked their respondents to remember a WOM message they generated that was based on a specific consumption experience. This can be construed as an indication of two different categories of WOM dissemination; one that is based on a consumption experience and another that precedes a consumption experience. Similarly, Wojnicki and Godes (2008) conceptualised WOM dissemination as an instance of communication between consumers that takes place after a consumption experience. Nevertheless, the authors acknowledge the possibility that WOM could be disseminated before a consumption experience. Hennig-Thurau, Gwinner, Walsh, and Gremler (2004) indicated that positive WOM messages can be generated by “potential, actual, and former customers” (p. 39). This articulation indicates that some WOM
researchers have envisaged the possibility of consumers generating positive WOM messages about products they have not consumed yet. A similar view can be found expressed in Larivière et al. (2013).
Dichter (1966) mentioned two types of WOM dissemination; pre-decision and post-decision. However, he did not elaborate on what this distinction entails. Moreover, not much research since Dichter’s article has been conducted to build on this typology. Nevertheless, in support of Dichter’s suggested typology, it can be argued that some predictors of WOM
22
after. For example, an interesting advertisement about a new product could stimulate a prospective consumer to talk positively about the product without purchasing it. In this hypothetical example, interest that is stimulated by the product or by the advertisement’s message would be associated with the generation of pre-consumption WOM. Conversely, a predictor like customer satisfaction cannot be associated with the behaviour of generating WOM except after consumption. Resonating with this line of thinking, Jung and Kim (2012) called for research investigating the effects of the timing of WOM.
Furthermore, empirical research has revealed a distinction between the influence of sought WOM and that of unsought WOM (East, Hammond, Lomax, & Robinson, 2005).
Nevertheless, previous attempts to suggest a typology that distinguishes between the dissemination of sought WOM and the dissemination of unsought WOM are few if not entirely absent. Utilising open-ended questions, Mangold et al. (1999) investigated the factors that stimulated consumers to generate WOM messages about the most recent consumption experience they had. The authors reported that half of the sample had generated WOM messages following a request from another consumer for a consumption- related advice. Similar results were reported by Mazzarol et al. (2007). Wojnicki and Godes (2008) delineated in passing between solicited and unsolicited WOM. However, they opted not to incorporate that distinction into their conceptualisation of WOM.
Nyilasy (2006)differentiated between what he calls active and passive WOM. The former refers to WOM messages which the sender initiated, whereas the latter refers to those which the sender did not necessarily initiate. A similar distinction was also made by Bristor (1990). Another conceptualisation of the behaviour of generating WOM that hints at a distinction between sought and unsought WOM was suggested by Silverman (2001). However, similar to Dichter’s (1966) pre-decision and post-decision typology, not much research has been conducted to build on the typologies alluded to in Silverman (2001) and Nyilasy (2006). The current research therefore proposes a new theoretical framework in which the concept of generating WOM is split into three separate categories: generating unsolicited pre-consumption WOM, generating unsolicitedpost-consumption WOM, and generating solicited WOM.
Knowledge about what drives consumers to generate WOM messages is fragmented, unclear and inconsistent. For example, there is empirical evidence in the literature of a
23
positive relationship between WOM and new products (Rogers, 1983). A correlation
between WOMand established products was also found by other studies (Bristor, 1990; Day, 1971). Moreover, it was found that WOM recommendations rely on current customers (Reichheld, 1996). Other studies report empirical evidence that WOM recommendations are more likely to be generated by new customers (East, Lomax, & Narain, 2000; Stokes, Syed, & Lomax, 2002). One explanation for some of the inconsistent findings of previous research in terms of predicting the behaviour of generating WOM might be the result of the broad conceptualisation of WOM. Thus, a refined and finer conceptualisation of WOM
dissemination might help resolve those inconsistencies. It might also result in a better and more accurate prediction of the behaviour of generating WOM.
In addition to the need for a re-conceptualisation of WOM dissemination, a new theoretical framework also needs to take into account the impact of product or consumption types. Sundaram, et al (1998) argued that consumers’ propensity to generate WOM could be largely explained by consumption types. However, out of the six frameworks cited in this section, only two(Dichter, 1966; Lovett et al., 2013)has alluded to the role of products or consumption types in the dissemination of WOM. Likewise, Jung and Kim (2012) report in their meta-analysis that out of the thirty articles they selected, only two focused on the relationship between product types and WOM.
Furthermore, most previous research examining consumers’ WOM dissemination tended to focus on social and personal variables to predict this behaviour(Fang, Lin, Liu, & Lin, 2011; Hogan et al., 2004). The personal relationship between the sender and the receiver of a WOM message and the personality traits of a WOM sender are examples of those variables. This tendency to overlook the influence of products and consumption on the dissemination of WOM has its roots in several fields of the social science (Solomon, 1983). In marketing research, Solomon (1983) observes that the influence of products is often approached in the context of predicting and explaining consumers’ purchase decision making; nevertheless, the effect of products is seldom presented as a predictor of consumers’ non-purchase-related behaviour.
Despite this tendency however, few attempts have been made to emphasise the role of products and consumption types in the stimulation of consumers’ WOM. In these few attempts however, scholars have used different product typologies. Two of these typologies
24
are the goods/services continuum (Fang et al., 2011) and to a lesser degree, the typology of products as hedonic or utilitarian (Alsulaiman, Forbes, Dean, & Cohen, 2015; Jones,
Reynolds, & Arnold, 2006).The goods/services continuum approach focuses on the tangibility and intangibility of the product. A good is a tangible product that can be touched, such as a car or a book. On the other hand, a service is an intangible benefit that cannot be touched such as teaching or hairstyling (Pride et al., 2007). The typology of products as hedonic or utilitarian focuses on the pleasure and usefulness of products respectively. Hedonic refers to those values of a product that provide the consumer with fun, pleasure, or excitement. Utilitarian refers to those values of a product that provide the consumer with functional and instrumental benefits such as usefulness or practicality (Batra & Ahtola, 1991; Okada, 2005). Utilising the first typology, several scholars seem to agree on the significance of WOM messages in aiding consumers to make purchase decisions, particularly those decisions pertaining to intangible services as opposed to tangible goods (Barrot, Becker, & Meyners, 2013). Intangible services often necessitate a pre-purchase brand evaluation process that is fundamentally different to that of tangible goods (Zeithaml, 1981). This difference is
attributed to a number of characteristics that are exclusive to services. The most defining of these service characteristics is intangibility (Pride et al., 2007). A university course is for example a service because the core benefits that the consumer receives (i.e., knowledge and skills) do not have a physical form, and hence, they cannot be perceived through the five senses (Silverman, 2001).Additionally, because services are usually provided by humans, the quality of the same type of service is likely to vary from consumer to consumer (Pride et al., 2007). This heterogeneity makes it difficult for service providers to provide prospective customers with warranties or guarantees (Sweeney, Soutar, & Mazzarol, 2012; Zeithaml, 1981).
Due to the two service characteristics of intangibility and heterogeneity, the consumer’s ability to make a pre-purchase evaluation of available service providers is likely to be limited. This in turn increases the perceived risk of making the purchase decision (Mazzarol et al., 2007). In contrast, the tangibility and homogeneity of a physical good make physical goods easier to evaluate before making a purchase decision (Silverman, 2001). Consequently, to compensate for their inability to make a well-grounded evaluation prior to purchase, consumers of services often resort to WOM from other consumers (Chang, Jeng, & Hamid,
25
2013; Gheorghe, 2012). This is why services are generally seen as natural candidates for WOM communication (Fang et al., 2011; Harrison-Walker, 2001).
Empirical evidence for this notion was reported by Murray (1991). The author found that consumers who are contemplating the purchase of a service, as opposed to a physical good, prefer to gain information about the service via WOM messages from other consumers before they make a decision. Additionally, Fang et al. (2011) found that consumers seek out WOM messages from others when they face a high-risk purchase decision. Based on this association between services and the occurrence of WOM, services have been suggested as a means by which consumers’ WOM could be predicted and influenced (Fang et al., 2011). However, it should not escape one’s attention that the above relationship between services and WOM pertains almost always to the behaviour of requesting WOM messages from other consumers. This specific WOM behaviour is a totally different behaviour than disseminating WOM to others.
Since the current research makes a distinction between these two WOM behaviours, and since the focus of the current research is on the latter, there is a need for a new theoretical framework that considers the influence of products and consumption on the dissemination of WOM messages. The theoretical framework proposed in the current research will utilise the two product typologies mentioned above; however, the two will play different roles. The goods/services typology will be subsumedin the prediction of solicited WOM dissemination. Alternatively, the prediction of the two other types of WOM dissemination will be
hypothesised to be conditioned by the hedonic/utilitarian typology.
The third characteristic of the proposed framework pertains to the universality of it in terms of explaining both online and offline WOM dissemination. In regard to this issue, two
arguments have been made in the literature. The first posits that the antecedents of online WOM dissemination are likely to be different from those predicting offline WOM
dissemination(Taghizadeh, Taghipourian, & Khazaei, 2013). This view seems to be the conventional wisdom among the majority of WOM researchers. Of the six frameworks reviewed in this section, three were put forth to predict online WOM exclusively; one was proposed before the Internet era; one could be interpreted as focusingsolely on offline WOM; and only one was applicable to both online and offline WOM. The second argument however posits that the antecedents of WOM dissemination are probably similar across the
26
two media (Gruen, Osmonbekov, & Czaplewski, 2006; Keller & Fay, 2012). Lovett et al.(2013) take a middle position between the two arguments cited above. They hypothesised and reported that WOM predictors have similar effects in terms of direction across the two media; however, they argue that those effects vary in terms of strength depending on the medium. Reflecting the second argument, the current research is of the view that predictors of consumers’ WOM are universal across the online and the offline spheres.
A discussion of the differences between online and offline WOM can be used to further argue for the universality of the proposed predictors in the current framework. Six differences are highlighted here; WOM richness, reach, retrievability, observability,
synchronicity, and the degree of personal familiarity of the individual with the other actor in the WOM instance. First, offline WOM messages have been described as possessing a higher level of richness than online messages (Henderson & Gliding, 2004). Richness here refers to non-verbal cues such as facial expression and appearance(Dichter, 1966). Offline WOM messages are likely to be rich with such cues. Oppositely, such cues are likely to be absent in online WOM (Blazevic et al., 2013). Nevertheless, it is argued here that the difference between online and offline WOM in terms of richness is unlikely to necessitate different conceptualisations of the predictors of the behaviour of generating WOM. This is so because the premise that offline WOM messages are richer than online messages is disputable. As a consequence of websites such as YouTube and technological innovations such as Skype, people are able to communicate using non-verbal cues online. Some of these
communications even take place in real time.
Second, online WOM has often been described as having a larger reach than offline WOM (Blazevic et al., 2013; Hennig-Thurau et al., 2004). A single online WOM message can be directed to a large number of people more easily than an offline WOM message. For that reason, generating an online WOM message has been dubbed in a number of studies as a one-to-many form of communication, and generating an offline WOM message as one-to- one (Lovett et al., 2013; Phelps, Lewis, Mobilio, Perry, & Raman, 2004). The wider reach of online WOM is driven largely by the widespread use of social media. In 2015, users of social media around the globe were estimated to have been around 1.96 billion. This number is expected to reach 2.44 billion by 2018. As of March 2015, Facebook had a record number of 1,415 billion active users; WhatsApp had seven hundred million; Skype and Instagram had
27
three hundred million each; Twitter had 288 million; Tumblr had 230 million; and Snapchat had 200 million (www.statista.com).
The above numbers might give the impression that online WOM ought to be more prevalent than offline WOM. Nevertheless, as reported earlier, the number of WOM messages
generated or requested offline largely exceeds those taking place online (Keller & Fay, 2012). Keller and Fay (2012) argued that the widespread use of social media is due to humans’ inherent social nature. In other words, humans’ innate tendency to be social was not brought about because of a technological innovation. Rather, platforms such as Facebook and Twitter merely provide more opportunities for those innate tendencies to manifest themselves. More importantly, it is acknowledged here that WOM reach is an important indicator in the assessment of the aggregate impact of consumers WOM across a particular market. However, it is unlikely to be a major factor in the decision of a single consumer to generate a WOM message.
Third, when a WOM message is posted online, it is more likely than not to remain available online for later retrieval by other consumers (Berger & Iyengar, 2013; Blazevic et al., 2013). Owing to this advantage, marketers would potentially have the ability to measure and analyse consumers’ online WOM in terms of both value and characteristics(Cheung & Thadani, 2012; Kaplan & Haenlein, 2011). Fourth, Cheung and Lee(2012) point to the observability of online WOM. Some consumers’ online WOM messages can be monitored, whereas offline WOM messages are much harder to observe (Berger, 2014). Similar to the characteristic of WOM reach, consumers’ engagement in the behaviour of generating a WOM message is unlikely to hinge upon whether the message is retrievable or observable. The characteristic of observability can be helpful to consumers who are seeking advice from other consumers. Nonetheless, it is likely to be irrelevant to a consumer’s decision to generate a WOM message. By the same token, WOM observability may be important to marketers and academics researching consumers’ WOM. However, it is likely to be irrelevant to the person generating the WOM message. Accordingly, these three differences between online and offline WOM should not entail a separate investigation of the predictors of WOM dissemination.
Fifth, an offline WOM message is more likely to be directed to people who are familiar to the sender (Meuter et al., 2013). In contrast, an online WOM message can be “broadcasted” to
28
and accessed by people who might be complete strangers (Blazevic et al., 2013). Finally, offline WOM conversations are described in the literature as “synchronous”, whereas online conversations tend to be “asynchronous”(Henderson & Gliding, 2004; Lovett et al., 2013). In other words, when a WOM message is communicated offline, the response is likely to follow the message immediately. In opposition, when a WOM message is communicated online, a delay before the response is communicated back is rather expected (Berger & Iyengar, 2013). Berger and Iyengar (2013) argue that asynchronous communication allows people enough time to talk about more interesting products. In synchronous communication however, the need for an immediate reply may limit people’s ability to remember and talk about interesting products.
The effects of personal familiarity and synchronicity on the behaviour of generating WOM do