# Why Are Users of Social Media Inclined to Word-of-Mouth?

Patrick Mikalef, Adamantia Pateli, Michail Giannakos

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Patrick Mikalef, Adamantia Pateli, Michail Giannakos. Why Are Users of Social Media Inclined to Word-of-Mouth?. 12th Conference on e-Business, e-Services, and e-Society (I3E), Apr 2013, Athens, Greece. pp.112-123, 10.1007/978-3-642-37437-1_10 . hal-01470527

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# Why are users of Social Media inclined to Word-of-Mouth?

Patrick Mikalef¹, Adamantia Pateli¹ and Michail Giannakos²

¹ Ionian University, Corfu, Greece

{mikalef, pateli}@ionio.gr

² Norwegian University of Science and Technology (NTNU), Trondheim, Norway

michail.giannakos@idi.ntnu.no

**Abstract.** Motivated by the fact that social media are continuously gaining in popularity, firms are piloting different approaches of promoting their products and services. However, there is much debate in the academic and business community about the effectiveness of social media as a platform for marketing. Specifically, practitioners are concerned with how Word-of-Mouth (WOM) is spread through these sites, and what aspects facilitate users in doing so. The aim of this research is to elucidate the motivations for WOM over social media based on utilitarian and hedonic theories. Partial Least Squares (PLS) analysis is performed on data obtained from 169 social media users to test our research model. Outcomes indicate that both, utilitarian and hedonic motivations impact WOM. Utilitarian motives are triggered through customized advertisements, while hedonic motives through the ability to socialize during product browsing.

**Keywords:** Word of Mouth, Social Media, Utilitarian and Hedonic Theory

## 1 Introduction

Word-of-Mouth (WOM) has been defined as the mechanism by which humans exchange information and experiences about a wide range of topics, such as products, companies and services [10]. WOM is recognized as one of the most reliable sources of information transmission since the begging of human society, and has been proven to greatly affect consumers buying decisions [27]. Consequently, it has managed to attract the attention of many researchers, in the attempt to understand what motivates consumers to pass on information. However, with the inception of the Internet, and the bidirectional communication capabilities which it facilitates, WOM has been shifted from an interpersonal to a global scale. As a result, WOM transmitted online has dominated the attention of marketers, since the type of information exchanged vastly impacts consumer purchasing decisions.

Research studies estimate that while 90% of WOM conversations take place of-fline, the information that is exchanged in these conversations is largely based on opinions found on the Internet [4]. Therefore, consumer motivations to share their
positive or negative feedback is of great importance for the sales of companies. Inter-
personal communication theories have tried to demystify the tendencies of consumers
to pass on their opinions. However, they have been rendered as inappropriate when
applied to online WOM, since other motives may propel consumer actions. Conse-
quently, efforts have recently been focused on explaining the psychological drivers
for online WOM. While traditionally researchers have focused on aspects of prod-
ucts/services and antecedents that drive users to pass on information, recent attempts
have recognized the importance of the medium in facilitating WOM [10].

Online WOM has seen a great rise, with Amazon.com being one of the first com-
panies to introduce the feature of opinion giving on purchased products. Today, it has
an estimated 10 million consumer generated comments [5] Following the successful
example of Amazon.com, numerous companies introduced this feature allowing their
customers to provide feedback on purchased items. Additionally, websites specialised
on opinion sharing have risen, such as epinions.com and buzzilions.com. These sites
provide a concentrated source of feedback for products of numerous types. Recently,
there has been an increasing amount of attention been placed on marketing over social
media websites as an alternative option for product promotion and customer feedback
[24]. Due to their large user base, companies have piloted attempts to harness the
potential that such sites may offer. It has been suggested that social media sites may
be the new frontier for marketing and retailing [8]. Despite the attention that Social
Media have managed to attract, little is known on how they enable consumers to share
product related information.

Building upon this gap, we examine how particular aspects of social media influ-
ence consumers to pass on information. We distinguish between utilitarian and hedon-
ic motivations based on perceived value of the medium, and examine how specific
characteristics of social media explain this realized value. Additionally, we perform a
multi-group analysis in order to discover differentiations that may exist between
males and females.

The following section presents a synopsis of literature concerning WOM and ex-
plains how social media may change the status quo of e-business through their unique
features. Building upon the utilitarian and hedonic theory, in section 3 we develop a
research model and formulate hypotheses regarding motivations of consumers to gen-
erate WOM. In section 4 we introduce our dataset and discuss results from the Partial
Least Square (PLS) analysis. In the last section, we present conclusions derived, and
highlight practical and theoretical implications of this study.

2 Theoretical Background

The importance of word of mouth has been noted in research and in practice for a
long time. It is a well-known fact that positive WOM has a direct effect on increased
product sales which in turn leads to further WOM. Therefore, it is critical for busi-
nesses to know what motivates users to engage in WOM, and by which means it can
be facilitated. Through the digitization of WOM over the Internet, there has been a
renewed interest in examining the feedback and recommendation that consumers make about products and businesses [10]. The main questions that researchers have been concentrating on are: what motivates users to WOM, and what impact positive and negative WOM has on product sales. These two questions respectively look at the antecedents and the outcomes of WOM. Although the former still remains largely unexplored due to the contingencies to which it is subject, the later has been subject to extant research. As early as 1967, Arndt found that positive WOM impacts profitability of a firm while negative opinion sharing had the opposite effect [2]. Since then, outcomes of WOM studies have revealed that its effect extends beyond sales by increasing perceived value of a company as well as loyalty [12]. With regard to WOM motivations and antecedents, research has remained mostly a theoretical, with most research attempts grounding their hypotheses on past studies. In the current study we apply a utilitarian and hedonic motivation theory perspective in order to examine how WOM is influenced.

Utilitarian and hedonic motivation theory tries to explain the differences in consumer behaviour during the shopping process. Utilitarian and hedonic motives differ fundamentally. An action performed based on a utilitarian motivation is defined as rational and goal oriented [17]. When considering utilitarian value in the shopping context, the perceived benefit lies on the efficiency during the process of acquisition. The initiation of the shopping process for utilitarian shoppers is triggered by a mission that must be completed, and value acknowledged by the shopper is dependent on the efficiency and completeness of the process [3]. On the contrary, hedonic motivation refers to the search of emotions, such as happiness, enjoyment and fantasy, experienced during the shopping procedure. Thus, consumers propelled by hedonic motivations seek the enjoyment of the process rather than the efficiency of the process. Hence, hedonic shoppers receive satisfaction from the experience itself and the emotions which it creates.

Traditionally, researchers focused on utilitarian motives in order to explain shopping behaviours. However, recently the importance of hedonic motivation has emerged. The combined effect of these two motivations was put to test by [3], who pinpointed that hedonic factors impact unplanned shopping, while utilitarian factors do not. Therefore, it can be postulated that although the two categories differ significantly, in order to view the shopping processes holistically, both must be investigated simultaneously. Antecedents that form hedonic and utilitarian motivation, as well as differences in shopping behaviour have also been subject of much attention over the past years [25]. These outcomes provide interesting implications since the behaviour of utilitarian and hedonic shoppers differ in many ways.

A number of recent scientific articles have examined these types of motivations with respect to the design of online environments [22]. Most such studies have identified utilitarian factors as being the primary force for shopping online [1]. Despite the dominance of utilitarian factors in influencing shopping behaviour, research on the hedonic aspects has not remained stagnant. [20] argue that consumers do not navigate through electronic shops solely to collect information about a specific product, but also to fulfill the needs of experience and emotion. Similarly to traditional means of shopping, the actions performed during the shopping process are influenced by the
aesthetics and enjoyment that it provides [23]. Summarizing the above, it can be as-
serted that with regard to shopping, utilitarian and hedonic motivations exist regard-
less of the context in which they are promoted.

We can identify a broadening in perspective with the terms hedonic and utilitarian not only being applied to motivations, but also to perceived usefulness of systems and aspects of experience [26]. A number of studies have gone past the examination of motivations as predictors of product search intention and purchasing intention, and applied the concepts in the domain of Information Systems (IS) [32], software design [15] and mobile device usage [33]. However, little research has been performed so far on the motivations for browsing products on social media platforms through the utili- tarian and hedonic motivation lens [25]. Additionally, most studies focus on anteced- ents of utilitarian and hedonic motivation, and with regard to shopping outcomes, only examine intentions to purchase. We argue that identifying how perceived utilitar- ian and hedonic value impacts WOM is an equally important question based on the growing literature. In this study, we investigate how perceived utilitarian and hedonic value affects WOM and explain this effect with the use of two mediated constructs: customized advertisements and socializing ability.

3 Research Model

**3.1 Utilitarian motivation**

Utilitarian motivations are regarded in literature as one of the two types of forces that engage consumers in the buying process [31]. In fact, it has been suggested that users with a strong utilitarian motivation, will both browse and purchase items that they are looking for [31]. Going beyond examining the purchasing intentions, [18] showed that users propelled by utilitarian motives will also end up engaging in word-of-mouth with peers.

A utilitarian motivation is not solely a result of the product itself, but also of the medium that is used to promote it [22]. This places emphasis on the features that should be considered when designing it. Taking into account that the first step in the purchasing process is the seeking of information about a product, whether goal- oriented or exploration-oriented, and in conjunction with the importance that is noted regarding the platform which it is promoted, we hypothesize the following regarding social media:

**H1. Utilitarian motivation of social media users (for product browsing) has a posi-**
**tive impact on Word-of-Mouth.**

One of the strongest points of social media in relation to marketing is their ability to generate advertisements that are tailored to the likings of each consumer. Social media users continuously declare their likings by joining product groups, following company news, submitting personal information on their online profiles etc. This constitutes social media as a very effective medium for presenting products and ser- vices to consumers and riding them of the information overload hassle. In many occa-
sions this is not done in a direct way, i.e. presenting an advertisement in a panel of a screen, but can be also accomplished in a more pervasive manner. According to [30], the service of customized advertisements is a feature that adds utilitarian value to a medium, meaning that the process of searching becomes more efficient. Research has identified that the relevance of customized advertisements is a strong predictor for the intention to purchase a product/service [7]. Additionally, it has been shown that features such as customized advertisements, add utilitarian value to the shopping process and have an impact on word of mouth [18]. Especially in the case in where there is a high degree of homophile, i.e. similarity of likings between users or information that is presented to them, users tend to proceed to WOM. Therefore, we hypothesize that:

**H2. Customized advertisements on social media mediate the positive influence that utilitarian motivation has on word-of-mouth.**

**3.2 Hedonic motivation**

Although the impact of hedonic motivations as part of the shopping process was noted late in comparison with utilitarian motivations, they are now considered as an essential aspect to be examined. Hedonic features have a greater impact on exploration-oriented consumers, which if sufficiently stimulating result in unplanned purchasing of products [31]. Accordingly, hedonic aspects are of equal importance when considering mediums of product browsing and commerce. Although marketers typically provide web-stores that fulfill all functional requirements, it is emphasized that they should not neglect more escapist items [17]. The authors note that such elements that are intrinsically enjoyable facilitate greater user participation. This engagement perceived by users is also found to impact user's word-of-mouth intention for conventional stores [18]. Hence, we can assume that for social media the same will apply:

**H3. Hedonic motivation of social media users (for product browsing) has a positive impact on Word-of-Mouth.**

Hedonic motivated shoppers are inclined to engage in the process of browsing and purchasing for a number of reasons. However, one of the most frequently noted motivations is the ability to engage in social interaction with others. This is an aspect noted as being a major hedonic motivation for product browsing and purchasing in conventional stores [28]. Through the emergence of Web 2.0 applications and especially social media, users can transfer this experience in an online community in a synchronous or/and asynchronous manner. According to [34], engaging in online conversations during the browsing process could elevate their perceived hedonic value, and motivate them to purchase and browse in the future. When individuals with common likings interact online and share opinions, it is found that engaging in WOM is enhanced. Therefore, social interaction in online communities or chat has an impact on purchasing, which in turn leads to WOM. This WOM that is facilitated then results in additional purchases, thus making these two concepts interlinked [4]. Consequently we can assume that:
H4. The socializing ability of social media mediates the positive influence that hedonic motivation has on word-of-mouth.

<table><caption>**Table 1.** Construct Operational Definitions</caption><thead><tr><td>Construct</td><td>Operational Definition</td><td>Sources</td></tr></thead><tbody><tr><td>Customized Advertisements</td><td>The perceived value from the service of customized advertisements presented to users of social media based on their likings</td><td>[14], [31]</td></tr><tr><td>Socializing Ability</td><td>The ability to engage in a conversation (synchronous or asynchronous) with fellow peers during the browsing of products on social media sites</td><td>[31], [34]</td></tr><tr><td>Utilitarian Motivation</td><td>The degree to which users perceive social media to be a useful and effective means to browse products.</td><td>[6], [26]</td></tr><tr><td>Hedonic Motivation</td><td>The degree to which users perceive browsing products on social media to be a fun and emotionally stimulating experience.</td><td>[6], [26]</td></tr><tr><td>Word of Mouth Intention</td><td>The intention of social media users to share information with peers about products or services which they find relevant or interesting through such platforms.</td><td>[4], [16]</td></tr></tbody></table>

## 4 Data Collection and Measurements

For each of the constructs described in the conceptual model a number of items were adapted from past and were measured by applying a 7-point likert scale. The final questionnaire was divided into three parts; the first gathered information about the demographics of the sample, the second measured the utilitarian and hedonic motivation constructs, while the third targeted in measuring intention to share information. Questionnaire links were e-mailed to social media users through a mailing list of over 600 respondents of an institution, and posted on 20 forum boards of various themes (Fashion, computers, hobbies etc.). The questionnaire was active for a period of 7 months approximately, from December 2011 to June 2012. In total 169 responses were received and retained for further analysis with a valid response rate of 16,9% (from the mailing list).

Table 2 presents some descriptive results regarding our sample. Only respondents that maintained at least one social media account were qualified to participate in the research. An almost equal amount of male and female respondents filled out the questionnaire, with younger user groups being more active in social media sites. The distribution of ages is justified since the vast majority of social media users also belong to these age categories (15-44). With respect to online spending habits, the vast majority is accustomed to purchasing; therefore they exhibit familiarity with the online buying process. Finally, outcomes from respondent's replies confirm recent suggestions
tions that social media users are considerably active by revealing that 76% of them visit them on a daily basis.

<table><caption>**Table 2.** Sample Descriptive Statistics</caption><thead><tr><th>Variable</th><th></th><th>%(N=169)</th><th>Variable</th><th></th><th>%(N=169)</th></tr></thead><tbody><tr><td>Gender</td><td>Male</td><td>56%</td><td>Online Expenditure (€/Month)</td><td>Never Purchased Online</td><td>6%</td></tr><tr><td rowspan="6">Education</td><td>Female</td><td>44%</td><td rowspan="6">Frequency of SM use</td><td>1-24 €</td><td>44%</td></tr><tr><td>Primary School</td><td>1%</td><td>25-50 €</td><td>25%</td></tr><tr><td>Junior High School</td><td>1%</td><td>51-100 €</td><td>16%</td></tr><tr><td>High School</td><td>14%</td><td>101-250 €</td><td>7%</td></tr><tr><td>University</td><td>56%</td><td>&gt; 250 €</td><td>2%</td></tr><tr><td>Post Graduate</td><td>28%</td><td>Several times a day</td><td>55%</td></tr><tr><td rowspan="5">Age Group</td><td>&lt;24</td><td>50%</td><td>About once a day</td><td>21%</td></tr><tr><td>25-34</td><td>37%</td><td>3-5 times a week</td><td>8%</td></tr><tr><td>35-44</td><td>7%</td><td>1-2 times a week</td><td>4%</td></tr><tr><td>45-54</td><td>6%</td><td>Every few weeks</td><td>4%</td></tr><tr><td>&gt;55</td><td>0%</td><td>Less often</td><td>7%</td></tr></tbody></table>

In accordance with the grouping of social media sites as proposed by [19], we developed a list of websites from which users could those that they maintained an active presence in. Furthermore, we included the option for additions of social media websites which we had not included initially by users and after examining if indeed they belonged to the social media spectrum where either kept or omitted from the list. As results indicate, the most popular websites among our group of respondents are YouTube (92%), followed by Facebook (82%) and Wikipedia (74%).

# 5 Analysis

Partial least squares (PLS) path modelling is applied in order to validate the causal relationships amongst variables as defined in the hypotheses. The minimum amount of observations according to Smart PLS documentation is ten for each of the constructs, thus the sample of 169 users surpasses this threshold.

The validity and reliability of the items was examined by testing item loadings are above the threshold of 0.7. Since loadings were well above 0.7, we can be sure that we have reliable indicators. Additionally, convergent validity was confirmed according to the proposed methodology for PLS by [13] by checking that Average Variance Extracted (AVE) values were all greater than 0.5.

In sequence, constructs were examined to determine if they are reliable to work upon. Composite reliability values measuring the internal consistency of each con-
struct, were all above 0.7, and are therefore considered reliable [13]. Additionally, the Average Variance Extracted (AVE) values were all greater than the squared correlations for any other construct, thus confirming discriminant validity. The outcomes of the discriminant and convergent validation tests are depicted in Table 3, with AVE being depicted in bold on the diagonal of the matrix.

<table><caption>**Table 3.** Inter-Construct Correlations and Validity Measures</caption><thead><tr><th>Items</th><th>Mean</th><th>S.D.</th><th>CR</th><th></th><th>UT</th><th>HE</th><th>CA</th><th>SC</th><th>WOM</th></tr></thead><tbody><tr><td>5</td><td>3.915</td><td>1.750</td><td>0.939</td><td>UT</td><td><strong>0.739</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>5</td><td>3.348</td><td>1.896</td><td>0.959</td><td>HE</td><td>0.722</td><td><strong>0.826</strong></td><td></td><td></td><td></td></tr><tr><td>3</td><td>3.096</td><td>1.907</td><td>0.908</td><td>CA</td><td>0.284</td><td>0.278</td><td><strong>0.768</strong></td><td></td><td></td></tr><tr><td>3</td><td>4.051</td><td>1.963</td><td>0.890</td><td>SC</td><td>0.490</td><td>0.485</td><td>0.494</td><td><strong>0.730</strong></td><td></td></tr><tr><td>5</td><td>3.071</td><td>2.017</td><td>0.922</td><td>WOM</td><td>0.453</td><td>0.463</td><td>0.503</td><td>0.565</td><td><strong>0.702</strong></td></tr></tbody></table>

The hypothesized model represents a mediation model. In order to test if the mediator variable fully mediates the association between independent and outcome variable, two effects are put to test. First we examine the direct effect of utilitarian and hedonic motivation on WOM. Then we test the relationship between independent variables is mediated. In order to test these effects, a bootstrapping procedure with replacement was used taking 1000 subsamples to estimate statistical significance. Figure 1 summarizes the results of the structural model assessment of the mediated analysis.

<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Structural Model with Path Coefficients</figcaption></figure>

To test the first hypothesis, we examine the direct effect that utilitarian motivation has on WOM without the inclusion of a mediator variable (β = 0.313, p < 0.01). This
indicates that there is a positive and significant effect of utilitarian motivation on WOM, thus confirming hypothesis 1. To test hypothesis 2 we follow the mediation testing procedure proposed by [11], including the mediator construct. Utilitarian motivation has a positive and significant effect on customized advertisements (β = 0.371, p < 0.001), and customized advertisements has a positive and significant impact on WOM (β = 0.276, p < 0.01). To test if the mediation is significant, we perform Sobel's mediation test which has a significant value of 2.345 (p < 0.01), hence confirming hypothesis 2 [29]. Since the effect of utilitarian motivation on WOM in the mediated model is found to be non-significant (β = 0.096 p > 0.05), we can state that customized advertisements fully mediate this relationship.

For hypothesis 3, the result of the direct effect of hedonic motivation on WOM yields a positive and significant effect (β = 0.260, p < 0.01). Therefore, we accept the statement that hedonic motivation influences WOM in a positive manner. In the mediated model, hedonic motivations effect on the mediator (Socializing) is significant and positive (β = 0.541, p < 0.001), as is the impact of the mediator to WOM (β = 0.301, p < 0.01). The total effect of the mediation is significant according to the Sobel test statistic with a value of 2.593 (p < 0.01), confirming hypothesis 4. In total, the model explains 41.6% of variance for the WOM construct, which is at moderate levels. The direct effect of hedonic motivation to WOM is rendered as non-significant in the mediated model (β = 0.121, p > 0.05), which means that socializing ability fully mediates the effect.

When performing a multi-group analysis splitting the sample into male and female we notice that a deviation from our results occurs for male users. The effect that perceived value of customized advertisements has on WOM is found to be positive but non-significant (β = 0.209, p > 0.05), while the effect of the mediation in total has reduced significance according to the Sobel test statistic (1.746, p < 0.05).

<table><caption>**Table 4.** Effects of associations and significance levels</caption><thead><tr><th></th><th>Entire Sample</th><th>Male</th><th>Female</th></tr></thead><tbody><tr><td colspan="4"><strong>Model (Direct Effect)</strong></td></tr><tr><td>UT -&gt; WOM</td><td>0.313**</td><td>0.297**</td><td>0.341**</td></tr><tr><td>HE -&gt; WOM</td><td>0.260**</td><td>0.372**</td><td>0.322**</td></tr><tr><td><strong>R<sup>2</sup></strong></td><td><strong>0.284</strong></td><td><strong>0.369</strong></td><td><strong>0.366</strong></td></tr><tr><td colspan="4"><strong>Model (Mediated)</strong></td></tr><tr><td>UT -&gt; CA</td><td>0.371***</td><td>0.399***</td><td>0.371***</td></tr><tr><td>CA -&gt; WOM</td><td>0.276**</td><td>0.209</td><td>0.290**</td></tr><tr><td>UT-&gt; CA -&gt; WOM (Sobel Statistic)</td><td>2.345**</td><td>1.746*</td><td>2.475**</td></tr><tr><td>UT -&gt; WOM</td><td>0.096</td><td>0.052</td><td>0.220</td></tr><tr><td>HE -&gt; SC</td><td>0.541***</td><td>0.648***</td><td>0.497***</td></tr><tr><td>SC -&gt; WOM</td><td>0.301**</td><td>0.417**</td><td>0.262**</td></tr><tr><td>HE -&gt; SC -&gt; WOM (Sobel Statistic)</td><td>2.593**</td><td>3.449***</td><td>2.646**</td></tr><tr><td>HE -&gt; WOM</td><td>0.121</td><td>0.119</td><td>0.021</td></tr><tr><td><strong>R<sup>2</sup></strong></td><td><strong>0.416</strong></td><td><strong>0.463</strong></td><td><strong>0.401</strong></td></tr></tbody></table>
# 6 Discussion and Implications

Our research aim was on explaining with the aid of utilitarian and hedonic theories, what features of social media affects users intention to WOM. In particular, we examine how these motives are facilitated on social media sites, and what features trigger this effect. To this end, we hypothesize that the perceived utilitarian and hedonic value of social media sites enhances WOM through the features of customized advertisements and socializing ability. Empirical outcomes support these two theoretical contributions.

The first contribution is an explanation of the importance of utilitarian motivation. In the initial model we show that there is a strong relationship between the utilitarian motivation of users on social media and their intention to pass on information. Through the mediating construct of customized advertisements we attempt to show that the utilitarian motive is facilitated through this feature. Traditionally, the effectiveness of customized advertisements is measured by monitoring the change in sales of a product. However, recent studies have noted the significance that WOM has, since it may result in an incremental increase of sales. Our results demonstrate that social media websites, due to their ability to present products or services that are in accordance with user's likings, will positively affect sharing of information. Since customized advertisements fully mediate the relationship of utilitarian value with WOM, we can conclude that they are the prime feature in motivating users to pass on product related information.

The second contribution concerns how the hedonic value perceived when browsing products on social media leads to WOM. We use the construct of socializing ability to measure the tendency of users to engage in social interaction while browsing. We find that when users interact with peers that are interested in the same products/companies, they are more inclined to share that information with their friends.

Consequently, we conclude that utilitarian and hedonic motivations result in WOM through the value perceived from the customized advertisements, and the ability to engage in social interaction. These two features, although highly significant in explaining WOM, may not be the only ones, since outcomes reveal that 58% of variance still remains unexplored. These could be other features on social media sites of a utilitarian or hedonic nature, or even be related to product aspects.

Another interesting observation concerns the differences between genders. From our split-sample analysis, we identified that male users are not motivated to engage in WOM because of the perceived value of customized advertisements. Instead, they are more inclined to do so compared with females due to the perceived value of socializing. In the initial model however, no significant differentiation is noted between utilitarian and hedonic motivation between genders. This finding raises implications for practitioners, whom should proceed to different strategies based on gender when targeting to participate in WOM. Therefore, managers should be well aware of these contingencies when constructing and deploying a marketing strategy over social media.

Our study presents a number of limitations that future research may address. One of the most important limitations is that we examined social media as a whole, includ-
ing a wide array of sites. In order to have a holistic view of how WOM is spread over social media, they may need to be examined separately. We chose to focus on the broad term of social media, since this study is one of the first to explore motivations in such a manner. We encourage future researchers to examine additional factors, specific to social media, which may influence WOM and complement our model.

## References

1. Alba, J., Lynch, J., Weitz, B., Janiszewski, C., Lutz, R., Sawyer, A., & Wood, S. (1997). Interactive home shopping: consumer, retailer, and manufacturer incentives to participate in electronic marketplaces. *The Journal of Marketing*, 38-53.

2. Arndt, J. (1967). Role of product-related conversations in the diffusion of a new product. *Journal of marketing Research*, 291-295.

3. Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: measuring hedonic and utilitarian shopping value. *Journal of consumer research*, 644-656.

4. Brown, J., Broderick, A. J., & Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. *Journal of interactive marketing*, 21(3), 2-20.

5. Chen, Y., & Xie, J. (2008). Online consumer review: Word-of-mouth as a new element of marketing communication mix. *Management Science*, 54(3), 477-491.

6. Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2002). Hedonic and utilitarian motivations for online retail shopping behavior. *Journal of retailing*, 77(4), 511-535.

7. Choi, S. M., & Rifon, N. J. (2002). Antecedents and consequences of Web advertising credibility: A study of consumer response to banner ads. *Journal of Interactive Advertising*, 3(1), 12-24.

8. Constantinides, E., Romero, C. L., & Boria, M. A. G. (2008). Social media: a new frontier for retailers? *European Retail Research*, 22(1), 1-28.

9. Darden, W R and Reynolds, F D (1971). Shopping Orientations and Product Usage, *Journal of Marketing Research*, Vol 8, November, pp 505-508.

10. Dellarocas, C. (2003). The digitization of word of mouth: Promise and challenges of online feedback mechanisms. *Management science*, 49(10), 1407-1424.

11. Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and media- tion: a general analytical framework using moderated path analysis. *Psychological methods*, 12(1), 1.

12. Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of cus- tomer-to-customer online know-how exchange on customer value and loyalty. *Journal of Business Research*, 59(4), 449-456.

13. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. *The Journal of Marketing Theory and Practice*, 19(2), 139-152.

14. Han, J., & Han, D. (2001). A framework for analyzing customer value of internet business. *Journal of Information Technology Theory and Application (JITTA)*, 3(5), 4.

15. Hassenzahl, M., Platz, A., Burmester, M., & Lehner, K. (2000). *Hedonic and ergonomic quality aspects determine a software's appeal*. Paper presented at the Proceedings of the SIGCHI conference on Human factors in computing systems.

16. Hennig-Thurau, T., Gwinner, K. P., Walsh, G., & Gremler, D. D. (2004). Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? *Journal of interactive marketing*, 18(1), 38-52.
17. Hirschman, E. C., & Holbrook, M. B. (1982). Hedonic consumption: emerging concepts, methods and propositions. *The Journal of Marketing*, 92-101.

18. Jones, M. A., Reynolds, K. E., & Arnold, M. J. (2006). Hedonic and utilitarian shopping value: Investigating differential effects on retail outcomes. *Journal of Business Research*, 59(9), 974-981.

19. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. *Business horizons*, 53(1), 59-68.

20. Kim, Y. M., & Shim, K. Y. (2002). The influence of Internet shopping mall characteristics and user traits on purchase intent. *Irish Marketing Review*, 15, 25-34.

21. Knapp, M. L., & Daly, J. A. (2002). *Handbook of interpersonal communication*: Sage Publications, Incorporated.

22. Kourouthanasis, P. E., Giaglis, G. M., & Vrechopoulos, A. P. (2008). Enhancing user experience through pervasive information systems: The case of pervasive retailing. *International Journal of Information Management*, 27(5), 319-335.

23. Mathwick, C., Malhotra, N., & Rigdon, E. (2001). Experiential value: conceptualization, measurement and application in the catalog and Internet shopping environment. *Journal of retailing*, 77(1), 39-56.

24. Mikalef, P., Giannakos, M., & Pateli, A. (2012). Exploring the Business Potential of Social Media: An Utilitarian and Hedonic Motivation Approach. *Proceedings of the 25th Bled e-Conference, Bled, Slovenia*.

25. Mikalef, P., Giannakos, M., & Pateli, A. (2013). Shopping and Word-of-Mouth Intentions on Social Media. *Journal of Theoretical and Applied Electronic Commerce Research*, 8(2).

26. O'Brien, H. L. (2010). The influence of hedonic and utilitarian motivations on user engagement: The case of online shopping experiences. *Interacting with Computers*, 22(5), 344-352.

27. Richins, M. L., & Root-Shaffer, T. (1988). The role of evolvement and opinion leadership in consumer word-of-mouth: An implicit model made explicit. *Advances in consumer research*, 15(1), 32-36.

28. Rook, D. W. (1987). The buying impulse. *Journal of consumer research*, 189-199.

29. Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. *Sociological methodology*, 13, 290-312.

30. Sun, Y., Lim, K. H., Jiang, C., Peng, J. Z., & Chen, X. (2010). Do males and females think in the same way? An empirical investigation on the gender differences in Web advertising evaluation. *Computers in Human Behavior*, 26(6), 1614-1624.

31. To, P. L., Liao, C., & Lin, T. H. (2007). Shopping motivations on Internet: A study based on utilitarian and hedonic value. *Technovation*, 27(12), 774-787.

32. Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: contributions from technology and trust perspectives. *European Journal of Information Systems*, 12(1), 41-48.

33. Wakefield, R. L., & Whitten, D. (2006). Mobile computing: a user study on hedonic/utilitarian mobile device usage. *European Journal of Information Systems*, 15(3), 292-300.

34. Wolfinbarger, M., & Gilly, M. C. (2001). Shopping online for freedom, control, and fun. *California Management Review*, 43(2), 34-55.