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ABSTRACT

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

Unlike traditional media, social media rely on high levels of consumer engagement, involvement, co-creation and propagation. By the very act of forwarding a viral message, there is an implicit endorsement of the content and the credibility of the message is enhanced. However, the fundamental factors affecting a recipient's decision to forward a viral message have received scant attention. To address this gap, a study was undertaken using three YouTube videos as exemplars of viral peer-to-peer stimuli often shared within digital social networks. Findings suggest that sender involvement and the amount of online communication across the tie are the most critical factors influencing propagation propensity. Tie strength, while still significant, was found to be less important, while knowledge of sharing YouTube videos online had no significant impact. This study provides the first empirical evidence regarding the factors affecting the forwarding of digital content across social networks. Copyright © 2011 John Wiley & Sons, Ltd.


INTRODUCTION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

The dissemination of a viral message through social networks can achieve a range of benefits for marketers, including increased brand awareness, improved brand advocacy (Kirby & Marsden, 2006), and the generation of ‘buzz’ (Dye, 2000). Successful viral marketing campaigns have the ability to reach, and connect with, ‘more cynical, marketing-savvy consumers’ by standing out from clutter across fragmented media (Kirby & Marsden, 2006). Transmission (or ‘forwarding’) of a viral message is critically dependent on interpersonal ties. Surprisingly, however, while previous studies have suggested that these ties are important in forwarding viral messages, they have not provided empirical evidence to demonstrate this (Boase & Wellman, 2001; Dobele, Toleman, & Beverland, 2005; Jurvetson & Draper, 1997; Phelps, Lewis, Mobilio, Perry, & Raman, 2004; Rayport, 1996; Subramani & Rajagopalan, 2003; Wilson, 2000). To date, only two published studies have attempted to measure the effect of tie strength in viral marketing. One restricted itself to stages in the message transmission process other than forwarding (De Bruyn & Lilien, 2008), while the other only examined the forwarding of online survey petitions (Norman & Russell, 2006). Neither of these studies contains any empirical data regarding the effect of tie strength on the forwarding of online viral messages. As the success of viral marketing relies fundamentally on the transmission of information between consumers, it is of critical importance to understand how social ties between individuals affect forwarding behaviour. The current study seeks to empirically test the factors claimed in the literature to be the main drivers of forwarding behaviour. The remainder of the article is set out as follows. First, extant literature on forwarding behaviour and propagation is reviewed. Research hypotheses are then developed, and a conceptual model is presented. Next, the empirical study is described, and the findings are discussed. Managerial implications are then considered, limitations noted, future research directions outlined and conclusions drawn.

FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

An essential step in the spread of a viral message is the act of actually forwarding the message. As previously noted, despite its importance, few studies have examined this phenomenon (De Bruyn & Lilien, 2008; Kibby, 2005; Norman & Russell, 2006; Phelps et al., 2004; Sun et al., 2006). Phelps et al. (2004) propose that a typical viral message transmission process consists of four stages: the receipt of the message, the decision of whether or not to open the message, the comprehension of the message, and the decision of whether or not to forward the message to others. Unfortunately, this model does not include any consideration of the tie strength between the sender and the recipients. Kibby (2005) asserts that the ‘persuasive appeal of the sender’ and an accompanying form of emotional response are two important factors that influence the forwarding of a viral message. Dobele, Lindgreen, Beverland, Vanhamme, and van Wijk (2007) agree with Kibby (2005) that the ability of a viral message to trigger an emotional response is crucial. Critically, however, this has not been empirically tested. Indeed, despite the pivotal role that these drivers must play in determining forwarding behaviour, there has been almost no investigation of them in the literature. In the context of online survey petitions, Norman and Russell (2006) empirically determined that involvement with the survey topic, size of a participant's social network, and tie strength have a significant impact on what they dubbed ‘the pass-along effect’. When investigating forwarding behaviour in relation to music-related communication, Sun et al. (2006) found that both opinion leadership and opinion seeking are significantly associated with online forwarding behaviour. This finding led Sun et al. (2006) to speculate that the ‘interactive and anonymous nature of the Internet’ (p.1118) has resulted in the blurring of the traditional line between opinion leadership and opinion seeking.

In summary, most viral marketing studies have ignored the forwarding decision phase, apparently assuming that the appeal of the viral message alone determines the extent to which it is propagated (Dobele et al., 2007).

CONCEPTUAL MODEL

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

The conceptual model (see Figure 1) outlines the hypothesised relationships among the variables identified as having a potential impact on the likelihood of forwarding a viral message. As the scope of the current study is limited to viral messages in the form of YouTube videos, the phrase ‘viral message’ is hereafter referred to interchangeably with ‘YouTube video’.

image

Figure 1. Conceptual model of factors affecting an individual's likelihood of forwarding a YouTube video across a tie.

Download figure to PowerPoint

Sender involvement is thought to play an important role in viral message transmission (Dobele et al., 2007; Phelps et al., 2004). Norman and Russell (2006) found that message involvement leads to a greater likelihood of it being forwarded; however, as noted previously, this finding has not been applied or tested within the viral marketing domain. The reason for sender involvement with the YouTube video being included in the interactions is that if YouTube video involvement is low, the likelihood of forwarding it will also be low, meaning that the moderating variables can only play a significant part if sender involvement with the YouTube video is significantly different from zero. Thus, it is hypothesised that

H 1. The greater a sender's involvement with a YouTube video, the greater the likelihood of forwarding it across a tie.

Strong ties are more likely to be activated for the flow of information (Brown & Reingen, 1987; Reingen & Kernan, 1986). Norman and Russell (2006) found that tie strength has a positive impact on forwarding likelihood when the message is personally involving, but this has not yet been tested in the viral marketing domain. In line with this finding, it is therefore hypothesised that

H 2. A sender's tie strength has a multiplicative effect with sender involvement in increasing the likelihood of a YouTube video being forwarded across a tie.

Those with a greater knowledge of sharing YouTube videos online are more likely to engage in forwarding behaviour (Phelps et al., 2004), meaning that knowledge of sharing should be positively associated with the act of sharing. Accordingly, it is hypothesised that

H 3. A sender's knowledge of sharing YouTube videos online has a multiplicative effect with sender involvement in increasing the likelihood of a YouTube video being forwarded across a tie.

A viral message is able to move quickly within a close-knit network due to the frequent contact that each group member has with every other member (Boase & Wellman, 2001). This means that an involving YouTube video should have a greater likelihood of being forwarded across a tie that is characterised by a significant amount of online communication. It is hypothesised that

H 4. The amount of online communication that a sender has across the tie has a multiplicative effect with sender involvement in increasing the likelihood of a YouTube video being forwarded across that tie.

In order to diagrammatically represent the above hypothesised relationships, a conceptual model has been developed (see Figure 1).

RESEARCH DESIGN

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

Sample

A convenience sampling technique was employed in this study, drawn from a population of undergraduate students enrolled at a large Australian university on the eastern seaboard. This sample population was deemed suitable due to its high level of engagement with computer-mediated communication (Merchant, 2001). Also, as the population is predominantly Generation Y, its buying habits are strongly influenced by the Internet, making these people one of the main segments targeted by online marketers (Wolburg & Pokrywczynski, 2001). The questionnaire was administered during the recess of two consecutive lectures for a first-year business unit. In total, 173 completed questionnaires were included in the analysis. The majority of respondents were under 20 years of age, with none over 25.

Stimuli

Three YouTube videos were used as stimuli. The motivation for using multiple videos was twofold: to provide multiple data sets, which would allow for checking the consistency of the findings, and to have a precautionary measure in case any of the videos had undergone viral dissemination ahead of the administration of the survey, therefore invalidating the result through loss of impact on the participants.

The selection of these YouTube videos followed three criteria. First, the videos had to contain an element of surprise, in the form of a humorous twist. Second, the videos needed to be relatively new to audiences within Australia in order to maximise the number of respondents who had not previously seen the videos. This was achieved by selecting videos released as close as possible to the data collection dates. Third, the videos needed to contain a marketing message presented in a clear and unambiguous manner. All three YouTube videos were pre-tested with the help of members of the target population in order to ensure that they satisfied the above three criteria.

The three YouTube videos selected for the current study include Telstra Bigpond's Kiss (http://www.funnyplace.org/stream.php?id=7662), Toom Baumarkt's Road Bumper (http://www.youtube.com/watch?v=9FQG6XsqQa4&feature=related), and Carling's Cracking (http://www.youtube.com/watch?v=ATXhTULzD18). A fourth YouTube video, Hygenix's Underwear (http://www.funnyplace.org/stream.php?id=7661), was shown prior to the commencement of the survey in order to establish a baseline emotion before the presentation of the stimuli.

Survey

The questionnaire contains three sections. The first section seeks personal information from each respondent, including demographic profiling questions such as those about age and gender, as well as scales measuring online socialising behaviour. The second section asks respondents to nominate one particular friend with whom they communicate most over the Internet, with the subsequent scales relating to their relationship. The third section requires respondents to view a YouTube video and then answer the scale items for that video; this process is repeated for all three videos. All conceptual model variables are measured using 10-point scales. The questionnaire was pre-tested with members of the target population, as well as three research experts. Some minor changes to the wording of the scales resulted from this process.

Sender involvement with the YouTube video was measured using a modified subset of the items developed by Zaichkowsky (1985), with additional items developed to capture elements of humour and entertainment.

To measure tie strength, the four indicators suggested by Granovetter (1973) were considered: the amount of time dedicated to the tie, its emotional intensity, its level of intimacy, and the amount of reciprocity shown within the tie. Frequent contact, or significant time dedicated to a relationship, is often viewed in the literature as being characteristic of a strong tie (e.g. Blumstein & Kollock, 1988; Brown & Reingen, 1987; Hansen, 1999). Marsden and Campbell (1984) conclude that measures of ‘closeness’, or emotional intensity, are the best indicators of tie strength because they are free of contamination from predictors such as friendship and co-worker status. One thing that Marsden and Campbell (1984) failed to do, however, was to fully define the constructs they measured; as a result, the constructs of emotional intensity and intimacy are not properly distinguished. Few studies have tried to capture the reciprocal element of tie strength (Frenzen & Davis, 1990; Shulman, 1976).

The current study used formative measures for tie strength to construct an index (Diamantopoulos & Winklhofer, 2001). The three components of the index, including time dedicated to the tie, reciprocity, and closeness, were each measured using their own combination of items. Time invested in the tie was measured using an item developed for the study, while emotional proximity was measured using a modified version of a scale developed by Camarena et al. (1990).

The indicators of emotion intensity and intimacy proposed by Granovetter (1973) were combined in the current study as they were decided to be conceptually similar (Camarena et al., 1990). In addition, a scale item from Frenzen and Davis (1990) was taken and modified in order to capture willingness to share personal views across the tie. Pre-testing revealed that friendship is characterised by wanting to do favours without expecting them to be returned. Two items from the Frenzen and Davis (1990) scale concerning the performance of favours were taken and modified based on this finding, while two more items were included to gauge the willingness of both respondent and their nominated friend to go out of their way to help each other.

Knowledge of sharing YouTube videos online was measured using a modified version of a scale developed by Roehm and Sternthal (2001) for measuring a person's familiarity and experience with a good, service or product category. Pre-testing revealed that the term ‘forwarding’ tended to refer exclusively to the email channel in the context of this scale, hence why the term ‘sharing’ was used instead. Amount of online communication across the tie was operationalised using two modified items from the knowledge of sharing YouTube videos scale, as well as two additional items to capture the reciprocal element of the online communication. A single item scale was devised to measure the likelihood of a YouTube video being forwarded across a tie. Once again, the current study opted not to use the term ‘forwarding’ due to its synonymity with the email channel, using the term ‘send’ in its place.

RESULTS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

The assumptions underlying multiple regression analysis were satisfied, and all scales were found to be statistically reliable (Cronbach, 1951) and valid (Nunnally, 1978). During hypotheses testing, each predictor is tested at the 5 per cent significance level. Mean scores and percentages for all measures are shown in Table 1. All three YouTube videos showed similar likelihoods of being forwarded (35%–40%; see Table 1). The multiple regression results are presented in Table 2.

Table 1. ‘Likelihood of the YouTube video being forwarded across a tie’ scale—means and per cent likely (6–10)
‘Likelihood of the YouTube video being forwarded across a tie’ scaleYouTubeYouTubeYouTube
video 1video 2video 3
Mean4.434.774.73
% Likely (6–10)36.940.340.6
Table 2. Multiple regression results
 YouTube video 1YouTube video 2YouTube video 3
Standardised beta estimateStandard errort-ValueStandardised beta estimateStandard errort-ValueStandardised beta estimateStandard errort-Value
  • Note:

  • *

    p-value < 0.001.

  • **

    p-value < 0.01.

  • ***

    p-value < 0.05.

  • ‘n.s.’ indicates non-significant.

  • Model 1 (YouTube video 1): adjusted R2 = 0.338, F = 22.982, p-value < 0.001.

  • Model 2 (YouTube video 2): adjusted R2 = 0.359, F = 25.133, p-value < 0.001.

  • Model 3 (YouTube video 3): adjusted R2 = 0.455, F = 36.707, p-value < 0.001.

Sender involvement with the YouTube video0.400.222.72**0.560.223.94*0.610.214.34*
Tie strength−0.310.01−2.00***−0.440.01−3.10**−0.330.01−2.42***
Knowledge of sharing YouTube videos online0.000.01−0.01n.s.0.090.010.99 n.s.0.090.011.16 n.s.
Amount of online communication across the tie0.500.023.91**0.390.023.04**0.340.022.88**

Overall Model Performance

Each of the multiple regression models tested are significant, with models 1, 2, and 3 returning F-values of 22.98, 25.13, and 36.71, respectively (all p-values < 0.001, see Table 2). The adjusted R-square values indicate that each model accounts for a reasonable amount of variation in the likelihood of a sender forwarding a YouTube video across a tie (see Table 2). The model for YouTube video 1 (Kiss) explains 33.8% of the variation, while the models for YouTube videos 2 (Road Bumper) and 3 (Cracking) explain 35.9% and 45.5% of the variation, respectively.

Sender Involvement with the YouTube Video

The independent variable sender involvement with the YouTube video is the first to be considered. All three models have positive standardised beta estimates (0.40, 0.56, and 0.61 for models 1, 2, and 3, respectively). Thus, H1 is supported for all three YouTube videos. This indicates a significant positive relationship between sender involvement with the YouTube video and the likelihood of forwarding a YouTube video across a tie.

Tie Strength

Tie strength is the first moderating variable (Z1) under consideration. All three models demonstrate significant negative standardised beta estimates (–0.31, –0.44, and –0.33 for models 1, 2 and 3, respectively). Thus, H2 is not supported by any of the three YouTube videos. This indicates that a sender's tie strength has a multiplicative effect with sender involvement in decreasing the likelihood of a YouTube video being forwarded across a tie.

Knowledge of Sharing YouTube Videos Online

Knowledge of sharing YouTube videos online is the second moderating variable (Z2). All three YouTube videos produced non-significant multiplicative effects (standardised beta estimates of 0.00, 0.09, and 0.09 for models 1, 2, and 3, respectively). Thus, H3 is not supported for any of the three videos. This result indicates that a sender's knowledge of sharing YouTube videos online does not have a significant multiplicative effect with sender involvement in increasing the likelihood of a YouTube video being forwarded across a tie.

Amount of Online Communication across the Tie

The third moderating variable under consideration is amount of online communication across the tie (Z3). All three models resulted in significant multiplicative effects with sender involvement with the YouTube video (standardised beta estimates of 0.50, 0.39, and 0.34 for models 1, 2, and 3, respectively). Thus, H4 is supported for all three YouTube videos. The positive standardised beta estimate in each model demonstrates that the multiplicative effect is positive, as expected. The amount of online communication that a sender has across the tie therefore has a significant multiplicative effect with sender involvement in increasing the likelihood of a YouTube video being forwarded across that tie.

DISCUSSION

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

Sender Involvement with the YouTube Video

Kirby and Marsden (2006) argue that to enable a message to become ‘viral’, it needs to contain something valuable to those who receive it—in other words, a message that is able to involve the recipient or provide an incentive for them to forward it. Involvement is considered to be a crucial determinant of forwarding behaviour (Dobele et al., 2007; Phelps et al., 2004) and a key consideration in the ‘seeding’ or accurate targeting of messages (Kaikati & Kaikati, 2004; Phelps et al., 2004).

By formulating a marketing message that is relevant to a particular consumer segment, the recipient within that segment is more likely to be persuaded by the message (Petty & Cacioppo, 1979) and share it with others in their social network (Westbrook, 1987). From a homophily principle perspective (Lazarsfeld & Merton, 1954), this is a consequence of similar individuals being more likely to interact online, thus increasing the chances of a viral message disseminating through targeted segments (Dobele et al., 2005). In the context of viral marketing, this means that a message is more likely to be forwarded, and recent studies have shifted their focus towards viral advertising (Dobele et al., 2007; Phelps et al., 2004) as creative agents that may themselves embody value.

Incentive schemes, on the other hand, while having had some spectacular successes in the past (e.g. Hotmail), could now be viewed as limited in the potential incentives that they can provide to recipients. For example, while Dodds, Muhamad, and Watts (2003) found that viral message transmission across social ties was sensitive to the use of incentives, excessive incentives in themselves may actually lower the credibility of the message (Leskovec, Adamic & Huberman, 2007).

This study views involvement as the essential ingredient of a viral message that facilitates its spread through social networks. When investigating forwarding behaviour in relation to online surveys, Norman and Russell (2006) found that involvement facilitates word-of-mouth communication, which leads to greater forwarding likelihood. However, this relationship has not been empirically tested with regard to viral message involvement.

With this position, it becomes apparent that there is a noticeable gap in the viral marketing literature. This is that involvement from the sender's perspective and involvement from the potential recipient's perspective have not been distinguished. This is surprising considering that it has been argued that in order for a viral message to be persuasive, ‘an appeal must be based on objects of agreement that are shared by both sender and receiver’ (Kibby, 2005, p.785). A limitation of De Bruyn and Lilien's (2008) study, for example, was that they did not obtain relevant recipient-side variables, such as the recipients' interest in the subject. Norman and Russell's (2006) finding that forwarding likelihood increases with tie strength was on the condition that involvement was high from the sender's point of view but again did not consider the recipient's point of view. Dobele et al. (2007) also fail to distinguish sender and potential recipient involvement when positing that an emotional connection between the viral campaign and the individual must be established to increase forwarding likelihood. With respect to Kibby's (2005) position, it is noted that a viral message may be forwarded even if the message is not involving to the sender. If the sender perceives that the viral message involvement may be high on the part of the potential recipient, this could influence the sender's forwarding decision. The homophily principle suggests that friends tend to be similar to one another, meaning that little difference is expected between the two types of involvement. By gathering data from the sender's side, it is therefore assumed that involvement from the sender's perspective and perceived recipient involvement are conceptually similar.

This study concludes that sender involvement with the YouTube video, tie strength, and the amount of online communication across the tie explain a significant amount of variation in likelihood of forwarding a YouTube video across a tie. These findings provide a better insight into the driving forces of viral message forwarding behaviour.

As discussed previously, Phelps et al. (2004) and Dobele et al. (2007) suggest that sender involvement with the YouTube video is positively correlated with the likelihood of forwarding a YouTube video across a tie, although no empirical evidence was provided. The current study shows that sender involvement with the YouTube video is a significant predictor in all three regression models. The current study therefore provides empirical support for the previously untested claims that message involvement is positively associated with the likelihood of that message being forwarded across a particular tie.

Tie Strength

As previously mentioned, social ties studies have found that strong ties are more likely to be activated for the flow of information (Brown & Reingen, 1987; Reingen & Kernan, 1986). Brown and Reingen (1987) argue that this is because of greater frequency of social contact within the strong tie network. In the context of online survey petitions, Norman and Russell (2006) found that tie strength is positively associated with forwarding likelihood. This study, however, demonstrates that tie strength has a significant negative interaction effect on the impact of sender involvement, resulting in a decreased forwarding likelihood. This finding is in contrast to the conclusion drawn by Norman and Russell (2006). A possible explanation for the negative tie strength is that close friends may be more discriminating in terms of the viral messages they forward to each other. If the content of a viral message does not meet an individual's quality threshold (Phelps et al., 2004), that individual may choose not to forward it to a close friend in order to avoid being deemed an online ‘pest’. Conversely, individuals may be less discriminating with regard to message quality when opting to forward a viral message to friends or contacts with whom they are not as close. This may provide an explanation as to why viral messages propagate across weaker ties. The current study's inability to replicate Norman and Russell's (2006) finding is indeed interesting and warrants further investigation.

Knowledge of Sharing YouTube Videos Online

Existing viral marketing literature suggests that knowledge of sharing YouTube videos online is positively associated with likelihood of forwarding a YouTube video across a tie (Phelps et al., 2004). The authors believed that this was driven by a need to ‘connect and share with others’ (Phelps et al., 2004, p.337). The current study, however, does not support this hypothesis. Knowledge of sharing YouTube videos online was found to have an insignificant interaction effect on the impact of sender involvement in increasing the likelihood of forwarding a YouTube video across a tie (p-value > 0.05 for all three YouTube videos). One possible explanation for these findings is the high significance of sender involvement with the YouTube video. If the YouTube videos presented were not considered to be involving enough by the respondents, their decision to not forward the videos may not be affected by their familiarity and expertise of sharing YouTube videos online. Conversely, if the YouTube videos were, in fact, considered to be involving, the respondents may have chosen to forward the videos regardless of whether they had ever forwarded YouTube videos in the past.

Amount of Online Communication across the Tie

Our findings indicate that the amount of online communication across the tie has a significant interaction effect on the impact of sender involvement and hence on the likelihood of forwarding a YouTube video across a tie (p-value < 0.01 for all three YouTube videos). This is an important result, as it suggests that while the role of tie strength does play a part in viral message transmission (De Bruyn & Lilien, 2008), it is the amount of online communication across the tie that is more important in determining forwarding likelihood. For example, if a sender and potential recipient are close friends yet rarely communicate online, the current study suggests that a YouTube video is less likely to be forwarded across the tie than if there was greater online communication across the tie.

It is interesting to note that the use of university students as part of the sample population did not affect the significance of the amount of online communication across the tie. This is despite their tendency to have high levels of engagement with computer-mediated communication (Merchant, 2001), especially with close friends (Koku, Nazer, & Wellman, 2001). While the significance of tie strength was possibly affected by extremity bias (Zikmund, Ward, Lowe, & Winzar, 2007), this appears to have not been the case with the amount of online communication across the tie, even though respondents reported consistently high amounts of online communication across the ties.

Variable Significance

The regression results show that each variable's ability to significantly explain the variation in forwarding likelihood was quite consistent over the three YouTube videos. The standardised beta estimates in Table 1 show that the positive impact of sender involvement with the YouTube video is much greater than the other significant variables in each respective regression model. This suggests that sender involvement with the YouTube video dominated the respondents’ decision of whether to forward each video to their nominated friend. It is possible that the responses to the likelihood of the YouTube video being forwarded across a tie scale may have been more of a reflection of sender involvement alone, rather than a balanced decision-making process based on how close the nominated friends were to the respondents, and how much they communicated online.

Managerial Implications

Managers are advised to not simply rely on the social network itself to facilitate the spread of a viral message. The existence of a social network is a necessary precursor to the propagation of a viral message; however, this in itself does not ensure that the message will ‘go viral’. The current study has identified variables that impact an individual's likelihood of forwarding a YouTube video across a tie, thus informing managers of the key factors that drive the propagation of a viral message through social networks. Based on these results, managers would need to recognise that the main factor influencing the success of a YouTube video being forwarded is the level of involvement it generates. A thorough pre-testing of any video developed for a viral campaign would therefore be advisable to ensure that the video engages targeted consumers. In the presence of stronger ties, optimising engagement levels would also help meet individuals’ quality thresholds when deciding whether or not to forward the video. Lastly, the amount of online communication between targeted consumers also has a significant role in facilitating the spread of a viral message within that group, and so managers should take this into account when designing a viral campaign.

Limitations and Future Research

This study focused only on viral marketing that occur over the Internet. Future studies may consider applying these results to other social media such as mobile phones (Barnes & Scornavacca, 2004). As the scope was restricted to YouTube videos containing a humorous twist, the findings should also be tested with videos containing other types of emotional appeal or forms of viral messages other than videos. It is suggested that future studies also examine forms of dyadic relationships other than friendships to test the applicability of the findings in broader social contexts. The ability to communicate online on a one-to-many basis, such as on a social network site page, a blog, or a distributed email, should also be taken into account in future research.

The current study focuses on students within an Australian university. Future studies could investigate the forwarding behaviour of other subsets of the population to gain a better understanding of the effect of variables such as Internet usage and age.

The conceptual model in the current study did not incorporate opinion leadership as a moderating variable. Although the impact of opinion leadership on viral message transmission has been questioned (Watts & Dodds, 2007), it warrants further examination, as it is regarded in the literature as having significant importance in the field of computer-mediated communication (e.g. Sun et al., 2006). Other factors such as the degree of personalisation of the viral message (Phelps et al., 2004) were considered to be beyond the scope of the current study. Perceived recipient involvement with the YouTube video was not included as part of the model, as it was assumed that it is similar to, or possibly even identical to, sender involvement with the YouTube video. Future studies may test the validity of this assumption.

Finally, while this study has established that sender involvement, tie strength, and the amount of online communication across the tie all have a significant association with forwarding likelihood, future work should also consider examining online forwarding behaviour in a more exploratory fashion. This may help to identify additional reasons why individuals engage in online forwarding behaviour. It is hoped that the current study may provide a foundation for future research in this area.

CONCLUSIONS

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

It has been shown that existing viral marketing literature has paid little attention to either online forwarding behaviour or to how the relationship between the sender and the potential recipient affects the likelihood of a particular viral message being forwarded. The current study has sought to address these gaps by empirically testing the main drivers of forwarding behaviour that have so far only been tentatively identified in the literature. The major finding of the current study is that sender involvement, tie strength, and amount of online communication across the tie are the most critical factors in affecting the likelihood of a YouTube video being forwarded across a tie. Knowledge of sharing YouTube videos online had no significant impact. The variation accounted for by the models suggests that there are other factors that impact forwarding likelihood but are absent from the current conceptual model. Future research needs to identify what these other variables are.

Appendix A: Questionnaire items used in the study

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES

Sender Involvement with the YouTube Video Scale

  • The YouTube video has no relevance to me.
  • The YouTube video is interesting to me.
  • The YouTube video means nothing to me.
  • The YouTube video is unappealing to me.
  • The YouTube video is entertaining to me.
  • The YouTube video is amusing to me.

Tie Strength Scale

  • I invest significant time into my relationship with this friend.
  • When I do a large favour for this friend, I do not seek for them to do a large favour in return.
  • This friend would be happy to do a large favour for me without expecting me to return it.
  • I would go out of my way to help this friend.
  • This friend would go out of their way to help me.
  • This friend is someone with whom I can share my personal views.
  • This friend accepts me no matter what I do.
  • This friend understands what I'm really like.
  • This friend is important to me.
  • I am satisfied with the relationship I have with this friend.

Knowledge of Sharing YouTube Videos Online Scale

  • I am well acquainted with sharing YouTube videos with my friends over the Internet.
  • I am familiar with sharing YouTube videos with my friends over the Internet.
  • I often share YouTube videos with my friends over the Internet.
  • I regularly share YouTube videos with my friends over the Internet.
  • I consider myself to be an expert at sharing YouTube videos with my friends over the Internet.

Amount of Online Communication across the Tie Scale

  • I often keep in touch with this friend over the Internet.
  • I give online opinions to this friend whenever they send me something over the Internet.
  • I receive online opinions from this friend whenever I send them something over the Internet.
  • I regularly keep in touch with this friend over the Internet.

Likelihood of the YouTube Video Being Forwarded Across a Tie Scale

  • Would you send the YouTube video to this friend?

REFERENCES

  1. Top of page
  2. ABSTRACT
  3. INTRODUCTION
  4. FORWARDING BEHAVIOUR IN PEER-to-PEER COMMUNICATION
  5. CONCEPTUAL MODEL
  6. RESEARCH DESIGN
  7. RESULTS
  8. DISCUSSION
  9. CONCLUSIONS
  10. Appendix A: Questionnaire items used in the study
  11. REFERENCES
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