Present-day PR practice
Are social media a more effective PR tool for companies than
newspapers?
Laura Overdorp
10812830
Master’s Thesis
Graduate School of Communication
Master’s programme Communication Science
Track Corporate Communication
Supervised by dr. P. Verhoeven
Abstract
Social media have been praised for their assumed interactive effectiveness and usefulness for public relations (PR). However, little empirical evidence has been found so far to reach the conclusion that social media actually are as useful as has been argued by many scholars and professionals. This study adds to this discussion by investigating the extent to which social media are more effective than traditional media in establishing relational outcomes and intention to engage in word of mouth (WOM). An online experimental survey with a between subject design was carried out to measure the difference between the effect that a Tweet and a news article had on relational outcomes and people’s intention to engage in WOM. The Twitter and news article message were both divided into three categories: an informational, dialogical and community message. The survey was distributed via Facebook and e-mail, and filled out by 197 respondents. The results show that the Tweet and the news article were equally as effective in establishing relational outcomes and an intention to engage in WOM. When only comparing the message types, community building messages were found to be significantly more effective than informational message in establishing both relational outcomes and an intention to engage in WOM. Thus, this study too, did not find empirical evidence to support the assumption that social media have more advantages for PR
professionals than traditional media. Moreover, social media and traditional media appear to be equally effective communication channels.
Introduction
In this society of online connectivity and over-stimulation, public relations professionals (PRPs) are faced with the task of getting their publics to notice their
organization, influence them and establish a relationship. Before online technology, PRPs were mostly dependent on traditional media as a one-way communication tool to reach publics. However, with the emergence of social media, the one-way communication and traditional practice of PR has changed (Valentini, 2015). Organizations have to actively find their publics and attract their attention with something relevant (Luoma-aho & Vos, 2010).
Quoting Benjamin Franklin’s words of wisdom: “Either write something worth reading or do something worth writing about”. This is easier said than done, because there is not one
definition of what is considered to be relevant to publics, and there is not one designated place where organizations can find their public on social media.
Since the emergence of the internet, public relations research has recognized its potential use for PRPs in their efforts to build relationships (e.g. Kent & Taylor, 1998). Early research on the practical use of communication technologies (Johnson, 1997) already stressed the importance of improving two-way communication and an audience-focus through new online technologies. Moreover, Johnson (1997) argued that many essays in public relations journals had discussed new communication technologies, but no theoretical frameworks had been established. The last few years many scholars have studied the practice of online media in relation to PR, which has led to frameworks and practical implications for PRPs to
incorporate online technologies. To date, most companies have already fully integrated communication technologies such as e-mail and intranet (D’Urso & Pierce, 2009). Therefore, research has narrowed their focus to the practical use of specific social media such as Twitter and Facebook (e.g. Saffer, Sommerfeldt & Taylor, 2013).
engage with their stakeholders. They found that social media are mainly used as a one-way communication tool and less than 20% of the total Tweets demonstrate some form of
conversation (Lovejoy, Waters & Saxton, 2012, p. 313). Other studies (e.g. Valentini, 2015) also found that most organizations fail to use the full interactive potential of social media and argue that it should be used for bigger purposes.
Studies that question the use of social media by organizations originate from the recent discussion on the effectiveness of social media in general. Most studies have focused on the best way to use social media and ignored the question whether social media are actually a useful corporate communication tool. In other words, most studies so far have focused on the ‘how’ instead of questioning ‘if’ social media should be implemented in the professional field of public relations. This discussion started by investigating whether this ‘so valued’ power of social media was evidence based, or merely a premature conclusion due to the popularity and worldwide acceptance of Twitter and Facebook. Previous literature that questioned the effectiveness of social media has focused on the effects for PR education (Taylor & Kent, 2010), employees (Wright & Hinston, 2008), politics (Trammell, 2006), PR crises (Sweetser & Metzgar, 2007), and found no results supporting the effectiveness of social media use for PRPs. The conflicting results on the use of social media led to a critical assessment of the effectiveness of social media as a communication tool (Taylor & Kent, 2010). This
aforementioned effectiveness is relative, since social media only have to be more effective than its alternative option (traditional media) to be considered as a more suitable tool to practice PR. Therefore, the research question is: to what extent is conveying corporate messages through social media more successful in establishing relationships with publics and generating electronic word of mouth than traditional media?
Theoretical background
To date, many definitions of PR exist. Harlow (1976) analysed the evolution of dominant terms over almost a century. “Using communication to build and hold goodwill” was a common theme in public relations for the first one or two decades of the 20th century, according to Harlow. The working definition he gave of PR is a combination of all these different terms:
“Public relations is a distinctive management function which helps establish and maintain mutual lines of communication, understanding. acceptance and
cooperation between an organization and its publics; involves the management of problems or issues; helps management to keep informed on and responsive to public opinion; defines and emphasizes the responsibility of management to serve the public interest; helps management keep abreast of and effectively utilize change, serving as an early warning system to help anticipate trends; and uses research and sound and ethical communication techniques as its principal tools (1976, p.36).”
This was the main definition of PR before the invention of internet and new computer technologies. With the emergence of ICT and social media, many scholars have proposed different definitions, since the relationship between organizations and its publics has
drastically changed (Valentini, 2015). New communication technologies such as social media equalize the power distribution between publics and organizations (Berger, 2005). There is no hierarchy on the internet, it is dynamic and much less controllable than traditional media. Regardless of the emergence of new definitions due to communication technologies, two core traditions of PR remain the same. The main function of PR professionals (PRPs) is to
influence publics and strengthen the organizational reputation by distributing informational corporate messages, followed by establishing and fostering relationships with publics. These core functions can be referred to as the informational and relational tradition of PR (Valentini, 2015). For the informational tradition it is important for PRPs to inform publics and to create awareness for the organization among publics. In order to do so, PRPs try to gain free
publicity (Nakra, 1991). Therefore, an important goal of PRPs is to raise people’s intention to spread the message and engage in WOM. When people are aware of the organization’s existence, the relational tradition of RPRs is to establish relational outcomes, which will be discussed is more detail. Even though the core functions of PR remains the same, new communication channels have changed the practice of these core traditions.
The informational and relational tradition of PR will be discussed separately. The literature will give a more in depth view per PR tradition, on how traditional and social media can affect relational outcomes and intention to engage in WOM.
Informational PR tradition
First, the informational tradition of PR includes telling the company’s story and
informing publics. This is one-way asymmetrical communication from an organization, which is spread in order to persuade publics and thereby influencing the corporate reputation
(Grunig & Grunig, 1992). A corporate message can be defined as informational when “an organization sends information about its activities or its history, vision or objectives, or detailed information about finances, performance, governance policies or ethical standards [...] to boost accountability and public trust” (Lovejoy & Saxton, 2012, p. 343). Thus, it is important to critically asses informational communication efforts of an organization, since informing people and creating awareness for the organization is the first step towards establishing relationships with publics. PRPs can decide whether to spread their information
via social media channels or traditional media to affect relational outcomes and people’s intention to engage in WOM.
Effects on relational outcomes
Social media are useful channels to spread corporate information, since it can give PRPs the possibility to bypass gatekeepers in the media who filter and frame the original message (Kent, 2013; Linke & Zerfass, 2013; Wright & Hinson, 2008). As mentioned before, it was found that many companies use social media to mainly inform. When all companies spread all their corporate information on social media, organizations will not stand out from the clutter of information. Moreover, publics might ignore or even become irritated by the organizations solely sending out information. Therefore, PRPs have to be critical of their social media practices and only send out relevant information tailored to their publics in order to establish meaningful relationships (Lovejoy & Saxton, 2012).
The same critical view on the message frequency and the information quality in a press release is required for traditional media (Theaker & Yaxley, 2013). However,
gatekeepers such as journalists can prevent organizations from spreading too much or irrelevant information. Another benefit of having a company’s information published by a newspaper, is the external source credibility, which will be discussed in more detail further in this article.
Effect on the intention to engage in WOM
An effective way for PRPs to gain free publicity is to motivate publics to spread a corporate message. In order for a message in traditional media to spread, organizations will have to rely on more traditional forms of WOM, such as publics talking about their message face-to-face. This underlines the downside of traditional media in comparison to social media with regard to WOM. Traditional WOM is usually diffused between strong ties, such as family and friends (Steffes & Burgee, 2008; Chung & Tsai, 2009). Tie strength means how
closely people are related to each other. This can be determined by the extent of time, emotional closeness, intimacy and reciprocity of a relationship between people (Frenzen & Davis, 1990). This became a more important factor for WOM with the emergence of social media (Dellarocas, 2003).
WOM via social media is also called electronic WOM (eWOM). People’s social networks consist of both strong and weak ties (e.g. acquaintances and strangers). A message can spread more easily and to more people on social media, because the message can easily diffuse through weak ties between disconnected groups of people as well as through strong ties (Groeger & Buttle, 2014). Thus, it takes less effort to spread a message through eWOM then via traditional WOM. On the other hand, research shows that WOM or eWOM is more likely to spread through strong ties (Brown & Reingen, 1987; Frenzen & Nakamoto, 1993). Thus, the ability for eWOM to spread through weak ties is not a considerably bigger
advantage for social media.
In the aforementioned debate on the effectiveness of social media, it was also argued that traditional media can be a more suitable communication channel to spread information than social media for PRPs. This can be explained by the idea that information through traditional media changes the source of the information. Traditional media can be considered as a more objective source than the organization itself, therefore more credible and might ultimately have a more positive effect on the organization, e.g. the public trust (Metzger, 2007;
Goldsmith and Horowitz, 2006; Groeger & buttle, 2014; Hornik, Shaanan Satchi, Cesareo & Pastore, 2015). Building trust among publics is an important way for PRPs to establish and foster relationships. Moreover, in line with the Credibility Theory (Birnbaum & Stegner, 1979), research has shown that when a source is perceived as more credible or trustworthy, they are more likely to engage in word of mouth (Brown, Broderick, & Lee, 2007; Chiu, Hsieh, Kao & Lee, 2007; Phelps, Lewis, Mobilio, Perry & Raman, 2004; Yeh & Choi, 2011).
It is therefore hypothesised that:
H1. Corporate informational messages through traditional media have a more positive
relational outcome than informational messages through social media.
H2. Corporate informational messages through traditional media show a higher intention of
publics to engage in word of mouth than informational messages on social media.
Relational PR tradition
Establishing and fostering relationships with stakeholders is part of the relational tradition of PR. Two-way symmetrical communication is said to be the best (Grunig & Grunig, 1992; Van Ruler & Verčič, 2005) and most ethical (Meisenbach, 2006) way to
engage with stakeholders. Building on this view, a distinction can be made between two types of two-way symmetrical communication messages for the relational tradition of PR. There are communicational messages that directly spark interactive conversations (dialogical
messages) and there are messages that try to strengthen the tie between organizations and its
followers without creating the expectancy of an interactive conversation (community
messages). Both types of messages should ultimately help PRPs to establish and maintain a
‘community’ for their organization (Lovejoy & Saxton, 2012). Organizations can chose to either use traditional media or social media as their communication channel to establish relational outcomes and WOM.
The effect of relational messages
Social media are online communication tools, which include interactive social networking sites and are based on consumer generated content (Taylor & Kent, 2010). This tool offers PRPs the opportunity to engage in interactive relational communication efforts.
Scholars suggest that social media hold more potential to establish and foster relationships than traditional media, because social media are interactive in nature and therefore can function more easily as a two-way symmetrical communication tool (Lessig, 2004; Benkler, 2007). As before mentioned, dialogical messages and community building require interaction. It
is therefore hypothesised that:
H3. Dialogical and community messages via social media have a more positive effect on
relational outcomes than via traditional media.
WOM can be facilitated by social media, because people can easily use their social network to spread corporate messages in any form (text,pictures, videos, etc.). There are many things that influence people’s intention to engage in eWOM, such as venting, helping other customers (altruism), exerting power over the organization, social benefits, economic incentives, helping the company or advise-seeking (Hennig-Thurau, Gwinner, Walsh & Gremler, 2004). If organizations want to elicit positive eWOM for their company, they should focus on the willingness of consumers to help the company. When people are more willing to help the organization, they might be more likely to spread corporate messages to others. Strong consumer-organization relationships could influence the aspired willingness of people to help an organization (McAlexander, Schouten, & Koenig, 2002; Yeh and Choi, 2011). Organizations can build these relationships by creating communities where people are
engaged in social interactions (Muniz & O’Guinn, 2001, Carlson, Suter, & Brown, 2008). The social interaction within communities can create a psychological bond or commitment to the organization (Kim, Sung, & Kang, 2014). This sense of organizational commitment tends to reinforce people’s ‘community behaviour’, e.g. eWOM intentions (McAlexander et al., 2002; Muniz & O’Guinn, 2001). This suggests a relation between relational outcomes and the
intention of people to engage in word of mouth. It is therefore hypothesised that:
H4. Relational outcomes are positively correlated with public’s intention to engage in word of
mouth, regardless of the communication channel used to distribute pr messages.
Moreover, relational messages might have a direct effect on public’s intention to engage in word of mouth as well. Social media require one click on the share button for people to engage in eWOM, which means it takes less effort to spread a message through social media than face-to-face. Moreover, dialogical messages from organization ask publics for a
response. Responding to a message on social media takes less effort than responding to a message in traditional media. Thus, it is therefore hypothesised that:
H5. Relational messages on social media show a higher intention of publics to engage in
word of mouth than relational messages in traditional media.
Relational outcomes in more detail
In order to establish the effectiveness of relational and informational efforts of PRPs, there is a need for accountability. Whereas the output of PR messages are mostly tangible and therefore reasonably easy to measure, the relational PR output causes difficulties for
accountability.
There are many different measures that evaluate the effectiveness and value of PR, but these mainly measure processes and outcomes (Hon & Grunig, 1999). As said before, one of the core functions of PR is to establish and maintain relationships with their publics. Many preliminary measures have been developed to evaluate the relationship efforts between organizations and their publics, but there is little agreement on the definitions of these relationships and how they are supposed to be measured (Broom, Casey & Ritchey, 1997).
Soon after, Hon and Grunig (1999) developed their PR Relationship Measurement Scale which can be used to establish the success of an organization’s long-term
relationship-building efforts with their publics. According to this measurement, there are four indicators to evaluate relationships between the organization and their public: control mutuality, trust, satisfaction and commitment.
Method
This study tries to investigate the extent to which conveying a corporate message through social media is more successful in establishing relationships with publics and
generating (electronic) word of mouth than traditional media. In order to answer this question, an experimental survey with a 2 (communication channel: social media, traditional media) by 3 (message type: informational, dialogical, community) between-subject design was carried out.
Participants
The respondents for this experimental survey were gathered from a convenient sample through Facebook and e-mail, by sending an invitation to participate with the internet link to the survey. Initially 260 people started the survey, after all incomplete entries were deleted 197 respondents remained. Of all the respondents (N = 197), 41.1% were male (n=81) and 58.9% female (n=116). The age ranged from 16 to 76 years old, with an average of 29 (SD= 11.37). 85.3% of the respondents lived in The Netherlands (n=168) at the time of their participation. Most respondents were either students (n= 48.2%) or employed for wages (n= 37.5%). The average level of education was between associates and bachelors degree (SD= 1.49). The average level of income of the participants was between €2,000 and €2,500 (SD= 2.54). All the respondents (N= 197) were divided between Communication channel and Text
type. Of the respondents exposed to a Twitter message (n= 98), 31 people received the
informational text, 35 people received the dialogical text and 32 people received the community text. Of all the respondents exposed to the news article conditions (n= 99), 32 received the informational text, 31 received the dialogical text and 36 people received the community text.
Materials
For this study an online experimental survey on Qualtrics was distributed. Participants were randomly assigned to one of the six conditions, which included two different kinds of communication channels, both divided into three message types.
As already mentioned, the first independent variable of this study was the communication channel used to spread a corporate message. The two communication channels in this study were traditional media and social media. Participants assigned to the traditional media conditions were exposed to a scenario which included a short introduction about a fictional company followed by an article from a newspaper. It was not explicitly mentioned if the news article was online or tangible. This was done in order to avoid excluding certain groups from this study that do not have a newspaper subscription. The participants that were assigned to the social media conditions, were given a similar
introduction text about the fictional company, followed by an image of a Twitter message. Social media was defined in this study as Twitter messages because Tweets can be read by everyone, in contrast to other social media such as Facebook. Media such as Facebook require a certain social connection between the organization and the public for a message to spread. Therefore, it was assumed that people can more easily imagine themselves reading a Twitter message from a company without any type of previous social connection.
was divided into three subgroups as defined by Lovejoy and Saxton (2012). The first type is informational messages. These messages only include information from the organization about its activities and events, facts, reports or any other kind of one-way communication from the organization to its publics. These messages may include links to websites where information can be found. The second and third message types are categorized as relational PR. These include the dialogue type of messages, which is defined as responses from the organization to the public’s messages and messages from the organization that ask for a response from the public. Lastly, ‘giving recognition and thanks’ and ‘acknowledgement of current and local events’ can be considered as community building messages (Lovejoy & Saxton, 2012, pp. 343-344). These messages do not directly ask for a response from the public but the organization acknowledges that they are part of the community by thanking publics and for example celebrating important holidays with publics (Lovejoy & Saxton, 2012). For the experiment a fictional company was created called FestEvents. The PR messages distributed were said to have come from this fictional company. The complete scenario texts can be found in Appendix B.
The dependent variables included relational outcomes and people’s intention to engage in
word of mouth. Many different scales to measure relational outcomes were developed over the
years. These different measurements were combined in the PR Relationship Measurement
Scale by Hon and Grunig (1999), which can be found in Appendix A. The scale include four
main indicators to measure the relational outcome of PR efforts. These indicators are control mutuality, trust, satisfaction and commitment and were all measure on 7-point Likert scales ranging from ‘strongly disagree’ to ‘strongly agree’. The indicators defined by Hon and Grunig (1999, p.3) can be described as follows:
power between one another. This variable consisted of five items (α = .75).
Trust. The willingness and confidence of someone to be vulnerable to the actions of
the other. There are three dimensions: integrity, dependability and competence. This variable was measured with six items (α = .89 ).
Satisfaction. The degree to which both parties feel favourably toward each other
because it lived up to their positive expectations. This variable consisted of five items (α = .92).
Commitment. The degree to which someone believes the relationship is worth
spending time and energy on. There are two dimensions: continuance and affective. This variable was measured with five items (α = .87).
These four main indicator were combined into one variable, which was labelled as
relational outcomes (α = .94).
WOM. The intention of people to engage in word of mouth about the organization
was measured with 4 items (α = .78), defined by Hunt, Keaveney and Lee (1995). The questions were answered on a 7-point Likert scale ranging from ‘strongly disagree’ to ‘strongly agree’. The questions were slightly altered to fit the fictional company that was created for the survey. Scale items can be found in Appendix A. The variables and before mentioned hypotheses fit into the conceptual model of this study, shown in Figure 1.
Several control variables were added to the survey. Apart from general demographic questions such as gender, age, level of education, income and occupation, people were also asked where they currently lived. This was later coded as either in the Netherlands or ‘other’. Two open manipulation questions were added which tested whether participants remembered where they had read the message and what it said. Later these answers were coded as either a right or wrong answer. Two wrong answers were not used in further analyses. To control for their using behavior of Twitter or news articles they were asked how frequent they read Tweets or articles, which was combined into one variable labeled as Reading frequency ranging from ‘never’ to ‘daily’ on a 7-point scale. Moreover, participants in the Twitter condition were asked whether they had a Twitter account. Lastly, they were asked to what extent they liked to attend summer events, which was answered on a 7-point scale ranging from ‘extremely dislike’ to ‘extremely like’.
Procedure
Participants were invited via Facebook and e-mail to participate in the online
experimental survey. For conducting the experiment, ASCoR’s ethical standards of informed consent were followed. Participants were able to decide to take the entire survey in Dutch or English. After answering several demographic questions they were randomly assigned to one if the six conditions. For each condition, the participants were exposed to a scenario.
Participants were instructed to read this text carefully before proceeding to the questions. The scenario informed the participant that a Dutch events company called FestEvents was
planning to branch out and that he/she was part of their new target group. The scenario also showed a corporate message. The participants were told they had found the corporate message from FestEvents on Twitter, or about FestEvents in a news article. For the Twitter message an
image of a regular Twitter screen was used. The image was slightly edited so it highlighted an informational, dialogical or community building message from FestEvents. The newspaper article was a passage from a news article, including a corporate message from FestEvents. The content of the corporate messages corresponded to the message types on Twitter. After the scenario participants were asked to rate statements with the provided scenario in mind on 7-point Likert scales. The questions measured the relational outcomes and WOM intention of the participants. Following these scales, participants were asked to answer the manipulation check and several control variable questions. After data collection, some variables were reversed and text entries for control variables were recoded as before mentioned. The scale reliability of the four relational indicators were measured separately and together. All reliabilities were high, thus one variable was created for relational outcomes combining all four indicators.
For the analysis, several correlation tests were carried out first to determine whether the assumed relations between variables were in line with the conceptual model in Figure 1. With select cases, a series of independent samples t-test were carried out to measure the differences in relational outcomes and intention to engage in WOM for the Tweet and the news article per message type (informational, dialogical and community). Two one-way ANOVAs were carried out to measure the differences in relational outcomes and intention to engage in WOM between message type, without distinguishing between communication channels. A univeriate analysis of variance was conducted to determine whether the relational outcomes for each message type were related to intention to engage in WOM. It also
established whether there were differences between the traditional and the social media condition.
Results
Manipulation check
In order to investigate whether the manipulation was successful, the answers of the manipulation check questions were analyzed. Exact frequencies per message type can be found in the Table 1. Manipulation question 1 asked the participant whether they could remember where they had read the message, as described in the scenario. Question 2 asked the participant what the message in the scenario said.
Table 1. Percentages of participant answering the manipulation questions incorrect
Newspaper (n=99) Twitter (n=99)
Manipulation 1 Manipulation 2 Manipulation 1 Manipulation 2 Informational message 34.4% 12.5% 6.6% 22.6% Dialogical message 22.6% 22.6% 11.4% 14.3% Community message 11.1% 33.3% 6.3% 21.9%
A frequency analysis showed that 77,8% of the participants who received the
corporate message as a news article (n = 99) answered correctly when asked where they had read the message and 76,7% correctly answered what the message said.
91,8% Of the participants exposed to a Twitter message (n = 98) answered correctly where they read the message. This high rate, compared to the news article condition, could be explained by the fact that all Twitter messages were shown in the survey as a Twitter image, whereas the news article passages showed only text. Of all the participants exposed to a Twitter message, 80,6% answered correctly what the message had said.
Participants were only excluded from any further analysis when they answered both questions incorrect. The analysis showed that no participants answered both manipulation
check questions incorrect. Thus, no participants were excluded from further analysis.
Randomization check
As a randomization check two one-way ANOVAs and several Chi-square tests were conducted to measure whether the control variables (demographics) were equally distributed over the independent variables Communication channel and Message type (conditions). The one-way ANOVA for the continuous control variable Age showed no significant differences in distribution for Communication channel (F(1,195) = 0.24, p = 0.63) and Message type
(F(2,194) = 0.45, p = 0.64).
A Pearson’s Chi-square test was conducted to measure the randomization of the categorical variables among the six conditions. The tests showed no significant differences for
Communication channel: Gender: χ 2(1, N= 197) = 0.91, p = 0.34; Level of education: χ 2(6,
N= 197) = 6.15, p = 0.41; Occupational status: χ 2(4, N= 197) = 1.36, p = 0.85; Home
country: χ 2(1, N= 197) = 0.05, p = 0.82; Level of income: χ 2(7, N= 197) = 11.39, p = 0.12. Moreover, no significant differences were found for the distribution between Message types:
Gender: χ 2(2, N= 197) = 0.43, p = 0.81; Level of education: χ 2(12, N= 197) = 19.49, p = 0.08; Occupational status: χ 2(8, N= 197) = 7.58, p = 0.48; Home country: χ 2(2, N= 197) = 0.40, p = 0.82; Level of income: χ 2(14, N= 197) = 14.03, p = 0.48.
Overall, no significant differences were found between participant’s demographic information and the conditions. Therefore, it was argued that the randomization of the sample was successful.
Covariates check
A bivariate correlation (Pearson’s r) test was conducted to see which continuous control variables had a significant relationship with the dependent variables relational
outcomes or intention to engage in WOM. There was no significant correlation found between relational outcomes and Age: r(197) = -0.14, p = 0.05; attitude towards summer events: r(197) = 0.13, p = 0.06; reading frequency: r(197) = 0.01, p = 0.91. Furthermore, no
significant relationships were found between intention to engage in WOM and age: r(197) = -0.02, p = 0.74; attitude towards summer events: r(197) = 0.14, p = 0.05; reading frequency:
r(197) = -0.01, p = 0.90.
A Spearman’s rho correlation test was conducted to measure whether the ordinal control variables correlated with the dependent variables relational outcomes and intention to
engage in WOM. No significant correlation was found between relational outcomes and level of education (ρ(197) = 0.05, p = 0.51) or level of income (ρ(197) = -0.14, p = 0.05). Moreover,
no significant correlation was found between intention to engage in WOM and level of
education (ρ(197) = -0.03, p = 0.66) or level of income (ρ(197) = -0.01, p = 0.86).
A Chi-square test was conducted to measure the correlation between the nominal categorical variables and the independent variables. No significant relation was found for
relational outcomes and gender: χ 2(61, N= 197) = 73.00, p = 0.14; occupational status: χ
2
(244, N= 197) = 265.73, p = 0.16; have a Twitter account: χ 2(52, N= 197) = 52.80, p = 0.44;
home country: χ 2(61, N= 197) = 51.32, p = 0.81. Furthermore, no significant relation was found for the independent variable intention to engage in WOM and gender: χ 2(23, N= 197) = 23.80, p = 0.42; occupational status: χ 2(92, N= 197) = 61.68, p = 0.99 ; have a Twitter
account: χ 2
(20, N= 197) = 29.46, p = 0.08; home country: χ 2(23, N= 197) = 22.11, p = 0.51. In sum, no control variables showed a correlation with the independent variables. Thus, further analyses were not controlled for covariance.
Testing the hypotheses
hypotheses in this study. The model can be found in the method section, Figure 1. The
statistical analyses are reported per hypothesized relationships, followed by a short conclusion of the outcomes.
Relationship between message type and relational outcomes.
In order to measure whether social media or traditional media is more successful in establishing relational outcomes, a Spearman’s rho correlation test was conducted to test the relationship between relational outcomes and message type for both Twitter and the news article. The test showed a significant relationship between relational outcomes and Twitter (ρ(98) = 0.34, p = 0.001), and the news article (ρ(99) = 0.29, p = 0.004). Several independent samples t-tests were conducted to compare the relational outcomes per message type between Twitter and the news article.
An independent samples t-test for the informational message type, showed no significant difference (t(61)= .24, p= .81) in relational outcomes between Twitter (M= 3.87,
SD= .82) and the news article (M= 3.92, SD= .97). Hypothesis 1, assuming that the news
article would show a significantly higher relational outcome than the Tweet for the informational message type, was therefore rejected.
An independent samples t-test for the dialogical message type, showed no significant difference (t(64)= .02, p= .90) in relational outcomes between Twitter (M= 4.31, SD= .84) and the news article (M= 4.33, SD= .56). An independent samples t-test for the community message type, showed no significant difference (t(66)= .44, p= .66) in relational outcomes between Twitter (M= 4.59, SD= .91) and the news article (M= 4.50, SD= .89). Hypothesis 3, assuming that the Tweet would show a significantly higher relational outcome than the news article for the dialogical and community message, was therefore rejected.
depth, a one-way ANOVA was conducted to measure the difference between text types without distinguishing between communication channels. The test showed a significant difference in relational outcomes per message type (F(2,194)= 9.97, p < .001). A Bonferroni post-hoc test showed that the relational outcome was significantly lower for informational messages (M= 3.89, SD= .89) than for the dialogical (M= 4.32, SD= .72) and community messages (M= 4.54, SD= .90). However, no significant differences were found in relational
outcomes between dialogical and community message.
Relationship between message type and WOM.
Before testing whether Twitter or news articles are more successful in sparking people’s intention to engage in WOM, a Spearman’s rho correlation test was conducted to measure whether there was a relationship between the Twitter message or news article and people’s intention to engage in WOM. The test showed a significant relationship between
WOM and Twitter (ρ(98) = .27, p = 0.008), and news articles (ρ(99) = .27, p = 0.006). Several
independent samples t-tests were conducted to compare the intention to engage in WOM per message type between Twitter and the news article.
An independent samples t-test for the informational message type, showed no significant difference (t(61)= .68, p= .50) in intention to engage in WOM between Twitter (M= 3.98, SD= 1.17) and the news article (M= 3.77, SD= 1.21). Hypothesis 2, assuming that the news article would show a significantly higher intention to engage in WOM than the Tweet, was therefore rejected.
An independent samples t-test for the dialogical message type, showed no significant difference (t(1,64)= .71, p= .48) in intention to engage in WOM between Twitter (M= 4.18,
SD= 1.20) and the news article (M= 4.37, SD= .96). An independent samples t-test for the
engage in WOM between Twitter (M= 4.73, SD= 1.04) and the news article (M= 4.56, SD=
1.18). Hypothesis 5, assuming that the Tweet would show a significantly higher intention to engage in WOM than the news article for the dialogical and community message, was therefore rejected.
To investigate the relationship between the text types and the people’s intention to engage in WOM in more depth, a one-way ANOVA was conducted to measure the difference between text types without distinguishing between communication channels. The test showed a significant difference between groups in people’s intention to engage in WOM (F(2,184)= 7.64, p = 0.001). A Bonferroni post-hoc test showed that people’s intention to engage in WOM was significantly lower after reading an informational messages (M= 3.87, SD= 1.18) than after begin exposed to the community message (M= 4.64, SD= 1.11). No significant differences were found in people’s intention to engage in WOM between the dialogical message (M= 4.27, SD= 1.09) and the informational and community message.
Relationship between relational outcomes and WOM.
To measure whether there was a relationship between relational outcomes and people’s intention to engage in WOM, a Pearson’s correlation test was conducted. The test showed a significantly strong positive correlation between the two dependent variables (r(197) = 0.68, p < .001). In order to investigate this interaction effect in more depth, several univeriate analyses of variance were conducted per message type, to establish whether the effect differed between Tweets and news articles. Moreover, it showed which specific message type showed an interaction effect between relational outcomes and intention to
engage in WOM. Select cases was used in order to investigate the effects per message type.
A univariate analysis of variance for the informational message was conducted. The analysis showed a significant relationship between relational outcomes and intention to
engage in WOM (F(32)= 3.57, p= .002, ղ2= .86). However, no significant difference for the interaction effect was found between Twitter and news articles (F(10)= 1.17, p= .37, ղ2= .38).
A univariate analysis of variance for the dialogical message showed no significant relationship between relational outcomes and intention to engage in WOM (F(30)= 1.90, p= .08, ղ2= .77). Thus, no significant differences were found for the interaction effect between the Tweet and news article (F(17)= .85, p= .63, ղ2= .46).
Lastly, a univariate analysis of variance for the community message was conducted. The test showed no significant relationship between relational outcomes and intention to
engage in WOM (F(40)= 1.93, p= .07, ղ2= .82), and therefore no differences were found between Twitter and the news article (F(9)= .65, p= .74, ղ2= .26).
In sum, the strong positive relationship between relational outcomes and intention to
engage in WOM only existed for the informational message type. There was no difference in
the interaction effect between Twitter and the news article. Thus, it cannot be concluded which communication channel was more effective in motivating people to engage in WOM through establishing relational outcomes. However, hypothesis 4, assuming that relational outcomes would be related to public’s intention to engage in WOM regardless of the message type, was accepted.
Conclusion
This study aimed to investigate to effectiveness of Twitter and traditional media, and by comparison establish which medium would be a more useful tool for PRPs. In order to answer this question, the relationship between the dependent and independent variables in the
conceptual model in Figure 1 had to be investigated. It showed that the Twitter messages and news articles were related to relational outcomes and intention to engage in WOM. Moreover, the analysis showed that intention to engage in WOM was related to relational outcomes,
when publics read the informational message. This means the informational message that participants read from the company, effected the relation outcome which in turn also affected their intention to engage in WOM. Therefore, hypothesis 4 was accepted. This is in line with literature that argued that a consumer-organization relationship can influence public’s
willingness to help (e.g. McAlexander, Schouten, & Koenig, 2002; Yeh and Choi, 2011), which includes intention to engage in WOM (Muniz & O’Guinn, 2001). However, this relationship was only measured for the informational message and no difference were found for this relationship between Twitter and the news article. Relating this result back to the main research question, it can be concluded that social media and traditional media are equally successful in establish intention to engage in WOM via relational outcomes.
From further analysis of the conceptual model, it can be concluded that hypotheses 1, 2,3 and 5 were rejected. The hypotheses assumed that either Twitter or news articles would be more effective in establishing relational outcomes and directly inspire people to engage in WOM, by sending out either informational, dialogical or community building messages. However, statistical analyses showed no significant differences in effectiveness between social media and traditional media for all three message types.
The analyses did show that both Twitter and the news article had a weak positive relationship with relational outcomes. Twitter seemed to have a stronger relationship, however no significant differences were found in relational outcomes between
communication channels for the informational, dialogical and community message. The same results were found for the relationship between the communication channels, messages types and people’s intention to engage in WOM. The statistical analyses showed a weak positive relationship between the messages from both communication channels and the intention to engage in WOM. The relationship strength was the same for Twitter and the news article, therefore no significant differences in effectiveness were found between the communication
channels. An analysis per message type also showed no significant difference in effectiveness between Twitter and the news article.
These results imply that Twitter and news articles are equally successful in establishing Relational outcomes and WOM. This would mean that PRPs can use social media and/or traditional media to have the same level of success in establishing relational outcomes and WOM. When disregarding the difference in communication channel and focusing only on the differences between message types, it shows that the community message is more successful in establishing both relational outcomes and WOM than
informational messages. Dialogical messages have a similar effect as community messages on relational outcomes and the dialogical message shows no significantly different outcomes in people’s intention to engage in WOM than the informational or community message. In sum, this means that the most successful way for PRPs to establish relational outcomes is to send publics dialogical and community messages, either on Twitter or via newspapers. The best way to heighten people’s intention to engage in WOM, is to send publics a community message.
It is not surprising that dialogical and community messages are more successful in establishing relational outcomes and intention to engage in WOM, because interaction and a sense of belonging and brand commitment are found to relate to these outcomes in previous literature (Lovejoy & Saxton, 2012). However, the results indicating that there is no
significant difference between Twitter and a traditional news article is surprising. First, the finding that informational messages via traditional media do not lead to higher relational outcomes and intention to engage in WOM is not in line with the literature. External sources were previously found to be perceived as more credible and trustworthy (Groeger & buttle, 2014), which would therefore imply that informing publics via traditional media would lead to higher relational outcomes. Moreover, the credibility of an external source was found to
lead to higher intention to engage in WOM (Brown, Broderick, & Lee, 2007), which the results of this study did not show. Secondly, the previously assumed interactive two-way symmetrical advantages of social media (Lessig, 2004; Benkler, 2007) for dialogical and community messages have not been established, because the communication channels proved to be equally effective in establishing relational outcomes and intention to engage in WOM. Social media have been praised for their interactive advantages by many scholars until a discussion started about to what extent this assumption is evidence based.
As mentioned before, previous studies have critically assessed the effects of social media and so far have not found any ground for assuming its usefulness over traditional media (Taylor & Kent, 2010; Wright & Hinston, 2008; Trammell, 2006; Sweetser & Metzgar,
2007). The findings of this study therefore ad to the discussion of the actual effectiveness of social media, by concluding that both tradition as well as social media are equally effective in establishing relational outcomes and an intention to engage in WOM.
Discussion
This study had several limitations that have to be taken into account while interpreting the results. First, certain decisions were made for the survey that could have had an influence. For the manipulation check, participants were asked what the message said and where they had read the message. Participants were able to use the ‘back’ button, which meant they could look up the answer. This button was added because some participants accidentally skipped the manipulation text at the beginning of the survey. Moreover, participants in the social media condition received an image of the Twitter message. The news article condition only showed a passage from a larger text. The visual image of the Twitter message might have helped people remember better where they had read the message. Also, participants were able to choose whether they wanted to fill out the entire survey in English or Dutch. Even though the
messages were an exact translation, people might have had a more favorable attitude towards corporate messages in English or Dutch.
Furthermore, the intention to engage in WOM was measured with the same items for both conditions. This variable was measured with questions such as ‘I would tell my friend about the company’. These questions were kept the same for the traditional media condition as well as for the social media condition in order to be able to compare the results afterwards. The limitation of doing so, is that these scales might have only measured people’s intention to spread the message face to face, which is good for the traditional media condition. However, people in the social media condition might have shown higher intention to engage in eWOM, if they had been asked whether they would share and Retweet the message.
Lastly, the variable measuring the Relational outcome was limited by the design of this study. The PR Relationship Measurement Scale (Hon & Grunig, 1999) was designed to measure long term relational outcomes. Due to time limitations, this study was only able to measure people’s attitude at one point in time. In order to establish relational outcomes from an informational, dialogical or community type of message, it might take more time and multiple exposure to messages in order to see actual results. Therefore, future research can focus on the long-term relational outcomes by exposing participants to more messages over a longer period of time. By comparing these results, it can be investigated whether the different message types can positively or negatively change participant’s Relational outcome.
Furthermore, the results from the manipulation check in Table 1 show that participants who received the dialogical and community message via Twitter, remembered better what the message had said than participants who received the news article condition. This first raises the questions whether people have less trouble to find and remember the important news in a social media message than in a news article. Further research could carry out a similar study, focusing on which communication channel is more effective in making people remember
corporate messages. The channels could for example have a different effect on people due to for example the length of messages. In general, social media messages are much shorter than news articles in traditional media. Moreover, the effect of exposure frequency on public’s attitude can be investigated. Since social media do not have gatekeepers, organizations can more frequently expose their publics to messages than via traditional media, which can have a different effect on public’s attitude towards the organization. Secondly, if people more easily remember social media messages, this might affect people’s long term relational outcome. A more practical example: if Twitter messages are more easily remembered, it might be a more effective tool for PRPs than traditional media in establishing organizational commitment and a long-term brand image. Furthermore, research could focus on public’s actual WOM
behavior, instead of their intention. This focus in combination with the scales adjusted to eWOM, might show a more substantial difference in effectiveness between traditional and social media.
Lastly, the informational and relational efforts of PRPs do not only affect external publics, but also influence the employees of an organization. For example, traditional media have gatekeepers and it is therefore more difficult to gain free publicity as an organization. It could be considered as a higher or more important achievement, if the organization’s name appears in traditional media. Thus, when an organization is mentioned in traditional media it can have a more positive effect on employees (e.g. strong feeling of pride, commitment or belonging, etc) than when the organization is mentioned online. The internal influence of PRPs efforts in traditional and social media can also be considered as important and effective, and should therefore be considered in further research.
These suggestions for further research could build on the results of this study, in order to further investigate the differences in effectiveness between traditional and social media as an effective communication tool for PRPs.
References
Benkler, Y. (2007). The wealth of networks. How social production transforms market and freedom. New Haven, CT: Yale University Press.
Berger, B. K. (2005). Power over, power with, and power to relations: Critical reflections on public relations, the dominant coalition, and activism. Journal of Public Relations
Research, 17(1), 5‐ 28.
Birnbaum, M. H., & Stegner, S. E. (1979). Source credibility in social judgment: Bias, expertise, and the judge’s point of view. Journal of Personality and Social
Psychology, 37(1), 48–74.
Broom, G. M., Casey, S., & Ritchey, J. (1997). Toward a concept and theory of organization- public relationships. Journal of Public Relations Research, 9(2), 83–98.
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), 2–19.
Brown, J., & Reingen, P. (1987). Social ties and word-of-mouth referral behavior. Journal of
Consumer Research, 14(3), 350 - 362.
Carlson, B. D., Suter, T. A., & Brown, T. J. (2008). Social versus psychological brand community: The role of psychological sense of brand community. Journal of
Business Research, 61(4), 284–291
Chiu, H.-C., Hsieh, Y.-C., Kao, Y.-H., & Lee, M. (2007). The determinants of e-mail receivers’ disseminating behaviors on the Internet. Journal of Advertising
Research, 47(4), 524–534.
Chung, C. M. Y, & Tsai, Q. (2009). The effects of regulatory focus and tie strength on word- of-mouth behavior. Asia Pacific Journal of Marketing and Logistics, 21(3), 329 – 341. Dellarocas, C. (2003). The digitization of word of mouth: promise and challenges of online
feedback mechanisms. Management Science, 49(10), 1407-1424.
D’Urso, S. C., & Pierce, K. M. (2009). Connected to the organization: A survey of
communication technologies in the modern organizational landscape. Communication
Research Reports, 26(1), 75–81.
Frenzen, J., & Davis, H. L. (1990). Purchasing behavior in embedded markets. Journal of
Consumer Research, 17(1), 1-12.
Frenzen, J., & Nakamoto, K. (1993). Structure, cooperation and the flow of market information. Journal of Consumer Research, 20(3), 360-375.
Goldsmith, R. E., & Horowitz, D. (2006). Measuring motivations for online opinion seeking. Journal of Interactive Advertising, 6(2), 1-16.
Groeger, L., & Buttle, F. (2014). Word-of-mouth marketing: Towards an improved
understanding of multi-generational campaign reach. European Journal of Marketing,
48(7/8), 1186-1208.
Grunig, J. E., & Grunig, L. A. (1992). Models of public relations and communication. In J. E. Grunig (Ed.), Excellence In public relations and communication management (pp. 285- 325). Hillsdale, NJ: LEA.
Harlow, R. F. (1976). Building a public relations definition. Public Relations Review, 2(4), 34-42.
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.
Hon, L. C., & Grunig, J. (1999). Guidelines for Measuring Relationships in Public Relations. Gainesville, FL: The Institute for Public Relations. Retrieved February 24, 2015, from http://www.aco.nato.int/resources/9/Conference%202011/Guidelines_Measuring_ Relationships[1].pdf
Hornik, J., Shaanan Satchi, R., Cesareo, L., & Pastore, A. (2015). Information dissemination via electronic word-of-mouth: Good news travels fast, bad news travels
faster! Computers in Human Behavior, 45, 273-280.
Hunt, K. A., Keaveney, S. M., & Lee, M. (1995). Involvement, attributions, and consumer responses to rebates. Journal of Business and Psychology, 9(3), 273-297.
Johnson, M. A. (1997). Public relations and technology: Practitioner perspectives. Journal of
Public Relations Research, 9(3), 213-236.
Kent, M. L. (2013). Using social media dialogically: Public relations role in reviving democracy. Public Relations Review, 39(4), 337–345.
Kent, M. L., & Taylor, M. (1998). Building dialogic relationships through the World Wide Web. Public Relations Review, 24(3), 321–334.
Kim, E., Sung, Y., & Kang, H. (2014). Brand followers’ retweeting behavior on Twitter: How brand relationships influence brand electronic word-of-mouth. Computers in Human
Behavior, 37, 18-15, http://dx.doi.org/10.1016/j.chb.2014.04.020
Lessig, L. (2004). Free culture: How big media uses technology and the law to lock down culture and control creativity. New York, NY: Penguin Press.
Linke, A., & Zerfass, A. (2013). Social media governance: regulatory frameworks for successful online communications. Journal of Communication Management, 17(3), 270-286.
Lovejoy, K., Waters, R. D., & Saxton, G.D. (2012). Engaging stakeholders through Twitter: How nonprofit organizations are getting more out of 140 characters or less. Public
Relations Review 38(2), 313-331, DOI: 10.1016/j.pubrev.2012.01.005
Luoma-aho, V., & Vos, M. (2010). Towards a more dynamic stakeholder model:
acknowledging multiple issue arenas. Corporate Communications: an International
McAlexander, J. H., Schouten, J. W., & Koenig, H. (2002). Building brand community. Journal of Marketing, 66(1), 38–54.
Metzger, M. J. (2007). Making sense of credibility on the web: Models for evaluating online information and recommendations for future research. Journal of the American Society
for Information Science and Technology, 58(13), 2078-2091. DOI: 10.1002/asi.20672
Meisenbach, R. J. (2006). Habermas's discourse ethics and principle of universalization as moral framework for organizational communication. Management Communication
Quarterly, 20(1), 39-62.
Muniz, A. M., Jr., & O’Guinn, T. C. (2001). Brand community. Journal of Consumer
Research, 27, 412–432.
Nakra, P. (1991). The changing role of public relations in marketing communications. Public
Relations Quarterly, 36(1), 42.
Phelps, J. E., Lewis, R., Mobilio, L., Perry, D., & Raman, N. (2004). Viral marketing or electronic word-of-mouth advertising: Examining consumer responses and
motivations to pass along email. Journal of Advertising Research, 44(4), 333–348. Steffes, E. M., & Burgee, L. E. (2008). Social ties and online word of mouth. Internet |
Research, 19(1), 42-59.
Sweetser, K. D., & Metzgar, E. (2007). Communicating during crisis: The use of blogs as a relationship management tool. Public Relations Review, 33(3), 340–342,
http://dx.doi.org/10.1016/j.pubrev.2007.05.016
Taylor, M., & Kent, M. L. (2010). Anticipatory socialization in the use of social media in public relations: A content analysis of PRSA’s Public Relations Tactics. Public
Relations Review, 36(3), 207–214.
Theaker, A., & Yaxley, H. (2013). The public relations strategic toolkit: An essential guide to successful public relations practice. New York, NY: Routledge
Trammell, K. D. (2006). Blog offensive: An exploratory analysis of attacks published on campaign blog posts from a political public relations perspective. Public Relations
Review, 32(4), 402–406.
Valentini, C. (2015). Is using social media “good” for the public relations profession? A critical reflection. Public Relations Review. Retrieved February 24, 2014, from http://dx.doi.org/10.1016/j.pubrev.2014.11.009
Van Ruler, B., & Verčič, D. (2005). Reflective communication management: Future ways for public relations research. Communication Yearbook, 29(1), 239‐273.
Wright, D. K., & Hinson, M. D. (2008). How blogs and social media are changing public relations and the way it is practiced. Public Relations Journal, 2(2), 1–21.
Yeh, Y.-H., & Choi, S. M. (2011). Mini-lovers, maxi-mouths: An investigation of antecedents to eWOM intention among brand community members. Journal of
Appendix A
Scale items for relational outcomes (Hon & Grunig, 1999) and WOM (Hunt, Keaveney & Lee 1995):
Control Mutuality
1. This organization and people like me are attentive to what each other say. 2. This organization believes the opinions of people like me are legitimate.
3. In dealing with people like me, this organization has a tendency to throw its weight around. (Reversed)
4. This organization really listens to what people like me have to say.
5. The management of this organization gives people like me enough say in the decision-making process.
Trust
1. This organization treats people like me fairly and justly.
2. Whenever this organization makes an important decision, I know it will be concerned about people like me.
3. This organization can be relied on to keep its promises.
4. I believe that this organization takes the opinions of people like me into account when making decisions.
5. I feel very confident about this organization’s skills.
6. This organization has the ability to accomplish what it says it will do. Commitment
1. I feel that this organization is trying to maintain a long-term commitment to people like me. 2. I can see that this organization wants to maintain a relationship with people like me.
3. There is a long-lasting bond between this organization and people like me.
4. Compared to other organizations, I value my relationship with this organization more. 5. I would rather work together with this organization than not.
Satisfaction
1. I am happy with this organization.
2. Both the organization and people like me benefit from the relationship. 3. Most people like me are happy in their interactions with this organization.
4. Generally speaking, I am pleased with the relationship this organization has established with people like me.
5. Most people enjoy dealing with this organization. Intention to engage in word of mouth
1. A situation like the one described in the scenario would encourage me to recommend to others that they go to a FestEvents event.
2. If I had experienced the situation in the scenario, I'd tell my friends about FestEvents. 3. The situation in the scenario would not inspire me to tell anyone about that product. (Reversed)
Appendix B Text of scenarios
General introduction message news article:
An organization called FestEvents, specialized in organizing events in the Netherlands, is planning to branch out. You are part of the new target group which the organization wants to start hosting events for next summer. You come across a news article from a newspaper about FestEvents and read the following message:
General introduction message Twitter:
An organization called FestEvents, specialized in organizing events in the Netherlands, is planning to branch out. You are part of the new target group which the organization wants to start hosting events for this summer. You are searching for #events on Twitter when you come across the following message from FestEvents on your newsfeed:
Informational message
Traditional media:
“ The successful events organization FestEvents has announced they are planning to branch out in the events industry. Festevents will start hosting new events next summer. The
company has organized events for all age groups throughout the Netherlands for several years and is now looking for a new concept. The event agenda for their new branch is not known to the public yet. For more information visit their website www.festevents.nl/news ”
Social media:
Dialogical message
Traditional media:
“ [...] FestEvents is still in the process of setting their events agenda. To make sure that their new events are tailored to their new target group, they would like to receive input from the public. Do you have creative or innovative ideas for concepts or locations? Or would you just like to attend an event in your area sometime? FestEvents kindly requests everyone to join in on the event discussion by sending their ideas or suggestions in an email to:
newidea@festevent.nl. ” Social media:
Community building message
Traditional media:
“ The summer festivities of this weekend, organized by FestEvents, were a good official start of everyone’s summer. FestEvents can look back on yet another successful day. Project manager of FestEvents: “We are very thankful for the great turnout, and we hope everyone enjoyed it as much as we did. Maybe we can celebrate more special days with everyone next year, when we start hosting our new events”. [...] ”
