tweeting the crisis - anton.nl · 2017-07-29 · tweeting the crisis: the role of source and timing...

Tweeting the Crisis The role of source and timing on social media while

using a denial crisis-response strategy.

Master’s Thesis Graduate School of Communication, University of Amsterdam

Corporate Communication

Author: Anton Bekenkamp (10266208) Supervisor: dr. G.L.A. (Toni) van der Meer Date: 30-06-2017

Master’s programme Communication Science

TWEETINGTHECRISIS:THEROLEOFSOURCEANDTIMINGONSOCIALMEDIAWHILEUSINGADENIALCRISISRESPONSESTRATEGY.

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Abstract Social media play an increasingly important role in crisis communication. Past literature has

shown the potential of employees as a source in crisis communication. Moreover, the timing

of disclosing crisis-related information is proven to be an important factor. This study builds

on previous research by investigating the role of source and timing while using a denial crisis-

response strategy. A 2 (source: employee vs. organization) x 2 (timing: stealing thunder vs.

thunder) experiment was conducted amongst 164 participants. The results show that

employees have a more positive effect on reputation compared to the organization. However,

the crisis source did not impact secondary crisis communication. When investigating timing, a

stealing thunder timing strategy did not impact reputation and secondary crisis

communication. Lastly, the effect of source on reputation and secondary crisis

communication is found to be mediated by crisis responsibility. This study provides relevant

insights for communication practitioners and functions as a starting point for future research

in the field of crisis communication.

Keywords: crisis communication, social media, source, timing, employees, stealing thunder


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Introduction

Social media play an increasingly important role in crisis communication. The public relies on

social media to obtain and share crisis-related information (Lachlan, Spence, Lin, Najarian &

Greco, 2016), while organization’s use these new technologies in their strategic

communication processes (Macnamara & Zerfass, 2012).

Crises can occur in any organization and are characterized as unexpected events that

impact the organization and its stakeholders, damaging the firm’s reputation (Coombs, 2006).

Hence, crisis management is critical to limit harm to the organization’s stakeholders or

society in general (Coombs & Holladay, 2002; Coombs, 2007). Crisis communication is, for

example, crucial to ensure public safety and welfare, avoid lawsuits and prevent financial loss

(Coombs & Holladay, 2002). Crisis-response strategies can help companies to minimize

reputational damage.

As outlined by situational crisis communication theory (SCCT), organizations have a

variety of crisis-response strategies to choose from (Coombs, 2006, 2007). When actual or

potential harm is done to the organization’s stakeholders, a victim-centered approach is

recommended, addressing concerns about the stakeholders’ safety (Coombs, 2014). In

practice however, denial is the most used strategy by organizations (Kim, Avery & Lariscy,

2009). Denial can be an effective strategy to minimize reputational damage in situations

where the organization holds no crisis responsibility (Coombs, 2007). Nevertheless,

organizations are frequently involved in the crisis to some extent. If the organization is shown

to have any connection to a crisis event while using a denial strategy, reputational damage is

intensified (Coombs, 2014).

Although it may be counterintuitive for practitioners to admit the organization’s

involvement or to disclose negative crisis-related information, an aggressive communication

approach is desirable over a passive approach (Moran & Gregory, 2014; Coombs, 2014). The


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timing of the crisis communication may be a crucial factor in this approach, to endeavor the

desired effects of the crisis response strategy.

Past literature has addressed the concept of stealing thunder as a beneficial timing

strategy in crisis communication (e.g. Arpan & Pompper, 2003; Coombs, 2015).

Organizations can use this strategy with the objective to ‘break the news’ about a crisis event

before other parties do, resulting in less reputational damage (Arpan & Roskok-Ewoldsen,

2005; Claeys & Cauberghe, 2012). The organization’s position may be weakened if third

parties, such as the news media, initially disclose the crisis, allowing their frame to become

dominant. Yet, research towards the effects of timing while using a denial strategy is largely

absent. Therefore, the current research builds on the previous findings by examining the

effects of timing when the organization denies any involvement in the crisis.

Moreover, the recent body of literature has addressed the role of social media in crisis

communication in more depth (e.g. Procopio & Procopio, 2007; Schultz, Utz & Göritz, 2011;

Lin, Spence, Sellnow & Lachlan, 2016). Social media has become an important vessel in

crisis communication for disseminating information from the organization to the affected

publics (Freberg, 2012). In line, other research has proven that crisis communication through

social networks result in a higher reputation and less secondary crisis communication

compared to online newspapers (Utz, Schultz & Glocka, 2013).

The advent of social media allows many actors other than the organization to actively

participate in the crisis conversation by sharing ‘opinions, insights, experiences, and

perspectives with others’ (Marken, 2007). Recent studies highlighted the importance of

employees as third-party senders of crisis communication (Van Zoonen, van der Meer &

Verhoeven, 2014; Van Zoonen & van der Meer, 2015), functioning as valuable brand

ambassadors of the organization (Cravens & Oliver, 2006; Dreher, 2014). Consequently,

employees could be considered as valuable assets in crisis communication as they can


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influence other stakeholders. Past crisis communication research (i.e. Van Zoonen & van der

Meer, 2015) concerning different sources on social media has not addressed the role of

timing. Also, little is known about the potential of employees in crisis communication while

using a denial strategy.

This research will contribute to established and recent crisis communication theories

focusing on social media. Further this study wants to contribute to SCCT (Coombs, 2006) by

further developing the role of denial crisis-response strategies when the organization’s

involvement in a crisis is still unknown or debatable. The results may provide practitioners

with relevant implications on how to prevent reputational damage when a crisis hits an

organization. The following research question is formulated: In times of crisis, can source and

timing help the organization to minimize reputational damage when using a denial crisis-

response strategy on social media?

Theoretical Framework

Impact of Crises on Organization’s

Organizational crises are characterized as unexpected and harmful events affecting the

organization on an operational or reputational level (Coombs & Holladay, 2002; Coombs,

2006). Events such as industrial and natural disasters can disrupt the daily operation of an

organization, and form a threat to public safety or the well-being of stakeholders (Sohn &

Lariscy, 2013). On the other hand, causalities such as mismanagement, human errors or

technological failures damage the firm’s reputation. Crises cause stakeholders to re-evaluate

their impressions about an organization and frequently result in a financial loss

(Zyglidopoulos & Phillips, 1999). Whenever a crisis hits an organization, the primary goal is

to protect the organization and its stakeholders from threats inflicted by the crisis (Coombs,

2007). The organization’s response can limit or repair reputational damage done by a crisis

(Coombs, 2002, 2006). Hence, selecting the appropriate response strategy can help managers


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to take control of the crisis and minimize harm to the organization (Coombs, 2002). In past

literature, scholars have focused on several key variables potentially affected by

organizational crises.

First, as mentioned before, crises impact reputation as one of the main assets for

organizations. Organizational reputation can be defined as the “stakeholders perceptions

about an organization's ability to create value relative to competitors” (Rindova, Williamson,

Petkova & Sever, 2005). Reputation is linked with perceived value, customer satisfaction and

loyalty (Booker & Serenko, 2007). Moreover, organizational reputation is developed through

interactions between the public and the organization or its employees (Van Zoonen & van der

Meer, 2015). Hence, understanding how reputation is affected by crisis communication is

essential for effective crisis management.

Secondly, several studies argue that secondary crisis communication affects how

stakeholders evaluate the organization in post-crisis communication. Schultz, Utz and Göritz

(2011) define secondary crisis communication as the “intentions to tell friends about the

crisis, to share the received information with others and to leave comments”. Secondary crisis

communication is comparable with word-of-mouth and can be either beneficial for the

organization (positive word-of-mouth) or cause potential damage (negative word-of-mouth)

(Coombs & Holladay, 2008; Laczniak, DeCarlo & Ramaswami, 2001). Minimizing negative

secondary crisis communication could therefore be an effective strategy to protect the

organization from reputational harm. Firms can also try to control secondary crisis

communication, for example by encouraging their audiences to spread official press releases

aimed at rebuilding the organization’s reputation (Lin, Spence, Sellnow & Lachlan, 2016).

Moreover, social media enable stakeholders to share crisis related information with ease,

stimulating secondary crisis communication. Hence, managing secondary crisis

communication has become even more essential with the advent of social networks.


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Situational Crisis Communication Theory (SCCT)

Communication in times of crisis can manage the stakeholder’s expectations and provide

crisis managers with options to limit reputational damage, negative secondary crisis

communication and improve crisis response acceptance. SCCT grants a framework to

minimize reputational harm in post-crisis communication by proposing several crisis-response

strategies that can be used to achieve this goal (Coombs, 2007). According to Coombs (1995),

crisis response strategies are “what an organization says and does after a crisis hits”. Coombs

and Holladay (2002) identify three crisis clusters, defining the crisis responsibility of the firm.

The degree of crisis responsibility affects the reputational threat, along with crisis history and

prior relationship reputation (Coombs, 2007). In the victim cluster, the organization is a

victim of the crisis event and holds no responsibility. In the accidental cluster, the crisis was

caused by the organization unintentionally. In turn, the intentional cluster reflects a situation

where the organization has a high responsibility for the crisis event.

Moreover, SCCT defines three groups of crisis-response strategies. Denial strategies

focus on rejecting any connection between the organization and crisis event. Second, diminish

strategies focus on assuring stakeholders the organization did not intend to do any harm or

claiming the crisis was not in control of the organization. Last, rebuild strategies aim to

restore the organization’s’ reputation by offering material or symbolic forms of aid to victims

(Coombs, 2007). Coombs and Holladay (2008) argue that organizational reputation is

influenced by the crisis-response strategy.

Denial as Crisis-response Strategy

The current research will focus on denial crisis-response strategies, being the most frequently

used by organization’s (Kim et al., 2009). Organization’s tend to use this strategies to avoid

legal actions and financial claims (Tyler, 1997). Although denial is the most frequently used


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strategy, it was also evaluated as the least effective strategy because it poses a risk when

perceived as inappropriate or fails to satisfy the stakeholders’ needs (Grebe, 2013). According

to Coombs (2007), organizations should prioritize protecting their stakeholders from harm

done by a crisis. While diminish and rebuild strategies are accommodative towards the

victims, denial strategies are defensive and organization-oriented. This might explain why a

denial strategy is not effective in most cases, since the main focus of this strategy is to

disclaim the organization’s guilt.

However, a denial strategy can be appropriate in given situations. For example,

research by Van der Meer (2014) found that a denial strategy can be effective when the

organization is not responsible for the crisis. In this case, the denial strategy resulted in frame

adoption and led to the acceptance of the organization’s response. Based on these findings,

denial strategies are only considered effective if the crisis fits the victim cluster. Denial

strategies are for example appropriate in misinformation crises, when the organization is

victimized by untrue information and holds no responsibility (Coombs, 2014). Uncontrollable

factors (i.e. natural disasters or malevolence) can also justify the use of denial (Coombs,

2007). However, in the initial phase of a crisis it is often unclear who holds responsibility and

thus which cluster the crisis fits. Crisis responsibility is partly determined in communication

when assigning meaning to crisis events (Claeys & Cauberghe, 2014).

Crisis Communication on Social Media

Stakeholders can turn to a variety of sources to make sense of a crisis (Palen, Vieweg, Liu &

Hughes, 2009). In crisis communication, social media can help to rebuild the stakeholders’

trust (Derani & Naidu, 2016) and diminish the impact of a crisis (Wendling, Radisch &

Jacobzone, 2013; Yates & Paquette, 2011). On the other hand, stakeholders often use social

networks to gather relevant information about crises while evaluating the associated risks and


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responsibilities (Valentini & Romenti, 2011). Furthermore, social media services can be

utilized to control negative word-of-mouth (Tucker & Melewar, 2005) and prevent damage to

the brand’s reputation caused by secondary crisis communication (Coombs & Holladay,

2007). Twitter is particularly used to share crisis-related information with the affected

community (Smith, 2010; Mendoza, Poblete & Castillo, 2010).

Employees as Source of Crisis Communication

Because social media allow anyone to be a content creator (Flanagin & Metzger, 2000), new

sources of crisis-communication have emerged. Third parties such as employees are often

forgotten as a potential source of crisis communication, despite their crucial role in protecting

the organization in times of crisis (Van Zoonen & van der Meer, 2015). Traditionally,

employees relied on internal communication systems and the long-established mass media to

voice their positive or negative experiences with the organization (Miles & Mangold, 2014).

Presently, social media enable employees to communicate their satisfaction or dissatisfaction

to a broad audience without effort. Miles and Mangold (2014) refer to this phenomenon as

employee voice, defined as “an employee’s attempt to use either organizationally sanctioned

or unsanctioned media or methods for the purpose of articulating organizational experiences

and issues or influencing the organization, its members, or other stakeholders”. While not all

enterprises have embraced employees as valuable communication assets, other organization’s

provided their employees with social media guidelines, encouraging employees to use social

media to the company’s advantage (Barker, 2008). More importantly, employees are

perceived as authentic representatives of their organization and therefore act as powerful

online influencers (Dreher, 2014).

In crisis communication, employees are both receivers and senders of information,

participating in social networks inside and outside of the organization (Frandsen & Johansen,


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2011). Employees are different compared to other stakeholders, as they hold a close

relationship with the organization (Frandsen & Johansen, 2011; Johansen, Aggerholm &

Frandsen, 2012). Employees see the organization as part of their identity (Wiesenfeld,

Raghuram & Garud, 2000), resulting in an obligatory feeling of protecting the organization

from reputational damage (Frandsen & Johansen, 2011). According to Van Zoonen, van der

Meer and Verhoeven (2014), employees can use social media to build relationships with

stakeholders and positively frame the organization online. In line, employees are well aware

of the possible negative effects of work-related tweets and are thus likely to tweet neutral and

factual information about the organization (Van Zoonen, Verhoeven & Vliegenthart, 2016). It

is expected that employees will not harm the organization in times of crisis when

communicating on social media. Instead, the literature suggests employees are valuable assets

in protecting the organization in times of crisis, preventing reputational harm. The credibility

of employees will lead to acceptance of the denial response-strategy. Thus, it is expected

secondary crisis communication will decrease. This leads to the following hypotheses:

H1a: In case of a denial strategy, an employee as crisis source leads to a higher reputation

compared to the organization as a source.

H1b: In case of a denial strategy, an employee as crisis source leads to decreased secondary

crisis communication compared to the organization as a source.

Timing in Crisis Communication

The timing of releasing crisis related information can be crucial (Arpan & Pompper, 2003;

Arpan & Roskos-Ewoldsen, 2005; Coombs, 2007). Timing refers to the moment when

information acknowledging the existence of a crisis is released (Coombs, 2015). Particularly


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in the early stage of a crisis, such as the prodromal period (Fink, 1986), choosing the right

timing strategy can prevent further organizational damage. News media often put pressure on

organizations to provide information quickly (Veil & Ojeda, 2010) due to the high news value

of crisis situations (Kleinnijenhuis, Schultz, Utz & Oegema, 2013). Moreover, crises can be

interpreted differently amongst stakeholders. After a crisis hits, sense-making processes

unfold rapidly resulting in a variety of frames surrounding the crisis event (Van der Meer,

Verhoeven, Beentjes, & Vliegenthart, 2013). Timely communication is, therefore, necessary

for the organization to become part of the frame building process and facilitate crisis

understanding. Existing literature about timing and crisis communication often refers to the

concept of ‘stealing thunder’ as a timing strategy. The concept was first addressed in literature

in the field of law, referring to stealing thunder as a “persuasion tactic in which an individual

reveals potential incriminating evidence first, for the purpose of reducing its negative impact

evaluative audience” (Dolnik, Case & Williams, 2003).

In crisis communication, an organization is ‘stealing thunder’ when it is the first to

report about an crisis incident before other sources do (Arpan & Pompper, 2003; Coombs,

2007). The opposite of stealing thunder is referred to as ‘thunder’ (Williams, Bourgeois &

Croyle, 1993; Dolnik et al., 2003), meaning others had discovered the crisis before the

organization itself acknowledged it. This is, for example, the case when journalists release

crisis-related information before the organization does. A stealing thunder strategy positively

impacts the organization’s’ credibility and diminishes reputational damage (Claeys &

Cauberghe, 2012; Arpan and Roskos-Ewoldsen, 2005). Social media can be used effectively

by organizations to steal thunder and enable crisis managers to quickly report a crisis without

relying on traditional news media (Coombs, 2014). Moreover, a timely response using

stealing thunder gives the organization more control of its response strategy, preventing news

agencies from spreading speculation about a crisis event (Ihlen, 2002). Last, accommodative


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response strategies (i.e. rebuild strategies) are deemed less necessary if the organization steals

thunder (Claeys & Cauberghe, 2012). This suggests that a defensive strategy (i.e. denial) is

effective when stealing thunder. In a situation where crisis responsibility is still unclear,

refuting any connection between the organization and the crisis using a defensive response

and stealing thunder timing strategy is expected to positively influence reputation. Moreover,

it is expected that stealing thunder leads to less secondary crisis communication because

stakeholders are more likely to accept the organization’s denial. Hence, the following

hypotheses are formulated:

H2a: In case of a denial strategy, a stealing thunder timing strategy leads to a higher

reputation than a thunder timing strategy

H2b: In case of a denial strategy, a stealing thunder timing strategy leads to less secondary

crisis communication than a thunder timing strategy

Source Credibility

In crisis communication, the credibility of the source is one of the predictors when evaluating

reputation (Van Zoonen and van der Meer, 2015). Credibility refers to the audience’s

confidence and acceptance of the source and its message (Hovland, Irving & Harold, 1968).

The current research will focus on the credibility of the source, or in other words, the

credibility of the communicator (Van Zoonen & van der Meer, 2015; Greer, 2003; Sundar &

Nass, 2001).

With regards to crisis communication on social media, stakeholders evaluate the

credibility of the sender of crisis-related information (i.e. the employee or organization).

Expertise and trustworthiness of the crisis source are important factors used by audiences in


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this evaluation process (Ibelma & Powell, 2001; Hovland et al., 1982). Moreover, the

credibility of the source influences how audiences form their opinion about the received

information (Beach, Mitchell, Deaton & Prothero, 1978). Hence, crisis managers should be

aware of the influence source credibility has on the organization's stakeholders. Credibility is

especially important when a denial crisis-response strategy is used. If the crisis source is

perceived as credible, the relevant audiences might accept the claim that the organization

holds no responsibility. Therefore, it is expected that the effect of crisis source and timing on

organizational reputation and secondary crisis communication is mediated by the credibility

of the source. The following hypotheses are formulated:

H3a: The main effect of crisis source on reputation is mediated by the credibility of the

source.

H3b: The main effects of crisis source on secondary crisis communication is mediated by the

credibility of the source.

H3c: The main effect of timing on reputation is mediated by the credibility of the source.

H3d: The main effects of timing on secondary crisis communication is mediated by the

credibility of the source.

Crisis responsibility

Stakeholders can have different opinions or thoughts about the extent to which the

organization is responsible for a crisis. Coombs and Holladay (2005) define crisis

responsibility as “how much people believe the organization is responsible for the crisis”.


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Crisis responsibility is not about the organization’s actual guilt, but about the audience’s

perception of the firm’s responsibility (Benoit, 1997). Attribution theory explains that people

have the need to search for causes of negative and unexpected events (Wiener, 1986).

Consequently, stakeholders determine crisis responsibility based on the attributions made

about the cause of the crisis (Coombs, 2007).

To minimize crisis responsibility, organization’s should take notice of the dominant

frames amongst their stakeholders and to what extent the firm is held responsible. It is

expected that the effect of source and timing on organizational reputation and secondary crisis

communication is mediated by the perceived crisis responsibility.

H4a: The main effect of crisis source on reputation is mediated by crisis responsibility.

H4b: The main effect of crisis source on secondary crisis communication is mediated by crisis

responsibility.

H4c: The main effect of timing on reputation is mediated by crisis responsibility.

H4d: The main effect of timing on secondary crisis communication is mediated by crisis

responsibility.

Crisis response acceptance

Third, the effectiveness of the crisis response strategy may predict if the organization’s’

response is perceived as appropriate by the publics. Acceptance of the crisis communication

strategy may limit reputational harm. Jin (2010) defines crisis response acceptance as “how

publics accept organization’s crisis strategy”. In line, Coombs and Holladay (2008) refer to


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this concept as account acceptance, meaning “how respondents feel about the crisis response

offered by the organization”. According to SCCT, crisis response acceptance is closely linked

with crisis-response strategies (Coombs, 2007). Whether stakeholders accept the crisis-

response from the organization, influences to what extent the response strategy affects

reputation (Coombs & Holladay, 2008). Therefore, it is expected crisis response acceptance

functions as an important mediator, leading to the following hypotheses:

H5a: The main effect of crisis source on reputation is mediated by crisis response acceptance.

H5b: The main effect of crisis source on secondary crisis communication is mediated by

response acceptance.

H5c: The main effect of timing on reputation is mediated by crisis response acceptance.

H5d: The main effect of timing on secondary crisis communication is mediated by crisis

response acceptance.

Method

Participants

An experiment was conducted amongst 192 participants. Participants have been recruited

trough social media and the researchers own network and were incentivized for their

participation by offering the chance to win a cinema voucher. It was ensured that the subjects

were familiar with Twitter. Respondents who did not meet this requirement were excluded.

Eventually, the final sample consisted of 164 subjects (39.6% male, 60.4% female) with a

mean age of 26 years (SD = 11.34). Of all participants, 69.5% (N = 114) followed or

completed higher education (university).


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Procedure and Design

To answer the research question, a 2 (crisis source: employee vs. organization) x 2 (timing

strategy: stealing thunder vs. thunder) between-subjects experimental design was used to

examine the main effects on organizational reputation and secondary crisis communication. In

addition, source credibility, crisis responsibility, and crisis response acceptance were included

as mediating variables to assess possible indirect effects.

The experiment was conducted using an online questionnaire. First, participants were

informed about the nature of the research and their consent for participation was asked. Since

the experimental material involves a Twitter profile, participants were asked if they were

familiar with Twitter. Only subjects acquainted with Twitter were allowed to continue. Next,

participants were familiarized with a fictitious company called ‘Best Coffee’. A short briefing

explained that Best Coffee is a well-known chain of coffee stores operating in The

Netherlands, serving coffee and other hot and cold beverages, sandwiches and snacks.

Further, the crisis was briefly introduced by explaining how a customer claimed to got sick

after visiting one of Best Coffee’s stores, but that it remains unclear if Best Coffee caused the

illness. Thus, crisis responsibility was open for the respondents to determine. Next, the

participants were randomly assigned to one of the four experimental conditions. Four

conditions were created, varying in the source of the crisis communication and the used

timing strategy (employee/thunder, employee/stealing thunder, organization/thunder,

organization/stealing thunder). Subsequently, organizational reputation, secondary crisis

communication, crisis response acceptance, source credibility and crisis responsibility were

measured. Finally, a manipulation check was conducted, and demographic data were asked.

On the last page, the participants were thanked for their participation, and it was explained


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that the organization, Twitter profile, and crisis were fictional and only created for the current

research.

Experimental Materials

For the current experiment, four different Twitter profile pages were fabricated, related to a

fictitious company called ‘Best Coffee’. The crisis case was held constant in all conditions

and reported a customer got ill due to a bacterial infection after visiting a Best Coffee store.

The source was manipulated by randomly assigning the respondents to either a Twitter profile

owned by Best Coffee or an employee. To maintain a high internal validity, several elements

of the Twitter profile were adjusted to make a clear distinction between the organization and

the employee.

The source was manipulated by altering the profile picture, header image and the

biography of the user’s profile. For example, the employee’s profile featured a personal

profile picture while the brand’s profile included their logo. Further, the profile’s statistics

such as the number of tweets and followers was changed. As is often the case with

professional accounts, the companies profile was verified by Twitter (indicated by a blue

badge next to the username) and included a link to Best Coffee’s website.

Timing was manipulated by altering the message of the first Tweet. The thunder

condition included a retweet (sharing another account's Tweet) of a news article published by

the NOS, a well-known Dutch public service news broadcaster. The official NOS Twitter-

account (@NOS) tweeted the following message: “Best Coffee customer claimed to got sick

from dangerous bacteria. Read the full article here: nos.nl/29382”. This retweet was

accompanied with a response from either the organization or the employee. The organization

responded: “According to the @NOS, a customer got sick due to a bacterial infection after

visiting Best Coffee.”, while the employees Twitter message stated: “I just read this article


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from @NOS, allegedly a customer got sick after visiting my store”. In turn, the stealing

thunder condition did not include a retweet from the news agency, but the initial report about

the incident was done by the employee or organization. In the employee source condition, the

Tweet stated: “While working at Best Coffee, a customer called us and claimed to got sick

after a visit to my store. Something with bacteria.”. On the contrary, the organization broke

the news by Tweeting: “Our customer service just got an alarming phone call. One of our

customers claimed to got sick by a bacterial infection.”.

To make sure the manipulation of the source and timing was perceived correctly, a

briefing before the manipulation also disclosed the owner of the Twitter profile (employee or

organization) and who initially reported the crisis incident (employee, organization or news

media).

Moreover, a denial strategy was used by both the employee and the organization.

Three more tweets simulated this strategy by denying the involvement of Best Coffee with the

incident, claiming the stores were recently checked and approved by the authority of food

safety and that this was the first time a customer got sick.

The questionnaire and experimental material were translated into Dutch (Appendix D),

as the research was conducted in The Netherlands.

Dependent Measurements

Organizational reputation was measured using six item 7-point Likert-scale adapted from the

research of Coombs and Holladay (2002) and Fombrun, Gardberg and Sever (2000).

Respondents were asked to what extend they agreed (1=fully disagree, 7=fully agree) with

items such as: “I trust Best Coffee”, “Best Coffee offers high quality products” and “Best

Coffee is a responsible company”. A new scale was created by calculating the means of the

six items of organizational reputation (Cronbach’s α = .90, M = 4.32, SD = 1.07).


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Secondary crisis communication was measured using a three item 7-point Likert-scale

adapted from the research of Schultz et al. (2011). Respondents were asked to indicate the

likeliness (1=very unlikely, 7=very likely) of: sharing the tweets with others (retweeting), tell

others about the tweets and placing a reaction on the tweets. A new scale was created by

calculating the means of the these items (Cronbach’s α = .75, M = 2.15, SD = 1.21).

Source credibility was measured using a five item 7-point Likert-scale based on the

research of Metzger, Flanagin, and Zwarun (2003) and Grewal, Gotlieb and Marmorstein

(1994). Respondents were asked to what extend they agreed (1=fully disagree, 7=fully agree)

with items such as: “The sender of the tweets is credible”, “The sender of the tweets can be

trusted” and “The sender of the tweets is an expert”. A new scale was created by calculating

the means of the five items (Cronbach’s α = .81, M = 3.79, SD = 1.11).

Crisis responsibility was measured by six items using a 7-point Likert-scale adapted

from the research of Brown and Ki (2013). Respondents were asked to what extend they

agreed (1=fully disagree, 7=fully agree) with items such as: “The cause of the crisis was

intentionally done by someone (or something) within the organization.”, “The crisis was

preventable by the organization.” and “The organization should be blamed for the crisis.”. An

initial reliability analysis suggested an unreliable scale, Cronbach’s α = .52. Therefore, two

items negatively affecting the scale were deleted. A new scale was created with the remaining

four items, by calculating the means of the crisis responsibility items (Cronbach’s α = .73, M

= 3.21, SD = 1.04).

Crisis response acceptance was measured by five items using a 7-point Likert-scale

adapted from the research of Jin (2010). Respondents were asked to what extend they agrede

(1=fully disagree, 7=fully agree) with items such as: “The reaction of the Twitter user was

appropriate”, “The Twitter user acted correctly” and “The reaction of the Twitter user was


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sincere”. A new scale was created by calculating the means of the five items (Cronbach’s α =

.93, M = 3.66, SD = 1.35).

Pretest

A pretest was conducted amongst 25 test participants to examine if the source and timing

manipulations were perceived as intended. Using an online questionnaire, respondents were

randomly assigned to one of the four conditions. First, to check the manipulation of the

source, respondents were asked to identify the owner of the Twitter profile as either an

employee or the organization. Moreover, to verify the manipulation of timing, respondents

were asked whether the employee, organization or news media was the first to report about

the crisis incident. A second question asked if the owner of the Twitter profile was the one to

announce the news about the crisis. Respondents could also select “don’t know” for each

question.

Appendix A summarizes the manipulation of source and timing. A chi-square test

showed significant differences between the groups for the manipulation of source X2 (6) =

17.34, p = 0.008 and the manipulation of timing X2 (9) = 32.67, p = 0.000.

Furthermore, the participants were asked to rate the authenticity of the experimental

material on a 7-point Likert scale. Results show the material was perceived as sufficient

authentic (M = 5,56, SD = 0.87). Additionally, 84% of the respondents indicated to be

familiar with Twitter. Hence, the manipulation material was not altered in the proceeded

experiment.

Data Analysis

Several statistical analysis were conducted to answer the defined hypothesis. For hypothesis1

and 2, a multivariate analysis of covariance (MANCOVA) was conducted. This analysis was


21

found most suitable as the dependent and mediating variables were measured on interval

level. Moreover, an MANCOVA it allows measurements for multiple dependent variables

and the inclusion of covariates. Based on the conditions, dummy variables were created for

source (0 = organization, 1 = employee) and timing (0 = thunder, 1 = stealing thunder).

Further, to test the effects of the mediators (hypothesis 3, 4 and 5), different regression

models were constructed using the PROCESS mediation analysis (Hayes, 2013). PROCESS

is a regression-based approach to test multiple regressions within one model. Moreover, the

PROCESS analysis uses bootstrapping to ensure reliable and accurate results for the

analytical models. Hence, the PROCESS analysis is found to be most suitable for the current

research as it allows testing of direct and indirect effects of multiple independent and

mediating variables.

Results

Randomization check

To check if the respondents are equally distributed amongst the four experimental conditions,

a one-way analysis of variance (ANOVA) was conducted with the four conditional groups as

the independent variable and age as the dependent variable. None of the four conditions

showed significant differences for age F (3, 159) = 1.74, p = .16. Further, a chi-square test

was conducted to check if the educational level was equal amongst the participants. Results

show insignificant differences for educational level between the conditions X2 (12) = 15.55, p

= .213. Further, another chi-square test showed no significant differences for gender between

the conditions X2 (3) = 3.68, p = 0.298. Last, it was checked if participants possessing a

Twitter account were divided equally amongst the groups. Again, no significant differences

between the conditions were found X2 (3) = 0.46, p = .927. Based on this analysis, it is

assumed that there are no differences between the conditions considering the variables age,

educational level, gender and Twitter account possession.


22

The participants were roughly equally divided amongst the conditions. Condition A

(employee/thunder) counted 38 participants (23,2%), condition B (employee/stealing thunder)

counted 43 participants (26,2%), condition C (organization/thunder) counted 42 participants

(25,6%) and last 41 participants (25%) were assigned to condition D (organization/stealing

thunder).

Manipulation check

In the current research, the source and timing of the Twitter messages were altered. To check

if the manipulation of the source was successful, a control question asked whether the Twitter

profile was owned by an employee or the organization. A chi-square test showed significant

differences between the groups X2 (6) = 116.71, p < .001, meaning the manipulation of the

source was successful. To check the manipulation of the timing, respondents had to indicate

who communicated about the crisis incident first: the news media, an employee or the

organization. A chi-square test checking the manipulation of timing showed significant

differences between the groups X2 (9) = 148.33, p < .001, suggesting successful manipulation.

Appendix B summarizes the results.

Covariates

A Pearson correlation matrix was constructed to control for the variables gender, age,

education and Twitter account in correspondence with the dependent variables organizational

reputation and secondary crisis communication. No significant correlations were found

between the control and dependent variables. Therefore, gender, age, education and Twitter

account were not included in further analysis. In addition, the mediator’s source credibility,

crisis responsibility and crisis response acceptance were included in the matrix. Significant

correlations were found. Hence, these variables were added as covariates in further analysis.


23

Appendix C shows an overview of the correlations and the significant effects.

Hypothesis testing

The hypothesis formulated in the current research are tested below.

Hypothesis 1a and 1b. First, testing the effect of crisis source, the MANCOVA found

a marginally significant effect for crisis source on organizational reputation, F (1, 157) = 3.05,

p = .083. Subjects who were exposed to the employee source condition scored marginally

significant higher on organizational reputation (M = 4.39, SD = 1.04) compared to subjects

exposed to the organization source condition (M = 4.26, SD = 1.10). However, no significant

effect was found for the effect of crisis source on secondary crisis communication, F (1, 157)

= 2.36, p = .127. Subjects exposed to the employee source condition did not score

significantly higher on secondary crisis communication (M = 2.23, SD = 1.31) compared to

subjects exposed to the organization source condition (M = 2.07, SD = 1.10). The results

suggest that using an employee as source of crisis communication results in a higher

organizational reputation while using a denial strategy then when the organization is the

source, accepting hypothesis 1a. However, these effects do not hold up for secondary crisis

communication, rejecting hypothesis 1b.

Hypothesis 2a and 2b. Second, testing the effects of timing, the MANCOVA showed

no significant effect was found for timing on organizational reputation, F (1, 157) = .24, p =

.624. Subjects exposed to the thunder timing strategy did not score significantly higher on

organizational reputation (M = 4.28, SD = 1.18) compared to subjects exposed to the stealing

thunder timing strategy (M = 4.36, SD = 0.96). Furthermore, no significant effect was found

for timing on secondary crisis communication F (1, 157) = .46, p = .499. Subjects exposed to

the thunder timing strategy did not score significantly higher on secondary crisis

communication (M = 2.18, SD = 1.34) compared to those exposed to the stealing thunder


24

timing strategy (M = 2.12, SD = 1.21). The results suggest that using an stealing thunder

timing strategy does not result in a higher organizational reputation or less secondary crisis

communication while using a denial strategy. Hence, hypothesis 2a and 2b are rejected.

Interaction source and timing. Furthermore, the ANCOVA revealed no significant

interaction effects of source and timing on reputation, F (1, 157) = .12, p = .707 and

secondary crisis communication, F (1, 157) = 1.49, p = .224. The means of the four

conditions on the dependent variables are summarized in Table 1. Although no significant

effects were found, the mean differences seem to be in the desired direction: when an

employee steals thunder, organizational reputation is perceived higher. Moreover, the stealing

thunder conditions both result in less secondary crisis communication.

Table 1. Means of interaction effect source and timing on dependent variables

Organizational reputation Secondary crisis communication

Condition M SD M SD

Employee / Thunder 4.36 1.23 2.39 1.62

Employee / Stealing Thunder 4.42 .84 2.09 .94

Organization / Thunder 4.30 1.07 2.14 1.20

Organization / Stealing Thunder 4.21 1.14 1.99 1.00

Last, Levene’s test assumed equal variances in the population for the variable

organizational reputation, F (3, 160) = 1.59, p = .194 and crisis response acceptance F (3,

160) = 0.91, p = .436. It should be noted that the assumption of equal variances in the

population has been violated for the variable secondary crisis communication, F (3, 160) =

2.81, p = .041.


25

Mediation analysis

To test hypothesis 3, 4, and 5, five regression models were constructed using the PROCESS

mediation analysis (Hayes, 2013). The first three models tested the effects of the independent

variables (source and timing) on the mediating variables (source credibility, crisis

responsibility and crisis response acceptance). The fourth model examined the effects of the

mediating variables and independent variables on organizational reputation while the fifth

model examined the effects on secondary crisis communication. When constructing each of

the models, either source or timing was added as covariate. Later the covariate and

independent variable were switched to accurately measure the direct effects of source and

timing on reputation and secondary crisis communication. The findings of the models are

summarized in Table 2. Finally, Sobel tests were conducted to check for significant mediation

effects.

Effects on source credibility, crisis responsibility and response acceptance.

Initial analysis revealed that the regression model of crisis source and timing with the

mediator source credibility as the outcome was not significant (Model 1). Source and timing

do not predict source credibility. Further, the regression model of source and timing with

crisis responsibility as the outcome was significant (Model 2), but the strength of the

prediction is weak. Only crisis source is found to be the significant predictor. Third, crisis

source and timing are not significant predictors for crisis response acceptance (Model 3). The

model is not found to be significant.

Effects on reputation.

The overall model (Model 4) with the effects of the independent and mediating variables on

organizational reputation was significant and has a strong prediction. It is suggested that


26

source credibility, crisis responsibility, and crisis response acceptance are significant

predictors for organizational reputation. Crisis source shows a marginally significant effect,

while no effect was found for timing. For all these effects, other variables are assumed to be

held constant.

Hypothesis 3a, 4a, and 5a. When looking at the direct effects of source on reputation

while ignoring the mediators and including timing as covariate, the regression was not

significant (b* = .13, t (2,161) = 0.78, p = .438). Results of the Sobel test suggests that the

relation between crisis source and organizational reputation is marginally significant mediated

by crisis responsibility (Sobel Z = 1.80, p = 0.073) but not by source credibility (Sobel Z = -

.58, p = 0.564) and response acceptance (Sobel Z = -1.50, p = 0.134). Based on these findings,

hypothesis 4a is accepted. However, no significant mediation effect was found for source

credibility and response acceptance on reputation, rejecting hypothesis 3a and 5a.

Hypothesis 3c, 4c, and 5c. Moreover, the regression of timing on reputation, ignoring

the mediators and including source as covariate, was not significant (b* = .08, t (2,161) =

0.46, p = .661), suggesting no direct effect of timing on reputation. The Sobel test suggests

that the relation between timing and organizational reputation is not significantly mediated by

source credibility (Sobel Z = .85, p = 0.398), crisis responsibility (Sobel Z = .68, p = 0.495)

and response acceptance (Sobel Z = -.96, p = 0.335). Based on these results, hypothesis 3c, 4c

and 5c are rejected.

Effects on Secondary Crisis Communication

The overall model (Model 5) with the effects of the independent and mediating

variables on secondary crisis communication was significant but has a weak prediction. The

model suggests that source credibility and crisis responsibility are significant predictors for


27

secondary crisis communication. Response acceptance, crisis source, and timing are however

not significant. For all these effects, other variables are assumed to be held constant.

Hypothesis 3b, 4b, and 5b. Looking at the direct effects of source on secondary crisis

communication while ignoring the mediators and including timing as covariate, the regression

was not significant (b* = .16, t (2,161) = .87, p = .388). Results of the Sobel test suggest that

the relation between crisis source and secondary crisis communication is marginally

significant mediated by crisis responsibility (Sobel Z = -1.76, p = 0.079) but not by source

credibility (Sobel Z = -.56, p = 0.574) and response acceptance (Sobel Z = .60, p = 0.550).

Taken together, these results suggest crisis responsibility is a possible mediator in the relation

between source and secondary crisis communication, accepting hypothesis 4b. No significant

mediation effect was found for source credibility and response acceptance on secondary crisis

communication, rejecting hypothesis 3b and 5b.

Hypothesis 3d, 4d, and 5d. The regression of timing on secondary crisis

communication, ignoring the mediators and including source a covariate, was not significant

(b* = .07 t (2,161) = -.36, p = .720), suggesting no direct effect of timing on secondary crisis

communication. A Sobel test suggests that the relation between timing and secondary crisis

communication is not significantly mediated by source credibility (Sobel Z = .82, p = 0.413),

crisis responsibility (Sobel Z = -.68, p = 0.498) and response acceptance (Sobel Z = .47, p =

0.636). Based on these results, hypothesis 3d, 4d and 5d are rejected.


28

Table 2. Regression models to predict dependent variables.

Note. N = 164

* p < 0.05

** p < 0.10 (marginally significant)

Model b* t p R2 F df

1 Outcome: Source credibility

Overall model .587 .01 .53 2, 161

Crisis source -.10 -.59 .558

Timing .15 .87 .388

2 Outcome: Crisis responsibility

Overall model .048* .04 3.09 2, 161

Crisis source -.38 -2.35 .020*

Timing -.12 -.74 .461

3 Outcome: Response acceptance

Overall model .166 .02 1.82 2, 161

Crisis source -.34 -1.60 .112

Timing -.21 -1.00 .319

4 Outcome: Reputation

Overall model .000* .56 40.53 5, 158

Source credibility .41 6.13 .000*

Crisis responsibility -.17 -3.01 .003*

Response acceptance .28 5.09 .000*

Crisis source .20 1.75 .082**

Timing .05 .48 .634

5 Outcome: Secondary crisis communication

Overall model .000* .14 5.21 5, 158

Source credibility .41 3.86 .000*

Crisis responsibility .25 2.87 .005*

Response acceptance -.07 -.76 .448

Crisis source .28 1.53 .129

Timing -.11 -.63 .532


29

Conclusion and Discussion

The current research experimentally investigated the effects of crisis source and timing on

social media while using a denial strategy. The effects on organizational reputation and

secondary crisis communication were measured. Moreover, the role of source credibility,

crisis responsibility and crisis response acceptance as possible mediators was explored.

First, it was expected that an employee as crisis source leads to a higher organizational

reputation than when the organization was the source. The results support this expectation as

employees are found to have a more positive effect on reputation than when the organization

was the source, when using a denial strategy. These findings are in line with Van Zoonen, van

der Meer and Verhoeven (2014), who argued that employees positively influence the

organization on social media. Further, the favorable impact employees have on reputation

might be accounted for by their authentic and credible appearance (Dreher, 2014).

Second, it was expected that an employee as crisis source decreased secondary crisis

communication compared to the organization as a source, while using a denial strategy.

However, this expectation was not supported by the current results. Although Schultz, Utz

and Goritz (2010) found that post-crisis communication influences secondary crisis

communication, the current results suggest consumers will not engage in more or less

secondary crisis communication irrespectively of the source.

Third, it was expected that a stealing thunder timing strategy results in a higher

organizational reputation than a thunder timing strategy. However, the current study implies

that timing does not impact organizational reputation. The results are in contrary with the

findings of Claeys and Cauberghe (2011) who argued that a stealing thunder strategy

positively impacts the organization’s’ credibility, diminishing reputational damage. The fact

that Claeys and Cauberghe (2011) focused on a preventable crisis while providing factual

information instead of denying the organization’s involvement, might explain these


30

differences. Future research on stealing thunder as timing strategy must decide if strategies

other than denial yield the same results.

Moreover, it was expected that a stealing thunder strategy leads to less secondary

crisis communication. However, secondary crisis communication was not affected by the

timing strategy. This is somewhat in line with the research by Arpan and Pompper (2003),

who suggested that the severity of the crisis was not impacted by timing. Hence it is possible

secondary crisis communication is linked with the gravity of the crisis.

In line, previous literature suggested that stealing thunder results in a higher credibility

of the source (Eagly, Wood and Chaiken, 1978; Arpan and Pompper, 2003). As the current

results prove otherwise, it could be that this effect does not hold up when using denial

strategies.

Lastly, the results show that the effect of crisis source on reputation and secondary

crisis communication is mediated by crisis responsibility. When the organization was the

source, subjects assigned more responsibility to the organization compared to the employee as

source. This could be explained by the fact that employees are seen as powerful online

influencers (Dreher, 2014). Thus, when employees use denial in their response, the results

suggest the organization’s responsibility for the crisis decreases, leading to a higher

reputation. Further, if the organization is found to be more responsible for the crisis, it is

likely secondary crisis communication will increase. However, the effect of timing on

reputation and secondary crisis communication was not mediated by crisis response

acceptance. The results further suggest that the effect of source and timing on reputation and

secondary crisis communication is also not mediated by source credibility and crisis

responsibility.

In conclusion, when organization’s in times of crisis use denial as their response

strategy on social media, employees should be considered as valuable actors in helping the


31

organization to minimize reputational damage. Timing, however, is not found to reduce

reputational damage when using a denial. Further research is needed to examine the effects of

timing in more detail.

Limitations & practical implications

One limitation of the current research is the use of a fictitious organization and crisis. Future

research could examine the effects of source and timing in an actual crisis, as Coombs (2007)

suggests that prior relational reputation and crisis history impacts the reputational thread.

Moreover, the current experiment was mostly conducted amongst students. Although this

group is likely to use and be familiar with social media platforms, it is possible that elderly or

less familiar consumers process information on social media differently. Further, Twitter was

especially examined in this study. However, it could be that the effects of source and timing

while using a denial strategy are different when applied in other online environments (i.e.

blogs, Facebook, corporate website).

The current research has several implications for crisis communication and public

relation practitioners. First, this research extends the SCCT by demonstrating the importance

of employees in crisis communication while using a denial strategy. Crisis managers could

use this knowledge to improve their strategic communication processes. For example, as

suggested by Barker (2009), offering social media guidelines for employees could prepare

them before a crisis hits. These guidelines could help organizations to use employees in crisis

communication to their full potential. Furthermore, the present results emphasize the

importance of crisis responsibility. With the emerging social media, many actors can engage

in the crisis discourse, framing the responsibility of the crisis. Therefore, companies should

not only be aware their actual responsibility but also if their audiences see the organization as

responsible.


32

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Appendix

Appendix A. Overview manipulation check of pre-test

Condition Employee

Thunder Employee

Stealing Thunder Organization


Thunder Owner Twitter profile

Employee 6* 4* 0 1 Organization 1 1 5* 6* Don’t know 0 1 0 0

Initial crisis reporting News media 6* 0 0 5* Employee 1 5* 0 0 Organization 0 0 3* 2 Don’t know 0 1 2 0

Note. N = 25. * manipulation was successful


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Appendix B. Overview manipulation check final experiment

Condition Employee

Thunder Employee



Thunder Owner Twitter profile

Employee 33* 39* 3 3 Organization 3 2 38* 36* Don’t know 2 2 1 2

Initial crisis reporting News media 33* 6 10 38* Employee 3 34* 8 2 Organization 0 1 20* 0 Don’t know 0 2 2 1

Note. N = 164. * manipulation was successful

Appendix C. Pearson correlation matrix

Organizational reputation Secondary crisis communication

Gender -.06 -.10 Age -.12 .10 Education .01 -.11 Twitter account .04 -.08 Source credibility .67* .29* Crisis responsibility -.28** .16** Crisis response acceptance .63* .13

Note. N = XXX. Pearsons correlations. * p < 0.001 ** p < 0.05 Appendix D. Questionnaire and stimulus material Q1 De Universiteit van Amsterdam vraagt uw medewerking voor een onderzoek over crisis communicatie en sociale media. Tijdens het onderzoek zullen wij u een aantal korte vragen stellen. Het onderzoek duurt tussen de 4 a 8 minuten. Wij raden u aan om dit onderzoek uit te voeren op een computer of tablet. Lees de instructies en vragen zorgvuldig. Q2 Bent u bekend met Twitter? Dat wil zeggen dat u ongeveer weet wat Twitter is en hoe het werkt. U heeft geen Twitter-account nodig. m Ja m Nee Q3 U gaat nu beginnen met het onderzoek. Lees de onderstaande instructies en klik daarna op 'Volgende'. Zometeen krijgt u een Twitter-profiel te zien. Beeld u zich in dat u de website van Twitter bezoekt en u dit profiel tegen komt. Bekijk het profiel en lees de bijhorende Twitter-berichten (Tweets) zorgvuldig.Neem alle tijd die u nodig heeft om het profiel te bekijken. Na ongeveer 20 seconden kunt u doorgaan naar de volgende pagina. Vervolgens krijgt u een aantal vragen voorgelegd over het Twitter-profiel dat u zojuist heeft bekeken.


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Lees de vragen rustig door. Er zijn geen goede of foute antwoorden. Nadat u alle vragen heeft beantwoord kunt u het onderzoek afronden. Q4a Lees de onderstaande tekst zorgvuldig. In het volgende scherm krijgt u een schermafbeelding te zien van een Twitterprofiel met een aantal Tweets die gaan over het bedrijf Best Coffee. Best Coffee is een grote keten van koffiehuizen met vestigingen door heel Nederland. Naast koffie verkoopt Best Coffee ook andere warme en koude dranken, broodjes en snacks. Een klant meldt ziek te zijn geworden na een bezoek aan een van de filialen van Best Coffee. Op de volgende pagina krijgt u een reactie van een werknemer hierop te zien via Twitter. De NOS was de eerste die een nieuwsbericht over deze situatie plaatste, waarop de werknemer reageert. Q4b Bekijk de onderstaande schermafbeelding zorgvuldig. U kunt verder gaan naar de volgende pagina als u het Twitter-profiel goed heeft bekeken. Als u de tekst niet goed kunt lezen kunt u de afbeelding in een nieuw venster openen. Het laden kan soms even duren. Q4c – Employee / Thunder

Q5a Lees de onderstaande tekst zorgvuldig. In het volgende scherm krijgt u een schermafbeelding te zien van een Twitter-profiel met een aantal berichten (Tweets) die gaan over het bedrijf Best Coffee. Best Coffee is een grote keten van koffiehuizen met vestigingen door heel Nederland. Naast koffie verkoopt Best Coffee ook andere warme en koude dranken, broodjes en snacks. Een klant meldt ziek te zijn geworden na een bezoek aan een van de filialen van Best Coffee. Op de volgende pagina krijgt u een reactie van een werknemer


41

hierop te zien via Twitter. De werknemer was de eerste die een bericht plaatste over deze situatie. Q5b Bekijk de onderstaande schermafbeelding zorgvuldig. U kunt verder gaan naar de volgende pagina als u het Twitter-profiel goed heeft bekeken. Als u de tekst niet goed kunt lezen kunt u de afbeelding in een nieuw venster openen. Het laden kan soms even duren. Q5c Employee / Stealing Thunder

Q6a Lees de onderstaande tekst zorgvuldig. In het volgende scherm krijgt u een schermafbeelding te zien van een Twitter-profiel met een aantal berichten (Tweets) die gaan over het bedrijf Best Coffee. Best Coffee is een grote keten van koffiehuizen met vestigingen door heel Nederland. Naast koffie verkoopt Best Coffee ook andere warme en koude dranken, broodjes en snacks. Een klant meldt ziek te zijn geworden na een bezoek aan een van de filialen van Best Coffee. Op de volgende pagina krijgt u een reactie van het bedrijf hierop te zien via Twitter. Het bedrijf was de eerste die een bericht plaatste over deze situatie.


42

Q6b Bekijk de onderstaande schermafbeelding zorgvuldig. U kunt verder gaan naar de volgende pagina als u het Twitter-profiel goed heeft bekeken. Als u de tekst niet goed kunt lezen kunt u de afbeelding in een nieuw venster openen. Het laden kan soms even duren. Q6c Organization / Stealing Thunder

Q7a Lees de onderstaande tekst zorgvuldig. In het volgende scherm krijgt u een schermafbeelding te zien van een Twitter-profiel met een aantal berichten (Tweets) die gaan over het bedrijf Best Coffee. Best Coffee is een grote keten van koffiehuizen met vestigingen door heel Nederland. Naast koffie verkoopt Best Coffee ook andere warme en koude dranken, broodjes en snacks. Een klant meldt ziek te zijn geworden na een bezoek aan een van de filialen van Best Coffee. Op de volgende pagina krijgt u een reactie van het bedrijf hierop te zien via Twitter. De NOS was de eerste die een nieuwsbericht plaatste over deze situatie, waarop het bedrijf reageert.


43

Q7b Bekijk de onderstaande schermafbeelding zorgvuldig. U kunt verder gaan naar de volgende pagina als u het Twitter-profiel goed heeft bekeken. Als u de tekst niet goed kunt lezen kunt u de afbeelding in een nieuw venster openen. Het laden kan soms even duren. Q7c Organization / Thunder

Q8 Geef aan in hoeverre u het eens of oneens bent met de onderstaande stellingen. De stellingen gaan over de Twitter-berichten (Tweets) en bijhorend profiel dat u zojuist heeft gezien. Selecteer het meest linker rondje indien u het volledig oneens bent met de betreffende


44

stelling. Selecteer het meest rechter rondje indien u het volledig eens bent met de betreffende stelling. U kunt ook de rondjes tussen de twee uitersten selecteren.

Volledig

mee oneens

Oneens Beetje oneens Neutraal

Beetje mee eens

Eens Volledig mee eens

De afzender van de Tweets

is geloofwaardig.

m m m m m m m

De afzender van de Tweets is betrouwbaar.

m m m m m m m


is niet bevooroordeeld.

m m m m m m m

De afzender van de Tweets is een expert.

m m m m m m m


is goed. m m m m m m m

Q9 Geef aan in hoeverre u het eens of oneens bent met de onderstaande stellingen. De stellingen gaan over de Twitter-berichten (Tweets) en bijhorend profiel dat u zojuist heeft gezien. Het voorval refereert naar de klant die meldt ziek te zijn geworden na een bezoek aan Best Coffee. Selecteer het meest linker rondje indien u het volledig oneens bent met de


45

betreffende stelling. Selecteer het meest rechter rondje indien u het volledig eens bent met de betreffende stelling. U kunt ook de rondjes tussen de twee uitersten selecteren.

Volledig

mee oneens


Beetje mee eens

Eens Volledig

mee eens

Het voorval is opzettelijk

veroorzaakt door iemand (of iets)

binnen Best Coffee.

m m m m m m m

Best Coffee had zich op het

voorval kunnen voorbereiden.

m m m m m m m

Best Coffee had het voorval

kunnen voorkomen.

m m m m m m m

Best Coffee is schuldig aan het

voorval. m m m m m m m

Het voorval is veroorzaakt door

problemen buiten Best

Coffee.

m m m m m m m

Best Coffee is verantwoordelijk omgegaan met

het voorval.

m m m m m m m

Q10 Geef aan in hoeverre u het eens of oneens bent met de onderstaande stellingen. De stellingen gaan over de Twitter-berichten (Tweets) en bijhorend profiel dat u zojuist heeft gezien. Selecteer het meest linker rondje indien u het volledig oneens bent met de


46

betreffende stelling. Selecteer het meest rechter rondje indien u het volledig eens bent met de betreffende stelling. U kunt ook de rondjes tussen de twee uitersten selecteren.

Volledig

mee oneens


Beetje mee eens

Eens Volledig

mee eens

Ik heb vertrouwen in Best Coffee.

m m m m m m m

Ik heb een goed gevoel bij Best

Coffee. m m m m m m m

Best Coffee staat achter haar producten.

m m m m m m m

Best Coffee biedt producten aan van hoge

kwaliteit.

m m m m m m m

Best Coffee geeft waar voor

je geld. m m m m m m m

Best Coffee is een

verantwoordelijk bedrijf.

m m m m m m m

Q11 Geef bij de onderstaande stellingen aan hoe waarschijnlijk het is dat u deze actie zult uitvoeren. De stellingen gaan over de Twitter-berichten (Tweets) en bijhorend profiel dat u zojuist heeft gezien. Selecteer het meest linker rondje indien het zeer onwaarschijnlijk is dat u de betreffende actie zult uitvoeren. Selecteer het meest rechter rondje indien het zeer waarschijnlijk is dat u de betreffende actie zult uitvoeren. U kunt ook de rondjes tussen de twee uitersten selecteren.

Zeer onwaarschijnlijk - - Neutraal - - Zeer

waarschijnlijk Ik zou de

Twitterberichten delen met

anderen (bijv: retweeten).

m m m m m m m

Ik zou vrienden vertellen over de Twitterberichten.

m m m m m m m

Ik zou reageren op de

Twitterberichten. m m m m m m m


47

Q12 Geef aan in hoeverre u het eens of oneens bent met de onderstaande stellingen. De stellingen gaan over de Twitter-berichten (Tweets) en bijhorend profiel dat u zojuist heeft gezien. De Twitter-gebruiker is de eigenaar van het profiel dat u zojuist heeft gezien. Selecteer het meest linker rondje indien u het volledig oneens bent met de betreffende stelling. Selecteer het meest rechter rondje indien u het volledig eens bent met de betreffende stelling. U kunt ook de rondjes tussen de twee uitersten selecteren.

Volledig

mee oneens

Oneens Beetje mee

oneens Neutraal

Beetje mee eens

Eens Volledig mee eens

De reactie van de Twitter-

gebruiker op het voorval

was passend.

m m m m m m m

De Twitter-gebruiker heeft juist gehandeld.

m m m m m m m


gebruiker was geloofwaardig.

m m m m m m m

De reactie van de Twitter-gebruiker is

passend in een vergelijkbare

situatie.

m m m m m m m


gebruiker was oprecht.

m m m m m m m


gebruiker was adequaat.

m m m m m m m

U bent bijna klaar. Er volgen nog een aantal korte vragen. Q13 Het Twitter-profiel dat u eerder heeft gezien was van: m Een werknemer van 'Best Coffee' m Het bedrijf 'Best Coffee' zelf m Weet ik niet (meer)


48

Q14 Wie kwam er volgens u als eerst naar buiten met het nieuws over de ziek geworden klant? m De (nieuws)media m Een werknemer van 'Best Coffee' m Het bedrijf 'Best Coffee' zelf m Weet ik niet (meer) Q15 Wat is uw geslacht? m Man m Vrouw Q16 Wat is uw leeftijd in jaren? Q17 Wat is uw hoogst genoten opleiding? Dit is uw hoogst afgeronde opleiding of de opleiding waar u momenteel mee bezig bent. m Geen m Basisonderwijs m Voortgezet onderwijs (VMBO, HAVO, VWO) m MBO (Middelbaar beroepsonderwijs) m HBO (Hoger beroepsonderwijs) m WO (Wetenschappelijk onderwijs) Q18 Heeft u een Twitteraccount? m Ja m Nee Q19 Als dank wordt er een bioscoopbon verloot onder de deelnemers van dit onderzoek. Als u hierop kans wilt maken, vul dan hieronder uw e-mailadres in. Deze wordt enkel gebruikt om willekeurig één winnaar te selecteren. De prijswinnaar ontvangt een e-mail. Uw anonimiteit is ten alle tijden gewaarborgd. Dit veld is niet verplicht. Klik op 'Volgende' om door te gaan. Q20 Alle vragen zijn beantwoord, hartelijk bedankt voor uw deelname. Het Twitterprofiel dat u heeft gezien, de crisis situatie en het bedrijf Best Coffee zijn fictief en enkel gecreëerd voor dit onderzoek. Klik op 'Afronden' om uw antwoorden op te slaan.

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