Can you handle the truth? : risk communication to prevent reputational damage of banks in times of crisis

“Can you handle the truth?”

Risk communication to prevent reputational damage of banks in times of crisis

Gilles de Jong 10700552 Master thesis

Graduate School of Communication: Corporate Communication Supervisor: Arie den Boon

Abstract

Can risk communication before a crisis minimize reputational damage? To answer this question different kinds of risk communication and crises are tested in an experiment. A sample of 215 respondents was split into 6 conditional groups and was surveyed on the reputation of a fictional bank. The results show significant negative influences on reputational damage. Remarkable is that banks that communicate about risks end up having an even less favorable reputation than banks that do not communicate about risk. This is explained by the fact that risk communication also has a significant negative influence on reputation before the crisis. The results call for a reevaluation of and further research on the topic of risk communication of the financial sector.

Introduction

The financial sector has been involved in frequent financial scandals and questionable practices (KPMG, 2008), and is considered as triggering the latest international financial crises (Bravo et al., 2011). Beside the financial damage these crises do, reputations of banks had also been damaged. Banks took risks and those risks apparently did not have public support, because the crisis caused outrage with the public that suddenly saw its money disappear. When the banks would have had support for their choices and publics would have been aware of the risks perhaps the reputational damage would have been lower. Recently the Boston Consultancy Group published an article about how banks should reserve a certain amount of money for possible sanctions that follow from litigation (Grasshoff, 2014). Appendix A shows recent developments on litigations and the financial sector. The table shows how the amount of litigation has increased the last five years. Grasshoff states that the regulatory environment will change resulting from previous crises and the costs of doing business will increase (2014). Often, litigation and sanctions follow a crisis to prevent that this kind of crisis happens again. Grasshoff believes that banks should count on paying these sanctions. A financial buffer can help with tangible damages and sanctions. However, the reputation of a company is also damaged during a crisis (Sohn & Lariscy, 2012) and money cannot buy a new reputation. Regester and Larkin (2005) point out that the communication part of risk management is totally ignored by top management. Coming from the communication science, this study aims to show that not only building a financial buffer for sanctions is important, but there also might be a change in reputation management in the form of risk communication needed when preparing for possible crises in the financial sector. The literature states that reputation is formed when something is communicated, this creates an image, and

of reputation is described in the literature as a buffer or as having a boomerang effect (Sohn & Lariscy, 2012; Dawar & Pillutla, 2000). In short, a good reputation can help, but, as is explained later, it can also backfire. The effects a good reputation can have are discussed in the theory section. This study proposes risk communication as a way of managing expectations resulting in a smaller boomerang-effect to minimize reputational damage. The main research question that is addressed is:

To what extent does risk communication before a crisis influence the reputational damage of a bank?

To answer this question, a survey is combined with an experiment to test and compare different kinds of risk communication and the effect on reputation in two types of crises. Regarding the structure of the thesis, first theories regarding different concepts is

elaborated on. From the theory four hypotheses are proposed. In the method section the way the experiment is conducted is explained. After this the sample and the dependent measures are depicted. The results section follows in which the hypotheses are tested. The study concludes with implications of the results, limitations and suggestions for future research.

Theory

In the theory section the framework in which this study operates is outlined. First the concepts reputation, crises and response strategies are defined. Then, theory about

expectations, transparency and risk communication is discussed to explain how this study fills the gap that exists in (pre-) crisis management literature. Four hypotheses are

Reputation

In their extensive research in (corporate) reputation Fombrun and Van Riel (1997) have depicted a broad spectrum of literature regarding this hard to define concept. In the inaugural issue of the journal Corporate Reputation Review they mention they “want to encourage a closer examination of corporate reputations” and “stimulate the growth of knowledge about the complex socially constructed environment in which companies operate” (Fombrun & Van Riel, 1997). The purpose of the journal is to combine different fields and literature to research corporate reputation. This suggests that the definition of corporate reputation is constructed by using, among others, sociological, economic, organizational, and strategic literature. Fombrun and Van Riel conclude by suggesting the following definition of corporate reputation:

“A corporate reputation is a collective representation of a firm’s past actions and results that describes the firm’s ability to deliver valued outcomes to multiple stakeholders. It gauges a firm’s relative standing both internally with employees and externally with its stakeholders, in both its competitive and institutional environments.” (Fombrun & Van Riel, 1997)

This definition refers to Hall (1992) when it states that corporate reputation is of great interest to the industry as it is a competitive strategic resource. However, corporate reputation can be seen as “banked goodwill [that] cushions the adverse consequences of bad publicity” (Bennett & Gabriel, 2001, p. 390). The goodwill that Bennett and Gabriel speak of and the stakeholders mentioned by Fombrun and van Riel indicate that

reputation is not something an organization can create and implement in society. It is society that constructs the reputation from the actions and results of a company. When a

company behaves in a way that the public deems positive, the company is perceived as good and obtains a positive reputation. So despite a good reputation is defined as a strategic competitive resource, it cannot be controlled completely by the company. Additionally, this means that a company can have several reputations regarding which stakeholder constructs the reputation based on its own interests, background and relation with the company. Suppliers base their perception of a company on their experiences that may differ from experiences of customers or other stakeholders, resulting in a different reputation. This study is interested in the customers’ perception of a bank and therefore focuses on the customer when measuring the bank’s reputation. Also, apart from what Bennett and Gabriel state, a favorable reputation does not always result in a positive outcome at times of bad publicity. Before these different effects of reputation are discussed something that can damage reputation is elaborated on: a crisis.

Crisis: Cause of Reputational Damage

When a BP oil platform had a big leak in 2010 this situation was framed as an

environmental crisis (Mufson, 2010), when the Lehman Brothers went bankrupt in 2008 this caused the financial crisis (Elliot & Treanor, 2013) and the outbreak of ebola in West Africa was a health crisis (Ebola, 2015). Situations that can be defined as a crisis are manifold. However, a general factor of all these crises is that it does some kind of damage; a crisis always seems to describe a situation in which something is harmed. For organizations Coombs defines a crisis as “[…] a significant threat to operations that can have negative consequences if not handled properly” (Coombs, Crisis management, 2007). What these consequences are, or what is harmed by a crisis can be manifold, but:

“Arguably one of the prime casualties of a corporate crisis is reputation of the firm confronting the crisis. Needless to say, tangible harms caused by a crisis such as property destruction and financial losses pose great threats to the

organization. However, even without these inflicted tangible damages, the crisis can still create a severe blow by changing key stakeholders’ perceptions about the organization.” (Sohn & Lariscy, 2012)

A crisis primarily damages a corporation’s reputation and consequently stakeholders will change how they interact with the corporation (Barton, 2001; Dowling, 2002).

Chibayambuya splits the environment of the bank in an internal and an external

environment (2007). This study uses this dichotomy to qualify crises and risks. Crises and risks coming from the outside of the company (external) and crises and risks inflicted by the doing of the bank itself (internal). The difference between these environments in regard to risks is the responsibility for the risks. With internal risks, the bank takes the risk, with external risks the bank is subjected to the risk.

Coombs mentions that damage is done if the crisis “is not handled properly”. This indicates that companies are able to respond to crises so that the damage can be minimized.

Response strategies

Commonly, in many crises the damage control is done afterwards. Companies can never exactly know if and how a crisis is going to happen and therefore react afterwards. This study, however, aims to show that the perception of the stakeholders can be managed by

communicating about risks in advance to minimize reputational damage. Multiple theories are developed to manage reputation and are generally called response strategies. In the next section, theory on response strategies is depicted. The literature poses several response strategies in which Timothy Coombs has a prominent presence.

Post-crisis communication. Literature about response strategy consists of ways for companies to react on crises. One of these strategies is constructed by Timothy Coombs. Timothy Coombs has developed the Situational Crisis Communication Theory (SCCT). In this theory he describes a way to manage crises and how people will react to the response strategy (Coombs, Protecting organizations, 2007). Also, Coombs and Holladay state that post-crisis communication can help prevent or repair reputational damage (Coombs & Holladay, 2005). Dawar sees the importance of post-crisis communication but adds that reputation also depends on expectations based on previous behavior by a corporation (2000).

Pre-crisis communication. A quantitative study by Avery et al (2010) looks at the three forms (post, during and pre) of crisis communication research in public relations. They found that:

“Most of the articles (n = 25, 38%) focused on the post-crisis, recovery stage (29%). Twelve articles (18%) analyzed both the during- and post-crisis states. Only 3 articles (5%) analyzed prevention and preparation in the pre-crisis stage, and 3 articles (5%) analyzed all three stages together.” (p. 192)

This shows that most of the research focuses on post-crisis stage. And the least, only 5%, discussed pre-crisis communication. Pre-crisis communication seems to be a road less travelled by theorists. Avery et al. conclude that “more attention to the pre-crisis stages” is needed (2010, p. 192). Apart from the fact there is little research addressing the possibilities of pre-crisis communication the research that does address it is always about preparation of evacuation, having a crisis team ready and doing annual tests (Coombs, Crisis management and communication, 2007; Seeger, 2006). This study proposes a perspective on pre-crisis communication strategy based on risk communication and expectancy management. As stated in the introduction, reputation can have multiple effects. These effects are taken into account in developing a strategy to manage reputational damage.

Effects of reputation: Buffer or Boomerang

Reputation can have different kinds of effects on a company during a crisis. Sohn and Lariscy (2012) argue that reputation can have either a buffering or boomerang effect. They use the expectancy violations (EV) theory to explain the so-called ‘boomerang effect’ and the theory of confirmation bias to explain the ‘buffering effect’. The theory of expectancy violations in combination with reputation and crisis theories, as produced by Sohn and Lariscy, forms the basis of this study’s theoretical framework. Expectancy Violation theory (EV) states that when a subject violates expectancy this “functions as a motivational trigger for cognitive processing” (Sohn & Lariscy, 2012, p. 3). This trigger leads to an evaluation of the subject wherein “positive and negative violations

(disconfirmation) lead to more positive and negative interaction outcomes respectively than does conformity to expectations” (Burgoon & LePoire, 1993, p. 69). Also, the relational expectancies can act in the sense that in the case of a violation subjects are

punished even more harshly than subjects with a neutral or bad reputation (Sohn, 2012). So, when a person does something against expectancy this has a greater effect than when he/she acts according the expectancy. When this person has a good reputation he/she will be punished more than when he/she did not have a good reputation. The theory of

expectations violations finds its origins in the writings of Burgoon and LePoire (1993) that explains inter-subjective interactions, but as Sohn and Lariscy explain: “people tend to anthropomorphize organizations and view them as conscious social actors or “whole” rather than social aggregates or collectivities” (2012). Therefore, EV can be applied to organizations and their reputations. The confirmation bias finds its roots in Festinger’s cognitive dissonance theory (1957). This theory states that when people get pieces of information that do not correspond with their previous beliefs, they experience cognitive dissonance. They try to reduce this dissonance “by selectively paying attention to

information that is consistent with previously held beliefs and weighing unequal values on different pieces of information” (Sohn & Lariscy, 2012). In this way they construct a confirmation bias; people confirm incoming information in relationship to their previous beliefs. In short, Sohn and Lariscy state that when having a good reputation in some cases stakeholders can grant companies some room for mistakes (buffering). In other cases companies violate the expectancies of stakeholders in a way that the good reputation ‘boomerangs’ and companies with a good reputation end up having a worse reputation than companies that have a neutral or negative reputation in advance (Sohn & Lariscy, 2012).

Managing expectations. The expectancy theory and the effect of it on corporate reputation imply that expectancies are of importance when managing reputation. When expectancies are realized instead of violated, there is less reputational damage. This

indicates that being honest could protect a company against reputational damage; the public is given honest information so that expectations are set to align with the most realistic outcome of a possible situation. In this study “being honest” is called risk communication to be able to operationalize this abstract concept.

Risk communication

Risk communication in specifically the financial sector is not frequently theorized. However, theory about risk communication in general is as broad as it is diverse. There does not seem to be a consensus on whether it is good or bad and what the motives are for risk communication. Stern and Fineberg (1996) define risk as things or circumstances that are a danger to people or the things they value. Risk commonly is described in terms of probability. For instance, risk is often linked to the chances a thing or circumstance is a danger. Risk communication in that respect is the exchange of risks among institutions and publics (McComas, 2007). In addition to that, risks are never completely objective but tend to be of a subjective nature, because they are perceived through social, cultural and psychological factors (Slovic, 1999). For example, an institution can estimate a risk differently than the publics due to lack of information or the different threats it poses.

Risk communication and transparency. Fombrun and Van Riel argue that companies that portray their corporate identities in a, among others, transparent way have the

strongest reputation (Fombrun & van Riel, 2004). Christensen describes that transparency is that “organizations of all stripes must be ready to yield as well as to put forth all sorts of information about their operations, including the life of their products from “cradle to grave” (Christensen, 2002). So, transparency is described as communicating about

everything you do and what you produce resulting in a stronger reputation. But can transparency be inherently paired with openness, insight and honesty?

Optimum vs. maximum transparency: forward guidance. Risk communication by a bank would be an answer to the demand of the public for more transparency. Issing finds maximum transparency to be impossible due to the impossibility of giving maximum insight and information about all the processes in a bank and the insatiable requests of media and the public for information. Issing opts for an optimum of transparency for central banks instead of a maximum of transparency (2014). The optimum transparency that Issing suggests must be developed on the basis of ‘forward guidance’. Forward guidance is used for reducing uncertainty of the public regarding monetary policy. In developing forward guidance Issing predicts a process that will better the communication of central banks. Forward guidance is transparency about the future with the

accompanying risks (Issing, 2014).

Risk communication as a tool. Issing opts to use forward guidance as a tool to inform the publics and better communication of central banks. Christensen states that companies decide what information to be transparent about and have full control of what window of the business they open for the public to peer through. Christensen concludes that

transparency has become merely a tool to better reputation that does not give direct insight in a company.

Risk communication as a measurement in hypotheses. Even though risk

communication is presumably just a tool to reach transparency, it might not reflect openness and honesty and it is nearly impossible to give maximum transparency, the

literature states that transparency does have an influence on the reputation of a company (Sohn & Lariscy, 2012; Fombrun & van Riel, 2004; Issing, 2014). For that reason risk communication in the form of forward guidance, as a form of transparency, is

hypothesized to influence reputation of banks. Four hypotheses are formed from the theory about risk communication and reputation. The main research question of this study is if reputational damage can be lowered by risk communication. However,

communicating about risk gives insight in the risks the bank is confronted with (and or takes). This scares consumers into thinking more negatively about the bank, therefore the first hypothesis is:

H1. Risk communication negatively influences the reputation of a bank.

When a bank looks responsible for a crisis, anger is evoked, but when it is not responsible sympathy is evoked (Weiner, 2006). Therefore, being perceived as a risk-taker may result in a less favorable reputation. The theory states that there is a difference in an internal crisis and external crisis due to the responsibility for and controllability of the crisis. Hypothesized is that the reputation before the crisis is mediated negatively by being perceived as a “risk-taker” and so hypotheses 2 states:

H2. Being perceived as a “risk-taker” negatively mediates the relationship between risk communication and reputation.

In addition, when a bank is confronted with a crisis due to external factors of the financial system the bank might be held less responsible for a possible crisis resulting in less reputational damage. Therefore, hypothesis 3 states:

H3. Responsibility mediates the relationship between a crisis and reputational damage.

The theory about Expectancy Violation warns for the damage violation of expectancies can do. When people know about the risks that the financial sector has they are aware of the risks the bank is involved in. This may result in lower expectancies resulting in the fact that consumers feel less betrayed or surprised by the crisis. Then, coming from EV, the reputational damage should be less. In other words, communicating about risks takes away expectations so that they cannot be violated anymore. This study therefore

hypothesizes that:

H4. Risk communication has a negative effect on reputational damage.

In figure 1 the conceptual research model is shown. In this model risk communication has a negative influence on pre-crisis reputation and on reputational damage. Also, the

mediating effects of responsibility in the crisis and of being perceived as a risk taker are incorporated in the model. This model is tested for internal and external crises.

Figure 1 Research model Risk communication Reputation: -Pre-crisis -Damage Responsibility “Risk-taker”

The results of the tests of the hypotheses are in the results section. Before that, the method section explains how the study is shaped and what the sample and the manipulations look like and defines the dependent measures.

Method The study

To find an answer to the research question and prove the hypotheses an experiment is conducted in combination with a survey. An experiment will be performed, so that the different causal effects of risk communication and crisis types on the consumers’

perception of a bank can be compared. To measure the reputation of the bank a survey is used. The experiment entails a 2 (external crisis vs. internal crisis cues) × 3 (no risk communication cues vs. external risk communication cues vs. internal risk

communication cues) design. All participants are randomly assigned to one of the six groups representing an experimental condition. The model for the experiment can be found in appendix B.

Sample

The data was collected using a convenience sample. Several social media groups that are founded specifically for collecting respondents are contacted. Also family, friends and acquaintances are contacted. All these people were asked to fill in the survey and also to forward it to people they know. The sample followed from this method consists of 215 respondents with an average age of 28 (SD = 9.6) with the oldest being 67 and youngest three respondents 20 years old. In the sample there were 77 women and 137 men and one person who would rather not say. Regarding the educational level, the largest group

(69.8%) finished a study at a university. The predominant part of the sample had the Dutch nationality.

Manipulations and procedures

A manipulation of certain information is often used in experimental studies that want to measure reputation (Brown & Dacin, 1997; Grunwald & Hempelmann, 2011; Klein & Dawar, 2004; Sohn & Lariscy, 2012). The manipulations were all constructed especially for this study. They consist of texts that respondents were assigned to randomly. For the experiment a fictitious bank (the URI bank) is used to eliminate possible previous attitudes towards existing banks. Because banks are companies that build up long-term relationships with their customers, customers have built up a reputation of their bank. This relationship will not be tested in this study, but it is imaginable that the experience of respondents with their own bank will be reflected in their answers about the URI bank. Nevertheless, this study measures average reputation so possible bias towards

respondents’ own banks and their actions is eliminated. The manipulations in the experiment are communicated as if they are real and the articles are written as if they were copied from actual news outlets. Research by Fombrun and Shanley (1990) shows that the public uses this kind of information to assess companies. By reading information they are able to form a reputation about companies (Sohn & Lariscy, 2012). Following this method, this study created six experimental groups on the basis of a 2 × 3 design. The sort of information a group gets is named risk communication 0, 1 or 2 and crisis 1 or 2. Crises and risks can come in different shapes and measures. Based on the analysis of the position of a bank by Chibayambuya (2007) this study includes two different types of crisis and risks. Risk communication 0 describes no risk and is inspired by the mission statement of an existing Dutch bank. It gives insight in the mission and vision of the

bank. Risk communication 1 describes risks the financial sector poses and all banks are in. This is called external risk. Risk communication 2 describes risks that only the URI bank takes. Issing (2014) claims that it is a huge challenge to describe forecasts of a central bank in a way that is properly understood by the public. For the experiment the texts the respondents receive are made as simple and understandable as possible without losing critical information needed to assess the reputation of the bank. The limitation section describes a disadvantage of the choice of giving not more than the needed information. When the respondents have read the information they fill out a survey regarding the reputation of the URI bank. Then, the respondents receive a fictional newspaper article about a crisis that the URI bank was in. There are two different crises described. Crisis 1 describes an external crisis caused by external factors and crisis 2 describes an internal crisis caused by internal factors. Both these news articles are based on actual news articles. The external crisis manipulation describes the collapse of a big American investment bank that has a negative influence on the URI bank. The internal crisis is a description of how risky investments made by the URI bank caused a crisis at the URI bank. The division of the groups following from the random assignment of the conditions is shown in the table below.

Table 1

6 experimental groups by risk communication and crisis type

Crises

Risk communication External (1) Internal (2)

No risks (0) Group 1 Group 4

External (1) Group 2 Group 5

After the respondents received risk communication they filled out a survey, after this they were informed on one of the two crises, then all groups complete a survey again on what they think about the reputation of the bank and its responsibility in the crisis. To collect responses the online survey tool Qualtrics was used. The respondents were randomly assigned to one of the three risk communication types and one of the two crisis types.

Dependent measures

The aim of this study is to measure the reputation of banks in the eye of the consumer. The reputation of the bank was measured using an aggregated item set from five different scales coming from Sohn and Lariscy (2012) and Hon and Grunig’s organizational-public-relationships (OPR) measures (1999). These scales were initially created to

measure reputation, trust, commitment, satisfaction and loyalty. For this study some items were left out that were not suspected to measure reputation in the eye of the consumer. Some items that characterize the scale are “This bank would offer high quality products and services”, “I have a good feeling about this bank” and “I would feel that this bank treats consumers like me fairly and justly”. The reputation scale consisted of 10 items. Some of the items were inverted before they were included in the reputation

measurement. A principal components analysis was done for these items. The reputation items loaded on 2 components; there were two components with an eigenvalue higher than one. These were 4.461 and 1.515. Also, the scree plot shows a point of inflexion after two components. The first component explained 44,6% and the second component explained 15,2% of the variance. After closer inspection of the items it appears that items that were framed negatively formed one component and items that were framed positive formed the second component. The difference in framing explains the two components; apparently people tend to answer differently to scales that are framed positively versus

negatively. However, this difference does not indicate that there were two different variables measured and therefore the ten items were taken together to measure one variable: pre_rep. To measure the reliability the Cronbach’s alpha was measured for the ten items. Analysis showed the ten items had a Cronbach’s alpha of .84. No items were deleted from the scale. The reputation measured before the crisis is called rep_pre and the reputation measured after the crisis was called rep_post. Even though the scale does not differ, the subject the scale was used to measure was different: the reputation after the crisis. Therefore another PCA is performed to make sure that the scale also measures only one variable when used in the case after the crisis. Factor analysis of the ten items

showed again that there were two components with an eigenvalue higher than 1. The first component had an eigenvalue of 4,594 and the second component had an eigenvalue of 1,841. The first component explained 45,9% and the second 18, 4% of the variance. The scree plot showed a point of inflexion after two components. However, as with the rep_pre scale the difference between the items of the two components was, as with the previous PCA, the negative versus positive framing of the items. Therefore the 10 items were taken together to measure one variable: reputation after the crisis (rep_post). To measure the reliability of this scale the Cronbach’s alpha was measured. The analysis showed an alpha of .83. No items were deleted from the scale. The difference between the two measurements before and after the crisis is called reputational damage (rep_dam). This variable is constructed by subtracting rep_post from rep_pre.

Risk communication is differentiated in internal and external risk. The difference

between the two forms is based on the question of who took the risk; was it the URI bank, or was the risk created by external factors. To see if respondents noticed this difference the item that measured whether respondents found that a bank was a “risk-taker” in

comparison to other banks was added as a manipulation check. The item about responsibility measures if banks were held responsible for the crises. This item was included because it is suspected that responsibility mediates the relationship between risk communication and reputational damage. The scale items are an adoption of Klein and Dawar’s items (2000). All items were measured using a 7-point Likert scale ranging from “very much disagree” to “very much agree”. In appendix C the items are shown that measure the different variables.

Results

For measurement of the hypotheses SPSS v. 22 was used. To measure whether or not risk communication of internal risks and external risks were perceived differently a variable was added to the survey that stated that the bank was in bigger risks than other banks. An independent t-test shows that there were no significant differences between the internal and external risk communications on this item. This means that it does not matter for being perceived as a “risk-taker” if you communicate about internal or external risks. Additionally, there was a significant difference in being perceived as a “risk-taker” between no risk communication and when communicating about internal and external risks. This means that when the URI bank did not communicate about risks it was perceived less as a “risk-taker” than when the URI bank did communicate about risks (internal or external). For this reason, for some hypotheses the difference between external and internal risk communication is ignored. Differences between no risk communication and risk communication in general cannot be ignored.

To find an answer to the research question of this study several hypotheses were

was that risk communication has a negative influence on the reputation of a bank. To measure this an independent sample t-test was done with one group that had received no risk communication and the other respondents who did receive risk communication (internal and external). The test variable was the reputation before the crisis (Rep_pre). Results showed that equal variances could be assumed (F = 5.73, p = .018) and there was a significant difference (t (213) = 6.86, p = .000) between the means of the reputation of the group that received no risk communication (n = 74, M = 4.63, SD = .65) and the group that did receive risk communication (n = 141, M = 3.84, SD = .87). This significant difference indicates that hypothesis 1 is accepted.

The second hypothesis stated: being perceived as a “risk-taker” mediates the relationship between risk communication and reputation. To measure this a regression model was designed. The dependent variable was rep_pre, the independent variable was risk communication and the independent variable was risk-taker in the process macro. The model (R2 = .21, F (2, 212) = 28.19, p < .000) shows that there is an indirect mediating effect (b = -.03, t (2, 212) = -2.070, p = .03, CI [-.0885, -.0008]). Even though the effect is relatively small, the hypothesis is accepted.

The third hypothesis was: responsibility mediates the relationship between the type of crisis and the reputational damage. To measure this a multiple regression model was designed. Reputational damage was the dependent variable, type of crisis was the

independent variable and the variable of responsibility was added as the indirect variable in a process macro. The model (R2 = .10, F = (1, 213) = 11.80, p < .000) shows that there is an indirect mediating effect (b = .16, t (213) = 2.033, p = .041, CI [.0169, .3143]) of

responsibility on the relationship between crisis type and reputational damage. Hypothesis 3 is therefore accepted.

The fourth hypothesis was: risk communication negatively influences the reputational damage after a crisis. To measure this the risk communication was put in a simple regression as an independent variable with reputational damage as the dependent

variable. The model showed that risk communication had a significant negative effect on the reputational damage after a crisis (R2 = .06, F (1, 214) = 13.91, p = .000) of risk communication on reputational damage (b = -.25, p < .000). Additional t-tests showed that equal variances could be assumed (F = 12.26, p = .001) and there was a significant difference in reputational damage (t (213) = 3.64, p = .000) when not communicating about risks (M = .82, SD = .98) and when risk is communicated about (M = .40, SD = .68). This means that the last hypothesis of the study is also accepted.

T-tests show that the greatest reputational damage of almost 1 point on a seven-point scale is caused when there is no risk communication and an internal crisis happens. The least reputational damage is caused when a bank communicates about internal risk and an external crisis happens. There were no significant differences between the external and internal risk communication on reputational damage. This was expected because there was no difference regarding risk communication 1 or 2 and being perceived as a “risk-taker”. Table 2 shows the means of rep_pre, rep_post and rep_dam regarding risk communication and type of crisis. The differences in the table are measured using t-tests with risk communication as a grouping variable. The significance of the difference between no risk communication and risk communication is shown for each DV.

Table 2

Differences in mean reputations in communicating about risks

External crisis Internal crisis

No risks Risks No risks Risks

DV’s n M SD n M SD n M SD n M SD

Pre 32 4.63 .70 76 3.9** .84 42 4.63 .62 65 3.72** .89

Post 32 4.05 .81 76 3.75 .83 42 3.6 .76 65 3.1** .77

Dam 32 .58 .87 76 .20** .53 42 1.00 1.03 65 .64* .76

*Significant at the .05 level **Significant at the .01 level

In figure 2 the slope of the decrease in reputation indicates the reputational damage. From this figure it becomes even clearer that the decrease in reputational damage is almost half the size of the non-risk communicating bank, but still the reputation of the

risk-communicating bank is lowest.

Figure 2

No risk communication vs. risk communication.

3,00 3,20 3,40 3,60 3,80 4,00 4,20 4,40 4,60 4,80

Pre crisis Post crisis

Rep u ta tio n No risk comm. Risk comm.

Conclusion

The financial sector is prone to reputational crises as it is a sector in the center of society with a great responsibility. Everyone has a bank account so when something happens in this sector a large part of the world is influenced. Because of this the financial sector is being watched continuously. Situations in this sector often result in a crisis and

reputational damage. This study suspected a role for risk communication in reputation management. Transparency of risks gives insight in the risks a bank takes and this lowers expectations of the consumer. When expectancies are lower they can be violated less. That way the boomerang effect, as described by Sohn and Lariscy (2012), is minimized resulting in a lower reputational damage after a crisis.

The results of the experiment show that the answer to the research question of this study cannot be without nuance. Hypothesis 4 was accepted; risk communication has a

significant negative influence on the reputational damage. This means that when a bank communicates about risks expectancies seem to be lower so there is a lower damage in reputation when a crisis happens. However, risk communication also has a negative effect on the reputation pre-crisis. When communicating about risks a bank gives insight in the risks and negative side of its actions resulting in a lower reputation. This influence was partly explained by the fact that consumers perceived the bank as a “risk-taker”. In other words, risk communication has an influence on the reputation because when a bank communicates about risks they are perceived as a risk-taker and this lowers reputation. The effect of the difference between internal and external crises on the reputational damage was partially explained by being held responsible for the crisis. In conclusion, the results show that banks that do not communicate about risks end up with a higher

damage due to expectancy violation in the case of no risk communication. In relationship to the theory of Expectancy Violation in particular, this study indicates that there is indeed a role for expectancies in reputation management; manage expectancies to control your reputational damage. Some limitations of the research are mentioned in the next section, afterwards implications of the findings are discussed and how future research should look.

Limitations

A few limitations came up during this study. This study aimed to keep the manipulations and questions as understandable as possible without losing crucial information. In the comments section of the survey a relatively large amount of respondents had shown insecurities about their knowledge of the subject, and if they had understood the questions and articles well. The topic of the financial sector is a difficult one to summarize and communicate in a manner that does not scare people. A practical limitation was the absence of a ‘back’-button. Some respondents indicated that they would have liked to be able to read the information on the bank again. Other respondents noted that there was too little information to have a decent opinion about the subject. Another limitation has to do with the sample. The way data was collected might have given a skewed sample; 69,8% had a university degree and the average age was quite low, 28.

Implications

At this point in time an important implication for communication professionals at banks seems to be that it is not recommended to communicate about risks. The transparency about risks damages the reputation pre-crisis too much to be of any worth to a bank.

However, as stated in the introduction it is becoming a common activity for banks to build in certain buffers to anticipate on coming crises. The decrease in reputational damage indicates that communicating about risks is a way to anticipate on crises. A bank can prepare the consumer for possible threats so that they are not surprised by a crisis and in this way you protect the reputation. The only downside of risk communication is that it damages the reputation. Despite this, this study believes that it is necessary to inform the consumer about the possible risks that the financial sector has for two reasons. The first reason comes forward from this study. When risks are clear reputations are damaged less after a crisis. This is important when looking for a more stable environment for banks and their reputation in which consumer and the financial sector come to trust and understand each other better. The second reason comes forward from the interests of the consumer. The consumer has the right to know about the risks that the financial sector takes or is involved in with their money. Protecting reputation must be put in contrast with

informing the public about risks. So not only does risk communication protect reputations but also it is an ethical, if not obvious, thing to do as a company that is anchored in

society in multiple ways. The question of responsibility for informing about these risks remains and is discussed in the future research section.

Future research

Making the public aware of risks causes transparency with lower reputational damage as an outcome. Responsibility for risk communication on this scale however cannot lie with the banks themselves. As the study shows it damages a bank’s reputation even when they communicate about risks that they and all other banks are in. It is too great of a risk for the reputation of one single bank to communicate about risks. Therefore it is unruly too ask of individual banks to take this responsibility. In the Netherlands companies that give

out loans are obliged to communicate that “loaning money, costs money” and companies that deal stocks: “past performance is no guarantee for the future”. Informing the public about the risks our financial-political system takes seems to be a governmental one. Aim of this study to give insight in risk communication of banks calls for further research on this topic. A few questions that rose were; “Who should be responsible for risk

communication?”, “can an overarching risk communication be designed that informs the public about risks we as a society are in?”, and “how does giving reasons for risks influence reputation?”. Especially this last question is of great importance for future research. When giving the reason for the risks banks take, public support can be created for these risks. When the reason is earning money to pay out bonuses to top management this might have a different influence on the reputation than when it is made clear that these risks are necessary to fuel our economy by making sure new businesses can start and people can get mortgages. On the other hand, one could say that banks have created these circumstances themselves so are responsible for the risk communication and the additional reputational damage. However, it looks like that it might counteract the stability of the relationships between banks and consumers when they get this

responsibility so this study would not advise to force banks to communicate about risks. Again, research in market stability in relationship to risk communication is needed to reinforce these propositions. Also the broader topic of pre-crisis communication needs to be addressed more thoroughly. As the literature review shows only 5% of literature on crisis management addressed how a crisis can be anticipated on in advance. Concept-wise, in this study risk communication was tested in relationship to pre-crisis

management but transparency, consumer relationships and CSR are only a few of the unstudied concepts that can help in preventing the reputational damage a crisis inflicts.

Appendix A

Appendix B Model of experiment

R 1 ____ Risk comm. 0_____Survey on rep._______Crisis 1_____Survey on rep.

R 2____ Risk comm. 1_____Survey on rep._______Crisis 1______Survey on rep.

R 3____ Risk comm. 2_____Survey on rep._______Crisis 1______Survey on rep.

R 4 ____ Risk comm. 0______Survey on rep.______Crisis 2______Survey on rep.

R 5____ Risk comm. 1._____Survey on rep._______Crisis 2______Survey on rep.

Appendix C

Measures of outcome variables. Reputation.

1. “This bank seems competent and effective in providing its products and services.”

2. “This bank would offer high quality products and services.” 3. “I have a good feeling about this bank.”

4. “I admire and respect this bank.”

5. “I feel this bank fails to satisfy the needs of consumers like me.”

6. “Both this bank and consumers like me would benefit from the relationship.” 7. “I feel this bank treats consumers like me fairly and justly.”

8. “This bank cannot be relied on to keep its promises to consumers like me.” 9. “I feel this bank’s behavior is guided by sound banking principles.”

10. “I feel this bank misleads consumers like me.”

Responsibility

1. “I feel that the URI bank could have prevented this incident from occurring.” 2. “In my opinion, the URI bank is responsible for this incident.”

Taking risks

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