M a s t e r t h e s i s U n i v e r s i t y o f A m s t e r d a m
The bigger the better?
A study into the organisational properties that affect
an organisation’s salience on the media agenda.
Draft version Masterthesis By: Rob van Zandvoort 10871667 supervisor: Piet Verhoeven
08
Abstract
The media have a large role in determining the visibility of an organisation since it is the foremost channel through which most people receive information about
organisations. The media have the power to create top of mind awareness regarding certain topics by giving salience to certain themes. This is called the agenda setting power of the media. Through this agenda setting power the media also play a role in building an organisation’s reputation. Through their agenda setting power the media have the power to make certain organisations more salient on the public agenda. Some organisations receive more media attention then others however, what
properties of organisations determine the frequency of their media appearance? The current study set out to research what properties of organisations predict the salience of these organisations on the media agenda of business news. In order to find out which organisations were mentioned most frequently in the news in 2014, a quantitative content analysis of the business section of the New York Times was performed. After the content analysis a correlation analysis and a multiple regression analysis were performed in order to find out which characteristics of organisations influenced their appearance in the media. The dependent variable of the study was the frequency of an organisation’s media appearance, while the independent variables were market value, brand value, reputation, and CSR activities. The correlation analysis showed a significant relationship between the frequency of an organisation’s media appearance, market value and brand value, while no significant relationship was found between frequency, reputation, and CSR activities. The results of the multiple regression analysis showed no significant relationship between the dependent variable and the independent variables.
Introduction
In September 2014 Apple announced a new product, the smartwatch, along with two new iPhones (Chen, 2014). The news went viral in an instant and media were
reporting on the new developments at Apple all over the globe. Apple’s product launches are always watched with quite a lot of interest throughout the world.
However, Apple does not only receive a large amount of media attention during their product launches. “Apple plans to produce smartwatches with FaceTime camera” (Chen, 2015) and “Apple allows for any track to be uploaded into Apple Music” (The, 2015), are only two examples of news articles related to Apple in the beginning of 2015. It seems the media report on almost every move Apple makes. On the other hand there is Lenovo. “I think the Lenovo brand still needs some work,” reads the first news article found. Lenovo is a Chinese organisation that manufactures the same sort of products as Apple and operates in the same market as Apple. Lenovo is the largest PC- and third largest smartphone producer in the world (Curtis, 2015). Lenovo also operates on a global level like Apple. There is however, a large difference in the media attention the two organisations receive. Apple receives media attention for almost every move they make, while Lenovo hardly receives any media attention when they make similar moves. How is it possible that two organisations with similar products and services, in the same market, receive such a different amount of media attention?
There has always been a relationship between the media and organisations. The media can be seen as stakekeepers (Fassin, 2009) who have a duty to inform the public on issues regarding organisations and to exert control over organisations. Since most people get informed about organisational activity through the media, the media have a large role in determining the visibility of an organisation (Pollock & Rindova,
2003). Visibility in the media has a high influence on public opinion and in the building of an organisation’s reputation (Capriotti, 2007).
The media do not only play a large role in determining the visibility of the media, they also play a large role in the legitimation process of an organisation
(Pollock & Rindova, 2003). Some organisations receive such a large amount of media attention they become celebrity firms (Rindova, Pollock & Hayward, 2006). The benefits of being a celebrity firm include loyalty to the organisation and the
willingness to pay higher prices for a celebrity firm’s products (Rindova et al. 2006). This means the amount of media attention given to an organisation influences the organisation’s performance.
There is a difference in the media attention that organisations receive, both in tone and volume. Some organisations make it to the front page almost every week, while others hardly get any media attention at all. The media have the power to create top of mind awareness regarding certain topics. This is called the agenda setting power of the media (McCombs & Shaw, 1972). By giving salience to some topics as opposed to others the media can determine what the public generally thinks about McCombs & Shaw, 1972; McCombs, 2005). Salience consists of the three dimensions attention, prominence and valence (Kiousis, 2004). The media gives salience to certain topics by filtering all available news and presenting a few topics to the public, hereby creating awareness for these topics (Carroll, 2004). By repeating these themes the media has the power to make these themes more apparent on the public’s agenda. Since the public continually sees and hears about the same topic, that topic is perceived to be more important than others.
There has already been extensive research into the power of the media over the public’s agenda (McCombs & Shaw, 1972; McCombs, 2005; Carroll, 2004;
Carroll & McCombs, 2003; Meijer & Kleijnneijenhuis, 2006a; Meijer &
Kleijnneijenhuis, 2006b) and how this affects the reputation of organisations. A study by Capriotti (2007) showed a relationship between large organisations with a good reputation and their visibility in the media however, the study did not look at the individual properties of organisations. This means there is little research into the specific properties of organisations that influence the media’s agenda.
In order to get a better understanding of the media’s agenda, this research will take a look at the different characteristics of an organisation that influence its salience on the media agenda. The current research will focus on the following research question:
RQ: What properties of organisations predict the salience of these organisations on the media agenda of business news?
Answering this question could aid in furthering the understanding of the agenda setting process. Furthermore it could give organisations a broader
understanding of how their actions influence the media’s agenda, and through their agenda setting power, over the public’s agenda. By improving the understanding of this complex relationship organisations could be able to improve their tactics to protect their reputation, and in the long term the success of the organisation.
Theoretical background
The media play an important role in determining the visibility of an organisation. (Pollock & Rindova, 2003). The appearance of an organisation in the media is even better for its recognition by the public than advertisements (Carroll, 2004). The role of
the media is of such importance in building an organisation’s reputation that Deephouse (2000, p. 1097) coined the term “media reputation”. An organisation’s media reputation is the overall evaluation of the organisation in the media. The evaluation of an organisation is a direct result of the different news stories about the organisation that appear in the media (Deephouse, 2000). Whenever an organisation receives negative publicity it affects the perceived reliability, expertise and
attractiveness of the organisation (Renkema & Hoeken, 1998). If an organisation receives positive publicity this aids the organisation in its legitimation towards stakeholders (Pollock & Rindova, 2003; Deephouse, 2000). In short, there is a
relation between the public image of an organisation and its favourability in the media (Carroll, 2004). When an organisation receives a lot of negative publicity it could result in a crisis (Coombs, 2007) and if an organisation receives a lot of positive publicity they could become a ‘celebrity firm’, which reaps economic benefits
(Rindova et al. 2006). These results are in line with research conducted by Meijer and Kleinneijenhuis (2006b) who found that a ‘bandwagon effect’ occurs when an
organisation is often mentioned in the media. The bandwagon effect can affect an organisations reputation in two different ways. The first is that everybody loves a winner, meaning that if an organisation is often portrayed positively in the media that its reputation will be positively influenced as well. On the other hand if an
organisation is often mentioned in the news in a negative way, its reputation will also be influenced in a negative way. In other words, stakeholders hop on the bandwagon in both directions. This does not always mean that whenever an organisation appears in the news in a negative manner that its reputation will diminish. Sometimes the ‘underdog effect’ can take place (Meijer & Kleijnneijenhuis, 2006b). The underdog effect explains that stakeholders sometimes have sympathy for organisations in need,
which could actually win the support of stakeholders and improve their reputation in times of crisis (Meijer & Kleinneijenhuis, 2006b). There are different kinds of positive and negative news related to organisations.
Different kinds of news
Not every article written about an organisation has the same impact. There are different kinds of business news. Since organisations are involved in different kinds of activities a distinction can be made between news on issues, success and failure news and support and criticism news (Meijer & Kleinneijenhuis, 2006a; Meijer & Kleinneijenhuis, 2006b). News on issues describes different issues that an
organisation has to deal with such as investments and profits as well as societal issues such as the environment (Meijer & Kleinneijenhuis, 2006a). Success and failure news describes the situation whenever an organisation gains or loses something. Finally, support and criticism news describes if a company gains support or criticism from another party, for example a competitor, the government or a NGO (Meijer & Kleinneijenhuis, 2006b).
It stands to reason that these different kinds of news have a different effect on the public’s opinion. By selecting and publishing different kinds of news the media has the power to shape the public’s agenda. This is called the agenda setting power of the media (McCombs & Shaw, 1972; McCombs, 2005).
Agenda setting
The main thought of agenda setting theory is that the salience of certain themes in the media influences the salience of these themes on the public agenda (McCombs & Shaw, 1972; McCombs, 2005). Media salience can be divided into three different
dimensions: attention, prominence and valence (Kiousis, 2004). Attention refers to the amount of news coverage a certain theme receives. Prominence is seen as the amount of front-page coverage a certain theme receives. Valence is seen as the ‘tone’ of the article. The three dimensions of attention, prominence and valence together form the first level of agenda setting
A distinction can be made between first-level agenda setting and second-level agenda setting. First-level agenda setting involves certain themes or ‘objects’ getting prominent attention in the media, which causes the public to become more aware of these themes (McCombs & Shaw, 1972; McCombs, 2005).
The media create awareness for certain themes by filtering news issues and presenting them to the public. Some themes get more coverage than others and some themes get no coverage at all. In doing so, the public perceives these themes to be more
important than other themes (Carroll, 2004). The first signs of agenda setting in the media came from research by McCombs and Shaw (1972). In their study during a political campaign in Chapel Hill, they found a high correlation between what voters named as major issues and the amount of attention the media paid to these issues. The issues mentioned were a reflection of the issues reported in the media.
By repeating certain themes the media can make sure these themes become more and more apparent on the public agenda (Carroll & McCombs, 2003). In other words, first-level agenda setting tells the public what to think about and creates top of mind awareness.
Second-level agenda setting is focused on the comprehension of the discussed themes (Carroll & McCombs, 2003). The second-level of agenda setting is more concerned with the salience of the characteristics of the different themes (Carroll & McCombs, 2003). Put differently, the second-level of agenda setting tells the public
how to think about an issue or theme by continuously portraying a certain view on a topic.
In summary, the media has the ability to both bring an issue or theme to the public’s attention as well as the ability to frame the theme or issue. By giving more attention to certain themes, the media can make a value judgement of the different themes discussed. Through first- and second-level agenda setting the media have the power to shape public opinion.
Since organisations conduct business in the public sphere, the media also forms opinions about the way they perform. Does this mean the media’s agenda setting power also applies to organisations?
Agenda setting in business news
Agenda setting describes the transfer of salience from the media to the public agenda. Meijer and Kleinneijenhuis (2006a) conducted research into whether general agenda setting theory is applicable to business news. The results of their study, which consisted of a content analysis combined with a panel survey, indicated that there is indeed evidence for second-level agenda setting in business news. This means that when an organisation is mentioned in combination with an issue, this issue is linked to the organisation and becomes salient in the mind of stakeholders as well. Proof was also found for issue ownership within business news (Meijer & Kleinneijenhuis, 2006a). An organisation claims ownership of an issue when this issue is positively related to the organisation’s core business (Meijer & Kleinneijenhuis, 2006a). For example, environmental news is positive for environmental organisations, whereas it is negative for organisations whose core business hurts the environment, such as oil companies.
To summarize, the media have the power to influence an organisation’s reputation through second-level agenda setting while issue ownership has a positive effect on an organisation’s reputation (Meijer & Kleinneijenhuis, 2006a).
Reputation
An organisation’s reputation is seen as one of the most important intangible assets that determine its success (Hall, 1992). A good reputation has different strategic benefits: it allows a firm to lower costs, increase its prices and it helps to create competitive barriers (Deephouse, 2000). A good reputation is build over the years and can act as a buffer when an organisation faces a crisis (Coombs, 2007). No wonder organisations spend time and resources to build a positive reputation. This brings us to the question: what is reputation exactly?
After a review of 54 often quoted articles, Walker (2010) concludes that reputation is the actual image all stakeholders have of an organisation. In other words, what stakeholders actually think of an organisation (Brown et al., 2006). This image in the mind of stakeholders consists of experiences stakeholders had with the
organisation in the past, combined with expectations of an organisation’s future behaviour (Walker, 2010). Stakeholder’s experiences and expectations are based on the market actions an organisation undertakes (Basdeo et al., 2006). Organisations build their reputation through market actions (Basdeo et al., 2006). Stakeholders perceive an organisation’s market actions and on the basis of these observations stakeholders form an image of the organisation. This image based on the market actions of an organisation is not the sole dimension that influences an organisation’s reputation. Reputation is an intangible asset, so which factors or dimensions influence an organisation’s reputation besides market actions? How is reputation measured?
Measuring reputation
Since reputation is an intangible asset, how can it be measured? This is a question that the reputation institute, founded by Cees van Riel, tried to answer. The reputation institute (2014) developed a tool to measure reputation and suggests that
organisational reputation consists of seven dimensions: products & services,
innovation, workplace, governance, citizenship, leadership and performance. In order for an organisation’s reputation to grow, the organisation has to score well on all seven dimensions. Nowadays it is not enough for an organisation to simply have good products or services, there has to be a thought behind the entire brand (Hatch & Schultz, 2009; Reputation Institute, 2014). This means that not only the products of an organisation need to be satisfactory, it also means an organisation’s entire brand has to have value in the eyes of their stakeholders. In other words, an organisation’s market actions are only one factor of the equation. An organisation has to brand itself in such a way that stakeholders want to be involved with the organisation.
Branding
An organisation’s brand is more than simply its logo or one of its products. An organisation’s brand consists of the different meanings that an organisation’s stakeholders give to its brand (Hatch & Schultz, 2009). The way stakeholders perceive the brand is communicated back to the organisation (Hatch & Schultz, 2009). As discussed above, the image stakeholders have of an organisation is its reputation. According to Hatch and Schultz (2009) organisations and their stakeholders influence each other in the image building process. This means an organisation has to be aware of its surroundings in order to build a solid reputation
and stay open to change. The process of aligning stakeholder images with the actual culture of an organisation is called branding (Hatch & Schultz, 2009). Put differently, branding can be defined as actions that instil a representation of the values and identity of an organisation into the minds of stakeholders (Hatch & Schultz, 2009) Branding is the process of aligning an organisation’s identity with its strategic vision, organisational culture and stakeholder images (Hatch & Schultz, 2009). All seven dimensions described by the reputation institute (2014) fit into this category. Which means that alignment between identity, culture, vision and stakeholder images could improve an organisation’s reputation. How does an organisation reach this state of alignment? A strong brand starts with a strong identity. If an organisation and its employees know what the organisation’s core values are, and act on these values, only then can an organisation become a strong brand. If these values are then
communicated through its products and services, stakeholders will feel the
authenticity of the brand. When stakeholders feel that a brand is authentic they are more likely to do business with the organisation or recommend it to others (Hatch & Schultz, 2009; Reputation Institute, 2014). This authenticity will then be
communicated back to the organisation, thus completing the alignment of the different dimensions. Organisations that brand themselves in such a way that stakeholders like to do business with them should gain more attention.
If an organisation aligns its market actions through the above-mentioned process it is likely that they will get a positive reputation. How do organisations inform stakeholders of their market actions? An organisation can send out press releases however, most stakeholders receive information of an organisation’s market actions through the media. This means, as mentioned before, the media have a big influence on the visibility of an organisation (Coombs, 2007; Pollock & Rindova,
2003). How do organisations cope with the media’s influence? In order to counter the power of the media most organisations have a PR department that handles their relationship with the media.
The relationship between organisations & the media
Through public relations, organisations try to influence the media to write about them in a positive manner. One of the reasons behind this is that information provided by the media is seen as trust worthier than information provided by organisations
themselves (Wang, 2006). The other reason is the agenda setting power of the media. Since the media have the power to create top of mind awareness it could be positive for an organisation’s reputation to appear in the media.
The communication/PR department of organisations are given the task to persuade different kinds of media to report on their organisation in a favourable manner. On the other hand journalists try to remain neutral and see things from their point of view. This tension between journalists and PR professionals results in an on-going frame negotiation (Cornelissen, Carroll & Elving, 2009). Both parties have a different frame of an event based on their own professional identity; which consists of their beliefs, values, and experience; and their organisational identity. In this frame negotiation both parties try to persuade the other of their respective frame
(Cornelissen et al., 2009). One of the tools that organisations use to persuade the media into adapting their frame is CSR communication.
Corporate Social Responsibility (CSR)
CSR is an organisation’s attempt to improve societal wellbeing through the use of an organisation’s resources and practices (Kotler & Lee, 2005). Through CSR an
organisation tries to be a good corporate citizen (Du, Bhattacharya & Sen, 2010). By being a good corporate citizen an organisation can turn stakeholders into brand ambassadors who advocate the organisation. These advocating behaviours are for example: positive word of mouth, willingness to pay more for an organisation’s products, and a resistance against negative news. In the long run an organisation’s CSR activities can lead to an improved reputation (Du et al., 2010). It is however, not entirely clear whether an organisation gets recognition for all its CSR activities. A study by Capriotti (2007) showed that the media portrays organisations as economic rather than social actors in society. An organisation’s size also has an effect on its CSR activities. Larger organisations with more resources are more likely to engage in CSR activities than smaller organisations (Udayasankar, 2008). Lee and Carroll (2011) researched the emergence of CSR in the public sphere over the last 25 years. They studied different kinds of printed media for the appearance of CSR related pieces. Their results showed an increase in CSR reporting over the last 25 years. This could be seen as an increase in the salience of CSR related issues on the agenda of the media.
Research question and hypotheses
To summarise, this study will focus on four different hypotheses.
The media fulfil the role of stakekeepers (Fassin, 2009) who inform the public on the actions of organisations and try to exert some control over the actions of organisations. It could be reasoned that larger organisations will receive more media attention since they have a bigger impact on the public and their stakes. This means that the larger the market value of an organisation is, the bigger the impact this organisation can have on the public sphere. This could cause the media to pay closer
attention to these organisations in their role as stakekeepers. This is in line with research by Capriotta (2007) who found that large organisations with a good reputation and products and services aimed towards mass consumption are more visible in the media. This leads to the following hypothesis:
H1: Organisations with a high market value are more salient on the media agenda than organisations with a low market value.
Organisations have realised their brand is not simply a logo anymore; a brand consists of all the different meanings stakeholders give to the brand (Hatch & Schultz, 2009). Organisations strive to align their core values with their brand in order to be seen as authentic and thrust worthy. If an organisation is seen as authentic and thrust worthy this increases their reputation. Organisations build their reputation, among other factors, through their market actions (Basdeo et al., 2006; Pollock & Rindova, 2003). The media reports on these market actions and in doing so have a large role in building an organisation’s reputation. This could mean that if an organisation has a highly favourable reputation, the media has mentioned this organisation often. The current study uses two different methods to measure reputation. The first is based on the branding strategies of an organisation. This leads to the following hypothesis:
H2: Organisations with a high brand value are more salient on the media agenda than organisations with a low brand value.
The second method focuses on the reputation of organisations. Large organisations with a good reputation are more visible in the media than smaller
organisations without a good reputation (Capriotti, 2007). The study by Capriotti (2007) did, however, not focus on reputation by itself. Reputation could have a positive impact on an organisation’s visibility. This leads to the following hypothesis:
H3: Organisations with a high reputation are more salient on the media agenda than organisations with a low reputation.
CSR strategies have been found to have a positive impact on an organisation’s reputation in the long run (Du et al., 2010). This could mean that through the
improvement of an organisation’s reputation through CSR, the use of CSR strategies could lead to more media reporting on an organisation. Research by Lee and Carroll (2011) showed an increase in the CSR reporting over the last 25 years. As mentioned before, this could be seen as an increase in the salience of CSR related issues on the media’s agenda. This could mean that the more CSR activities an organisation engages in, the more attention the media has for that organisation. This leads to the following hypotheses:
H4: Organisations with a high CSR score are more salient on the media agenda than organisations with a low CSR score.
The above-mentioned hypotheses combined try to answer the main research question of the current study:
RQ: What properties of organisations predict the salience of these organisations on the media agenda of business news?
Method
In order to answer the research question a quantitative content analysis of the business news in the New York Times was conducted (N= 8.282). The New York Times was chosen since it can be seen as a quality newspaper due to its informative content, international outlook, and educated target audience (George & Waldfogel, 2006; Bakker & Scholten, 2007). The dependent variable in the current study was the frequency with which organisations appeared in the media. The independent variables in the current study were market value, brand value, reputation, and CSR score. The period that was chosen for the analysis was 2014.
The current study used data from different lists (The Financial Times 500, The Forbes 100 most valuable brands, The Reputation Institute’s reputation results, and the CSR REPTRAK 2014) in order to determine the values of the independent variables. The values found in the different lists were rather different in nature. The Financial Times 500 and the The Forbes top 100 were all values based on billions of dollars, while the Reputation Results and the CSR REPTRAK were based on a score of 0 to 100. All these values were not normally distributed. In order to analyse these different variables they had to be brought back to a normal distribution. A logarithmic transformation was used for the values of the Financial Times 500 and the Forbes top 100, while the Square Root function was used for the frequencies, the reputation score, and the CSR score.
After these transformations a correlation analysis was performed in order to check whether there was a correlation among the different variables.
The final step in the analysing process was to find out whether there was a relationship between the dependent variable and the independent variables. A multiple
regression analysis was performed in order to check if there was a correlation between the frequency of an organisation in the media and their market value, brand value, reputation, and CSR score.
Materials
In order to find out which articles were published in 2014 the newspaper database LexisNexis was used. LexisNexis is a database that contains newspaper articles from over 1.300 international newspapers. By using the power search function it is possible to find articles from a specific newspaper and from a specific section. The power search function was used to search for all the articles related to companies activity and management. This section was chosen since it contains all articles related to businesses and their performance. The search was narrowed down to the period between January 1 and December 31st, 2014. The search resulted in more than 3000 articles, in which case LexisNexis only shows the first 1000 results.
In order to circumvent these restrictions, and to gain a better insight into the articles published in 2014, the search term was divided into different sub index terms. These index terms were the following: Board & Management changes, Business Climate & Conditions, Business Ethics & Corporate Citizenship, Business operations, Company Locations & Facilities, Company Strategy, Company Structures &
Ownership, Contracts & Bids, Financial Perfomance & Reports, Government Business Support, Management Theory & Practice, Product Manegement, Public Sector Business, Research & Development, and lastly Sales & Selling. These different index terms produced a total list of N=8.282 articles.
The next step consisted of compiling a frequency list in order to find out which organisations were mentioned in these 8.282 articles. AntConc (Anthony, 2014) was used to compile a frequency list of all the words that appeared in the articles over 2014. AntConc is free software that is used for concordancing and text analysis (Anthony, 2014). In order to use AntConc all the articles had to be converted to plain text files. After the convergence of all articles to plain text files AntConc produced a list of 76.673 words that were used in the business section of the New York Times over 2014.
In order to compile a list of organisations the frequency list had to be shortened first. By using the stop list function of AntConc, commonly used words could be filtered out of the list. Words mentioned in the stop list will be filtered out of the frequency list produced by AntConc. After the stop list was applied AntConc produced a list of 76.585 different words. This new list was searched manually for organisations. Eventually this resulted in a top 50 of organisations that were
mentioned in the New York Times over 2014.
Variables
The dependent variable in the current study was the frequency of an organisation appearing in the media. The independent variables in the current study were: market value, brand value, reputation and CSR score.
Market value
The market value of the organisations was based on the Financial Times 500 (Dullforce, 2015). Each year the Financial Times releases a list of the top 500 organisations by market value. This list was used as a reference for the market value
of an organisation. The Financial Times 500 was chosen since it is globally seen as a credible source of information.
Brand value
In order to look at the branding activities of an organisation the Forbes top 100 most valuable brands (Forbes, 2015) was used as a reference. In the current studies the branding strategies of an organisation were measured by their brand value. In other words, how much a brand is worth in dollars. The Forbes list was chosen since Forbes is seen as a reliable source, just like the Financial Times.
Reputation
Since reputation is an intangible asset it is quite hard to give a reputation score to organisations. The reputation institute, founded by Cees van Riel, has created a system to rate an organisations reputation. Their analysis results in a yearly list of the top 50 most reputable organisations in the world (Reputation Institute, 2014a). The current study uses this list as the basis for a reputation score. The RepTrak list was chosen since the Reputation Institute is one of the frontrunners in the field of measuring reputation.
CSR
The reputation institute also produces a list of the CSR score of organisations. This list ranks different organisations on their CSR strategies and gives them a score based on their CSR (Reputation Institute, 2014b). This CSR top 100 was used to determine the CSR score of the organisations ranked in the frequency list.
Statistical Analysis
The analyses of the current study were al performed using the programme IBM statistics 21, also known as SPSS.
The first step in this study was compiling the dataset through a quantitative content analysis in order to find which organisations were mentioned most often in the business section of the New York Times over 2014. The resulting frequency list was used as the basis for the analysis.
It should be noted that the above-mentioned lists did not cover all the
organisations that were on the frequency list. This means some values were missing from the start. Since there were some missing values a multiple imputation was performed in order to analyse the missing data.
The next step in the study was a correlation analysis of the different variables to check whether there was a correlation between the different variables. The results of this analysis showed there was a significant reasonably strong positive correlation between frequency of media appearance and the variables market value and brand value, while no significant relationship was found between frequency and the variables reputation and CSR-score.
Finally, in order to study whether there is a relationship between the independent variable (the frequency of the appearance in the media) and the
dependent variables (market value, brand value, reputation, and CSR score) a multiple regression analysis was performed. The results of the multiple regression analysis showed there was no significant correlation between the frequency in the media and the independent variables market value, brand value, reputation, and CSR score.
This study focused on the question what properties of organisations predicted the salience of these organisations on the media agenda of business news in the NY times?
The current study performed a content analysis of N= 8.282 articles from the business section of the New York Times in 2014. The content analysis resulted in a frequency list of organisations mentioned in the business section of the New York Times over 2014. The frequency list was narrowed down to the top 50 most mentioned organisations. The results showed that Apple was the most frequently mentioned organisation (n= 2428) while Mercedes (n= 404) completed the top 50. The total list can be found in appendix A. This list was compared to 4 other lists: The Financial Times 500 (Dullforce, 2015), the Forbes top 100 most valuable brands (Forbes, 2015), The Reputation Institute’s Reputation results (Reputation institute, 2014a) and the CSR REPTRAK (Reputation institute, 2014b).
Not every organisation that was found during the compilation of the frequency list was mentioned in these lists. The missing organisations were the cause of some missing values in the dataset. In order to properly analyse the data these missing values had to be taken into account. In order to account for these missing values a multiple imputation was performed on the dataset to fill in the missing values.
Analysis
The current study used the frequency list of organisations that appeared in the business section of the New York Times in 2014 as a basis. This resulted in a list of
N= 50 organisations. This frequency list was compared to the Financial Times 500
(n=35) the Forbes top 100 most valuable brands (n=25), the van Riel Reputation results (n=14), and the reputation institute’s CSR REPTRAK (n=16). As mentioned
before, there were some missing values in the dataset since not every organisation found on the frequency list was also present in the other lists. Since the data on the lists used in this study were of a wide variety of values a logarithmic transformation was performed in order to make the values more normally distributed. The
transformed values that were used in the analysis can be found in Table 1.
Table 1: Descriptive statistics of the analysed data.
Variables N M SD Frequency 50 27.48 6.82 Market value 35 25.24 .803 Brand value 25 23.75 .875 Reputation 14 8.64 .122 CSR 16 8.29 .162 The hypotheses
The first hypothesis focused on the relationship between an organisation’s market value and the salience of the organisation on the media agenda of the business news. In order to study this relationship the top 50 most frequently mentioned organisations in 2014 were compared to the Financial Times 500 largest organisations based on market value.
The second hypothesis focused on the relationship between an organisation’s brand value and the salience of the organisation on the media agenda of the business news. Comparing the top 50 most frequently mentioned organisations with the Forbes top 100 most valuable brands tested this hypothesis.
The third hypothesis tested whether there was a correlation between an organisation’s reputation and the salience of the organisation on the media agenda of the business news. This hypothesis was tested using the reputation institute’s
reputation results of 2014 and comparing them to the frequency list.
The fourth and final hypothesis looked at the relationship between an
organisation’s CSR score and its salience on the media agenda of the business news. The final hypothesis was tested using the reputation institute’s CSR REPTRAK (2014).
A Pearson correlation analysis was performed in order to check whether there was a relationship between the different variables in the current research. The results of this correlation analysis will be discussed below.
A significant reasonably strong positive correlation was found between the frequency of an organisation’s media appearance and its market value (r (37) = .37, p = .025). Organisations with a high market value were shown to appear more
frequently in the media.
A significant reasonably strong positive correlation was found between the frequency of an organisation’s media appearance and its brand value (r (37) = .36, p = .041). Organisations with a high brand value were shown to appear more frequently in the media.
No significant correlation was found between the frequency of an organisation’s media appearance and its reputation (r (37) = - .02, p = .922).
Organisations with a high reputation were not shown to appear more frequently in the media.
No significant correlation was found between the frequency of an organisation’s media appearance and its reputation (r (37) = .07, p = .744).
Organisations with a high CSR score were not shown to appear more frequently in the media.
The correlation analysis showed some other interesting results as well. The analysis showed a significant very strong relationship between reputation and CSR score (r (37) = .87, p = .001). Organisations with a high reputation were shown to have a high CSR score as well.
Another interesting result from the correlation analysis was that market value was shown to have a significantly positive relationship to all the other variables except for reputation. A significant strong positive relationship was found between market value and brand value (r (37) = .67, p < .001). Organisations with a high market value were shown to have a high brand value as well. A significant reasonably strong positive relationship was found between market value and CSR score (r (37) = .43, p = .026). Organisations with a high market value were shown to also have a high CSR score. The results from the correlation analysis can be found in table 2.
Table 2: Correlations (r) between Frequency, market value, brand value, reputation, and CSR.
Variable Frequency Market value Brand value Reputation Frequency Market value .37* Brand value .36* .67** Reputation -.02 .28 .10 CSR .07 .43* .26 .87** * p < .05, ** p < .01
The results of the multiple regression analysis showed that the variables entered explained 58% of the variance in frequency (F (3, 9) = 6.56, p = 0.012). This means the model was found to be significant. The market value of an organisation was not shown to be a significant predictor of the frequency of an organisation’s media appearance (β = .47, p = .170), neither were brand value (β = .42, p = .220), reputation (β = -.18, p = .380), and CSR score (β = -.18, p = .380). This means all the hypotheses are rejected. Table 3 shows the results of the analysis.
Table 3: Regression analysis for the variables that predict the frequency of an organisation appearing in the media
Variable B SE B β Market value 6.96 4.67 .47 Brand value 5.09 3.86 .42 Reputation -11.98 12.97 -.18 CSR -11.98 12.97 -.18 R
²
.58* F 6.56 * p < .0,05Conclusion & Discussion
The current study set out to investigate the relationship between different
characteristics of organisations and their appearance on the media agenda. The current study was one of the first to look at the characteristics of organisations that appear on the media’s agenda in this specific manner. The focus of this study was on the
these organisations on the media agenda of business news in the NY times? In order to answer this research question four hypotheses were developed. These hypotheses will be discussed below.
H1 Organisations with a high market value are more salient on the media agenda
than organisations with a low market value.
The results of the correlation analysis showed a significant reasonably strong positive relationship between an organisation’s market value and the frequency of an organisation’s media appearance. However, the results of the multiple regression analysis showed there was no significant relationship between an organisation’s market value and its salience on the media agenda. The results of the analyses lead to the rejection of H1. This means even though a relationship was found between organisations with a high market value and the frequency of their appearance in the media, market value cannot be seen as a predictor for the frequency of an
organisation’s media appearance. This could mean the media are not influenced by the size of an organisation in their role as stake keepers (Fassin, 2009). This result is not in line with the study of Capriotti (2007), who found that large organisations were more visible in the media. The results of this study could indicate that an
organisation’s actions speak louder than its status in terms of media coverage.
The current study used the Financial Times 500 as a reference for the market value of organisations. The list did however not contain information on all the organisations that were mentioned on the frequency list. This resulted in some missing values that had to be filled in through a multiple imputation. Since there is no apparent logic to these values this could have been a factor that influenced the current results. Future research should try to find more conclusive data in order to get more reliable results.
The timeframe of the current study sadly did not allow such an elaborate method of data collection.
H2 Organisations with a high brand value are more salient on the media agenda than
organisations with a low brand value.
The results of the correlation analysis showed a relationship between brand value and the frequency of an organisation’s media appearance, however the results of the multiple regression analysis were not significant. This means there is a
relationship between brand value and the frequency of an organisation’s media
appearance however, brand value cannot be seen as a predictor for the frequency of an organisation’s media appearance. This means the second hypothesis is rejected. The results show that even though branding strategies help organisations to be seen as authentic and trustworthy (Basdeo et al., 2006; Hatch & Schultz, 2009; Rindova & Pollock, 2009), branding strategies do not help in gaining more media visibility. The correlation analysis did show a relationship between the frequency of an
organisation’s media appearance and its brand value. Future research could delve more deeply into this relationship between brand value and media visibility. As mentioned above this result could be explained due to the fact there were some missing values. Another explanation could be that the media does not necessarily focus on brands as much as it does on the actions of an organisation.
H3: Organisations with a high reputation are more salient on the media agenda than
organisations with a low reputation.
The third hypothesis focused on the relationship between an organisation’s reputation and its salience on the agenda of the business news.
The correlation analysis did not show a significant relationship between reputation and the frequency of an organisation’s media appearance. The results of the multiple regression analysis also did not show a significant relationship between reputation and frequency of media appearance. This means the third hypothesis is also rejected. These results are in contrast to the study performed by Capriotti (2007), who found that large organisations with a good reputation were more visible in the media. It seems that even though the media plays an important role in determining the visibility (Pollock & Rindova, 2003) and building the reputation (Deephouse, 2000) of an organisation, the media are not influenced by an organisation’s reputation. This means the media will not mention an organisation more often if they have a good reputation. Once again this could be the result of the missing values in the current study. The relationship between reputation and appearance on the media agenda seems to be more complicated than was hypothesised in the current study. In retrospective this is not very strange. Whenever an organisation goes through a crisis there is a high chance of appearing on the media agenda. Whenever an organisation goes through a crisis its reputation is diminished. This means that an organisation with a low
reputation can appear on the media’s agenda quite frequently. Future research should focus on a more detailed content analysis.
H4: Organisations with a high CSR score are more salient on the media agenda than
organisations with a low CSR score.
The fourth and final hypothesis focused on the relationship between an organisation’s CSR score and its appearance on the agenda of the business news.
The correlation analysis did not show a significant relationship between CSR and media visibility. The results of the multiple regression analysis did not show a
significant correlation between CSR rating and frequency of media appearance either. This means the fourth hypothesis is rejected as well. These results could be seen as strange, since the study by Lee and Carroll (2011) showed an increase in CSR
reporting over the last 25 years. The results of the current study could indicate that the media do not focus on the organisation behind the CSR strategies as much as they focus on the good it does. Another reason for this result could be that organisations are not always accredited for their CSR activities, which is in line with research by Capriotti (2007). This could mean organisations are not directly mentioned in the media with regard to their CSR actions. Once again, a reason for this result could also be the limited data in the used lists.
Other results
The results from the correlation analysis showed a significant relationship between market value, brand value and CSR activities. These results could be explained to the fact that large organisations have more resources to influence their branding and CSR strategies (Udayasankar, 2008). Future research could investigate this relationship more thoroughly.
A significant positive relationship was also found between reputation and CSR strategies. These results are in line with the study by Du (et al., 2010) who found that CSR strategies have a positive impact on an organisation’s reputation. Another reason for this result could be that the reputation institute measured both reputation and CSR scores.
Implications and Future Research
setting theory in business news. Although all of the hypotheses were rejected and no clear answer could be found to the research question, solace can be found in a famous quote among researchers: “no result is a result as well”. The results of the current study are welcome news for smaller organisations, since there is no indication of a significant relationship between market value and media appearance. This could theoretically mean that smaller organisations have the same chances as large organisations to appear in the media. This might especially be good news for PR organisations and their strategies to gain free publicity.
Future research should focus on a more in depth analysis of the tone of voice of the articles the organisations were mentioned in. It would be interesting to see whether an organisation is mentioned positively or negatively and which
organisations are mentioned most frequently in each way. This could give more insight into the impact the appearance on the media agenda has on an organisations reputation and overall performance. As mentioned before, the current study had some missing data values. Future research should try to obtain a more complete dataset in order to perform a more complete analysis of the media agenda. More organisations could also be used in future research since the current study only focused on the 50 most frequently mentioned organisations.
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Appendix A: Frequency list of the New York Times Business section
2014
Positie freq lijst aantal x genoemd Organisatie/woord
285 2428 apple
385 1947 ford
494 1547 reuters 542 1430 fed 602 1325 amazon 618 1293 microsoft 620 1287 facebook 678 1189 twitter 683 1179 chrysler 750 1088 toyota 868 957 samsung 905 918 jpmorgan 934 892 bloomberg 945 886 century 1024 830 honda 1079 793 goldman 1083 790 alibaba 1091 780 walmart 1100 773 citigroup 1123 753 ibm 1193 702 warner 1237 683 bp 1266 667 bmw 1271 662 chevrolet 1322 632 barclays 1355 616 deutsche 1455 571 tesla
1489 556 swiss 1509 549 williams 1515 547 volkswagen 1576 521 gap 1603 514 mcdonald 1658 493 comcast 1671 489 disney 1717 474 uber 1747 466 seat 1813 449 nissan 1838 442 harvard 1899 424 herbalife 1935 416 youtube 1943 411 fiat 1947 409 blackberry 1970 404 yahoo 1972 403 cadillac 1998 395 intel 2040 385 sony 2047 383 hyundai 2057 380 ubs 2078 375 mercedes
Appendix B Financial Times 500 Market value 2014
Global rank 2014 Company Market value $m2 Exxon Mobil 422.098,3 3 Microsoft 340.216,8 4 Google 313.003,9
5 Berkshire Hathaway 308.090,6 6 Johnson & Johnson 277.826,2 7 Wells Fargo 261.217,5
8 General Electric 259.547,3 9 Roche 258.542,1
10 Wal-Mart Stores 246.805,7 11 Nestle 242.954,9
12 Royal Dutch Shell 238.993,5 13 JP Morgan Chase 229.897,9 14 Novartis 229.770,4
15 Chevron 227.014,7 16 PetroChina 220.893,7
17 Procter & Gamble 218.539,4 18 Samsung Electronics 208.518,6 19 Pfizer 205.359,9
20 IBM 200.447,6
21 Industrial & Commercial Bank of China 200.179,4 22 Verizon Communications 196.939,7 23 Toyota Motor 195.057,4 24 HSBC 191.251,3 25 China Mobile 184.573,4 26 AT&T 182.604,1 27 Oracle 182.412,9 28 Bank of America 181.086,3
29 China Construction Bank 174.465,7 30 BHP Billiton 173.490,4 31 Coca-Cola 170.331,6 32 Anheuser-Busch InBev 168.640,3 33 Merck 166.938,9 34 Total 155.984,8 35 Amazon.com 154.480,4 36 BP 147.771,1 37 Citigroup 144.627,3
38 Agricultural Bank of China 141.661,8 39 Walt Disney 140.287,3
40 Sanofi 138.132,8
41 Qualcomm 133.358,4
42 Tencent Holdings 129.640,5
43 Philip Morris International 129.387,9 44 Comcast 129.376,1 45 GlaxoSmithKline 128.915,8 46 Intel 128.347,1 47 PepsiCo 128.267,9 48 Schlumberger 127.377,9 49 Facebook 119.943,2 50 Volkswagen 119.119,8
52 Bank of China 118.616,7 53 Siemens 118.567,5 54 Ambev 117.679,2
55 Commonwealth Bank of Australia 115.695,0 56 Cisco Systems 115.465,9 57 Bayer 112.126,2 58 Banco Santander 110.278,0 59 Home Depot 109.306,3 60 Gilead Sciences 108.972,2 61 Visa 108.859,5 62 United Technologies 107.077,3
63 British American Tobacco 104.634,8 64 Rio Tinto 104.308,8
65 Basf 102.105,5
66 Daimler 101.624,0
67 Taiwan Semiconductor Manufacturing 100.899,1 68 Novo Nordisk 100.804,4 69 SAP 99.642,7 70 Westpac Banking 99.587,5 71 L'Oreal 99.197,5 72 Vodafone Group 97.106,8 73 McDonald's 97.038,0 74 Sinopec 96.667,8 75 BNP Paribas 96.085,6 76 American Express 95.396,9 77 Royal Bank Canada 95.246,2 78 Saudi Basic Industries 93.991,1 79 Inditex 93.555,3 80 Amgen 93.122,5 81 Boeing 92.495,8 82 LVMH 92.323,7 83 Gazprom 91.289,4 84 Eni 91.209,2 85 Softbank 90.937,0 86 Statoil 90.007,9 87 3M 89.238,2 88 CVS Caremark 88.972,4
89 Lloyds Banking Group 88.822,7 90 Petrobras 88.517,8
91 Toronto-Dominion Bank 86.509,0 92 ConocoPhillips 86.358,3
93 Bristol Myers Squibb 86.079,7 94 Union Pacific 85.396,1 95 Mastercard 85.253,9 96 ANZ Banking 84.083,1 97 Abbvie 82.036,9 98 AstraZeneca 81.492,6 99 BMW 81.192,2 100 UnitedHealth Group 81.103,8
102 UBS 79.420,6
103 US Bancorp 78.007,5
104 Mitsubishi UFJ Financial 77.980,8 105 Diageo 77.907,2
106 Allianz 77.544,3
107 National Australia Bank 77.357,9 108 Occidental Petroleum 75.289,4 109 Altria Group 74.592,4 110 Goldman Sachs 74.183,4 111 EDF 73.611,6 112 Itau Unibanco 73.339,3 113 Honeywell International 72.537,6
114 American International Group 72.466,6 115 Biogen Idec 72.305,7
116 Deutsche Telekom 72.175,4 117 Telefonica 72.038,1
118 Vale 71.839,3 119 eBay 71.516,7
120 Twenty-First Century Fox 71.469,8 121 BBVA 70.883,8
122 Rosneft 70.737,1
123 Bank of Nova Scotia 70.477,3 124 Viacom 70.105,9
125 Tata Consultancy Services 69.961,2 126 United Parcel Service 69.094,1
127 NTT DoCoMo 69.002,4
128 Glencore Xstrata 68.359,3 129 CNOOC 67.111,8
130 GDF Suez 66.043,0
131 China Life Insurance 66.032,0 132 Eli Lilly 65.908,8
133 Las Vegas Sands 65.639,1 134 Honda Motor 63.919,3 135 Barclays 63.659,6 136 BG Group 63.518,6 137 Caterpillar 63.380,4 138 Walgreen 63.014,5 139 Japan Tobacco 62.921,8 140 Axa 62.904,9
141 Hennes & Mauritz 62.179,7 142 Priceline.com 62.147,9
143 Nippon Telegraph & Telephone 62.019,7 144 Medtronic 61.590,1
145 E I Du Pont de Nemours 61.482,1 146 Morgan Stanley 61.481,0
147 Hewlett-Packard 61.326,1 148 Ford Motor 60.553,9
149 Sumitomo Mitsui Financial 60.538,6 150 Hyundai Motor 60.521,0
152 Sands China 60.242,1 153 ABB 59.746,5 154 Monsanto 59.718,9 155 Metlife 59.492,2 156 Colgate-Palmolive 59.463,6 157 Abbott Laboratories 59.423,6 158 Dow Chemical 58.768,8 159 Mondelez International 58.768,7 160 Reckitt Benckiser 58.682,6 161 Telstra 58.586,2 162 Time Warner 58.317,5 163 Express Scripts 58.233,2 164 Nordea Bank 57.342,9 165 AIA Group 57.137,6 166 Celgene 56.680,4 167 Hutchison Whampoa 56.445,2 168 Airbus 56.144,2 169 EMC 55.570,9 170 Starbucks 55.467,9 171 Intesa Sanpaolo 55.228,0 172 Ping An Insurance 54.855,5 173 General Motors 54.720,5 174 ING 54.397,2 175 Prudential 54.151,0 176 EOG Resources 53.579,5 177 Sberbank of Russia 53.397,0 178 Enel 53.239,7 179 Unicredit 52.977,6 180 Blackrock 52.678,1 181 Danaher 52.386,1 182 Nike 52.257,9 183 Lockheed Martin 52.117,4 184 KDDI 52.048,8 185 A P Moller - Maersk 51.729,3 186 Credit Suisse Group 51.660,0
187 Simon Property Group 51.537,1 188 Suncor Energy 51.462,2 189 Schneider Electric 51.365,9 190 National Grid 51.121,1 191 Texas Instruments 51.014,9 192 Standard Chartered 50.727,0 193 Accenture 50.468,3 194 Reliance Industries 50.367,8 195 Duke Energy 50.349,3 196 Halliburton 50.107,5 197 BT Group 50.100,0 198 Richemont 49.875,6 199 Lowe's Companies 49.818,1 200 Societe Generale 49.212,0
202 Teva Pharmaceutical 48.971,5
203 LyondellBasell Industries 48.292,1 204 Continental 48.183,0
205 Mizuho Financial Group 48.028,6 206 Lukoil 47.443,9
207 Thermo Fisher Scientific 47.109,1 208 ITC 46.988,6
209 Emerson Electric 46.959,4
210 Bank of Communications 46.744,8 211 Canadian National Railway 46.521,6 212 China Shenhua Energy 46.493,2 213 PNC Financial Services 46.463,6 214 Singapore Telecom 46.276,0
215 Naspers 45.926,4 216 AMX 45.783,3
217 Deutsche Bank 45.764,3
218 Zurich Financial Services 45.745,6 219 Oil & Natural Gas 45.655,0
220 Henkel 45.536,7
221 Deutsche Post 45.248,1 222 Vinci 44.865,7
223 Danone 44.641,9 224 Iberdrola 44.588,2
225 Capital One Financial 44.193,9
226 Valeant Pharmaceuticals International 44.125,8 227 Ericsson 43.763,5 228 Phillips 66 43.708,3 229 Wesfarmers 43.646,2 230 Anadarko Petroleum 43.403,6 231 Bank of Montreal 43.202,4 232 TJX Cos 43.134,2 233 Jardine Matheson 42.931,6 234 Denso 42.475,8 235 Air Liquide 42.409,7 236 Fanuc 42.338,6
237 Canadian Natural Resources 41.868,8 238 Walmex 41.799,1 239 Kimberly-Clark 41.749,9 240 Nextera Energy 41.631,3 241 Woolworths 41.538,2 242 Asml Holding 41.402,0 243 Canon 41.326,7 244 Dominion Resources 41.288,1
245 China Merchants Bank 40.900,2 246 McKesson 40.633,5
247 Nissan Motor 40.385,0
248 Jardine Strategic 40.174,3 249 Heineken 40.106,1
252 Baxter International 39.802,1 253 Imperial Oil 39.533,2 254 Credit Agricole 39.459,7 255 Munich Re 39.340,7 256 Fedex 39.173,6 257 Orange 39.136,4 258 E On 39.034,5 259 Liberty Global 39.024,3 260 Prudential Financial 39.021,9 261 Southern 39.016,1 262 DirecTV 38.970,6 263 Imperial Tobacco 38.824,2 264 Fast Retailing 38.557,7 265 Praxair 38.432,5 266 Cheung Kong 38.398,5 267 MTN Group 38.368,4 268 Target 38.313,4
269 Time Warner Cable 38.060,7 270 Enbridge 37.829,9
271 Takeda Pharmaceutical 37.511,4 272 General Dynamics 37.478,0
273 Vivendi 37.332,0
274 Automatic Data Processing 37.225,8 275 Linde 37.215,6
276 Hon Hai Precision Industry 37.205,7 277 Allergan 37.119,4
278 Galaxy Entertainment 36.765,8 279 Precision Castparts 36.707,8
280 Associated British Foods 36.704,7 281 Sasol 36.433,7
282 Yahoo 36.237,2 283 Sprint 36.170,7
284 Qatar National Bank 36.050,6 285 Actavis 35.919,7 286 Hitachi 35.763,4 287 Eaton 35.754,2 288 Manulife Financial 35.715,1 289 Charles Schwab 35.541,5 290 Anglo American 35.482,8 291 Syngenta 35.243,8 292 Saudi Telecom 35.196,7 293 Christian Dior 35.002,1 294 Atlas Copco 34.836,1 295 Salesforce.com 34.830,6 296 Generali 34.717,9 297 Swiss RE 34.391,8
298 Freeport-McMoran Copper & Gold 34.340,5 299 CIBC 34.334,4
302 Illinois Tool Works 34.146,5 303 Seven & I Holding 33.947,9 304 Volvo 33.866,1
305 Repsol 33.817,2
306 Swatch Group 33.735,8 307 Rolls-Royce 33.667,6
308 China Minsheng Banking 33.621,6 309 Telenor 33.615,3 310 Deere 33.568,9 311 Saint Gobain 33.552,4 312 BCE 33.518,2 313 Reed Elsevier 33.511,3 314 Kinder Morgan 33.486,7 315 Kraft Foods Group 33.448,4
316 National Oilwell Varco 33.369,3 317 Ace 33.349,3
318 Yum! Brands 33.317,9 319 Covidien 33.170,3
320 Sun Hung Kai Properties 33.122,3 321 Mitsubishi Estate 33.023,3 322 Philips Electronics 32.967,0 323 Apache 32.742,4 324 Adobe Systems 32.720,8 325 CaixaBank 32.685,9 326 TeliaSonera 32.591,4 327 Ecolab 32.492,6
328 Royal Bank of Scotland 32.360,7 329 American Tower 32.340,1
330 China Citic Bank 32.332,8 331 Transcanada 32.214,8 332 Surgutneftegas31.864,7 333 Swisscom 31.843,5 334 General Mills 31.843,0 335 Femsa 31.652,7 336 DBS Group 31.511,6 337 Johnson Controls 31.421,8 338 Infosys Technologies 31.408,6 339 China Unicom 31.274,7 340 Svenska Handelsbanken 31.255,6 341 CSL 31.178,8 342 Raytheon 31.070,3 343 Industries Qatar 30.970,7 344 Pernod-Ricard 30.911,2
345 Potash Corporation of Saskatchewan 30.853,7 346 Stryker 30.811,9
347 Mitsubishi 30.762,9
348 Cognizant Technology Solutions 30.735,6 349 Hang Seng Bank 30.438,5
352 Boc Hong Kong 30.122,1 353 Norfolk Southern 30.099,2 354 Alexion Pharmaceuticals 30.095,9 355 HDFC Bank 30.079,3 356 State Street 30.020,2 357 Travelers Cos. 29.983,0 358 Al Rajhi Bank 29.897,2 359 Woodside Petroleum 29.796,9 360 SEB 29.737,7 361 Husky Energy 29.547,3
362 Delta Air Lines 29.431,0 363 Carnival 29.418,9
364 Regeneron Pharmaceuticals 29.399,8 365 East Japan Railway 29.172,9
366 Industrial Bank 29.169,8
367 Shanghai Pudong Development Bank 29.159,1 368 CSX 29.126,0 369 Public Storage 29.031,6 370 Sampo 28.996,4 371 Corning 28.957,5 372 Banco Brasil 28.952,7 373 Safran 28.904,9 374 Bridgestone 28.896,9 375 Shire 28.866,9 376 Hyundai Mobis 28.806,7 377 Exelon 28.775,0 378 Renault 28.750,3 379 Aflac 28.669,5 380 Reynolds American 28.658,6 381 BB&T 28.569,7
382 Archer Daniels Midland 28.453,6 383 Baker Hughes 28.360,4 384 DNB 28.320,8 385 Valero Energy 28.286,7 386 Gas Natural 28.149,1 387 Wellpoint 28.118,8 388 Danske Bank 28.115,3 389 Carrefour 28.033,7 390 Yahoo Japan 27.980,8 391 Panasonic 27.940,3 392 Thomson Reuters 27.929,9 393 Nokia 27.820,3 394 Centrica 27.810,0 395 Williams Cos. 27.773,6 396 Luxottica 27.636,6
397 Great West Lifeco 27.582,7 398 WPP 27.540,9
399 Investor 27.486,1 400 Twitter 27.459,6
