HETEROGENEITY IN UNITED STATES
BASED BANKS
Erwin Plantinga
Rijksuniversiteit Groningen Management and Organisation
International Business and Management
29 August 2006
ABSTRACT
This paper explores heterogeneity in United States banks. The fundamental objective is to criticise the existing believes about team heterogeneity as well as focusing from a new perspective. For 30 United States banks heterogeneity in the variables gender, nationality, level of education, and the way of recruitment was correlated to performance, as well as an overall score for heterogeneity. Performance was measured by return on assets as well as market value. Results only partially conformed the hypotheses.
Gender correlates to return on assets, and heterogeneity in nationality positively influenced market value. The overall score on heterogeneity (the average of the four individual scores on heterogeneity) did not correlate with any performance measure. Only when two variables (level of education and the way of recruitment) were excluded of the total heterogeneity score there was a positive significant relation when performance was measured as market value. Overall, this paper provides a new perspective for looking at the upper echelons, by showing that 1 and 1 does not always equal 2.
TABLE OF CONTENTS
INTRODUCTION 4 LITERATURE REVIEW AND RESEARCH QUESTION 5
The single leader 5
Team heterogeneity 6
HYPOTHESES 10
Heterogeneity 10
Gender 11
The nationality mix 13
Level of formal education 14
Inside versus outside 16
METHODOLOGY 17
Sample 17
Dependent variables 18
Independent variables 18
RESULTS 20
DISCUSSION 23 REFERENCES 29 APPENDICES 33
Appendix A: Conceptual model 34
Appendix B: Categories 35
INTRODUCTION
Since the 1980s many papers have been written about top management teams. Research in the ‘upper echelon perspective’, (Hambrick and Mason, 1984) focuses on the background of top managers and the characteristics of the team as a whole. It is argued that organisational outcomes are linked to the values and cognitive bases of powerful actors in the organisation. (Hambrick and Mason, 1984, p. 193) So the background of people has formed the way people think and act, and therefore the managers make certain choices. And these choices have a direct influence on the organisational outcomes.
After Hambrick and Mason’s study a lot of variables were the main target of research. Most of these variables are tested separately and these have proven to be relevant. Problem here is that the interaction between different variables, which was the initial proposal of Hambrick and Mason, is missing. Hambrick, Cho, and Chen (1996) are one of the first to come up with heterogeneity in top management teams as subject of study. They tried to find a relation between diversity and organisational outcomes by combining three types of heterogeneity (functional heterogeneity, education curriculum heterogeneity, and company tenure heterogeneity). They overlook the possibility that one homogeneous variable (all managers have the same age) can balance one heterogeneous variable (all managers went to a different university).
In this paper a framework will be used which tests the influence of four individual variables on performance, as well as one score on heterogeneity. The focus in the empirical research lies on 30 United States based banks. By using this framework it can be seen in what way heterogeneity of a top management team really has an influence on organisational outcomes. These organisational outcomes are mostly measured by the profit of a company. In this research the focus will also be on profit. The choice for United States based companies lies in the desire to come up with comparable results, to precisely measure the influence of heterogeneity.
To come to the research question it is necessary to explore the consisting literature. This literature review provides the history of the upper echelon perspective and the reason why this topic needs to be researched. After that hypotheses will be formulated, supported by literature as well. Then the methodology will be described, explaining how the hypotheses will be tested. The empirical results will be explained in the results-section, followed by a discussion how the results can be interpreted.
LITERATURE REVIEW AND RESEARCH QUESTION The single leader
When you look for papers written about heterogeneity in top management teams, you will notice that a lot of papers have the names Hambrick and Mason in their first sentence. Their research in the ‘upper echelon perspective’ (Hambrick and Mason, 1984) focuses on the background of top managers and the characteristics of the team as a whole, and this way of thinking was new for that time. It is argued that organisational outcomes are linked to the values and cognitive bases of powerful actors in the organisation (page 193). The background of people (e.g. age, socio- economic background) has formed the way people think and act, and therefore managers make certain choices. These choices, is argued, have a direct influence on the organisational outcomes.
This way of reasoning started as a counterattack on the assumption of various studies that large organisations can not be controlled. Hambrick and Mason mention the study of Hall (1977) in particular. Hall claims that the organisation does not need to be controlled by a leader or a management team. For the most part organisations need maintenance, and only in times of uncertainty and change the leader can exercise its control. The leader can only react and intervene and has no power to steer the organisation.
In the article by Lubatkin and Chung (1985) this school of thought is called the “small man” notion. In this school, authors claim, just like Hall, that an individual does not make a difference. The foundation of this school is the paper by Lieberson and O’Connor (1972). They empirically discovered that the industry and the company have more influence on organisational outcomes than leadership.
And Lieberson and O’Connor do not stand alone in their beliefs. Even one of the most influential person in strategic management, Henry Mintzberg, claims in his contribution to the book of Hofer and Schendel (1979) that the leader has no power to adjust the organisational outcomes.
This belief in an independently operating organisation causes some criticism.
The empirical results of Lieberson and O’Connor can easily be rejected by looking at the variables they used. Hambrick and Mason (1984) are right when they state that dollar sales and earnings are ‘primarily indicators of the firm’s size and the type of
industry it is in’ (page 194). And because evidence of the powerless leader remains low and unclear, a new school arises: the school of the “great man” (Lubatkin and Chung, 1985). Main difference is that in these studies the topic of research is the CEO, and then especially the successful CEOs.
Later in the career of Mintzberg, he still criticises this way of thinking. In Strategy Safari (1998) he questions (together with Lampel and Ahlstrand) the vision of the magazine Fortune. Fortune is a magazine that still fits in the school of the
“great man”. An example is in the Fortune of April 28, 1997, the article by Teitelbaum. The CEO of Exxon, Lee Raymond, ‘has consistently delivered handsome results to shareholders’ (135), while he sometimes ‘could practically run the company on automatic pilot’ (140).
One influential paper focusing on a single, all deciding person is written by Weiner and Mahoney (1981). They counterattacked the paper of Lieberson and O’Connor (1972) by controlling the research much more. By identifying specific environmental, organisational and leadership variables they tried to adjust the results of Lieberson and O’Connor. This resulted in a contradictory result, explaining that leadership did influence firm’s performance in a significant amount.
Team heterogeneity
Due to these opposing schools of thought it was hard to tell what was right.
Like always when there are contradictory results, there had to be some factors that were overlooked. The answer came by the article of Hambrick and Mason in 1984.
Their article was based on the notion that leadership did make a difference, but that this was not a one-player game. The entire top management team decided the goal of the company and the strategies to reach this goal.
The innovativeness of their article lies in the combination of choosing the top management team as the unit of analysis, in stead of the single leader, and the influence of demographic characteristics on choices of managers. This last part of their hypothesis had been in business research for a long time. Numerous papers empirically tested the relation between the background of managers and the outcomes of their decisions. These relationships differ in nature. Fiedler in 1965 already states that ‘[t]he success or failure of an organization depends on the quality of its management.’ (115) He claims that it is necessary to look at the characteristics of managers and see if their jobs matches with their characteristics.
Several studies after that followed the same routine, but with a different focus. Buchholz (1977) for example focuses on the willingness of managers to change authority patterns and the level of influence of blue-collar workers. And Gupta and Govindarajan (1984) suggest that the influence of a leader depends on how well the characteristics of the leader matches with the challenges of the organisation. These studies fit in a broad context of mainly psychological based studies.
Hambrick and Mason try to make it less psychological by focusing on demographic indicators, like age, tenure and educational background. Their paper does not empirically test relationships. Hambrick and Mason made testable propositions for future research. The foundation of these propositions can be found in an article of Hambrick and Snow (1977): the so-called sequential view of the perceptual process. Hambrick and Mason (1984) summarise this view as followed:
‘First, a manager, or even an entire team of managers, cannot scan every aspect of the organization and its environment. The manager’s field of vision – those areas to which attention is directed – is restricted, posing a sharp limitation on eventual perceptions. Second, the manager’s perceptions are further limited because one selectively perceives only some of the phenomena in the field of vision. Finally, the bits of information selected for processing are interpreted through a filter woven by one’s cognitive base and values.’ (page 195)
This means that a manager does not see every possibility, threat or another administrative situation. The situations that are not filtered, will be dealt with. The way these situations are approached, depends on the background of the manager. It might be expected that managers with a master’s degree in history solve problems differently than managers with a doctorate in business. And the same way of reasoning yields for a number of other characteristics, like age, nationality, etcetera.
All these filters create a path dependency which makes it possible to partially predict and explain managerial choices.
Hambrick and Mason name in their article 7 characteristics that are probably causing this path dependency. These characteristics are the following: age, functional track, other career experiences, formal education, socio-economic background, financial position, and group heterogeneity. The latter is obviously an
interesting topic for study, and in this list the ‘odd one out’. Group heterogeneity should be the sum of the other characteristics.
This shows that studies in the upper echelon perspective can be divided in two groups. On the one hand there are the papers that focus on one or more of the first variables. An example is the paper of Wiersema and Bantel (1992). This paper explores the influence of demographic characteristics on changes in corporate strategy. They do not focus on heterogeneity of variables, but they look at the intensity of variables. For example they hypothesise that the ‘average age of a top management team will be negatively related to change in corporate strategy’ (page 97).
Other papers try to measure more broadly the heterogeneity of a team.
Heterogeneity means the amount of dispersion in a management team. The problem with heterogeneity is how to measure this dispersion. When is a group heterogeneous? Which factors should be included? If our basic assumption is that every person is unique, than all teams are to a high degree heterogeneous. In research it is common to take two or more variables and see if the group is heterogeneous for those variables. The fundamental objective behind this is that by measuring one variable it would not be possible to draw conclusions about the diversity in a team. A heterogeneous score on ‘different nationalities’ does not directly imply that the whole team is heterogeneous.
For example, let us take a top management team, which contains out of 5 members. When 2 members come from country A, 2 other members come from country B, and 1 member comes from country C, it appears that the top management team scores high on heterogeneity. But if they all are from the same age, worked their entire working career for this company, and have the same educational background, then they are more homogeneous then heterogeneous.
This would imply that articles written about group heterogeneity have this perspective, for the literal meaning is heterogeneity of the whole group. In practice, it appears that studies on heterogeneity is nothing more than a single-variable or multiple-variable study. Elron for example focuses on the heterogeneity of one variable. His paper tries to give an answer to what extent different cultures in a top management team influence the organisational performance. Simple and effective.
Also other factors have proven to be relevant, like the way of recruitment (Michel and Hambrick, 1992) and the educational background (Norburn and Birley, 1988).
Hambrick, Cho and Chen (1996) are the ones that started looking for multi- variable heterogeneity in a top management team, but they as well do not take an overall score on heterogeneity in their methodology. Hambrick, Cho and Chen take three types of ‘heterogeneity’, namely functional heterogeneity, educational background heterogeneity, and company tenure heterogeneity. Other studies (e.g.
Carpenter, 2002) follow the same routine, claiming to measure heterogeneity, but actually conducting a multiple regression analysis.
In my research the argumentation differs. This paper fits into the same context of research, which believes that the background of managers influences organisational outcomes. It is argued that it is not sufficient to look at heterogeneity in a single variable. This single-variable perspective will not be attacked, because of its proven relevance, and the proven correlation between a number of variables. This paper argues that there is a link between different variables, and that an overall score of heterogeneity needs to be taken into account. This becomes clear in the methodology of this paper, where four single-variable are tested, as well as one overall score on heterogeneity. This last concept is relatively new, and this adds information to the discussion in upper echelon research. The research question in this paper therefore is:
To what extent is heterogeneity in United States based multinationals correlated to performance?
The new perspective this paper takes, is that, besides measuring the correlation between four variables (gender, nationality, educational background, way of recruitment) and profit, an overall score on heterogeneity is used to measure heterogeneity in another way than has been done before. The research question is visualised in the conceptual model (Appendix A), where the four variables alone influence the organisational outcomes, as well as the total of the four variables together. Because a regression analysis will be conducted, the prediction formula looks like the following:
Y = aX1 + bX2 + cX3 + dX4 + eX1X2X3X4
These four variables are chosen, because they are all basic demographic characteristics. Another important feature of these variables is that they all have contradicting results, which might be solved by this research.
To get acquainted with the topic, it is important to know what has been written about those four variables and what is known about team heterogeneity. The next part therefore will give an overview of the existing literature about these variables, presenting arguments why these variables need to be included in the research.
HYPOTHESES Heterogeneity
Like mentioned before, there are two types of research on heterogeneity in top management teams. On the one hand there are the papers that focus on one variable, examining if for example multinational top management teams outperform single-national teams. On the other hand there are studies using a multiple-variable angle. These multiple-variable studies are a follow-up of Hoffman and Maier’s paper (1961) in which they state that heterogeneous groups come up with qualitative better solutions. A conclusion confirmed later by numerous other studies.
These studies are based on the belief that ‘diversity enhances the breadth of perspective and overall problem-solving capacity of the group’ (Hambrick et al. 1998, page 188). This belief is supported by for example Bantel and Jackson (1989), who examined 199 banks in the United States. There appeared to be a relationship between heterogeneity and the level of innovation. In Hambrick’s paper with Cho and Chen (1996) similar results were found in a sample of 32 United States airlines:
diverse top management teams were more active in decision-making.
Yet, they also found negative factors. It appeared that heterogeneous teams were slower in actions and responses. Besides that, they were less likely to react to competitor’s initiatives. Other studies come up with the same conclusion. One example is the research of Ancona and Caldwell (1992). Some diverse teams could well come up with answers and new products, but they had, due to team work troubles, problems with the implementation.
Remind that all these studies did not use one score on heterogeneity.
Hambrick, Cho, and Chen’s methodology is first correlating functional heterogeneity
with action and response characteristics, then correlating educational background heterogeneity with the same characteristics, and then correlating company tenure heterogeneity. They find for example that functional heterogeneity and educational background heterogeneity correlate significant with action scope. Their conclusion is automatically that diverse top management teams are bolder in competitive actions.
This conclusion is logical, but does not per se has to be true.
In this study one overall score will be used (details will be explained in the methodology section) to see if and how this correlates to performance. Because this way of analysing has, as for as I know it, not been done before, it is hard to say which correlation can be expected. Performance is measured by return on assets as well as market value. It might be expected that heterogeneity will be positively related to market value and negatively correlated to return on assets. This expectation is based on the conclusion of Ancona and Caldwell (1992), where diverse teams are able to be innovative and creative in problem solving, which would lead to a higher market value. The implementation of these creative solutions is harder in heterogeneous teams, which might lead to a negative correlation with return on assets. I propose therefore two opposing hypotheses1:
1a: There will be a positive correlation between performance and team heterogeneity.
1b: There will be a negative correlation between performance and team heterogeneity.
The result of this hypothesis will be compared with the results of four single-variable tests. These single-variable tests are in the same context as a lot of studies in upper- echelons research. Four variables will be tested: gender, nationality, level of education, and the way of recruitment.
Gender2
The variable gender is not included in the research of Hambrick and Mason.
This appears odd, because there is extensive literature written about the differences
1 It might look strange to propose opposing hypotheses. This way of hypotheses has, however, been used in methodology sections of other papers (see e.g. Carpenter, 2002), which provides enough ground for me to follow the same way of acting.
2 For the used categories, see appendix B
between males and females in management teams. A possible explanation of this missing variable is that in the time that Hambrick and Mason wrote their paper the amount of women in top management team was much lower than it is now. When more women entered the top management team, maybe more was written about the decision-making differences between men and women. Besides that, it has been shown that in many cases people have the tendency to ‘think manager, think male’
(Powell et al. 2002), which might cause a lower need for studying gender differences in top managers.
The literature that does deal with this topic is not unanimous in their findings.
Some studies, like Powell (1990) and Perry (2002), find that there is no gender difference in decision making. Other studies, however, do find differences between male top managers and female top managers. Many papers (e.g. Eagley and Johnson, 1990, Grant, 1988, Buttner, 2001) discover that females manage in a more democratic and participative way. Or as Carter, Williams and Reynolds (1997) state it: ‘men use human and financial resources to enhance the chances of their firms' survival, women find strategic choice more beneficial’ (page 141). Overall, the most literature claims that organisational outcomes is influenced by whether the manager is a male or a female.
An interesting remark at these findings is the theoretical framework proposed by Klenke (2002). She also believes in the existence of differences between ways of decision-making by men and women, but this is not per se caused by difference in gender. ‘(…) gender works indirectly though power, organizational politics/political savvy, conflict management and trust and produces differences between female and male top executives’ approaches to decision making (…)’ (page 1025). This provides even more reason to believe that gender influences the decision-making process.
Unfortunately, a direct relationship between gender and performance never has been proven. The expected correlation between performance and team heterogeneity with respect to gender depends on the amount of women in top management team. It might be expected that the influence of female managers is to balance the intuitive way of decision making of male managers. This might result in a negative correlation when performance is measured in market value, while a small positive correlation might be expected when measured in return on assets. This causes the need for two opposing hypotheses:
2a: There will be a positive correlation between performance and team heterogeneity with respect to gender.
2b: There will be a negative correlation between performance and team heterogeneity with respect to gender.
The nationality mix3
The nationality of team members is also not included in the by Hambrick and Mason proposed variables. This seems a gap in the upper echelon research. If the basic idea for this stream of research is that the cognitive values of managers cause the organisational outcomes, then how come that one of the largest influence on cognitive values, national culture, is excluded? In business research the study of Hofstede (1980) is well known, where countries get an average score on multiple value dimensions. These dimensions show clearly that there are differences in values of people, caused by nationality.
An example is that on average inhabitants of Belgium avoid unknown risk more than Dutch people. In a management team this would mean that a Belgian and a Dutch manager think differently about the strategies to take. Besides that, the original focus of Hambrick and Mason is on the top management team and the cooperation between different members. It appears in the line of logic that different nationalities would cause difficulties creating congruence in the believes of all the members, not in the last place due to the different languages spoken.
Also in this case, Donald Hambrick is helpful. Together with Davison, Snell and Snow he writes an article in 1998 about this topic. The authors believe that
‘group members drawn from various nationalities tend to differ in ways that have substantial implications for group functioning’ (page 183). Important remark is that
‘individuals, through accumulated experience and exposure, can surmount, to some degree, their nationality-based tendencies.’ (page 184) This phenomenon appears, however, to be rare. In the paper by Laurent (1983) it appears that managers who were active for some time in international teams, still had clear national distinctions.
Laurent’s hypothesis ‘the national origin of European managers significantly affects their views of what proper management should be’ (page 77) was therefore accepted.
3 For the used categories, see appendix B
The conclusion of Hambrick, Davison, Snell, and Snow is that the effect of diversity depends on the task of the group. Multinational diversity causes problems when the group has a coordinated task (like monitoring and maintenance), while it can be beneficial when creativity is needed. When there is a diversity in demeanours (‘various kinds of surface behaviour involving punctuality, conversational style, body language, and so on’ page 198) there will be no benefit at all, independent of the task. Overall, the argument is that multinational groups do not possess inherent advantages over single-nationality groups, but when the nationality-mix matches the task it will profit (page 199).
This makes it hard to draw conclusions for the dataset used in this study, because the fit between task and diversity is not included in this research. It might be expected that if a positive correlation is found, this could mean that the nationality-mix of the banks matches their creative task. A negative correlation is then a match between nationality and the coordinated task. If no correlation is found, the reason may lie in the misfit between task and diversity in demeanours. I do expect that nationality influences organisational outcomes, and thereby performance. Because the sample contains out of banks in the United States, language will probably not be a problem. This might create a situation where the negative factors connected to multinational teams are decreasing. Therefore, multinational teams will probably benefit from the extra outside knowledge of non- United States members. Hypothesis 3a and 3b are the following:
3a: There will be a positive correlation between performance and team heterogeneity with respect to nationality.
3b: There will be a negative correlation between performance and team heterogeneity with respect to nationality.
Level of formal education4
The literature about the influence of different educational backgrounds on top management teams is, just like papers about the nationality mix, not that broad. The literature that is written about this topic focuses mainly on the influence of different educational backgrounds on the innovation process, like Bantel and Jackson (1989).
4 For the used categories, see appendix B
Often the conclusion is that highly educated and diverse educated management teams innovate more.
A paper that also works with the level of education is the paper of Wiersema and Bantel (1992). They discovered that top management teams with a high educational level were most likely to undergo strategic change. Another interesting relationship discovered by Wiersema and Bantel was that strategic change was more common in top management teams with diverse educational backgrounds.
Another leading paper about the level of education in top management teams is the one of Thomas, Litschert, and Ramaswamy (1991). They combine the formal education with the three viable strategies of Miles and Snow (1978): Prospectors, Analysers, and Defenders. Prospectors are organisations that stand for innovative marketing techniques and the creation of new products. Defenders stand on the other side of the spectrum and are more conservative. These organisations try to be successful by improving the efficiency. Analysers are a hybrid form of both strategies. Thomas, Litschert, and Ramaswamy discovered that the top executives of Prospectors had higher levels of education than the managers of Defender firms.
All these papers do not take diversity in educational level into account. Having managers with different levels of education can have an influence on the way of decision-making. If the studies prove that companies with managers with higher levels of education are more innovative and better skilled, then the next step is that each level of education causes a cognitive filter for choices. This implies that heterogeneity in the level of education can cause differences in performance, but it is unknown how these are correlated. This leads to hypothesis 4a and 4b:
4a: There will be a positive correlation between performance and team heterogeneity with respect to level of education.
4b: There will be a negative correlation between performance and team heterogeneity with respect to level of education.
The type of education is not included in this research. Although the type of education a person chooses is known to correspond to the personality, attitudes, and cognitive values of the person (Holland, 1976), the relationship between diverse educated teams and performance has never been proven. One of the first papers about this topic is by Sambharya (1989). They tested the propositions of Hambrick
and Mason and found a positive correlation between the variables age, tenure, functional background and outsider orientation on performance measures as ROA (return on assets) and ROS. No correlation was found for educational background.
Bantel and Jackson (1989) find a positive correlation between diverse educated top management teams and innovation, but this correlation is far from significant. This leads to the conclusion that the type of education is not of that importance for measuring heterogeneity in a top management team.
Inside versus outside5
The question whether it is better to educate a manager or attract a manager from another company has been wondered many times. And for decades it has been proven that there are differences in corporate strategies, when there is a high amount of externally recruited managers. Problem with these studies is that the unit of analysis is mainly the chief executive officer.
And also in this discussion the results are contradictory. Supporters of recruiting internally (e.g. Chung, Lubatkin, Rogers, & Owers, 1987) state that the continuity is of great importance. It takes time for outsiders to get to know the company and this time can be costly. Managers recruited internally provide a smooth transition and are well-known with the situation and the chosen strategies of the company.
This would explain the results of Helmich and Brown (1972). They accept the hypothesis that organisations with executives brought in from the outside have more strategic changes. This would suggest that bad performing companies would attract a manager externally, because this causes new insights. In 1987 Chaganti and Sambharya discovered for example that there was a relationship between the amount of outsiders in a board and the chosen strategies of the companies.
Wiersema and Bantel (1992) also discovered a negative correlation between tenure and strategic change.
Concluding, internally recruited managers follow more often the already chosen strategies, while externally recruited managers go for new, innovative strategies. This means that when a top management team consists of solely internally recruited managers, they would take other decisions then when also
5 For the used categories, see appendix B
externally recruited managers are in the management team. This implies that heterogeneity in the way of recruitment might influence performance.
This direct relation between the way of recruitment and performance is tested before. One example is the research of Datta and Guthrie (1994). They state that
‘the choice of an internal versus an external CEO candidate is undoubtedly influenced by a firm’s desire to achieve desired performance levels.’ (page 570) They eventually found that companies that performed poorly hired more often managers from outside the company. The problem with these studies is that they reason the other way around: performance influences the way of recruitment.
In conclusive it might be stated that it is not common in research to study the heterogeneity for the way of recruitment. It is much more common to test the tenure of managers, as well as the relation between previous performance results and the way of recruitment. In this study the question is whether the way of recruitment influences performance, and due to the non-existing amount of literature it is hard to propose hypotheses. I expect that outsiders bring in more creativity and a new way of thinking into the top management team. This would cause a positive correlation between heterogeneity in the way of recruitment and performance. As explained earlier, it might be expected that creativity would be seen the clearest when market value is used as a measurer for performance. Still, due to ignorance in this part of research, it is hard to come up with one explanation and one hypothesis. Therefore hypothesis 5 is two folded.
5a: There will be a positive correlation between performance and team heterogeneity with respect to the way of recruitment.
5b: There will be a negative correlation between performance and team heterogeneity with respect to the way of recruitment.
METHODOLOGY Sample
Due to the high proportion of United States based literature, it might be useful to test this framework on United States based companies as well. This improves the level of comparativeness. Another factor for choosing this sample is the
accessibility to data for United States based companies. As told above the sample consists of 30 United States based banks. These are the largest banks in the country, which is necessary to draw some conclusions about non-U.S. companies. Large banks can be looked at as multinational companies (Citigroup for example operates in more than 100 countries, and is the number one in Forbes’ top 2000 list.1), which might look more similar with multinationals from other countries than single-national companies.
These banks are chosen from Forbes’ top 2000 list.6 Only banks with a top management team containing four or more members are included. This is done because I conducted tests before this paper, which show that the influence of heterogeneity can be biased when small management teams are included. Therefore the thirty largest top management teams with more than 4 managers were selected.
Data for all these management teams were selected. When not all data was available companies were still included. This causes differences in observations per hypothesis.
In this database 30 observations are used for gender and nationality. 27 observations were for education used, and 28 for the way of recruitment. For heterogeneity the sum of the first four hypothesis was used, which makes the number of observations for heterogeneity 27 as well. In total, data for 245 managers was collected. For 21 managers data was incomplete. For all those 21 managers no data was available on their educational background. For 11 of the 21 managers no data was available on the way of recruitment.
Dependent variable
The dependent variable in all hypotheses is performance. Performance will be measures by the return on assets (ROA). This is a widely used measure in comparable studies (e.g. Hitt, Schoonhoven, Kimm, 1997;) which is calculated by dividing the net income from continuing operations, excluding extraordinary items, by the total assets. Information was found in annual reports of 2005. Some companies have a book year which ends in March. In those cases the bookyear 2005/2006 was used.
A second performance measuring variable is market value. This extra variable shows not solely the financial performance, but whether the top management team
6 http://www.forbes.com/2006/03/29/06f2k_worlds-largest-public-companies_land.html
succeeds in gaining the confidence of its investors. This means it is a more overall performance measure. Information about market value was in the Forbes database.
Independent variables
The top management team is defined as all executives above the vice- president level (Hambrick, Cho, and Chen, 1996; Chaganti and Sambharya, 1987).
This means all the managers with titles like chief executive officer, vice chairman, and senior vice president. Non executive directors, chairmen, and secretaries are not included. Information about the managers was mainly found on the companies website. Almost every company has a special part in which the top managers are presented. If the company’s website did not provide enough information, annual reports, and other websites (like www.forbes.com) were used.
The score on heterogeneity for all hypotheses will be calculated by using the measure that Hambrick, Cho, and Chen (1996) use, which is originally composed by Blau (1977):
n H = 1 -
∑
pi 2t=1
H stands for the score on heterogeneity. n is the number of possible categories, for example for gender this will be 2. For the level of education a scale by Herrmann and Datta (2005) with seven categories will be used:
1 High School 2 Some college
3 Undergraduate degree 4 Some graduate school 5 Master’s degree
6 Attended doctoral programme 7 Doctorate (no honorary doctorate)
p stands for the percentage of the team members in each of the category.
This leads to a score between 0 and 1. The higher the score, the more heterogeneous the team is for that variable. These numbers will then be separately
tested for hypothesis 2 – 5. For hypothesis 1 the four results will be added to get one overall score on heterogeneity within a top management team. This score will be tested on a possible correlation with ROA and market value, resulting in whether hypothesis 1a or 1b should be accepted.
For hypotheses 5a and 5b externally recruited managers are defined as individuals who have been employed by the company for less than one year before their appointment in the board (see Murphy, 2002, with the exception that his definition focuses solely on the CEO). When managers enter the top management team from a daughter company, the manager is labeled as internally recruited.
Managers entering the top management team, because of acquisition of their company are regarded as externally recruited.
The H-scores that come out of Blau’s formula will be used in a single- regression analysis. Hypotheses will be tested on an alpha of 0.10.
RESULTS
Descriptive statistics (mean and standard deviation) for the independent variables and the top management team size can be found in table 1. These statistics show the composition of an average top management team. The mean of the heterogeneity scores is not given, because due to the different number of categories for each variable, the scores could not be compared. (Harrison, Sin, 2006).
Mean St.Deviation
Mean top management team size 8.16 2.92
Male top managers 7.05 2.48
Female top managers 1.14 0.66
U.S. top managers 7.82 2.81
Non-U.S. top managers 0.34 1.00
High School 0.06 NA
Some college 0.00 NA
Undergraduate degree 2.67 1.94
Some graduate school 0.06 NA
Master’s degree 4.44 1.92
Attended doctoral programme 0.17 0.00
Doctorate (no honorary doctorate) 0.78 0.88
Internall recruited 5.11 2.96
Externally recruited 3.06 2.42 Table 1
The average top management team contains out of 8.16 members. This appears to be a high number, which is mainly caused by the filter of choosing top management teams with 4 members or more. If this filter was not applied the average team size would have been 6.64. On average 7.05 top management team members are male, with a standard deviation of 2.48. This means that over 86% of the managers is male, which results automatically in the fact that 14% of the managers is female. This appears to be a low percentage, but the opposite is true. In the Catalyst production of 2004 a sample is used with 353 companies of the Fortune top 500. They find that the average representation of women in top management teams is 10.2%. One of the industries that had a higher than average percentage was the industry called ‘financials’. The 14% of my sample therefore appears to be a good representation of other companies as well.
A striking observation is the low number of non-United States managers. Only 10 managers were no United States citizen. 2 managers are German, 2 managers have the Mexican nationality, and there are 2 Indian managers. 4 managers have a Canadian passport.
This high number of United States managers influences the descriptive statistics for education as well. In papers (see e.g. Franck and Opitz, 2003) it is argued that for entering the top management team it is necessary to follow specific national education paths. For the U.S. this means that a high number of managers have at least a undergraduate degree, but a relative low number of managers have a doctorate. This result can also be discovered in my database.
Of the 245 managers 63% were hired from the inside, while 37% was recruited externally. The reason that managers are more recruited internally can be explained by several reasons. First, companies often look first in their own resources if someone can enter the top management team. Besides that, due to the strict definition (individuals who have been employed by the company for less than one year before their appointment in the board) a number of managers were labelled as externally recruited, while they only were several weeks or months longer than one year employed by the company. This is a follow-up of the different perspective of this paper. It is more common to use the company tenure as a proxy for the way of recruitment. In this paper the focus lies on wondering whether it benefits when a team consists out of both insiders and outsiders.
Table 2 presents the regression results with the four variables solely as independent variables, and the ROA and market value as dependent variable.7
* Significant at an alpha of 0.10
Some things come to mind looking at the results. First, almost none of the hypotheses are supported. Only 2 hypotheses are partially supported at an alpha of maximum 0.10. Also the regression between gender and performance (measured as ROA) is very significant, which supports hypothesis 2a. The regression between nationality and performance is significant at an alpha of 0.10 when performance is measured as market value. This partially supports hypothesis 3. Hypothesis 4 and 5 are both rejected.
In table 3 the regression results are shown, with the overall score on heterogeneity as independent variable.8
These results show that hypothesis 1 is also rejected, due to its lack of significance. It can be stated that there is a positive correlation, but this is too small to draw clear conclusions. This might be caused by the low number of observations.
Another reason may be the very low correlation for the variables ‘education’ and
‘recruitment’. Therefore, it might be that the overall score on heterogeneity does
7The standardised regression coefficients are listed, with the level of significance in parentheses.
8The standardised regression coefficients are listed, with the level of significance in parentheses.
Table 2
ROA Market value
Heterogeneity .200 .340
(.425) (.167) Table 3 ROA Market value N
Gender .596 * .266 30
(.009) (.287)
Nationality .341 .440 30
(.166) (.068) *
Education .079 .163 27
(.756) (.518)
Recruitment .158 .091 28
(.532) (.719)
correlate, when you only consider the variables ‘gender’ and ‘nationality’. Therefore an additional test is conducted, using a heterogeneity score, which consists of the sum of the heterogeneity score for ‘nationality’ and ‘gender’. These results can be found in table 4.8
* Significant at an alpha of 0.10
Table 4 proves that heterogeneity with respect to education and heterogeneity with respect to recruitment influence the correlation influence the overall score on heterogeneity in a high amount. Still, hypothesis 1 can only partially be accepted, when market value is used as dependent variable, and when the variables education and way of recruitment are excluded.
In table 5 an overall picture is given about which hypotheses are accepted and rejected when an alpha of 0.10 is used. A ‘+’ means that the hypothesis is accepted, while a ‘-‘ means a rejection of the hypothesis.
DISCUSSION
This paper can be placed in ‘upper echelon’ research, because it takes the top management team as the unit of analysis, and because it focuses on background characteristics of managers to try to predict organisational outcomes. Its fundamental objective is to provide a new perspective in this type of research, by focusing on overall group heterogeneity. This as a counterattack on the majority of studies in this part of business research, because often only a small part of the total picture is examined, which causes a situation where the interaction between
Table 4
ROA Market value Heterogeneity (nationality+gender) .254 .487 *
(.308) (.040)
Table 5
Type of ROA Market correlation Value
Heterogeneity Positive - -
Gender Positive + -
Nationality Positive - +
Education Positive - -
Recruitment Positive - -
Heterogeneity (nationality+gender) Positive - +
variables is overlooked. In this paper 30 United States banks are examined, and for the top management teams the diversity in gender, nationality, education, and way of recruitment are correlated with return on assets and market value. After that, an overall score for heterogeneity was calculated, and this score as well was correlated with performance measures.
Surprisingly, almost none of the hypotheses is supported. The relationship between gender and performance is partially supported. Only when return on assets is used as a performance measurer the correlation is significant. This correlation between performance and the proportion of women in top management team has recently been proven by other studies, like Krishnan and Park (2005). One explanation they give is that ‘women are more likely to possess a “feeling” cognitive style, a style that emphasizes harmony, compared to their male counterparts. This style is likely to enable women to inspire confidence among peers and subordinates, share information and power, bring people together, and respond to challenges’.
(page 1713).
The positive correlation between heterogeneity in nationality and performance is also partially supported, although in this case the correlation is significant when market value is used as a performance measurer. The correlation between return on assets and the nationality-mix is not that far from significant. In advancing the hypothesis I suggested that a possible correlation may lie in the fit between task and nationality-mix (as suggested by Hambrick, Davison, Snell, Snow, 1998). Due to the possible correlation and the (almost) significant results, it might be concluded that the fit between task and nationality-mix is right in the banking sector. A comment on this is that due to the low number of non-United States managers a correlation easier was found. It might be that in other sectors other results can be found.
Especially in the smaller banks it appeared that the number of non-United States managers decreased, which leads to the comment that the results need to be interpreted carefully.
There is clearly no relationship between heterogeneity in terms of level of education and performance, as well as between heterogeneity in terms of the way of recruitment and performance. The lack of significance for the level of education might be explained by the unusual context of the tests. It is common to test a relationship between for example a higher level of education (calculated by the average number of years of education) and some organisational outcome (see e.g.
Bantel and Jackson, 1992). Here the heterogeneity is tested, meaning that 3
managers with high school education, and 1 manager with a bachelor’s degree get the same score as 3 managers with a doctorate and 1 manager with a master’s degree. Having a top management team with managers with a diverse level of education is therefore not that relevant for achieving a good company performance as the level of education on its one.
The rejection of the fifth hypothesis, which examines heterogeneity in terms of the way of recruitment, may appear puzzling for researchers. An explanation for this possibly lies in the tested industry. In the United States banking regulations require bank presidents to have significant bank experience (Hambrick and Mason, 1984). An externally recruited manager then will not really bring in new creative ideas, because the manager is grown up in the same industry. Therefore the influence of the way of recruitment probably is small.
One other thing that comes to mind when analysing the results is the striking difference between the two dependent variables. No hypothesis has a significant result for both ROA and market value. Moreover, for all hypotheses there are large differences between both variables. A top management team with a high diversity in gender correlates best with return on assets. Market value correlates better than ROA with heterogeneity, and is even significant for heterogeneity (nationality + gender). This could support previous findings (Hambrick, Cho, and Chen, 1996;
Ancona, and Caldwell, 1992) that heterogeneous top management teams are creative in entering new markets, seize opportunities, and decision creativity, which would lead to a high market value. Unfortunately, most heterogeneous teams have difficulties implementing their ideas, leading to differences in ROA results. Remind, results were not significant, and so these are speculations, which can be examined in future research.
Another interesting observation is that 1 and 1 does not always equal 2. In other words: when one variable (gender) correlates heavily with ROA, and one variable (nationality) is almost significant, this does not have to mean that the total heterogeneity score correlates in a high degree with ROA as well. This gives the opportunity to draw two opposing conclusions.
First, group heterogeneity should not be measured as been done in previous studies. If in this study only the four variables were tested on their correlation with return on asset, the conclusion would have been that there is a significant correlation between gender and ROA, and that nationality heterogeneity is also strongly, although not significant, correlated with ROA. If this study only used the sum of both
heterogeneity scores, the conclusion would have been that it is far from significant.
Due to the insignificant results it is hard to tell the truth. Therefore it is necessary that future research examine more thoroughly how diversity is measured, because this influences results strongly.
The second conclusion must be taken into account in future research. It might be that the methodology for calculating the overall score on heterogeneity in this paper is not the right one. Perhaps it is even better to divide the entire team in groups for a selected number of criteria. In other words, imagine there is a male chief executive officer, United States citizen, who owns a doctorate and is externally recruited. In the methodology in this paper all those four characteristics would be filled in separately in a database. If a second managers appears to have the same characteristics, with the exception that he own a bachelor’s degree, then he should not be categorised in the group where the CEO is already in. This because they differ in one or more variables.
This would look like the following:
Top management team consists out of 7 members:
1 man, U.S. citizen, doctorate, externally recruited
3 women, U.S. citizen, master’s degree, internally recruited 1 woman, Mexico citizen, master’s degree, internally recruited 2 men, U.S. citizen, bachelor’s degree, externally recruited
Group 1 Group 2 Group 3 Group 4 Heterogeneity score 1 3 1 2
0.020408 0.183673 0.020408 0.081633 0.693878
As can be seen in table 69, this top management team contains out of four groups. This means, using Blau’s (1977) formula, that the heterogeneity score is
9In the second row the number of observations are written down. In the third row the p-value is noted, which stands for the percentage of the team members in each of the category is measured. The heterogeneity score is calculated by 1 minus the total of the p-values.
Table 6
0.69. In table 710 the methodology of this paper is shown, resulting in a heterogeneity score of 1.80.
Male Female Hetero- geneity score
for gender
U.S. Mexico Hetero- geneity score for nationality
Bachelor Master Doctorate Hetero- geneity score for education
Internal recruited
External recruited
Hetero- geneity score for the way of recruitment
Total hetero- geneity
score
3 4 0.4898 6 1 0.2449 2 4 1 0.5714 4 3 0.4898 0.448975
If one of the U.S. citizen women only went to high school, the score would become 0.78, while in the methodology of this paper it would become 1.92, a smaller change in percentages than the first way of calculating. This means that a different way of calculating comes up with different results. This is a phenomenon that needs to be addressed more, because this will improve the discussion about ‘upper echelons’ research.
An additional argument in heterogeneity research is that if this framework is examined more thoroughly, extra attention must be given to allocation formula. It looks logical that some variables have a bigger influence on the heterogeneity score than others. This needs to be examined as well in future research to solve puzzles in
‘upper echelons’ research.
Another issue that needs to be considered is the focus on United States based companies. It might improve the discussion across countries when there is more known about the influence of team characteristics on organisational outcomes in European based organisations, and then especially companies in coordinated market economies. This type of economy is first mentioned in the book by Hall and Soskice (2001). Their framework tries to explain how variances in national institutions structure economic policy, and thereby indirectly performance. They constitute two opposing ideal types of political economies, which each stands on the end of a spectrum.
On the one side stands the liberal market economy (LME), with as main examples the United States and the United Kingdom. In liberal market economies there is often a market-based financial system, which means that management has to make choices to satisfy shareholders. A second cause of the financial system is
10 Beneath each possible variable outcome (male or female) stand the number of observations. Then each heterogeneity score is calculated by the formula of Blau (1977). The total heterogeneity score is the sum of the four other heterogeneity scores.
Table 7
that finance can be provided with a higher risk, which is useful for radically innovating start-ups. This creates room and need for flexibility, which is also supported by the highly fluid labour markets.
The coordinated market economy (CME) has typically a bank-based financial system, creating possibilities for long-term orientation. This means more incremental innovation and a higher need for highly skilled labour. Typical examples over here are Germany and Japan. Due to this long-term orientation other results may arise. In German companies it is common that a top management team member has worked almost his entire working career for the same company. Besides, education is more focused on speciality (Hall and Soskice, 2001), which might cause a higher number of doctorates. Preliminary studies performed by myself proves a different composition of top management teams in Germany, where 84% has at least a master’s degree. This phenomenon must be examined in the future. My believe is that in coordinated market economies a more homogeneous top management team will be found. This makes it interesting to see if heterogeneity or homogeneity is more beneficial in coordinated market economies.
A final comment is that heterogeneity perhaps should be examined more thoroughly. By focusing solely on demographic characteristics other influential factors, like psychological factors, may be overlooked. Besides that, it might be interesting to focus more on the question how heterogeneity in top management teams influences organisational outcomes. (see e.g. Priem, Lyon, Dess, 1999)
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