The effect of CEO gender on commitment
to innovation
by
EGBERT JAN GROOTENHUIS
University of Groningen
Faculty of Economics and Business
1
Abstract
These days, firms devote a lot of time and money to find the 'right' CEO for their company. Based on the 'upper echelon theory' of Hambrick & Mason (1984) the managerial influence on organizational outcomes and strategic choices is thought to be very high. Facing the consequences of the economic crisis, businesses would simply appoint a female CEO since women are assumed to act more risk-averse. This study is highly relevant for policy makers and organizational theorist for our results show there's no difference between the commitment to innovation of companies with a female CEO and those with a male CEO. Moreover, tenure is the only CEO characteristics with a significant influence on the commitment to innovation. In capital intensive industries organizational size is of dire importance in elucidating organizational outcomes, e.g. the commitment to innovation.
Research theme
Organizational characteristics and innovative behavior and performance
First supervisor Dr. F. Noseleit
Second supervisor Dr. I. Estrada Vaquero
Keywords
2 Table of contents
1. Introduction ... 3
2. Literature review ... 5
2.1 Top management characteristics and innovation ... 5
2.2 Leadership ... 7
2.3 Gender and risk ... 8
3. Methodology ... 11
3.1 Sample characteristics ... 11
3.2 Data collection ... 12
3.3 Dependent variable: Risk aversion ... 12
3.4 Independent variable: ... 13
3.5 Control variables ... 13
4. Analysis ... 14
4.1 Comparing the two groups ... 14
4.2 Distribution ... 15 4.3 Regression ... 16 5. Discussion ... 19 6. Conclusion ... 21 6.1 Conclusion ... 21 6.2 Implications ... 21
6.3 Limitations and possibilities for future research. ... 22
References ... 23
3
1. Introduction
"During an economic crisis highly educated employees prefer their company to be led by a female CEO. They appreciate the sympathetic, compliant and non-authoritarian behavior that characterizes the feminine leadership approach. This stands in sharp contrast with the classic masculine leadership approach that is thought to be greedy, egocentric and focused on power." These sentences summarize the main empirical findings of Rink & Stoker's (2012) study on leadership in times of crisis. Whether or not caused by the crisis, fact is that more and more companies appoint a female CEO. Figure 1.1 shows the percentage of Fortune 500 companies with a female CEO (Catalyst, 2013). Furthermore there is the topic of creating more gender equality in the business environment. There is currently an intense debate going on about the intention of the European Commission to establish a quota for female top managers. At the moment we may therefore speak of CEO-gender as an interesting topic.
Figure 1.1 percentage of Fortune 500 companies with a female CEO Source: catalyst.org
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counterparts and that this is a good thing. While this might be true for some sectors, e.g. banking, other industries thrive at making (the right) risky decisions. The high-tech branch shows some illustrative examples: Google buys YouTube, Apple enters the phone market, and Microsoft decides to compete with Sony and Nintendo through the introduction of the XBOX (Businessinsider, 2012). In these industries 'playing safe' is often not the right strategy to survive. These companies need radical innovations to stay ahead of their competitors, and one characteristic of such an innovation is the high amount of risk it comprises (Kor, 2006). These insights provide a quite different perspective on the topic of female leadership. Although there is already a large body of literature on the role of gender diversity in top management teams (TMT) there is still little known about the effects of a female chief executive officer . Only very recently, Khan & Vieto (2013, still in press) studied the effects of a female CEO on company performance. Their results showed that firms managed by female CEOs performed better in comparison with the male led companies. In their article about gender diversity in top management teams Krishnan & Park (2005) properly summarize the current scientific work on female top managers. First, there are studies focused only on statistics (Burke & Mattis, 2000; Joy et al., 2007). Second, you'll find studies that are mainly interested in the compensation differences between male and female directors (Krishnan & Park, 2012; Bertrand & Hallock, 2001). Third, there have been studies directed at the leadership differences between male and female managers (Eagly & Johnson, 1990). Finally, the most recent studies focus on the performance differences between companies being led by a male director and those led by a female director (Krishnan & Park, 2005; Smith & Verner, 2006; Khan & Vieto, 2013). Generally speaking we assume that women take less risk than men do. This is also the reason why women get a discount on their car insurance, they drive more carefully (autoos.com, 2010).
In this study we investigate if there is a relationship between CEO gender and the relative amount of money invested in research and development (R&D). We expect a female CEO to be more risk averse and hence spend relatively less money on R&D. R&D intensity will be used as proxy for risk aversion.
5
2. Literature review
Much of the recent academic work on female top managers focused on industries that promote stability. This study differentiates from the usual approach since it uses a sample consisting of manufacturing firms. Businesses in this sector need to take more risk in order to survive (Bromiley, 1991). The steep increase in Fortune 1000 companies with a female CEO provides an excellent opportunity to advance the earlier work on the link between top management characteristics and commitment to innovation. The first part of the literature review will discuss the current academic work directed at the various factors that impact the commitment to innovation. The second part is dedicated to work on gender differences, especially related to the topic of risk taking.
2.1 Top management characteristics and innovation
Innovation is important for the growth of the economy in general (Schumpeter, 1943), and is an important source of competitive advantage for the individual firm itself (Porter, 1998). Investing in research and development is therefore thought to be one of the most important decisions to be made by top management (Barker & Mueller, 2002). Investing in R&D can be seen as an innovation input, and is sometimes also called 'commitment to innovation'.
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or R&D background, and highly educated were more likely to have successful market innovation strategies. These studies are limited due to their focusing on one particular industry. They may therefore reflect industry idiosyncrasies while ignoring the broader patterns (Barker & Mueller, 2002).
Deallenbach et al. (1999) was one of the first to do a multi-industry analysis. They found a positive relation between technical work experience and R&D expenditures whereas education, company and industry experience showed no direct link with R&D expenditures. In addition, Barker & Mueller (2002) found that CEOs with career experience in marketing and R&D were positively related with R&D expenses as well as those with greater wealth in stock invested. Other results were a significant increase in R&D spending when CEOs had an advanced science degree, and the effect of tenure on R&D. Education, however, did not seem to be an issue once a CEO has gained a college degree.
Little attention is paid to the possible effects of gender differences in top management, especially in the context of innovative performance. This may be caused by the low percentage of women that had a top management position until recent times (Krishnan & Park, 2005). But times are changing, and at the moment we can witness a steady growth of women in higher management positions (Figure 1.1). Large multinational companies like IBM, Walmart, Yahoo, HP, Sara Lee and eBay are all being led by a female chief executive officer (Forbes, 2012). One common explanation for this increase is that a female CEO takes less risk than her male opponent (Palvia et al, 2011).
7 2.2 Leadership
2.2.1 Implicit theories about leadership
Most people associate leadership with men. When thinking of a manager, the image of a somewhat older man immediately pops up. Scholars argue that this supposed relationship between men and leadership is caused by the implicit theories people have about leadership and gender (e.g. Heilman et al., 1989; Eagly & Karau, 2002; Agars, 2004). Male leadership is characterized by acting emotionally stable, aggressive, self-reliant, competitive, objective and ambitious (Ryan & Haslam, 2005) whereas female leadership is characterized by being helpful, understanding, sophisticated, intuitive and cheerful (Schein, 1973;1975). Schein also showed that both male and female respondents thought men possessed the right characteristics to be a successful manager. Replications of this study proved these results are still valid today (e.g, Brenner et al. 1989; Schein & Muller, 1992; Boyce & Herd, 2003). These implicit feelings about gender and leadership prevent females from taking managerial positions in two ways. First these implicit feelings reduce the perceived suitability for a women to fulfill management roles, by stating that 'a woman is not up to the task' (e.g. Heilman, 1983; Kent & Moss, 1994) Secondly, female managers receive greater criticism and are evaluated less favorable as men when showing the same behavior (Eagly et al, 1992). Thus, a male manager acting aggressive and competitive is displaying leadership, however, when a female manager is acting in this way her behavior is seen as unacceptable pushy (Ryan & Haslam, 2007). These implicit theories do, however, show some variation that is caused by the context in which the company operates (Ryan & Haslam (2007). Female managers are more accepted in "feminine" sectors like healthcare and retail than in "masculine" industries as manufacturing and mining (Blum et al., 1994; Singh & Vinnicombe, 2003 cited in Ryan & Haslam, 2007).
2.2.2 The rise of female CEOs
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sympathetic, compliant and non-authoritarian (Emrich, 1999; Ryan & Haslam, 2007, Rink & Stoker, 2012). Another explanation for the growing amount of female directors is the board policy of investors that only want to invest in companies with a diversified board of directors since this enhances the firm value (Carter, Simkins & Simpson, 2003). The third reason for the recent growth of female executives are the government regulations that require a minimum percentage of female top managers (Terjesen, Sealy and Sing, 2009). Additionally the literature proposes an explanation that has nothing to do with the environment or organization, but with the female managers themselves. Furst & Reeves (2008) state that "successful women leaders break many traditional stereotypes regarding “female” leadership traits and demonstrate a willingness to take risks and make decisions that defy conventional wisdom".
2.3 Gender and risk
2.3.1 What is risk?
In the decision making theory, risk relates to the variation of the possible outcome distribution and the likelihood of this outcome. This implies that a choice is considered risky when it has a wide range of possible outcomes (March & Shapira, 1987). In general people are thought to be risk averse decision makers, when choosing between two alternatives with the same expected outcome, an individual will prefer the alternative with the highest certainty to the less certain alternative (Pratt, 1964; Arrow, 1965; Ross, 1981). Therefore decision makers have to be compensated in order to consider the riskier alternative (March & Shapira, 1987). The decision making theory distinguishes between averse decision makers and risk-seeking decision makers. Risk-averse decision makers prefer a low risk and are willing to give up some expected returns in order to reduce the variation in the possible outcomes. Risk-seeking decision makers prefer a higher risk and are willing to give up some expected return as to increase the variation of the possible outcomes (March & Shapira, 1987).
2.3.2 Psychological research
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of a nuclear war, the dangers of radioactive waste, and the process of environmental degradation (Flynn et al., 1994). In general we thus find that that women are more risk-averse than men. Byrnes et al. (1999) notice that this relation seems to be stronger when it concerns intellectual risks.
The common explanation for the recurring differences in risk taking between men and women is that these differences originate from evolutionary aspects related to reproductive success. Eckel & Grossman (2002) write that: for a female, the low-risk investment in parenting effort yields the highest returns, whereas for a male, the higher-risk investment in mating effort produces a higher expected payoff (Daly & Wilson, 1988; Geary, 1998; Low 2000). A proper summary of psychology literature concerning gender differences in risk taking behavior is that "men took more risks even when it was clear that it was a bad idea to take a risk. The opposite was true for women, they seemed to be disinclined to take a risk even when it was clear that taking the risk was a good idea. Men thus encounter more failure compared to women. Women do, however, experience less success than they should". (Byrnes et al., 1999, p.378 )
2.3.3 Economical research
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2.3.4 R&D and risk
R&D expenditures are usually classified as risky investment when compared with expenditures on equipment and property (Bhagat and Welch, 1995; Kothari et al., 2002). This relatively high amount of risk could be explained by the long-term orientation of R&D projects (Barker and Mueller, 2002) and because R&D expenses are seen as irreversible (Kothari et al. 2002). Furthermore, R&D projects are characterized by uncertainties in achieving their technical goals, commercialization and appropriation, causing a high uncertainty of future returns (Mansfield, 1969; Scherer and Ross, 1990).
The psychological and economic literature indicates that women are more risk-averse than men. This finding combined with the notion that R&D expenditures are seen as risky decisions presumes a female CEO to approach R&D investments differently compared with a male CEO. Most studies use R&D intensity, measured as R&D expenses divided by net sales revenue, as a proxy for risk aversion (Hoskisson et al., 1993; Daellenbach et al., 1999). We therefore hypothesize that:
Ceteris paribus, firms with a female CEO will exhibit a lower R&D intensity as compared to firms with a male CEO.
This research attempts to extend the existing literature concerning the influence of CEO characteristics on R&D spending. The main question will be to examine the role of gender effects on commitment to innovation.
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3. Methodology
3.1 Sample characteristics
12
Female CEO Male CEO
Name SIC-Code Innovation
Ratio Name SIC-Code Innovation Ratio HP 357 2.82% Apple 357 2.16%
Archer Daniels 204 0.06% Philip Morris 211 1.32% Mondelez Int. 202 1.32% Tyson Foods 201 0.13%
DuPont 282 5.90% Dow Chemical 282 3.01%
General Dynamics 381 1.72% Honeywell Int. 382 4.90% PepsiCo 208 0.84% Dr. Pepper Snapple Gr. 208 0.25% Xerox Corporation 386 2.43% Emerson Electronic 382 2.24% Avon Products 284 0.70% Ecolab Inc. 284 1.55% Campbell Soup 203 1.62% Hormel Foods 201 0.36% Ingredion Inc. 204 0.54% Ralcorp Holdings 203 0.43%
Mylan 283 6.52% Actavis 283 8.50%
Xylem 356 2.80% Pall Corp. 356 3.10%
Oil States Int. 353 2.22% Lennox Int. 358 1.72% Salix Pharmaceuticals 283 16.72% Cubist Pharmaceuticals 283 29.98% Axcelis Technologies 367 19.86% Monolithic Power Syst. 367 22.82%
ITT 356 2.81% Brocade Comm. 357 16.23%
Int. Game Technology 399 10.12% Hasbro Inc. 394 4.50%
Average 4.65% 6.07%
Table 3.1: companies compared by SIC-codes
3.2 Data collection
The databases of COMPUSTAT and Bureau van Dijk were used to gather the data on company sales, research and development expenses, number of employees and industry classifications. Because these databases contained only little information about the CEOs, the various company websites were used to collect more detailed information on this topic. Since quite a few female CEOs were appointed in 2011, this study only used the company records of the year 2012.
3.3 Dependent variable: Risk aversion
13 3.4 Independent variable:
CEO gender is the key variable in this study. It is used as a dummy variable, a female CEO gets the value '0' and a male CEO gets the value '1' assigned.
3.5 Control variables
Based on the existing strategic management literature (e.g. Daellenbach et al., 1999; Barker & Mueller, 2002) we use the subsequent variables to control for factors that are known to influence the innovation ratio of a company.
First there are the company characteristics, size and type of industry in which the business is active. Company size is sometimes measured in terms of total revenue, other studies use the number of employees to describe the size. In this study we use both variables, the size is determined by multiplying the number of employees with the total revenue. Initially we expect an negative relation between size and innovation ratio, to check whether this relation stays negative we also use the squared term of firm size. A log transformation measure for firm size was used since this shows a stronger association with innovation (e.g. Damanpour, 1992).
The other organizational control variable is the industry classification in which a company operates. We distinguish between low-tech and high-tech industries. Using the SIC-code classification we can differentiate between the traditional manufacturing companies and those who make use of more advanced production processes. For statistical reasons the low-tech companies get the value '0' assigned, and the high-tech '1'.
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4. Analysis
4.1 Comparing the two groups
Before testing our hypothesis that women are more risk-averse than men, and therefore spent less money on R&D, we need to make sure that the two groups of companies are comparable. We need to minimize differences of anything other than CEO gender. From the literature (e.g. Rothwell, 1984; Baysinger & Hoskisson, 1989) it is clear firm size has a significant influence on R&D expenses, therefore we want to make sure the two groups are almost homogenous. This is measured by looking at the amount of sales which is often used in the literature as proxy for firm size (e.g. Elston & Goldberg, 2003; Aggarwal & Samwick, 2003) and also the number of employees.
Table 4.1: Descriptive statistics (N is for both groups 17, data of year 2012)
Variables Mean Std. Deviation Sigma (2-tailed)
Company characteristics
Sales (mln) Female CEO 26.153 34.772 0,798 Male CEO 22.918 38.106 0,798 Employees (th.) Female CEO 71.519 97.747 0,297 Male CEO 43.429 47.285 0,297
CEO characteristics
CEO Age (years) Female CEO 55,41 4,976 0,750 Male CEO 54,88 5,608 0,750 CEO Tenure (days) Female CEO 1046 940 0,088
Male CEO 1780 1440 0,088
15 4.2 Distribution
Figure 4.1 uses a boxplot to analyze the innovation ratio of the selected companies, it distinguishes between the companies with a female CEO and those with a male CEO. At first sight it seems there are little differences between the two groups. The median innovation ratio of the female led companies is with 2,43% slightly higher than the median 2,24% of the male led companies. The only outstanding difference is that the third quartile for female led companies is higher (6,2%) than those of the male led companies (4,9%). This implies, before even making a regression analysis, that the differences between the two groups are minimal. In figure 3.1 we have seen that the average innovation ratio of male led firms is somewhat higher than that of female led firms, respectively 6.07% and 4.65%. This is mainly caused by a few outliers, e.g. Cubist Pharmaceuticals. These outliers are not shown in figure 4.1.
Figure 4.1
Boxplot comparing innovation ratio between firms with female CEO and male CEO
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not significant, we notice the mean innovation ratio of younger CEOs is twice the size of the innovation ratio of the older CEOs.
4.3 Regression
A SPSS diagnostics check suggested collinearity between the company characteristics 'high-tech/low-tech', 'LN-size' and 'Squared LN-size'. In case of multi-collinearity, the literature (e.g. Barker & Mueller, 2002) recommends to use separate regression models. We will therefore run a separate ordinary least regression (OLS) analysis to investigate the effects 'high-tech/low-tech' and organizational size on commitment to innovation. Figure 4.2 summarizes the results of various tests. Since we had to test 'High-tech/low-tech' separate from each other, we have two control models and also two full models. Model 1 acts as basis model because it includes the control variables with the exception of the 'high-tech/low-tech' variable.. Model 2, in addition, includes the variable 'CEO gender' and is therefore seen as our full model. Model 3 also acts as base model, with the difference that the variables for measuring organizational size are replaced by the variable 'high-tech/low-tech'. Model 4 complements model 3 since it introduces the variable 'CEO gender'. The explanatory power with only the control variables is substantial. In addition, models that include the measures for organizational explain more of the variance in R&D intensity compared with models that contain the variable 'high-tech/low-tech'. In model 1 we find the variables LN-size, the squared term of LN-size and LN-tenure to be of significant importance. We observe a negative relation between innovation ratio and size, indicating that larger companies have a lower innovation ratio. The squared term of LN-size is positive, meaning that although initially negative, the relation between size and innovation ratio will eventually become positive for very large firms. LN-tenure also turned out to be of significance, there is a positive relation indicating that tenure positively influences the innovation ratio of a firm. Although not significant, CEO age showed to have a negative effect on the innovation ratio. Control model nr. 2 also found a significant positive influence of LN-tenure, while CEO age showed an insignificant positive relation. Furthermore, high-tech firms showed a significant higher innovation ratio, although not as significant as organizational size in model 1.
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positive effect on R&D intensity. Model 4, just like model 2, shows that LN-tenure has a positive influence and is also significant. CEO age seems to cause a higher R&D intensity, although not significant. High-tech firms have a significant higher R&D intensity. CEO gender has a somewhat negative influence on the innovation ratio, indicating that the commitment to innovation is a little higher for companies with a female CEO. This result is, however, far from significant. Somewhat remarkable is that models with the control measure for organizational size included show that companies with an older CEO seem to have a lower innovation ratio, while models that include the variable 'high-tech/low-tech' illustrate a positive effect of CEO age.
18 Figure 4.2
Results of regression analysis (OLS) with as dependent variable: innovation ratio (N=34)
Model 1: Control Model 2: Control Model 3: Full model Model 4: Full model Organizational size (LN) Beta -3.564*** -3.563***
B -7.797 -7.793 Std. error 1.439 1.463 Organizational size (LN) Squared term Beta 2.896*** 2.895*** B 0.177 0.177 Std. error 0.040 0.041
CEO tenure (LN) Beta 0.180* 0.452** 10.189* 0.466**
B 1.233 3.091 1.289 3.186
Std. error 0.645 0.950 0.688 1.015
CEO age (LN) Beta -0.061 0.067 -0.063 0.007
B -5.028 0.793 -5.187 0.540
Std. error 7.508 11.834 7.653 12.048
Low Tech / High Tech Beta 0.514*** 0.514***
B 7.728 7.734
Std. error 2.151 2.185
CEO Gender Beta -0.026 -0.044
B -0.375 -0.634
Std. error 1.382 2.127
R2 0.766 0.427 0.767 0.428
Adjusted R2 0.734 0.369 0.726 0.350
19 5. Discussion
The various regression models presented in figure 4.2 disclose some interesting outcomes. The most remarkable result is that there is no linkage found between gender and commitment to innovation. None of the models showed a significant influence of 'CEO gender'. A possible explanation for the trivial impact of CEO gender might be that the differences in risk-taking between men and women decreases as they get older (Byrnes et al., 1999). Since most executives are seasoned managers, the differences between a male and female might be larger in lower-level management where the average age lies lower.
The only CEO characteristic that significantly influenced commitment to innovation is 'CEO tenure', indicating that a CEO with longer tenure will exhibit more commitment to innovation. Strategic management literature suggest an inverted U-shaped relation between tenure and risk taking. On one hand it is believed that a higher tenure leads a CEO to take more risks since past experiences gathered in handling risks will lead to a lower perceived uncertainty considering these risks (Simsek, 2007). On the other hand, a high tenure may cause CEOs to commit to the status quo and fail to adapt to changing paradigms (Cyert and March, 1963). The positive influence of CEO tenure in our sample might be explained by the fact that the average CEO in our sample has served for only 3.5 years. The negative influence of CEO tenure on risk taking seems to take place when a CEO is in place for at least 10 years (e.g. Eitzen & Yetman, 1972; Hambrick & Fukutomi, 1991).
20
All firm characteristics play a significant role in explaining commitment to innovation. Organizational size and the fact whether a company could be classified as high-tech or as low-tech are strongly related. Organization size seems, however, to be the most important characteristic for explaining commitment to innovation. The relationship is negative, indicating that the larger an organization becomes the smaller the innovation ratio gets. We thus find that smaller companies spend relatively more money on R&D compared to larger businesses, which is a normal result since the innovation literature states that the R&D intensity and productivity for small firms is likely to be very high because of the relatively small workforce and low amount of capital invested (Globerman, 1975; Rothwell, 1978; Nooteboom, 1994). The squared term of organization size, on the other hand is positive, implying that the initial negative relationship between size and commitment to innovation turns positive at a given moment. Very large firms thus experience a positive relation between size and commitment to innovation. This result is conform literature findings that large firms are relatively more innovative in capital intensive industries (e.g. Damanpour, 1992; Audretsch et al., 1994; Shefer & Frenke, 2003). Furthermore, we find that high-tech companies have a significant higher commitment to innovation than low-tech companies, which is logical since R&D intensity is one of the main criteria used for distinguishing between the two groups (Von Tuzelman & Acha, 2005; OECD, 2011).
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6. Conclusion
6.1 Conclusion
These days, many firms devote a substantial amount of time and money to find the 'right' CEO for their company. Based on the 'upper echelon theory' of Hambrick & Mason (1984) the managerial influence on organizational outcomes and strategic choices is thought to be very high. In the wake of the economic crisis many companies appoint a female CEO in order to lower organizational risk taking. On the opposite, when more risk taking is needed companies would benefit from appointing a male CEO. We did not find evidence to support the hypothesis that a female CEOs is more risk averse compared with a male CEO. Furthermore, our results give reason to believe that the impact of a CEO on organizational outcomes might be overestimated. Especially in capital intensive industries organizational characteristics seemed of greater importance for elucidating organizational outcomes than CEO characteristics.
6.2 Implications
22 6.3 Limitations and possibilities for future research.
The main limitations of this study are data related. Only data from the year 2012 could be used because many female CEOs were appointed in 2011. Most studies use data from multiple years to avoid any discrepancies that might happen in one specific year. Furthermore, the sample size was quite small with only 34 companies included. If the increase of female CEOs in Fortune 1000 businesses will continue, future studies may be able to select a larger sample. Although related with the sample size, the currently used sample was forced to compare firms operating in a sometimes slightly different industry. Ideally we would compare two firms that have both the same 3-digit SIC code, the only difference being that one CEO is male while the other is female. Further research should therefore include a larger sample of female CEOs.
In order to generalize the conclusion for other organizational outcomes it is desirable to select an industry in which commitment to innovation is of vital importance. E.g. the biotech or pharmaceutical industry.
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References
Acs, Z. J. & Audretsch, D.B. "Innovation in Large and Small Firms: An Empirical Analysis." American
Economic Review, September 1988, 78(4), pp. 678-90.
Agars, M. D. (2004). Reconsidering the impact of gender stereotypes on the advancement of women in organizations. Psychology of Women Quarterly,28(2), 103-111.
Aggarwal, R. K., & Samwick, A. A. (2003). Why do managers diversify their firms? Agency reconsidered. The
Journal of Finance, 58(1), 71-118.
Arrow, K. J. (1965). Aspects of the theory of risk-bearing. Yrjö Jahnssonin Säätiö.
Audretsch, D. B., & Feldman, M. P. (1996). R&D spillovers and the geography of innovation and production. The American economic review, 86(3), 630-640.
Autos.com. Car insurance rates men vs women. [online] Available at: <http://www.autos.com/auto-insurance/car-insurance-rates-men-vs-women> [Accessed 1 June 2013].
Batjelsmit, V.L. & J. A. VanDerhei. "Risk Aversion and Retirement Income Adequacy." In Positioning Pensions for the Twenty-first Century, edited by M. S. Gordon, 0. S. Mitchell, and M. M. Twinney. Philadelphia: University of Pennsylvania Press, 1997, 45-66.
Bajtelsmit, V. L., Bernasek, A. & Nancy A. Jianakoplos. "Gender Differences in Defined Contribution Pension Decisions." Financial Services Review 8 (1999): 1-10.
Barker, V. L., III, & Mueller, G. C. 2002. CEO characteristics and firm R&D spending. Management Science, 48:782–801.
Barsky, R. B., Juster, F. T., Kimball, M. S., & Shapiro, M. D. (1997). Preference parameters and behavioral heterogeneity: An experimental approach in the health and retirement study. The Quarterly Journal of
Economics, 112(2), 537-579.
Baysinger, B., & Hoskisson, R. E. (1989). Diversification strategy and R&D intensity in multiproduct firms. Academy of Management Journal, 32(2), 310-332.
Bertrand, M. & Hallock, K.F.. 2001. “The Gender Gap in Top Corporate Jobs.” Industrial
24
Bhagat, S., Welch, I., 1995. Corporate research and development investments: International comparisons.
Journal of Accounting and Economics 19, 443–470
Bligh, M. C, Kohles, J. C, & Meindl, J. R. 2004. Charisma under crisis: Presidential leadership, rhetoric, and me dia responses before and after the September 11th ter rorist attacks. Leadership Quarterly, 15: 211-239.
Blum T. C Fields D. L., & Goodman, J. S. 1994. Organization level determinants of women in management.
Academy of Management Journal, 37: 241-268.
Brinig, M. F., & Crafton, S. M. (1994). Marriage and opportunism. The Journal of Legal Studies, 23(2), 869-894.
Bound, J., Cummins, C., Griliches, Z. Hall, B and Jaffe, A. "Who Does R&D and Who Patents?" in Zvi Griliches, ed., R&D, patents, and productivity. Chicago: University of Chicago Press
for the National Bureau of Economic Research, 1984, pp. 21-54.
Boyce, L. A., & Herd, A. M. (2003). The relationship between gender role stereotypes and requisite military leadership characteristics. Sex Roles, 49(7-8), 365-378.
Brenner, O. C., Tomkiewicz, J., & Schein, V. E. (1989). The relationship between sex role stereotypes and requisite management characteristics revisited. Academy of Management Journal, 32, 662–669.
Bromiley, P. (1991). Testing a causal model of corporate risk taking and performance. Academy of Management
Journal, 34(1), 37-59.
Brun-Gulbranden, S., & As, B. (1973). Kjonnsroller og uly kker. InW. T. Singleton & J. Hovden (Eds.), Risk and decisions. New York: Wiley
Businessinsider, 2012. The 10 riskiest tech business decisions. [online] Available at: <http://www.businessinsider.com/the-10-riskiest-tech-business-decisions-2012-7?op=1> [Accessed 2 June 2013].
Burke, R. J., & Mattis, M. C. (2000). Women on corporate boards of directors: International challenges and
opportunities (Vol. 14). Kluwer Academic Pub.
Bushee, B. 1998. The influence of institutional investors on myopic R&D investment behavior. The Accounting
Review73 (3): 305-333
25
Carter, D., Simkins, B., Simpson, W., 2003. Corporate governance, board diversity, and firm value. Financial Review 38, 33-53.
Catalyst, 2013. Women CEOs of the Fortune 500. [online] Available at:
<http://www.catalyst.org/knowledge/women-ceos-fortune-500> [Accessed 14 May 2013].
Chaganti, R., R. Sambharya. 1987. Strategic orientation and characteristics of upper management. Strategic
Management Journal. 8 393401.
Cohen, W., Nelson, R., Walsh, J., 2002. Links and impacts: the influence of public research on industrial R&D.
Management Science (January)
Cremers, M., & Grinstein, Y. (2009). The market for CEO talent: Implications for CEO compensation. Unpublished working paper. Yale University.
Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ, 2.
Daellenbach,U . S., A. M. McCarthy, T. S. Schoenecker. 1999. Commitment to innovation: The impact of top management team characteristics. R& D Management.29 199-209.
Daly, M., & Wilson, M. (1988). Homicide. Aldine de Gruyter.
Danilda, I. and Granat Thorslund, J. (eds) (2011), “Innovation & Gender”, Vinnova, Sweden. [online] Available at: <http://www.vinnova.se/upload/EPiStore PDF/vi-11-03.pdf> [Accessed 20 May 2013].
Damanpour, F. (1992). Organizational size and innovation. Organization studies, 13(3), 375-402.
De Vries, M. F. K., & Miller, D. (1986). Personality, culture, and organization. Academy of Management
Review, 11(2), 266-279.
Dewar, R.D., & Dutton, J.E., 1986 "The adoption of radical and incremental innovations: An empirical analysis." Management Science, 32: 1422-1433.
Drucker, P.F., 1985. The discipline of innovation. Harvard Business Review. 63, 67 – 72 (May/June)
Eagly, A. H., & Johnson, B. T. (1990). Gender and leadership style: A meta-analysis. Psychological
26
Eagly, A. H., Makhijani, M. G., & Klonsky, B. G. 1992. Gender and the evaluation of leaders: A meta-analysis.
Psychological Bulletin, 111: 3-22.
Eagly, A. H., & Karau, S. J. (2002). Role congruity theory of prejudice toward female leaders. Psychological
review, 109(3), 573.
Eckel, C. C., & Grossman, P. J. (2002). Sex differences and statistical stereotyping in attitudes toward financial risk. Evolution and Human Behavior,23(4), 281-295.
Eitzen, D. S., & Yetman, N. R. (1972). Managerial change, longevity, and organizational effectiveness. Administrative Science Quarterly, 110-116.
Elston, J. A., & Goldberg, L. G. (2003). Executive compensation and agency costs in Germany. Journal of
Banking & Finance, 27(7), 1391-1410.
Emrich, C. G. 1999. Context effects in leadership perception. Personality and Social Psychology Bulletin, 25: 991-1006.
Friend, I. & Blume, M.E. "The Demand for Risky Assets." American Economic Review (December 1975): 900-22.
Forbes, 2012. Introducing the new class of female CEOs. [online] Available at: <http://www.forbes.com/sites/carolinehoward/2012/08/22/introducing-the-new-class-of-female-ceos/>
[Accessed at 15 May 2013].
Furst, S. A., & Reeves, M. (2008). Queens of the hill: Creative destruction and the emergence of executive leadership of women. The Leadership Quarterly,19(3), 372-384.
Flynn, J., Slovic, P., & Mertz, C. K. (1994). Gender, race, and perception of environmental health risks. Risk
analysis, 14(6), 1101-1108.
Gabaix, X., & Landier, A. (2008). Why has CEO pay increased so much?. The Quarterly Journal of
Economics, 123(1), 49-100.
Geary, D. C. (1998). Male, female: The evolution of human sex differences (p. 110). Washington, DC: American Psychological Association.
Globerman, S. (1975). Technological diffusion in the Canadian tool and die industry. The review of economics
27
Goodstein J, Boeker W. 1991. Turbulence at the top: a new perspective on governance structure changes and strategic change. Academic Management Journal. 34:306-30
Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of management review, 193-206.
Hambrick, D. C., & Fukutomi, G. D. (1991). The seasons of a CEO's tenure. Academy of Management Review, 719-742.
Heilman, M. E. (1983). Sex bias in work settings: the lack of fit model. Research in Organizational Behavior, 5, 269 – 298.
Heilman, M. E., Block, C. J., Martell, R. F., & Simon, M. C. (1989). Has anything changed? Current characterizations of men, women, and managers. Journal of applied psychology, 74(6), 935.
Hersch, J. (1996). Smoking, seat belts, and other risky consumer decisions: Differences by gender and race. Managerial and Decision Economics, 17(5), 471-481.
Hersch, J. (1998). Compensating differentials for gender-specific job injury risks. The American Economic
Review, 88(3), 598-607.
Hinz, Richard P., David D. McCarthy, and John A. Turner. "Are Women Conservative Investors? Gender
Differences in Participant-Directed Pension Investments." In Positioning Pensions for the Twenty-First Century,
edited by M. S. Gordon, 0. S. Mitchell, and M. M. Twinney. Philadelphia: University of Pennsylvania Press, 1997, 91-103.
Hoskisson, R. E., Hitt, M. A., & Hill, C. W. (1993). Managerial incentives and investment in R&D in large multiproduct firms. Organization Science, 4(2), 325-341.
Jianakoplos, N. & Bernasek, A. "Are Women More Risk Averse?" Economic Inquiry 36 (October 1998): 620-630.
Joy, L., Carter, N. M., Wagner, H. M., & Narayanan, S. (2007). The bottom line: Corporate performance and women’s representation on boards. Catalyst, 3.
Khan, W.A. & Vieto, J.P., 2013. Ceo gender and firm performance. Journal of Economics and Business. In press, [online] Available at: <http://dx.doi.org/10.1016/j.jeconbus.2013.01.003
28 Kothari, S. P., Laguerre, T. E., & Leone, A. J. (2002). Capitalization versus expensing: Evidence on the uncertainty of future earnings from capital expenditures versus R&D outlays. Review of accounting Studies, 7(4), 355-382.
Krishnan, H. A., & Park, D. (2005). A few good women on top management teams. Journal of Business
Research, 58, 1712–1720. doi:10.1016/j.jbusres.2004.09.003
Levy, H., Elron, E., & Cohen, A. (1999). Gender differences in risk taking and investment behavior: An experimental analysis. Unpublished manuscript, The Hebrew University.
Ling, Y., Simsek, Z., Lubatkin, M. H., & Veiga, J. F. (2008). The impact of transformational CEOs on the performance of small-to medium-sized firms: Does organizational context matter?. Journal of Applied
Psychology, 93(4), 923.
Lofstrom (2009) Gender equality, economic growth and employment. Umea: Department of Economics, Umea University.
Low, B. S. (2001). Why sex matters: A Darwinian look at human behavior. Princeton University Press. Mansfield, E. (1969). The economics of technological change (Vol. 120). Longmans.
March, J. G., & Shapira, Z. (1987). Managerial perspectives on risk and risk taking. Management
science, 33(11), 1404-1418.
Mark, M., Katz, B., Rahman, S., and Warren, D., 2008. MetroPolicy: Shaping A New Federal Partnership for a
Metropolitan Nation. Brookings Institution: Metropolitan Policy Program Report. P 4-103.
Millward, L.J. and Freeman, H. (2002) ‘Role expectations as constraints to innovation: the case of female managers’, Creativity Research Journal, 1532-6934, Vol. 14, No. 1, pp.93–109.
Munson, F.C. and D.C. Pelz (1979), The Innovating Process: A Conceptual Framework, Working Paper, University of Michigan
Niessen, A., & Ruenzi, S. (2006). Sex matters: Gender differences in a professional setting (No. 06-01). CFR Working Paper.
Nooteboom, B. (1994). Innovation and diffusion in small firms: theory and evidence. Small Business
Economics, 6(5), 327-347.
29
Olgiati, E and Shapiro, G 2002. Promoting Gender Equality in the Workplace European
Foundation for the Improvement of Living and Working Conditions, Luxembourg.
Palsson, A. M. "Does the Degree of Relative Risk Aversion Vary with Household Characteristics?" Journal of
Economic Psychology 17: 1996.
Palvia, A., Peni, E., & Vähämaa, S. (2009). Do Female CEOs and Chairs Constrain Bank Risk-Taking? Evidence from the Financial Crisis. risk, 174(7), 13.
Pillai, R., & Meindl, J. R. 1998. Context and charisma: A meso level approach to the relationship of organic structure, collectivism and crisis to charismatic leadership. Journal of Management, 24: 643-671.
Porter, M. (1998). Clusters and competition: New agendas for companies, governments, and institutions. In M. Porter, On competition (pp. 197-287). Boston: Harvard Business School Press
Pol, E, Carroll, P, 2005, An introduction to the Creative Economy, McGraw-Hill, Australia
Powell, G. N. (1990). One more time: Do male and female managers differ? Academy of
Management Executive, 12, 731-743
Powell, G.N., 1999. Handbook of Gender & Work, Thousand Oaks, California: Sage P.651
Pratt, J. W. (1964). Risk Aversion in the Small and in the Large. Econometrica: Journal of the Econometric
Society, 122-136.
Ross, S. A. (1981). Some stronger measures of risk aversion in the small and the large with applications. Econometrica: Journal of the Econometric Society, 621-638.
Rothwell, R. (1978). Small and medium sized manufacturing firms and technological innovation. Management
Decision, 16(6), 362-370.
Rothwell, R. & Zegveld, W., 1982. Innovation and the Small and Medium Sized Firm. University of Illinois at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship. Available at SSRN: http://ssrn.com/abstract=1496714
Rothwell, R. (1984). The role of small firms in the emergence of new technologies. Omega, 12(1), 19-29.
30
Ryan, M. K., & Haslam, S. A. (2007). The glass cliff: Exploring the dynamics surrounding the appointment of women to precarious leadership positions. Academy of Management Review, 32(2), 549-572.
Schein, V. E. 1973. The relationship between sex role stereotypes and requisite management characteristics.
Journal of Applied Psychology, 57: 95 - 100.
Schein, V. E. (1975). Relationships between sex role stereotypes and requisite management characteristics among female managers. Journal of applied psychology, 60(3), 340.
Schein, V. E., & Mueller, R. (1992). Sex role stereotyping and requisite management characteristics: A cross cultural look. Journal of Organizational Behavior, 13(5), 439-447.
Scherer, F. (1984). Using linked patent and R&D data to measure inter-industry technology flows. In R & D,
Patents, and Productivity (pp. 417-464). University of Chicago Press.
Scherer, F. M., & Ross, D. (1990). Industrial market structure and economic performance. University of Illinois
at Urbana-Champaign's Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.
Schubert, R., Brown, M., Gysler, M., & Brachinger, H. W. (2000). Gender specific attitudes towards risk and
ambiguity: an experimental investigation. Institut für Wirtschaftsforschung, Eidgenössische Technische
Hochschule.
Schumpter, J.A., 1943. Capitalism, Socialism, and Democray (6th ed.). Routledge. P. 81-84.
Shefer, D., & Frenkel, A. (2005). R&D, firm size and innovation: an empirical analysis. Technovation, 25(1), 25-32.
Simsek, Z. (2007). CEO tenure and organizational performance: an intervening model. Strategic Management
Journal, 28(6), 653-662.
Singh, J. V. 1986. Performance, slack, and risk taking in organizational decision making. Academy of
Management Journal, 29: 562 - 585.
Singh, V., & Vinnicombe, S. 2003. The 2003 Female FTSE Index. Women Pass a Milestone: 101 Directorships
on the FTSE 100 Boards. London: Cranfield School of Managent
31
Spigner, C., Hawkins, W. E., & Loren, W. (1993). Gender differences in perception of risk associated with alcohol and drug use among college students. Women & health, 20(1), 87-97.
Smith, N., Smith, V., & Verner, M. (2006). Do women in top management affect firm performance? A panel study of 2,500 Danish firms. International Journal of Productivity and Performance Management, 55(7), 569-593.
Terjesen, S., R. Sealy and V. Singh, 2009, ‘‘Women directors on corporate boards: A review and research
agenda’’. Corporate Governance: An International Review, 17(3): 320–337
Thomas, A. S., R. J. Litschert, K. Ramaswamy. 1991. The performance impact of strategy-manager-co alignment: An empirical examination. Strategic Management Journal. 12 509-522.
Von Tunzelmann, N., & Acha, V. (2005). Innovation in ‘low-tech’industries. The Oxford handbook of
innovation, 407-432.
32
Appendix
Figure 1
Sizes high-tech and low-tech
Industry classification N Mean Std. Deviation Sigma (2-tailed)
Low-tech 12 2731631104,33 5106087678,290 0.845 High-tech 22 3267476485,55 8619754203,916 0.845
* p<0.05 **p<0.01 ***p<0.001
Figure 2
Innovation ratio: high-tech vs. low-tech
Industry classification N Mean Std. Deviation Sigma (2-tailed)
Low-tech 12 0.7612% 0.56043% 0,05*
High-tech 22 7.8680% 8.04888% 0,05*
* p<0.05 **p<0.01 ***p<0.001
Figure 3
Innovation ratio: young CEO vs. older CEO
CEO Age N Mean Std. Deviation Sigma (2-tailed)
≤ 55 17 7,3619% 9,10020% 0,111
> 56 17 3,3575% 4,29227% 0,111
