how group gender composition affects levels of risk taking

how group gender composition affects

levels of risk taking

Bing Liu s2094126

HRM & Master Thesis

Abstract

Introduction

This research examines one aspect of “Lehman Sisters hypothesis”, namely that having more women in financial decision making board will reduce excessive risk taking. Especially for today, women are more involved in the labour market and operate more often in corporate boards. As a result, highest level decision-making teams are more likely to be characterized by some gender diversity. Therefore, gender differences have gained a lot of attention because of the increasing participation of women in business and investment decisions. For example, in US the female civilian labour force has increased by 74% since 1975, and there are more women in the work force than ever before (Bureau of Labour Statistics Data, 2000). As women enter the work force in greater numbers, they will likely be participating more at all levels of organizations; work groups will become more gender-balanced, and gender-based segregation in organizations will decrease (Jackson et al., 1995; Wood, 1987).

Given more gender diversity in the workforce, also teams have become increasingly diverse with regard to gender. Although much research has examined gender diversity and its effects on team and organizational outcomes (Kanter,1977), few studies have looked at how team gender composition may affect risk taking behaviour. There are, however, reasons to assume that gender composition will affect risk taking of a team. In fact, psychological studies have found that females find risky situations more stressful than males do (Kerr & Vlaminkx, 1997). Young males especially will be more willing to take risks in an effort to breed successfully than young females. In species like humans where risk-taking may itself become a form of display, this sex difference may be exaggerated and risk-taking may characterize many aspects of behavior. Many studies have noted that young human males are more prone than females to take risks in relation to conflict (Campbell, 1999; Daly & Wilson, 1988; Wilson & Daly, 1993) and have found sex differences in risk-taking in our daily life, such as car driving, smoking, but also in gambling and financial decisions (Bruce & Johnson, 1994, Powell & Ansic, 1997). Given that women are less risk-taking than men, it seems possible that more gender-diverse teams are less likely to take excessive risks than homogeneous male teams. However, this possibility has, to our knowledge not been explored in research.

meta-analysis by Wood (1987) showed that mixed gender groups tended to perform better than same gender groups because of gender differences in group behaviour—men tend to offer opinions and suggestions during group tasks, whereas women tend to act friendly and agree with others. There is thus a need to examine the implications of gender diversity on work groups. This research will more specifically focus on the question of how gender diversity within teams relates to risk taking.

Theory

Risk-taking behaviours are those that involve some potential for danger or harm while also providing an opportunity to obtain some form of reward (Leigh, 1999). Risk taking encompasses positive or negative possibilities and the consequences of any risk taking are quite clear: (a) the behaviour in question could lead to more than one outcome and (b) some of these outcomes are undesirable or even dangerous (Furby & Beyth-Marom, 1992). In essence, risk taking involves the implementation of options that could lead to negative consequences.

Individual differences, in the form of demographics, psychological traits, and even physiology, and their impacts on the levels of risk taking have long been recognized and researched. Strong evidence from previous research showed that men are more inclined to take risks than women(Kogan,1978) Decision making, especially under uncertainty situation , is a complex mental process given that both cognitive and emotional factors are involved (Loewenstein,2001]. For instance, two experiments investigated gender differences in risk taking behavior, using a computerized military game. It was found that females showed lower risk preference than males when subjects repeated a previously undertaken task(Hudgens, 1985). It was also found that female entrepreneurs are less willing than male entrepreneurs to become involved in situations with uncertain outcomes. In contrast, under the uncertainty, men tend to be evaluated more positively than women for task performance (e.g., Craig & Sherif, 1986; Fairhurst & Snavely, 1983; Ott, 1989; Sackett, Dubois, & Noe, 1991). Men tend to be more dominant, task oriented, risk taking and less friendly than women (Larissa,2005).

Pattern 2 would consist of varying gender differences across contexts, but the distribution of effect sizes would include only zeros and positive values (i.e., it would be men who take more risks when gender differences occur). Pattern 3 would be a distribution of effect sizes that includes a full range of values (i.e., negatives, positives, and zeros).When people move from one context to another, however, they generally hold different expectations and values. As a result, gender differences would vary by context and that some contexts would promote greater risk taking. For example, if there was reason to believe that women might feel more confident in a particular situation than men, and it mattered more to women to be successful in that situation, expectancy-value models would support an expectation of greater risk taking on the part of women. As result, women usually takes less risk than men, but in some certain situations, women may also take high level of risk.

However, studies on gender differences impacting on risk taking have most commonly been done at the individual level, but with modern economies developing, gender diversity at most levels of organization is increasing. It is also goal of this paper to examine how the group gender composition affects the levels of risk taking of groups. This has not been done before by previous research. Most previous studies worked on the relationship between gender differences and team performance and how gender diversity influence decision making. Some evidence indicates that gender diversity may be disadvantageous, with mixed gender groups not necessarily performing as well as single gender groups (Maznevski, 1994). Some other investigations indicate that an increase in gender diversity may enrich management in organizations (Kanter, 1977a; Rigg and Sparrow,1994) Consequently, it is informative to reflect on the outcomes of diversifying the gender mixes of teams in the workplace and the effectiveness for decision making.

Previous studies have shown that gender composition of groups will affect the effectiveness of women in groups. Therefore, we aim to examine whether gender composition affects the level of risk taking for groups with a female majority and those with a female minority. Given the higher levels of risk taking of men as compared to women, we expect homogeneous groups of men to be more risk taking than homogeneous groups of women. However, given that women who are in a minority often have little influence, we expect that groups with a female minority are similar in risk taking as homogeneous groups of men. When women are in the majority, we expect that risk taking will be lower. However, given that men in a minority position still often have some influence, we expect that risk taking in female majority groups will be higher than in homogeneous groups of women. Thus, we predict:

The relationship between proportion of women in a group and level of risk taking is negative and non-linear. Specifically, groups with only men and groups with a female minority are more risk taking than groups with a female majority, and groups with a female majority are more risk taking than groups with only women.

In our research, we examine how gender composition affects risk taking in three-person groups. In these group, four types of gender composition are designed as A (3, 0) represents a group with 3-male and 0-fe3-male members; B (2, 1) represents a group with 2-3-male and 1-fe3-male members; C (1, 2) represents a group with 1-male and 2-female members; and D (0, 3) represents a group with 0-male and 3-female members. Our hypothesis entails that the level of risk taking in group (3,0) and (2,1) groups is similar and higher than the group (2,1) and group (0,3).

Methods

Participants

Experimental Task: The BART

Participants played the Balloon Analogue Risk Taking Task (BART), in their 3-person group. The BART is a computerized, laboratory-based measure that involves actual risky behaviour for which, similar to real world situation. The development and validation of this measure represent a first step in the establishment of a behavioural task that can be used as assessment of risk-taking propensity (Leiuez,2002). The BART was conducted in experimental room including a desk supporting a computer with colour monitor and a mouse.

The BART was designed to provide a context in which actual risky behavior could be examined. The BART was presented on the computer in the experimental room. Specifically, the computer screen showed a small simulated balloon accompanied by a balloon pump, a reset button labelled Collect

$$$,a permanent money-earned display labelled Total Earned, and a second display listing the

money earned on the last balloon and labelled Last Balloon (see Figure 1).

Each click on the pump inflated the balloon. With each pump, 5 cents were accrued in a temporary reserve (the amount of money in this reserve is never indicated to the participant). When a balloon was pumped past its individual explosion point, a “pop” sound effect was generated from the computer. When a balloon exploded, all money in the temporary bank was lost, and the next uninflated balloon appeared on the screen. At any point during each balloon trial, the participant could stop pumping the balloon and click the Collect $$$ button. Clicking this button would transfer all money from the temporary bank to the permanent bank, during which the new total earned would be incrementally updated cent by cent while a slot machine payoff sound effect played. After each balloon explosion or money collection, the participant’s exposure to that balloon ended, and a new balloon appeared until a total of 30 balloons had been completed. Participants were given no detailed information about the probability of an explosion. They were told that at some point each balloon would explode and that this explosion could occur as early as the first pump all the way up to the point at which the balloon had expanded to fill the entire computer screen.

Figure 1: Diagram of the balloon risk task Press to

collect $$$ Press this button to pump up _{the ballon}

Total earned:

Procedure

Participants registered at different timeslot through our research lab system. There were three participants in one timeslot. Groups were scheduled for a half-hour session during 3 weeks. The purpose of the experiment was described as decision making in the lab website so that the participants learned about our experiment before they came.

Participants came to the lab at the scheduled time. They first read and signed the consent form. We directed the three participants to enter the lab room, where they sat around the table. Each place at the table was clearly marked with a group member identification (A, B, or C). Then participants were informed that they would first complete personality questionnaire with 40 questions, that they would next play the BART, and would finally complete a second questionnaire.

After completing the personality questionnaire, in which we assessed each participant’s level of sensation seeking, participants were instructed about the BART. Participants learned that the three groups with the highest earnings on the balloon task would actually be awarded the money they earned. The BART was thoroughly explained with a visual depiction of the task accompanied by verbal instructions. Participants learned that during the task, they would be presented with 30 balloons, one at a time. For each balloon, participants could click on the button labelled “Press This Button to Pump Up the Balloon” to increase the size of the balloon. Then 5 cents went to a temporary bank for each pump. At any point, participants could stop pumping up the balloon and click on the button labelled “Collect $$$.” Clicking this button would start the next balloon and would transfer the accumulated money from the temporary bank to the permanent bank labelled “Total Earned.” The amount earned on the previous balloon was shown in the box labelled “Last Balloon.” Participants could determine how often to pump up the balloon, but were aware that at some point the balloon would explode. The explosion point varied across balloons, ranging from the first pump to enough pumps to make the balloon fill the entire computer screen. If the balloon exploded before clicking on “Collect $$$,” then the next balloon would appear and all money in the temporary bank was lost. At the end of the task, Participants could only see how much in total they had earned.

Measures

Number of pumps

A first measure of risk taking consists of the total number of times each balloon was pumped. Although pumping up a balloon more often will potentially earn more money, it also increases the chance that a balloon would explode. We collected the number of pumps for the first, second, and third series of ten balloons, to be able to track risk-taking over time.

Number of balloons exploding

A second measure of risk taking consists of the number of exploded balloons. Excessive risk taking implies that relatively many balloons will explode. We collected data on exploded balloons for the first, second, and third series of ten balloons.

Total money earned

The final measure derived from the BART was the total amount of money earned. More money will be earned when groups do not take excessive risks.

Questionnaire data

Before completing the BART, we administered the 40-item Sensation Seeking Scale (Zuckerman et al., 1978), which includes questions focusing on thrill and adventure seeking, experience seeking, disinhibition, and boredom susceptibility. For each item, the participant had to make a forced choice between two options. An example item is ‘I like wild uninhibited parties’ versus ‘I refer quiet parties with good conversation’. The number of times an answer was chosen that reflects high sensation seeking was counted to arrive at a composite measure of sensation seeking.

Results

Gender differences in risk taking and influence

To test the assumption that men would be more inclined to take risks than women, we conducted two-way ANONA, with gender and gender composition as independent variables, and peer ratings of risk taking as the dependent variable. It should be noted that, of course, no ratings of women in the MMM condition or of men in the FFF condition can be analysed (see Table 1)

Table 1. Means and standard deviations of risk taking in the different conditions

Gender Gender composition MMM MMF MFF FFF Male Female 4.92(1.59) --- 5.45(1.03) 4.39(1.13) 4.92(1.12) 4.57(1.25) ---- 5.11(1.02)

This analysis showed a main effect of gender on risk taking, F(1,210) = 5.06, p = .016. Men (M = 5.00) were perceived to be more risk taking than women (M = 4.81). There was a main effect of gender composition as well, F(3,210) = 3.23, p = .023. Surprisingly, post hoc tests (LSD) showed that risk taking in FFF groups (M = 5.11) was higher than risk taking in MFF groups (M = 4.69). The interaction was not significant, F (1, 210) =0 .79…, p = .38. In sum, this analysis showed that, as expected, men are more inclined to take risks than women in the BART, but that the level of risk taking in all female groups was surprisingly high.

Table 2 Means and standard deviations of influence in the different conditions

This analysis showed that men were not be more influential in mixed gender groups than women F(1,210)= 1.26 p=.26. The effect of gender composition F(3,210)=0.78 p=.51 was not significant. The interaction was not significant, F (1, 210) = 0.03, p = .88. In sum, this analysis showed that, contrary to expected, men are not more influential in mixed groups than women.

Gender composition and BART performance

Based on the first hypotheses, we expected that groups with only men (MMM) and groups with a female minority (MMF) would be more risk taking than groups with a female majority, and that groups with a female majority would be more risk taking than groups with only women. In order to test this hypothesis, we conducted one way ANOVAs on total earnings, total number of pumps and total numbers of exploded balloons (see Table 3 )

Table 3. Means and standard deviations for BART measures in the different conditions

Measure Condition MMM MMF MFF FFF Total earning Total pumps Total explode 36.23 (10.97) 920.25 (303.75) 8.75 (1.71) 35.26 (13.77) 895.57 (399.71) 8.00 (3.35) 29.97 (9.58) 775.00 (298.37) 7.90 (2.73) 31.76 (9.02) 835.74 (274.59) 8.96 (2.69)

no effect of gender composition on total earnings F(3,68) = 1.07, p=.37. Further, a one way ANOVA was performed with gender composition as the independent variable and total number of pumps as the dependent variable. The result of this analysis showed no effect of gender composition on total number of pumps F(3,68) = 0.63, p = .60. Finally, a one way ANOVA was performed with gender composition as the independent variable and number of exploded balloons as the dependent variable. The result of this analysis showed no effect of gender composition on total number of exploded balloons, F(3.68) = 0.71, p = .55. Thus, the hypothesis of group with only men and group with a female minority are more risk taking than group with a female majority, and groups with a female majority are more risk taking than groups with only women was not confirmed.

Discussion

The goals of our research was to examine the effects of gender composition on risk taking in small groups. We predicted that men would be more inclined to take risks than women, and examined whether groups with only men and groups with a female minority would be more risk taking than groups with a female majority, and that groups with a female majority would be more risk taking than groups with only women. We conducted a lab experiment to test our predictions. The Balloon Analogue Risk Taking Task (BART) was used to examine risky behaviour in our experiment. It is a computerized, laboratory based and validated measure that involves actual risk behaviour. The BART consists of 30 trials, in which the group was asked to pump up balloons. Although each additional pump earns more money, it also increases the risk that the balloon explodes, in which case all money for that trial is lost.

One reason for the lack of results on the BART is that we found little evidence for excessive risk taking in our study. The level of risk taking for men lies on average level. For example, for only men (MMM) groups, total earning were not extreme (M=36.23) and neither were total number of exploded balloons (M=8.75). The average explode number is only 8.75 by pumping up 30 balloons which means they are not preferring to taking excessive risk for more earning and only reserve the balloon not exploding. Actually, the number of exploded balloons is positively correlated with total earnings, so they were not taking too much risk. The people in the group were not pumping the balloon enough and tried to keep the number of exploding as lower as possible for money earning. From the aspect of participants’ attitude, we also found that some students were not motivated to do the experiment and treated it not seriously enough.

Additionally, we found that the level of risk taking in all female groups(FFF) was surprisingly higher than that in MFF groups. We had assumed the only women group may prefer to the least risk taking than other gender composition, but in fact, from the total number explode and total pumps in BART experiment, only the women group conducted the higher number than MFF group. If a group is formed only by women, they can be more concentrated on pumping and exploding the balloons and do not need to consider the voice from the different gender. The only women group may be more aggressive than women group with men involved. The only women group may feel more relaxed and make their decision without any hesitation or consideration. Like a saying in China, if three women come together, they can play a drama. The communication among themselves could be more open and creative.

psychological factor of men of this instance could be the weight of the issue on their minds. Men may not offer opinions to the group if the consequence is not essential to them. They would rather follow or keep silence. The extent of men’s influence mostly depends on the situational factors.

Even though we have 72 groups in total, but only have 4 MMM groups and 14 FFM groups. The number of male groups actually is not enough for our analysis. More MMM and FFM groups could be required for further research. Larger groups could also eliminate the special cases and extend the generality of the finding. Secondly, the samples of students are all non-experience in workplace and their English skills are also at different levels. Some students are not motivated to treat the experiment seriously. In the further study, the sample could be collected from experienced bankers in financial institutions and the data would be more trustable and reliable. Thirdly, the BART experiment task is used for our research to find excessive risk taking, but the result was not able to be seen. Apparently, we cannot reach the goal by using BART task and another experiment task has to be considered in the future study.

Conclusion

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