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Culture, Gender, and GMAT Scores: Implications for Corporate Ethics

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Abstract

Business leadership increasingly requires a master’s degree in business and graduate management admission test (GMAT) scores continue to be an important component of applications for admission to such programs. Given the ubiquitous use of GMAT scores as gatekeepers for business leadership, GMAT scores are likely to influence organizational ethical behavior through gender, cultural, and other biases in the GMAT. There is little prior literature in this area and we contribute by empirically documenting that GMAT scores are negatively related to the cultural dimensions of masculinity and power distance and are positively related to math literacy, uncertainty avoidance, and individualism. We estimate that cultural factors may account for as much as an 80-point difference in cross-national mean GMAT scores which are also related negatively to local language literacy, national educational spending, wealth per capita, wealth inequality, and gender development. Most interestingly, we also find a significant negative association of GMAT scores with ethical orientation. These findings have important implications for business schools and corporate ethics and leadership.

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Notes

  1. While there has been some controversy in the past, the effectiveness of the GMAT score as a predictor of academic success has recently been reaffirmed (Kuncel et al. 2007).

  2. According to the Graduate Management Admissions Council (GMAC), over a quarter million applicants globally now take the GMAT exam every year, with about 40 % being women and a quarter located outside the United States.

  3. www.mba.com, accessed September 2010.

  4. Oh et al. (2008) re-examine Kuncel et al. (2007) and find that Kuncel et al. (2007) underestimate the validity of the GMAT as a success predictor by 7 %.

  5. Given the extensive literature on test bias (e.g., Berk 1982; Jensen 1980; Reynolds and Brown 1984), it is reasonable to expect test publishers to incorporate controls for bias into their test development procedures as a matter of course; so that obvious biases are not evident. Nevertheless, in this section we consider a number of possible biases related to the GMAT.

  6. They find the written component of the GMAT has little predictive value.

  7. In this regard, Clark et al. (2009) find evidence of a selectivity bias in college admission tests across US states. They find that SAT scores are biased based on whether the ACT or the SAT is the dominant test in a state. If the SAT is not dominant, average scores will be generally higher because students interested in out-of-state education will take both the ACT and SAT.

  8. The question of testing bias versus selectivity bias is important to this study. In this study we are implicitly assuming that populations of GMAT test takers in respective countries are reflective of their respective national cultures. While some research has suggested that gender may influence national culture (e.g., Stedham and Yamamura 2004), we note in this regard that Hofstede (1980) and Hofstede (2001) conclude that cultural dimensions do not differ by gender.

  9. An exception is perhaps Sireci and Talento-Miller (2006).

  10. We measure cultural distance from the United States, rather than another country because the GMAT is designed and implemented by a United States organization, has the largest number of test takers in the US, and is used by the largest number of institutions in the US.

  11. In other models we also investigate distances along each cultural dimension singularly. Again these distances from the US are not significant. We also have investigated the cultural distance from a weighted basket of English-speaking countries. Again, while the dummy variable for native English speaker is significant, cultural distance is not.

  12. Because they have been orthogonalized, we are able to include both RESID_MATH and RESID_READING in the same with less variance inflation than including MATH and READING in the same model.

  13. Of course the actual impact of all four cultural dimensions could be considerably larger or smaller depending on the country-specific combination of the estimates of all four cultural dimensions.

  14. As noted by prior studies, the residuals in the first equation may result from an incompletely specified model, and so when variables are estimated from estimated residuals, estimated findings can lose accuracy (Pagan 1986). Substituting the residuals from a first equation is an example of what Pagan (1984) classifies as a type-two generated regressor. Such models with “generated regressors” may lead to uncertainties in interpretation (Oxley and McAleer 1993). However, we consider the use of the orthogonalization procedure in this context to be a reasonable trade-off to reduce multicollinearity.

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Acknowledgments

The authors are grateful to Kenneth Brown, Mary Funck, Pawan Jain, Debmalya Mukherjee, Janet Murray, Gabriele Suder, anonymous reviewers and others for useful comments, but remain solely responsible for the contents.

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Authors and Affiliations

  1. Sullivan Professor of International Business and Finance, University of Akron, Akron, OH, 44325, USA

    Raj Aggarwal

  2. College of Education and Human Services, Cleveland State University, Cleveland, OH, 44115, USA

    Joanne E. Goodell

  3. College of Business Administration, University of Akron, Akron, OH, 44325, USA

    John W. Goodell

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  1. Raj Aggarwal
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Table 7 Pearson correlation coefficients
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Aggarwal, R., Goodell, J.E. & Goodell, J.W. Culture, Gender, and GMAT Scores: Implications for Corporate Ethics. J Bus Ethics 123, 125–143 (2014). https://doi.org/10.1007/s10551-013-1800-5

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