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Female owners versus female managers: Who is better at introducing innovations?

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Abstract

This paper uses firm-level survey for more than 100 countries to examine whether firms’ female managers or female owners were better at bringing innovations to the market than males. In contrast to most of the literature that focuses on the performance of female managers/owners, this paper addresses conduct with regard to innovation. Results show that female owners, rather than female managers, were more likely to introduce innovations. Further, R&D performing firms introduced innovations, as did larger and older firms. The presence of an informal sector and finance availability constraints actually spurred innovation introductions, with economic prosperity leading to complacency in innovation introductions.

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Notes

  1. Using information on more than 25,000 faculty members, Leakey and Blume (2017) try to determine the reasons for lower patenting by female academics. The authors find the institutional context to be crucial in explaining the patenting behavior of female academics.

  2. This interpretation is backed by the prominent “Study on the Status of Women Faculty in Science at Massachusetts Institute of Technology”, which documents pervasive gender inequalities in access to the strategic resources of the Institute (http://web.mit.edu/fnl/women/women.html).

  3. To be precise, the dependent variable in Dezsö and Ross (2012) is Tobin’s Q, with innovation intensity and female management representation as key explanatory variables.

  4. Also see Masser and Abrams (2005).

  5. Another dimension is the difference in innovative versus imitative approaches across developed and developing nations (see Koellinger 2008).

  6. Along another dimension related to research inputs, Pfeifer and Wagner (2014) find that firms with a higher share of female employment in German manufacturing were more active in R&D. Furthermore, given that performance may be measured along various dimensions, Robb and Watson (2012) find no performance difference across male- and female-owned new ventures in the United States, when performance was evaluated more broadly (i.e., not directly related to R&D or innovation).

  7. One should keep in mind that there are other related dimensions like patent quality and invention disclosures (not necessarily patenting, that are also important but, given the detail in the underlying survey data, are not considered here. For example, Muñoz and Graña (2016) focused on patent quality and found that the quality of patents in Spain was higher when R&D teams had gender diversity. Furthermore, examining the behavior of more than 4500 academics across universities, Thursby and Thursby (2005) found that women were less likely to disclose inventions than men, even though there were no significant gender differences in publication patterns. However, the disclosure activity of women and men converged over the sample period. Finally, Goel and Nelson (2018) recently study the incentives of firms to introduce process innovations.

  8. The vast majority of firms in our sample belong to developing countries (see the Appendix), where the typical size of enterprises is likely to be smaller than their developed-country counterparts. For instance, Mead and Liedholm (1998) report that a fourth of micro and small firms in their sample of six African nations had one employee, with less than ten percent having more than ten employees.

  9. http://www.enterprisesurveys.org/methodology.

  10. While the underlying survey has a wealth of detailed information, we are nevertheless constrained by the type and depth of questions asked, especially since the survey was not conducted with this research in mind.

  11. Note that, as stated in Table 1, our R&D variable is a dichotomous variable that captures engagement in R&D in the previous year. R&D can alternately be measured via expenditures or personnel involved. Such information, in general, is not widely available at the firm level, and even more challenging in the case of developing nations. Besides, our treatment mitigates issues of potential reverse feedbacks.

  12. We thus take into account that errors–which, in principal, are assumed to be i.i.d.–may have arbitrary correlation across firms within a given country.

  13. There is some related evidence, however, from individual nations. Using Canadian data, Rosa and Sylla (2016) find that in 2011 a majority female-owned SMEs were more likely to be innovative than majority male-owned enterprises. However, these gender differences disappeared in 2014, although female-owner innovation superiority persisted in some industries in 2014. While our work is unable to account for industry differences, it provides an analysis across countries and compares the relative attitudes of female owners and managers vis a vis their male counterparts.

  14. The relatively low statistical significance of female_manager in Table 3 did not necessitate a similar numerical exercise in that case.

  15. Specifically, the GII is an inequality index. It shows the loss in potential human development due to the disparity between female and male achievements in two dimensions: empowerment and economic status. The GII ranges between 0 and 1, with higher GII values indicating greater inequalities. For details, see http://hdr.undp.org/en/content/gender-inequality-index-gii.

  16. GDP and GII are highly (negatively) correlated. Thus, to avoid issues with multicollinearity, all models in Table 6 drop GDP as a regressor.

  17. Appropriate caution, however, is advised in interpreting findings based on composite indices.

  18. Other studies either look at female managers or at female owners, or they put both in one basket like Mukhtar (2002) who investigates “owner managers”, (also see Lee-Gosselin and Grisé 1990).

  19. We also considered the effects of greater competition (via the number of competitors) and found the effect on innovation introductions to be positive with female managers–the supply-push theory of innovation. However, the number of usable observations, in this case, was about a tenth of the overall sample, and insufficient to conduct a meaningful analysis in the case of female owners. Additional details are available upon request.

  20. Goel et al. (2016) examine the effects of alternate innovation dimensions on entrepreneurship in the formal and informal sectors using aggregate data for about 50 nations.

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Authors and Affiliations

  1. Kiel Institute for the World Economy, Kiel, Germany

    Dirk Dohse & Rajeev K. Goel

  2. Department of Economics, Illinois State University, Normal, IL, 61790-4200, USA

    Rajeev K. Goel

  3. University of Akron, Akron, USA

    Michael A. Nelson

Authors
  1. Dirk Dohse
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  2. Rajeev K. Goel
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  3. Michael A. Nelson
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Corresponding author

Correspondence to Rajeev K. Goel.

Additional information

We are grateful to Al Link and a referee for useful comments. An earlier version of this paper was circulated as a Kiel Working Paper (#2091).

Appendix

Appendix

Countries included in the data set

Afghanistan (2014), Albania (2013), Antigua and Barbuda (2010), Argentina (2010), Armenia (2013), Azerbaijan (2013), Bahamas (2010), Bangladesh (2013), Barbados (2010), Belarus (2013), Belize (2010), Benin (2016), Bhutan (2015), Bolivia (2010), Bosnia and Herzegovina (2013), Bulgaria (2013), Burundi (2014), Cambodia (2016), Cameroon (2016), Central African Republic (2011), Chile (2010), China (2012), Colombia (2010), Congo, Dem. Rep. (2013), Costa Rica (2010), Côte d’Ivoire (2016), Croatia (2013), Czech Republic (2013), Djibouti (2013), Dominica (2010), Dominican Republic (2010, 2016), Ecuador (2010), Egypt, Arab Rep. (2013), El Salvador (2010, 2016), Estonia (2013), Ethiopia (2011, 2015), Georgia (2013), Ghana (2013), Grenada (2010), Guatemala (2010), Guinea (2016), Guyana (2010), Honduras (2010), Hungary (2013), India (2014), Indonesia (2015), Israel (2013), Jamaica (2010), Jordan (2013), Kazakhstan (2013), Kenya (2013), Kosovo (2013), Kyrgyz Republic (2013), Laos PDR (2016), Latvia (2013), Lebanon (2013), Lesotho (2016), Lithuania (2013), Macedonia, FYR (2013), Malawi (2014), Malaysia (2015), Mali (2016), Mauritania (2014), Mexico (2010), Moldova (2013), Mongolia (2013), Montenegro (2013), Morocco (2013), Myanmar (2014, 2016), Namibia (2014), Nepal (2013), Nicaragua (2010), Nigeria (2014), Pakistan (2013), Panama (2010), Papua New Guinea (2015), Paraguay (2010), Peru (2010), Philippines (2015), Poland (2013), Romania (2013), Russian Federation (2012), Rwanda (2011), Senegal (2014), Serbia (2013), Slovak Republic (2013), Slovenia (2013), Solomon Islands (2015), South Sudan (2014), Sri Lanka (2011), St. Kitts and Nevis (2010), St. Lucia (2010), St. Vincent and the Grenadines (2010), Sudan (2014), Suriname (2010), Swaziland (2016), Tajikistan (2013), Tanzania (2013), Thailand (2016), Timor-Leste (2015), Togo (2016), Trinidad and Tobago (2010), Tunisia (2013), Turkey (2013), Uganda (2013), Ukraine (2013), Uruguay (2010), Uzbekistan (2013), Venezuela, R.B. (2010), Vietnam (2015), West Bank and Gaza (2013), Yemen (2013), Zambia (2013), Zimbabwe (2011, 2016).

  1. N = 119 (5 countries surveyed twice)

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Dohse, D., Goel, R.K. & Nelson, M.A. Female owners versus female managers: Who is better at introducing innovations?. J Technol Transf 44, 520–539 (2019). https://doi.org/10.1007/s10961-018-9679-z

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