Women in Business Process Management: a Systematic Mapping
DOI:
https://doi.org/10.5753/reviews.2026.6779Keywords:
Business Process Management, BPM, Systematic Mapping, Gender Diversity, Women in BPM, Women in TechnologyAbstract
In recent years, Business Process Management (BPM) has increasingly incorporated non-technical dimensions, recognizing cultural and social factors as critical to the success of BPM projects. Against this backdrop, this study investigates women’s participation in the BPM research domain, a field where their presence has traditionally been lower, especially in technology-related areas. Employing a systematic mapping methodology, the authors analyzed 5,029 scientific papers to assess patterns of authorship. The results demonstrate that women’s scientific production in BPM remains considerably below that of men, accounting for less than one-third of all identified authors. Moreover, this disparity exhibits a slight decreasing trend over time, revealing only modest progress in female participation. By providing empirical evidence of gender diversity trends in BPM academia, this research contributes valuable insights into women’s evolving role within the discipline and underscores the need for further efforts to foster inclusivity in this community.
Downloads
References
Agresti, A. (2018). An introduction to categorical data analysis. John Wiley & Sons. Book.
Alarcón-Alarcón, J., Pérez-Arriaga, J. C., Sánchez-García, Á. J., and Hemández-González, L. A. (2024). Gender diversity in software development teams: A systematic literature review. In 2024 12th International Conference in Software Engineering Research and Innovation (CONISOFT), pages 304-312. IEEE. DOI: 10.1109/CONISOFT63288.2024.00047.
Aleem, S. and Ahmed, F. (2023). Practicing equity diversity inclusion (edi) in software development teams: A systematic literature survey. IEEE Access, 11:98977-98987. DOI: 10.1109/ACCESS.2023.3312681.
Arrazola, M., Campos, R., and de Hevia, J. (2025). Do labour market outcomes influence why women are underrepresented in engineering? Higher Education, pages 1-19. DOI: 10.1007/s10734-025-01445-9.
Arrow, K. (1973). The theory of discrimination. DOI: 10.1515/9781400867066-003.
Babbie, E. R. (2020). The practice of social research. DOI: 10.2307/1318620.
Becker, G. (1957). The economics of discrimination. DOI: 10.2307/1055714.
Bello, M. and Galindo-Rueda, F. (2020). "charting the digital transformation of science". "OECD Science, Technology and Industry Working Papers, No. 2020/03, OECD Publishing". DOI: 10.1787/1b06c47c-en.
Cameron, A. C. and Trivedi, P. K. (2013). Regression analysis of count data. DOI: 10.1017/cbo9781139013567.
Campbell, L. G., Mehtani, S., Dozier, M. E., and Rinehart, J. (2013). Gender-heterogeneous working groups produce higher quality science. PLOS ONE, 8:1-6. DOI: 10.1371/journal.pone.0079147.
Cheryan, S., Ziegler, S. A., Montoya, A. K., and Jiang, L. (2017). Why are some stem fields more gender balanced than others? Psychological Bulletin, 143:1–35. DOI: 10.1037/bul0000052.
Cochran, W. (1977). Sampling techniques. DOI: 10.2307/2528108.
Dumas, M., Rosa, M., Mendling, J., and Reijers, H. (2018). Fundamentals of business process management. DOI: 10.1007/978-3-642-33143-5.
Ellis, J., Fosdick, B. K., and Rasmussen, C. (2016). Women 1.5 times more likely to leave stem pipeline after calculus compared to men: Lack of mathematical confidence a potential culprit. PLoS ONE, 11. DOI: 10.1371/journal.pone.0157447.
Felizardo, K. R., Ramos, A. M., de Claudia, C., Érica Ferreira de Souza, Vijaykumar, N. L., and Nakagawa, E. Y. (2021). Global and latin american female participation in evidence-based software engineering: a systematic mapping study. Journal of the Brazilian Computer Society, 27. DOI: 10.1186/s13173-021-00109-7.
Gorbacheva, E., Stein, A., Schmiedel, T., and Müller, O. (2015). A gender perspective on business process management competences offered on professional online social networks. 23rd European Conference on Information Systems, ECIS 2015, 2015-May:1-17. DOI: 10.18151/7217329.
Gorbacheva, E., Stein, A., Schmiedel, T., and Müller, O. (2016). The role of gender in business process management competence supply. Business and Information Systems Engineering, 58:213-231. DOI: 10.1007/s12599-016-0428-2.
Hicks, M. (2018). Programmed inequality. Mit Press, Cambridge. Book.
Holman, L., Stuart-Fox, D., and Hauser, C. (2018). The gender gap in science: How long until women are equally represented? PLoS Biology, 16(4). DOI: 10.1371/journal.pbio.2004956.
Jones, G., Chirino Chace, B., and Wright, J. (2020). Cultural diversity drives innovation: empowering teams for success. International Journal of Innovation Science, 12(3):323-343. DOI: 10.1108/IJIS-04-2020-0042.
Kerpedzhiev, G. D., König, U. M., Röglinger, M., and Rosemann, M. (2021). An exploration into future business process management capabilities in view of digitalization: results from a delphi study. Business & Information Systems Engineering, 63(2):83-96. DOI: 10.1007/s12599-020-00637-0.
Knobloch-Westerwick, S., Glynn, C., and Huge, M. (2013). The matilda effect in science communication: An experiment on gender bias in publication quality perceptions and collaboration interest. Science Communication, 35(5):603-625. DOI: 10.1177/1075547012472684.
Kohl Silveira, K. and Prikladnicki, R. (2019). A systematic mapping study of diversity in software engineering: A perspective from the agile methodologies. In 2019 IEEE/ACM 12th International Workshop on Cooperative and Human Aspects of Software Engineering (CHASE), pages 7-10. DOI: 10.1109/CHASE.2019.00010.
Kordaki, M. and Berdousis, I. (2020). Identifying barriers for women participation in computer science. Pro Edu. International Journal of Educational Sciences, 2:5-20. DOI: 10.26520/peijes.2020.2.2.5-20.
Llorens, A., Tzovara, A., Bellier, L., Bhaya-Grossman, I., Bidet-Caulet, A., Chang, W. K., Cross, Z. R., Dominguez-Faus, R., Flinker, A., Fonken, Y., Gorenstein, M. A., Holdgraf, C., Hoy, C. W., Ivanova, M. V., Jimenez, R. T., Jun, S., Kam, J. W., Kidd, C., Marcelle, E., Marciano, D., Martin, S., Myers, N. E., Ojala, K., Perry, A., Pinheiro-Chagas, P., Riès, S. K., Saez, I., Skelin, I., Slama, K., Staveland, B., Bassett, D. S., Buffalo, E. A., Fairhall, A. L., Kopell, N. J., Kray, L. J., Lin, J. J., Nobre, A. C., Riley, D., Solbakk, A.-K., Wallis, J. D., Wang, X.-J., Yuval-Greenberg, S., Kastner, S., Knight, R. T., and Dronkers, N. F. (2021). Gender bias in academia: A lifetime problem that needs solutions. Neuron, 109(13):2047-2074. DOI: 10.1016/j.neuron.2021.06.002.
Lotka, A. J. (1926). The frequency distribution of scientific productivity. Journal of the Washington academy of sciences, 16(12):317-323. Available at:[link].
McKinney, W. et al. (2010). Data structures for statistical computing in python. In Proceedings of the 9th Python in Science Conference, volume 445, pages 51-56. Austin, TX. DOI: 10.25080/Majora-92bf1922-00a.
Montgomery, D. C., Peck, E. A., and Vining, G. G. (2021). Introduction to linear regression analysis. DOI: 10.2307/1269673.
Müller, O., Schmiedel, T., Gorbacheva, E., and vom Brocke, J. (2016). Towards a typology of business process management professionals: identifying patterns of competences through latent semantic analysis. Enterprise Information Systems, 10:50-80. DOI: 10.1080/17517575.2014.923514.
NIH (2020). NIH-Funded Research Workforce - Data by gender. Available at:[link]. [Online; accessed 16-October-2021].
Petersen, K., Feldt, R., Mujtaba, S., and Mattsson, M. (2008). Systematic mapping studies in software engineering. 12th International Conference on Evaluation and Assessment in Software Engineering, EASE 2008, (February 2015). DOI: 10.14236/ewic/ease2008.8.
Petersen, K., Vakkalanka, S., and Kuzniarz, L. (2015). Guidelines for conducting systematic mapping studies in software engineering: An update. volume 64, pages 1-18. DOI: 10.1016/j.infsof.2015.03.007.
Phelps, E. S. (1972). The statistical theory of racism and sexism. American Economic Review, 4(LXII):659–661. Available at:[link].
Ralph, P. and Baltes, S. (2022). Paving the way for mature secondary research: the seven types of literature review. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022, page 1632–1636, New York, NY, USA. Association for Computing Machinery. DOI: 10.1145/3540250.3560877.
Rodríguez-Pérez, G., Nadri, R., and Nagappan, M. (2021). Perceived diversity in software engineering: a systematic literature review. Empirical Software Engineering, 26. DOI: 10.1007/s10664-021-09992-2.
Santamaría, L. and Mihaljević, H. (2018). Comparison and benchmark of name-to- gender inference services. PeerJ Computer Science, 2018. DOI: 10.7717/peerj-cs.156.
Schmiedel, T. and vom Brocke, J. (2015). Business Process Management: Potentials and Challenges of Driving Innovation, pages 3-15. Springer International Publishing, Cham. DOI: 10.1007/978-3-319-14430-6_1.
Seabold, S. and Perktold, J. (2010). statsmodels: Econometric and statistical modeling with python. In 9th Python in Science Conference. Austin, TX. DOI: 10.25080/Majora-92bf1922-011.
Trauth, E. M. (2011). Rethinking gender and mis for the twenty-first century. The Oxford Handbook of Management Information Systems: Critical Perspectives and New Directions. DOI: 10.1093/oxfordhb/9780199580583.003.0025.
Truong, B. Q., Nguyen-Duc, A., and Van, N. T. C. (2023). A quantitative review of the research on business process management in digital transformation: A bibliometric approach. Software, 2(3):377-399. DOI: 10.3390/software2030018.
Yang, Y., Tian, T. Y., Woodruff, T. K., Jones, B. F., and Uzzi, B. (2022). Gender-diverse teams produce more novel and higher-impact scientific ideas. Proceedings of the National Academy of Sciences, 119(36):e2200841119. DOI: 10.1073/pnas.2200841119.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Thayna Minuzzo, Guilherme Rego Rockembach, Rachelle Bianchi Sganderla, Pedro Vitor Alexandre, Encarna Sosa Sánchez, Lucineia Heloisa Thom
This work is licensed under a Creative Commons Attribution 4.0 International License.
