Gender equality: opportunities and challenges for the OR community

Figures & data

Figure 1. Gender participation in EURO National OR Societies Boards, ordered by board size.

Table 1. OR/Gender nexus SLR results.

Explanatory Variable	Hirschfield et al. (1995), Rivett and Roberts (1995), Stevenson et al. (2010), De Witte et al. (2010), Otamendi et al. (2012), Keskin et al. (2021), Baldiga (2014), Dede et al. (2023), Eryarsoy et al. (2023), Eskandarian et al. (2023), Sherman et al. (2023)
Optimisation Models	Sutcliffe et al. (1984), Alpern and Katrantzi (2009), Durán and Wolf-Yadlin (2011), Tang and Yuan (2023)
Stakeholder Involvement	Mwiti and Goulding (2018), Amorosi et al. (2021)

Table 2. History of OR SLR results.

OR Community	Biography: (Rosenhead, 1989), (Finan & Hurley, 1997), (Kirby, 1999)
	(Assad, 2006), (Hollocks, 2008), (Haeusler, 2012)
	(Green et al., 2015)
	Review: (Thomas, 1994), (Merigó & Yang, 2017)
	Regional: (Fildes & Ranyard, 1997), (Keys, 1998)
	(Kirby & Capey, 1998)
	(Lindsey, 1998), (Machol, 1998), (Tomlinson, 1998),
	(Turner, 2008), (Rosenhead, 2009), (Yousef, 2011),
	(Ittmann, 2021), (Jablonský et al., 2022),
	(Povh et al., 2023; Rand, 2024)
Epistemological	Analytics: (Mortenson et al., 2015)
	Discrete Event Simulation: (Hollocks, 2006)
	Probabilistic Decision Analysis: (Morton & Phillips, 2009)
	Soft OR: (Paucar-Caceres, 2010), (Paucar-Caceres, 2011)
	Systems Dynamics: (Coyle, 1997)
	Strategic OR: (Bell, 1998)
Phronesis and Techne	Iron, Steel and Coal industries: (Kirby, 2000) Locational Analysis: (Smith et al., 2009)
	Military: (Kirby & Godwin, 2010), (Kirby & Capey, 1997b),
	(Kirby & Capey, 1997a),
	(Sawyer et al., 1989)
	Problem Structuring Methodologies: (Klein, 2009)
	Town Planning: (Yewlett, 2001a, 2001b)

Figure 2. Survey Responses: Count by age, affiliation (academic faculty or practioner) and gender (172 female vs 146 male), frequency count on the y-axis.

Figure 3. Count of caring hours by age and gender. 34% of all respondents reported care duties, 66 female vs 42 male respondents.

Table 3. Career break vs. gender.

	Gender
Career break	Male	Female
Yes	9.1%	28.7%
Parental leave	5.8%	22.4%
Health-related reasons	2.1%	4.5%
Other	1.2%	1.8%
No	35.8%	26.4%

Figure 4. Count of EJOR sub-discipline by age and gender.

Figure 5. Respondents by faculty type, age and gender.

Table 4. Average age (years) by academic role and gender.

	Academic role
Gender	PhD	Postdoc	Asst Prof	Assoc Prof	Prof	Full Prof	Other
Male	28.13	34.50	41.61	41.32	49.50	52.31	39.25
Female	30.29	33.71	41.64	43.25	54.50	53.98	42.83

Table 5. Number of changes of institution since PhD vs. gender.

	Gender
Institution changes since PhD	Male	Female
0	18.5%	23%
1	9.3%	15.3%
2	10.9%	8.1%
3	5.7%	5.2%
4	2.0%	0.8%
$\ge$ 5	0.4%	0.8%

Table 6. Reasons not to change institution vs. gender.

	Gender
Reasons not to change	Male	Female
Too soon since appointed	5.8%	7.9%
I have been promoted so don’t need to move	11.5%	12.2%
Can’t move because of caring responsibilities	0.7%	6.5%
I am satisfied with my current work/life balance	23.7%	23%
Other, please describe	2.9%	5.8%

Table 7. Reasons to change institution vs. gender.

	Gender
Reasons for a change	Male	Female
To get a promotion	16.3%	15.3%
To allow a change of career direction	14.2%	14.2%
To meet my family or caring responsibilities	10%	7.9%
Other, please specify	10.5%	11.6%

Table 8. Author name ordering convention vs. gender.

	Gender
Author name ordering convention	Male	Female
Alphabetic by surname with lead author acting as corresponding author	18.0%	18.8%
Lead author first, senior author last, other authors in between ordered by their contribution	19.6%	28.2%
Other, please specify	6.7%	8.7%

Table 9. Challenges to participation in OR vs. gender.

	Gender
Challenges	Male	Female
Balancing work/life	9.1%	14.4%
Getting a permanent position	7.2%	8.9%
Getting papers published	7.1%	9.3%
Getting promoted	3.2%	7.7%
Securing research funding	8.3%	8%
Finding PhD students	5.2%	6.7%
Other, please explain	2.3%	2.6%

Table 10. MATLAB classification Learner APP results.

	Accuracy
Classification model	Validation	Testing
Fine tree	63.5%	55.6%
Medium tree	65.6%	61.9%
Coarse tree	68.2%	74.6%
Optimisable tree	68.6%	76.2%
Logistic regression	66.7%	55.6%
Optimisable Naïve Bayes	62.7%	66.7%
Boosted trees	64.7%	63.5%
Bagged trees	69%	60.3%
Ensemble	69.4%	63.5%

Figure 6. Gender predicting decision tree.

Table A1. Survey questions.

Question	Question text	Response choice
Q0	Are you participating in the EURO2021 Conference?	Yes/No
Q1	Which of the following best describes your gender?	Male/Female/Non-binary/Prefer to self-describe/Prefer not to say
Q2	How old are you?	Up to 24 years/25–34 years/35–44 years/45–54 years/55–64 years/65–74 years/75+ years/Prefer not to say
Q3	In which country is your workplace located?	Free text
Q4	A ’carer’ is someone who provides regular, unpaid personal help for a friend or family member. Do you currently have any caring responsibilities?	Yes/No
Q4.1	If yes, since you have caring responsibilities, which kind do you have? Tick all that apply	Primary carer of a child or children (<18)/Joint primary carer of a child or children (<18)/Primary carer of a disabled child or children/ Joint primary carer of a disabled child or children/ Primary carer or assistant for a disabled adult ($\ge$18)/Joint primary carer or assistant for a disabled adult ($\ge$18)/Primary carer or assistant for an older person or people ($\ge$65)/Joint primary carer or assistant for an older person or people ($\ge$65)/Secondary carer (another person carries out the primary caring role)/I have caring responsibilities but prefer not to specify what these are/Prefer not to say
Q4.2	If yes, since you have caring responsibilities, how many hours per week on average do you spend caring?	$\le$2 h/2–5 h/5–10 h/>10 h
Q5	Have you ever taken a career break (excluding research sabbaticals)? Tick all that apply	Maternity or paternity leave/Health reasons/Other, please explain/No
Q6	With which of the EJOR sub-disciplines do you associate yourself? Tick all that apply	Continuous Optimisation/Discrete Optimisation/Production, Manufacturing, Transportation, Logistics/Stochastics and Statistics/Decision Support/Analytics, Computational Intelligence, Information Management/Interfaces with Other Disciplines/Additional sub-disciplines not listed above
Q6.1	If additional sub-disciplines not listed above is selected, please provide up to three keywords to describe your interests	Keyword 1/Keyword 2/Keyword 3
Q7	How would you describe your employment status? Tick all that apply	Employed in academia/ Employed in practice/ Self-employed/ Retired/Other, please describe
Q7.A1	If employed in academia, with which type of faculty are you most associated?	School of Business/School of Mathematics/School of Engineering/School of Computer Science/Research centre/A combination of the previous options, please specify/Other, please specify
Q7.A2	If employed in academia, prior to your current academic career, did you have a career in practice or industry?	Yes/No
Q7.A3	If employed in academia, what role are you currently in?	Adjunct professor/Assistant professor (includes lecturer and senior lecturer roles)/Associate professor/Professor/Full professor/Postdoctoral researcher/PhD researcher/Other, please specify
Q7.B1	If employed in practice, with which sector are you associated?	Private/Public/Other, please specify
Q7.B2	If employed in practice, prior to your current career in practice or industry, did you have a career in academia?	Yes/ No
Q7.1	If employed either in academia or practice or self-employed, what size is the unit/department you are associated with?	Small (<10 people)/Medium ($\ge$10–<20 people)/Large ($\ge$20 people)
Q7.2	If employed either in academia or practice, what type of contract(s) do you currently hold? Tick all that apply	Temporary (or fixed-term) part-time/Permanent part-time/Temporary (or fixed-term) full-time/Permanent full-time/Other, please specify

Table A2. Survey questions (Cont’d).

Question	Question text	Response choice
Q8	How long have you worked in your current institution?	1 year/1–2 years/ 3–7 years/7–12 years/>12 years/Not applicable
Q9	If you hold a PhD, how many years since you were awarded your PhD?	<1 year/1–2 years/3–7 years/7–12 years/>12 years/Not applicable
Q9.1	If any duration has been selected, how many times have you changed institution since your first post-PhD position?	0/1/2/3/4/$\ge$5
Q9.1.A1	If Q9.1 == 0, can you tell us why you chose not to change? Tick all that apply	Too soon since appointed/I have been promoted so don’t need to move/ Can’t move because of caring responsibilities/I am satisfied with my current work-life balance/Other, please describe/ Prefer not to say
Q9.1.B1	If Q9.1 != 0, how long, on average, have you stayed in each institution?	1–2 years/3–7 years/ 7–12 years/>12 years/Not applicable
Q9.1.B2	If Q9.1 != 0, what was your motivation for changing institution?	To get a promotion/To allow a change of career direction/To meet my family or caring responsibilities/Other, please specify
Q10	If employed in academia, what author name ordering convention do you generally use?	Alphabetic by surname with lead author acting as corresponding author/Lead author first, senior author last, other authors in between ordered by their contribution/Other, please specify
Q11	What are the biggest challenges you have encountered to build your career in OR? (Tick all that apply)	Balancing work-life and caring responsibilities/Getting a permanent position/Getting papers published/Getting promoted/Securing research funding/Finding PhD students/Other, please explain
Q12	During your early career, did you have a role model (possibly your PhD advisor or any other researcher or practitioner of OR)?	Yes/No
Q12.1	If yes, can you tell us about your role model: were they the same gender as you?	Yes/No/Prefer not to say
Q13	Are there particular barriers for your gender to participate in OR?	Yes/ No/Prefer not to say
Q13.1	If yes, can you tell us about what has been a challenge for you and any solution you found?	Free text
Q14	What advice would you give to your younger self to develop your career in OR?	Free text
Q15	Is there a gender dimension to your research or practice of OR, or anything else you would like to note in relation to gender and OR?	Free text
Q16	A Buddy programme encourages informal connections and networking between members of the OR community. Are you interested in joining a EURO WISDOM Forum Buddy programme?	Yes/Maybe/No
Q16.1	If yes or maybe, please indicate what you want from such a programme, and/or what you would like to contribute	Free text
Q17	Finally, why did you choose a career in OR?

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