What do women want? An exploration of workplace attraction and retention factors for women in construction

Abstract

Increasing skill shortages in the construction industry are a concern worldwide. The industry is seeking to find effective ways to encourage more women to pursue careers in construction. This study explores the factors that attract and retain women, comparing them based on age (under 35 years, 35–44 years and 45 plus years) and role levels (managers, professionals and nonmanagers). A total of 655 responses were collected through a nationwide survey of women in construction in Australia. The findings suggest that to attract women, career opportunities must be emphasized; and that career advising, attractive salary/wages and training must be highlighted to attract young female talent. Further, working conditions are important factors considered by managerial and professional women when leaving the industry, particularly younger women. Organizational leaders and decision-makers seeking to recruit more women into construction may improve the effectiveness of their recruitment and retention initiatives by tailoring them to role level and age.

Keywords:

• Construction industry
• women
• attraction
• retention
• age

Introduction

The construction industry is an important contributor to economic performance and employment markets worldwide (Albattah et al. 2016; Choi et al. 2018). Being traditionally male-dominated, construction is experiencing a long-term challenge with vertical and horizontal gender role segregation (Baker et al. 2019; Ness 2012) and ongoing difficulty with effective attraction and retention of women (Bigelow et al. 2019; Bigelow et al. 2021; Perrenoud et al. 2020). While improving, women’s participation in this significant economic sector still accounts for a very small proportion of the workforce, at just 25.9% (WGEA 2022). This represents a concern in the face of increasing skill shortages and expectations that the industry’s employment share will significantly increase in the future (Toohey et al. 2009). With government infrastructure investment expected to reach AUD218 billion and annual spending forecast to reach AUD52 billion by 2023 (Infrastructure Australia 2021), construction employment is projected to rise by 80,700 (6.8%) in Australia by 2025 (National Skills Commission 2021).

Recruiting women into the industry has been identified as a promising solution to the skills gap (Crawford et al. 2015; Morello et al. 2018). Unfortunately, the construction sector has continued to be less attractive to women due to their experience of relative disadvantage and inequality, and lack of development and promotional opportunities, compared to their male counterparts (Dainty et al. 2000). In fact, the data shows that while female appointments increased from 16% in 2016 to 25.9% in 2021, resignations also increased from 18.4% to 28.2%, respectively (WGEA 2022). It has been reported that in Australia, women are leaving the construction professions at a rate almost 39% higher than that of their male colleagues (Association of Professional Engineers, Scientists and Managers 2010). By comparison, the overall appointment of male employees decreased from 84% in 2016 to 74.1% in 2021 (WGEA 2022). However, the overall male resignation rates also decreased from 81.6% to 71.8%, respectively (WGEA 2022). Tackling female recruitment and retention issues is therefore of high importance (Perrenoud et al. 2020).

Given the desire to employ more women in the construction industry, this exploratory study aims to understand and provide insights into women’s perceptions of what attracts them, what career barriers they face, and what may lead them to leave the industry. Further, it aims to explore how these factors differ by age and role level. As pointed out by Bigelow et al. (2021), more research on this topic is needed in construction. While much research has been delivered about attraction and retention issues in general, this topic is understudied in construction, and empirical evidence remains particularly limited (Bigelow et al. 2021). Previous research has focused mainly on comparing the career choices of men and women (Bigelow et al. 2021; Perrenoud et al. 2020), the attraction and retention of women in trade roles (Bigelow et al. 2017, 2019; Oo et al. 2022), and early career experiences of women in construction (Moore and Gloeckner 2007; Bigelow et al. 2015; Oo et al. 2020; Kelly et al. 2022). The present study is significant in that it makes new contributions to the body of knowledge on this important topic. It provides empirical evidence for factors that attract and retain women in construction, while looking more closely at the important differences by age and role levels. It delivers to the industry timely and important insights into tailoring recruitment and retention initiatives to increase appointments and reduce resignations.

The remainder of this paper comprises a review of the relevant literature, methods used to collect data, exploratory results, and a discussion of the findings.

Women in the Australian construction industry

The Australian construction industry, like that in jurisdictions worldwide, has always been male dominated. In 2021, women made up just 20.1% of board directors, 4.4% of CEOs, 18.7% of managers and 29.2% of professional employees (WGEA 2022). While appointment rates of women managers have increased from 12.3% in 2016 to 22% in 2021, resignations rates have also increased, from 12.1% to 23.2%, respectively (WGEA 2022). Similarly, appointment rates of women nonmanagers increased from 16.3% in 2016 to 26.4% in 2021, but resignation rates for this cohort also increased, from 19.1% to 28.6%, respectively (WGEA 2022). This contrasts with male employees, whose appointment levels have reduced slightly, but whose resignation levels have also reduced, for both managers and nonmanagers (WGEA 2022).

In recent years, construction organizations have significantly improved their recruitment and retention strategies. For instance, the number of organizations with gender equality recruitment policies and strategies has increased from 74.9% in 2016 to 86.6% in 2021 (WGEA 2022). Similarly, the number of organizations with gender equality retention strategies increased from 48.7% to 69% over the same period, and those with flexible working policies 4 and strategies from 44.1% to 71% (WGEA 2022). However, these initiatives have not yet led to many more women managers and nonmanagers in the construction industry. Increasing diversity in construction continues to be a priority (Menches and Abraham 2007).

Factors attracting women in construction

As discussed, while extensive research exists relating to workplace attraction of women in general, considerably less is known about the factors affecting attraction of women in construction (Bigelow et al. 2021). Previous research in construction has focused mainly on specific industry sectors and specific role types (Kelly et al. 2022). Bigelow et al. (2019) compared data from tradespeople in the drywall and electrical construction industry. They found that ‘family influence’ exerted a strong positive influence on tradespeople selecting the construction career. ‘Salary/wages’ was the strongest positive influence factor; however, electrical workers rated ‘available training’ as more positively influential than ‘salary’ and ‘career opportunities,’ suggesting that in that industry sector, promoting the trade as a career and not just a job is an effective technique for attracting workers. The remaining factors, that is, ‘industry image,’ ‘career advising,’ and ‘no other opportunities,’ were also positive, though not as strongly. Comparisons between the trades showed that while certain factors can be positively influential in attracting workers to construction in general, the influence of the factors varies depending on the specific trade, and therefore recruiting efforts should reflect that variation. However, the study was limited to examining data from tradespeople in the drywall and electrical construction industries, specifically.

Similarly, Perrenoud et al. (2020) investigated factors that attracted managerial-level men and women to the electrical construction industry. They found that women identified ‘career opportunities’ and ‘salary/wages’ as the most influential factors attracting them to the industry. ‘Career advising’ and ‘no other opportunities for work’ attraction factors were found to have a small positive impact on attracting women. With a low number of women indicating ‘industry image’ as a positive factor, this may still be an issue in attracting women to the industry. Perrenoud et al.’s (2020) research pointed to significant differences in factors influencing attraction of women versus men and showed that the influence of the factors varies based not only on trades but also on gender.

Career barriers for women in construction

Career barriers are complex and multidimensional, and affect career goals, decision-making and outcomes (Leung 2008). They are defined as obstacles that hinder career progression (Ng and Feldman 2014). Research suggests that, in construction, women confront multiple career barriers. English and Le Jeune (2012) posit that to increase the representation of women in construction, it is critical to understand it from the perspectives both of women already working in the industry and those seeking to enter it. Navarro-Astor et al. (2017) delivered a comprehensive literature review of recent research that explored women’s career barriers in the construction industry. The authors summarized the most prevalent barriers, quoting lack of work–family balance, gender stereotypes, unequal allocation of posts and activities, unequal promotions, challenging working conditions, sexist work cultures, harassment and lack of respect, unequal recruitment and selection practices, lack of recognition for work performed, gender pay gaps and lack of social networks (for the full review, see Navarro-Astor et al. 2017).

In another review, Menches and Abraham (2007) identified slow career progression, difficulty with work–life balance, male-dominated work cultures and inflexible work structures as the most frequently cited barriers to women’s success in construction. Further, Naoum et al. (2020) found that the construction industry is struggling with ‘zig-zag’ career development paths for women and, according to the ‘leaky pipeline’ theory, the industry has not yet addressed the issue of women leaving the industry as they age (Morello et al. 2018). Further, the construction industry struggles with a poor public image (Lekchiri and Kamm 2020; Yng Ling and Ho 2013; Yng Ling et al. 2016); plus, women don’t have role models within it to inspire to (Gaines 2017; Wright 2016), and are often discouraged by discrimination from pursuing their careers (King and Sumner 2015), as well as by hostility and sexual harassment (Lekchiri and Kamm 2020). While previous research has involved different occupational samples, i.e. architects, engineers, professional technicians (Menches and Abraham 2007; Morello et al. 2018), women executives and managers (Francis 2017; Bigelow et al. 2021; Perrenoud et al. 2020), female professional technicians and tradeswomen (Bigelow et al. 2019; Kelly et al. 2022; Oo, et al. 2022; Wright 2016), it has not compared career barriers based on age and role levels.

Factors for leaving construction

A considerable amount of research has investigated factors that influence retention of women in the workplace, but research investigating their retention in the construction industry is limited (Bigelow et al. 2021). One such study by Oo et al. (2022) investigated the likelihood of tradeswomen leaving the industry and the factors that may affect their decisions to do so. The authors found that ‘personal factors’ (e.g. retirement, work–family balance, personal development) were the factors most likely to influence leaving a construction trades career, followed by ‘opportunity to work in another job with same pay and benefits.’ Factors related to ‘industry culture’ were the third most influential. However, a limitation of this study is that it collected data from just 78 respondents, all of whom were engaged in trades careers.

Comparisons by age

To date, only Bigelow et al. (2021) has explored differences between factors that attract and retain construction employees based on age. Age of prospective employees is important in recruiting, as it affects attraction and retention (Newman and Lyon 2009). For instance, older employees may have more experience and higher skill levels due to a longer history of employment as well as reduced financial needs, allowing them to be more selective when deciding whether to join an organization (Skirbekk 2008; Wong and Tetrick 2017). They may also remain longer with an organization than younger employees (Chih et al. 2016).

Bigelow et al. (2021) explored age-based differences in attraction factors among electrical construction managers, using five age groups: under 30, 31–40, 41–50, 51–60 and 61 or older. While they found similarities across age groups, they also found many differences. For instance, the ‘career advising’ factor was most positively influential for people aged under 40. The factors ‘family influence,’ ‘salary/wages,’ and ‘available training’ were positively influential across all age groups. The factor ‘career advising’ was most positively influential for the under 30 age group. While ‘industry image’ had a higher percentage of negative influence in the under 30 age group, it also had the highest positive influence within that age group, suggesting that it influenced younger age groups more, both positively and negatively. The factor ‘career opportunities’ had the most positive influence on the under 30 age group, suggesting that career opportunities available in the electrical construction industry sector attracted this group more than older groups. Similarly, the ‘no other opportunities’ factor had the highest negative influence in the under 30 group, also suggesting that while they had other opportunities, they still selected electrical construction. These differences based on age in factors that attract employees to the industry represent important insights for effective recruitment and addressing workforce shortages. However, a limitation of that study is that it only examined data from managerial-level men and women in a specific industry sector, namely electrical construction.

Comparison by role level

Similarly, differences based on role level can provide important data for more effective recruitment and retention practices. Research has shown that various factors, both individual and organizational, shape employees’ experiences and organizations’ abilities to recruit and retain them (Boyas et al. 2015). For instance, Oo et al. (2020) compared attraction factors and the impact of career barriers on women in construction trades based on years of experience, which allowed them to understand whether the experience of those factors was different for women starting their careers in different decades. They found differences for both attraction and career barriers. For instance, ‘opportunities to develop new skills’ and ‘opportunity to complete challenging tasks’ were much more influential on people with less than 10 years of experience in the industry. Regarding career barriers, those with more years of experience were found to be more positively influenced by ‘negative attitudes of male co-workers’ and ‘fewer career supports’ than the less experienced. Given this, it would be reasonable to expect that other demographic differences, such as role levels, would also have an impact on the factors relevant to attracting and retaining employees. Role levels have, for instance, been studied in research into the influence of various diversity initiatives on the representation of women in construction (Baker et al. 2021).

In summary, the present study is unique in exploring perceived differences in factors that attract and retain women in construction. Previous research focused on specific roles within the industry or specific industry sectors, or compared women with men, leaving a gap in the body of knowledge. This study has national scope, covers a variety of roles, and includes data from across the construction industry sectors. In addition, it compares those factors based on age (under 35 years, 35–44 years and 45 years plus) and role levels (managers, professionals and nonmanagers), thus offering a meaningful contribution to the body of knowledge on this important topic.

Methods

This exploratory study adopted a quantitative research design and a survey research method to explore women’s perceptions of factors attracting and retaining women in construction. Data were collected from a survey of women (managers, professionals and nonmanagers) who were employed in the Australian construction industry. We obtained a high sample size of 655 valid responses from women. Table 1 presents the categories, frequencies and percentages of all of the demographic questions. Most survey participants belonged to the age categories of 25–34 years (37.1%) and 35–44 years (30.7%). Mature-aged women (45+) comprised only 24.5% of the sample. Professionals had the highest representation (37.7%), while all other categories (nonmanagement, supervisors, middle managers and senior managers) had similar representations of approximately 15% each. Almost half (42.7%) of the participants were previously in a nonmanagement role.

Table 1. Demographics of respondents.

Demographic Variable	Categories	Frequency	Percentage
Age	15–24 years	49	7.5
	25–34 years	243	37.1
	35–44 years	201	30.7
	45–54 years	121	18.5
	55–64 years	36	5.5
	65+ years	3	.5
	No response	2	.3
Country of birth	Australia	436	66.6
	Others	215	32.8
	No response	4	.6
Aboriginal/Torres Strait Islander	Yes	15	2.3
	No	628	95.9
	No response	12	1.8
Marital Status	Single	150	22.9
	In a relationship	71	10.8
	De facto relationship	142	21.7
	Married	241	36.8
	Separated	13	2
	Divorced	35	5.3
	No response	3	.5
Dependents	0	383	58.5
	1	94	14.4
	2 or more	174	26.6
	No response	4	.6
Education	Below undergraduate	174	26.6
	Undergraduate	272	41.5
	Above undergraduate	209	31.9
Work Experience	Up to 10 years	191	29.2
	11–20 years	253	38.6
	21 years plus	209	31.9
	No response	2	.3
Work experience in construction	Up to 10 years	361	55.1
	11–20 years	199	30.4
	21 years plus	94	14.4
	No response	1	.2
Current Role in construction	Nonmanagement	114	17.4
	Professional	247	37.7
	Supervisor	96	14.7
	Middle manager	93	14.2
	Senior manager	103	15.7
	No response	2	.3
Previous role	Nonmanagement	280	42.7
	Professional	132	20.2
	Supervisor	64	9.8
	Middle manager	37	5.6
	Senior manager	131	20
	No response	11	1.7
Work status	Self-employed/casual/contract	47	7.2
	Part-time	57	8.7
	Full-time	548	83.7
	No response	3	.5
How current job was found	Promotion/internal appointment	59	9
	Job advertisement	154	23.5
	Family member/friend in construction	116	17.7
	Job agency	71	10.8
	Professional network	168	25.6
	Other	87	13.3
Previous Industry	Health care and social assistance	62	9.5
	Education and training	44	6.7
	Retail trade	6	.9
	Accommodation and food services	17	2.6
	Administrative and support services	24	3.7
	Public administration and safety	11	1.7
	Rental, hiring and retail services	24	3.7
	Financial and insurance services	18	2.7
	Arts and recreation services	14	2.1
	Professional scientific and technical services	8	1.2
	Information media and telecommunications services	26	4
	Wholesale trade	21	3.2
	Agriculture, forestry and fishing	8	1.2
	Manufacturing and fishing	13	2
	Transport, postal and warehousing	92	14
	Electricity, gas, water and waste services	6	.9
	Mining	2	.3
	Other services	47	7.2
	Construction or none	208	31.8
	No response	4	.6

Measures

Influence of factors in attracting women (7 items)

We used a 7-item Likert scale to measure the influence of factors in attracting women, from Bigelow et al. (2019). The Cronbach’s alpha was .70 for the current study. See the Appendix for a list of the items.

Barriers to working in construction (16 items)

A relevant 16-item scale was borrowed from Oo et al. (2022) to measure the perceptions of women about barriers to working in construction. The Cronbach’s alpha for the current study was .88. See the Appendix for a list of the items.

Factors for leaving construction (5 items)

The factors for leaving construction were measured through five items from Oo et al. (2022). See the Appendix for a list of the items. Cronbach’s alpha is not relevant, as these responses were in the form of frequencies for each of the five categories.

Results

Table 2 presents means and standard deviations of the seven factors attracting women to construction, with career opportunities being highly positively influential, and industry image being the least attractive. The table also presents the frequencies for each of the responses for the seven factors and their percentages. Most women perceived career advising, no other opportunities for work, and available training as having no influence in attracting women. A high percentage of women also considered family influence and industry image to not be influential. Salary/wages and career opportunities in construction were slightly positively influential for a high percentage of participants.

Table 2. Influence of factors in attracting women.

Factor	Mean	SD	Responses^a	Frequency	%^b
Career advising	3.30	.89	Highly negatively	31	4.7
			Slightly negatively	25	3.9
			No influence	371	58.2
			Slightly positively	146	22.9
			Highly positively	65	10.2
Family influence	3.57	.10	Highly negatively	26	4
			Slightly negatively	22	3.4
			No influence	293	44.7
			Slightly positively	162	24.7
			Highly positively	137	20.9
Salary/wages	3.79	.88	Highly negatively	9	1.4
			Slightly negatively	28	4.3
			No influence	194	29.6
			Slightly positively	270	41.2
			Highly positively	143	21.8
Industry image	3.20	.95	Highly negatively	29	4.4
			Slightly negatively	98	15
			No influence	276	42.1
			Slightly positively	180	27.5
			Highly positively	51	7.8
No other opportunities	3.00	.92	Highly negatively	61	9.3
for work			Slightly negatively	42	6.4
			No influence	405	61.8
			Slightly positively	85	13
			Highly positively	41	6.3
Career opportunities in	3.94	.87	Highly negatively	10	1.5
construction			Slightly negatively	17	2.6
			No influence	154	23.5
			Slightly positively	285	43.5
			Highly positively	180	27.5
Available training	3.45	.84	Highly negatively	15	2.3
			Slightly negatively	22	3.4
			No influence	342	52.2
			Slightly positively	179	27.3
			Highly positively	80	12.2

^a Coded as follows: Highly negatively 1; Slightly negatively 2; No influence 3; Slightly positively 4; and Highly positively 5.

^b The small number of nonresponses were not included and thus total may not equal 100.

Table 3 presents means and standard deviations for the 16 barriers, along with the frequencies and percentages of the responses. Male-dominated culture is the most influential barrier, with the highest mean value of 4.64, followed by difficulty in balancing work and family at 4.42, unequal treatment on the job at 4.25, long working hours at 4.03 and sexual harassment at 4.01. Except for bad working conditions (33.7% indicating no influence) and discouragement from family and friends (39.47% indicating no influence), all other barriers had higher frequencies for one of these two responses: slightly influential or extremely influential.

Table 3. Barriers to working in construction.

Factor	Mean	SD	Responses^a	Frequency	%^b
Discrimination in hiring	3.96	.96	Not influential at all	18	2.7
			Not very influential	44	6.7
			No influence	68	10.4
			Slightly influential	331	50.5
			Extremely influential	182	27.8
Male-dominated culture	4.64	.67	Not influential at all	5	.8
			Not very influential	10	1.5
			No influence	12	1.8
			Slightly influential	158	24.1
			Extremely influential	467	71.3
Lack of separate and hygienic	3.54	1.10	Not influential at all	37	5.6
sanitary facilities on job sites			Not very influential	77	11.8
			No influence	163	24.9
			Slightly influential	248	37.9
			Extremely influential	126	19.2
Unequal treatment on the job	4.25	.86	Not influential at all	10	1.5
			Not very influential	23	3.5
			No influence	50	7.6
			Slightly influential	279	42.6
			Extremely influential	289	44.1
Limited apprenticeship	3.70	1.03	Not influential at all	26	4
opportunity			Not very influential	45	6.9
			No influence	178	27.2
			Slightly influential	245	37.4
			Extremely influential	154	23.5
Sexual harassment	4.01	.93	Not influential at all	14	2.1
			Not very influential	31	4.7
			No influence	100	15.3
			Slightly influential	295	45
			Extremely influential	209	31.9
Negative attitudes of male	4.18	.90	Not influential at all	12	1.8
co-workers			Not very influential	26	4
			No influence	64	9.8
			Slightly influential	279	42.6
			Extremely influential	268	40.9
Fewer career supports	3.89	1.01	Not influential at all	19	2.9
			Not very influential	36	5.5
			No influence	149	22.7
			Slightly influential	238	36.3
			Extremely influential	207	31.6
Difficulty in balancing work	4.42	.87	Not influential at all	10	1.5
and family			Not very influential	18	2.7
			No influence	52	7.9
			Slightly influential	180	27.5
			Extremely influential	387	59.1
Lack of participation in	4.03	.99	Not influential at all	17	2.6
decision-making			Not very influential	33	5
			No influence	108	16.5
			Slightly influential	246	37.6
			Extremely influential	245	37.4
Physical strength	3.27	1.11	Not influential at all	53	8.1
			Not very influential	93	14.2
			No influence	216	33
			Slightly influential	201	30.7
			Extremely influential	86	13.1
Bad working conditions	3.46	1.07	Not influential at all	38	5.8
			Not very influential	64	9.8
			No influence	221	33.7
			Slightly influential	212	32.4
			Extremely influential	114	17.4
Fewer career opportunities	3.61	1.10	Not influential at all	29	4.4
			Not very influential	68	10.4
			No influence	185	28.2
			Slightly influential	211	32.2
			Extremely influential	157	24
Long working hours	4.03	1.05	Not influential at all	18	2.7
			Not very influential	45	6.9
			No influence	108	16.5
			Slightly influential	208	31.8
			Extremely influential	271	41.4
Changing work locations	3.66	1.07	Not influential at all	26	4
			Not very influential	60	9.2
			No influence	180	27.5
			Slightly influential	219	33.4
			Extremely influential	161	24.6
Discouragement from family and friends	3.34	1.06	Not influential at all	39	6
			Not very influential	77	11.8
			No influence	258	39.4
			Slightly influential	177	27
			Extremely influential	98	15

^a Coded as follows: Not influential at all 1; Not very influential 2; No influence 3; Slightly influential 4; and Extremely influential 5.

^b The small number of nonresponses were not included and thus total may not equal 100.

Table 4 presents means, standard deviations, frequencies and percentages of the responses for the five factors for leaving construction. Personal factors (mean .79) are the most important reasons for participants leaving the industry, followed by opportunity to work in another job (mean .46). Except for personal factors (which 76.6% selected), all other factors had more ‘No’ responses than ‘Yes’ responses.

Table 4. Reasons for leaving.

Factor	Mean	SD	Responses^a	Frequency	%
Personal factors (e.g. retirement, work–family balance, personal development)	.79	.41	Yes	502	76.6
			No	131	20
			No response	22	3.4
Opportunity to work in another job with same pay and benefits	.46	.50	Yes	289	44.1
			No	344	52.5
			No response	22	3.4
Industry culture factors (e.g. sex discrimination, male-dominated culture,	.39	.49	Yes	248	37.9
discriminatory hiring)			No	385	58.8
			No response	22	3.4
Past work-related injury	.04	.20	Yes	25	3.8
			No	608	92.8
			No response	22	3.4
Working conditions factors (e.g. long working hours, changing work locations,	.39	.49	Yes	250	38.2
lack of sanitary facilities on job sites)			No	383	58.5
			No response	22	3.4

^a Coded as follows: Yes 1; No 0.

We compared participants’ responses based on their ages and current roles in construction. Table 5 presents the results of a one-way between-subjects ANOVA with three categories of age (under 35 years, 35–44 years and 45 plus years) as the independent variable and each of the attraction factors and barriers as the dependent variable. The results showed a significant difference among the categories of age for four attraction factors (career advising, salary/wages, career opportunities in construction and available training) and three barriers (discrimination in hiring, lack of participation in decision-making and fewer career opportunities). The mean scores are higher for the group aged under 35 years for the four attraction factors, and higher for the 45 plus years group for the three barriers.

Table 5. ANOVA results for age categories.

Variable	Mean for under 35	Mean for 35–44	Mean for 45 plus	F
Attraction
Career advising	3.45	3.21	3.11	8.99, p < .001
Family influence	3.59	3.60	3.47	.86, n.s.
Salary/wages	3.95	3.72	3.58	9.48, p < .001
Industry image	3.21	3.22	3.13	.42, n.s.
No other opportunities for work	2.93	3.13	2.98	2.87, n.s.
Career opportunities in construction	4.04	3.88	3.83	3.74, p < .05
Available training	3.53	3.43	3.31	3.56, p < .05
Barriers
Discrimination in hiring	3.82	4.06	4.07	5.08, p < .01
Male-dominated culture	4.62	4.66	4.66	.22, n.s.
Lack of separate and hygienic sanitary facilities	3.50	3.53	3.60	.41, n.s.
Unequal treatment on the job	4.26	4.26	4.22	.14, n.s.
Limited apprenticeship opportunity	3.71	3.75	3.64	.51, n.s.
Sexual harassment	4.01	4.06	3.94	.64, n.s.
Negative attitudes of male co-workers	4.20	4.25	4.06	2.09, n.s.
Fewer career supports	3.82	3.97	3.90	1.32, n.s.
Difficulty in balancing work and family	4.41	4.47	4.35	.94, n.s.
Lack of participation in decision-making	3.92	4.10	4.14	3.46, p < .05
Physical strength	3.31	3.18	3.30	.83, n.s.
Bad working conditions	3.38	3.54	3.51	1.52, n.s.
Fewer career opportunities	3.48	3.65	3.81	4.93, p < .01
Long working hours	3.97	4.14	3.99	1.76, n.s.
Changing work locations	3.58	3.80	3.64	2.57, n.s.
Discouragement from family and friends	3.37	3.34	3.27	.44, n.s.

N for under 35 years is about 290; 35–44 years is about 200; 45 plus years is about 155.

A chi-square test was performed to evaluate the association between reasons for leaving (yes or no responses) and age categories (under 35 years, 35–44 years and 45 plus years). The results suggest that only two reasons for leaving were significantly associated with the three age categories: industry culture factors χ²(2) = 20.93, p < .001, and working conditions factors χ²(2) = 15.52, p < .001. Younger women considered these factors more important reasons for leaving than did older women (Table 6).

Table 6. Chi-square results for age categories.

Variable	N for ‘1’ for under 35	N for ‘1’ for 35–44	N for ‘1’ for 45 plus	Chi-square
Reasons for leaving
Personal factors	227	147	127	5.17(2), n.s.
Opportunity to work in another job	137	92	59	5.10(2), n.s.
Industry culture factors	127	84	37	20.93(2), p<.001
Past work-related injury	13	7	5	.70(2), n.s.
Working conditions factors	129	79	42	15.52(2), p<.001

Table 7 presents the results of the one-way between-subjects ANOVA with three categories of current role (nonmanagers, professionals and managers) as the independent variable and each of the attraction factors and barriers as the dependent variable. The results showed a significant difference between the categories of current role for four attraction factors (career advising, industry image, no other opportunities for work and available training) and three barriers (difficulty in balancing work and family, physical strength and long working hours). The mean scores are higher for nonmanagers for the four attraction factors and higher for managers for the two barriers. Physical strength had a higher mean score for nonmanagers as a barrier.

Table 7. ANOVA results for current role.

Variable	Mean for nonmanagers	Mean for professionals	Mean for managers	F
Attraction
Career advising	3.48	3.32	3.21	3.96, p < .05
Family influence	3.46	3.61	3.57	.86, n.s.
Salary/wages	3.86	3.71	3.84	1.78, n.s.
Industry image	3.39	3.21	3.12	3.17, p < .05
No other opportunities for work	3.23	3.00	2.93	4.31, p < .05
Career opportunities in construction	3.98	3.94	3.94	.12, n.s.
Available training	3.65	3.44	3.37	4.60, p < .05
Barriers
Discrimination in hiring	4.00	3.91	3.97	.39, n.s.
Male-dominated culture	4.55	4.66	4.67	1.27, n.s.
Lack of separate and hygienic sanitary facilities	3.55	3.52	3.54	.05, n.s.
Unequal treatment on the job	4.14	4.28	4.27	1.09, n.s.
Limited apprenticeship opportunity	3.76	3.66	3.71	.42, n.s.
Sexual harassment	3.94	4.03	4.01	.38, n.s.
Negative attitudes of male co-workers	4.18	4.21	4.16	.22, n.s.
Fewer career supports	3.94	3.86	3.90	.27, n.s.
Difficulty in balancing work and family	4.05	4.50	4.48	12.44, p < .001
Lack of participation in decision-making	3.99	4.00	4.08	.51, n.s.
Physical strength	3.60	3.28	3.13	7.42, p < .001
Bad working conditions	3.51	3.46	3.44	.16, n.s.
Fewer career opportunities	3.75	3.54	3.62	1.52, n.s.
Long working hours	3.68	4.09	4.11	7.93, p < .001
Changing work locations	3.53	3.69	3.69	1.03, n.s.
Discouragement from family and friends	3.45	3.33	3.31	.75, n.s.

N for nonmanagers is about 114; professionals about 247; managers about 290.

Finally, a chi-square test was performed to assess the association between reasons for leaving (yes or no responses) and current role categories (nonmanagers, professionals and managers). The results suggest that only two reasons for leaving were significantly associated with the three age categories: past work-related injury χ²(2) = 13.67, p < .01, and working conditions factors χ²(2) = 11.01, p < .01. Nonmanagers considered past work-related injury an important reason for leaving, while professionals and managers considered working conditions an important reason (Table 8).

Table 8. Chi-square results for current role.

Variable	N for ‘1’ for nonmanagers	N for ‘1’ for professionals	N for ‘1’ for managers	Chi-square
Reasons for leaving
Personal factors	83	189	229	2.67(2), n.s.
Opportunity to work in another job	46	120	123	3.35(2), n.s.
Industry culture factors	39	96	113	1.12(2),.n.s.
Past work-related injury	11	9	5	13.67(2), p < .01
Working conditions factors	29	105	116	11.01(2), p < .01

Discussion

This study aimed to understand women’s perceptions of factors that attract and retain women in the construction industry. In addition, this study explored the dynamics of those factors across three age categories (under 35 years, 35–44 years and 45 plus years) and role levels (managers, professionals and nonmanagers), providing unique findings.

Attracting women to construction

Overall, ‘career opportunities’ is the most positively influential factor in attracting women to the construction industry. This confirms the findings of previous research conducted among women in construction trade roles and female construction students (Bigelow et al. 2015), indicating that ‘career opportunities’ are important across industry sectors and roles. However, in contrast to previous research, we found that the factor ‘salary/wages’ was only slightly positively influential. Bigelow et al. (2019) found that higher salaries were identified as the single best means of attracting and retaining trade workers, while Oo et al. (2020) found that the belief that they would get better pay attracted construction female students to the industry.

The ‘image of the construction industry’, previously found to be largely influential in either a positive (Perrenoud et al. 2020) or a negative way (Menches and Abraham 2007; Wang et al. 2021; Yng Ling and Ho 2013; Yng Ling et al. 2016), was found to have limited influence for women in this study. This change may be due to the image of the industry improving due to recent positive changes in hiring and diversity policies and programs in the industry (Baker, et al. 2021), growing support for women by the industry bodies, and promotional efforts by governments. Most women perceived ‘career advising’ and ‘no other opportunities for work’ as not influential in attracting women. While previous research with women in trades and female students found that ‘available training’ and ‘family influence’ had a significant importance in attracting efforts in construction trades (Bigelow et al. 2015; Bigelow et al. 2019), this was not confirmed in this study.

The findings take on a different lens when considering the attraction factors based on the age of the respondents. For instance, ‘career advising,’ ‘salary/wages,’ ‘career opportunities,’ and ‘available training’ proved to be significantly more important to the younger cohort of women, the under 35 years category. This is consistent with results from previous research on construction students and early career women (Bigelow et al. 2015; Oo et al. 2020), indicating that these factors are critical for successful career development at an early stage of a career. Further, considering role levels, the nonmanager-level participants perceived ‘career advising,’ ‘industry image,’ ‘no other opportunities for work,’ and ‘available training’ as very important attractors to the industry in comparison to other role levels.

Barriers to working in construction

Except for ‘bad working conditions’ and ‘discouragement from family and friends’ (both showing no influence), all 14 other barriers were either slightly or extremely influential. The most influential barriers to women which had been previously identified in other research were: ‘male dominated culture’ (Oo et al. 2022; Shewring 2009), followed by ‘difficulty in balancing work and family’ (Malone and Issa 2014 Navarro-Astor et al. 2017,), ‘unequal treatment on the job’ (Galea et al. 2020), ‘long working hours’ (Baker and French 2018), ‘sexism’ and ‘sexual harassment’ (Holdsworth et al. 2020; Perrenoud et al. 2020).

When considering the impact of barriers based on the age of the respondents, participants in the 45 plus years age category identified ‘discrimination in hiring,’ ‘lack of participation in decision-making,’ and ‘fewer career opportunities’ as the main career barriers in construction. This can potentially be explained by ageism in the industry (Chan et al. 2020; Powell and Sang 2013). With the construction industry culture built on images of masculinity, physical strength and domination (Powell and Sang 2013, Smith 2013), it is likely that ageism is a concern for all older workers, and particularly for women. Further, based on the barriers identified by different role categories, ‘difficulty in balancing work and family’ and ‘long working hours’ were found to be the main barriers for managers, while ‘physical strength’ was an important barrier for nonmanagers. The industry culture of presenteeism affects the working hours and therefore the ‘work–life balance’ of the managers (Baker and French 2018; Bryce et al. 2019; Galea et al. 2020). Nonmanagers, particularly trade workers, could be concerned about the physical strength barriers due to work requirements on-site (English and Le Jeune 2012).

Reasons for leaving

Overall, ‘personal factors’ (e.g. retirement, work–family balance and personal development) were the most important reasons for possibly leaving the industry, confirming the results from previous research (Francis 2017; Oo et al. 2022). Following this, the ‘opportunity to work in another job with same pay and benefits’ was the most important reason for leaving. By contrast, Oo et al. (2020) found that, in their study, most tradeswomen respondents would not leave their jobs for another job with the same pay and benefits. In this study, nonmanagers identified ‘past work-related injuries’ as important reasons for leaving. The professionals and managers identified ‘working conditions’ as potential reasons for leaving.

Further, younger women in the under 35 years category considered ‘industry culture’ and ‘working conditions’ more important reasons for leaving than did older workers. Similarly, Oo et al. (2020) found that factors related to the industry culture were important among tradeswomen. By contrast, Bigelow et al. (2021) found that ‘industry image’ was either positive or had no influence for at least 86% of respondents across all age groups of electrical construction managers, suggesting that the ‘image issue’ may no longer be a significant problem for the industry. In addition, nonmanagers considered ‘past work-related’ injury as an important reason to leave, while professionals and managers considered ‘working conditions’ the most important reason to leave.

Contributions

The results of this study provide a contribution to the body of knowledge and propose several recommendations for practice. While identifying significantly important attracting factors, career barriers and reasons for leaving the industry, our study also identified differences between those factors based on age and role levels. To attract young talent in under 35 years category, highlighting ‘career advising,’ ‘salary/wages,’ ‘career opportunities,’ and ‘available training’ in recruitment efforts will be most effective. Younger women also consider ‘industry culture’ and ‘working conditions’ their main reasons for leaving the industry, indicating that those areas may benefit from improved human resources strategies and policies. On the other hand, when recruiting more mature female employees in the 45 plus years category, initiatives to remove discrimination in hiring, improve autonomy in decision-making and create more career opportunities will be critical.

Considerably different approaches are recommended for different role levels. For women nonmanagers it is recommended to focus on attraction factors such as career advising and training opportunities, while also promoting a positive industry image. Focusing on minimizing career barriers including difficulty in balancing work and family and long working hours will work best in attracting and retaining women managers. Further, the value of well-considered work-life policies and practices is highlighted in achieving more effective recruitment and retention outcomes. Implementing regular and ongoing employees’ consultation via surveys, focus groups or exit interviews, may be beneficial in achieving better understanding of what is important in attracting and retaining women at different role levels (Oo et al. 2020; Dutta and Mishra 2021).

Conclusion

This study focused on exploring the perceived factors that attract and retain women in the construction industry, based on three age categories (under 35 years, 35–44 years and 45 plus years) and three role levels (managers, professionals and nonmanagers). The results provide evidence that recruitment and retention process is complex and the factors that influence the attraction and retention of women in construction are varied based on age and role levels. To effectively attract and retain female applicants, organizations will benefit from differentiating and tailoring their recruitment and retention policies and practices instead of using all-encompassing ‘one size fits all’ strategies. Accurate understanding of what factors are most valued by women of different ages and role levels is needed. Based on this understanding, current policies and programs can be reviewed for relevance and effectiveness, and in turn improved impact and return on investment. However, the study’s limitations call for further research to identify other personal and work-related factors that impact organizational recruitment and retention efforts that have not been considered in this study. Future research could also investigate specific interventions and measures to attract, retain and develop women in the construction industry.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study are available on request from the corresponding author, MB. The data are not publicly available due to restrictions e.g. their containing information that could compromise the privacy of research participants.

Appendix

Scales

Influence of factors in attracting women

How did the following influence your decision to join the construction industry? (1) Career advising; (2) Family influence; (3) Salary/wages; (4) Industry image; (5) No other opportunities for work; (6) Career opportunities in construction; and (7) Available training. The response choices were: Highly negatively (coded as 1); Slightly negatively (coded as 2); No influence (coded as 3); Slightly positively (coded as 4); Highly positively (coded as 5). Source: Bigelow et al. (2019).

Barriers to working in construction

What factors do you believe keep women from working in the construction industry? (1) Discrimination in hiring; (2) Male dominated culture; (3) Lack of separate and hygienic sanitary facilities on job sites; (4) Unequal treatment on the job; (5) Limited apprenticeship opportunity; (6) Sexual harassment; (7) Negative attitudes of male coworkers; (8) Fewer career supports; (9) Difficulty in balancing work and family; (10) Lack of participation in decision-making; (11) Physical strength; (12) Bad working conditions; (13) Fewer career opportunities; (14) Long working hours; (15) Changing work locations; and (16) Discouragement from family and friends. The response choices comprised: Not influential at all (coded as 1); Not very influential (coded as 2); No influence (coded as 3); Slightly influential (coded as 4); and Extremely influential (coded as 5). Source: Oo et al. (2022).

Factors for leaving construction

What factors would affect your decision to leave your construction career in the future? (1) Personal factors (e.g. retirement, work–family balance, personal development); (2) Opportunity to work in another job with same pay and benefits; (3) Industry culture factors (e.g. sex discrimination, male-dominated culture, discriminatory hiring), (4) Past work-related injury and (5) Working conditions factors (e.g. long working hours, changing work locations, lack of sanitary facilities on job sites). The participants could select as many as required. Source: Oo et al. (2020).