Barriers to Attracting and Retaining Female Construction Graduates into Academic Careers in Higher Education Institutions

Abstract

Increasing women’s representation in male-dominated professions has become an unending debate due to different gender barriers across various sectors. This study examined the barriers to female construction graduates’ employment as construction faculty in Nigerian higher education institutions. This study developed a quantitative questionnaire to examine the barriers to female construction graduates entering academic careers using purposive sampling technique to identify Master of Science graduate students in higher education institutions in southwestern Nigeria. Three hundred copies of the questionnaire were administered to female construction graduate students, while two hundred and fifty-nine retrieved data were analysed. Firstly, data validity and reliability were determined using Cronbach’s alpha, the Kaiser–Meyer–Olkin (KMO) test, and Bartlett’s sphericity tests, followed by descriptive and exploratory factor analysis. The exploratory factor analysis clustered five factors of barriers to female graduate student recruitment as faculty in higher education institutions: gender profiling, academics competency requirements, non-prioritised support for female careers in academics, female enrolment, graduation, and job position difficulties and perceived difficulties in women’s recruitment, workload, and growth. The study recommends establishing grassroots female careers support, improving female enrolment and graduation rates, campaigning against gender profiling, and establishing career pathways in academics to improve gender inclusiveness in higher education institutions when recruiting female construction graduates as faculty.

1. Introduction

Ongoing debates exist about making career decisions and increasing women’s representation in male-dominated professions [1,2]. This is because countless efforts to increase this status quo across various sectors face different barriers [3,4]. As noted in ref. [5], women’s under-representation in male-dominated professions is due to their being ill-equipped for such work. Beninger [4] reported that about 53% of women, compared to 31% of men, tend to leave jobs in science and tech-intensive industries at higher rates than men due to the intensity of the professions considered male-dominated. Tunji-Olayeni et al. [6,7] posited that several changes have been taking place that have attracted women to move into professions previously considered strictly for men in education, health services, insurance, banking, and retail trade. However, understanding the strategies and drivers guiding against the barriers to recruiting and retaining female employees in male-dominated professions has become imperative in the business, academic, and management literature and in the media [8,9].

The ongoing debate on women’s underrepresentation in certain professions, particularly academics, has been expressed using different perspectives. Bridges et al. [10] viewed the barriers to women’s underrepresentation in male-dominated professions from the perspective of gender identity or segregation. Halliday [1] studied females in male-dominated professions by exploring gender and culture from the perception of social exchange and social identity theories to employee attitudes and behaviours. Notably, females in male-dominated positions are subject to identity threats because, numerically, they are under-represented and subject to negative stereotypes [1,11,12,13,14]. Roksana [11,15] admitted that the female participation rate is lower in construction and engineering, leading to extreme anxiety about professionalism. Given the number of female graduates who complete engineering and construction degree courses yearly, the percentage of women entering academic careers as faculty is still meagre globally [11]. Roksana [11] observed that this dichotomy makes women lose interest in building career progression within this male-dominated industry and divert toward other professions. Thus, the belief that women are less interested in working within the construction or engineering industry (practices or academics) has led to a skills shortage in developing countries [6,11,15].

Ogunbayo et al. [16] admitted that the challenges of HEIs in developing countries, particularly Nigeria, are often based on equity, equality, finance, efficiency, and governance challenges. Likewise, the working conditions and environment of HEIs hinder women’s ability to express themselves without the risk of adverse consequences [17]. Roksana [11,18] argued that a future employment crisis in male-dominated professions is inevitable, with sixty–seventy percent of men in construction and engineering being nearly retirement age, making academic careers in construction more vulnerable to the employment skills gap and the ageing workforce. Tunji-Olayeni et al. [6,19] considered women as untapped human resources to solve skills shortages in the construction industry. However, the masculinised nature of the construction industry is also a significant factor affecting women’s career choices and workforce value [20].

Ceci [21] maintained that much had been written in the last two decades about women’s academic careers in science, engineering, and construction. The most widely agreed-upon conclusion shows that women are underrepresented in academic careers, college majors, and graduate school programmes, which are the most mathematically intensive, like geoscience, construction, engineering, economics, mathematics/computer science, and the physical sciences [21]. Nevertheless, Howe-Walsh [22] states that women struggle to navigate their careers in a gendered environment at each stage, from recruitment and selection to retirement. Research findings revealed that women in academics faced challenges in the recruitment processes of HEIs, discrimination of their competency, and lower publication outputs and research funding than their male counterparts [22]. Cooke [23] added that female faculty are not represented in HEIs and often struggle to attain the positions of associate or full professorships.

Nonetheless, in addressing various problems with women’s employment in construction and engineering, this study seeks to understand the barriers deterring female construction graduates from entering and staying in academic careers within HEIs. Hence, the need for female construction graduates’ recruitment into academia created a gap between improving the demand and supply and overcoming the skills and employment shortages of construction faculties in HEIs. There is a need to holistically identify barriers that could deter female construction graduates from being recruited at construction faculties in Nigerian HEIs. Thus, this study examines barriers to female construction graduates’ recruitment as construction faculty in Nigerian higher education institutions. Likewise, the descriptive statistics examined significant differences in the barriers deterring female construction graduates (architecture, building technology, and quantity surveying) from entering academic careers in Nigerian HEIs. Hence, this study’s objective is achieved through a literature review to establish the barriers deterring female graduates from entering male-dominated professions, especially within the education sector. Given this, the research work intends to provide answers to the following questions.

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what are the identified barriers to female construction graduates in male-dominated professions?

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how can the implications arising from the current study influence the development of knowledge for overcoming the barriers?

Thus, the study findings are expected to assist construction stakeholders, management of HEIs, government policymakers, and professional institutions in understanding strategies to overcome barriers to female construction graduates entering academic careers in Nigerian HEIs.

2. Literature Review

2.1. Theoretical Background Explaining Gender Equality in Academic Careers of Female Construction Graduates

This study engaged labelling theory in explaining the barriers to female construction graduates’ entry into academic careers. The labelling theory propounded by Becker [24,25] is rooted in a sociological perspective that explains contextual knowledge based on self-identity or behaviour using determinants of social status or characteristics for labelling. Ref. [26] admitted that labelling theory is a popular sociological perspective that interrogates dominant norms and values and questions the taken-for-granted understanding of normalcy and deviancy. Kumar [26] added that labelling is a complex procedure rooted in cultural, social, political, and psychological ideologies, which has far-reaching impacts on the identity of individuals or gender profiling threats. Ref. [27] reported that gender stereotypes or gender profiling are threatening and harmful when they limit women’s or men’s capability to excel in a particular field, make a career choice, or develop their abilities. Kumar [26] describes labelling as the perspective that focuses on the interaction between individuals in society, which is the basis for meanings within that society. It indicates that the dominant and influential individuals, social groups, and the state create a widespread perception of crime by labelling some behaviours unacceptable. The labelling process lays bare the social–cultural fundamentals of students’ and faculties’ lives, impacting their life chances, access to capital, and social status within organisational contexts [26]. The labelling theory has been previously explored in race or crime literature to explain social classification, making certain individuals or genders vulnerably labelled and victims of stigmatisation [24,25].

The sociological perspective of labelling theory in this study explains gender equality in the academic careers of female construction graduates in HEIs. Various thoughts labelled gender equality in academic careers as equity are equated with equality through equivalent access to recruitment opportunities, equal payment structures, career development opportunities, and freedom from harassment [23]. Nevertheless, labelling equality is still different from equating equity with equality, assuming the workplace is completely separated from the rest of life. Furthermore, refs. [23,28] argued that labelling gender equality should go beyond balancing opportunities but should be based on practices that promote fairness and take into consideration an academic’s life outside the academy. Labelling gender equality in academic careers considers practices like parental leave but neglects the career consequences for women who take advantage of the leave [23]. Hence, ref. [23] admitted that being gender-neutral or the different life experiences of men and women are often ignored in gender equality definitions and makes the current ‘male’ model the ideal academic normative.

Nonetheless, Becker [24,28] used the experiences of female academics at the Massachusetts Institute of Technology in 2003 to produce the perspective that labelling gender equality that gives full expression should be based on integrating the private sphere of life (community, family, and other personal involvements) and the public sphere of work inclusive. Gender equality in HEIs will require integrating the public and the private sphere of life into organisational culture, policies, and practices and must be modified accordingly and understood by everyone [23]. However, Bailyn [29] maintained that the proportion of female academia generally increases slowly, and women are likelier to be found in junior positions (lecturer), less than their male counterparts, and less likely to be tenured. Researchers have reflected that inherent biases, such as assessing professional competence, disadvantage women while giving men credit for high levels of competence [30,31]. These assumptions labelled women as less competent, which is often found in male-dominated careers, particularly construction and engineering [32,33]. Kumar [26,34] affirmed that the impact of labelling in education on gender or specific individuals could facilitate the passage of supportive policies to provide structures for organisations and organising government programmes. Labelling has often served the purpose of inclusiveness in students’ matriculation or enrolment, graduation, and career choice, linking opportunity to providing additional support to females in male-dominated professions [27]. Such labels tend to profile women’s identity and reduce the degree to which female construction graduates socialise, mix, and enter academic careers in HEIs.

Effort towards improving gender inclusiveness of women and girls in male-dominated careers is supported by the Sustainable Development Goal 5. Gender equality towards women and girls explicitly drives sustainable development [35]. Nonetheless, as informed by the Sustainable Development Goals (SDGs, 2012) [35], Goal 5, gender equality, advocated for women’s and girls’ empowerment against any form of discrimination. The core relevance of Goal 5 is to eliminate violence and harmful practices and ensure equal participation and opportunities for leadership. According to ref. [36], the strategies for achieving SDG 5, gender equality, are by measuring the extent to which countries have legal frameworks in place for gender equality in four areas: overarching legal frameworks and public life, violence against women, employment and economic benefits, and marriage and family. Therefore, this study is underpinned by the labelling theory and its application in examining the barriers to attracting and retaining female construction graduates into academic careers using perceptions of Master of Science students in southwestern Nigerian HEIs as a case study.

2.2. Perspective of Women’s Underrepresentation in Higher Education Institutions

According to Ceci [21], various views were held regarding understanding women’s underrepresentation in academic careers. This includes understanding the perspective of the independent attributes that contribute to women’s underrepresentation, which comprises the demand for students’ enrolment and graduation rates, rates of obtaining tenure-track positions, hiring outcomes, job satisfaction, transition rates, interviewing outcomes, hiring outcomes, promotion rates, salary, work-product evaluation, job persistence, grant-getting success, and number of publications [21]. Ceci [21] argued that understanding the conceptualisation of women’s excellence and productivity, the linkage of women from high school to college to graduate school, and making career choices are also essential. Imasogie [37] admitted that understanding and closing the gap in women’s enrolment in construction and engineering professions will improve gender balance. Hence, stakeholders must appraise existing strategies towards delimiting policies, primordial cultures, curricula, and changed career paths to improve women’s enrolment and participation in construction and engineering professions [37]. The low record of women’s enrolment over time has significantly led to a higher concentration of male professional engineers than women [37,38,39]. Maintaining gender balance in academic careers requires addressing women’s enrolment in construction programmes (architecture, building, quantity surveying) in the HEIs to close the gap of female graduates entering academic careers [38]. Nonetheless, Blair-Loy [40] admitted that the prevalent barriers to women in construction in HEIs over two decades include policymakers and researchers focusing on recruitment, retention, and social equity challenges.

Further, Lindberg [41,42] explored the vertical and horizontal analysis of gender balance in recruiting and retaining academia in HEIs. The vertical analysis explains the gender balance of women to men in senior positions (senior lecturer and professorships) in HEIs using the correlation between sex and hierarchical position [41,42]. Refs. [42,43] posited that women are better represented at the lower levels of the academic hierarchy than men at the senior levels. Lindberg [41,42] noted that focusing on the vertical aspect of gender equality contributes to why women’s underrepresentation in several disciplines is not addressed and does not consider that the solutions to underrepresentation must vary across disciplines. However, the demands of HEIs make it challenging to tie women’s underrepresentation to gender inequality in academics to a specific time when it was introduced [42]. Rather, it involves several processes interacting at different periods [42,43]. Hence, Silander [42] argued that a horizontal gender analysis is needed to complement the commonly used vertical analysis to improve gender equality in academia within HEIs. This is because the horizontal analysis of gender balance explains the correlation between sex and the demands of the academic field in which a person works [42].

2.3. Barriers to Female Construction Graduates Entry into Academic Careers in Higher Education Institutions

According to Marra [20,37,44], significant factors affect women’s representation in maintaining gender balance in male-dominated professions. They include cultural setup, sociocultural factors, career path opportunity, psychosocial influence, gender policies, awareness, and negative perception of academic careers for women [6,20,37,44]. Historically, as observed by ref. [23,37,44], women’s participation in male-dominated careers, particularly academic careers, suffered setbacks due to specific stratification attributes that characterised tradition, gender hierarchies, and norms prevailing in the clan, family, and society. Hence, certain cultural or traditional structures support male dominance in a social context [37,44,45]. This stratification often causes women’s work roles to be marginalised within the organisational policies and practices [37,46,47,48]. Nonetheless, the sociocultural and employment biases created due to cultural stratification critically affected female construction graduates’ career choices, training, recruitment, and advancement [21,22,37].

Consequently, scholars also attributed barriers to female construction graduates’ entry into academic careers to the absence of role modelling, mentor–mentee relationships, and low exposure to career paths and opportunities [6,37,44]. The traditional beliefs among family or parents often discourage females from pursuing careers in construction (professional practices and academia). Marra [20,49,50] maintained that poor advising and teaching, lack of family support, and blind cultural setup create difficulties in career path opportunities for women’s workforce value, particularly in academics. These circumstances are evidenced in the role-stereotyped upbringing of females in most families, denying them exposure to career paths in construction from an early age [38]. Thus, women’s career choices in construction, engineering, and science-based education have significantly been influenced by prominent gender segregation and role stereotyping [37].

Furthermore, ref. [37] observed that barriers to women’s career choices in STEM-related subjects (Science, Technology, Engineering, and Mathematics) could be attributed to psychosocial influences. Psychosocial describes the superordinate attributes like psychological or emotional well-being and social and collective well-being [51,52]. It often influences future career choices, levels of achievement, and perspectives. These attributes of psychosocial influence determine the performance of students’ learning in STEM-related subjects. Likewise, ref. [37] posited that poor performance in mathematics or construction is linked to psychological issues and societal differences that make up males compared to females. Notably, the attributes related to the absence of supportive gender policies predominantly affect balancing women’s representation in male-dominated careers [37]. According to refs. [37,42,53], several organisational policies were developed globally. The structures and functions of such policies do not always support women’s career patterns and their need to integrate work with family responsibilities [37,48,54].

Subsequently, the negative perception of the construction field due to its non-gender-inclusive nature concerning women’s recruitment, development, and career advancement often led to sexual harassment, bullying, and discrimination [6,37,54,55,56]. Van-Veelen [17,20,22] attributed the barriers to female construction graduates’ entry into academic careers to lower publication outputs, demanding workplace conditions, and competency discrimination. The set of negative perceptions towards academic careers and the anecdotal feedback about negative experiences and low enrolments affected the recruitment of female graduates’ faculties globally [37,55]. Nonetheless, ref. [18] further informed that the external and internal problems affecting the gender balance of female construction graduates include low wages, time demands, demand for continuous development, high degree of workload, work–life balance problems, job satisfaction, and fear of sexual harassment. Thus, the identified barriers to female construction graduates in male-dominated professions are summarised in

Table 1. Barriers to female construction graduates’ entry into academic careers.

Barriers to Female Construction Graduates’ Entry into Academic Careers	Authors
Women’s marginalised work role	[21,23,37,46,47,48]
Gender identity segregation	[1,10]
Negative stereotypes	[1,37]
Gender profiling threats	[1,10,12,13,14,26]
Difficulties in attaining senior positions	[23,41,42]
Low female students’ matriculation	[21,37,38,39]
Low female graduation rates	[21,40]
Rates of obtaining tenure-track positions	[21,40]
Job satisfaction	[21,40]
Work performance evaluation	[21,40]
Cultural stratification	[18,21,22,23,37]
Difficulties with career path opportunity	[6,20,37,44]
Traditional gender hierarchies	[23,37,44]
Absence of mentor–mentee relationship	[6,38,45]
Lack of family support	[49,50]
Females’ role-stereotyped upbringing	[23,37,57]
Non-supportive organisational policies	[23,37]
Negative perceptions of academic careers	[38,56]
A high degree of workload	[18,23,40]
Demand for continuous development	[10,23,40]
Continuous research and publication demands	[18,23,28]
Fear of sexual harassment	[18,23,40]
The problem of work–life balance	[18,23]
Perceived fairness in the recruitment process	[18,23,29,40]
Demanding workplace conditions	[18,21,23]
Competency discrimination	[20,22]
Lower publication outputs	[20,22]

Source: Authors Literature Review (2023).

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3. Methodology

A quantitative research approach was adopted to examine the barriers for female construction graduates using purposive sampling techniques to identify Master of Science graduate students in HEIs in southwestern Nigeria, as illustrated in Figure 1 below. The study explored the literature review to understand and identify the barriers to female construction graduates’ entry into academic careers in HEIs. A literature review is a quantitative or qualitative channel to identify, select, and critically appraise research questions to formulate answers [58,59]. Ref. [60] admitted that using an extant literature review provides an in-depth understanding of the existing knowledge in the field of research to establish gaps that need consideration. Also, the extant literature review involves a collection of relevant peer-reviewed articles, conference papers, dissertations, and books from online academic databases [61]. Thus, the extant literature review conducted in this study enabled the researchers to understand barriers to female construction graduates’ entry into academic careers in HEIs. A quantitative research design describes the analysis of unbiased mathematical, statistical, or numerical data [62]. It allows structured questionnaires, voting polls, survey studies, or computational techniques to measure or validate existing statistical data and enables the generalisation of research findings [63,64,65]. Hence, a quantitative research method is appropriate for establishing relationships, testing hypotheses, and determining the opinions of a large population, as adopted in this study [65].

A purposive sampling method was used for the field survey to collect data from the targeted population of female graduate students of a Master of Science in construction programmes (architecture, building technology, and quantity surveying departments) within accredited HEIs in southwestern Nigeria. Zhao [66] described purposive sampling as a non-probability sampling technique that allows a representative sample using a subjective method. Zhao [67] maintained that a non-probability sample could be adopted when the research sampling frame is unknown. A non-probability sampling also allows the selection of respondents willing to participate in a survey when a random sampling method could not be used in a chosen representative sample size [68,69]. The HEIs in southwestern Nigeria chosen for this study were accredited universities regulated by the National Universities Commission (NUC) [70]. The accredited HEIs in southwestern Nigeria comprise thirty-nine public and private universities [70]. Nonetheless, the number of universities offering construction programmes in southwestern Nigeria includes ten offering architecture, seven offering building technology, and seven offering quantity surveying degrees [70,71]. The selected accredited HEIs offering construction programmes in southwestern Nigeria include Covenant University, Ota, Ogun State; Federal University of Technology, Akure Ondo State; Obafemi Awolowo University, Ile-Ife, Osun State; and University of Lagos, Lagos State.

Hence, through a purposive sampling approach, a sample size of 300 construction female graduate students was selected within the accredited HEIs in the selected schools. The criteria for inclusion were as follows: female graduate students, particularly Master of Science students studying architecture, building technology, and quantity surveying, and female graduate students in private and public universities within the selected HEIs. A structured questionnaire was developed and used as the primary data collection instrument because of its ability to reach a wide range of audiences promptly. A quantitative research questionnaire was developed for data collection from the extant literature review in the study area. The variables (see Table 1) that informed the development of the research questionnaire were identified through a relevant literature review on the barriers to female construction graduates’ entry into academic careers. A quantitative research questionnaire was then developed based on the variables identified. The extant literature review helped the study to understand the existing knowledge and instruments related to the research area, and this helped to identify the established measurement scales and adapt validated questions for the study.

The research questionnaire was distributed among female construction graduates (Master of Science students) in southwestern Nigerian HEIs to assess the respondents’ knowledge level and perception of the research area. The field survey was conducted to quantify the extent to which the respondents perceived the 27 identified barriers to female construction graduates. The survey questions were based on a five-point Likert scale to codify the responses with 5 = very high extent, 4 = high extent, 3 = moderate extent, 2 = small extent, and 1 = no extent, and to determine the influence of each of the respondent’s scores. The Likert scale was chosen for this study due to its high-reliability coefficients and the enhanced possibility of getting responses that adequately reflect the subject matter. Female graduate students in architecture, building technology, and quantity surveying and female graduate students who at least registered as Master of Science students within selected private and public HEIs were considered relevant to this study. HEIs in southwestern Nigeria were selected due to the high volume of universities offering construction programmes in architecture, building technology, and quantity surveying [70]. A sample size of 300 respondents was selected within the study area. Of the 300 questionnaires administered, 259 completed the survey electronically, representing an 86.3% response rate. Thus, the selected sample size used in this study met the approximate 200–500 participants sample size for using exploratory factor analysis (EFA) [72]. The participants were contacted through the heads of departments and leaders of students’ association bodies of the relevant departments within the selected HEIs. The questionnaire was electronically emailed to the selected respondents via Google Forms. Likewise, the survey biases were managed using a large sample size, indicating the respondents’ voluntary rights to participate or withdraw from the survey at any time. Likewise, only female construction graduates were considered, and research questions were based on facts extracted from the literature reviewed to overcome response bias.

Consequently, IBM SPSS Statistic V28 was used to analyse the data obtained from the field survey. The analysis comprised descriptive statistics (percentages, mean, and standard deviation), the Kruskal–Wallis test, and exploratory factor analysis (Cronbach’s alpha test, Kaiser–Meyer–Olkin (KMO) test, Bartlett’s sphericity tests, and EFA) to examine the respondents’ perceptions of the identified barriers to female construction graduates’ entry into the academic career in the study area. The descriptive analysis in ref. [73] involves using frequency and percentiles for the respondents’ demographic information. Likewise, refs. [74,75,76,77] described the Kruskal–Wallis H as a non-parametric test used to analyse groups’ variance to compare the mean scores on the continuous variables according to the survey participants responses. An exploratory factor analysis (EFA) is a statistical tool that eliminates the high tendency of interrelatedness or severe autocorrelation among the variable factors to produce reliable and stable orthogonal findings [67]. Ref. [78] maintained that EFA establishes the correlation patterns within the dataset, using this in extracting variables into the different factor components. Likewise, the Kaiser–Meyer–Olkin (KMO) and Bartlett’s sphericity tests were used to test the EFA’s data sampling adequacy. EFA helps to reduce large data into small components by discovering their levels of relationship [79]. Cronbach’s alpha test was conducted to determine the data reliability and the interrelatedness of the variables in each component [79]. Hence, Cronbach’s alpha test was used to measure the data reliability and the scale interrelatedness of the identified variables by considering the same construct [79]. As ref. [75] noted, a value of 0.6 is required for the coefficient of a scale to test for data reliability using Cronbach’s alpha. Nonetheless, the data collected for this study returned a Cronbach’s alpha value of 0.938, justifying that the data collection instrument (questionnaire) was reliable and validated the responses obtained from the field survey. Thus, the results of the data analysis were presented in tables and figures.

4. Results and Discussion of Findings

4.1. Respondents’ Demographic Information

Figure 2 presents the respondents’ construction programmes in higher education institutions. Forty-one percent of the total respondents were architecture graduate students, followed by thirty-four percent of building technology graduate students, and twenty-five percent quantity surveying graduate students in the study area.

Figure 3 shows the study findings concerning the respondents’ career choices in academics as faculty. Ninety-five percent of the respondents answered no to career choices in academics as faculty compared to five percent of the study sample size that were willing to choose a career choice as faculty in the construction programme in HEIs. The findings justify the potential barriers known to respondents for not being willing to make career choices in academics.

4.2. Findings from the Descriptive Analysis

Table 2. Barriers to female construction graduates’ entry into academic careers.

Barriers to Female Construction Graduates’ Entry into Academic Careers	Mean	Std. Deviation	Rank	Chi-Square	Asymp-Sig
Competency discrimination	3.67	1.102	1	61.001	0.001
Demanding workplace conditions	3.42	1.088	2	12.452	0.002
Lower publication outputs	3.22	1.121	3	22.069	0.001
Women’s marginalised work role	2.91	0.966	4	8.206	0.017
Gender profiling threats	2.89	0.972	5	6.004	0.005
Gender identity segregation	2.86	1.016	6	3.502	0.174
Difficulties in attaining senior positions	2.73	0.942	7	0.865	0.649
Negative stereotypes	2.73	1.026	7	6.004	0.050
Rates of obtaining tenure-track positions	2.66	0.964	9	2.376	0.385
Job satisfaction	2.66	0.902	9	7.325	0.026
Low female graduation rates	2.59	1.009	11	5.478	0.065
Low female students’ matriculation	2.57	1.003	12	2.197	0.333
Absence of mentor–mentee relationship	2.55	1.057	13	5.840	0.054
Traditional gender hierarchies	2.55	0.985	13	10.976	0.004
Lack of family support	2.50	1.017	15	4.478	0.107
Difficulties with career path opportunity	2.49	0.958	16	1.137	0.567
Cultural stratification	2.46	1.079	17	7.021	0.030
A high degree of workload	2.42	1.126	18	1.758	0.415
Work performance evaluation	2.41	1.021	19	3.523	0.172
Negative perceptions of academic careers	2.40	1.023	20	5.693	0.058
Demand for continuous academic development	2.39	1.157	21	1.788	0.409
Non-supportive organisational policies	2.37	1.101	22	3.918	0.141
Continuous research and publication demands	2.31	1.110	23	3.108	0.211
Females’ role-stereotyped upbringing	2.29	1.078	24	5.478	0.065
Fear of sexual harassment	2.06	1.124	25	1.834	0.400
Problem of work–life balance	2.04	1.113	26	7.691	0.021
Perceived fairness in the recruitment process	1.85	1.121	27	18.977	0.001

presents the respondents’ mean score (MS) and standard deviation (SD) ranking of the barriers to female construction graduates’ entry into academic careers in HEIs within southwestern Nigeria. The respondents ranked the extent of influence of the twenty-seven identified barriers using a five-point Likert scale of 5 = very high extent, 4 = high extent, 3 = moderate extent, 2 = small extent, and 1 = no extent. The analysis results ranked competency discrimination first, with MS 3.67 and SD 1.102; demanding workplace conditions ranked second, with MS 3.42 and SD 1.088; lower publication outputs ranked third, with MS 3.22 and SD 1.121; women’s marginalised work role ranked fourth, with MS 2.97 and SD 0.966; gender profiling threats ranked fifth, with MS 2.86 and SD 0.972; gender identity segregation ranked sixth, with MS 2.89 and SD 1.016; difficulties in attaining senior positions, with MS 2.73 and SD 0.942 and negative stereotypes with MS 2.73 and SD 1.126 ranked seventh; followed by rates of obtaining tenure-track positions with MS 2.66 and SD 0.964 and job satisfaction with MS 2.66 and SD 0.902 ranked ninth. Likewise, low female graduation rates ranked eleventh, with MS 2.59 and SD 1.009; low female students’ matriculation ranked twelfth, with MS 2.57 and SD 1.003; followed by an absence of a mentor–mentee relationship with MS 2.55 and SD 1.057′and traditional gender hierarchies with MS 2.55 and SD 0.985 ranked thirteenth. Lack of family support ranked fifteenth, with MS 2.50 and SD 1.017; difficulties with career path opportunity ranked sixteenth, with MS 2.49 and SD 0.958; cultural stratification ranked seventeenth, with MS 2.46 and SD 1.079; a high degree of workload ranked eighteenth, with MS 2.42 and SD 1.126; work performance evaluation ranked nineteenth, with MS 2.41 and SD 1.021; negative perceptions of academic careers ranked twentieth, with MS 2.40 and SD 1.023. The demand for continuous academic development ranked twenty-first, with MS 2.39 and SD 1.157; non-supportive organisational policies ranked twenty-second, with MS 2.37 and SD 1.101; continuous research and publication demands ranked twenty-third, with MS 2.31 and SD 1.101; females role-stereotyped upbringing ranked twenty-fourth, with MS 2.29 and SD 1.078; fear of sexual harassment ranked twenty-fifth, with MS 2.06 and SD 1.124; the problem of work–life balance ranked twenty-sixth, with MS 2.04.and SD 1.113; and perceived fairness in the recruitment process ranked twenty-seventh, with MS 1.85 and SD 1.121 as the least barrier to female construction graduates entry into academic careers.

As shown in Table 2, a Kruskal–Wallis non-parametric test was used to compare the perspectives depending on their construction programme (architecture, building technology, and quantity surveying). Table 2 shows that eleven out of the twenty-seven identified barriers to female construction graduates’ entry into academic careers had a significant p-value of below 0.05, ranging from 0.001 to 0.05. They included competency discrimination p-value 0.001, demanding workplace conditions p-value 0.002, lower publication outputs p-value of 0.001, women’s marginalised work role p-value of 0.017, gender profiling threats p-value 0.005, negative stereotypes p-value 0.050, rates of obtaining tenure-track positions p-value 0.026, traditional gender hierarchies p-value 0.004, the problem of work–life balance p-value 0.021, and perceived fairness in the recruitment process p-value 0.001. The study findings conform with refs. [12,16], who admitted the existence of low women’s representation in construction and all engineering industries, leading to extreme anxiety on the professionalism level. The study findings also align with refs. [7,12,16], who maintained that women are less interested in working within the construction or engineering industry (practices or academics), which has led to a skills shortage in developing countries.

4.3. Findings from the Exploratory Factors Analysis

4.3.1. KMO and Bartlett’s Test

Table 3. KMO and Bartlett’s Test.

KMO and Bartlett’s Test
Kaiser–Meyer–Olkin Measure of Sampling Adequacy.		0.920
Bartlett’s Test of Sphericity	Approx. Chi-Square	3932.127
	Df	351
	Sig.	0.000

presents the results of the exploratory analysis (EFA) of the twenty-seven identified barriers to female construction graduates’ entry into academic careers in HEIs within southwestern Nigeria, using the IBM SPSS statistics version 26. The EFA used a principal component to check the data appropriateness for factor analysis using Bartlett’s test of sphericity and the Kaiser–Meyer–Olki (KMO) test. A value of 0.920 returned for the KMO test was far more than the 0.6 minimum value, and 0.000 for Bartlett’s test of sphericity was less than the 0.05 level of significant value recommended for EFA data suitability [80,81].

4.3.2. Scree Plot

Figure 4 presents the scree plot graph based on the oblimin rotation method, highlighting the eigenvalue of the twenty-seven identified barriers to female construction graduates’ entry into academic careers in HEIs within southwestern Nigeria. The scree plot graph shows the five factors correlated above 1 eigenvalue before the break in the steep slope. The steep slope represents the extraction of five significant factors clustered, while the gradual trailing represents the other factors <1.0 eigenvalue [73,74].

4.3.3. Communalities

Table 4. Communalities for BCG.

BCG Variables	Initial	Extraction
Women’s marginalised work role	1.000	0.481
Gender identity segregation	1.000	0.727
Negative stereotypes	1.000	0.694
Gender profiling threats	1.000	0.592
Difficulties in attaining senior positions	1.000	0.579
Low female students’ matriculation	1.000	0.636
Low female graduation rates	1.000	0.606
Rates of obtaining tenure-track positions	1.000	0.696
Job satisfaction	1.000	0.680
Work performance evaluation	1.000	0.611
Cultural stratification	1.000	0.629
Difficulties with career path opportunity	1.000	0.526
Traditional gender hierarchies	1.000	0.547
Absence of mentor–mentee relationship	1.000	0.601
Lack of family support	1.000	0.565
Females’ role-stereotyped upbringing	1.000	0.555
Non-supportive organisational policies	1.000	0.665
Negative perceptions of academic careers	1.000	0.612
A high degree of workload	1.000	0.584
Continuous demand for continuous development	1.000	0.677
Research publication demands	1.000	0.593
Fear of sexual harassment	1.000	0.707
Problem of work–life balance	1.000	0.743
Perceived fairness in recruitment process	1.000	0.568
Demanding workplace conditions	1.000	0.603
Competency discrimination	1.000	0.657
Lower publication outputs	1.000	0.699

Extraction method: principal component analysis.

presents the commonalities of the BCG variables of extraction. All the BCG variables had extraction values above 0.1, and the data were appropriate for EFA.

4.3.4. Total Variance Explained

Table 5. Total variance explained.

Component	Initial Eigenvalues			Extraction Sums of Squared Loadings			Rotation Sums of Squared Loadings a
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %	Total
BCG 1	11.185	41.425	41.425	11.185	41.425	41.425	8.314
BCG 2	1.989	7.368	48.793	1.989	7.368	48.793	2.146
BCG 3	1.534	5.683	54.475	1.534	5.683	54.475	4.113
BCG 4	1.103	4.084	58.560	1.103	4.084	58.560	6.743
BCG 5	1.019	3.775	62.335	1.019	3.775	62.335	7.892
BCG 6	0.904	3.347	65.681
BCG 7	0.827	3.062	68.743
BCG 8	0.767	2.841	71.584
BCG 9	0.718	2.658	74.242
BCG 10	0.686	2.539	76.782
BCG 11	0.600	2.223	79.005
BCG 12	0.547	2.027	81.032
BCG 13	0.539	1.997	83.029
BCG 14	0.525	1.943	84.972
BCG 15	0.504	1.868	86.839
BCG 16	0.451	1.669	88.508
BCG 17	0.411	1.521	90.029
BCG 18	0.379	1.402	91.432
BCG 19	0.342	1.268	92.700
BCG 20	0.330	1.222	93.921
BCG 21	0.309	1.144	95.065
BCG 22	0.304	1.126	96.191
BCG 23	0.256	0.947	97.139
BCG 24	0.214	0.791	97.930
BCG 25	0.201	0.745	98.675
BCG 26	0.195	0.722	99.397
BCG 27	0.163	0.603	100.000

Extraction method: principal component analysis. ^a When components are correlated, sums of squared loadings cannot be added to obtain a total variance.

presents the latent root, or Kaiser’s criterion for retaining EFA factors greater than 1.0 eigenvalues of the total variance that explained barriers to female construction graduates’ entry into academic careers in HEIs within southwestern Nigeria. The five factors with eigenvalues >1.0 were explored as 11.185, 1.989, 1.534, 1.103, and 1.019, which explained 41.4252%, 7.368, 5.683, 4.084, and 3.7756%. These factors explained a cumulative percentage of 62.335 of the variance, highlighting the significance of the variables of the five factors.

4.3.5. Pattern Matrix^a

The pattern matrix of how the five factors clustered the BCG variables is presented in

Table 6. Pattern Matrix ^a.

BCG Variables	Component
	1	2	3	4	5
Gender identity segregation	0.919
Negative stereotypes	0.720
Cultural stratification	0.681
Work performance evaluation	0.592
Difficulties with career path opportunity	0.503
Traditional gender hierarchies	0.496
Women’s marginalised work role	0.461
Gender profiling threats	0.425
Lower publication outputs		0.820
Competency discrimination		0.806
Demanding workplace conditions		0.758
Negative perceptions of academic careers			0.620
Non-supportive organisational policies			0.584
Females’ role-stereotyped upbringing			0.449
Lack of family support			0.406
Absence of mentor–mentee relationship			0.406
Rates of obtaining tenure-track positions				0.803
Job satisfaction				0.754
Low female graduation rates				0.597
Low female students’ matriculation				0.531
Difficulties in attaining senior positions				0.524
Problem of work–life balance					0.845
Fear of sexual harassment					0.822
Demand for continuous development					0.698
Continuous research and publication demands					0.682
Perceived fairness in recruitment process					0.651
A high degree of workload					0.503

Extraction method: principal component analysis. Rotation method: oblimin with Kaiser normalisation. ^a Rotation converged in 17 iterations.

. As recommended by refs. [81,82], a common name was given to the five factors clustered from the EFA as follows: Factor 1 was named “gender profiling”; Factor 2 was named “academics competency requirements”; Factor 3 was named; “non-prioritised support for female career in academics”; Factor 4 was named “women enrolment, graduation, and job position difficulties”; and Factor 5 was named “perceived difficulties in women’s recruitment, workload, and growth”. However, the factors were interpreted in line with the inherent relationship between the variables loaded in each factor. Yong [77] recommended a 0.40 loading cut-off as a criterion for retaining the loading value and a significant variable in the EFA factors based on pragmatic reasons. The criterion guided this study to retain the underlying variables with loadings of 0.4 and above.

• Factor 1: Gender profiling.

Gender profiling gathered 41.455% of the variance explained and possessed the highest factor loadings with eight variables loaded. These included gender identity segregation (91%), negative stereotypes (72%), cultural stratification (68%), work performance evaluation (59%), difficulties with career path opportunities (50%), traditional gender hierarchies (50%), women’s marginalised work role (46%) and gender profiling threats (43%), as indicated in Table 6. This emphasised that gender profiling directly influences female graduate students in the construction programme career choice of entry into academics as faculty in HEIs within southwestern Nigeria. The results are in collaboration with [26], who admitted that gender profiling threats labelling are complex procedures rooted in cultural, social, political, and psychological ideologies, which have far-reaching impacts on the identity of individuals. Likewise, to further understand barriers to female graduate students’ employment as faculty in HEIs, we considered various contributing factors to female gender profiling because of gender identity segregation. These are due to women’s unequal access to education, unequal employment opportunities, inadequate legal protection, lack of religious freedom, and inadequate women’s political representation. The study findings also align with the conclusion in ref. [27], which reported that gender stereotype is harmful when it limits an individual’s (women’s or men’s) capability to make career choices, develop personal abilities, or excel in a particular field. The study findings align with the submissions in refs. [23,37,44,45] that cultural or traditional structures support gender hierarchies and norms prevailing in the clan, family, and society, which affect women in male-dominated professions, particularly academic careers. In addition to the findings of refs. [49,50], poor advising and teaching, lack of family support, and blind cultural setup create difficulties in career path opportunities for women’s workforce value, particularly in academics. Thus, the management of HEIs and stakeholders in the construction industry must understand the barriers associated with gender profiling against women to improve women’s career choices in academics as faculty.

• Factor 2: Academics competency requirements.

As indicated in Table 6, due to the correlation of the underlying variables in this cluster, it was renamed as academics competency requirements. This second cluster accumulated 7.368% of the total variance, with three variables loaded as follows: lower publication outputs (82%), competency discrimination (81%), and demanding workplace conditions (78%). The naming of this cluster emphasised academic competency requirements, which directly influenced female construction graduate students in making career choices as academics as faculty in HEIs within southwestern Nigeria. The study findings are consistent with the studies in refs. [17,20,22], which attributed the barriers to female construction graduates’ entry into academic careers to the concern of lower publication outputs, demanding workplace conditions, and competency discrimination. Competency requirements are essential when recruiting faculty in HEIs. However, the process and procedures should be able to balance gender inclusiveness. Hence, in agreement with ref. [40], the prevalent barriers to women in construction in HEIs include policymaking guiding recruitment, retention, and promoting social equity. Therefore, academic competency requirements of female faculty are needed to guide stakeholders, management, and policymakers to improve women’s representation as faculty in HEIs.

• Factor 3: Non-prioritised support for female academic careers.

The naming of the third cluster as non-prioritised support for female academic careers was based on the five loading variables clustered as follows: negative perceptions of academic careers (62%), non-supportive organisational policies (58%), female role-stereotyped upbringing (45%), lack of family support (41%), and absence of a mentor–mentee relationship (41%). This factor amounted to 5.683% of the total variance, directly influencing female construction graduate students’ entry into academics as faculty in HEIs within southwestern Nigeria. The study results show that non-prioritised female career support in academics limits the gender balance in male-dominant professions, particularly construction. These findings collaborated with the factors in refs. [6,37,44], including the absence of role modelling, mentor–mentee relationships, and low exposure to career paths and opportunities, which contributed to the barriers for low female construction graduates’ entry into academic careers. Nonetheless, prioritising support for attracting and retaining female graduates in academic careers is essential for understanding and improving women’s gender balance in HEIs by increasing grassroots female careers support. It will also require a campaign against gender profiling by engaging local, national, and regional interventions. Further, partnering with non-governmental agencies will increase financial support to campaign against gender profiling in reducing female role-stereotyped upbringing.

• Factor 4: Women’s enrolment, graduation, and job position difficulties.

The fourth factor had five variables, including rates of obtaining tenure-track positions (80%), job satisfaction (75%), low female graduation rates (60%), low female students’ matriculation (53%), and difficulties in attaining senior positions (52%). This fourth factor accounted for 4.084% of the total variance. Women’s enrolment, graduation, and job position difficulties were barriers emphasised as directly influencing female construction graduate students’ career choices in academics. Generally, women’s enrolment, graduation, and job position difficulties are dominant when addressing their underrepresentation in the construction or engineering professions. As noted in this study’s findings, refs. [37,55] affirm that the negative perceptions towards academic careers, women’s low enrolment, and graduation rates in construction programmes affected the recruitment of female graduates’ faculty globally. Likewise, aligning the study findings with refs. [21,41,42], the demands of HEIs make it difficult for women in academics to improve the gender balance of the women-to-men ratio in senior positions or hierarchical positions (senior lecturer and professorships). Maintaining the gender balance in academic careers requires addressing women’s enrolment in construction programmes (architecture, building, quantity surveying) in the HEIs to close the gap of female graduates entering academic careers [37]. Thus, improving women’s enrolment, graduation, and job position opportunities in construction professions is essential in attracting and retaining female graduates in academic careers. Furthermore, improving women’s enrolment and graduation in construction programmes will also help solve skills shortages and the ageing faculty workforce in HEIs.

• Factor 5: Perceived difficulties in women’s recruitment, workload, and growth.

The naming of this cluster was based on the perceived difficulties in women’s recruitment, workload, and growth, which negatively impact construction female graduate students’ career choices in HEIs. The six variables in this cluster accounted for 3.775% of the total variance explained and were the least factor loadings. They were the problem of work–life balance (85%), fear of sexual harassment (82%), demand for continuous development (70%), continuous research and publication demands (68%), perceived fairness in the recruitment process (65%), and a high degree of workload (50%). The second factor clustered 3.775% of the total variance. These perceived difficulties in women’s recruitment, workload, and growth are dominant and often contribute to female construction graduates’ underrepresentation in the HEIs. The findings agree with refs. [6,37,54,55] that the negative perception of the construction field is due to its non-inclusive gender nature towards women’s recruitment, fear of sexual harassment, bullying, and discrimination. In addition to this study’s findings in alignment with refs. [6,37,48,53,54], organisational policy structures and functions do not always support women’s career patterns and the need to combine work with family responsibilities. Refs. [23,28] further established that gender equality should go beyond balancing opportunities based on practices that promote fairness and consider taking into account an academic’s life outside the academy. Therefore, attracting and retaining female graduates in academic careers requires fairness in women’s recruitment, job workload, and growth opportunities to balance work–life.

4.3.6. Component Correlation Matrix and Reliability of the Factors

Table 7. Component correlation matrix and reliability of the factors.

Factor	1	2	3	4	5	Cronbach’s Alpha Coefficient
1	1.000	0.102	0.276	0.522	0.539	0.894
2	0.102	1.000	0.033	0.080	0.064	0.725
3	0.276	0.033	1.000	0.260	0.384	0.831
4	0.522	0.080	0.260	1.000	0.447	0.825
5	0.539	0.064	0.384	0.447	1.000	0.873

Extraction method: principal component analysis. Rotation method: oblimin with Kaiser normalisation.

presents the relationship between the cluster group of the factor’s correlation matrix in some clusters with a value around 0.300, showing the relationship within these clusters. Likewise, the result is consistent with refs. [81,82], affirming that clusters value around 0.300, showing the variables relationship dependence highly correlates among these factors. In addition, Table 7 shows the Cronbach alpha coefficient on each variable clustered in the five factors ranging from 0.725 to 0.894. The results agree with refs. [80,81], revealing that the Cronbach alpha coefficient above 0.6 value for the five factors is valid and reliable, validating the data collection instrument used for this study.

5. Conclusions and Recommendations

This study examined the barriers to female construction graduates’ recruitment as faculty in Nigerian higher education institutions. The study adopted a quantitative research approach to examine the barriers to female construction graduates entering academic careers using snowball sampling techniques to identify Master of Science graduate students in HEIs in southwestern Nigeria. The descriptive analysis non-parametric test, using the Kruskal–Wallis H test, showed that the respondents had a significant difference regarding eleven out of the twenty-seven identified barriers to female construction graduates’ entry into academic careers. The barriers included competency discrimination, demanding workplace conditions, lower publication outputs, women’s marginalised work roles, gender profiling threats, negative stereotypes, rates of obtaining tenure-track positions, traditional gender hierarchies, problems of work–life balance, and perceived fairness in the recruitment process. Likewise, the EFA clustered the twenty-seven identified female construction graduates entering academic careers as faculty into five factors. The five barriers to female construction graduates’ entry into academic careers as faculty in Nigerian HEIs were gender profiling, academic competency requirements, non-prioritised support for female academic careers, female enrolment, graduation and job position difficulties, and perceived difficulties in women’s recruitment, workload, and growth. The empirical results from the study supported a theoretical review of barriers to women’s representation in male-dominant professions. According to the descriptive variable ranking, competency discrimination, demanding workplace conditions, lower publication outputs, women’s marginalised work roles, and gender profiling threats were the top-ranked barriers to female construction graduates’ entry into academic careers as faculty in HEIs in Nigeria. Therefore, the management of HEIs and stakeholders in the construction industry must understand the barriers associated with gender profiling against women in academics to improve women’s career choices as faculty. This study shows that maintaining the gender balance in academic careers requires addressing women’s enrolment in construction programmes (architecture, building, quantity surveying) in the HEIs to close the gap of female graduates entering academic careers.

The study findings provide theoretical and practical implications supporting the knowledge gaps. Empirically, the study admitted the need to understand barriers to female construction graduates’ entry into academic careers as faculty in HEIs. The five identified factors from the EFA could assist construction stakeholders, policymakers, and management in higher education institutions in developing strategies to improve women’s recruitment into graduate programmes as faculty in HEIs. Theoretically, the study findings could advance knowledge of the barriers to women’s recruitment into graduate programmes as faculty in HEIs, as indicated in the five factors from the EFA. The essential factors were gender profiling and non-prioritised support for female academic careers, indicating that prioritising support for attracting and retaining female graduates is essential for understanding and improving women’s gender balance in HEIs. The practical implication of the study findings could provide a relevant understanding of barriers to women in male-dominated professions to solve the problem of skill gaps and the ageing workforce in HEIs. These identified factors will help to attract and retain female graduates in academic careers and require fairness in women’s recruitment, job workload, and growth opportunities to help women balance workforces.

This study concludes that using strategies such as media awareness, strengthening female legal protection, equal access to education, and better women’s political representation will improve female enrolment, graduation, and job position opportunities in construction professions. It will also increase efforts in attracting and retaining female graduates in academic careers. Furthermore, improving women’s enrolment and graduation in construction programmes by creating female career path opportunities, eliminating traditional gender hierarchies, and providing access to early mentor–mentee relationships will help solve skills shortages and the ageing faculty workforce in HEIs. The study recommends that the five clustered barriers to female construction graduates’ entry into academic careers encourage women’s inclusiveness and reduce male dominance in construction in senior positions within the HEIs faculty hierarchy. In addition, the study recommends various strategies for improving gender inclusiveness in HEIs when recruiting female construction graduates as faculty. The potential strategies include establishing grassroots female careers support, improving female enrolment and graduation rates, campaigning against gender profiling, and establishing career pathways in academics for women to solve skill gaps and the ageing workforce in HEIs.

This study is limited to female construction graduate students (Master of Science in Architecture, Building Technology, and Quantity Surveying) within southwestern Nigeria HEIs, which means the study findings could be generalised for HEIs in Nigeria. Nonetheless, it is imperative to establish that the construction graduate Master of Science students (architecture, building technology, and quantity surveying) surveyed in this study fairly represent female graduate students in Nigerian higher education institutions. Further research could explore how construction female graduates’ career choices aligned with the academic employment requirements and performances in HEIs.