Gender participation gap appears prominent in the real estate profession, perhaps owing to firms’ unwillingness to engage female employees or the stereotyped perception of female graduates. This study aims to examine the employment considerations of real estate firms and the factors influencing female employees’ participation in real estate practice.
This study adopted the concurrent mixed-method research approach. For the quantitative, the study adopted closed-ended questionnaires administered to real estate employers and female real estate employees. From 190 to 125 questionnaires administered, respectively, to the employers and the female employees, only 110 (57.89%) and 73 (58.40%) questionnaires were retrieved from the real estate firms and the female employees, respectively. The qualitative data were sourced through interviews. Using a structured interview guide, 10 interviewees representing employers of real estate firms and 10 female employees were interviewed. While the quantitative data were analysed using descriptive and inferential analysis, the qualitative was analysed thematically using NVIVO.
The quantitative inquiry revealed that the major employment considerations are academic qualification, skill requirement, understanding of the local market, professional qualification and salary consideration, among others. The qualitative data also revealed similar results and further revealed other factors including creative and soft skills like computer literacy and positive attitude. Concerning female employees’ interest in real estate practice, factor analysis revealed five factors. These factors include financial and working conditions, the nature of tasks and the industry’s image, the potential for career advancement and economic conditions, the influence of third parties/mentorship and the financial prospects of the profession.
This study established that gender bias and stereotypes do not influence employment by real estate firms; rather, the firms emphasize efficiency, capacity and profitability factors in their recruitment process.
The findings of this study could guide in making real estate firms working environment and practice more attractive for female professionals. The finding could also help employers make the internal structure of real estate firms more welcoming for female employees.
1. Introduction
The construction industry is a significant contributor to economic growth. It contributes an average of about 8–10% to the economies of different countries such as China, the United Kingdom and Australia (Opoku et al., 2021). The real estate industry is characterized by male dominance and work cultures that have resulted in the low representation of women (Ernst and Young, 2016; CREW Network, 2020). Although data from the Nigeria Bureau of Statistics (NBS) show that the employment rate for women has increased over the years, from 47.11% in 1991 to 50.55% in 2018, the progress of women’s participation in the Nigerian real estate sector has been abysmally slow (Jimoh et al., 2016; Olaniyan, 2021). Women’s under-representation in the real estate sector is often attributed to the sector’s image and perhaps issues of gender bias and stereotypes (Navarro-Astor, 2016). Lack of information on opportunities and skewed employment considerations are some of the other challenges being faced by female real estate employees (Ishaya et al., 2011; Olaniyan, 2021). Also, Lingard and Francis (2008) identified cultural and structural barriers, limited networking opportunities, long and inflexible working hours and high levels of stress as some other challenges faced by women. These challenges have a foreseeable effect on female staff employment and turnover in the real estate sector.
Historically, the real estate sector is a gendered organization with work practices that favour men and undermine women (Poon and Brownlow, 2016). Isah (2005) submitted that females often experience differential treatment with the type of work and the terms of pay/remuneration. Most often, their qualifications do not influence their job positions, and they are often assigned agency and management roles (Ishaya et al., 2011). Higher education levels attained by women do not seem to be directly translating into increased formal employment levels for women compared to men with comparable levels of education. Thus, the variation between men and women in relation to employment seems to significantly influence recruitment, allocation of roles and promotion decisions among real estate firms. The gender bias seems to be reinforced by the preconceived notion about the inability of females to handle some work-related tasks such as site visits, property development and other physically exerting roles. Issues of work disparity and gender preference could be more pronounced in Nigeria’s real estate practice where professional real estate practitioners, referred to as Estate Surveyors and Valuers (ESVs) are general practitioners. Such individuals are registered and licensed to practice all aspects of the real estate profession, including valuation, investment appraisal, property management, development, real estate brokerage and auctioneering, among others. Thus, the disparities between men and women concerning job positions and work schedules could be significantly influenced during recruitment and promotion decisions. Hence the low participation rate of the female gender in the real estate sector.
The foregoing presupposes that issues relating to gender bias and stereotypes could be major factors influencing employment patterns, labour force participation and the resultant gender participation gap. An important concern for businesses, especially in the real estate industry, is to recognize and manage issues relating to the gender gap (RICS Insight, 2019) through a gender-inclusive workplace culture that transcends equity in gender representation. However, a major challenge towards redressing the gender participation gap is the unconscious bias, which can come from both the employer and female employees. While the issue of the gender participation gap appears prominent in the real estate profession, it might not necessarily be a result of the firms’ unwillingness to engage female real estate practitioners but rather a stereotyped perception about the profession or personal work preferences of the female graduates. Towards this end, this study examined the factors influencing the gender participation gap in real estate practice. This study seeks to answer the following research questions:
What are the employment considerations of real estate firms?
What factors influence female employees’ participation in real estate practice?
2. Literature review
2.1 Employment considerations of real estate firms
Most extant studies (Poon, 2012, 2014) investigating employment considerations of real estate firms seem to focus on general employability skills and competencies, that is, technical or academic competencies of real estate graduates. For instance, focusing on soft skill expectations and gaps, Ayodele et al. (2020a; 2021) argued that employers have high expectations for soft skills such as responsibility, administrative abilities, listening, communication, business negotiation and work ethics. However, gaps exist in skills like logical thinking, marketing and dispute resolution. Oladokun and Gbadegsin (2017) highlighted the preference of firms for technical competencies in valuation, property management, marketing, report writing and landlord-tenant laws. There are yet few studies investigating the demographic and gender-related employment considerations of real estate firms. Poon (2016) noted that English proficiency was an important employment consideration for real estate graduates in Australia. Ford and Elkes (2008) found that real estate employers prioritise skills in real estate finance and teamwork skills, oral communication and interpersonal skills. Highlighting the preference of human resource managers for employability skills, Poon (2012) reiterated the emphasis on soft skills such as report writing skills, communication skills, presentation skills, client care and professional standards and commercial awareness. The study concluded that universities should integrate soft skills into their curriculum.
Several studies have also examined employment considerations with job satisfaction factors and demographic influences. For instance, Martin and Black (2006) found that the quality of the workspace, including specialized spaces like daycare centers, has a significant impact on employees’ productivity, loyalty and retention. With a focus on demographic influences, Ayodele et al. (2020b) found that male real estate employees showed higher organizational commitment than their female counterparts and factors such as age, professional qualifications, marital status and academic qualifications impact employees’ commitment. Ayodele et al. (2020c) submitted that age and marital status are significant factors that affect employees’ job satisfaction and organizational commitment. While these studies provided some insights into employment considerations of real estate firms, focusing on skill competencies and employees’ commitment and job satisfaction, there are still gaps as to how these factors influence the employment consideration of real estate firms.
2.2 Factors influencing female employees’ participation in real estate practice
In the real estate sector, several factors influence female employees’ participation in real estate practice. Dimovski et al. (2013) noted the influence of organizational size and structure on female employees’ participation. The study found that larger real estate enterprises and those with larger boards are more likely to employ female directors.
Highlighting the importance of cultural and socioeconomic factors, Obi-Aso et al. (2024) submitted that the influence of societal stereotypes and culturally imposed burdens has also impacted the career advancement and experiences of married female real estate professionals. Corroborating this view, based on data collected from male and female employees across various fields, Sunita (2023) found that an entry barrier that significantly influences female participation in the workforce is the need for family support. Other influencing factors include gender discrimination and stereotyping. Especially as it relates to the perception that women are less capable of handling some professional tasks effectively (Oluwunmi et al., 2019). These often limit females’ interest in career opportunities and progression in the real estate sector. In a stereotyped work environment, women who lack confidence and self-efficacy are often challenged, and this may hinder their participation and career advancement. Hansen et al. (2023) and Lan Oo et al. (2019) argued that the construction industry generally is characterized by long and inflexible working hours, which can be particularly challenging for women who may have additional family responsibilities. Corroborating this view, Oluwunmi et al. (2019) noted that female real estate professionals face the challenge of balancing work and home responsibilities. The study further noted that this dual burden often deters women from fully engaging in their careers or advancing to higher positions, and they are seen as incapable of practising the profession.
Lack of mentorship has also been identified as a barrier to female participation in real estate practice. For instance, Chiwuzie et al. (2024) submitted that while female students in real estate programs face a lack of access to mentorship opportunities and perceive gender discrimination, mentorship can help to overcome these barriers and pursue careers in the industry. Mcilongo and Strydom (2021) argued that mentorship provides career support and leadership development and helps women overcome gendered barriers to progression in various sectors, including real estate. Corroborating this view, Babatope (2024) noted that mentorship offers psychosocial support, which is crucial for women to develop confidence and leadership skills. This support helps them navigate the male-dominated real estate industry more effectively. Females who are mentored may find it easy to navigate the complexities of their careers, especially in male-dominated industries like real estate. Another barrier to female participation in real estate is the observed gender disparities in the sector. This affects female students’ experiences and readiness to practice (Chiwuzie et al., 2024). Concerns about workplace safety also exist, especially in areas where women perceive the real estate sector as unsafe (Hansen et al., 2023). Lan Oo et al. (2019) alluded to the lack of access or limited informal networks that are crucial for career advancement in male-dominated industries like real estate. Struthers and Strachan (2019) also highlighted that fear of intimidation and harassment deters females from pursuing careers in male-dominated fields. Lack of confidence and inequality in the recruitment process are also identified as key barriers to female students’ career choices in the construction industry by Hansen et al. (2023).
2.3 Review of extant literature
Participation and career progress of the female gender has been of concern across different non-real estate professions. For example, studies have established this in accounting, legal and in other service-oriented professions. In the accounting profession, Flynn et al. (2015) found that there were few female accountants at senior positions among Irish accounting firms because it took longer for women to be promoted to the position of partner. This, according to the authors, represents the existence of the “glass ceiling” effect, an agelong metaphor for the invisible barrier that keeps women from reaching the top level of their profession (Cotter et al., 2001). Flynn et al. (2015) also found that for the female gender to succeed in the accounting profession, they must adapt to masculine occupational values and norms. In the legal profession, Michelson (2013) examined the supply side of lawyers between 1970 and 2010 across eighty-six countries and found that the growth in the supply of female lawyers across the world was far more than that of male lawyers within the period of study because there was a need to fill the wide gap of women access to legal services in the early 1970s. However, despite the increase in number, women in the legal profession remain under-represented across sectors of the legal profession (Latourette, 2004; Brenner, 2014). Also, in Canada, Basin and Ridgedale (2009) found that while women match their male counterparts in law school graduation rate, they are far less represented in private practice, suggesting a low rate of women participation in law practice.
With a focus on real estate-related literature, extant studies have been conducted concerning women and the workplace, unemployment, recruitment and gender stereotypes. Dimovski et al. (2013) assessed the factors influencing the gender composition of the board of directors of Australian Real Estate Investment Trusts (A-REITs). The study found that larger A-REITs companies are more likely to employ a female director. Pauli (2014) examined how annual reports of public housing and commercial real estate companies contribute to “doing gender” in the Swedish real estate industry. Findings from the study showed that men alone were shown more often as employees, while both women and men were portrayed in stereotypical positions. In addition, women were depicted more often as young and presented in “token positions”. Warren (2016) evaluated the role of professional bodies in addressing gender inequality in the makeup of the board composition of the leading professional associations and industry bodies in Australia. The finding showed that the real estate profession, while publicly promoting women, still maintained governing boards that significantly under-represents women. Ibisola et al. (2017) studied the challenges facing women entrepreneurs in the real estate profession in Nigeria. The study found that factors militating against women entrepreneurs in real estate practice in Nigeria include lack of start-up capital, inadequate networking, religion, limited time to spend with families, gender discrimination and a lack of interest in calculation-related tasks, amongst others. In a similar study, Oluwunmi et al. (2019) evaluated gender inequality and discrimination in the real estate industry. The study found that there were fewer female real estate practitioners, and most were attached to the property management department. The challenges encountered by these female employees included difficulty in balancing work and the home front.
Efobi et al. (2020) examined the challenges faced by female estate surveyors and valuers in both the public and private sectors. Challenges identified included difficulty in balancing work and family lives, the inability to attend to assignments outside the town at short notice and lack of marital support. Saka et al. (2022) revealed that female construction professionals represented 6% of the professionals in the Nigerian construction sector, and occupational hazards, matrimonial/family, sexist attitude, expecting/nursing mothers and the nature of the construction industry are the factors that significantly limit female participation. Callanan et al. (2024) examined gender diversity in the Australian valuation industry from the perspective of valuers in senior management and leadership roles. The findings revealed that while gender diversity in the Australian valuation industry has improved over the years, females remained under-represented.
The foregoing suggests that several barriers exert significant influence on female participation in the real estate sector, and these factors are often interconnected and vary across different regions and contexts. Thus, addressing these barriers requires a multifaceted approach that promotes gender diversity and inclusivity. Struthers and Strachan (2019) noted that addressing these barriers requires strategic efforts from industry leaders, policymakers and educational institutions to create a more inclusive and supportive environment for women in the real estate sector. Yet, there are a few studies investigating the recruitment process and interest of women in the real estate profession.
3. Methodology
This study adopted the concurrent mixed-method research approach. The study population consisted of 388 registered real estate firms in Lagos State, according to the Nigeria Institution of Estate Surveyors and Valuers directory (NIESV, 2023). The practice of real estate in Nigeria is regulated by the Nigeria Institution of Estate Surveyors and Valuers. While the practice encompasses all aspects of the real estate profession, the members, referred to as ESVs, are general practitioners licensed to practice all aspects of the profession within the country. The real estate practice in Nigeria is not designed to embrace specialization as it is practiced in other markets like the UK and some other African countries, and this informs the philosophy underpinning the academic, professional training and practice of real estate in Nigeria. Hence, real estate practice, as used in this study, refers to all aspects of the real estate profession.
Based on Watson’s (2001) submission that a minimum of 50% is adequate for a population of about 100, the study employed a sampling frame of 50% of the 388 registered real estate firms in Lagos using simple random sampling. This gives a sample size of 194 real estate firms in Lagos. While there is no sufficient quantitative evidence on the gender distribution of female real estate practitioners in Nigeria, Odudu (2014) cited in Oladapo (2017), suggests that females are about 20% of NIESV members. Regarding the female real estate employees in the case study area, based on a pilot survey, approximately one in every four real estate firms (i.e. 25% of 388) have at least two female real estate employees. This resulted in a sample size of 194 female real estate employees.
The qualitative data were sourced through face-to-face and telephone interviews, using a structured interview guide. Interviewees representing the real estate firms and female real estate employees must have at least 5 years of work experience in real estate practice. The number of interviews conducted was based on the point of saturation, when no new information was gotten (Guest et al., 2020). For the interviews, the point of saturation was reached at the 10th interviewee for both the real estate firms and the female employees. The structured interview for this study was designed for real estate employers and female real estate employees. For the employers, the interview questions focused on the employment considerations of the firms. The interview questions for the female real estate employees focused on the factors influencing female employees’ participation in real estate practice.
The study adopted self-administered, close-ended questionnaires. Two different questionnaires were administered. The first was for heads or managing partners/senior managers of the real estate firms, while the respondents for the second questionnaire were female real estate employees, two of whom were chosen in each firm. While the first questionnaire covered questions relating to the firm’s profile, the next section considered questions on the profile of the respondent. Questions on employment considerations were discussed in the subsequent section. The second questionnaire covered questions relating to the demographic profile of the real estate employees, their perception of the employment consideration and factors influencing their participation. The questions were drawn using a 7-point Likert scale for better reflection of the respondent’s true evaluation, with 7 representing the highest level of importance, agreement and influence and 1 representing the lowest level of importance, agreement and influence.
From a total of 190 and 125 questionnaires administered to the real estate firms and the female real estate employees, only 110 (57.89%) and 73 (58.40%) questionnaires were retrieved from the real estate firms and the female employees, respectively. The quantitative data were analysed using frequency, percentages, mean ranking, independent sample t-test and factor analysis. The statistical reliability and viability were examined using Cronbach’s alpha test. In ascertaining the acceptability of the values of the Cronbach’s alpha test, the test rule according to previous studies, such as Kline (2000), indicated that α > 0.9 is regarded as excellent, 0.9 > α > 0.8 is regarded as good, and 0.8 > α > 0.7 is regarded as acceptable. An examination of the alpha coefficient of all the factors indicated that all the items/constructs had a satisfactory measure of internal consistency.
The interviews were analysed using the N-VIVO. The interviewees (employers and female real estate employees) were coded to ensure anonymity and confidentiality. The employers were coded as EMPL1, EMPL2, …, EMPL10, while the female real estate employees were coded as FPE1, FPE2, …, FPE10. Furthermore, the data collected from the interviewees was analysed with the use of N-VIVO, and the results were used to triangulate the results of the quantitative survey.
Concerning the first objective, the study evaluated the differences/agreement in the rating of the employers and the female employees using the Rank agreement analysis (Adabre et al., 2020). The “rank agreement factor” (RAF) shows the absolute average disparity or consensus in the mean item rating between the employers (Category 1) and female employees (Category 2). The RAF is computed using the following formulae:
The percentage disagreement (PD) is given by
The percentage agreement (PA) is given by
where: Ri1 and Ri2 represent the rank in groups 1 and 2, respectively; Rij is the sum of the ranks by the two groups; Rj2 represents the mean value of the total ranks; N denotes the number of benefits in each component; K is the number of groups, that is, 2); (Ri1-Ri2) represents the difference in the ranks obtained from the two categories; Ri of an item is the sum of the ranks of the item from the employers and female employees.
4. Analysis and discussion of results
The discussion is divided into three sections. The first presents the profile of the respondents. The second examines the employment considerations of the firms from the viewpoint of the employers, that is, the real estate firms and the employees. The third section assesses the factors influencing female employees’ participation in real estate practice.
4.1 Profile of the respondents
Real Estate Employers
The result showing the profile of employers is presented in Table 1. The gender distribution showed a dominance of male employers (85.5%). Thus reinforcing the male gender-dominated nature of the real estate profession. The result of the years of experience in real estate practice showed that 60.8% of employers cumulatively had over 5 years of work experience. The analysis of the highest academic qualification showed that 76.4% of the respondents had at least a first degree, that is, Higher National Diploma (HND)/Bachelor of Science (BSc) degrees. The analysis suggests that the respondents are experienced and familiar with the work practices of the profession, the gender implications and perceptions of the real estate sector and employment preferences.
Female Real Estate Employees
Respondents profile
| Profile | Frequency | Percentage (%) | |
|---|---|---|---|
| Employers | |||
| Gender | Male | 94 | 85.5 |
| Female | 16 | 14.5 | |
| Total | 110 | 100.0 | |
| Years of Experience in Real Estate Practice | Up to 5 years | 42 | 38.2 |
| 6–10 years | 42 | 38.2 | |
| 11–15 years | 15 | 13.6 | |
| 16–20 years | 5 | 4.5 | |
| 21 years and above | 5 | 4.5 | |
| No Response | 1 | 0.9 | |
| Total | 110 | 100.0 | |
| Highest Academic Qualification | HND/BSc | 84 | 76.4 |
| PGD | 4 | 3.6 | |
| MBA/MSc/MPhil | 22 | 20.0 | |
| PhD | 0 | 0.0 | |
| Total | 110 | 100.0 | |
| Female Real Estate Employees | |||
| Designation | Associate Partner | 1 | 1.4 |
| Estate Surveyor | 68 | 93.2 | |
| Management Surveyor | 3 | 4.1 | |
| Head of Department | 1 | 1.4 | |
| Total | 73 | 100.0 | |
| Age | 30 years and below | 45 | 61.6 |
| 31–40 years | 28 | 38.4 | |
| 41–50 years | 0 | 0.0 | |
| 51–60 years | 0 | 0.0 | |
| 61 years and above | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Marital Status | Single | 45 | 61.6 |
| Married | 28 | 38.4 | |
| Divorced | 0 | 0.0 | |
| Widowed | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Academic Qualification | HND/BSc | 70 | 95.9 |
| PGD | 0 | 0.0 | |
| MBA/MSc/MPhil | 3 | 4.1 | |
| PhD | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Professional Qualification | Prob/Graduate | 60 | 82.2 |
| ANIVS | 13 | 17.8 | |
| FNIVS | 0 | 0.0 | |
| RSV | 0 | 0 | |
| Total | 73 | 100.0 | |
| Years of Experience in Real Estate Practice | 1 to 5 | 57 | 78.1 |
| 6 to 10 | 16 | 21.9 | |
| 11 and above | 0 | 0 | |
| Total | 73 | 100.0 | |
| Years of Experience in the Firm | 1 to 5 | 68 | 93.2 |
| 6 to 10 | 5 | 6.8 | |
| Total | 73 | 100.0 | |
| Management Level | Junior | 47 | 64.4 |
| Mid | 24 | 32.9 | |
| Senior | 2 | 2.7 | |
| Total | 73 | 100.0 | |
| Profile | Frequency | Percentage (%) | |
|---|---|---|---|
| Employers | |||
| Gender | Male | 94 | 85.5 |
| Female | 16 | 14.5 | |
| Total | 110 | 100.0 | |
| Years of Experience in Real Estate Practice | Up to 5 years | 42 | 38.2 |
| 6–10 years | 42 | 38.2 | |
| 11–15 years | 15 | 13.6 | |
| 16–20 years | 5 | 4.5 | |
| 21 years and above | 5 | 4.5 | |
| No Response | 1 | 0.9 | |
| Total | 110 | 100.0 | |
| Highest Academic Qualification | HND/BSc | 84 | 76.4 |
| PGD | 4 | 3.6 | |
| MBA/MSc/MPhil | 22 | 20.0 | |
| PhD | 0 | 0.0 | |
| Total | 110 | 100.0 | |
| Female Real Estate Employees | |||
| Designation | Associate Partner | 1 | 1.4 |
| Estate Surveyor | 68 | 93.2 | |
| Management Surveyor | 3 | 4.1 | |
| Head of Department | 1 | 1.4 | |
| Total | 73 | 100.0 | |
| Age | 30 years and below | 45 | 61.6 |
| 31–40 years | 28 | 38.4 | |
| 41–50 years | 0 | 0.0 | |
| 51–60 years | 0 | 0.0 | |
| 61 years and above | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Marital Status | Single | 45 | 61.6 |
| Married | 28 | 38.4 | |
| Divorced | 0 | 0.0 | |
| Widowed | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Academic Qualification | HND/BSc | 70 | 95.9 |
| PGD | 0 | 0.0 | |
| MBA/MSc/MPhil | 3 | 4.1 | |
| PhD | 0 | 0.0 | |
| Total | 73 | 100.0 | |
| Professional Qualification | Prob/Graduate | 60 | 82.2 |
| ANIVS | 13 | 17.8 | |
| FNIVS | 0 | 0.0 | |
| RSV | 0 | 0 | |
| Total | 73 | 100.0 | |
| Years of Experience in Real Estate Practice | 1 to 5 | 57 | 78.1 |
| 6 to 10 | 16 | 21.9 | |
| 11 and above | 0 | 0 | |
| Total | 73 | 100.0 | |
| Years of Experience in the Firm | 1 to 5 | 68 | 93.2 |
| 6 to 10 | 5 | 6.8 | |
| Total | 73 | 100.0 | |
| Management Level | Junior | 47 | 64.4 |
| Mid | 24 | 32.9 | |
| Senior | 2 | 2.7 | |
| Total | 73 | 100.0 | |
Note(s): F – frequency, % Percentage
Source(s): Authors’ own work
The analysis of the demographic profile of female real estate employees (Table 1) showed that 4.1% and 1.4% were management surveyors and Heads of Departments, respectively. Respondents below 30 years of age were 61.6%, suggesting predominantly young and active respondents. The marital status of the respondents showed that 61.6% are single. The higher percentage of single female respondents indicates an increasing number of females practising real estate. Studies such as Blau and Kahn (2017) found that unmarried women participate more in the labour market but have a higher tendency to quit their jobs once married due to the inability to balance work and family responsibilities.
The academic qualification showed that most of the respondents (95.9%) have an HND/BSc. Nevertheless, with the increasing number of women with appropriate academic qualifications, Fortin (2005) submitted that there is still a perception of the lack of suitably qualified women for managerial positions. The respondents’ professional qualifications showed that 82.2% and 17.8% of the respondents are probationers/graduate members and Associate members of the Nigerian Institution of Estate Surveyors and Valuers (NIESV). The high level of unregistered female respondents might be a result of uncertainty in building a career in the profession. The level of interest in pursuing professional development in any profession can be compromised due to uncertainty. Also, lack of motivation could be the predisposing factor for the high percentage of unregistered female respondents, as their qualifications do not influence their job positions and career progression, as noted by Ishaya et al. (2011).
The result also showed that most of the female respondents (78.1%) had 1–5 years of experience in real estate practice. Most of the respondents (93.2%) have been working in their current firms for 1–5 years. The result further showed that respondents in the junior management cadre accounted for 64.4%, while mid and senior management cadre accounted for 32.9 and 2.7%, respectively. Bezbaruah (2008) noted that the under-representation of women in senior management roles, given the rise of women in professional jobs, is a recurring theme across the service sector.
Profile of Interviewees
For the employers, the result of the analysis showed that 60% had a bachelor’s degree and 40% had a Master’s degree. All are professional members of the Nigerian Institution of Estate Surveyors and Valuers with 159 years (mean - 15.9 years; min - 10 years, max – 36 years) of cumulative experience in the real estate practice. This implies that the employers have gathered experience to be familiar with the work practices of the profession, hence, they are suitable interviewees.
The profile of the female real estate employees showed that 80% have a bachelor’s degree and 20% have a master’s degree. Most of them are also professional members of the NIESV. Cumulatively, the employees have a total of 66 years (mean - 6.6 years; min - 5 years, max – 10 years) of work experience in real estate practice. This shows that the female estate surveyor employees have the minimal number of years of experience required to be interviewed; hence, they are suitable for the interview.
4.2 Employment considerations
The employment considerations of the firms were analysed using quantitative and qualitative analysis from the viewpoint of both the employers and female employees.
4.2.1 Quantitative Analysis
An analysis of the mean rating of the general employment considerations (Table 2) showed that academic qualifications (mean = 5.43), skill requirements (mean = 5.34), professional competence (mean = 5.28), academic competence (mean = 5.12), professional qualification (mean = 5.12) and years/level of experience (mean = 5.05) were the top-rated factors influencing employment considerations by the employers. From the female employees’ viewpoint, factors such as professional competence (mean = 5.58), knowledge of the local market (mean = 5.56), skill requirements (mean = 5.49), academic qualifications (mean = 5.47), the firm’s policy regarding employment (mean = 5.36), and the potential to meet financial targets (mean = 5.34) were top-rated considerations for employment by real estate firms.
General factors influencing employment considerations
| General employment considerations | Employers | Female employees | Independent samples test | Rank agreement analysis | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mean(SD) | Ri1 | mean(SD) | Ri2 | T | Df | p-value | Mean diff | Ri | Ri1 – Ri2 | Ri – Rj2 | PD | PA | |
| Academic qualification(s) | 5.43(1.63) | 1 | 5.47(2.02) | 4 | −0.136 | 132 | 0.892 | −0.038 | 5 | 3 | 26 | 26.63 | 73.37 |
| Skill requirement(s) | 5.34(1.53) | 2 | 5.49(1.50) | 3 | −0.683 | 181 | 0.496 | −0.157 | 5 | 1 | 26 | ||
| Professional competence | 5.28(1.59) | 3 | 5.58(1.55) | 1 | −1.239 | 181 | 0.217 | −0.294 | 4 | 2 | 27 | ||
| Academic competence | 5.12(1.50) | 4 | 5.16(1.80) | 10 | −0.182 | 135 | 0.856 | −0.046 | 14 | 6 | 17 | ||
| Professional qualification(s) | 5.11(1.55) | 5 | 5.18(1.90) | 9 | −0.258 | 132 | 0.797 | −0.069 | 14 | 4 | 17 | ||
| Years/level of experience | 5.05(1.56) | 6 | 4.97(1.78) | 17 | 0.292 | 181 | 0.771 | 0.073 | 24 | 10 | 7 | ||
| Salary considerations | 5.05(1.61) | 7 | 5.33(1.60) | 7 | −1.171 | 181 | 0.243 | −0.283 | 13 | 1 | 18 | ||
| Firm’s financial capacity | 5.05(1.70) | 8 | 5.10(1.71) | 14 | −0.196 | 181 | 0.845 | −0.050 | 22 | 6 | 9 | ||
| Firm policy regarding employment | 4.97(1.63) | 9 | 5.36(1.49) | 5 | −1.608 | 181 | 0.110 | −0.383 | 14 | 4 | 17 | ||
| The firm’s vacancy needs | 4.92(1.67) | 10 | 5.04(1.71) | 16 | −0.483 | 181 | 0.630 | −0.123 | 26 | 6 | 5 | ||
| Potential to meet financial targets | 4.88(1.63) | 11 | 5.34(1.52) | 6 | −1.923 | 181 | 0.056 | −0.461 | 17 | 5 | 14 | ||
| Prior performance during the internship | 4.87(1.70) | 12 | 4.96(1.75) | 18 | −0.331 | 181 | 0.741 | −0.086 | 30 | 6 | 1 | ||
| Negotiation/marketing skills | 4.86(1.66) | 13 | 5.21(1.73) | 8 | −1.344 | 180 | 0.181 | −0.343 | 21 | 5 | 10 | ||
| Applicant’s understanding of the local market | 4.83(1.70) | 14 | 5.56(1.63) | 2 | −2.910 | 181 | 0.004 | −0.734 | 16 | 12 | 15 | ||
| Referral/Recommendation | 4.65(1.71) | 15 | 5.15(1.54) | 11 | −2.033 | 181 | 0.044 | −0.505 | 26 | 4 | 5 | ||
| Proximity of workplace to residence | 4.63(1.70) | 16 | 5.12(1.82) | 12 | −1.882 | 181 | 0.061 | −0.496 | 28 | 4 | 3 | ||
| Medical fitness | 4.57(1.87) | 17 | 5.05(1.91) | 15 | −1.695 | 181 | 0.092 | −0.482 | 32 | 2 | 1 | ||
| Applicant’s ability to fit into corporate goals | 4.51(1.68) | 18 | 5.11(1.75) | 13 | −2.328 | 181 | 0.021 | −0.600 | 31 | 5 | 0 | ||
| Applicant’s class of degree | 4.43(1.59) | 19 | 4.74(2.10) | 21 | −1.078 | 125 | 0.283 | −0.312 | 40 | 2 | 9 | ||
| The university the applicant attended | 4.40(1.66) | 20 | 4.78(1.90) | 20 | −1.436 | 181 | 0.153 | −0.381 | 40 | 0 | 9 | ||
| Age | 4.37(1.73) | 21 | 4.45(1.58) | 23 | −0.314 | 181 | 0.754 | −0.079 | 44 | 2 | 13 | ||
| Year of graduation | 4.19(1.72) | 22 | 4.81(1.92) | 19 | −2.219 | 143 | 0.028 | −0.617 | 41 | 3 | 10 | ||
| Permanency/retention potential | 4.08(1.78) | 23 | 4.64(1.93) | 22 | −2.020 | 181 | 0.045 | −0.562 | 45 | 1 | 14 | ||
| Background search | 3.92(1.88) | 24 | 4.34(1.92) | 24 | −1.482 | 181 | 0.140 | −0.424 | 48 | 0 | 17 | ||
| Religious sect | 3.43(1.67) | 25 | 4.07(2.02) | 25 | −2.338 | 181 | 0.020 | −0.641 | 50 | 0 | 19 | ||
| Ethnicity | 3.35(1.70) | 26 | 3.77(2.02) | 26 | −1.524 | 181 | 0.129 | −0.422 | 52 | 0 | 21 | ||
| Family size | 3.22(1.58) | 27 | 3.42(2.15) | 27 | −0.705 | 123 | 0.482 | −0.206 | 54 | 0 | 23 | ||
| Rj2 = 31 | = 94 | = 353 | |||||||||||
| 3.48 | 13.07 | ||||||||||||
| General employment considerations | Employers | Female employees | Independent samples test | Rank agreement analysis | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mean(SD) | Ri1 | mean(SD) | Ri2 | T | Df | p-value | Mean diff | Ri | Ri1 – Ri2 | Ri – Rj2 | PD | PA | |
| Academic qualification(s) | 5.43(1.63) | 1 | 5.47(2.02) | 4 | −0.136 | 132 | 0.892 | −0.038 | 5 | 3 | 26 | 26.63 | 73.37 |
| Skill requirement(s) | 5.34(1.53) | 2 | 5.49(1.50) | 3 | −0.683 | 181 | 0.496 | −0.157 | 5 | 1 | 26 | ||
| Professional competence | 5.28(1.59) | 3 | 5.58(1.55) | 1 | −1.239 | 181 | 0.217 | −0.294 | 4 | 2 | 27 | ||
| Academic competence | 5.12(1.50) | 4 | 5.16(1.80) | 10 | −0.182 | 135 | 0.856 | −0.046 | 14 | 6 | 17 | ||
| Professional qualification(s) | 5.11(1.55) | 5 | 5.18(1.90) | 9 | −0.258 | 132 | 0.797 | −0.069 | 14 | 4 | 17 | ||
| Years/level of experience | 5.05(1.56) | 6 | 4.97(1.78) | 17 | 0.292 | 181 | 0.771 | 0.073 | 24 | 10 | 7 | ||
| Salary considerations | 5.05(1.61) | 7 | 5.33(1.60) | 7 | −1.171 | 181 | 0.243 | −0.283 | 13 | 1 | 18 | ||
| Firm’s financial capacity | 5.05(1.70) | 8 | 5.10(1.71) | 14 | −0.196 | 181 | 0.845 | −0.050 | 22 | 6 | 9 | ||
| Firm policy regarding employment | 4.97(1.63) | 9 | 5.36(1.49) | 5 | −1.608 | 181 | 0.110 | −0.383 | 14 | 4 | 17 | ||
| The firm’s vacancy needs | 4.92(1.67) | 10 | 5.04(1.71) | 16 | −0.483 | 181 | 0.630 | −0.123 | 26 | 6 | 5 | ||
| Potential to meet financial targets | 4.88(1.63) | 11 | 5.34(1.52) | 6 | −1.923 | 181 | 0.056 | −0.461 | 17 | 5 | 14 | ||
| Prior performance during the internship | 4.87(1.70) | 12 | 4.96(1.75) | 18 | −0.331 | 181 | 0.741 | −0.086 | 30 | 6 | 1 | ||
| Negotiation/marketing skills | 4.86(1.66) | 13 | 5.21(1.73) | 8 | −1.344 | 180 | 0.181 | −0.343 | 21 | 5 | 10 | ||
| Applicant’s understanding of the local market | 4.83(1.70) | 14 | 5.56(1.63) | 2 | −2.910 | 181 | 0.004 | −0.734 | 16 | 12 | 15 | ||
| Referral/Recommendation | 4.65(1.71) | 15 | 5.15(1.54) | 11 | −2.033 | 181 | 0.044 | −0.505 | 26 | 4 | 5 | ||
| Proximity of workplace to residence | 4.63(1.70) | 16 | 5.12(1.82) | 12 | −1.882 | 181 | 0.061 | −0.496 | 28 | 4 | 3 | ||
| Medical fitness | 4.57(1.87) | 17 | 5.05(1.91) | 15 | −1.695 | 181 | 0.092 | −0.482 | 32 | 2 | 1 | ||
| Applicant’s ability to fit into corporate goals | 4.51(1.68) | 18 | 5.11(1.75) | 13 | −2.328 | 181 | 0.021 | −0.600 | 31 | 5 | 0 | ||
| Applicant’s class of degree | 4.43(1.59) | 19 | 4.74(2.10) | 21 | −1.078 | 125 | 0.283 | −0.312 | 40 | 2 | 9 | ||
| The university the applicant attended | 4.40(1.66) | 20 | 4.78(1.90) | 20 | −1.436 | 181 | 0.153 | −0.381 | 40 | 0 | 9 | ||
| Age | 4.37(1.73) | 21 | 4.45(1.58) | 23 | −0.314 | 181 | 0.754 | −0.079 | 44 | 2 | 13 | ||
| Year of graduation | 4.19(1.72) | 22 | 4.81(1.92) | 19 | −2.219 | 143 | 0.028 | −0.617 | 41 | 3 | 10 | ||
| Permanency/retention potential | 4.08(1.78) | 23 | 4.64(1.93) | 22 | −2.020 | 181 | 0.045 | −0.562 | 45 | 1 | 14 | ||
| Background search | 3.92(1.88) | 24 | 4.34(1.92) | 24 | −1.482 | 181 | 0.140 | −0.424 | 48 | 0 | 17 | ||
| Religious sect | 3.43(1.67) | 25 | 4.07(2.02) | 25 | −2.338 | 181 | 0.020 | −0.641 | 50 | 0 | 19 | ||
| Ethnicity | 3.35(1.70) | 26 | 3.77(2.02) | 26 | −1.524 | 181 | 0.129 | −0.422 | 52 | 0 | 21 | ||
| Family size | 3.22(1.58) | 27 | 3.42(2.15) | 27 | −0.705 | 123 | 0.482 | −0.206 | 54 | 0 | 23 | ||
| Rj2 = 31 | |||||||||||||
| 3.48 | 13.07 | ||||||||||||
Note(s): SD Standard Deviation; MD Mean Difference; R Rank
*significant at 95% (p = 0.05)
Source(s): Authors’ own work
An examination of the rank agreement analysis of the general employment considerations showed that, though the female employees returned higher mean scores across most of the factors, the ratings of the two groups were similar with some factors. The ratings of the last three factors were similar across both groups. These are affiliation with a religious sect, ethnicity and family size. These ranked, respectively 25th, 26th and 27th across both groups. This suggests that there is consensus among the respondents that these factors do not impact the employment considerations of the real estate firms and perhaps follow the pattern in most western countries where demographic details are not demanded from employees. Overall, the rank agreement analysis had a percentage agreement (PA) value of 73.37%. This indicates a high level of agreement between the two groups.
An examination of the statistical differences between the ratings of the two groups showed that only six factors were significant at p < 0.05. These are the applicant’s understanding of the local market (p = 0.004), referral/recommendation (p = 0.044), applicant’s ability to fit into corporate goals (p = 0.021), year of graduation (p = 0.028), permanency/retention potential (p = 0.045) and religious sect (p = 0.020).
An examination of the gender-related employment considerations (Table 3) showed that employers rated the nature of the work schedule (mean = 4.94), potential to balance work-family life (mean = 4.84), considerations of maternity leave (mean = 4.77), flexibility to cope with complex schedule (mean = 4.73) and industry tradition (mean = 4.72) as important considerations that could influence female employment in real estate firms. Concerning gender-related considerations, the female employees rated clients’ preferences on gender, nature of work schedule, need for an equal employment opportunity and potential to balance work-family life more highly than other factors. These have mean scores of 5.40.5.36, 5.33 and 5.27, respectively. The rank agreement analysis for the gender-related factors showed an agreement percentage of 76.24%, suggesting a high rate of agreement in the rating across both genders.
Gender-related factors influencing employment considerations
| Gender related considerations | Employers | Female employees | Independent samples test | Rank agreement analysis | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean (SD) | Ri1 | Mean (SD) | Ri2 | t | Df | p-value | Mean diff | Ri | Ri1 – Ri2 | Ri – Rj2 | PD | PA | |
| Nature of work schedule | 4.94(1.70) | 1 | 5.36(1.56) | 2 | −1.651 | 180 | 0.101 | −0.411 | 3 | 1 | 15 | 23.76 | 76.24 |
| Potential to balance work family life | 4.84(1.73) | 2 | 5.27(1.81) | 4 | −1.649 | 181 | 0.101 | −0.438 | 6 | 2 | 12 | ||
| Considerations of maternity leave | 4.77(1.70) | 3 | 4.95(1.62) | 7 | −0.685 | 181 | 0.494 | −0.172 | 10 | 4 | 8 | ||
| Flexibility to cope with complex schedule | 4.73(1.59) | 4 | 5.07(1.62) | 6 | −1.414 | 181 | 0.159 | −0.341 | 10 | 2 | 8 | ||
| Industry tradition | 4.72(1.65) | 5 | 4.77(1.66) | 11 | −0.196 | 181 | 0.845 | −0.049 | 22 | 0 | 30 | ||
| Ability to work for long hours | 4.67(1.63) | 6 | 5.08(1.67) | 5 | −1.656 | 181 | 0.100 | −0.409 | 17 | 7 | 35 | ||
| Flexibility to travel | 4.65(1.75) | 7 | 4.78(1.62) | 10 | −0.478 | 180 | 0.633 | −0.123 | 15 | 5 | 15 | ||
| Need for equal employment opportunity | 4.65(1.80) | 8 | 5.33(1.75) | 3 | −2.510 | 181 | 0.013 | −0.674 | 9 | 3 | 9 | ||
| Clients’ preferences on gender | 4.59(1.79) | 9 | 5.40(1.59) | 1 | −3.115 | 181 | 0.002 | −0.806 | 14 | 12 | 14 | ||
| Potential sexual harassment | 4.36(1.83) | 10 | 4.25(2.06) | 14 | 0.403 | 181 | 0.688 | 0.117 | 21 | 7 | 3 | ||
| Marital status | 4.34(1.83) | 11 | 4.51(1.83) | 13 | −0.616 | 181 | 0.539 | −0.170 | 27 | 1 | 27 | ||
| Employers/Firm preference on gender | 3.98(1.71) | 12 | 4.84(1.85) | 8 | −3.198 | 181 | 0.002 | −0.854 | 16 | 0 | 2 | ||
| Feeling that females are feeble | 3.94(1.83) | 13 | 4.75(1.94) | 12 | −2.887 | 181 | 0.004 | −0.817 | 21 | 3 | 3 | ||
| Gender | 3.85(1.69) | 14 | 4.81(1.86) | 9 | −3.595 | 181 | 0.000 | −0.954 | 19 | 1 | 1 | ||
| 18 | 48 | 202 | |||||||||||
| 3.43 | 14.43 | ||||||||||||
| Gender related considerations | Employers | Female employees | Independent samples test | Rank agreement analysis | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mean (SD) | Ri1 | Mean (SD) | Ri2 | t | Df | p-value | Mean diff | Ri | Ri1 – Ri2 | Ri – Rj2 | PD | PA | |
| Nature of work schedule | 4.94(1.70) | 1 | 5.36(1.56) | 2 | −1.651 | 180 | 0.101 | −0.411 | 3 | 1 | 15 | 23.76 | 76.24 |
| Potential to balance work family life | 4.84(1.73) | 2 | 5.27(1.81) | 4 | −1.649 | 181 | 0.101 | −0.438 | 6 | 2 | 12 | ||
| Considerations of maternity leave | 4.77(1.70) | 3 | 4.95(1.62) | 7 | −0.685 | 181 | 0.494 | −0.172 | 10 | 4 | 8 | ||
| Flexibility to cope with complex schedule | 4.73(1.59) | 4 | 5.07(1.62) | 6 | −1.414 | 181 | 0.159 | −0.341 | 10 | 2 | 8 | ||
| Industry tradition | 4.72(1.65) | 5 | 4.77(1.66) | 11 | −0.196 | 181 | 0.845 | −0.049 | 22 | 0 | 30 | ||
| Ability to work for long hours | 4.67(1.63) | 6 | 5.08(1.67) | 5 | −1.656 | 181 | 0.100 | −0.409 | 17 | 7 | 35 | ||
| Flexibility to travel | 4.65(1.75) | 7 | 4.78(1.62) | 10 | −0.478 | 180 | 0.633 | −0.123 | 15 | 5 | 15 | ||
| Need for equal employment opportunity | 4.65(1.80) | 8 | 5.33(1.75) | 3 | −2.510 | 181 | 0.013 | −0.674 | 9 | 3 | 9 | ||
| Clients’ preferences on gender | 4.59(1.79) | 9 | 5.40(1.59) | 1 | −3.115 | 181 | 0.002 | −0.806 | 14 | 12 | 14 | ||
| Potential sexual harassment | 4.36(1.83) | 10 | 4.25(2.06) | 14 | 0.403 | 181 | 0.688 | 0.117 | 21 | 7 | 3 | ||
| Marital status | 4.34(1.83) | 11 | 4.51(1.83) | 13 | −0.616 | 181 | 0.539 | −0.170 | 27 | 1 | 27 | ||
| Employers/Firm preference on gender | 3.98(1.71) | 12 | 4.84(1.85) | 8 | −3.198 | 181 | 0.002 | −0.854 | 16 | 0 | 2 | ||
| Feeling that females are feeble | 3.94(1.83) | 13 | 4.75(1.94) | 12 | −2.887 | 181 | 0.004 | −0.817 | 21 | 3 | 3 | ||
| Gender | 3.85(1.69) | 14 | 4.81(1.86) | 9 | −3.595 | 181 | 0.000 | −0.954 | 19 | 1 | 1 | ||
| 18 | 48 | 202 | |||||||||||
| 3.43 | 14.43 | ||||||||||||
Note(s): SD Standard Deviation; MD Mean Difference; R Rank
*significant at 95% (p = 0.05)
Source(s): Authors’ own work
The results of the mean differences, as shown by the negative mean differences, imply that the female employees rated a higher influence of most of these factors than the real estate employers. The result of the statistical differences between the two groups showed that statistically significant considerations are employers’/firms’ preferences on gender, feeling that females are feeble, gender, need for equal employment opportunities and clients’ preferences on gender. These are significant at p < 0.05.
4.2.2 Qualitative Analysis (Real Estate Employers)
The interview responses of real estate employers showed a similar pattern to mean ratings. A total of 4 interrelated themes influencing employment considerations for female employees were identified and emphasized to include competence and qualifications, personal characteristics and attitude, achievement and results and work habits and ethics.
a. Theme 1: competence and qualifications
These factors primarily relate to the candidate’s ability to perform the job requirements and their level of expertise in the relevant areas. It also includes the organization’s approach to recruiting and selecting candidates, with a focus on merit-based criteria to ensure fairness and equality.
Incisive quotes from the respondents based on the subthemes include:
Effective Job Performance
The normal considerations of employing people, ability to do the job effectively. (EMPL_1)
Competency and Qualifications
Competence …, It is important that the person is very competent and understands the basics. (EMPL_5)
Qualifications, for it to show that they really know what they are doing. (EMPL_2)
We interview them based on their credentials. (EMPL_3)
You have to definitely be a graduate of estate management before the firm can even review your cv. (EMPL_10)
Knowledge of Local Market Areas
Most importantly, at times is your ability to have knowledge about Lagos … to navigate yourself. (EMPL_1)
Work Experience
… experience, for it to show that they really know what they are doing. (EMPL_2)
… your years of experience in the field … aside from the fact that you graduated as a student of estate management, your years of experience comes into play as well which the firm will also want to consider in employing a staff. (EMPL_10)
Merit-Based Recruitment
Well in our firm we don’t have a particular criterion, we only employ based on merit without considering the gender of the candidate. (EMPL_8)
b. Theme 2: personal characteristics and attitude
Beyond competence and qualification, a major theme relates to the candidate’s personal qualities, attitude and approach to their work, which can impact their job performance and fit with the organization.
Incisive quotes from the respondents disaggregated into subthemes include:
Determination and Positive Attitude
… determination to succeed, positive attitude. (EMPL_6)
Willingness to Learn and Grow
Ability to learn … willingness to learn. (EMPL_6)
Willingness for growth and development … Are they willing to grow? (EMPL_7)
Interest and Passion for the Profession
It’s more about people’s attitude and their interest in the profession not what they have upstairs. (EMPL_7)
Zeal, passion for the profession. One cannot practice because it’s a means to an end. (EMPL_9)
Professionalism and Good Temperament
Well I’ll say professionalism. Whoever we decide to hire here is essentially representing our firm. Therefore, we want someone who possesses the characteristics of a professional. (EMPL_4)
Above all, temperament. Some clients can provoke you. (EMPL_9)
c. Theme 3: achievement and results
These factors relate to the employee’s ability to achieve results such as closing deals and perform well in high-pressure situations, such as during interviews and probationary periods.
Incisive quotes from the respondents include:
… and then necessary that they click deals. (EMPL_3)
… and what they are able to deliver at the point of interview. (EMPL_3)
We place them on a period of probation between 3 and 6 months … measured on some parameters, punctuality, interest on the job, how they are able to push one particular assignment or the other … (EMPL_3)
d. Theme 4: work habits and ethics
Another important theme relates to employees’ work habits and ethics, especially as it relates to motivation and the ability to think critically and creatively, which can impact employees’ productivity and job performance.
Incisive quotes related to this theme include:
That's, that's what we want, hardworking. (EMPL_1)
… ability to multitask, … Mental capacity and intellectual capacity. (EMPL_9)
What we try to do in our firm is not to rely so much on qualifications on paper but your creativity. (EMPL_3)
Someone that is creative, not someone that we have to give instruction to all the time. (EMPL_5)
We need someone that can think outside the box. (EMPL_9)
The insights gathered from this report emphasize that real estate employers prioritize a diverse range of skills and characteristics when considering candidates for employment. Key attributes such as effective job performance, competency, the ability to close deals and local market knowledge are essential in their hiring decisions. Employers also value mental and intellectual capacity, alongside creativity, as crucial in adapting to the evolving challenges of the industry.
Moreover, while attributes like hard work, a strong work ethic and professionalism are highly regarded, a focus on merit-based recruitment ensures that gender does not influence hiring decisions, presenting equal opportunities for women in the industry. The significance placed on candidates’ determination, willingness to learn and genuine passion for the profession illustrates the dynamic nature of real estate work.
By understanding these themes, stakeholders can create initiatives that support female participation in real estate, such as targeted training programs and mentorship opportunities that address the competencies and values emphasized by employers. Ultimately, fostering a more equitable, inclusive and supportive environment can enhance female representation in the real estate sector, paving the way for a more diverse and effective workforce.
4.2.3 Qualitative Analysis (Female Real Estate Employees)
The interview responses of the female employees present two distinct outcomes. While some responses resonated with the earlier outcomes that the employers emphasize inclusive and equitable work environment, some others raised issues of bias and discriminatory practice and low wage and toxic workplace culture. Three themes were identified:
a. Theme 1: inclusive and equitable work environment
These factors relate to the creation of a fair and inclusive work environment where all employees are treated equally and have access to the same opportunities, regardless of their gender. The responses showed that some firms demonstrate gender inclusiveness in their hiring and operational practices, promoting equality in the workplace. The perception of equal opportunities for both genders is noted, with some employees affirming a lack of bias in job roles. A notable presence of female employees in certain firms is seen as a sign of a non-biased work environment. Also, the recognition of merit-based staffing practices that include both genders signifies progressive hiring processes.
Incisive quotes include:
… they are gender inclusive. My boss here is not bias when it comes to gender. (F_EMPLOYEE 3)
… they see equal opportunities … They believe ladies too can do the job. (F_EMPLOYEE 6)
My boss was not biased in the process of choosing a staff, he wanted both males and females. There was a kind of balance and in a way, everyone is included. There is no form of bias. Everything is based on merit. (F_EMPLOYEE 8)
Well, in my own time, if you do well then you are qualified. (F_EMPLOYEE 9)
… I don’t think they are bias. We have about eleven female employees working here.” (F_EMPLOYEE 4)
b. Theme 2: discrimination and bias
These factors relate to the presence of bias and discrimination in the workplace, which can negatively impact female employees and create an unfair work environment, as evidenced by some firms’ tendency to prefer male employees for specific roles, citing perceptions of better suitability for job demands and discriminatory hiring practices, such as disproportionately placing female employees on probation, a practice not typically applied to their male counterparts.
Incisive quotes include:
Some ESV firms prefer male employees because they have the quality and can handle the requirements of the work better. (F_EMPLOYEE 1)
During interviews, they are always emphasizing the job description and asking you a thousand time if you can do the job” (F_EMPLOYEE_10)
… I have worked in other firms where there is this form of discrimination … they eventually put you on maybe 3 months’ probation which they don’t usually do for the males. (F_EMPLOYEE_10)
c. Theme 3: low wage and toxic workplace culture
This factor relates to the overall work environment and conditions, including compensation and workplace culture, that disregard personal circumstances and can impact employee well-being and job satisfaction.
Incisive quote:
Their pay is extremely bad and also the way they use the employees is nothing to write home about … they don’t care if you are married or not, they don’t care about your status, you just have to get the work done. (F_EMPLOYEE 2)
The responses illustrate a complex landscape of employment considerations for females in the real estate sector, highlighting both positive trends toward inclusion and areas of deficiencies, such as potential gender biases. Fostering a more equitable work environment requires awareness and targeted interventions against identified biases while promoting the existing positive practices of gender inclusivity and meritocracy.
Triangulating the responses from the mean rating and the interviews, the results, though suggesting a level playing field and non-gender bias considerations during employment, there seems to be an undertone for employees’ capacity and work roles. This might be influenced by the nature of work and complex work schedules peculiar to the real estate profession.
4.3 Factors influencing female employees’ participation in real estate practice
4.3.1 Quantitative Analysis of Factors Influencing Female Employees Participation
The a priori expectation is that one of the factors influencing female employees’ interest in real estate practice is the level of interest in the profession, owing to the gender stereotype associated with most disciplines in the built environment. Thus, the factors influencing female employees’ interest in real estate practice were analysed using factor analysis. Factor analysis was used to group the influencing factors into themes. Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity were used to assess the suitability of the data. The KMO value of 0.639 and Bartlett’s test of sphericity reached a statistical significance (p = 0.00), thereby supporting the factorability of the data sets. Table 4 shows the total variance explained. Using the Varimax rotation, five-factor components accounting for 63.644% of the total variance were extracted. Based on the order of influence, the variance of the five factors was 15.378%, 13.324%, 12.162%, 11.640 and 11.140%.
Total variance explained
| Initial eigenvalues | Extraction sums of squared loadings | Rotation sums of squared loadings | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | % variance | % | Total | % Of variance | % | Total | % Of variance | % | |
| 1 | 6.386 | 22.019 | 22.019 | 6.386 | 22.019 | 22.019 | 4.459 | 15.378 | 15.378 |
| 2 | 4.997 | 17.231 | 39.250 | 4.997 | 17.231 | 39.250 | 3.864 | 13.324 | 28.702 |
| 3 | 2.755 | 9.499 | 48.749 | 2.755 | 9.499 | 48.749 | 3.527 | 12.162 | 40.864 |
| 4 | 2.254 | 7.773 | 56.522 | 2.254 | 7.773 | 56.522 | 3.376 | 11.640 | 52.504 |
| 5 | 2.065 | 7.122 | 63.644 | 2.065 | 7.122 | 63.644 | 3.231 | 11.140 | 63.644 |
| Initial eigenvalues | Extraction sums of squared loadings | Rotation sums of squared loadings | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Total | % variance | % | Total | % Of variance | % | Total | % Of variance | % | |
| 1 | 6.386 | 22.019 | 22.019 | 6.386 | 22.019 | 22.019 | 4.459 | 15.378 | 15.378 |
| 2 | 4.997 | 17.231 | 39.250 | 4.997 | 17.231 | 39.250 | 3.864 | 13.324 | 28.702 |
| 3 | 2.755 | 9.499 | 48.749 | 2.755 | 9.499 | 48.749 | 3.527 | 12.162 | 40.864 |
| 4 | 2.254 | 7.773 | 56.522 | 2.254 | 7.773 | 56.522 | 3.376 | 11.640 | 52.504 |
| 5 | 2.065 | 7.122 | 63.644 | 2.065 | 7.122 | 63.644 | 3.231 | 11.140 | 63.644 |
Note(s): Extraction Method: Principal Component Analysis
Source(s): Authors’ own work
Subsequently, the reliability and consistency of the five components were assessed using Cronbach’s alpha test. The Cronbach’s alpha test result (Table 5) showed an alpha value of 0.874 for Component 1, 0.838 for Component 2, 0.872 for Component 3, 0.819 for Component 4 and 0.822 for Component 5. Tavakol and Dennick (2011) stated that an acceptable Cronbach’s alpha value should not be less than 0.700. Hence, the reliability test showed that the components are reliable with a good measure of internal consistency.
Rotation component matrix and communalities
| Factors | Component | Cronbach’s alpha | Mean | SD |
|---|---|---|---|---|
| Financial prospects/Working Schedule | 0.874 | |||
| Financial prospects of the profession | 0.927 | 4.85 | 2.03 | |
| Financial security | 0.835 | 5.16 | 1.80 | |
| Work schedule | 0.706 | 5.03 | 1.67 | |
| Personal interest | 0.680 | 4.66 | 1.90 | |
| Workplace environment | 0.671 | 4.54 | 2.29 | |
| Job security against unemployment | 0.664 | 4.97 | 1.95 | |
| Nature of task/Industry’s image | 0.838 | |||
| Preference varied nonrepetitive tasks | 0.836 | 4.99 | 1.65 | |
| Remuneration considerations | 0.776 | 5.10 | 1.72 | |
| Desire balance work-family | 0.699 | 5.05 | 1.76 | |
| Inability to get desired job placement | 0.694 | 4.73 | 1.84 | |
| Real estate industry image | 0.663 | 5.10 | 1.49 | |
| To take advantage of inmate business skills | 0.574 | 5.05 | 1.69 | |
| Entrepreneurial nature of the profession | 0.516 | 5.03 | 1.79 | |
| Career advancement | 0.872 | |||
| To build a long-term career | 0.842 | 5.25 | 1.66 | |
| Desire to satisfy clients housing needs | 0.828 | 5.04 | 1.78 | |
| Good opportunities for career advancement | 0.825 | 5.15 | 1.61 | |
| Personal entrepreneurial ambition | 0.780 | 5.00 | 1.64 | |
| Work conditions and terms | 0.619 | 4.86 | 1.60 | |
| Influence of third-party | 0.819 | |||
| Influence from friends/peers | 0.827 | 4.44 | 1.97 | |
| Parental preference/influence | 0.784 | 4.60 | 1.85 | |
| Inability to get the desired course | 0.694 | 4.32 | 1.88 | |
| Advice from career counsellors | 0.616 | 4.89 | 1.55 | |
| Personal prestige/satisfaction | 0.515 | 4.88 | 1.96 | |
| Mentorship | 0.822 | |||
| Influence of parent’s employment | 0.861 | 4.44 | 1.79 | |
| Advice from real estate mentors | 0.813 | 4.70 | 1.73 | |
| Advice from non-real estate mentors | 0.811 | 4.47 | 1.80 | |
| Age | 0.618 | 4.64 | 1.97 | |
| Past experience with real estate professional | 0.585 | 4.75 | 1.76 |
| Factors | Component | Cronbach’s alpha | Mean | SD |
|---|---|---|---|---|
| Financial prospects/Working Schedule | 0.874 | |||
| Financial prospects of the profession | 0.927 | 4.85 | 2.03 | |
| Financial security | 0.835 | 5.16 | 1.80 | |
| Work schedule | 0.706 | 5.03 | 1.67 | |
| Personal interest | 0.680 | 4.66 | 1.90 | |
| Workplace environment | 0.671 | 4.54 | 2.29 | |
| Job security against unemployment | 0.664 | 4.97 | 1.95 | |
| Nature of task/Industry’s image | 0.838 | |||
| Preference varied nonrepetitive tasks | 0.836 | 4.99 | 1.65 | |
| Remuneration considerations | 0.776 | 5.10 | 1.72 | |
| Desire balance work-family | 0.699 | 5.05 | 1.76 | |
| Inability to get desired job placement | 0.694 | 4.73 | 1.84 | |
| Real estate industry image | 0.663 | 5.10 | 1.49 | |
| To take advantage of inmate business skills | 0.574 | 5.05 | 1.69 | |
| Entrepreneurial nature of the profession | 0.516 | 5.03 | 1.79 | |
| Career advancement | 0.872 | |||
| To build a long-term career | 0.842 | 5.25 | 1.66 | |
| Desire to satisfy clients housing needs | 0.828 | 5.04 | 1.78 | |
| Good opportunities for career advancement | 0.825 | 5.15 | 1.61 | |
| Personal entrepreneurial ambition | 0.780 | 5.00 | 1.64 | |
| Work conditions and terms | 0.619 | 4.86 | 1.60 | |
| Influence of third-party | 0.819 | |||
| Influence from friends/peers | 0.827 | 4.44 | 1.97 | |
| Parental preference/influence | 0.784 | 4.60 | 1.85 | |
| Inability to get the desired course | 0.694 | 4.32 | 1.88 | |
| Advice from career counsellors | 0.616 | 4.89 | 1.55 | |
| Personal prestige/satisfaction | 0.515 | 4.88 | 1.96 | |
| Mentorship | 0.822 | |||
| Influence of parent’s employment | 0.861 | 4.44 | 1.79 | |
| Advice from real estate mentors | 0.813 | 4.70 | 1.73 | |
| Advice from non-real estate mentors | 0.811 | 4.47 | 1.80 | |
| Age | 0.618 | 4.64 | 1.97 | |
| Past experience with real estate professional | 0.585 | 4.75 | 1.76 |
Note(s): Extraction method: Principal component analysis
Source(s): Authors’ own work
In the order of influence based on the percentage of variance, the first component themed financial prospects/working schedules includes factors such as financial prospects of the profession, financial security and work schedule. The second component was tagged nature of task/industry’s image, which includes factors such as preference for varied nonrepetitive tasks, remuneration consideration, desire to balance work and family life and inability to get desired job placement.
The third component was termed career advancement, which includes a long-term career, the desire to satisfy clients’ housing needs and good opportunities for career advancement. The fourth component, the influence of third party, had five factors which include influence from friends, parental preference and advice from career and counsellors. The fifth component, termed mentorship, had factors such as the influence of parent’s employment, advice from non-real estate mentors and advice from real estate mentors.
4.3.2 Qualitative Analysis of Factors Influencing Female Employees Participation
In assessing the factors influencing female employees’ participation in real estate practice, four themes were identified and emphasized. These include personal motivations and drivers, practical experience and training, personal belief and family influence and financial and societal factors.
a. Theme 1: personal motivations and drivers
Personal motivations and drivers are significant influences on the career choices and decisions of employees. For many females, an intrinsic love for specific aspects of the profession, such as valuation and agency, serves as a key motivator. However, some individuals may find themselves in the industry without a distinct motivation, often due to circumstances such as admission processes or enrollment decisions. Also, a strong sense of self-efficacy and determination influences females, as they believe in their capabilities and are willing to adapt to the challenges and demands of the profession.
Incisive comments include:
Passion for Professional and Management Aspects
Initially, it was just a course of study but then along the line, I found that I was best skilled in agency … that was when I decided to venture into agency, building and selling of properties. (F_EMPLOYEE 3)
It is a profession a female can also do because it is related to management, …that was what motivated me. (F_EMPLOYEE 1)
… I know estate management has to do with managing of properties, and that was one of the reasons I went for estate management. (F_EMPLOYEE 6)
Self-Efficacy and Determination
I believe I can do, that is like my watchword whatever field I find myself, Just by believing that I can do it … That’s what has been keeping me going, believing that I can do anything and adjusting to any field. (F_EMPLOYEE 2)
Lack of Specific Motivation
… I applied for engineering for my pre-degree but was given estate management. (F_EMPLOYEE 1)
To be honest, I did not even choose real estate, it was not like anything motivated me. I just found myself in real estate and so far, so good I can say that I’m enjoying it. (F_EMPLOYEE 5)
I won’t say there’s anything in particular. (F_EMPLOYEE 6)
… I did not put in for estate management, but because of admission stuff like not getting admission on time, I just found myself in estate management. (F_EMPLOYEE 7)
b. Theme 2: practical experience and training
Practical experience and training, such as industrial training, play a significant role in shaping career interests and skills in the real estate industry. The hands-on nature of real estate work, including inspections and client interactions, appeals to individuals who thrive in dynamic environments and helps to foster a deeper understanding and appreciation of the profession.
Incisive comments from the respondents include:
when we went for IT in part 4 that was when we knew that the course was very nice. It was as if we were not interested while we were in school … but IT opened our eyes to know more. (F_EMPLOYEE 7)
I am the type of person that loves seeing how things are done. I love practical. Real estate practice requires physical tasks, going for inspections with clients, marketing properties, and valuation inspections, the process of determining the value of a property. (F_EMPLOYEE 8)
c. Theme 3: personal belief and family influence
These factors relate to the influence of personal beliefs as a significant factor influencing career choices and the role of support from family members in choosing a career in real estate.
Well, the God factor … I was looking for companies to do my IT … I prayed about it and the first real estate office I went to, they took me in without any interview. Immediately I graduated before youth service, I got a job in an estate firm and I have been working in estate firms ever since. (F_EMPLOYEE 9)
I went for the course because my cousin is into real estate. It was just based on his advice. (F_EMPLOYEE 10)
d. Theme 4: financial and societal factors
These factors relate to financial incentives and social norms and expectations that influence career choices. The responses showed that employees’ attractiveness is enhanced by financial rewards, such as bonuses and commissions, and the opportunity for females to challenge and break down prevailing gender stereotypes, promoting diversity and inclusion.
Economic Incentives
… during my 6months industrial training … I got a percentage of the commission for the sale of a property which was a lot fell in love with the profession immediately … I could only think of what I would have collected if I was a full-time staff (F_EMPLOYEE 4)
… apart from your normal daily activity, if you bring in any extra job, they give you a percentage like a bonus, this motivates. (F_EMPLOYEE 7)
I just wanted a job and I needed money, …, when I got a job in real estate firm. I started loving the job … (F_EMPLOYEE 8)
Challenging Stereotypes
… people say estate management is meant for men. (F_EMPLOYEE 1)
… that what a man can do a lady can do, so I will not say better or not better but I will say a lady can do it if she is determined. (F_EMPLOYEE 6)
The responses gathered from interviews illustrate a diverse range of factors influencing female participation in real estate. From practical experiences during industrial training to personal motivations rooted in love for certain aspects of the profession, traditional gender stereotypes and the need for economic security, these themes reveal both challenges and opportunities within the industry. While some women may find themselves driven by family influence or personal beliefs, others may thrive in the hands-on and client-interactive nature of the job.
5. Discussion of findings
This study provided a bifocal viewpoint of both employers and female real estate employees on issues relating to the gender gap in real estate practice. On the employment considerations of real estate firms, the quantitative inquiry from the employers and female employees revealed that the major factors that estate firms look out for when employing real estate graduates are academic qualification, skill requirement, understanding of the local market, professional qualification and salary consideration, among others. The qualitative data also revealed similar results and further revealed other factors, including creative and soft skills like computer literacy, creativity and positive attitude. It can be deduced from this finding that rather than gender-discriminating factors, real estate firms emphasize efficiency and profitability factors in their recruitment process. This means that factors that estate firms consider in the process of employment are not gender sensitive; hence, female professionals in real estate practice are not discriminated against based on gender in the employment process. This means that the employment process in real estate firms provides equal opportunity for employment for males and females. This study further confirms the findings of a related study from the audit profession, which found education, training, mentorship, gender balance and social skills as supporting factors influencing the career progress of female auditors (Ying et al., 2023). Furthermore, this finding provides valuable clues into areas where real estate students need to develop themselves to increase their chances of securing employment and growing career in real estate practice. On the other hand, while this study focused on the private sector, a similar study by Shukri and Jamaiudin (2020) on the public sector found that gender discrimination exists in the recruitment and promotion process of the civil service system. This further accentuates the difference in the operation of private and public establishments. While private practice firms are purely after efficiency and profitability and thus emphasize these at the recruitment stage, public sector establishments are more of bureaucracy and social services.
On the issue of female employees’ interest in real estate practice, factor analysis revealed five factors that influence the interest of female graduates in taking up the practice of real estate. These include financial/working conditions, nature of task/industry’s image, career advancement/economic condition, the influence of third party/mentorship and the financial prospect of the profession. Furthermore, while the qualitative strand of the study confirmed some of the identified factors, it further revealed a few other interesting factors like experience during Industrial Training (IT), desire to gender stereotype and family influence. This finding provides valuable information that could help in designing policies that could increase female participation in real estate practice. For instance, the study identified good working conditions as an important factor, which suggests that, beyond financial reward, employers should provide a working environment conducive for female employees to strive without feeling inferior to their male counterparts. It is also clear from this study that a mentorship programme for female real estate students could increase their interest in the practice. The importance of mentoring for female practitioners was emphasized by Groenewald et al. (2019), which found one of the reasons why female audit managers resign from audit firms to be a lack of female role models to mentor them. Hence, mentorship programmes should be encouraged by estate firms. Furthermore, the finding suggests the need to make Industrial Training more engaging and practical for female students to boost their interest in the profession. The role of the professional body cannot be overemphasized. For instance, in a bid to encourage and propagate better participation of the female gender in the real estate profession, the NIESV recently made provision for a “Women Estate Surveyor Forum” in the association’s constitution (NIESV, 2023). This is deemed as an avenue to give female professionals a sense of belonging and provide a platform for networking and mentoring, especially for young female real estate professionals.
6. Conclusion
This study investigated factors influencing the gender participation gap in real estate practice, with emphasis on the employment considerations in real estate firms and factors influencing female professionals’ involvement in the practice of real estate. The study employed a mixed-methods approach to data collection and analysis. The findings revealed that the factors that real estate firms consider for employment are not gender discriminatory. Rather, they emphasize productivity, excellence and profit-driven factors. The study also revealed five major factors that make female employees/professionals remain in the practice of the profession.
Based on the findings of this study, we can argue that real estate employers in the Lagos real estate market do not discriminate against female professionals in their employment process. We also argue that gender stereotyping does not influence the interest of female employees in the practice of real estate. This debunks our a priori expectation in this regard.
The findings of this study have implications for both the practice and academic training of female real estate professionals. On the side of practice, the findings of this study could guide in making the working environment and practice in general more attractive for female professionals. The finding could help employers make the internal structure of real estate firms more welcoming for female employees. For example, by emplacing a mentoring system for career advancement in the system. By this, the gender gap in real estate practice could be reduced. On academic training, this study has reiterated the need to make real estate training more practical and the need to lay more emphasis on Industrial Training (IT) to boost the interest of the students in the profession. The study’s findings could help increase the advocacy for diversity, equality and inclusiveness in the real estate industry across other emerging economies where there are increasing calls for increased female participation in real estate practice.
The findings of this study show the need for further studies about the gender gap in real estate practice. For instance, this study was limited to the employment process. Further studies could enquire into whether there are gender discriminatory practices in the internal operations of estate firms. Also, the perspectives of the male real estate employees regarding female employee participation in real estate could be assessed to give a comparative perspective. In addition, we argue that while female participation is low due to several identified factors, further studies could examine the relationship between female participation and the career progression of female employees in real estate practice. Increased participation will give greater access to more females in leadership positions across the real estate sector.
