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Women in Construction Industry Encapsulation of Gender Disparities In Construction Industries of Sindh, Pakistan( MCE THESIS)

By: Engr. Sumra Atique 22-MCE-07 Supervisor - Dr. Jam Shahzaib Khan.
Material type: materialTypeLabelBookPublisher: Nawabshah QUEST 2024Description: 89p.Subject(s): Department of Civil EngineeringOnline resources: Click here to access online Summary: ABSTRACT The industry of construction continues to face challenges regarding gender equality and inclusivity, with women encountering numerous barriers that hinder their participation and advancement within the sector. The research examines the barriers governing gender disparities that women encounter in the industry of construction to understand also the factors contributing to these barriers and proposing evidence-based strategies to address them. The study begins with an exploration of the existing literature on gender inequality and barriers within the construction industry, examining topics such as difficulties faced by the women in construction industry. The research adopted the SPSS, ANNOVA and Regression Analysis. The results outlined and suggested that Security and Equality (WC12), Diversity and Inclusivity (WC14), and Leadership and Advancement (WCI7) are significant predictors of Workplace Challenges. However, Work Environment Perception (WC13), Organizational Support (WC15), Job Satisfaction (WCI), and Gender Perception (WC18) do not significantly influence Workplace Challenges in this model, underrepresentation of women in construction, barriers that women face in construction industry. From all the above-identified results and model, the practitioners of the industry of construction of Pakistan can predict and calculate how much and what change in indicators of industry of construction will occur by putting values of predictors in model. This model will help the construction organizations devise ways to see any adverse effect on the indicator. Moreover, this predictive model will guide them to identify the effect of predictors and decide before starting the activity. Also, this will be helpful for Pakistan's industry of construction to uplift the status of this sector, which will finally result in the country's prosperity. xi
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Thesis and Dissertation Thesis and Dissertation Research Section
Available MP/90-1308
Thesis and Dissertation Thesis and Dissertation Research Section
Available MP/87-1252
Thesis and Dissertation Thesis and Dissertation Research Section
Available MP/87-1253
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ABSTRACT

The industry of construction continues to face challenges regarding gender equality and inclusivity, with women encountering numerous barriers that hinder their participation and advancement within the sector. The research examines the barriers governing gender disparities that women encounter in the industry of construction to understand also the factors contributing to these barriers and proposing evidence-based strategies to address them. The study begins with an exploration of the existing literature on gender inequality and barriers within the construction industry, examining topics such as difficulties faced by the women in construction industry. The research adopted the SPSS, ANNOVA and Regression Analysis. The results outlined and suggested that Security and Equality (WC12), Diversity and Inclusivity (WC14), and Leadership and Advancement (WCI7) are significant predictors of Workplace Challenges. However, Work Environment Perception (WC13), Organizational Support (WC15), Job Satisfaction (WCI), and Gender Perception (WC18) do not significantly influence Workplace Challenges in this model, underrepresentation of women in construction, barriers that women face in construction industry. From all the above-identified results and model, the practitioners of the industry of construction of Pakistan can predict and calculate how much and what change in indicators of industry of construction will occur by putting values of predictors in model. This model will help the construction organizations devise ways to see any adverse effect on the indicator. Moreover, this predictive model will guide them to identify the effect of predictors and decide before starting the activity. Also, this will be helpful for Pakistan's industry of construction to uplift the status of this sector, which will finally result in the country's prosperity.

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