Use of LinkedIn Data and Machine Learning to Analyze Gender Differences in Construction Career Paths

Hickey, Paul J.; Erfani, Abdolmajid; Cui, Qingbin

doi:10.1061/(asce)me.1943-5479.0001087

Cited by 25 publications

(7 citation statements)

References 54 publications

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“…To combat the COVID-19 pandemic, governments and private companies around the world were promoting the use of digital public health technologies for data collection and processing [54][55][56][57][58]. Through the use of GPS, cellular networks and Wi-Fi, smartphones can collect and aggregate location data in real-time to monitor population flows, identify transmission hotspots, determine the effectiveness of non-pharmacologic interventions [59], and predict future COVID-19 cases [7,20,25].…”

Section: Discussionmentioning

confidence: 99%

A fairness assessment of mobility-based COVID-19 case prediction models

Erfani,

Frias-Martinez

2023

PLoS ONE

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In light of the outbreak of COVID-19, analyzing and measuring human mobility has become increasingly important. A wide range of studies have explored spatiotemporal trends over time, examined associations with other variables, evaluated non-pharmacologic interventions (NPIs), and predicted or simulated COVID-19 spread using mobility data. Despite the benefits of publicly available mobility data, a key question remains unanswered: are models using mobility data performing equitably across demographic groups? We hypothesize that bias in the mobility data used to train the predictive models might lead to unfairly less accurate predictions for certain demographic groups. To test our hypothesis, we applied two mobility-based COVID infection prediction models at the county level in the United States using SafeGraph data, and correlated model performance with sociodemographic traits. Findings revealed that there is a systematic bias in models’ performance toward certain demographic characteristics. Specifically, the models tend to favor large, highly educated, wealthy, young, and urban counties. We hypothesize that the mobility data currently used by many predictive models tends to capture less information about older, poorer, less educated and people from rural regions, which in turn negatively impacts the accuracy of the COVID-19 prediction in these areas. Ultimately, this study points to the need of improved data collection and sampling approaches that allow for an accurate representation of the mobility patterns across demographic groups.

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Section: Discussionmentioning

confidence: 99%

A fairness assessment of mobility-based COVID-19 case prediction models

Erfani,

Frias-Martinez

2023

PLoS ONE

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“…While this measure might be beneficial for achieving a targeted share of women in the total workforce in the short term, its effectiveness in the long run may be limited. A recent study in the U.S. from Hickey, et al [56] found that women had higher turnover rates compared to men, while men were nearly four times more likely than women to become managers inside a single company throughout their careers. This is consistent with the findings, which highlighted that out of 25 women who took parental leave, only 8 remained employees of that company 12 months later.…”

Section: Theme 5: Shared Caring Responsibilitymentioning

confidence: 99%

Analysis of Gender Diversity Initiatives to Empower Women in the Australian Construction Industry

Yan,

Sunindijo,

Wang

2024

Buildings

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Organizations play an essential role in fostering a diverse and inclusive work environment. Despite attempts to encourage gender diversity in the workplace, the construction industry in Australia remains one of the most male-dominated industries. Existing research tends to focus on identifying barriers to gender equality and women’s career development, with limited exploration of organizations’ current initiative implementation. To fill this research gap, this study aims to examine how organizations implement initiatives affecting gender equality and women’s career development in the Australian construction industry. This study applied the women’s empowerment framework and conducted a thematic analysis of diversity, inclusion, and equality policies, strategies, action plans, corporate reports, annual reports, and websites within the context of gender equality and women’s career development in construction companies. Through a comprehensive analysis, the study identifies prevalent practices and initiatives related to gender equality initiatives in the construction industry, synthesizing them into six themes: flexible working arrangements, inclusive and anti-discriminatory culture, promoting career development, recruitment, and promotion, shared caring responsibility, and strategic commitments. The findings also revealed areas for improvement, giving recommendations on how to further empower women in the construction industry through enhanced gender diversity initiatives. This study sheds light on the current state of gender diversity and inclusion efforts within construction companies and provides practical recommendations for policymakers, industry stakeholders, and organizational leaders who seek to foster more inclusive and equitable work environments.

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“…The single-case study has also been the primary method of megaproject management research to date (Hu et al, 2015;Lehtinen et al, 2019). However, new methods like machine learning and different data collection such as the internet secondary data (e.g., LinkedIn) are recommended to extend and explore the career development of construction professionals (Hickey et al, 2022).…”

Section: Potential Direction For Applying New Techniques For Behavior...mentioning

confidence: 99%

Research evolution and thematic breakthroughs in project leadership: a bibliometric analysis

Zheng,

Gu,

et al. 2023

ECAM

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PurposeThe development of project managers and leadership has been highlighted as crucial for improving project success and performance, resulting in a rise of interest in project leadership research over the last two decades. While several qualitative reviews have been conducted, there have been limited quantitative and systematic reviews on project leadership. This study fills this gap by portraying the knowledge landscape and tracking the evolution of project leadership research from 1998 to 2022 through bibliometric approaches.Design/methodology/approachBased on 816 records, including 793 articles extracted and selected from the Web of Science database and specific journals, and 23 articles selected from three non-SCI/SSCI indexed journals, the authors used CiteSpace and bibliometrix R-package to depict visualizations of the trajectory of co-cited references, the landscape of co-occurred keywords and emerging trends in project leadership via reference co-citation analysis, keyword co-occurrence analysis and thematic mapping.Findings The bibliometric analyses enabled the authors to understand the conceptual aspects of project leadership and its theoretical background. Three stages of the intellectual bases were identified and tracked: the infancy phase (1998–2007), the growth phase (2008–2014) and the new development phase (2015–2022). The results of keyword co-occurrence analysis indicated that the research focus evolved from investigating traits and competences to examining the effects of traditional leadership behaviors, and then considering context-specific leadership. The findings of thematic mapping and theoretical interpretation illustrate the potential directions of the competence comparison, new and appropriate leadership, and the interaction between leadership and context.Originality/value This study advanced the field by providing a systematic review of project leadership, developing potential future directions for project leadership research and providing practical implications for career development and training.

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Use of LinkedIn Data and Machine Learning to Analyze Gender Differences in Construction Career Paths

Cited by 25 publications

References 54 publications

A fairness assessment of mobility-based COVID-19 case prediction models

A fairness assessment of mobility-based COVID-19 case prediction models

Analysis of Gender Diversity Initiatives to Empower Women in the Australian Construction Industry

Research evolution and thematic breakthroughs in project leadership: a bibliometric analysis

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