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In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 364 kr
Skickas inom 5-8 vardagar
1 463 kr
Läs direkt efter köp
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 324 kr
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This volume contains an Open Access chapter.
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include recent trends in the digitalization of job postings, the use of online vacancy and job applicants’ data to study skill dynamics, the insights gained from linked vacancy data regarding skill demand and wages, the tracking of gender norms over time, the utilization of domain-specific word embeddings to examine the demand for skills, the latest evidence on employee agreements in the franchise sector, and the impact of vertical restraints on labor markets in franchised industries. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 236 kr
Skickas inom 5-8 vardagar
1 324 kr
Läs direkt efter köp
This volume contains an Open Access chapter.
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include recent trends in the digitalization of job postings, the use of online vacancy and job applicants’ data to study skill dynamics, the insights gained from linked vacancy data regarding skill demand and wages, the tracking of gender norms over time, the utilization of domain-specific word embeddings to examine the demand for skills, the latest evidence on employee agreements in the franchise sector, and the impact of vertical restraints on labor markets in franchised industries. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 579 kr
Läs direkt efter köp
1 435 kr
Läs direkt efter köp
1 786 kr
Skickas inom 5-8 vardagar
1 617 kr
Läs direkt efter köp
1 507 kr
Skickas inom 5-8 vardagar
1 617 kr
Läs direkt efter köp
1 463 kr
Läs direkt efter köp
1 364 kr
Skickas inom 5-8 vardagar
1 463 kr
Läs direkt efter köp
1 463 kr
Läs direkt efter köp
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 364 kr
Skickas inom 5-8 vardagar
1 463 kr
Läs direkt efter köp
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include labor force transition dynamics, the labor demand side of involuntary part-time employment, the insights gained from wages in online job postings regarding wage growth, the role of online vacancies in labor market performance, the demand for personality traits, and an analysis of job descriptions from university job boards. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 324 kr
Läs direkt efter köp
This volume contains an Open Access chapter.
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include recent trends in the digitalization of job postings, the use of online vacancy and job applicants’ data to study skill dynamics, the insights gained from linked vacancy data regarding skill demand and wages, the tracking of gender norms over time, the utilization of domain-specific word embeddings to examine the demand for skills, the latest evidence on employee agreements in the franchise sector, and the impact of vertical restraints on labor markets in franchised industries. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.
1 236 kr
Skickas inom 5-8 vardagar
1 324 kr
Läs direkt efter köp
This volume contains an Open Access chapter.
In the digital age, Big Data offers an unparalleled lens into the intricacies of human behavior. Data sourced from job boards, social media platforms, or news websites allows researchers to answer questions that could not be answered with conventional data sources. Labor markets are no exception here: every day, millions of workers and firms interact, and big data allows us to better understand the complex dynamics arising from worker-firm interactions.
This volume showcases new, original research using Big Data to gain fresh insights into how labor markets work. The volume is compiled by Solomon Polachek, a pioneer in gender-related labor market research, and Benjamin Elsner, an expert on causal inference and the economics of migration. Topics include recent trends in the digitalization of job postings, the use of online vacancy and job applicants’ data to study skill dynamics, the insights gained from linked vacancy data regarding skill demand and wages, the tracking of gender norms over time, the utilization of domain-specific word embeddings to examine the demand for skills, the latest evidence on employee agreements in the franchise sector, and the impact of vertical restraints on labor markets in franchised industries. All chapters use a combination of innovative data sources and machine learning methods to enhance our understanding of how labor markets work.