Isbn: 9781836087137 - big data applications in labor economics (21 risultati)

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  • Lingua: Inglese

    Editore: Emerald Publishing Limited, 2024

    1836087136 / 9781836087137

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  • Lingua: Inglese

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: Emerald Publishing Limited, 2024

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  • Lingua: Inglese

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: Emerald Publishing Limited, 2024

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  • Lingua: Inglese

    Editore: Emerald Publishing Limited, GB, 2024

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    Hardback. Condizione: New. 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.

  • Lingua: Inglese

    Editore: Emerald Publishing Limited, GB, 2024

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    Hardback. Condizione: New. 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.

  • Lingua: Inglese

    Editore: Emerald Publishing Limited, 2024

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  • Lingua: Inglese

    Editore: Emerald Publishing Limited, 2024

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  • Lingua: Inglese

    Editore: Emerald Group Pub Ltd, 2024

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    Hardcover. Condizione: Brand New. 436 pages. 9.01x5.98x9.02 inches. In Stock.

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  • Lingua: Inglese

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    Hardback. Condizione: New. 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.

  • Lingua: Inglese

    Editore: Emerald Publishing Limited Dez 2024, 2024

    1836087136 / 9781836087137

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    Buch. Condizione: Neu. Neuware - 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.

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    Lingua: Inglese

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    Buch. Condizione: Neu. Big Data Applications in Labor Economics | Benjamin Elsner (u. a.) | Buch | Research in Labor Economics | Einband - fest (Hardcover) | Englisch | 2024 | Emerald Publishing Limited | EAN 9781836087137 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Emerald Group Pub Ltd, 2024

    1836087136 / 9781836087137

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    Hardcover. Condizione: Brand New. 436 pages. 9.01x5.98x9.02 inches. In Stock.

  • Lingua: Inglese

    Editore: Emerald Publishing Limited, GB, 2024

    1836087136 / 9781836087137

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    Hardback. Condizione: New. 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.