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Abstract(s)
A literatura é unânime no evidenciar a atração de talentos como um dos principais
desafios das organizações no contexto do atual mercado de trabalho. Nesse sentido, os
profissionais de recrutamento, possuem o desafiante papel de encontrar o candidato “perfeito”.
É neste âmbito, que esta dissertação pretende contribuir para esta problemática, explorando o
papel transformador que o Machine Learning desempenha na revolução do processo de
recrutamento.
Metodologicamente realizou-se uma revisão sistemática da literatura e uma análise de
conteúdo online. O objetivo foi sistematizar, para a comunidade de Recursos Humanos, o
conhecimento científico já produzido sobre a utilização do Machine Learning no recrutamento,
articulando-o com a oferta técnica efetivamente disponível para o recrutador já acessível na
world wide web. A revisão sistemática da literatura foi realizada através de combinações de
termos booleanos em artigos publicados entre o ano 2017 e 2022 tendo sido recolhidos 644
artigos e 106 válidos apos a aplicação dos critérios de exclusão. Na análise de conteúdo online
foram identificadas as 10 primeiras empresas de recrutamento que utilizam Machine Learning
no motor de busca da Google. Posteriormente, as informações recolhidas foram compiladas e
consequentemente criadas categorias e macro categorias que proporcionaram uma melhor
compreensão dos dados obtidos.
Analisaram-se as vantagens, desvantagens e as fases de utilização do Machine Learning
no processo de recrutamento. Foi possível concluir que a adoção de Machine Learning no
processo de recrutamento representa um avanço significativo para as empresas, oferecendo uma
abordagem mais inteligente, baseada em dados. Com a devida utilização, é possível alcançar
resultados mais eficientes, identificar os candidatos mais qualificados para determinadas vagas
e impulsionar o sucesso das contratações. Por fim, importa ainda referir que esta abordagem
tecnológica é escassamente explorada na literatura de Recursos Humanos, tendo o material de
investigação disponível sido recolhido essencialmente na literatura das áreas das tecnologias de
informação e engenharia informática.
The literature is unanimous in highlighting the attraction of talent as one of the main challenges for organisations in the context of the current labour market. In this sense, recruitment professionals have the challenging role of finding the "perfect" candidate. It is in this context that this dissertation aims to contribute to this problem, exploring the transformative role that Machine Learning plays in revolutionising the recruitment process. Methodologically, a systematic literature review and an online content analysis were carried out. The objective was to systematize, for the Human Resources community, the scientific knowledge already produced on the use of Machine Learning in recruitment, articulating it with the technical offer effectively available to the recruiter already accessible on the world wide web. The systematic literature review was carried out through combinations of Boolean terms in articles published between the year 2017 and 2022 having been collected 644 articles and 106 valid after applying the exclusion criteria. In the online content analysis the top 10 recruitment companies using Machine Learning were identified in the Google search engine. Subsequently, the information collected was compiled and consequently categories and macro categories were created that provided a better understanding of the data obtained. The advantages, disadvantages and the phases of using Machine Learning in the recruitment process were analysed. It was possible to conclude that the adoption of Machine Learning in the recruitment process represents a significant advance for companies, offering a more intelligent approach, based on data. With proper use, it is possible to achieve more efficient results, identify the most qualified candidates for certain vacancies and boost the success of hiring. Finally, it is also important to mention that this technological approach is scarcely explored in the Human Resources literature, with the available research material having been collected mainly in the literature from the areas of information technology and computer engineering.
The literature is unanimous in highlighting the attraction of talent as one of the main challenges for organisations in the context of the current labour market. In this sense, recruitment professionals have the challenging role of finding the "perfect" candidate. It is in this context that this dissertation aims to contribute to this problem, exploring the transformative role that Machine Learning plays in revolutionising the recruitment process. Methodologically, a systematic literature review and an online content analysis were carried out. The objective was to systematize, for the Human Resources community, the scientific knowledge already produced on the use of Machine Learning in recruitment, articulating it with the technical offer effectively available to the recruiter already accessible on the world wide web. The systematic literature review was carried out through combinations of Boolean terms in articles published between the year 2017 and 2022 having been collected 644 articles and 106 valid after applying the exclusion criteria. In the online content analysis the top 10 recruitment companies using Machine Learning were identified in the Google search engine. Subsequently, the information collected was compiled and consequently categories and macro categories were created that provided a better understanding of the data obtained. The advantages, disadvantages and the phases of using Machine Learning in the recruitment process were analysed. It was possible to conclude that the adoption of Machine Learning in the recruitment process represents a significant advance for companies, offering a more intelligent approach, based on data. With proper use, it is possible to achieve more efficient results, identify the most qualified candidates for certain vacancies and boost the success of hiring. Finally, it is also important to mention that this technological approach is scarcely explored in the Human Resources literature, with the available research material having been collected mainly in the literature from the areas of information technology and computer engineering.
Description
Keywords
Gestão de recursos humanos Recrutamento Machine learning Inteligência artificial Human resources management Recruitment Artificial intelligence