Detalhes bibliográficos
| Ano de defesa: |
2023 |
| Autor(a) principal: |
SANTOS, Erivelton Antonio dos
 |
| Orientador(a): |
SILVA, Carlos Eduardo Sanches da
|
| Banca de defesa: |
Não Informado pela instituição |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
eng |
| Instituição de defesa: |
Universidade Federal de Itajubá
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação: Doutorado - Engenharia de Produção
|
| Departamento: |
IEPG - Instituto de Engenharia de Produção e Gestão
|
| País: |
Brasil
|
| Palavras-chave em Português: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
https://repositorio.unifei.edu.br/jspui/handle/123456789/3514
|
Resumo: |
Supply chains are susceptible to uncertainties, such as large-scale natural disasters, manufacturing fires, terrorist attacks, widespread electrical shutdowns, financial and political tension, and wars. Therefore, rising unemployment rates have driven the workforce into short-term contracts or the on-demand market known as the gig economy. However, selecting skilled professionals is difficult and risky when organizations are immersed in fast-paced environments. In this context, we investigated the analysis scenario of contracting professionals in global software developments (GSD). This thesis aims to develop clusters of criteria for hiring self-employed professionals in the “Global Software Development” or “Gig Economy” context. We systematically reviewed 319 criteria in 65 papers and grouped them into two innovative ways. Thus, we obtained 25 criteria clusters and a hierarchical structure with their relationships, indicating that we had only 40% of the cause. We are proposing two innovative criteria grouping methods. The first delivers a fast aggregation clustering, and the second with the relationships between the criteria clusters. This tool can be handy for researchers in exploring new data via literature review or even through surveys. Another point is that the practitioners could easily use the spreadsheet with all the data, remove or join new criteria, and run the algorithm to create new clusters on their own. The main results were, firstly, for the applicants, in software development, the project requirements are gathered over the clients and stakeholders; this process involves rich and looping communication. Secondly, the enterprises first check the criteria clusters. Then, the list of criteria, and taking into account the job position or profile, they choose how to make the hiring process, reflecting on the relationship of criteria clusters (cause/effects). Finally, these results also imply the design of new subjects for computer science courses, mainly concerning soft skills, as highlighted in the Communication criteria cluster, in which we have a list of criteria highly cited in SLR. |
