Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020

Detalhes bibliográficos
Autor(a) principal: Laureano, R. M. S.
Data de Publicação: 2021
Outros Autores: Trindade, G., Laureano, L. M. S.
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/23666
Resumo: Since Portugal joined the European Union (EU) that it has been receiving incentives/funds to reduce disparities with other EU countries. Despite this goal, disparities between European regions still exist and the impact of such funds is questionable. What if it is possible to predict the success of such incentives when the funds are awarded to the beneficiaries? Using data from the database of The Agency for Competitiveness and Innovation (IAPMEI), for the programs National Strategic Reference Framework (QREN), and Portugal 2020, two predictive models are developed to estimate the number of applications to be received and the schedule of expected payments to beneficiaries for a four-month period. The results allow for a better prediction, on one hand, of the resources to be allocated to the evaluation process of the applications, and on the other hand, of the financial execution plan for the upcoming period, in order to prepare the financial execution.
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spelling Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020Financial incentivesForecastSince Portugal joined the European Union (EU) that it has been receiving incentives/funds to reduce disparities with other EU countries. Despite this goal, disparities between European regions still exist and the impact of such funds is questionable. What if it is possible to predict the success of such incentives when the funds are awarded to the beneficiaries? Using data from the database of The Agency for Competitiveness and Innovation (IAPMEI), for the programs National Strategic Reference Framework (QREN), and Portugal 2020, two predictive models are developed to estimate the number of applications to be received and the schedule of expected payments to beneficiaries for a four-month period. The results allow for a better prediction, on one hand, of the resources to be allocated to the evaluation process of the applications, and on the other hand, of the financial execution plan for the upcoming period, in order to prepare the financial execution.IEEE2021-12-09T11:47:27Z2021-01-01T00:00:00Z20212021-12-09T11:45:47Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10071/23666eng978-989-54659-1-02166-072710.23919/CISTI52073.2021.9476655Laureano, R. M. S.Trindade, G.Laureano, L. M. S.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-07-07T02:46:26Zoai:repositorio.iscte-iul.pt:10071/23666Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T02:46:26Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
title Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
spellingShingle Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
Laureano, R. M. S.
Financial incentives
Forecast
title_short Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
title_full Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
title_fullStr Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
title_full_unstemmed Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
title_sort Predictive models for managing financial incentives oriented to companies: Application to Portugal 2020
author Laureano, R. M. S.
author_facet Laureano, R. M. S.
Trindade, G.
Laureano, L. M. S.
author_role author
author2 Trindade, G.
Laureano, L. M. S.
author2_role author
author
dc.contributor.author.fl_str_mv Laureano, R. M. S.
Trindade, G.
Laureano, L. M. S.
dc.subject.por.fl_str_mv Financial incentives
Forecast
topic Financial incentives
Forecast
description Since Portugal joined the European Union (EU) that it has been receiving incentives/funds to reduce disparities with other EU countries. Despite this goal, disparities between European regions still exist and the impact of such funds is questionable. What if it is possible to predict the success of such incentives when the funds are awarded to the beneficiaries? Using data from the database of The Agency for Competitiveness and Innovation (IAPMEI), for the programs National Strategic Reference Framework (QREN), and Portugal 2020, two predictive models are developed to estimate the number of applications to be received and the schedule of expected payments to beneficiaries for a four-month period. The results allow for a better prediction, on one hand, of the resources to be allocated to the evaluation process of the applications, and on the other hand, of the financial execution plan for the upcoming period, in order to prepare the financial execution.
publishDate 2021
dc.date.none.fl_str_mv 2021-12-09T11:47:27Z
2021-01-01T00:00:00Z
2021
2021-12-09T11:45:47Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/23666
url http://hdl.handle.net/10071/23666
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-989-54659-1-0
2166-0727
10.23919/CISTI52073.2021.9476655
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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