Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector

Descripción del Articulo

The research work is based on the analysis of demand in a tourism company using mathematical models. The methodology design presents a correlational and descriptive scope where the company's sales are collected to calculate the mean absolute percentage error in demand. With the help of machine...

Descripción completa

Detalles Bibliográficos
Autores: Ludeña Roman, Sayuri Arleth Renatta, Zelada Collazos, Sebastian, Corzo Chávez, Jorge Antonio
Formato: objeto de conferencia
Fecha de Publicación:2024
Institución:Universidad de Lima
Repositorio:ULIMA-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.ulima.edu.pe:20.500.12724/21853
Enlace del recurso:https://hdl.handle.net/20.500.12724/21853
https://doi.org/10.11159/icmie24.110
Nivel de acceso:acceso abierto
Materia:Pendiente
id RULI_f4396f9f04a4ce3cce7903718a834a93
oai_identifier_str oai:repositorio.ulima.edu.pe:20.500.12724/21853
network_acronym_str RULI
network_name_str ULIMA-Institucional
repository_id_str 3883
spelling Ludeña Roman, Sayuri Arleth RenattaZelada Collazos, SebastianCorzo Chávez, Jorge AntonioCorzo Chávez, Jorge AntonioLudeña Roman, Sayuri Arleth Renatta (Ingeniería Industrial)Zelada Collazos, Sebastián (Ingeniería Industrial)2025-01-14T16:02:43Z2025-01-14T16:02:43Z2024Ludeña-Roman, S. A. R., Zelada-Collazos, S., & Corzo-Chavez, J. A. (2024). Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector. Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering. https://doi.org/10.11159/icmie24.1102369-8136https://hdl.handle.net/20.500.12724/21853121541816Proceedings of the World Congress on Mechanical, Chemical, and Material Engineeringhttps://doi.org/10.11159/icmie24.1102-s2.0-85205133591The research work is based on the analysis of demand in a tourism company using mathematical models. The methodology design presents a correlational and descriptive scope where the company's sales are collected to calculate the mean absolute percentage error in demand. With the help of machine learning tools, a predictive analysis will be carried out to estimate the sales for the following year, seeking to reduce the error using one of the selected mathematical models, calculate the necessary sales force, and thereby reduce the economic impact equivalent to $16 789,02. The MAPE (Mean Absolute Percentage Error) in the tourism sector is 12,03%. Through calculations using Python and RISK, a value of 15, 36% was obtained, reducing the MAPE by 4,24% compared to the year 2022. The Systematic Review of the Literature allows us to showcase the tools that can be developed in similar or atypical scenarios. The choice will depend on the behaviour pattern or trend. © 2024, Avestia Publishing. All rights reserved.application/htmlengAvestia PublishingCAinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/Repositorio Institucional - UlimaUniversidad de Limareponame:ULIMA-Institucionalinstname:Universidad de Limainstacron:ULIMAPendientePendienteDemand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sectorinfo:eu-repo/semantics/conferenceObjectArtícuo de conferencia en ScopusCorzo Chávez, Jorge Antonio (Ingeniería Industrial)Corzo Chávez, Jorge Antonio (Facultad de Ingeniería, Universidad de Lima)PendientePendiente20.500.12724/21853oai:repositorio.ulima.edu.pe:20.500.12724/218532025-03-05 12:42:45.43Repositorio Universidad de Limarepositorio@ulima.edu.pe
dc.title.none.fl_str_mv Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
title Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
spellingShingle Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
Ludeña Roman, Sayuri Arleth Renatta
Pendiente
Pendiente
title_short Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
title_full Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
title_fullStr Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
title_full_unstemmed Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
title_sort Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
author Ludeña Roman, Sayuri Arleth Renatta
author_facet Ludeña Roman, Sayuri Arleth Renatta
Zelada Collazos, Sebastian
Corzo Chávez, Jorge Antonio
author_role author
author2 Zelada Collazos, Sebastian
Corzo Chávez, Jorge Antonio
author2_role author
author
dc.contributor.other.none.fl_str_mv Corzo Chávez, Jorge Antonio
dc.contributor.student.none.fl_str_mv Ludeña Roman, Sayuri Arleth Renatta (Ingeniería Industrial)
Zelada Collazos, Sebastián (Ingeniería Industrial)
dc.contributor.author.fl_str_mv Ludeña Roman, Sayuri Arleth Renatta
Zelada Collazos, Sebastian
Corzo Chávez, Jorge Antonio
dc.subject.none.fl_str_mv Pendiente
topic Pendiente
Pendiente
dc.subject.ocde.none.fl_str_mv Pendiente
description The research work is based on the analysis of demand in a tourism company using mathematical models. The methodology design presents a correlational and descriptive scope where the company's sales are collected to calculate the mean absolute percentage error in demand. With the help of machine learning tools, a predictive analysis will be carried out to estimate the sales for the following year, seeking to reduce the error using one of the selected mathematical models, calculate the necessary sales force, and thereby reduce the economic impact equivalent to $16 789,02. The MAPE (Mean Absolute Percentage Error) in the tourism sector is 12,03%. Through calculations using Python and RISK, a value of 15, 36% was obtained, reducing the MAPE by 4,24% compared to the year 2022. The Systematic Review of the Literature allows us to showcase the tools that can be developed in similar or atypical scenarios. The choice will depend on the behaviour pattern or trend. © 2024, Avestia Publishing. All rights reserved.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2025-01-14T16:02:43Z
dc.date.available.none.fl_str_mv 2025-01-14T16:02:43Z
dc.date.issued.fl_str_mv 2024
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.type.other.none.fl_str_mv Artícuo de conferencia en Scopus
format conferenceObject
dc.identifier.citation.none.fl_str_mv Ludeña-Roman, S. A. R., Zelada-Collazos, S., & Corzo-Chavez, J. A. (2024). Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector. Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering. https://doi.org/10.11159/icmie24.110
dc.identifier.issn.none.fl_str_mv 2369-8136
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12724/21853
dc.identifier.isni.none.fl_str_mv 121541816
dc.identifier.event.none.fl_str_mv Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering
dc.identifier.doi.none.fl_str_mv https://doi.org/10.11159/icmie24.110
dc.identifier.scopusid.none.fl_str_mv 2-s2.0-85205133591
identifier_str_mv Ludeña-Roman, S. A. R., Zelada-Collazos, S., & Corzo-Chavez, J. A. (2024). Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector. Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering. https://doi.org/10.11159/icmie24.110
2369-8136
121541816
Proceedings of the World Congress on Mechanical, Chemical, and Material Engineering
2-s2.0-85205133591
url https://hdl.handle.net/20.500.12724/21853
https://doi.org/10.11159/icmie24.110
dc.language.iso.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.uri.none.fl_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/4.0/
dc.format.none.fl_str_mv application/html
dc.publisher.none.fl_str_mv Avestia Publishing
dc.publisher.country.none.fl_str_mv CA
publisher.none.fl_str_mv Avestia Publishing
dc.source.none.fl_str_mv Repositorio Institucional - Ulima
Universidad de Lima
reponame:ULIMA-Institucional
instname:Universidad de Lima
instacron:ULIMA
instname_str Universidad de Lima
instacron_str ULIMA
institution ULIMA
reponame_str ULIMA-Institucional
collection ULIMA-Institucional
repository.name.fl_str_mv Repositorio Universidad de Lima
repository.mail.fl_str_mv repositorio@ulima.edu.pe
_version_ 1840270840926568448
score 13.11166
Demand Forecasting Model To Reduce The Mean Absolute Percentage Error By Applying Seasonal Breakdown Tools In A Sme In The Tourism Sector
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).

Ejemplares Similares