Ticket consumption forecast for Brazilian championship games
Main Author: | |
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Publication Date: | 2017 |
Other Authors: | , , , , |
Format: | Article |
Language: | eng |
Source: | Revista de Administração (São Paulo) |
Download full: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0080-21072017000100070 |
Summary: | Abstract For the efficiency of sales and marketing management of athletic clubs, it is crucial to find a way to appropriately estimate the level of demand for sporting events. More precise estimates allow for an appropriate financial and operational plan and a higher quality of service delivered to the fans. The focus of this study is to analyze and forecast the ticket consumption for soccer games in Brazilian stadiums. We compare the results of the regression model with normally distributed errors (benchmark), the TOBIT model and the Gamma generalized linear model. The models include explanatory variables related to the economic environment, product quality, as well as monetary and non-monetary incentives that people are given to attend sporting events at stadiums. We show that most of these variables are statistically significant to explain the amount of fans that go to stadiums. We used different measures of accuracy to evaluate the performance of demand forecasts and concluded that Gamma generalized linear model presented better results to forecast the ticket consumption for Brazilian championship games, when compared to a benchmark. |
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Ticket consumption forecast for Brazilian championship gamesSports managementGLMTicket consumptionSoccerAbstract For the efficiency of sales and marketing management of athletic clubs, it is crucial to find a way to appropriately estimate the level of demand for sporting events. More precise estimates allow for an appropriate financial and operational plan and a higher quality of service delivered to the fans. The focus of this study is to analyze and forecast the ticket consumption for soccer games in Brazilian stadiums. We compare the results of the regression model with normally distributed errors (benchmark), the TOBIT model and the Gamma generalized linear model. The models include explanatory variables related to the economic environment, product quality, as well as monetary and non-monetary incentives that people are given to attend sporting events at stadiums. We show that most of these variables are statistically significant to explain the amount of fans that go to stadiums. We used different measures of accuracy to evaluate the performance of demand forecasts and concluded that Gamma generalized linear model presented better results to forecast the ticket consumption for Brazilian championship games, when compared to a benchmark.Departamento de Administração da Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo2017-03-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0080-21072017000100070Revista de Administração (São Paulo) v.52 n.1 2017reponame:Revista de Administração (São Paulo)instname:Universidade de São Paulo (USP)instacron:USP10.1016/j.rausp.2016.09.007info:eu-repo/semantics/openAccessBortoluzzo,Adriana BruscatoBortoluzzo,Mauricio MesquitaMachado,Sérgio JurandyrMelhado,Tatiana TerabayashiTrindade,Pedro IaropoliPereira,Bruno Santoseng2017-02-20T00:00:00Zoai:scielo:S0080-21072017000100070Revistahttp://rausp.usp.br/PUBhttps://old.scielo.br/oai/scielo-oai.phprausp@usp.br||reinhard@usp.br1984-61420080-2107opendoar:2017-02-20T00:00Revista de Administração (São Paulo) - Universidade de São Paulo (USP)false |
dc.title.none.fl_str_mv |
Ticket consumption forecast for Brazilian championship games |
title |
Ticket consumption forecast for Brazilian championship games |
spellingShingle |
Ticket consumption forecast for Brazilian championship games Bortoluzzo,Adriana Bruscato Sports management GLM Ticket consumption Soccer |
title_short |
Ticket consumption forecast for Brazilian championship games |
title_full |
Ticket consumption forecast for Brazilian championship games |
title_fullStr |
Ticket consumption forecast for Brazilian championship games |
title_full_unstemmed |
Ticket consumption forecast for Brazilian championship games |
title_sort |
Ticket consumption forecast for Brazilian championship games |
author |
Bortoluzzo,Adriana Bruscato |
author_facet |
Bortoluzzo,Adriana Bruscato Bortoluzzo,Mauricio Mesquita Machado,Sérgio Jurandyr Melhado,Tatiana Terabayashi Trindade,Pedro Iaropoli Pereira,Bruno Santos |
author_role |
author |
author2 |
Bortoluzzo,Mauricio Mesquita Machado,Sérgio Jurandyr Melhado,Tatiana Terabayashi Trindade,Pedro Iaropoli Pereira,Bruno Santos |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Bortoluzzo,Adriana Bruscato Bortoluzzo,Mauricio Mesquita Machado,Sérgio Jurandyr Melhado,Tatiana Terabayashi Trindade,Pedro Iaropoli Pereira,Bruno Santos |
dc.subject.por.fl_str_mv |
Sports management GLM Ticket consumption Soccer |
topic |
Sports management GLM Ticket consumption Soccer |
description |
Abstract For the efficiency of sales and marketing management of athletic clubs, it is crucial to find a way to appropriately estimate the level of demand for sporting events. More precise estimates allow for an appropriate financial and operational plan and a higher quality of service delivered to the fans. The focus of this study is to analyze and forecast the ticket consumption for soccer games in Brazilian stadiums. We compare the results of the regression model with normally distributed errors (benchmark), the TOBIT model and the Gamma generalized linear model. The models include explanatory variables related to the economic environment, product quality, as well as monetary and non-monetary incentives that people are given to attend sporting events at stadiums. We show that most of these variables are statistically significant to explain the amount of fans that go to stadiums. We used different measures of accuracy to evaluate the performance of demand forecasts and concluded that Gamma generalized linear model presented better results to forecast the ticket consumption for Brazilian championship games, when compared to a benchmark. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-03-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0080-21072017000100070 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0080-21072017000100070 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1016/j.rausp.2016.09.007 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Administração da Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo |
publisher.none.fl_str_mv |
Departamento de Administração da Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo |
dc.source.none.fl_str_mv |
Revista de Administração (São Paulo) v.52 n.1 2017 reponame:Revista de Administração (São Paulo) instname:Universidade de São Paulo (USP) instacron:USP |
instname_str |
Universidade de São Paulo (USP) |
instacron_str |
USP |
institution |
USP |
reponame_str |
Revista de Administração (São Paulo) |
collection |
Revista de Administração (São Paulo) |
repository.name.fl_str_mv |
Revista de Administração (São Paulo) - Universidade de São Paulo (USP) |
repository.mail.fl_str_mv |
rausp@usp.br||reinhard@usp.br |
_version_ |
1748936717248757760 |