Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/18938 |
Resumo: | Plenty of literature on megatrends escapes the logic of validation. Most publications on forecasting apply quantitative methods and the use of qualitative forecasting is scarce especially in the Hospitality and Tourism (H&T) industry, which is so sensitive to macro level factors. Alongside this, it is surprising that studies that explore the accuracy of such predictions are scarce which hampers the capacity to improve forecasting techniques. With this in consideration, the main goal of this study was to uncover the potential predictors of accuracy in qualitative forecasting sources in H&T. In order to do so, we identified and selected a set of documents that used qualitative forecasting methods to predict trends in H&T for the 1998-2008 period, and devised an empirical study that puts to test the expected trends against the test of time. With a panel of 14 experts in H&T that indicated what occurred in the aforementioned period, we computed a weighted score of accuracy for each document and classified it according to four potential causal variables (Explicit methods, Number of cites, Multisource, and Multimethod, thought of as indicators of forecasting quality). The model was tested with a fuzzy set qualitative comparative analysis (fs/QCA) which indicated that clarifying the qualitative forecasting methods (Explicit) and having multiple sources (Multisource) are the main predictors of the qualitative forecasting sources’ accuracy in H&T. |
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Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industryQualitative forecastingMegatrendsPredictorsHospitality and tourismfs/QCAPrevisão qualitativaMegatendênciasPreditoresHotelaria e turismoFonte de informaçãoTécnicas de previsãoModelos de precisãoPlenty of literature on megatrends escapes the logic of validation. Most publications on forecasting apply quantitative methods and the use of qualitative forecasting is scarce especially in the Hospitality and Tourism (H&T) industry, which is so sensitive to macro level factors. Alongside this, it is surprising that studies that explore the accuracy of such predictions are scarce which hampers the capacity to improve forecasting techniques. With this in consideration, the main goal of this study was to uncover the potential predictors of accuracy in qualitative forecasting sources in H&T. In order to do so, we identified and selected a set of documents that used qualitative forecasting methods to predict trends in H&T for the 1998-2008 period, and devised an empirical study that puts to test the expected trends against the test of time. With a panel of 14 experts in H&T that indicated what occurred in the aforementioned period, we computed a weighted score of accuracy for each document and classified it according to four potential causal variables (Explicit methods, Number of cites, Multisource, and Multimethod, thought of as indicators of forecasting quality). The model was tested with a fuzzy set qualitative comparative analysis (fs/QCA) which indicated that clarifying the qualitative forecasting methods (Explicit) and having multiple sources (Multisource) are the main predictors of the qualitative forecasting sources’ accuracy in H&T.A maioria das publicações sobre previsão usam métodos quantitativos e a previsão de base qualitativa é escassa especialmente no sector da Hospitalidade e Turismo (H&T) que é tão sensível a fatores de nível macro. Em acréscimo, é surpreendente que os estudos que exploram a precisão de tais previsões sejam escassos, o que reduz a capacidade de melhorar as técnicas de previsão. Considerando isto, o principal objetivo deste estudo foi o de descobrir os potenciais preditores de precisão nas fontes de previsão qualitativa em H&T. Para o concretizar, identificámos e selecionámos um conjunto de documentos que usam métodos qualitativos de previsão para as tendências de H&T para o período de 1998-2008 e desenvolvemos um estudo empírico que põe à prova as tendências esperadas em relação ao teste do tempo. Com um painel de 14 peritos em H&T que indicaram o ocorrido no período mencionado calculámos um score ponderado de precisão para cada documento e classificámo-lo de acordo com quatro potenciais variáveis causais (métodos explícitos, número de citações, multi-fonte e multi-método, tidos como indicadores da qualidade da previsão). O modelo foi testado por via da análise comparada qualitativa de conjunto difuso (fs/QCA) que indicou que clarificar os métodos de previsão usados (explícito) e contar com várias fontes de informação (multi-fonte) são os principais preditores da precisão dos documentos que oferecem previsões qualitativas em H&T.2022-10-13T00:00:00Z2019-10-14T00:00:00Z2019-10-142019-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/18938TID:202294595engCercas, Francisco José Brancoinfo: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:RCAAP2024-07-07T02:50:44Zoai:repositorio.iscte-iul.pt:10071/18938Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T02:50:44Repositório 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 |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
title |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
spellingShingle |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry Cercas, Francisco José Branco Qualitative forecasting Megatrends Predictors Hospitality and tourism fs/QCA Previsão qualitativa Megatendências Preditores Hotelaria e turismo Fonte de informação Técnicas de previsão Modelos de precisão |
title_short |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
title_full |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
title_fullStr |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
title_full_unstemmed |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
title_sort |
Assessing accuracy predictors in megatrend qualitative forecasting in the hospitality and tourism industry |
author |
Cercas, Francisco José Branco |
author_facet |
Cercas, Francisco José Branco |
author_role |
author |
dc.contributor.author.fl_str_mv |
Cercas, Francisco José Branco |
dc.subject.por.fl_str_mv |
Qualitative forecasting Megatrends Predictors Hospitality and tourism fs/QCA Previsão qualitativa Megatendências Preditores Hotelaria e turismo Fonte de informação Técnicas de previsão Modelos de precisão |
topic |
Qualitative forecasting Megatrends Predictors Hospitality and tourism fs/QCA Previsão qualitativa Megatendências Preditores Hotelaria e turismo Fonte de informação Técnicas de previsão Modelos de precisão |
description |
Plenty of literature on megatrends escapes the logic of validation. Most publications on forecasting apply quantitative methods and the use of qualitative forecasting is scarce especially in the Hospitality and Tourism (H&T) industry, which is so sensitive to macro level factors. Alongside this, it is surprising that studies that explore the accuracy of such predictions are scarce which hampers the capacity to improve forecasting techniques. With this in consideration, the main goal of this study was to uncover the potential predictors of accuracy in qualitative forecasting sources in H&T. In order to do so, we identified and selected a set of documents that used qualitative forecasting methods to predict trends in H&T for the 1998-2008 period, and devised an empirical study that puts to test the expected trends against the test of time. With a panel of 14 experts in H&T that indicated what occurred in the aforementioned period, we computed a weighted score of accuracy for each document and classified it according to four potential causal variables (Explicit methods, Number of cites, Multisource, and Multimethod, thought of as indicators of forecasting quality). The model was tested with a fuzzy set qualitative comparative analysis (fs/QCA) which indicated that clarifying the qualitative forecasting methods (Explicit) and having multiple sources (Multisource) are the main predictors of the qualitative forecasting sources’ accuracy in H&T. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-14T00:00:00Z 2019-10-14 2019-09 2022-10-13T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/18938 TID:202294595 |
url |
http://hdl.handle.net/10071/18938 |
identifier_str_mv |
TID:202294595 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/octet-stream |
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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1817546337043873792 |