Modeling determinants of tourism demand in Colombia

Purpose – This paper estimates the determinants of international tourist arrivals to Colombia from 1995 to 2014. Design – Tourist demand is related to interlinking relationships between origins and destinations. The international movement of travelers has grown exponentially in recent decades, and t...

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Autores:
Vanegas López, Juan Gabriel
Valencia Cárdenas, Marisol
Restrepo Morales, Jorge Aníbal
Muñetón Santa, Guberney
Tipo de recurso:
Article of investigation
Fecha de publicación:
2020
Institución:
Tecnológico de Antioquia
Repositorio:
Repositorio Tdea
Idioma:
eng
OAI Identifier:
oai:dspace.tdea.edu.co:tdea/2814
Acceso en línea:
https://dspace.tdea.edu.co/handle/tdea/2814
Palabra clave:
Países en Desarrollo
Developing Countries
Países em Desenvolvimento
Tourism demand
Tourist flows
Generalized linear mixed model
Demanda turística
Flujos turísticos
Modelo mixto lineal generalizado
Rights
openAccess
License
https://creativecommons.org/licenses/by-nc-sa/4.0/
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oai_identifier_str oai:dspace.tdea.edu.co:tdea/2814
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repository_id_str
dc.title.none.fl_str_mv Modeling determinants of tourism demand in Colombia
title Modeling determinants of tourism demand in Colombia
spellingShingle Modeling determinants of tourism demand in Colombia
Países en Desarrollo
Developing Countries
Países em Desenvolvimento
Tourism demand
Tourist flows
Generalized linear mixed model
Demanda turística
Flujos turísticos
Modelo mixto lineal generalizado
title_short Modeling determinants of tourism demand in Colombia
title_full Modeling determinants of tourism demand in Colombia
title_fullStr Modeling determinants of tourism demand in Colombia
title_full_unstemmed Modeling determinants of tourism demand in Colombia
title_sort Modeling determinants of tourism demand in Colombia
dc.creator.fl_str_mv Vanegas López, Juan Gabriel
Valencia Cárdenas, Marisol
Restrepo Morales, Jorge Aníbal
Muñetón Santa, Guberney
dc.contributor.author.none.fl_str_mv Vanegas López, Juan Gabriel
Valencia Cárdenas, Marisol
Restrepo Morales, Jorge Aníbal
Muñetón Santa, Guberney
dc.subject.decs.none.fl_str_mv Países en Desarrollo
Developing Countries
Países em Desenvolvimento
topic Países en Desarrollo
Developing Countries
Países em Desenvolvimento
Tourism demand
Tourist flows
Generalized linear mixed model
Demanda turística
Flujos turísticos
Modelo mixto lineal generalizado
dc.subject.proposal.none.fl_str_mv Tourism demand
Tourist flows
Generalized linear mixed model
Demanda turística
Flujos turísticos
Modelo mixto lineal generalizado
description Purpose – This paper estimates the determinants of international tourist arrivals to Colombia from 1995 to 2014. Design – Tourist demand is related to interlinking relationships between origins and destinations. The international movement of travelers has grown exponentially in recent decades, and these dynamics have affected Colombia as well. Methodology/Approach – We propose a generalized linear mixed model, with a consideration of factors from the theory of consumer choice and those approached from the perspective of new economic geography. Findings – Apart from purchasing power and institutional factors as facilitators of travel, we found that general aspects of the country (such as language and geographical proximity) directly affect the flow of visitors, whereas exchange differences and physical distance reduce tourist attraction. Originality of the research – Estimation of tourist flows will serve as a diagnostic and planning tool for developing proposals of tourism attractiveness related to different environment. Keywords tourism demand, tourist flows, generalized linear mixed model, developing countries
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2023-04-22T22:12:05Z
dc.date.available.none.fl_str_mv 2023-04-22T22:12:05Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.eissn.spa.fl_str_mv 1847-3377
identifier_str_mv 1330-7533
1847-3377
url https://dspace.tdea.edu.co/handle/tdea/2814
dc.language.iso.spa.fl_str_mv eng
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dc.relation.citationendpage.spa.fl_str_mv 67
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dc.relation.citationstartpage.spa.fl_str_mv 49
dc.relation.citationvolume.spa.fl_str_mv 26
dc.relation.references.spa.fl_str_mv Akın, M. (2015), “A novel approach to model selection in tourism demand modeling”, Tourism Management, Vol. 48, pp. 64-72. https://doi.org/10.1016/j.tourman.2014.11.004
Athanasopoulos, G., Hyndman, R., Song, H. and Wu, D. (2011), “The tourism forecasting competition”, International Journal of Forecasting, Vol. 27 No. 3, pp. 822-844. https://doi.org/10.1016/j.ijforecast.2010.04.009
Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R., Singmann, H. and Grothendieck, G. (2015), “Fitting Linear Mixed-Effects Models Using lme4”, Journal of Statistical Software, Vol. 67, No. 1, pp. 1-48. https://doi.org/10.18637/jss.v067.i0
Bonilla, J. and Moreno, M. (2010), “Determinantes de la demanda de turismo en Colombia 2004-2007: seguridad, comercio y otros factores”, Bachelor’s thesis, Universidad del Rosario, Bogotá
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CEPII: Centre d‘Etudes Prospectives et d‘Informations Internationales (2015), “GeoDist database. Research and Expertise on the World Economy”, viewed 8 August 2016, http://www.cepii.fr/
Cerda, R. and Leguizamón, M. (2005), “Análisis del comportamiento de la demanda turística urbana de Colombia”, Anuario Turismo y Sociedad, Vol. 4, pp. 70-98
Chu, F. (2014), “Using a logistic growth regression model to forecast the demand for tourism in Las Vegas”, Tourism Management Perspectives, Vol. 12, pp. 62-67. https://doi.org/10.1016/j.tmp.2014.08.003
Chung, Y., Rabe-Hesketh, S., Dorie, V., Gelman, A. and Liu, J. (2013), “A Nondegenerative Penalized Likelihood Estimator for Variance Parameters in Multilevel Models”, Psychometrika, Vol. 78, No. 4, pp. 685-709. https://doi.org/10.1007/s11336-013-9328-2
Claveria, O., Monte, E. and Torra, S. (2015), “Common trends in international tourism demand: Are they useful to improve tourism predictions?”, Tourism Management Perspectives, Vol. 16, pp. 116-122. https://doi.org/10.1016/j.tmp.2015.07.013
Deluna, R. and Jeon, N. (2014), “Determinants of International Tourism Demand for the Philippines: An Augmented Gravity Model Approach”, MPRA Paper No. 55294, University of Southeastern Philippines.
Dorie, V. (2015), “blme: Bayesian Linear Mixed-Effects Models”, viewed 8 August 2016, https://cran.rproject.org/
Eilat, Y. and Einav, L. (2004), “Determinants of international tourism: a three-dimensional panel data analysis”, Applied Economics, Vol. 36, No. 12, pp. 1315-1327. https://doi.org/10.1080/000368404000180897
Galvis, L. and Aguilera, M. (1999), “Determinantes de la demanda por turismo hacia Cartagena: 1987-1998”, Lecturas de Economía, Vol. 51, pp. 47-87
Gardella, R. and Aguayo, E. (2002), “Análisis econométrico de la demanda turística internacional en la CAN”, Universidad de Santiago de Compostela, Compostela, pp. 1-17
Garin-Munoz, T. and Amaral, T. (2000), “An econometric model for international tourism flows to Spain”, Applied Economics Letters, Vol. 7 No. 8, pp. 525-529. https://doi.org/10.1080/13504850050033319
Gómez-Restrepo, J. and Cogollo-Flórez, M. (2012), “Detection of Fraudulent Transactions through a Generalized Mixed Linear Model”, Ingenieria y Ciencia, Vol. 8, No. 16, pp. 221-237. https://doi.org/10.17230/ingciencia.8.16.8
Guizzardi, A. and Mazzocchi, M. (2010), “Tourism demand for Italy and the business cycle”, Tourism Management, Vol. 31 No. 3, pp. 367-377. https://doi.org/10.1016/j.tourman.2009.03.017
Hanafiah, M. and Harun, M. (2010), “Tourism demand in Malaysia: A cross-sectional pool time-series analysis”, International Journal of Trade, Economics and Finance, Vol. 1 No. 1, pp. 80-83. https://doi.org/10.7763/IJTEF.2010.V1.15
Ibrahim, M. (2011), “The determinants of international tourism demand for Egypt: panel data evidence”, European Journal of Economics, Finance and Administrative Sciences, Vol. 30, pp. 50-58. http://dx.doi.org/10.2139/ssrn.2359121
Jiang, J. (2007), Linear and Generalized Linear Mixed Models and their Applications, Springer-Verlag, New York. http://dx.doi.org/10.1007/978-0-387-47946-0
Kaplan, F. and Aktas, A. (2016), “The Turkey Tourism Demand: A Gravity Model”, The Empirical Economics Letters, Vol. 15, No. 3, pp. 265-272
Karim, M. and Zeger, S. (1992), “Generalized linear models with random effects; salamander mating revisited”, Biometrics, Vol. 48, pp. 631-644. https://doi.org/10.2307/2532317
Keum, K. (2010), “Tourism flows and trade theory: a panel data analysis with the gravity model”, The Annals of Regional Science, Vol. 44, No. 3, pp. 541-557. https://doi.org/10.1007/s00168-008-0275-2
Li, G., Song, H. and Witt, S. (2005), “Recent developments in econometric modeling and forecasting”, Journal of Travel Research, Vol. 44, pp. 82-99. https://doi.org/10.1177/0047287505276594
Lozano, S. and Gutiérrez, E. (2018), “A complex network analysis of global tourism flows”, International Journal of Tourism Research, Vol. 20, No. 5, pp. 588-604. https://doi.org/10.1002/jtr.2208
Massidda, C. and Etzo, I. (2012), “The determinants of Italian domestic tourism: A panel data analysis”, Tourism Management, Vol. 33, No. 3, pp. 603-610. https://doi.org/10.1016/j.tourman.2011.06.017
McNeil, A, and Wendin, J. (2007), “Bayesian inference for generalized linear mixed models of portfolio credit risk”, Journal of Empirical Finance, Vol 14, No. 2, pp. 131-149. https://doi.org/10.1016/j.jempfin.2006.05.002
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Soria, E., de la Garza, M., Rebollar, S., Martínez, J. and Salazar, J. (2011), “Factores determinantes de la demanda internacional del turismo en México”, GCG: Revista de Globalización, Competitividad y Gobernabilidad, Vol. 5, No. 3, pp. 30-49
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spelling Vanegas López, Juan Gabriel06b45ca3-001c-4ffc-bdd8-53d760752726Valencia Cárdenas, Marisol7d8db2ff-5466-4ebb-a8b6-daf0bdc169d8Restrepo Morales, Jorge Aníbalaa712fa4-0570-4e4c-897d-9db795a7e78eMuñetón Santa, Guberney7e56973f-d282-4b2b-af2a-065c09f2cc132023-04-22T22:12:05Z2023-04-22T22:12:05Z20201330-7533https://dspace.tdea.edu.co/handle/tdea/28141847-3377Purpose – This paper estimates the determinants of international tourist arrivals to Colombia from 1995 to 2014. Design – Tourist demand is related to interlinking relationships between origins and destinations. The international movement of travelers has grown exponentially in recent decades, and these dynamics have affected Colombia as well. Methodology/Approach – We propose a generalized linear mixed model, with a consideration of factors from the theory of consumer choice and those approached from the perspective of new economic geography. Findings – Apart from purchasing power and institutional factors as facilitators of travel, we found that general aspects of the country (such as language and geographical proximity) directly affect the flow of visitors, whereas exchange differences and physical distance reduce tourist attraction. Originality of the research – Estimation of tourist flows will serve as a diagnostic and planning tool for developing proposals of tourism attractiveness related to different environment. Keywords tourism demand, tourist flows, generalized linear mixed model, developing countries19 páginasapplication/pdfengUniversidad de RijekaCroaciahttps://creativecommons.org/licenses/by-nc-sa/4.0/Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2https://hrcak.srce.hr/file/340108Modeling determinants of tourism demand in ColombiaArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Colombia6714926Akın, M. (2015), “A novel approach to model selection in tourism demand modeling”, Tourism Management, Vol. 48, pp. 64-72. https://doi.org/10.1016/j.tourman.2014.11.004Athanasopoulos, G., Hyndman, R., Song, H. and Wu, D. (2011), “The tourism forecasting competition”, International Journal of Forecasting, Vol. 27 No. 3, pp. 822-844. https://doi.org/10.1016/j.ijforecast.2010.04.009Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R., Singmann, H. and Grothendieck, G. (2015), “Fitting Linear Mixed-Effects Models Using lme4”, Journal of Statistical Software, Vol. 67, No. 1, pp. 1-48. https://doi.org/10.18637/jss.v067.i0Bonilla, J. and Moreno, M. (2010), “Determinantes de la demanda de turismo en Colombia 2004-2007: seguridad, comercio y otros factores”, Bachelor’s thesis, Universidad del Rosario, BogotáBruegel (2014), “Real effective exchange rates for 178 countries: a new database”, viewed 19 September 2016, https://bruegel.org/publications/datasets/real-effective-exchange-rates-for-178-countries-a-newdatabase/CEPII: Centre d‘Etudes Prospectives et d‘Informations Internationales (2015), “GeoDist database. Research and Expertise on the World Economy”, viewed 8 August 2016, http://www.cepii.fr/Cerda, R. and Leguizamón, M. (2005), “Análisis del comportamiento de la demanda turística urbana de Colombia”, Anuario Turismo y Sociedad, Vol. 4, pp. 70-98Chu, F. (2014), “Using a logistic growth regression model to forecast the demand for tourism in Las Vegas”, Tourism Management Perspectives, Vol. 12, pp. 62-67. https://doi.org/10.1016/j.tmp.2014.08.003Chung, Y., Rabe-Hesketh, S., Dorie, V., Gelman, A. and Liu, J. (2013), “A Nondegenerative Penalized Likelihood Estimator for Variance Parameters in Multilevel Models”, Psychometrika, Vol. 78, No. 4, pp. 685-709. https://doi.org/10.1007/s11336-013-9328-2Claveria, O., Monte, E. and Torra, S. (2015), “Common trends in international tourism demand: Are they useful to improve tourism predictions?”, Tourism Management Perspectives, Vol. 16, pp. 116-122. https://doi.org/10.1016/j.tmp.2015.07.013Deluna, R. and Jeon, N. (2014), “Determinants of International Tourism Demand for the Philippines: An Augmented Gravity Model Approach”, MPRA Paper No. 55294, University of Southeastern Philippines.Dorie, V. (2015), “blme: Bayesian Linear Mixed-Effects Models”, viewed 8 August 2016, https://cran.rproject.org/Eilat, Y. and Einav, L. (2004), “Determinants of international tourism: a three-dimensional panel data analysis”, Applied Economics, Vol. 36, No. 12, pp. 1315-1327. https://doi.org/10.1080/000368404000180897Galvis, L. and Aguilera, M. (1999), “Determinantes de la demanda por turismo hacia Cartagena: 1987-1998”, Lecturas de Economía, Vol. 51, pp. 47-87Gardella, R. and Aguayo, E. (2002), “Análisis econométrico de la demanda turística internacional en la CAN”, Universidad de Santiago de Compostela, Compostela, pp. 1-17Garin-Munoz, T. and Amaral, T. (2000), “An econometric model for international tourism flows to Spain”, Applied Economics Letters, Vol. 7 No. 8, pp. 525-529. https://doi.org/10.1080/13504850050033319Gómez-Restrepo, J. and Cogollo-Flórez, M. (2012), “Detection of Fraudulent Transactions through a Generalized Mixed Linear Model”, Ingenieria y Ciencia, Vol. 8, No. 16, pp. 221-237. https://doi.org/10.17230/ingciencia.8.16.8Guizzardi, A. and Mazzocchi, M. (2010), “Tourism demand for Italy and the business cycle”, Tourism Management, Vol. 31 No. 3, pp. 367-377. https://doi.org/10.1016/j.tourman.2009.03.017Hanafiah, M. and Harun, M. (2010), “Tourism demand in Malaysia: A cross-sectional pool time-series analysis”, International Journal of Trade, Economics and Finance, Vol. 1 No. 1, pp. 80-83. https://doi.org/10.7763/IJTEF.2010.V1.15Ibrahim, M. (2011), “The determinants of international tourism demand for Egypt: panel data evidence”, European Journal of Economics, Finance and Administrative Sciences, Vol. 30, pp. 50-58. http://dx.doi.org/10.2139/ssrn.2359121Jiang, J. (2007), Linear and Generalized Linear Mixed Models and their Applications, Springer-Verlag, New York. http://dx.doi.org/10.1007/978-0-387-47946-0Kaplan, F. and Aktas, A. (2016), “The Turkey Tourism Demand: A Gravity Model”, The Empirical Economics Letters, Vol. 15, No. 3, pp. 265-272Karim, M. and Zeger, S. (1992), “Generalized linear models with random effects; salamander mating revisited”, Biometrics, Vol. 48, pp. 631-644. https://doi.org/10.2307/2532317Keum, K. (2010), “Tourism flows and trade theory: a panel data analysis with the gravity model”, The Annals of Regional Science, Vol. 44, No. 3, pp. 541-557. https://doi.org/10.1007/s00168-008-0275-2Li, G., Song, H. and Witt, S. (2005), “Recent developments in econometric modeling and forecasting”, Journal of Travel Research, Vol. 44, pp. 82-99. https://doi.org/10.1177/0047287505276594Lozano, S. and Gutiérrez, E. (2018), “A complex network analysis of global tourism flows”, International Journal of Tourism Research, Vol. 20, No. 5, pp. 588-604. https://doi.org/10.1002/jtr.2208Massidda, C. and Etzo, I. (2012), “The determinants of Italian domestic tourism: A panel data analysis”, Tourism Management, Vol. 33, No. 3, pp. 603-610. https://doi.org/10.1016/j.tourman.2011.06.017McNeil, A, and Wendin, J. 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(2010), “Analysis of international tourist arrivals in China: The role of World Heritage Sites”, Tourism Management, Vol. 31, No. 6, pp. 827-837. https://doi.org/10.1016/j.tourman.2009.08.008Países en DesarrolloDeveloping CountriesPaíses em DesenvolvimentoTourism demandTourist flowsGeneralized linear mixed modelDemanda turísticaFlujos turísticosModelo mixto lineal generalizadoORIGINALModeling determinants of tourism demand in Colombia.pdfModeling determinants of tourism demand in Colombia.pdfapplication/pdf822577https://dspace.tdea.edu.co/bitstream/tdea/2814/1/Modeling%20determinants%20of%20tourism%20demand%20in%20Colombia.pdfff724f7b314591d59b81816fd817e930MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://dspace.tdea.edu.co/bitstream/tdea/2814/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessTEXTModeling determinants of tourism demand in Colombia.pdf.txtModeling determinants of tourism demand in Colombia.pdf.txtExtracted 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 incorporada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.


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