El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes
Introduction: Previous studies have found a strong relationship between the degree to which individuals believe a technology helps to gain performance (performance expectancy) and the use of that technology. However, there is little empirical research that tests the mechanisms and conditions through...
- Autores:
-
Arcila Calderón, Carlos
Lopez Ponce, Marcela
Peña, Jennie R.
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/2160
- Acceso en línea:
- https://hdl.handle.net/11323/2160
https://repositorio.cuc.edu.co/
- Palabra clave:
- Adoption
ICT
Innovation
Performance expectancy
Use
Social media
Youth
- Rights
- openAccess
- License
- Atribución – No comercial – Compartir igual
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El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| dc.title.translated.spa.fl_str_mv |
The Conditional Indirect Effect of Performance Expectancy in the Use of Facebook, Google+, Instagram and Twitter by youngsters |
| title |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| spellingShingle |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes Adoption ICT Innovation Performance expectancy Use Social media Youth |
| title_short |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| title_full |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| title_fullStr |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| title_full_unstemmed |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| title_sort |
El efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenes |
| dc.creator.fl_str_mv |
Arcila Calderón, Carlos Lopez Ponce, Marcela Peña, Jennie R. |
| dc.contributor.author.spa.fl_str_mv |
Arcila Calderón, Carlos Lopez Ponce, Marcela Peña, Jennie R. |
| dc.subject.spa.fl_str_mv |
Adoption ICT Innovation Performance expectancy Use Social media Youth |
| topic |
Adoption ICT Innovation Performance expectancy Use Social media Youth |
| description |
Introduction: Previous studies have found a strong relationship between the degree to which individuals believe a technology helps to gain performance (performance expectancy) and the use of that technology. However, there is little empirical research that tests the mechanisms and conditions through which this effect operates in the adoption of social media by youngsters. Methods: We surveyed 502 students from Colombia and run a moderated mediation analysis to check conditional indirect effects. Results and conclusions: Data revealed high adoption rates (68%) of popular social media (Facebook, Google+, Instagram and Twitter) and, consistent with the Unified Theory of Acceptance and Use of Technology (UTAUT), results showed that the conditional indirect effect of performance expectancy in the use of social media is a relevant predictor with weights up to 0.53. This effect is mediated by the behavioral intention, but only in some cases moderated by age and gender. |
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2017 |
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2017 |
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2019-01-23T21:22:55Z |
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2019-01-23T21:22:55Z |
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Artículo de revista |
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Agarwal, R. y Karahanna, E. (2000). Time flies when you‟re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. Akbulut, Y. y Günüç, S. (2012). Perceived Social Support and Facebook Use among Adolescents. International Journal of Cyber Behavior, Psychology and Learning, 2 (1), 30-41. Akram, M.S; Albalawi, Wi. (2016). Youths' Social Media Adoption: Theoretical Model and Empirical Evidence. International Journal of Business and Management. 11(2), 22-30 Arcila, C., Calderín, M. y Aguaded, I. 2015. Adoption of ICTs by Communication Researchers for Scientific Diffusion and Data Analysis. El Profesional de la Información, 24 (5). Aydn, B. y Volkan Sar, S. (2011). Internet addiction among adolescents: the role of self-esteem. Procedia Social and Behavioral Sciences, 15, 3500–3505. Ben, M. (2016). Futuro Digital Colombia 2016. Trabajo presentado en IAB Day Colombia. Agosto 28, 2016 Bringué, X. y Sádaba, C. (2008). Generación Interactiva en Iberoamérica. Niños y adolescentes frente a las pantallas. Retos educativos y sociales. Barcelona: Ariel, Colección Fundación Telefónica. Bringué, X. y Sádaba, C. 2011. Menores y redes sociales. Madrid: Foro generaciones interactivas. Cázares, A. (2010). Proficiency and attitudes toward information technologies' use in psychology undergraduates. Computers in Human Behavior, 26(5), 1004-1008. Cheung CM, Chiu P-Y y Lee MK. (2011). Online social networks: Why do students use Facebook? Computers in Human Behavior, 27, 1337–1343 Cheung CM, Lee MK. (2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49, 24–30 Claggett, J. L y Goodhue, D. L. (2011). Have IS researchers lost bandura's self-efficacy concept? A discussion of the definition and measurement of computer self-efficacy. Trabajo presentado en 44th Hawaii International Conference on System Sciences (HICSS). Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297- 334. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-339. Davis, F. D., Bagozzi, R. P. y Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111- 1132. Duggan, M. (2015). Mobile Messaging and Social Media – 2015. Recuperado de http://www.pewinternet.org/2015/08/19/mobile-messaging-and-social-media-2015/ Faul, F., Erdfelder, E., Buchner, A. y Lang, A. (2009). Statistical power analysis using G*Power 3.1: Tests for correlation and regression analysis. Behavior Research Methods, 41(4), 1149-1160 doi: http://dx.doi.org/10.3758/BRM.41.4.1149 Faul, F.; Erdfelder, E.; Lang, A. & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191, doi: http://dx.doi.org/10.3758/BF03193146 Hall, D. y Mansfield, R. (1995). Relationships of Age and Seniority with Career Variables of Engineers and Scientists. Journal of Applied Psychology, 60(2), 201-210. Hayes, A. (2005). Statistical Methods for Communication Science. Mahwah, NJ: Lawrence Erlbaum Associates. ISBN: 978-0805854879 Hayes, A. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression based approach. New York: Guilford Press. Igartua, J.J. (2006). Métodos Cuantitativos de Investigación en Comunicación. Madrid: Editorial Bosch. Jackson, C. M., Chow, S., y Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389. Kemp, S. (2017). Digital, Social and Mobile in 2017. We are social, January 2017 Recuperado de https://wearesocial.com/blog/2017/01/digital-in-2017-global-overview Lin K-Y y Lu H-P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27, 1152–1161 Mac Callum, K. y Jeffrey, L. (2013). The influence of students' ICT skills and their adoption of mobile learning. Australasian Journal of Educational Technology, 29(3), 303-314. Macía-Sepúlveda, F. (2010). Validez de los tests y el análisis factorial: nociones generales, Ciencia y Trabajo, 12(35), 276-280. Mander, J. (2016). GWI Social Summary. Recuperado de https://www.globalwebindex.net/hubfs/Reports/GWI_Social_-_Q1_2016_Summary.pdf Minton, H. L., y Schneider, F. W. (1980). Differential Psychology. Waveland Press, Prospect Heights, IL. Notley, T. (2009). Young People, Online Networks, and Social Inclusion. Journal of ComputerMediated Communication, 14: 1208-1227. Pérez-Gil, J., Chacón, S. y Moreno, R. (2000). Validez de constructo: El uso de análisis factorial exploratorio-confirmatorio para obtener evidencias de validez. Psicothema, 12(2), 442-446. Porter, L. (1963). Job Attitudes in Management: Perceived Importance of Needs as a Function of Job Level. Journal of Applied Psychology, 47(2), 141-148 Quinlan, S., Gummer, T., Roßmann, J., & Wolf, C. (2017). „Show me the money and the party!‟– variation in Facebook and Twitter adoption by politicians. Information, Communication & Society, 1-19. Subrahmanyam, K. y Lin, G. (2007). Adolescents on the net: internet use and wellbeing. Adolescence, 42(168), 659-677 Valkenburg, P.M. y Peter, J. (2007). Preadolescents and Adolescents Online Communication and their Closeness to Friends. Developmental Psychology, 43, 267-277. Venkatesh, V., Morris, M. G., Davis, G. B. y Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Venkatesh, V., Thong, J.y Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157- 178 Wang, N. y Yongqiang, S. (2015). Social influence or personal preference? Examining the determinants of usage intention across social media with different sociability. Information Development (2015): 0266666915603224. Yuki, T. y Marchant, I. (2014). El Estado de Social Media en América Latina. [Presentación de PowerPoint]. Recuperado de https://www.comscore.com/esl/Insights/Presentations-andWhitepapers/2014/The-State-of-Social-Media-in-Latin-America-and-the-Metrics-that-ReallyMatter Zhang, P., Aikman, S.N. y Sun, H. (2008). Two Types of Attitudes in ICT Acceptance and Use. Journal of Human Computer Interaction, 24(7), 628–648. Zheng, R. y Cheok, A. (2011). Singaporean Adolescents‟ Perceptions of On-line Social Communication: An Exploratory Factor Analysis. Journal of Educational Computing, 45(2), 203-221. |
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Arcila Calderón, CarlosLopez Ponce, MarcelaPeña, Jennie R.2019-01-23T21:22:55Z2019-01-23T21:22:55Z201711385820https://hdl.handle.net/11323/2160Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Introduction: Previous studies have found a strong relationship between the degree to which individuals believe a technology helps to gain performance (performance expectancy) and the use of that technology. However, there is little empirical research that tests the mechanisms and conditions through which this effect operates in the adoption of social media by youngsters. Methods: We surveyed 502 students from Colombia and run a moderated mediation analysis to check conditional indirect effects. Results and conclusions: Data revealed high adoption rates (68%) of popular social media (Facebook, Google+, Instagram and Twitter) and, consistent with the Unified Theory of Acceptance and Use of Technology (UTAUT), results showed that the conditional indirect effect of performance expectancy in the use of social media is a relevant predictor with weights up to 0.53. This effect is mediated by the behavioral intention, but only in some cases moderated by age and gender.Arcila Calderón, Carlos-a3f412d4-269f-46bb-934a-2bee66419ecd-0Lopez Ponce, Marcela-0000-0001-7340-3570-600Peña, Jennie R.-e68948cb-1a82-46c7-b8a5-8d5b702661d6-0spaRevista Latina de Comunicacion SocialAtribución – No comercial – Compartir igualinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2AdoptionICTInnovationPerformance expectancyUseSocial mediaYouthEl efecto condicional indirecto de la expectativa de rendimiento en el uso de Facebook, Google+, Instagram y Twitter por jóvenesThe Conditional Indirect Effect of Performance Expectancy in the Use of Facebook, Google+, Instagram and Twitter by youngstersArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersionAgarwal, R. y Karahanna, E. (2000). Time flies when you‟re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665–694. Akbulut, Y. y Günüç, S. (2012). Perceived Social Support and Facebook Use among Adolescents. International Journal of Cyber Behavior, Psychology and Learning, 2 (1), 30-41. Akram, M.S; Albalawi, Wi. (2016). Youths' Social Media Adoption: Theoretical Model and Empirical Evidence. International Journal of Business and Management. 11(2), 22-30 Arcila, C., Calderín, M. y Aguaded, I. 2015. Adoption of ICTs by Communication Researchers for Scientific Diffusion and Data Analysis. El Profesional de la Información, 24 (5). Aydn, B. y Volkan Sar, S. (2011). Internet addiction among adolescents: the role of self-esteem. Procedia Social and Behavioral Sciences, 15, 3500–3505. Ben, M. (2016). Futuro Digital Colombia 2016. Trabajo presentado en IAB Day Colombia. Agosto 28, 2016 Bringué, X. y Sádaba, C. (2008). Generación Interactiva en Iberoamérica. Niños y adolescentes frente a las pantallas. Retos educativos y sociales. Barcelona: Ariel, Colección Fundación Telefónica. Bringué, X. y Sádaba, C. 2011. Menores y redes sociales. Madrid: Foro generaciones interactivas. Cázares, A. (2010). Proficiency and attitudes toward information technologies' use in psychology undergraduates. Computers in Human Behavior, 26(5), 1004-1008. Cheung CM, Chiu P-Y y Lee MK. (2011). Online social networks: Why do students use Facebook? Computers in Human Behavior, 27, 1337–1343 Cheung CM, Lee MK. (2010). A theoretical model of intentional social action in online social networks. Decision Support Systems, 49, 24–30 Claggett, J. L y Goodhue, D. L. (2011). Have IS researchers lost bandura's self-efficacy concept? A discussion of the definition and measurement of computer self-efficacy. Trabajo presentado en 44th Hawaii International Conference on System Sciences (HICSS). Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Erlbaum. Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297- 334. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-339. Davis, F. D., Bagozzi, R. P. y Warshaw, P. R. (1992). Extrinsic and Intrinsic Motivation to Use Computers in the Workplace. Journal of Applied Social Psychology, 22(14), 1111- 1132. Duggan, M. (2015). Mobile Messaging and Social Media – 2015. Recuperado de http://www.pewinternet.org/2015/08/19/mobile-messaging-and-social-media-2015/ Faul, F., Erdfelder, E., Buchner, A. y Lang, A. (2009). Statistical power analysis using G*Power 3.1: Tests for correlation and regression analysis. Behavior Research Methods, 41(4), 1149-1160 doi: http://dx.doi.org/10.3758/BRM.41.4.1149 Faul, F.; Erdfelder, E.; Lang, A. & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175-191, doi: http://dx.doi.org/10.3758/BF03193146 Hall, D. y Mansfield, R. (1995). Relationships of Age and Seniority with Career Variables of Engineers and Scientists. Journal of Applied Psychology, 60(2), 201-210. Hayes, A. (2005). Statistical Methods for Communication Science. Mahwah, NJ: Lawrence Erlbaum Associates. ISBN: 978-0805854879 Hayes, A. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression based approach. New York: Guilford Press. Igartua, J.J. (2006). Métodos Cuantitativos de Investigación en Comunicación. Madrid: Editorial Bosch. Jackson, C. M., Chow, S., y Leitch, R. A. (1997). Toward an understanding of the behavioral intention to use an information system. Decision Sciences, 28(2), 357-389. Kemp, S. (2017). Digital, Social and Mobile in 2017. We are social, January 2017 Recuperado de https://wearesocial.com/blog/2017/01/digital-in-2017-global-overview Lin K-Y y Lu H-P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27, 1152–1161 Mac Callum, K. y Jeffrey, L. (2013). The influence of students' ICT skills and their adoption of mobile learning. Australasian Journal of Educational Technology, 29(3), 303-314. Macía-Sepúlveda, F. (2010). Validez de los tests y el análisis factorial: nociones generales, Ciencia y Trabajo, 12(35), 276-280. Mander, J. (2016). GWI Social Summary. Recuperado de https://www.globalwebindex.net/hubfs/Reports/GWI_Social_-_Q1_2016_Summary.pdf Minton, H. L., y Schneider, F. W. (1980). Differential Psychology. Waveland Press, Prospect Heights, IL. Notley, T. (2009). Young People, Online Networks, and Social Inclusion. Journal of ComputerMediated Communication, 14: 1208-1227. Pérez-Gil, J., Chacón, S. y Moreno, R. (2000). Validez de constructo: El uso de análisis factorial exploratorio-confirmatorio para obtener evidencias de validez. Psicothema, 12(2), 442-446. Porter, L. (1963). Job Attitudes in Management: Perceived Importance of Needs as a Function of Job Level. Journal of Applied Psychology, 47(2), 141-148 Quinlan, S., Gummer, T., Roßmann, J., & Wolf, C. (2017). „Show me the money and the party!‟– variation in Facebook and Twitter adoption by politicians. Information, Communication & Society, 1-19. Subrahmanyam, K. y Lin, G. (2007). Adolescents on the net: internet use and wellbeing. Adolescence, 42(168), 659-677 Valkenburg, P.M. y Peter, J. (2007). Preadolescents and Adolescents Online Communication and their Closeness to Friends. Developmental Psychology, 43, 267-277. Venkatesh, V., Morris, M. G., Davis, G. B. y Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. Venkatesh, V., Thong, J.y Xu, X. (2012). Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology. MIS Quarterly, 36(1), 157- 178 Wang, N. y Yongqiang, S. (2015). Social influence or personal preference? Examining the determinants of usage intention across social media with different sociability. Information Development (2015): 0266666915603224. Yuki, T. y Marchant, I. (2014). El Estado de Social Media en América Latina. [Presentación de PowerPoint]. Recuperado de https://www.comscore.com/esl/Insights/Presentations-andWhitepapers/2014/The-State-of-Social-Media-in-Latin-America-and-the-Metrics-that-ReallyMatter Zhang, P., Aikman, S.N. y Sun, H. (2008). Two Types of Attitudes in ICT Acceptance and Use. Journal of Human Computer Interaction, 24(7), 628–648. Zheng, R. y Cheok, A. (2011). Singaporean Adolescents‟ Perceptions of On-line Social Communication: An Exploratory Factor Analysis. Journal of Educational Computing, 45(2), 203-221.PublicationORIGINALEl efecto condicional indirecto de la expectativa.pdfEl efecto condicional indirecto de la expectativa.pdfapplication/pdf543753https://repositorio.cuc.edu.co/bitstreams/f4daf986-88a3-4847-b129-f74d814a25f6/downloadba0566724e12354f2dcad81961ed3f51MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/779e1b75-cd58-4482-aeb0-20a16e0fceea/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILEl efecto condicional indirecto de la expectativa.pdf.jpgEl efecto condicional indirecto de la expectativa.pdf.jpgimage/jpeg79150https://repositorio.cuc.edu.co/bitstreams/6c394939-01c3-41cf-bb2d-9350c16a3e04/downloadc7507078c9453c1af18d00b39f28591dMD54TEXTEl efecto condicional indirecto de la expectativa.pdf.txtEl efecto condicional indirecto de la expectativa.pdf.txttext/plain58938https://repositorio.cuc.edu.co/bitstreams/1916cb0a-de4f-4496-aa16-50025e59d01c/downloadaa3a2606ef1ff4a348c4df4ff1a6baf3MD5511323/2160oai:repositorio.cuc.edu.co:11323/21602024-09-17 11:07:39.781open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.coTk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo= |