El Impacto del Uso del Big Data en el Mercado de Bebidas Refrescantes en Mexico
| dc.contributor.author | Perez Morales, Fabian Alejandro | |
| dc.contributor.cvlac | https://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001456134 | |
| dc.date.accessioned | 2024-05-07T17:43:50Z | |
| dc.date.available | 2024-05-07T17:43:50Z | |
| dc.date.issued | 2024-03-02 | |
| dc.description | En la actualidad, el avance tecnológico y la proliferación de datos han transformado diversos sectores económicos, siendo el mercado de bebidas refrescantes en México uno de los más impactados. La disponibilidad de grandes volúmenes de datos, conocidos como Big Data, ha proporcionado a las empresas del sector valiosa información para analizar tendencias del consumidor, mejorar la eficiencia operativa y desarrollar estrategias de marketing más precisas. Este ensayo se centra en explorar las implicaciones del uso del Big Data en dicho mercado, específicamente en relación con la privacidad de los consumidores y las estrategias de mercado implementadas por las empresas. El documento se estructura en tres partes: contextualización de los avances en el Big Data, argumentos que responden a la pregunta guía utilizando casos de compañías (multinacional y local), y conclusiones. Se destaca que el uso estratégico del Big Data por parte de empresas, como Coca-Cola y Jarritos Cola en México, ha sido fundamental para analizar patrones de consumo, comprender el comportamiento del consumidor y anticipar tendencias del mercado. Sin embargo, se plantean desafíos éticos, especialmente en términos de privacidad, transparencia y equidad en el tratamiento de la información de los consumidores. La conclusión resalta la importancia de regulaciones éticas para garantizar un equilibrio adecuado entre la obtención de información valiosa y la protección de la privacidad. | spa |
| dc.description.abstract | Currently, technological advancement and the proliferation of data have transformed various economic sectors, with the soft drinks market in Mexico being one of the most impacted. The availability of large volumes of data, known as Big Data, has provided companies in the sector with valuable information to analyze consumer trends, improve operational efficiency, and develop more accurate marketing strategies. This essay focuses on exploring the implications of the use of Big Data in such a market, specifically in relation to consumer privacy and the market strategies implemented by companies. The document is structured in three parts: contextualization of advances in Big Data, arguments that answer the guiding question using cases of companies (multinational and local), and conclusions. It is highlighted that the strategic use of Big Data by companies, such as Coca-Cola and Jarritos Cola in Mexico, It has been instrumental in analyzing consumption patterns, understanding consumer behavior, and anticipating market trends. However, ethical challenges arise, especially in terms of privacy, transparency and fairness in the treatment of consumer information. The conclusion highlights the importance of ethical regulations to ensure an appropriate balance between obtaining valuable information and protecting privacy. | spa |
| dc.description.degreelevel | Pregrado | spa |
| dc.description.degreename | Profesional en Mercadeo | spa |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | Perez Morales, F. A. (s.f.). El Impacto del Uso del Big Data en el Mercado de Bebidas Refrescantes en Mexico. [Trabajo de Grado, Universidad Santo Tomás]. Repositorio Institucional. | spa |
| dc.identifier.instname | instname:Universidad Santo Tomás | spa |
| dc.identifier.reponame | reponame:Repositorio Institucional Universidad Santo Tomás | spa |
| dc.identifier.repourl | repourl:https://repository.usta.edu.co | spa |
| dc.identifier.uri | http://hdl.handle.net/11634/55046 | |
| dc.language.iso | spa | |
| dc.publisher | Universidad Santo Tomás | spa |
| dc.publisher.branch | CRAI-USTA Bogotá | spa |
| dc.publisher.faculty | Facultad de Mercadeo | spa |
| dc.publisher.program | Pregrado Mercadeo | spa |
| dc.relation.references | Agarwal, R., & Dhar, V. (2014). Big Data, Data Science and Analytics: The opportunity and challenge for IS research. Information Systems Research, 443 - 448 | spa |
| dc.relation.references | Akter, S., Wamba, S., Gunasekaran, A., & Dubey, R. (2016). How to improve firm performance using big data analytics capacbility and business strategy aligment. International Journal of Production Economics, 113 - 131 | spa |
| dc.relation.references | Benítez-Amado, J., & Walczuch, M. (2012). Information technology, the organizational capability of proactive corporate environmental strategy and firm performance: a resource-based analysis. European Journal of Information Systems, 664 - 679. | spa |
| dc.relation.references | Berliner, D., Palmer-Rubin, B., & Tapia, J. (2022). Big data y acceso a la información en México. Obtenido de bigdataytransparenciamx.lse.ac.uk/ | spa |
| dc.relation.references | Boubiche, S., Boubiche, D. E., Bilami, A., & Toral-Cruz, H. (2018). Big Data Challenges and Data Aggregation Strategies in Wireless Sensor Networks. IEEE, 558 - 571 | spa |
| dc.relation.references | Cao, G., Tian, N., & Blankson, C. (2021). Big Data, Marketing Analytics, and Firm Marketing Capabilities. Journal of Computer Information Systems , 442 - 451 | spa |
| dc.relation.references | Clader, B., Malthouse, E., & Maslowska, E. (2016). Brand marketing, big data and social innovation as future research directions for engagement. Journal of Marketing Management, 579 - 585. | spa |
| dc.relation.references | Ebner, K., Buhnen, T., & Urbach, N. (2014). Think Big with Big Data: Identifying Suitable Big Data Strategies in Corporate Environments. IEEE, 748 - 757. | spa |
| dc.relation.references | García, N. (2013). The Effects of Language on Attitudes Toward Advertisements and Brands Trust in Mexico. Journal of Current Issues & Research in Advertising, 77 - 92. | spa |
| dc.relation.references | Gómez, E. (2019). Coca-Cola’s political and policy influence in Mexico: understanding the role of institutions, interests and divided society . Health Policy and Planning, 520 - 528. | spa |
| dc.relation.references | Goyzueta, S. (2015). Big Data Marketing: una aproximación. Revista Perspectivas, 147 - 158. | spa |
| dc.relation.references | Gupta, M., & George, J. (2016). Toward the development of a big data analytics campability. Information & Management, 1049 - 1064. | spa |
| dc.relation.references | Hilbert, M. (2016). Big Data for Development: A Review of Promises and Challenges. Technology Virtual Issue, 135 - 174. | spa |
| dc.relation.references | Huse, O., Reevw, E., Bell, C., Sacks, G., Baker, P., Wood, B., & Backholer, K. (2022). Strategies used by the soft drink industry to grow and sustain sales: a case-study of The Coca-Cola Company in East Asia . BMJ Global Healt | spa |
| dc.relation.references | Janssen, M., Van Der Vort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 338 - 345 | spa |
| dc.relation.references | Jieren, L., & Xiaolin, L. (2016). Innovation business model of Big Data. Taking Coca-Cola as an example. International Conference on Management. | spa |
| dc.relation.references | Klievink, B., Romijn, B.-J., Cunningham, S., & Bruijn, H. (2017). Big data in the public sector: Uncertainties and readiness. Information Systems Frontiers, 267 - 283. | spa |
| dc.relation.references | Lee, J., Lapira, E., Bagheri, B., & Kao, H. (2013). Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters, 38 - 41. | spa |
| dc.relation.references | Macca, L., Shehzad, N., Kovacova, M., & Santoro, G. (2024). Unlocking e-commerce potential: micro and small enterprises strike back in the food and beverage industry. European JOurnal of Innovation Management | spa |
| dc.relation.references | McLaren, T., Head, M., Yuan, Y., & Chan, Y. (2011). A multilevel model for measuring fit between a firm’s competitive strategies and information systems capabilities. MIS Quarterly, 909 - 929 | spa |
| dc.relation.references | Medina La Plata, E. H. (2023). Big Data. Los datos como generadores de valor. En E. H. Medina La Plata. Lima: Editorial UPC. | spa |
| dc.relation.references | Merendino, A., Dibb, S., & Meadows, M. (2018). Big data, big decisions: The impact of big data on board level decision-making. Journal of Businessc Research, 67 - 78. | spa |
| dc.relation.references | Mittelstadt, B., & Floridi, L. (2016). The Ethics of Big Data: Current and Foreseeable Issues in Biomedical Contexts. Law, Governance and Technology Series, 445 - 480. | spa |
| dc.relation.references | Montgomery, K., Chester, J., Nixon, L., & Dorfman, L. (2017). Big Data and the transformation of food and beverage marketing: undermining efforts to reduce obesity? Critical Public Health, 110 - 117. | spa |
| dc.relation.references | Nolasco-Mamani, M., Espinoza, S., & Choque-Salcedo, R. (2023). Innovación y Transformación Digital en la Empresa. Guayaquil: ACVENISPOH. | spa |
| dc.relation.references | Ortiz, D., Joyanes, L., & Giraldo, L. (2016). Los desafíos del marketing en la era del big data. e Ciencias de la información. | spa |
| dc.relation.references | Popovic, A., Hackney, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. The Journal of Strategic Information Systems, 209 - 222. | spa |
| dc.relation.references | Salinas, A. (2016). Análisis de las preferencias en el consumo de bebidas carbonatadas en los hogares del municipio de Tenancingo, Estado de México. Centro Universitario UAEM Tenancingo. | spa |
| dc.relation.references | Shanks, G., Gloet, M., Asadi, I., Frampton, K., & Tamm, T. (2018). Achieving benefits with enterprise architecture. The Journal of Strategic Information Systems, 139 - 156. | spa |
| dc.relation.references | Toledo, H., & Hubenova, V. (2018). Contemporary Marketing Practices in Mexico. Economic Alternatives, 239 - 249. | spa |
| dc.relation.references | Van Horn, D., Olewnik, A., & Lewis, K. (2013). Design Analytics: Capturing, Understanding, and Meeting Customer Needs Using Big Data . 863 - 875. | spa |
| dc.relation.references | Zwitter, A. (2014). Big Data Ethics. Big Data & Society | spa |
| dc.rights | Atribución-NoComercial-SinDerivadas 2.5 Colombia | |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | spa |
| dc.rights.local | Abierto (Texto Completo) | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/2.5/co/ | |
| dc.subject.keyword | Spanish Golde age | spa |
| dc.subject.lemb | Mercadeo | spa |
| dc.subject.lemb | Tecnología | spa |
| dc.subject.lemb | Economía | spa |
| dc.subject.lemb | Empresa | spa |
| dc.subject.lemb | Consumidor | spa |
| dc.subject.proposal | Big Data | spa |
| dc.subject.proposal | Bebidas Refrescantes | spa |
| dc.subject.proposal | México | spa |
| dc.title | El Impacto del Uso del Big Data en el Mercado de Bebidas Refrescantes en Mexico | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_7a1f | |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| dc.type.drive | info:eu-repo/semantics/bachelorThesis | |
| dc.type.local | Trabajo de grado | spa |
| dc.type.version | info:eu-repo/semantics/acceptedVersion |
Archivos
Bloque original
1 - 3 de 3
Cargando...
- Nombre:
- 2024PerezFabian.pdf
- Tamaño:
- 322.97 KB
- Formato:
- Adobe Portable Document Format
- Descripción:
Cargando...
- Nombre:
- 2024Cartaautoarchivo (3).pdf
- Tamaño:
- 578.22 KB
- Formato:
- Adobe Portable Document Format
- Descripción:
Cargando...
- Nombre:
- 2024Cartafacultad (1).pdf
- Tamaño:
- 262.24 KB
- Formato:
- Adobe Portable Document Format
- Descripción:
Bloque de licencias
1 - 1 de 1
Cargando...
- Nombre:
- license.txt
- Tamaño:
- 807 B
- Formato:
- Item-specific license agreed upon to submission
- Descripción:

