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dc.contributor.advisorRuiz Cruz, Carlos Rodrigo
dc.contributor.authorOsorio Giraldo, Oscar David
dc.date.accessioned2018-12-04T19:39:58Z
dc.date.available2018-12-04T19:39:58Z
dc.date.issued2018-09-23
dc.identifier.citationAndresen, C., Larsen, T., Thernoe, C. (2014). Supply chain collaboration: theoretical perspective and empirical evidence. International Journal of Physical Distribution & Logistics Management, Vol. 33(6), p. 531-549. doi: 10.1108/09600030310492788.
dc.identifier.citationAnthony, T. (2000). Supply chain collaboration: success in the new internet economy. Achieving Supply chain Excellence Through Technology, Montgomery Research Inc, Vol. 2, p. 41-44. Recuperado de ftp://openstorage.gunadarma.ac.id/idkf/idkf-wireless/aplikasi/ecommerce/anthony.pdf
dc.identifier.citationBarrat, M., Oliveira, A. (2001). Exploring the experiences of collaborative planning initiatives. International Journal of Physical Distribution & Logistics, Vol. 31(4), p. 266-289. doi: 10.1108/09600030110394932
dc.identifier.citationBarrat, M. (2004). Understanding the meaning of collaboration in the supply chain. Supply Chain Management, Vol. 9(1), p. 30-42. doi: 10.1108/13598540410517566.
dc.identifier.citationBoyer, S., Stock, J. (2009). Developing a consensus definition of supply chain management: a qualitative study. International Journal of Physical Distribution & Logistics Management, Vol. 39(8), p. 690-771. doi: 10.1108/09600030910996323.
dc.identifier.citationByrne, P., Heavey, C., Panahifar, F. (2015). A hybrid approach to the study of CPFR implementation enablers. Production Planning & Control, Vol. 26(13), p. 1090-1109. doi: 10.1080/09537287.2015.1011725
dc.identifier.citationCannela, S., Ciancimino, E. (2010). On the bullwhip avoidance phase: supply chain collaboration and order smotthing. International Journal of Production Research, Vol. 8(22), p. 6739- 6776. doi: 10.1080/00207540903252308.
dc.identifier.citationCao, M., Zhang, Q. (2011). Supply chain collaboration impact on collaborative advantage and firm performance. Journal of Operations Management, Vol. 29(3), p. 163-180. doi: 10.1016/j.jom.2010.12.008
dc.identifier.citationCaridi, M., Cigolini, R., De Marco, D. (2005). Improving supply chain collaboration by linking intelligent agents to CPFR. International Journal of Production Research, Vol. 43(20), p. 4191-4218. doi: 10.1080/00207540500142134.
dc.identifier.citationCaridi, M., Cigolini, R., De Marco, D. (2006). Linking autonomous agents to CPFR to improve SCM. International Journal of Production Research, Vol. 43(5), p. 4191-4218. doi: 10.1108/17410390610703620.
dc.identifier.citationCederlund, J., Kohli, R., Sherer, S., Yao, Y. (2007). How motorola put CPFR into action. Supply Chain Management Review, Vol. 11(7), p. 28-35. Recuperado de https://search-proquestcom.ez.unisabana.edu.co/docview/221133917?accountid=45375
dc.identifier.citationChang, T., Fu, H., Hsueh, H., Lee, W., Lin, Y. (2007). A study of an augemented CPFR model for the 3C retail industry. Supply Chain Management: An International Journal, Vol. 12 (3), p. 200-209. doi: 10.1108/13598540710742518.
dc.identifier.citationChase, C. (2014). Innovation in business forecasting. Journal of Business Forecasting, Vol. 3(1), p. 29-34.
dc.identifier.citationChen, S., Chi, X., Lai, K., Shu, T., Wang, S. (2010). AVE-CPFR working chains on the basis of selection model of collaborative credit-grating guarantee approaches. International Journal of Information Technolgy & Decision Making, Vol. 9(2), p. 301-325. doi: 10.1142/s021962201000383x.
dc.identifier.citationChopra, S., Meindl, P. (Ed. 2) (2004). Supply Chain Management –Strategy, Planning and Operations. New Jersey, Estados Unidos: Pearson.
dc.identifier.citationConstantino, F., Gravio, G., Shaban, A., Tronci, M. (2015). The impact of information sharing on ordering policies to improve supply chain performances. Computers & Industrial Engineering, Vol. 82(2017), p. 127-142. doi: 10.1016/j.cie.2015.01.024.
dc.identifier.citationCooke, J. (1998). VMI: very mixed impact. Logistics Management and Distribution Report, Vol. 37(12), p. 51-53. Recuperado de https://search-proquestcom.ez.unisabana.edu.co/docview/197197395?accountid=45375
dc.identifier.citationCox, J., Blackstone, J. (Ed. 10) (2004). APICS Dictionary: the industry standards for more than 3.500 terms and definitions. Estados Unidos, Chicago: American Production and Inventory Control Society
dc.identifier.citationCSCMP (2017). Council of Supply Chain Management Professionals. CSCMP supply chain management definitions and glossary. Recuperado de https://cscmp.org/imis0/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms/CSC MP/Educate/SCM_Definitions_and_Glossary_of_Terms.aspx?hkey=60879588-f65f-4ab5- 8c4b-6878815ef921
dc.identifier.citationCuthbertson, R. (2002). European CPFR insights. European Retail Digest, Vol. 35, p. 1-54.
dc.identifier.citationDanese, P. (2007). Designing CPFR collaborations: insight from seven case studies. International Journal of Operations & Production Management, Vol. 27(2), p. 181-204
dc.identifier.citationDatamonitor (2010). Industry profile: global home improvement retail. Datamonitor, p. 1-29. Recuperado de http://web.b.ebscohost.com.ez.unisabana.edu.co/ehost/pdfviewer/pdfviewer?vid=7&sid=92 71e94c-44b8-4558-9aff-b535e59b101a%40sessionmgr103
dc.identifier.citationDavenport, T., Harmon, P. (Ed. 2) (2007). Business Process Change. Burlington, Estados Unidos: Morgan Kaufmann.
dc.identifier.citationDeCarlo, N., Samuel, P., Silverstein, D. (Ed. 1) (2009). The innovator’s toolkit: 50+ techniques for preditable and sustainable organic growth. New Yersey, Estados Unidos: John Wiley & Sons.
dc.identifier.citationDezdar, S., Lee, S., Mallasi, H., Sulaiman, A. (2015). Electronic data interchange adoption from technological, organisational and environmental perspectives. International Journal of Business Information Systems, Vol. 18(3), p. 299-320. doi: 10.1504/IJBIS.2015.068166
dc.identifier.citationDisney, S., Towill, D. (2003). The effect of vendor managed inventory (VMI) dynamics on the bullwhip effect in supply chains. International Journal of Production Economics, Vol. 85(2), p. 199-125. doi: 10.1016/S0925-5273(03)00110-5
dc.identifier.citationEMIS (2015a). Estudio macroeconómico 2014 y perspectivas 2015. Benchmark, p. 1-61. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview/industryreport?sector_id=99990100&pc=CO&sv=BC K
dc.identifier.citationEMIS (2017a). Benchmark. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview?sector_id=99990100&sv=BCK&pc=CO
dc.identifier.citationEMIS (2017b). Benchmark. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview?sector_id=999906&sv=BCK&pc=CO
dc.identifier.citationEMIS (2017c). Benchmark. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview/rankingssector?sector_id=99990102&grupo_id=1&ag g=SUM&pc=CO&sv=BCK
dc.identifier.citationEMIS (2017d). Benchmark. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview/rankingssector?sector_id=9999015&grupo_id=1&agg =SUM&pc=CO&sv=BCK
dc.identifier.citationEMIS (2017e). Benchmark. Recuperado de https://bck-emiscom.ez.unisabana.edu.co/mainview?sector_id=999907&sv=BCK&pc=CO
dc.identifier.citationEsper, T., Williams, L. (2003). The value of collaborative transportation management (CTM): its relationship to CPFR and information technology. Transportation Journal, Vol. 42(4), p. 55- 65
dc.identifier.citationFan, W., Yang, T. (2014). Information management strategies and supply chain performance under demand disruptions. International Journal of Production Research, Vol. 54(1), p. 1-14. doi: 10.1080/00207543.2014.991456.
dc.identifier.citationFiorito, S., May, E., Straughn, K. (1995). Quick response in retailing: components and implementation. International Journal of Retail & Distribution Management, Vol. 23(5), p. 12-21. Doi: 10.1108/09590559510147127
dc.identifier.citationFliedner, G. (2003). CPFR: an emerging supply chain tool. Industrial Management & Data Systems, Vol. 103(1), p. 14-21. doi: 10.1108/02635570310456850
dc.identifier.citationFolinas, D., Rabi, S. (2011). Estimating benefits of demand sensing for consumer goods organisations. Database Marketing & Customer Strategy Management, Vol. 19(4), p. 245- 261. doi: 10.1057/dbm.2012.22.
dc.identifier.citationGalberth, M., Kurtulus, M. & Shor, M. (2015). How collaborative forecasting can reduce forecast accuracy. Operations Research Letters, Vol. 43(4), p. 349-353. doi: 10.1016/j.orl.2015.04.006.
dc.identifier.citationGunasekaran, A., Ramanathan, U. (2014). Supply chain collaboration impact of success in long term partnerships. International Journal Production Economics, Vol. 147(part b), p. 252- 259. doi: 10.1016/j.ijpe.2012.06.002.
dc.identifier.citationHead, M., McLaren, T., Yuan, Y. (2002). Supply chain collaboration alternatives: understanding the expected costs and benefits. Internet Research: Electonic Networking Applications and Policy, Vol. 12(4), p. 348-364. doi: 10.1108/10662240210438416
dc.identifier.citationHoffman, J., Mehra, S. (2000). Efficient consumer response as a supply chain strategy for grocery businesses. International Journal of Service Industry Management, Vol. 11(4), p. 365-373
dc.identifier.citationHollmann, R., Scarvarda, L., Tavares, A. (2014). Collaborative planning, forecasting and replenishment: a literature review. International Journal of Productivity and Performance Management, Vol. 64(7), p. 971-993. doi: 10.1108/IJPPM-03-2014-0039.
dc.identifier.citationHow to Create SMART Goals Using a Tree Diagram, (2014). Journal of Staff Development, vol. 35(6), 54-57. Recuperado de https://search-proquestcom.ez.unisabana.edu.co/docview/1628379486?accountid=45375
dc.identifier.citationHundunkar, M., Jakhar, S., Rathod, U. (2014). Factors affecting collaboration in supply chain: a literature review. Procedia - Social and Behavioral Sciences, Vol. 133, p. 189-202. doi: 10.1016/j.sbspro.2014.04.184. Recuperado de http://ac.elscdn.com/S1877042814030948/1-s2.0-S1877042814030948-main.pdf?_tid=663ebd68- 5380-11e7-acf0- 00000aab0f02&acdnat=1497719839_0382e593414762e2ec42bbf270e63204
dc.identifier.citationJones, D., Womack, J. (Ed. 2) (2011). Seeing the whole value stream. Cambridge, Estados Unidos: Lean Enterprise Institute
dc.identifier.citationKubde, R. (2012). Collaborative planning, forecasting and replenishment: determinants of joint action in buyer-supplier relationships. Research Journal of Business Management, Vol. 6(1), p. 12-18. doi: 10.3923/rjbm.2012.12.18
dc.identifier.citationIreland, R. (2005). ABC of collaborative planning, forecasting and replenishment. The Journal of Business Forecasting, Vol. 24(2), p. 3-4.
dc.identifier.citationIreland, R., Crum, C. (2005). Supply chain collaboration: how to implement CPFR and other best collaborative practices. Florida, Estados Unidos: J. Ross.
dc.identifier.citationLee, H., Padmanabhan, V., Whang, S. (1997). Information distortion in a supply Chain: the bullwhip effect. Management Science, Vol. 43(4), p. 546-558.
dc.identifier.citationMarketline (2016a). Company profile: Whirlpool Corporation. Marketline. Recuperado de http://web.a.ebscohost.com.ez.unisabana.edu.co/ehost/pdfviewer/pdfviewer?vid=3&sid=fb 32c65a-7d91-4172-b8dc-96af52cc929d%40sessionmgr4006&hid=4101.
dc.identifier.citationMarketline (2016b). Company profile: Motorola Solutions. Marketline. Recuperado de http://web.a.ebscohost.com.ez.unisabana.edu.co/ehost/pdfviewer/pdfviewer?vid=16&sid=d 12a5aff-0fa6-490e-a290-e4105ecf7757%40sessionmgr4010&hid=4112.
dc.identifier.citationMcCullen, P., Towill, D. (1999). The impact of an agile manufacturing on supply chain dynamics. International Journal of Logistics Management, Vol. 10(1), p. 83-96. doi: 10.1108/09574099910805879
dc.identifier.citationMacLeod, L. (2012). Making smart goals smarter. Physician Executive, Vol. 38(2). P. 68-70.
dc.identifier.citationMontoya-Torres, J., Vargas, D. (2014). Collaboration and information sharing in dyadic supply chains: a literature review over the period 2000 – 2012. Estudios Gerenciales, Vol. 30(103), p. 343-354. doi: 10.1016/j.estger.2014.05.006
dc.identifier.citationPeterson, R., Pyke, D., Silver, E. (Ed. 3) (1998). Inventory Management and Production Planning and Scheduling. New York, Estados Unidos: John Wiley & Sons
dc.identifier.citationRaghunathan, S. (1999). Interorganizational collaborative forecasting and replenishment systems and supply chain implications. Decision Sciences, Vol. 30(4), p. 1053-1071.
dc.identifier.citationRyu, C. (2014). Review of Collaborative Planning, Forecasting, and Replenishment as a Supply Chain Collaboration Program. Journal of Distribution Science, Vol. 12(3), p. 85-98. doi: 10.13106/jds.2014.
dc.identifier.citationSIC (2017a). Superintendencia de Industria y Comercio. Prácticas restrictivas de la competencia. Recuperado de http://www.sic.gov.co/practicas-restrictivas-de-la-competencia
dc.identifier.citationSIC (2017b). Superintendencia de Industria y Comercio. Competencia desleal. Recuperado de http://www.sic.gov.co/los-actos-de-competencia-desleal
dc.identifier.citationSimatupang, T., Sridharan, R. (2002). The collaborative supply chain: a scheme for information sharing and incentive alignment. International Journal of Logistics Management, Vol. 13(1), p. 15-30. doi: 10.1108/09574090210806333.
dc.identifier.citationSimatupang, T., Sridharan, R. (2005). An integrative framework for supply chain collaboration. The International Journal of Logistics Management, Vol. 16(2), p. 257-274. doi: 10.1108/09574090510634548
dc.identifier.citationSimatupang, T., Sridharan, R. (2008). Design for supply chain collaboration. Business Process Management Journal, Vol. 14(3), p. 401-418. doi: 10.1108/14637150810876698.
dc.identifier.citationSimatupang, T., Sridharan, R. (2013). Power and trust in supply chain collaboration. International Journal of Value Chain Management, Vol. 7(1), p. 76-96. doi: 10.1504/IJVCM.2013.057344
dc.identifier.citationTranschel, S., Ullrich, K., Wagner S. (2014). The game plan for aligning the organization. Business Horizons, Vol. 57(2), p. 189-201. Doi: 10.1016/j.bushor.2013.11.002.
dc.identifier.citationVargas, D. (2012). Programación de la producción bajo un ambiente de colaboración en la cadena de suministro (Tesis de Maestría). Universidad de la Sabana, Bogotá.
dc.identifier.citationVlčkvá, V. (2008). Demand forecasting in CPFR. Economics and Management, Vol. 13, p. 336-342
dc.identifier.citationVICS (2004). Voluntary Interindustry Commerce Standards. Collaborative planning, forecasting and replenishment (CPFR). Recuperado de https://www.gs1us.org/DesktopModules/Bring2mind/DMX/Download.aspx?command=co re_download&entryid=492&language=en-US&PortalId=0&TabId=134
dc.identifier.citationVICS (2007). Voluntary Interindustry Commerce Standards. Implementing successful large scale CPFR programs & onboarding trading parterns bussines process guide. Recuperado de https://www.gs1us.org/DesktopModules/Bring2mind/DMX/Download.aspx?command=co re_download&entryid=491&language=en-US&PortalId=0&TabId=134
dc.identifier.citationVICS (2010). Voluntary Interindustry Commerce Standards. Linking CPFR and S&OP: a roadmap to integrated business planning. Recuperado de https://www.gs1us.org/DesktopModules/Bring2mind/DMX/Download.aspx?command=co re_download&entryid=433&language=en-US&PortalId=0&TabId=134
dc.identifier.citation
dc.identifier.urihttp://hdl.handle.net/10818/34516
dc.description128 páginases_CO
dc.description.abstractEn la actualidad y debido a la libre competencia en el mercado de bienes y servicios, las exigencias de los consumidores en cuanto a velocidad de respuesta, calidad, innovación y servicio postventa, va en aumento. En consecuencia, las empresas se ven en la necesidad de optimizar los procesos a lo largo de la cadena de suministro. El término “planeación colaborativa de pronósticos de demanda y reabastecimiento” hace referencia a uno de los modelos más completos en cuanto a la unión de esfuerzos, tácticas, y estrategias a lo largo y ancho de todos los actores de la cadena de suministro; en aras de mejorar la eficiencia y rapidez, construyendo fuertes lazos comerciales entre los participantes. El presente proyecto de investigación tiene por objetivo general, la exploración de los diferentes modelos de implementación de la planeación colaborativa de pronósticos de demanda y reabastecimiento (CPFR), con el propósito de plantear una alternativa que se ajuste al contexto y las condiciones de una empresa perteneciente a una cadena de suministro del sector de alimentos de consumo masivo en el mercado colombiano.es_CO
dc.formatapplication/pdfes_CO
dc.language.isospaes_CO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceUniversidad de La Sabana
dc.sourceIntellectum Repositorio Universidad de La Sabana
dc.subjectAdministración de la producciónes_CO
dc.subjectCadena de suministroses_CO
dc.subjectPlanificación estratégicaes_CO
dc.subjectCanales de comercializaciónes_CO
dc.titlePlaneación colaborativa de pronósticos de demanda y reabastecimiento en una empresa del sector de alimentos procesados de consumo masivoes_CO
dc.typemasterThesises_CO
dc.publisher.programMaestría en Gerencia de Operacioneses_CO
dc.publisher.departmentEscuela Internacional de Ciencias Económicas y Administrativases_CO
dc.identifier.local270077
dc.identifier.localTE09916
dc.type.hasVersionpublishedVersiones_CO
dc.rights.accessRightsrestrictedAccesses_CO
dc.creator.degreeMagíster en Gerencia de Operacioneses_CO


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