政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/136442

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/136442

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政大典藏 > College of Commerce > International MBA > Theses > Item 140.119/136442

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/136442

Title:	供應鏈管理中的大數據應用：瓜地馬拉製藥公司的案例研究 Big data use in Supply Chain Management: An understanding of the pharmaceutical companies in Guatemala
Authors:	茉莉 Fuentes, Alexa Yasmine Folgar
Contributors:	劉秀明 Liu, Sandra 茉莉 Alexa Yasmine Folgar Fuentes
Keywords:	供應鏈管理大數據分析製藥公司瓜地馬拉調查分析 Supply Chain Management Big Data Analytics Pharmaceutical Companies Guatemala Survey Analysis
Date:	2021
Issue Date:	2021-08-04 15:07:02 (UTC+8)
Abstract:	Big Data Analytics can generate great value in many ways, especially to pharmaceutical companies who strive to maintain supply chain efficiency by integrating and establishing visibility and complexity of all their available data. This case study aims to analyze the Big Data usage in the supply chain management in pharmaceutical companies in Guatemala. A 30-question survey instrument was sent to professionals in the area; receiving 230 completed surveys from a total of 19 companies. The survey included the analytics for enablement, effectiveness, and earnings of the supply chain management. It was found that pharmaceutical companies in Guatemala are actively working on the enablement and effectiveness areas regarding the Big Data in Supply Chain Management, while they still need to work and focus on the earnings, specifically on the total cost to serve. It is recommended to replicate this survey in other countries of the area to determine the perception of each country regarding Big Data Analytics.
Reference:	References 1. Flood, D.; Mathieu, I.; Chary, A.; García, P. et al. 2017. Perceptions and utilization of generic medicines in Guatemala: a mixed-methods study with physicians and pharmacy staff. BMC Health Services Research. 17, 27. https://doi.org/10.1186/s12913-017-1991-z 2. Vides, A. 2020. Guatemala principal proveedor de productos farmacéuticos en Centroamérica. AGEXPORT.https://agexporthoy.export.com.gt/sectores-de-exportacion/sector-manufacturas/guatemala-principal-proveedor-de-productos-farmaceuticos-en-centroamerica/ 3. Cealsa. 2020. Desafíos logísticos en la industria farmacéutica y cómo podemos ayudarte. Cealsa blog. https://cealsa.com.gt/blog/desafios-logisticos-en-la-industria-farmaceutica-y-como-podemos-ayudarte/ 4. Onciouiu, I.; Bunget, O.; Turkes, M. et al. 2019. The impact of Big Data Analytics on Company Performance in Supply Chain Management. Sustainability. 11, 4864 5. Addo-Tenkorang, R.; Helo, P. 2016. Big Data applications in operations/ supply-chain management: A literature review. Elsevier. Computers & Industrial Engineering 101, 528-543 6. McGrail, S. 2020. Fundamentals of the Pharmaceutical Supply Chain. Pharma News Intelligence. https://pharmanewsintel.com/news/fundamentals-of-the-pharmaceutical-supply-chain 7. Snapp, J.; Rangarajan, S. 2015. Supply Chain Analytics: Pharma’s Next Big Bet. Pharmaceutical Executive. https://www.pharmexec.com/view/supply-chain-analytics-pharma-s-next-big-bet 8. Comunicado del Ministerio de Economía (Mineco). 2015. Clasificación como MiPYMe en Guatemala. CentralAmericaData.com. https://www.centralamericadata.com/es/article/home/Clasificacin_como_MiPYMe_en_Guatemala 9. 2018. Supply Chain Integrity. Supply Chain Visibility is a key part of delivering proof of product integrity. 14th. Annual Temperature Controlled Logistics Europe. Pharma Supply Chain 360. https://www.iqpc.com/media/8927/30913.pdf 10. UKEssays. 2018. Procurement Strategy in the Pharmaceutical Industry. Retrieved from https://www.ukessays.com/essays/commerce/procurement-strategy-in-pharmaceutical-industry.php?vref=1 11. Berg, N. 2012. Today´s Pharma: Big Challenges, Big Expectations. Pharma Manufacturing. https://www.pharmamanufacturing.com/articles/2012/084/#:~:text=The%20challenges%20facing%20pharmaceutical%20manufacturing,constantly%20adapt%20their%20business%20models 12. Fersht, P.; Joshi, R. 2011. HFS Analytics Market Landscape. www.hfsresearch.com. 13. Merkuryeva, G.; Valberga, A.; Smirnov, A. 2019. Demand Forecasting in pharmaceutical supply chains: A case study. ICTE in Transportation and Logistics. Procedia Computer Science 149 (2019) 3-10
Description:	碩士國立政治大學國際經營管理英語碩士學位學程(IMBA) 108933059
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0108933059
Data Type:	thesis
DOI:	10.6814/NCCU202100679
Appears in Collections:	[International MBA] Theses

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