การบูรณาการข้อมูลขนาดใหญ่ผ่านกระบวนการจัดการโซ่อุปทานเพื่อการขับเคลื่อนอุตสาหกรรมไมซ์สู่ความยั่งยืน
Integration of Big Data Through the Supply Chain Management Process for Driving MICE Industry towards Sustainability
Abstract
การบูรณาการความก้าวหน้าทางเทคโนโลยีโดยการนำข้อมูลขนาดใหญ่มาใช้ในพัฒนาการจัดการโซ่อุปทานในอุตสาหกรรมไมซ์ สำหรับอุตสาหกรรมไมซ์นั้นประกอบด้วยธุรกิจที่เกี่ยวข้องกับการจัดประชุมบริษัทข้ามชาติ การท่องเที่ยวเพื่อเป็นรางวัลการประชุมนานาชาติ และการจัดนิทรรศการ ทั้งนี้ธุรกิจในกลุ่มดังกล่าวต้องสร้างกระบวนการไหลของข้อมูลในทุกกิจกรรมภายใต้โซ่อุปทาน ดังนั้น ผู้ประกอบการอุตสาหกรรมไมซ์แต่ละรายต้องมีความเข้าใจในการนำกลยุทธ์ วิธีการ แนวปฏิบัติ หรือทฤษฎี มาประยุกต์ใช้จากหน่วยหนึ่งไปยังอีกหน่วยหนึ่งอย่างมีประสิทธิภาพเพื่อให้เกิดการขับเคลื่อนสู่ความยั่งยืน อีกทั้งเพื่อเป็นการสร้างความมั่นใจแก่ผู้จัดงานและผู้เข้าร่วมงานทั้งหลาย ผู้ประกอบการอุตสาหกรรมไมซ์จำเป็นต้องมีการประเมินศักยภาพและความพร้อมของตน และใส่ใจในทรัพยากรการจัดกิจกรรมไมซ์ โดยตลอดทั้งกระบวนการเกี่ยวข้องกับการคัดแยกและกลั่นกรองข้อมูลขนาดใหญ่ ส่งผลให้สถาปัตยกรรมด้านข้อมูลขนาดใหญ่ถูกออกแบบขึ้นเพื่อดึงข้อมูลจากปริมาณข้อมูลจำนวนมากที่มีความหลากหลายโดยอาศัยการประมวลผลที่ซับซ้อน ช่วยประหยัดค่าใช้จ่าย รวมทั้งส่วนจัดเก็บและขนส่งข้อมูลซึ่งปัจจุบันสามารถรองรับการทำงานระยะยาวได้นั้นยิ่งเสริมสร้างความยั่งยืนแก่อุตสาหกรรมไมซ์
This academic article presents an integration of technological advancements by using Big Data to improve supply chain management in the MICE industry. The MICE industry consists of global level businesses related to Meeting, Incentive Travel, Conventions and Exhibitions. In this regard, businesses in that group must create a data flow process for all activities in the supply chain. Each MICE operator must have an understanding on the application and implementation of strategies, methods, practices or theories from one unit to another which helps to drive sustainability and build industry confidence for the MICE organizers and participants. MICE operators need to evaluate their capabilities and readiness. They have to pay attention to resources for organizing MICE activities throughout the process, which involves the separation and screening of Big data. As a result, large data architectures are designed to extract data from a large amount of diverse data through complex processing. The procedure helps save data storage and transportation costs. Currently the aspect is able to support long-term work and enhance sustainability for the MICE industry.
Keywords
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DOI: 10.14416/j.kmutnb.2021.12.003
ISSN: 2985-2145
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