基于混合大数据分析模型的服务质量改进:以AYCE韩国烧烤餐厅为例

Teknik Pub Date : 2021-11-25 DOI:10.14710/teknik.v42i3.32949
R. Sukwadi, Williem Halim, Nguyen Thi Bich Thu
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引用次数: 0

摘要

烹饪行业每年都在不断发展。其中一种现象就是你能吃到的(AYCE)韩式烧烤餐厅。这将导致餐饮业的竞争日益激烈。本研究的目的是识别顾客需求,确定服务属性的优先级,并为AYCE韩式烧烤餐厅提供适当的建议。在Zomato评审的基础上,运用LDA方法进行大数据分析,确定客户需求。结果表明,10个顾客需求被识别为质量功能部署(QFD)的顾客声音(VOC)。层次分析法的结果表明,改进策略有5个优先级。对于韩式BBQ餐厅,适当的建议是建立分层控制系统和顾客满意度调查,实施先进先出和后进先出系统,检查原材料储存设备的状况,改进现有的服务sop,并提供定期的简报和培训。
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Quality Service Improvement using Hybrid Big Data Analytics Model: A Case of AYCE Korean BBQ Restaurant
The culinary industry continues to develop every year. One of the phenomena is all you can eat (AYCE) Korean BBQ restaurant. This will cause increasingly intense competition in the restaurant business. The aims of this study are to identify customer needs, to determine the priority of the service attributes, and to provide appropriate suggestions to AYCE Korean BBQ restaurant. The big data analysis using LDA method was applied to determine customer needs based on the Zomato review. The results showed that ten customer needs are identified as Voice of Customer (VOC) for HOQ of the Quality Function Deployment (QFD). The results of the AHP showed that 5 priorities of improvement strategies. The appropriate suggestions for Korean BBQ restaurant are to create a layered control system and customer satisfaction surveys, to implement FIFO and LIFO systems, to check the condition of raw material storage equipment, to improve existing service SOPs, and to provide periodic briefings and training.
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0.00%
发文量
8
审稿时长
12 weeks
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