潜在Dirichlet分配
顾客满意度
独创性
前因(行为心理学)
营销
广告
价值(数学)
业务
旅游
客户体验
突出
质量(理念)
心理学
主题模型
计算机科学
地理
人工智能
社会心理学
哲学
考古
机器学习
认识论
创造力
作者
Semra Aktaş-Polat,Serkan Polat
标识
DOI:10.1108/bfj-02-2021-0138
摘要
Purpose The purpose of this study is to discover the factors affecting customer delight, satisfaction and dissatisfaction in fine dining experiences (FDEs). Design/methodology/approach Online user generated 2,585 reviews on TripAdvisor for 46 five-star hotel restaurants operating in Istanbul were analyzed with the latent Dirichlet allocation (LDA) algorithm. Findings LDA created nine, eight and seven topics for delight, satisfaction and dissatisfaction, respectively. The most salient topics for customer delight, satisfaction and dissatisfaction in FDEs are staff (17.3%), view (19%), and food quality (23%), respectively. Originality/value This study is one of the few studies investigating customer delight and satisfaction together. The study shows that FDEs can be analyzed with text mining techniques. Moreover, the study contributes to the literature on customer delight by adding staff topic as an antecedent.
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