Exploring dynamic customer requirement trend of buffet restaurant: a two-stage analysis from online reviews

Purpose Customer expectations and preferences may evolve as they experience more. This study aims to analyze the dynamics of customer requirements (CRs) as customer experience familiarity increases, offering insights for enhancing product-service quality. Design/methodology/approach This study categorizes dynamic requirements into two conversion stages: from new to repeat customers and from repeat to frequent customers. First, crawl online reviews (ORs) and determine each review’s conversion stage. Second, identify product-service attributes from reviews and conduct aspect-level sentiment analysis. Then, examine each attribute’s trend direction and magnitudes in the two stages. Finally, a dynamic-trend importance-performance analysis (DTIPA) model is developed to analyze the dynamic requirements and provide strategies for optimizing product services. Findings This study identifies eight attributes of buffet restaurants with varying requirement change trends. In particular, customer attention to “waiting time,” “variety of dishes,” “cost performance” and “taste” decreases in the first stage. In the second stage, “environment” and “freshness” increase differently from the first. Satisfaction with “cost performance” increases in the first stage but decreases in the perception of frequent customers. Improvement strategies are also provided based on these trends. Originality/value Research on dynamic requirement trends based on ORs and customer experience familiarity is scarce, particularly in the context of buffet restaurants. Moreover, existing methods have their limitations. This study proposes a novel approach for the progressive exploration and extraction of evolving CRs from ORs. By incorporating the trend direction and magnitude of attributes’ importance and satisfaction, DTIPA is developed to form strategies for optimizing buffet restaurant product services.

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Publication Details

Journal
British Food Journal
Published
2024-11-28
DOI
https://doi.org/10.1108/bfj-06-2024-0597
Citations
1
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
1.13
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article

Exploring dynamic customer requirement trend of buffet restaurant: a two-stage analysis from online reviews

Yanlai Li, Zifan Shen, Shouyang Wang, Cuiming Zhao
1 citations
British Food Journal
Digital Marketing and Social Media
1.13
article

Exploring dynamic customer requirement trend of buffet restaurant: a two-stage analysis from online reviews

Yanlai Li, Zifan Shen, Shouyang Wang, Cuiming Zhao
article en
1 citations

Abstract

Purpose Customer expectations and preferences may evolve as they experience more. This study aims to analyze the dynamics of customer requirements (CRs) as customer experience familiarity increases, offering insights for enhancing product-service quality. Design/methodology/approach This study categorizes dynamic requirements into two conversion stages: from new to repeat customers and from repeat to frequent customers. First, crawl online reviews (ORs) and determine each review’s conversion stage. Second, identify product-service attributes from reviews and conduct aspect-level sentiment analysis. Then, examine each attribute’s trend direction and magnitudes in the two stages. Finally, a dynamic-trend importance-performance analysis (DTIPA) model is developed to analyze the dynamic requirements and provide strategies for optimizing product services. Findings This study identifies eight attributes of buffet restaurants with varying requirement change trends. In particular, customer attention to “waiting time,” “variety of dishes,” “cost performance” and “taste” decreases in the first stage. In the second stage, “environment” and “freshness” increase differently from the first. Satisfaction with “cost performance” increases in the first stage but decreases in the perception of frequent customers. Improvement strategies are also provided based on these trends. Originality/value Research on dynamic requirement trends based on ORs and customer experience familiarity is scarce, particularly in the context of buffet restaurants. Moreover, existing methods have their limitations. This study proposes a novel approach for the progressive exploration and extraction of evolving CRs from ORs. By incorporating the trend direction and magnitude of attributes’ importance and satisfaction, DTIPA is developed to form strategies for optimizing buffet restaurant product services.

British Food JournalVol. 127(2)
Liaoning University (CN), Chinese Academy of Sciences (CN), Academy of Mathematics and Systems Science (CN)
Openalex Percentile: Top 15%
Digital Marketing and Social Media
1.13
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