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

Yanlai Li,

Shouyang Wang

et al.

British Food Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

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

Language: Английский

Product design improvement method driven by online product reviews DOI Creative Commons
Fangmin Cheng, Jing Wang, Chen Chen

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 25, 2025

Customer-centered design plays a crucial role in achieving sustainable by aligning product features with actual customer needs, promoting resource efficiency, and supporting environmental protection. To better meet expectations enhance satisfaction, improvement method driven online reviews is proposed. By leveraging the unique characteristics of reviews, opinions are systematically integrated into process, specific integration methods developed for each stage. Using target competitive products as inputs, progresses through five stages: review collection attribute extraction, problem identification product, analysis case knowledge base construction, structural solution generation, scheme decision-making. This results plan that addresses both needs enterprise goals. The feasibility this approach was demonstrated study involving 3D printer task.

Language: Английский

Citations

0
Fusion of KANO theory and Attention-BiLSTM models for user demand analysis and trend prediction DOI
Jinghua Zhao,

Yajie Huang,

Juan Feng

et al.

Information Fusion, Journal Year: 2025, Volume and Issue: unknown, P. 103210 - 103210

Published: April 1, 2025

Language: Английский

Citations

0
How to promote sustainable consumption and development of NEV? Decoding complex interrelationships in consumer requirements and design practice DOI
Zeng Wang,

Shi-fan Niu,

Shijie Hu

et al.

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: unknown, P. 144524 - 144524

Published: Dec. 1, 2024

Language: Английский

Citations

2
Exploring dynamic customer requirement trend of buffet restaurant: a two-stage analysis from online reviews DOI
Zifan Shen,

Yanlai Li,

Shouyang Wang

et al.

British Food Journal, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 28, 2024

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

Language: Английский

Citations

0