Volume 201

With the continuous development of China.com" she Ritz-Carlton Hotel Nanjing Based on UGC Reviews important in the national economy, with the hotel industry facing fierce competition. Customer perceived service quality has gradually become a core factor in measuring the comprehensive competitiveness of high-end hotels. This study takes The Ritz-Carlton Nanjing as a case, collecting user-generated content (UGC) from major tourism platforms, and applies text mining techniques to systematically analyze customer’s seasoning the comprehensive competitiveness of high-end hotels. This study takes The Ritz-Carlton Nanjing as a case, collecting user-generated content (UGC) from major tourism platforms, and applies text mining techniques to systematically analyze custonse. Based on word frequency analysis, sentiment analysis, and topic identification, this paper constructs a UGC-based service quality perception framework and proposes practical improvement suggestions, including enhancing staff service awareness, optimizing cleaning procedures, and improving dining services. The research enriches theoretical studies on high-end hotel service quality in the Chinese context and provides data-driven insights for managerial practice. It also discusses the application prospects of UGC in service quality evaluation and suggests future research directions.

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In the context of rapid advancements in the field of intelligent economy, there is an increasing demand for community distribution. This study is firmly rooted in the paradigm of an intelligent economy. Its objective is clear: to explore the contemporary challenges associated with optimising community distribution strategies. This investigation is being conducted in the context of the rapid advancements witnessed in the field of e-commerce, which have resulted in the diversification of consumer demands. This is happening because of inefficiency and high costs in community distribution. The intelligent economic background creates an opportunity for community distribution. This involves analysing the current situation and problems of community distribution, analysing the application of intelligent logistics technology in community distribution, proposing optimisation strategies based on intelligent algorithms for distribution path optimisation, dynamic demand prediction, and customer service quality, and verifying the feasibility of the strategies through case studies. The findings show that using intelligent technology to optimise community distribution is the key to achieving efficient and high-quality results, ensuring both enhanced efficiency and elevated customer satisfaction.

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