Identifying hotel competitiveness based on hotel feature ratings

ABSTRACT

Identification of hotel competitiveness is crucial for hotel managers in developing effective marketing strategies and promoting their business. A common practice in representing hotel competitiveness is to advertise hotel features with high customer ratings as selling points. However, this approach is ineffective to clearly distinguish top-tier hotels with similar high ratings, while low-tier hotels are disadvantaged because of their low ratings. This study presents a new approach for hotel competitiveness evaluation by identifying the unique aspects that combine multiple features. The proposed approach could distinguish a hotel from its counterparts, rather than rely solely on the high ratings of hotel features. We introduce a data mining technique to automatically discover the distinct aspects of a hotel based on the ratings of hotel features. The proposed method is beneficial to researchers and hotel managers in evaluating hotel competitiveness and identifying critical features that need improvement to considerably attract potential customers.

摘要

饭店竞争力的识别对于饭店管理者制定有效的营销策略和促进其业务发展至关重要。代表酒店竞争力的一个普遍做法是以高顾客满意度为卖点宣传酒店特色。然而，这种方法显然无法区分具有类似高收视率的顶级酒店，而低层酒店由于其低收视率而处于不利地位。本研究提出了一种新的方法，通过识别独特的方面，结合多种特征的酒店竞争力评价。所提出的方法可以区分酒店与其同行，而不是仅仅依靠酒店的高评级。我们介绍了一种数据挖掘技术，自动发现酒店的不同方面的评级酒店的特点。所提出的方法有助于研究人员和酒店管理者在评估酒店竞争力和识别需要改进的关键特征，以吸引潜在客户。

KEYWORDS:

• Hotel competitiveness
• hotel reviews
• feature ratings
• kernel destiny estimation
• data mining

Acknowledgments

The work described in this paper was supported by a research grant funded by the Hong Kong Polytechnic University.

Additional information

Funding

This work was supported by the The work described in this paper was supported by a research grant funded by the Hong Kong Polytechnic University.