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基于大数据分析的酒店在线销量关键影响因素研究

Study on the Key Influencing Factors of Hotel Online Sales Based on Big Data Analysis

【作者】 周丽华;

【导师】 叶飞;

【作者基本信息】 华南理工大学 , 管理科学与工程, 2020, 硕士

【摘要】 随着移动互联网的普及,旅游行业的在线化进程不断推进,电商环境下汇集了丰富的酒店信息,也带来了不同的消费者行为,如在线评分成为购物的重要参考。另一方面,消费者在购买过程中,往往会货比三家,除了产品自身表现,竞品信息同样会对消费者的选择造成影响。此外,无论是前期的选址还是后续的设施服务提供,酒店往往会考虑多方面的因素,但选择的位置特征与设施不一定都是有效的。因此,研究评分、折扣等关键信息如何影响酒店在线销量,并进一步识别不同维度评分的重要性,以及提高消费者满意度的位置与设施特征是有必要的。本文基于大数据分析方法,利用web爬虫程序收集了Agoda网站上的2392家酒店及其竞争者的数据,首先检验了评分、折扣、价格等关键因素对酒店在线销量的影响,以及各因素的重要程度。而由于虚假评分和折扣的兴起,过高的评分和折扣可能会引发消费者的质疑,因此本文也检验了在线评分和折扣对酒店在线销量的非线性影响,并分析了酒店星级带来的差异和竞争酒店的在线评分和折扣的调节作用。其次,本文进一步分析了清洁、位置等各方面评分对酒店在线销量的影响,并利用支持向量机、决策树等方法识别了影响消费者在设施及位置满意度的关键特征。研究发现,酒店星级、客房数量、所在城市经济水平均对酒店在线销量呈正面影响,价格则负向相关,而在线评分和折扣对在线销量均呈现倒u型的影响。也就是说,随着在线评分和折扣的增加,在线销量并不总是随之增长,当其超过某一阈值时,在线销量反而下降。其中高评分对经济型酒店的销售增长更有利,而豪华型酒店的折扣更能吸引消费者。而竞品的在线评分的增加,会缩短焦点酒店的评分与其销量的正相关区间,带来消极作用,同时也增强了焦点酒店评分过高对销量的负面影响;竞品的折扣仅对前期焦点酒店的折扣与在线销量的关系带来负面作用。进一步分析发现,位置对酒店销量增长十分重要,即使其它各方面评分较低,好的位置仍能促进销量增长,但位置不佳时,通过提高其它方面客户的满意度对酒店销量增长同样行之有效。最后,本文识别了提高消费者满意度的关键设施与位置特征。本文研究结果丰富了现有的在线评论和消费者行为方面的研究,同时对酒店管理者具备重要价值,不仅可以为竞争环境下的商家制定营销策略促进营业收入增长提供参考,也有利于帮助商家进行针对性的改进,节约成本。

【Abstract】 With the popularity of the mobile Internet,e-commerce has shown unprecedented potential,reshaping trade mechanisms in many industries.In the tourism industry,the consumption upgrade has increased the travel demand of residents,which has also promoted the vigorous development of the accommodation market.The e-commerce platform gathers various hotel information,which also brings different consumer behaviors.For example,online rating has become an important reference when people make purchase decision.On the other hand,consumers tend to shop around during the purchase process.In addition to the information of the products themselves,competing products will also affects consumers’ choice.The consumption behavior of different star hotels may also be different.In addition,many factors will be considered when the hotel choose location to site and facilities to provided,but not all the characteristics will be necessarily effective.Therefore,it is necessary to study how ratings,discounts and other information affect hotel online sales,and further identify the importance of ratings in different dimensions,as well as the effective facilities and location features to improve customer satisfaction.In this paper,based data of 2392 hotels and their competitor set in Agoda website and the big data analysis method,firstly,we examine the influence of factors such as online rating,discount and price on the hotel online sales and the importance of factors.Due to the rise of fake online ratings and discounts,excessive ratings and discounts may lead to consumers’ doubts.Therefore,this paper also examines the non-linear impact of online ratings and discounts,and analyzes the differences between different hotel stars and the moderate effect of competitive hotel’s online ratings and discounts.Secondly,we analyzes the impact of cleanliness,location and other aspects of ratings on the hotel’s online sales,and use support vector machine,decision tree and other methods to identify the important facilities and location features.Our study shows that the hotel star rating,number of rooms,and the city’s economic level will be positive to the online sales of hotels,while the price was negatively correlated,and both online ratings and discounts have an inverted U-shaped effect on online sales.Interestingly,with the increasing of online ratings and discounts,the online sales cannot always see an increase,and conversely incur a decrease due to their less credibility.What’s more,the increase of online ratings of competitive products will shorten the positive correlation interval between focus product’s online ratings and its sales,and enhance the negative impact of high ratings.Competitor’s discounts will only bring negative effect on the relationship between the discounts of focus hotels and online sales in the early stage.Specifically,high online ratings are more conducive to the sales growth of budget hotels,while high online discount are more effective to luxury hotels.Furthermore,the location is key factor to hotel online sales,even if the other aspects of the evaluation is low,excellent location still promote the sales growth;and when the location is bad,high satisfaction of other aspects can also be conducive.Finally,this paper identifies the important facilities and location features that can improve customer satisfaction.The findings contribute to the existing online reviews and consumer behavior knowledge in hotel industry and can be valuable to hotel managers,not only provide reference for the making better marketing strategies to promote sales in the competitive environment,but also help in making targeted improvements to save costs.

【关键词】 在线销量; 影响因素; 酒店; 大数据分析;
【Key words】 online sales; influence factors; hotel; big data;
  • 【分类号】F724.6;F719.2
  • 【被引频次】1
  • 【下载频次】624
  • 攻读期成果
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