Study On The Key Influencing Factors Of Hotel Online Sales Based On Big Data Analysis

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.