Research On The Factors Affecting Comsumer's Satisfaction With Residence Experience From The Perspective Of Sharing Economy

With the booming mobile Internet,the sharing economy is changing the way people's way of life.The residence industry can serve as a representative representative to understand the development trend of the sharing economy.In 2018,the transaction volume of China's homestay market was about 16.5 billion yuan,which is 1.37 times that of the previous year.The number of tourists staying in shared homestay was about 79.45 million.And consumers have booked from the previous hotel selection to the current hotel reservation.This transform in travel residence seems to be more fashionable and more in line with the current traveler's philosophy.The appearance of the hotel has changed the way traditional consumers travel,and the experience of the hotel affects the satisfaction of consumers and whether they choose to stay at the hotel again.The demand for human travel residence is constantly changing,but what services does the Airbnb in the shared economy have to meet the travel and accommodation needs of the public? From the perspective of the hosts,what kind of personalized service can provide the occupancy rate of their own listings;from the perspective of the sharing residence platform,what measures are taken to enable consumers to continue to use the platform;from the perspective of consumers,how can consumers quickly find a listing that meets their travel accommodation requirements...In response to the questions raised,the author studies the satisfaction of consumers' staying in the residen through questionnaire survey and comment mining& analysis.Two parts of the specific research contents:(1)Questionnaire data survey:Through the literature review and interviews,the main factors attracting consumers to stay in the homestay are extracted.Then,based on the previous literature basis and interview results,the questionnaire data is designed and collected,and the model is confirmed based on the expectation.Determine the factors affecting the satisfaction of consumers and the willingness to follow.Then,the influence satisfaction factor obtained by the above method is subjective attitude,which is difficult to measure.However,the author guesses whether data mining technology can be used to analyze these subjective factors to further subdivide to obtain more satisfactory satisfaction evaluation indicators.So,the author did the second part of the experiment.(2)Based on comment mining analysis: Crawl online users of existing Airbnb in Hangzhou to pre-process the collected data,then use TF-IDF algorithm to convert the online comment of crawled online frequency matrix,and then use none.Supervised learning:K-means algorithm clusters the comment texts,and visualizes the clustering results to mine the factors affecting consumer satisfaction and specific refinement indicators.The final result shows that among the many factors that affect consumers' satisfaction with the hotel's occupancy experience,the most influential is the quality of service,followed by social interaction,and the weakest is the uniqueness and perceived security.In general,for homeowners,the property maintains a high service quality(providing fruit,comfort,cleanliness,new facilities,full functionality)and social interaction with consumers(in a timely and effective way to solve consumer 'problem)is a key factor in attracting tourists.The hosts can also provide additional personalised services,such as pick-up and drop-off service,specialties or answering local attractions.At the same time,the hotel platform must also protect the safety of consumers,strengthen the audit of landlord and housing qualifications,and build a safe shared accommodation environment.At all,this not only requires improvement of the hotel platform,but also requires the landlord to increase its non-standardized services in a targeted manner,so that consumers can increase their satisfaction and generate willingness to stay again.This research has certain theoretical and practical significance.And the main theoretical significance is: Firstly,expand the expectation confirmation model in thecontext of shared economy,study the factors affecting consumer satisfaction and follow-up behavior;Secondly,use clustering algorithm to mine from unstructured data(online comments)The satisfaction factors affecting the consumers staying at the sharing residence,based on the results,suggest the operation of the platform.At the same time,the practical significance lies in: Firstly,sharing as an alternative to consumption,in this context,the sharing residence industry can be used as a representative representative to understand the development trend of the sharing economy,by understanding the consumer's consumption behavior in the residence.Then improve the construction of the hotel platform and improve the service level of the landlord;Secondly,during the research period,the Airbnb launched the “Airbnb Plus” program to build a set of consumer-friendly experience through the analysis of background data.Satisfaction service standards to screen out the “Airbnb Plus listing”,on the other hand,verify the actual value of the study;thirdly,hotel managers can also gain a deeper understanding of the success of the residence service model in the context of sharing economy experience and competitive advantage,and optimize their own operating strategies to create a brilliant tourism residence industry.