Reflections on the Accounting Treatment of Lessees in the New Lease Standard

The new lease standard no longer makes distinguishes between operating leases and financial leases for accounting treatment of lessees, and uniformly uses the “right-of-use model” to separately list an asset and a liability in the balance sheet. The accounting treatment has undergone a disruptive change in comparison with the past. This article intends to analyze the lessees' accounting requirements from the original lease standard and the new lease standard, and proposes problems, reflections and suggestions for lessee accounting treatment after implementing the new standard.

I. INTRODUCTION
A large number of leased assets around the world are undervalued, and financial information is extremely lacking in comparability. Investors and analysts often adjust their statements based on the disclosure information of off-balance sheet leases of enterprises in order to obtain true information about the company. However, most investors and analysts cannot adjust the statements accurately, which leads to a decrease in the comparability of the financial statements. The application of the right-of-use asset model reflects the financial status of the leased enterprise more accurately and effectively, and is also very beneficial to investors' decisions. On December 7, 2018, the Ministry of Finance issued the 2018 "New Lease Standards" (CAS 21), and subsequently, the Ministry of Finance issued the 2019 "Lease Guideline". The guideline laid the foundation for the implementation of the new standard through numerous detailed guidelines and examples. CAS 21 was formulated by China in the light of international lease criterion and combined with China's actual conditions. According to the main content and characteristics of IFRS16 officially released in January 2016, the main impacts and responses of IFRS16 are explained (Lu Qilin, 2017). It proposes the revised changes of the new international standards, and analyzes the impact since the promulgation and implementation, and proposes China's countermeasures (Zhou Long, Li Yaxing, 2016). Based on the literature on the issue of international leasing standards in recent years, this article is based on the 2018 "New Lease Standards" issued by the Ministry of Finance on December 7, 2018. By comparing and analyzing the accounting treatment of the new lease standard by the lessee, it is hoped to provide a reference for the effective application of the new lease standard in practice.

A. Specific requirements for the implementation of the new lease standard
The new lease standard has made major changes to the lessee's accounting treatment, lease definition, consolidation, etc., and has more specific and detailed disclosure of the lessor's accounting information, and users of the report can also obtain more useful information from it. The time when the Chinese and foreign listed companies implement the new leasing standards is different: the implementation time of overseas listed companies or Chinese and foreign simultaneous listed companies is January 1, 2019; the implementation time of other companies that implement corporate accounting standards is January 1, 2021; Enterprises whose subsidiary's overseas listing or parent company's overseas listing are prepared in accordance with international standards or corporate accounting standards can implement the new lease standard in advance, but the implementation time must be later than the date of the new "Financial Instruments Recognition and Measurement" standard and the new "Revenue" standard. How to implement and respond to the new leasing standards is an important issue that needs to be solved at present. The specific implementation time is shown in " Table I".   TABLE I.  IMPLEMENTATION TIME OF NEW LEASE STANDARDS AND RELATED REGULATIONS   Adapted company  Implementation time  Regulations  Overseas listed companies or Chinese and overseas  listed companies   January 1, 2019 The retrospective adjustment method is adopted, and the cumulative impacts are adjusted for retained earnings at the beginning of the year. Information for comparable periods doesn't need to adjust.
Other companies implementing corporate accounting standards January 1, 2021 Enterprises whose subsidiary's overseas listing or parent company's overseas listing are prepared in accordance with international standards or corporate accounting standards may implement the new lease standard in advance.
Later than the date of the new "Financial Instruments Recognition and Measurement" standard and the new "Revenue" standard. a. Source: December 7, 2018, Ministry of Finance issued "Accounting Standards for Business Enterprises No. 21 -Leasing".

A. Analysis of standard provisions
The original lease standard divided lease types into financing leases and operating leases. Under the financial lease method, the lessee will list the assets obtained from the financial lease as one asset and one liability in the balance sheet. Under the operating lease method, the lessee recognizes the lease fee paid as an expense, which is listed in the income statement, and the assets obtained from the lease are not recognized, resulting in an incomplete reflection of operating lease assets in the balance sheet, and the comparability of financial statements has also decreased.
The new lease standard no longer distinguishes leases into operating leases and financial leases, but instead recognizes them as a "right-of-use asset" and "lease liability", and depreciates the right-of-use asset in accordance with the fixed asset standard. In addition, the disclosure of the lessor's accounting information is more abundant, providing more useful accounting information.

B. Analysis of similarities and differences of the new and old standards for the lessee's accounting treatment
The original lease standard and the new lease standard have the same accounting treatment for lessees: the accounting treatments for financial lease lessees are basically the same. On the lease start date, the lessee recognizes the assets of the financial lease as a leased asset and related liabilities. The subsequent measurement model of the leased assets is the cost model. Depreciation of the leased assets is based on the fixed asset standard. At the same time, the leased assets are tested for impairment in accordance with the asset impairment standards, impairment losses are recognized, financial lease assets are listed in the balance sheet.
The differences between the original lease standard and the new lease standard for the lessee's accounting are: The original lease standard did not recognize an asset and a liability for assets leased under operating leases, and did not list it in the balance sheet. It only recognized lease expenses separately and disclosed information related to operating leases in the notes; The new lease standard no longer distinguishes between operating leases and financial leases for lessees. The lessee's accounting treatment of operating lease assets has been changed from a dual model to a single model, that is, the lessee recognizes an asset and related liabilities for the assets leased from the operating lease on the lease start date, uses the cost model to measure it in the subsequent measurement process, and depreciates the right-of-use asset in accordance with the fixed asset standards, while considering the lease and interest expenses incurred during the use process. According to the provisions of the asset impairment standards, the right-of-use assets are tested for impairment, and the impairment of assets that have been impaired is provided for losses.

III. LESSEE'S ACCOUNTING TREATMENT
The original lease standard only reflected the accounting information of the operating lease lessees off-balance sheet, and did not explicitly regulate the processing of contract changes after the lease and the revaluation of options. The handling of this in practice was not uniform and was controversial. The new standard requires the cost model to be used for subsequent measurement of right-of-use assets, to determine whether the right-of-use assets are impaired, and to depreciate and accrue expenses separately. The new lease standards clearly stipulate that the lessee should re-evaluate whether to purchase the right-of-use assets at maturity, whether to renew the lease at maturity, or to terminate the lease at maturity, and make corresponding accounting treatments. In addition, lease changes should be re-recognized as a lease liability or reflected separately as a lease. The subsequent measurement of the lessee is more complete in the new lease standard, and the accounting information Advances in Economics, Business and Management Research, volume 150 disclosure of the lessor and lessee is also more abundant and reliable. Based on the requirements and practices of the new lease standard, the author conducted a brief analysis.

A. Initial confirmation of the lessee
The new standard no longer distinguishes between operating leases and financial leases for lessees, and there is no need to judge the type of lease when accounting for lease operations. The lessee recognizes an asset and a related liability at the beginning of the lease. The specific accounting treatment is shown in " Table II".   TABLE II. INITIAL CONFIRMATION OF THE LESSEE Initial measurement Processing principle Accounting treatment Initial measurement of lease liabilities It uses the leased interest rate or incremental borrowing interest rate as the discount rate to calculate the present value of lease payments, and confirms the initial amount of a "leasing liability" Borrow: Right-of-use assets Lease liabilitiesunrecognized financing costs Loan: Lease liabilitieslease payment Bank deposit (initial direct costs) Estimated liabilitiesrecovery costs Initial measurement of right-of-use assets "Right-of-use asset" initial cost = initial measurement amount of lease liabilities -lease incentive + initial direct costs + recovery costs For example: A business enterprise is a general taxpayer. A real estate company signed a lease contract with the business enterprise on December 31, 2018. The contract stipulates the following relevant content: The lease will begin on December 31, 2018. One house (self-developed old project), the lease period is 5 years (starting and ending dates: December 31, 2018-December 31, 2023). On December 31, 2019, 2020, 2021, 2022, and 2023, the rent will be paid 500,000 yuan (excluding tax), a total of 2.5 million yuan (excluding tax) (Simple tax calculation for developed old projects, VAT rate of 5%). Assuming that the fair value of the house on December 31, 2019 is 1.68 million excluding tax and the interest rate stipulated in the house lease contract is 6% (annual interest rate), after the contract expires on December 31, 2023, the lessee will return the property to the lessor after paying the rent as agreed. Assumptions: The unrecognized financing expenses to be apportioned in the current period are recognized according to the actual interest rate method; the lease period of the house is 5 years, and the depreciation method of the right-of-use asset is the average life method; the transaction fee and transportation expenses paid by the commerce and trade enterprise during the signing of the contract shall be 10,000 yuan (no input tax deductible); at the end of the lease period, the business enterprise needs to restore the original appearance of the leased house. A business enterprise estimates that it will cost 20,000 yuan to restore the house after the five-year lease expires.
According to the analysis of the above data, the initial measurement amount of the lease liability = 50 × 4.2124 = 210.62 (4.2124 is the annuity present value coefficient with interest rate of 6% and the period of 5 years) Borrow: Right-of-use assets 213.62 Lease liabilitiesunrecognized financing costs 39.38 Loan: Lease liabilitieslease payments 250 Bank deposit (initial direct cost) 1 Estimated liabilitiesrecovery costs 2

B. Subsequent measurement of the lessee
The lessee's subsequent measurement adopts the cost model, and the depreciation and impairment test of the right-of-use asset are based on the fixed asset standard and the asset impairment standard, respectively. In addition, the lessee calculates the interest expenses that should be borne by each period of the lease based on a certain interest rate, which are included in the current profit and loss or related asset costs as required. The variable lease payment is not included in the lease liability in the new lease standard, but is included in the current profit and loss when it actually occurs. The specific accounting treatment is shown in " Table III". The lessee calculates the interest expenses that should be borne by each lease period based on a certain interest rate, and includes them in the current profit or loss or capitalization as required Borrowing: Financial costs / construction in progress, etc. Loan: Lease liabilitiesunrecognized financing expenses Depreciation of leased assets Depreciate the right-of-use assets with reference to fixed asset standards (The right-of-use asset is usually accrued from the month beginning the lease period. If it is difficult to accrue, depreciation may also be accrued from next month and disclosed in the notes) Borrow: Management expenses, etc. Loan: Accumulated depreciation of right-of-use assets Impairment of leased assets Perform impairment test on the right-of-use asset with reference to the asset impairment standard and perform corresponding accounting treatment Borrow: Asset impairment losses Loan: Provision for impairment of right-of-use assets

Variable lease payments
The variable lease payments that are not included in the measurement of lease liabilities shall be included in the current profit and loss when they actually occur.
Borrow: Management expenses, etc. Loan: Bank deposit For example, following the example above, on December 31, 2019, the business enterprise paid the rent of 525,000 yuan (including tax) for the current year; the leased assets are depreciated on a straight-line basis, and the depreciation period is 5 years. The rightof-use asset is usually accrued from the month of the lease period, and the business enterprise is depreciated over 5 years, with an annual depreciation amount = 213.62 ÷ 5 = 422,724 yuan. The allocation of unrecognized financing costs is shown in " Table IV" below.  After the right-of-use asset is accrued for impairment, it cannot be reversed. The lessee makes subsequent depreciation based on the book value of the right-of-use asset after depreciation. Therefore, the annual depreciation amount from 2020 to 2023 = (213.62-42.724-2.986) ÷ 4 = 420,000 yuan

C. Confirmation of lease termination
When the lease is terminated, the lessee should reevaluate: whether to purchase the right-of-use assets at maturity, whether to renew the lease at maturity, or to

Advances in Economics, Business and Management Research, volume 150
terminate the lease at maturity, and make corresponding accounting treatment, as shown in " Table V".   TABLE V. CONFIRMATION OF LEASE TERMINATION

Lease termination
Processing principle Accounting treatment Enterprise sublease use right assets to form a financial lease For example, following the example above, after the contract expires on December 31, 2023, the lessee pays the rent in accordance with the contract and the house ownership is returned to the lessor real estate company.

D. Disclosure of lessee information
The new lease standard clearly stipulates that the lessee should separately list an asset and a liability on the balance sheet. Lease liabilities are classified into long-term liabilities and long-term liabilities due within one year according to their nature, and right-of-use assets are classified into long-term assets and long-term assets due within one year according to their nature. The depreciation expense of the right-of-use asset and the interest on the lease liability are shown separately in the income statement. Paying the principal and interest of the lease liability in cash should be included in the cash flow statement of financing activities. The lease fees and variable lease payments for short-term leases and leases of low-value assets are cash outflows from operating activities. The information disclosure requirements of the new lease standards fully reflect the company's assets and liabilities, eliminate the opportunity for lessees to use operating leases for offbalance sheet financing, and improve the transparency and comparability of statements.

NEW LEASE STANDARDS FOR THE ACCOUNTING TREATMENT OF LESSEES
First, under the new leasing standards, the lease of investment real estate is not explicitly excluded from the scope of the lease standards. The new lease standard requires the subsequent measurement of leased assets to use the cost model. The author believes that the new lease standard applies to investment real estate leasing. If the lessee uses the fair value measurement model to measure investment real estate, the right-of-use assets that meet the definition of investment real estate can also be carried out using the fair value measurement model.
Second, under the new lease standard, there are special provisions for subleasing, that is, "the subleasor

Advances in Economics, Business and Management Research, volume 150
should be based on the right-of-use asset generated by the original lease, not the underlying asset of the original lease". According to the standards, the new lease standard no longer distinguishes the types of leases of lessees and adopts the right-of-use asset model uniformly. Therefore, the accounting treatment of subleases should also be based on the right-of-use assets recognized in the original lease. If the sub-lease is a finance lease, the original right-of-use asset should be derecognized and the profit or loss should be confirmed; if the sub-lease is an operating lease, the right-of-use asset should be reasonably depreciated during the sub-lease period, matching the rental income. At this time, the right-of-use asset for the same leasehold property will appear in the statements of the sub-lessor and lessee at the same time. The author believes that the reason for this situation is that the changes to the new standard are only for lessees, and for the lessors, it still needs to make distinguish between financial leases and operating leases.
Third, the impairment provisions for the right-ofuse assets in the new lease standard refer to the provisions of "Enterprise Accounting Standards No. 8 -Asset Impairment", and it needs to use similar methods to fixed assets to determine whether there are signs of impairment. In many cases, the right-of-use asset cannot generate cash inflow independently, especially if the leased asset is used for its own production and operation rather than sublease. The author believes that if the leased assets are merged into the asset group to which they belong, considering the signs of impairment and impairment testing as a whole, they can better reflect the effectiveness of the assets.
Forth, the new standard includes the lease fee paid in each period as the initial value of the right-of-use asset. In the case of variable lease costs, the new standard simplifies the treatment and does not include the initial value of the right-of-use asset. Similarly, as it in the original standard, it is included in the current lease expenses. This requirement caused the same nature of expenses to be artificially shown in the balance sheet and income statement. If most of the future price of a lease contract is variable, then the initial asset value only contains a small part of the total price in the contract, can it reasonably reflect the value of this lease behavior? Does the new lease standard work as it should? These issues need to be continuously improved by the new standard.

V. CONCLUSION
To sum up, the author briefly analyzes the accounting treatment of the lessee by the new lease standard, expounds the changes in the accounting confirmation and measurement of the lessee by the new lease standard, and analyzes the impact of changes in the new lease standards on the lessee's accounting confirmation and measurement through specific cases. Because the new lease standards were not promulgated for a long time, and Chinese listed companies have not yet implemented the new standards, the author's interpretation of the relevant provisions of the new lease standard and its application guide needs to be continuously improved. It is hoped that this article will help learners to deepen their understanding of the new lease standard and provide valuable reference for practitioners.


Research on Customer Satisfaction of Budget Hotels Based on Revised IPA and Online Reviews

Online reviews are the emotional expressions of customers after product or service experience. Compared with survey questionnaires, they can more truly reflect customers' perception of product or service. Therefore, combined with online reviews and importance-performance analysis (IPA), managers can make corresponding corporate strategic according to the priority of features. This research uses the Meituan.com hotel online reviews of budget hotels as an example. First, we uses natural language processing technology to preprocess online reviews, and uses K-means to build a feature lexicon. Second, based on the sentiment dictionary, we perform fine-grained sentiment analysis on “feature-view pairs” to obtain feature satisfaction scores. Third, combined with the revised IPA, we obtain implicitly derived importance, and then the priority of each feature improvement is determined. The conclusions show that (1) service, location, and price are the advantages of budget hotels. Managers should maintain a competitive advantage and ensure the supply of resources. (2) Catering and room facilities are the main disadvantages of budget hotels. Managers should improve these two features to improve customer satisfaction as soon as possible. This study implements the method of managing IPA through online reviews, which replaces the previous questionnaire method. At the same time, revised IPA provides more realistic and concrete reference for hotel managers when making decisions.

Introduction
With the rapid development and popularity of the Web 2.0 era, people are more inclined to post their ideas and interact on social platforms. Previous studies have shown that online reviews are an important form of social interaction [1], so online customer reviews (OCRs) become a major source of information for consumers and industry managers. Compared with the objective descriptions published by merchants, OCRs are derived from the emotional expression of consumers after the experience, so they are more trustworthy and persuasive, especially for experiential products. Hotels are one of the most typical experiential products, OCRs will have a significant impact on the consumer behavior of potential customers.
Marketing and economic theory [2] believe that products and services have multi-dimensional features, and consumers' preferences for each feature are different, so the degree of the emotional expression of each feature displayed in OCRs will be different.
Recognizing the importance of multi-dimensional features can be more accurately improved according to consumer needs. At present, most consumer satisfaction surveys are in the form of questionnaires. Some researches set a large number of items in the questionnaire to investigate the comprehensiveness and accuracy of the information, such as the classic service quality model (SERVQUAL) [3], and its theory is relatively strong, there are certain limitations in both the size of the data and the richness of the content. Summarizing the existing research, it is found that the researches on hotel satisfaction have been more in-depth, but most of them use questionnaires or directly use website numerical scores, and rarely analyze the text of OCRs. At present, the most widely used hotel satisfaction measurement model is importance-performance analysis (IPA), which was proposed by Martilla and James in 1977 [4], and has been widely used in many fields since then. IPA mainly determines the improvement strategy to achieve the optimal use of resources by comparing the satisfaction and importance values of each feature. Although IPA is widely used, it also has certain defects [5]. When mapping each feature to a matrix figure, it is required that the two coordinates, that is, importance and satisfaction are independent of each other. However, due to the similarity between importance and satisfaction, the interviewees could not distinguish the two well, so that the final quadrant distribution results were also biased. Based on the above problems, many scholars have revised the IPA analysis method. Deng has summarized the research results of other scholars and optimized the IPA analysis method statistically [6]. The revised model has achieved good results.
This research uses the reviews of Meituan.com to conduct research to explore consumer preferences and attention to hotel features. First, combined with natural language processing, machine learning and other methods, we process review texts. Second, we transform the crawled hotel reviews into word vectors through Word2Vec, and use the K-means method to cluster the word vectors. Third, the sentiment dictionary method is used to assign features to obtain features satisfaction. Finally, according to revised IPA to acquire importance, the hotel features are judged through the IPA matrix figure, so as to provide more accurate and reasonable suggestions to the hotel industry.

Features of Budget Hotels and Consumer Satisfaction
The features of the hotel are divided into many categories, such as intangible features and tangible features; practical features and experience features. The perception of hotel is the evaluation of the importance and satisfaction of all the features by consumers during the process of staying in the hotel. Callan and Bowman [7] conducted a survey of 38 features of the hotel. They found that the features that consumers consider important include employee service attitude, service efficiency, health environment, etc. At the same time, many respondents said that the experiential features are relative important. Rhee and Yang [8] researched the literature on hotel features and summarized the six categories that consumers are more concerned about. At the same time, many tourism websites also used these six categories of hotel features to gauge consumer evaluation. Consumers' perception of the importance and satisfaction of hotel features is uncertain. Some features may have high satisfaction but may not be very important to consumers. Some features are important but their existence and optimization do not improve satisfaction. The KANO model proposed by Kano [9] explains the above features. KANO model is classified according to the provision of product attribute and consumer satisfaction, it mainly includes: basic attributes, performance attributes, and excitement attributes, where the basic attributes and the excitement attributes are non-linearly related. Combining and summarizing the existing literature, we found that there are more domestic researches on the tourism market, but less research on the features of budget hotels. Although there are literature survey on domestic consumers' needs and satisfaction in hotels, they only studies specific features. Gao et al. [10] found that hotel location is an important feature that consumers will pay special attention to when making decisions. Shan et al. [11] researched the four features of hotel type and room size, etc. when portraying user portraits of online reviews for hotels. In general, the analysis of all features of budget hotels lacks systematic and in-depth research. Therefore, in the domestic hotel industry research, it is necessary to further explore consumer perceptions of budget hotel features.

Traditional IPA and Revised IPA
The IPA method uses the satisfaction and importance of features as a combination evaluation of various factors, and analyzes each factor based on the quadrant distribution in the matrix, thereby to find out the factors that need urgent improvement. The IPA method is relatively widely used at home and abroad. Wu [12] studied typical domestic budget hotels and found that the most important thing for consumers is still the hotel location. Kuo et al. [13] explored the factors affecting Hong Kong consumers' choice of hotel accommodation, and used IPA analysis to study 26 hotel service features, and found that the hotel's location, environment, catering and other aspects urgently need to be improved and optimized.
There are two necessary prerequisites for the use of IPA analysis. First, the two coordinate axes in the matrix diagram are required to be independent of each other; second, the relationship between the satisfaction of each feature and overall satisfaction must be linearly related and symmetrical. In reality, because of the similarity between importance and satisfaction, consumers cannot distinguish them well. Many scholars have revised and expanded the IPA analysis method. Deng summarized previous research and revised the problems existing in traditional IPA. He proposed to replace the self-reported importance with the implicitly derived importance, that is, to analyze the correlation logarithm of the satisfaction evaluation of each factor, and then conduct a partial correlation analysis of overall satisfaction and the satisfaction of each feature. The obtained partial correlation coefficient is used as the implicitly derived importance [6]. The partial correlation coefficient excludes the impact of other satisfaction variables on the correlation between the specified variable and the overall satisfaction, and can reflect the true situation of each feature [14].

Sentiment Analysis of Online Reviews
Sentiment analysis, also is known as opinion mining or comment extraction. It is an objective and subjective analysis of unstructured text data, and classifies an emotional polarity of the extracted subjective sentences. The purpose of sentiment analysis is to obtain praise or disapproval opinions on a certain commodity, and to provide a basis for decision-making [15]. Sentiment analysis is divided into coarse-grained sentiment analysis and fine-grained sentiment analysis. Coarse-grained sentiment analysis includes chapter-level and sentence-level sentiment analysis. Fine-grained sentiment analysis is based on the analysis of feature level. Medhat et al. [16] believe that the main steps in fine-grained analysis of online reviews are: emotion recognition, feature extraction, emotion classification, and emotion polarity recognition. Zhao [17] used the DBSCAN-based text clustering process to mine the hotel's reputation dimension. The results show that consumers are more concerned about the features include hardware, service, environment, diet and value. This research draws on the previous method based on sentiment dictionary, and calculates sentiment scores based on sentiment polarity and intensity to obtain satisfaction which are used to analyze the revised IPA.

K-means Features Clustering
K-means clustering is an unsupervised machine learning algorithm. Because of its simple principle, easy implementation, and good results, it is a more commonly used clustering method. It calculates the distance between objects and judges the similarity between them, and then classifies them. The main purpose of clustering is to divide the data set into K classes, so that the data within the class is smallest, and the inter-class clustering is the largest.
The main process of K-means clustering includes four steps. First, determining the number of clusters K, and then it can randomly select K initial points as the cluster centers. Second, calculating the distance between each point in the data set and K initial points, they can assign the points to the cluster center with the smallest distance. Third, after classifying all points in the data set, it should recalculate the cluster center. Finally, repeating second and third steps until the cluster center does not change, then it is considered that the optimal clustering has been reached.

Research Design
The overall research framework of this paper mainly includes text preprocessing, Word2Vec, K-means clustering, fine-grained sentiment analysis, and partial correlation analysis. The concrete process is shown in Figure 1. The stage1 main includes data processing and features extraction. The stage2 main obtain satisfaction and implicitly derived importance of features. In stage3, we construct the IPA figure to analysis the features of hotel and provide suggestions.

Data Sources
The representative brands of Chinese budget hotels including Home Inn, Hanting Inn and 7Days Inn, etc. Therefore, this study chooses 21 budget hotels from Qingdao including Home Inn, Hanting Inn and 7Days Inn, etc. By writing a Python program for the web crawler, a total of 35,398 online reviews were obtained, including text reviews, star scores, and review usefulness scores. Through clearing all data and deleting invalid reviews, this research finally gets 30,877 reviews.

Hotel Features Clustering Based on K-means
1. Online reviews are segmented form a Word2Vector corpus, and then we use the Word2Vec technology trains the segmented corpus (window = 10, vector = 300), finally, the words map to the K-dimensional vector space to form the corresponding word vector. 2. K-means algorithm is used clusters nouns in the dictionary. First we need to determine the number of clusters of K-means. There are two best clustering methods: the elbow method and the contour method. The core idea of the elbow method is that as the number of clusters increases, the sample segmentation will be more accurate, and the sum of the squared errors will gradually become smaller. When the number of true clusters is reached, the degree of aggregation obtained by increasing the number of clusters will rapidly decrease, so the decrease in the sum of squared errors will decrease sharply. Then it becomes flat as the number of clusters increases, that is, the elbow corresponds to the true number of clusters in the data. The core index of the contour method is the Silhouette Coefficient. The larger the average contour coefficient, the better the clustering effect. Therefore, the maximum average contour coefficient is the optimal number of clusters. Because the number determined by the contour method is not necessarily the optimal, it is sometimes necessary to judge by SSE, so the elbow method is selected to determine the optimal number of clusters. The number of clusters is set to 1 to 15 for repeated prediction. The final results show that when the number of clusters is 13, the number of clusters is optimal. Therefore, this paper divides features into 13 categories for research.
The process of K-means clustering is as follows: (1) Segmenting the reviews, the nouns in the reviews are selected as candidate words for feature clustering. And keep the nouns that appear at least 10 times to form a noun dictionary. (2) After the words in the dictionary are trained by Word2Vec, they are transformed into word vectors as a clustered corpus.
(3) The K-means algorithm is used to cluster the word vectors. According to the optimal number of clusters, the number of clusters is 13 and judged based on the distance formula. At the same time, referring to previous related research and manual classification, the final hotel feature is classified. The concrete classification is shown in Table 1.

Sentiment Analysis Based on Sentiment Dictionary
Consumers usually express their opinions on specific features when they post reviews, so "feature-view pairs" can be extracted as evaluation units. The central idea of sentiment analysis is to judge sentiment through adjectives and adverbs closest to feature nouns. After extracting the "feature-view pairs" of each sentence, we will classify the features by sentiment dictionary. In order to make the classification results more accurate, the words related to hotels are added in this research to form a special dictionary for hotels. The concrete construction principles are as follows.
HowNet2007 [18] dictionary is used as the basic dictionary. The positive basic sentiment dictionary is a combination of positive evaluation words and positive emotional words. The negative basic sentiment dictionary is a combination of negative evaluation words and negative emotional words. In the end, 7020 positive emotion words and 5949 negative emotion words are obtained. In order to improve the classification accuracy of the hotel-specific sentiment dictionary, manual processing is required: all valid reviews are processed by word segmentation, etc., and then word frequency statistics are performed on the adjectives, and the sentiment polarity of the selected adjectives is judged to form a special sentiment dictionary.
Except for nouns and adjectives, consumers have different emotional strengths when they post reviews. Therefore, this research determines the quantitative standard of emotional polarity based on the emotional level of degree adverbs in HowNet2007, as shown in Table 2. The sentiment polarity score of the feature is equal to the degree adverb multiplied by the sentiment polarity value, if there is no degree adverb, the score is 1 or -1. The extracted "feature-view pairs" are calculated, and then calculate the average of all features in a category to get the sentiment score of every category of the hotel.

Implicitly Derived Importance and Satisfaction of Features
Through the above experiments, 13 categories of hotel features are obtained. The sentiment score represents the satisfaction score of each feature. The correlation test is performed on the extracted 13 categories of features. There are a total of 78 correlation coefficients, of which there are only 8 features that are not related to each other, including: catering-infrastructure, catering-room facilities, catering-network, insulation-network, environment-network, brand-bathroom, brand-location and network-location.
In order to resolve the mutual influence between the features, the existing data was revised according to Deng's conversion method, and the implicitly derived importance is used to replace the self-stated importance. The conversion method mainly has two steps: First, the natural logarithm ln ( ) is taken for each feature. Since the sentiment score in this paper is calculated, the minimum positive score is -2, therefore, ln ( + 3) is used as the independent variable of each attribute to make it linearly distributed. Secondly, using ln ( + 3) and overall satisfaction , we perform partial correlation analysis. The overall satisfaction score is obtained by the crawler for the hotel star rating, with an integer ranging from 1 to 5, where 1 is very dissatisfied and 5 is very satisfied. Partial correlation coefficients obtained from partial correlation analysis are made to be implicitly derived importance. The implicitly derived importance and satisfaction scores of hotel features are shown in Table 3.

Revised IPA
The satisfaction is taken as the horizontal axis and implicitly derived importance is taken as the vertical axis. The mean value of all feature satisfaction and implicitly derived importance are used as the center points to divide the matrix into four quadrants. The 13 features are mapped in the matrix quadrant according to the scores of each feature in Table 3. The results are shown in Figure 2. According to the IPA analysis figure, the satisfaction and importance of the quadrant I are high, including three features: service (3), location (13), and price (6). Among them, the satisfaction and importance of service are the highest, reflecting the customer's attention to service personnel and service attitude. With the development of society and the improvement of civilized quality, customers pay more attention to the requirements of intangible features and more emphasis on the consumption of things. As a typical experience product, hotels should pay more attention to the improvement of service. The second is the hotel location. The hotel location has always been used as an important reference feature. In the past research on hotel features, the "hotel location" was also researched separately. Therefore, location is very important. It is more inclined to choose hotels with convenient transportation, around the scenic area or surrounding facilities. Finally, for the price, the rapid development of budget hotels in recent years has benefited from its price positioning. Compared with other types of hotels, such as four-star and high-end hotels, budget hotels have obvious price advantages. Since most consumers' economic conditions are relatively ordinary, and they are still sensitive to price issues. Therefore, budget hotels should continue to give play to their price advantages, and strive to optimize based on the market share they have already occupied. Because the features of the quadrant I represent the competitive advantage of the company, the strategy adopted is "keep up the good work." The quadrant II is low satisfaction and high importance, and includes two features: catering (1) and room facilities (8). Catering is essential for people to travel. The initial service mode of budget hotels is accommodation and breakfast. With the modern people's pursuit of healthy living, breakfast has become the standard of daily life. Therefore, customers are paying more attention to the free food and beverage provided by hotels. Because the features of quadrant II represent the aspects that enterprises urgently need to improve, if they are ignored, it will pose a serious threat to the development of the enterprise. People's demand for hotel catering is not harsh, and does not require the variety and richness of catering types, therefore, it is necessary for hotel managers to provide a relatively simple diet and improve it. For room facilities, such as air conditioners, kettles, and other basic room types, they are the basis for the consumer experience and the most basic service of the hotel. They directly affect consumers' overall perception and satisfaction of the hotel. The strategy adopted by this quadrant is "concentrate here." The quadrant III, that is, satisfaction and importance are relatively low, including seven features: brand (10), infrastructure (7), cleanliness (9), bathroom (12), bedding (2), network (11), and insulation (4). Infrastructure such as parking lots, bathrooms such as bathing facilities, beddings such as quilts, and insulation of rooms, are the basic equipment of the hotel, so they do not attract much attention. Customers are accustomed to these essential features, so they are of low importance and have a low impact on overall satisfaction. Regarding brand feature, this research finds that a certain amount of online reviews will mention the hotel name, such as "Hanting Inn", "Home Inn", etc. Therefore, customers will be affected by the brand to a certain extent when making consumer choices, but most customers prioritize other factors before considering the brand. The cleanliness feature is also an important basic condition. Under the condition that other basic features are provided, the cleanliness of the hotel should reach a certain standard. Network as an indispensable factor for modern cities, especially tourism cities, it can already reach a high coverage rate, and it is no longer an additional feature that customers pay attention to. Therefore, the strategy adopted for the features of the quadrant III is "low priority", and it can be improved under the condition of sufficient hotel resources.
The quadrant IV is high satisfaction and low importance, and includes one feature: environment (5). The environment may be noisy in places with convenient transportation or around the scenic area, and the environment may be relatively quiet in relatively remote places, however, there is also less convenient transportation. Because location is a feature that customers pay great attention to when consuming, and the convenience of location contradicts the quietness of the environment to a certain extent. Therefore, the general customer will give priority to the hotel location and ignore the quiet environment. It is considered to be "possible overkill". When the resources of the hotel are limited, the features of the other quadrants are prioritized, and the excessive resources are transferred to other aspects to increase the overall satisfaction of the hotel.

Conclusion
The IPA analysis method is widely used because of its simplicity and ease of operation. However, due to the limitations of the IPA method and the complexity of traditional questionnaires, the use of IPA has also been restricted. Therefore, from the perspective of management, the focus of this article is the empirical application of Bi et al.'s [19] method of introducing online reviews into IPA. Compared with the questionnaire, online reviews are more authentic and easier to obtain. Based on a large amount of data, more objective and accurate results can be obtained. Hotel managers determine more accurate and reasonable improvement strategies based on the objective and precise results, while effectively reducing the company's human, material, and time costs. Secondly, we use the existing principles and methods to revise IPA to meet the assumptions of the use of IPA, so as to make the conclusions more accurate. From the perspective of practice, it is possible to understand the current development status of budget hotels in Qingdao more realistically and effectively. Based on a more trustworthy conclusion, it is proposed the improvement strategy. The strategy can obtain higher satisfaction through meeting customer needs as much as possible and provide reference for the improvement of hotels for Qingdao to build a national central city.
The research in this paper also has certain limitations. Firstly, the selected hotel sample is only targeted at the economy of Qingdao, and cannot represent the overall development of the hotel industry in Qingdao. Follow-up research and analysis will be conducted for different types of hotels. Secondly, although the revised IPA referenced in this article includes the three-factor theory of asymmetry, it cannot accurately reflect the asymmetry between the satisfaction and importance of each feature. Therefore, we will carry out more in-depth research on the revision method of IPA.


extfieldsofstudy: Economics Physics

text:
Discussion on the Concept and Model of New Retail Energy Finance

The development of intelligent and automated information technologies such as 5G and blockchain has provided development conditions for new retails in energy finance. At present, State Grid Corporation of China is vigorously promotes the construction of ubiquitous power Internet of Things, and takes the function of revitalizing the power supply business hall and the innovative side-by-side service mode of electricity generation as the starting point to create a new “hub-type, platform-type, shared-type” energy finance retail business. But however, the current concept of new retail energy finance is still unclear, and the plan is still unclear. Through a large number of capital collections, research and interviews, the project team discussed the concept, necessity and mode of the new energy retailing retail for reference!

The Concept and Connotation of New Retail Energy Finance
In October 2016, Alibaba proposed the concept of "new retail": the combination of online and offline depth, through the integration of modern intelligent logistics, highly integrated with big data, cloud computing and other innovative technologies, realizing the integrated integration from customer demand to logistics warehousing, production and manufacturing. Energy finance is to involve finance more comprehensively and deeply into the development of the energy industry, especially to embed the genes of financial innovation into the energy industry, and to exert the keen effect of finance on resource allocation, making it the main driving force for promoting high-quality energy development. With the development of the Internet, the adjustment of energy industry institutions, and the innovation of financial services, the connotation of new retail of energy finance is also expanding. The research team believes that the new energy finance retail in the narrow sense is based on the power business hall to carry out financial business. This service is one-way and information asymmetrical. In the broad sense, the new retail of energy finance is to embed financial in the process of upgrading the national energy structure, integrate it into the process of sales and service of energy-related products, revitalize the power supply business hall, maximize the endowment of energy resources, and maximize the efficiency of operation. And through the optimal implementation form to meet customer needs, to achieve customer value and corporate value added, while enabling the system to achieve a total profitable goal of the overall solution.

The Necessity Analysis of New Retail Energy Finance
(1) Promoting energy finance New retail is an important way to adapt to the new trend of integration of industry and finance in central enterprises. The report of the 19th National Congress of the Communist Party of China stated that it is necessary to deepen the reform of the financial system and enhance the economic capabilities of financial services. The combination of industry and finance is a combination of financial capital and industrial capital, and it is an inevitable trend for the central enterprises to become better and stronger in the future. In recent years, central enterprises have achieved many positive results in the integration of industry and finance, and in promoting production, and have developed a variety of new models of integration of industry and finance. In this context, the development of new retail energy finance, the use of energy resources endowment to provide comprehensive and professional financial services to the society, to maximize the energy allocation efficiency of the energy industry and the efficiency of the use of financial capital, is an effective way to adapt to the new trend of combining production and integration of central enterprises.
(2) Promoting energy finance New retail is an effective measure for the company to cope with external competition pressure and maintain competitive advantage. The new round of power system upholds "controlling the middle and releasing the two ends", demanding to adhere to the market direction, gradually introducing the power sales business, further introducing competition, improving the operation mechanism of the electricity market, and encouraging more and more market participants to participate in the sale. In the electricity market, the distribution business will be developed in a mixed-ownership manner, and the incremental power distribution investment business will be released to eligible market entities. In the future, in the field of placing electricity business, the company will directly compete with social capital and face greater external competitive pressure. Promoting energy finance New retail can take advantage of the company's leadership and influence in the industry, and use its own advantages to achieve business model innovation, thereby maintaining competitive advantage and responding to external environmental changes.
(3) Promoting energy finance New retail can create new profit growth points for the company. At present, the company faces greater pressure on profit growth and needs to continuously innovate its business model and find new profit growth points. On the one hand, the reform of the power system introduced the external market competition mechanism, which weakened the company's profit margin in the field of power distribution; on the other hand, as a public utility enterprise, the company assumed a large amount of social responsibility and has been continuously policy-oriented for the past two years. The price cuts continue to compress the company's profit margins, making the company's continued development facing challenges. Energy Finance New retail is a business model innovation based on the company's existing resources. The new retail approach can promote the rapid development of the company's financial sector, thus providing a new growth engine for the company as a whole. (4) The development of science and technology provides technical support and development opportunities for new retail of energy finance, and also puts forward realistic and urgent requirements for new retail of energy finance. At present, the development of new generation information technologies such as mobile Internet, cloud computing, and Internet of Things is integrated with modern manufacturing and traditional industries. The development of technology has changed the original one-way "production-consumption" relationship, and consumers are no longer limited, instead, it can influence the supply of products by upstream producers through individualized and diverse needs. On the one hand, the development of technology has provided technical conditions for new retail of energy finance, which has spawned the development of new retail of energy finance. On the other hand, technology application has the characteristics of short conversion time and fast iteration. If it cannot keep up with technology development, it will promote energy finance. New retail, innovative sales model of existing financial products, will be in a competitive disadvantage in the industry, facing the risk of being eliminated. (5) New retail of energy finance has positively promoted the development of energy Internet enterprises and the construction of ubiquitous power Internet of Things. With the implementation of the energy Internet strategy and the ubiquitous development of the power Internet of Things, the company's financial industry needs to continuously innovate business models in serving the main grid and service energy industries, giving full play to the functions and values of industry and finance, and strengthening risk prevention and control of financial business. Since the establishment of the company's financial industry, the "main service industry" has been the primary position, and the ability to serve the main business of the power grid has been continuously improved in terms of fund management, internal and external financing, and insurance protection. Under the situation that the energy Internet and the ubiquitous power Internet of Things continue to develop in depth, the company's financial industry should give full play to the company's core hub advantages in the power grid industry chain, provide targeted financial services, and innovate financial products and models. The development of new retail energy finance can provide a good foundation for further unlocking business potential and expanding profitability in the future.

New Energy Retail Selection Model of the Company
(1) Analysis of organizational patterns At present, based on the business system with the traditional power supply service as the core, the company has vigorously expanded the ubiquitous power Internet of Things emerging business. Energy Finance New retail needs to build an interactive, network-based, multi-dimensional organizational structure that fits the business development model in a new context. The design is as follows from the two phases of the near and the future. Recent Program: Establishing the New Retail Management Working Group of Energy Finance Established a new retail management team for energy finance, including personnel from relevant departments of the provincial company, relevant personnel of the Yingda Finance Department, and relevant personnel of the electric vehicle company. The management work meeting was held regularly, and the marketing department of the headquarters could send relevant personnel to participate. The basic structure. The working mechanism of this program is to uniformly exchange, research, formulate and deploy corresponding management work in the form of convening working meetings, and all relevant departments work together. Specifically, it includes: 1 the specific transformation plan of the business hall and the functional area configuration; 2 the collaborative work plan of each business system of the business hall; 3 the overall training, incentive and emergency plan system of the business hall. Long-term plan: create a matrix organization structure Evolved from the management working group, through the integration of all business personnel in the business hall, all business integration training, strengthen communication, collaboration and cooperation; give full play to the effectiveness of the business hall ecosystem. The working mechanism of this organization design mainly includes the following characteristics: First, the organizational platform is higher, the internal resources of the system can be more comprehensively integrated, and the working mechanism of efficient and smooth operation can be established quickly and effectively. The second is to be able to achieve a higher level of direct dialogue, thereby enhancing the right to speak in professional dialogue between formats. The third is to strengthen the ability to communicate internally and externally. At present, the company's industrial and financial business is highly correlated with the main business, which helps the company to accurately locate the role of different businesses in the company.
(2) Analysis of business model Through the service flow, business flow and capital flow, the power business hall is activated to create an electric business environment ecosystem. First, the business category: through the integration of various businesses into the network, to achieve business, I have you, you have me; second, the service flow: refers to the spread and flow of services generated in various stages of the business, including pre-, in-, and post-event phases. The service content includes both physical services and value-added services. Third, the flow of funds includes both the flow of funds between members and the transfer of physical goods and their ownership, as well as financial products provided by financial institutions to companies/individuals that require funds. The retail energy finance system operation model shown as below.  Figure 1. New retail energy finance system opearation model framework.
(3) Analysis of platform mode At present, the company has platforms such as State Grid Mall, "Electronic e-Link", "State Grid Business Travel", "Love Ruyi" and other platforms, focusing on new retail business. The company has platforms such as "Electronic E-Link" and "Huonong Gang". Most of the platforms are independent construction, and users, professions, and channel resources are relatively scattered. The scale, flow, data, and brand have not yet formed a synergistic amplification effect. The future platform design takes the service company's "three-type and two-network" modern enterprise construction as the fundamental requirement, taking the function of revitalizing the power supply business hall and the innovative power-side marginal service mode as the starting point, taking "online + offline + data system" as the means to launch new energy retail business. Through finance as a convergence point, we will build a comprehensive new platform for all parties, value sharing, efficient interaction, and convenient interconnection. From decentralization to intensiveness is the direction of future development. The first is to unify service channels and user portals. Based on the enterprise portal and mobile application platform of the integrated platform, establish a unified access portal for the e-commerce business application system, and promote the entry sharing and user diversion of the existing platforms. The second is to coordinate customer management and data analysis. According to the common needs of business and customers, we manage, mine and share data such as supplier credit, customer service and behavior, and give play to the value support of the company's data assets for various business services. The third is to optimize business service processes. Starting from meeting user needs and improving user experience, we will continue to improve and optimize existing business and service processes, and provide one-stop service and system solutions for users in combination with "Internet +". (4) Product model analysis For the products covered by the energy finance "new retail" business and the corresponding services, a unified product service portfolio system is constructed according to the product service supply-sales-after-sales chain. Products include financing products, including receivables financing, prepaid financing, inventory financing, insurance products, and asset management products. The two-step model of the product. The first phase is mainly based on electricity/energy, designing financial products that are strongly related to electricity/energy, opening up the market and implementing the strategy of "marketing for capital"; the second phase fully spreads the company's financial products. The first is to embed finance into the "window" of the business hall. For private business, the customer pre-stores a certain amount of electricity charges, and can freely donate the property and insurance related to the electricity and the customer; in the business related to the electricity fee, the peer-to-peer marketing securities and fund-based financial products; for the public business, for example In the process of implementing the expansion business of the customer industry, the company provides financing services to customers. For the analysis of electricity consumption of the group customers, some new types of electricity-value-added financial service products are designed in a targeted manner. On the one hand, it can save money for customers, on the other hand, it brings value to the enterprise and achieves a win-win goal. The second is to embed financial into the products and corresponding services covered by the new "new retail" business, the first phase to provide financial services related to products (industry chain related financial services); the second phase to provide extended financial services (all Financial product services). In the electric vehicle system, finance can play a capital advantage, expand the purchase volume by reducing funds, reduce product procurement costs, provide professional financing and loan services to customers, and provide auto insurance services to customers by utilizing the company's professional and brand advantages; In the networked home appliance system. By signing a financial service agreement with well-known smart IoT home appliance manufacturers at home and abroad, customers who purchase smart home appliances prefer YingDa financing. Bundling the company's financial products with smart home appliances. For example, if customers purchase smart home appliances to different levels, they will give different types of financial products (property insurance, life insurance, etc.). Small-scale genuine home appliances system, can be point-to-point precision marketing, develop financial products and services related to electricity / energy; precision poverty alleviation agricultural products system. On the one hand, it will intervene in the supply area and provide financing assistance. On the other hand, customers can give poverty alleviation products when purchasing/investing a certain amount of financial products or services. (5) Analysis of profit model The profit in the power business circle ecosystem mainly includes the main business (electricity fee + industry expansion report, etc.), financial institutions and four new formats of profit. The profits of these three types of enterprises promote each other and develop together. The profit model of the main business includes the existing profit, as well as the profit from the increase in electricity consumption caused by the potential increase in electricity consumption such as electric vehicles, smart appliances, and rural electrification, and the service cost of adding financial services in the process. . The profit of financial institutions is combined with the company's power basic data resources to classify the qualifications of customers and design targeted financial service products for different customers. In the initial stage, service customers mainly used electricity-related related financial products to occupy the market and train customers' viscosity. With the cultivation of the market, diversified financial products provide diversified services to realize value added. For the four new formats involving related financial products, financial institutions and the four formats expand the market by sharing customers and sharing profits, reducing unit costs through transaction volume increase, and increasing product profit margins. The Solution overall framework of new retail energy finance shown as below.