Research on Informationization Construction and Management Innovation of Hotel Industry in the Rapid Development of Tourism Market
Data publikacji: 17 mar 2025
Otrzymano: 30 paź 2024
Przyjęty: 10 lut 2025
DOI: https://doi.org/10.2478/amns-2025-0269
Słowa kluczowe
© 2025 Qili Tian, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
As one of the important components of tourism activities, the development of the hotel industry has been synchronized with the development of China’s tourism industry, in which the star-rated hotel industry is the first hotel industry promoted by the influence of tourism development [1-2]. Star hotel industry along with the growth of China’s inbound tourism and booming development, in the domestic tourism into the era of tourism, has been as a destination for tourism development of the development of the front and basic development projects, there was a time around the construction of star-rated hotels and hotels assessed the star boom. And star hotel standardized services, business reception and conference organization functions have also become the core attraction of some tourist destinations and the main consumption items [3-4].
The role of star-rated hotel industry on tourism development has a multi-level comprehensive, first of all, star-rated hotels form the core part of the hospitality system in tourist destinations, and their standardized accommodation, catering, rest, entertainment and other functions to meet the basic needs of tourists, and secondly, star-rated hotels own development and construction of the requirements of the development of public services in tourist destinations and the construction of facilities put forward supporting requirements to improve the supply of commodities to the tourist destinations, Road traffic, municipal facilities, civilized etiquette and other aspects of the conditions, and then star-rated hotels in absorbing the employment of local workers, to promote the growth of financial tax revenues has an obvious role to play, and can thus enhance the local support for tourism development of the economic level [5-7]. At the same time, the efficiency of star-rated hotels’ own development, brand building and marketing effects also form an important force in tourism attraction, tourism competitiveness and destination marketing, and this role is especially significant in some international tourist destinations and coastal vacation tourism. Over the past forty years since the reform and opening up, benefiting from the double promotion of economic development and tourism development in all parts of China, the domestic star-rated hotel industry has developed rapidly and entered a steady development trend [8-10].
In the hotel industry, unique service is always a unique chip in the competition. But the current customer requirements for hotel services have been far more than just waiters and room service [11]. The leading hotels of the future will offer more diverse services to their guests and earn more profits from their hotel operations. More services and higher productivity mean higher guest satisfaction and these will ultimately drive overall profits [12-13]. Hotels are facing a highly competitive environment with declining customer loyalty and many hotels today are unable to meet the technological needs of their guests such as videoconferencing, integrated unified messaging and high-speed wireless access throughout the hotel. The key to a hotel’s competitiveness is no longer the décor, but rather the hotel’s ability to access the Internet. Today’s travelers want to extend their work and home lives into the on-the-go environment, enjoying the comfort of their rooms while being comfortable using a variety of leading-edge technologies [14].
Hotel informatization can provide hotel managers and decision makers with timely and accurate information technology to grasp the situation of all aspects of hotel operations, followed by information management and control technology for hotel operations, in order to save operating costs, improve the quality of operations and management efficiency, and then directly facing the information services provided by the customer. The use of new computer network information management system can improve the management efficiency of the hotel in the following aspects, first of all, improve the level of service, to provide comprehensive and accurate information data for sales, to provide guests with fast, detailed and thoughtful service, to provide financial tight accounting system, followed by the ability to deal with a variety of complex situations, to provide strong support for the leadership of the decision-making, and finally, to achieve Access control, consumption “one card”, for the Internet and e-commerce [15-16].
The hospitality industry is one of the basic support industries for tourism development and has a very important impact on all stages of regional tourism development, growth, maturity and renewal. Literature [17] describes the need for tourism development to consider systematic investment in hotels, transportation infrastructure, food and beverage, etc., and focuses on understanding the structural barriers to regional tourism assets and infrastructure, and finally proposes an analytical framework for evaluating the potential for tourism development in developing countries. Literature [18] based on Hedonic pricing strategy examined the association of hotel price and location with the characteristics of the proposed site, the study revealed that the specific environment and location are highly correlated with the hotel pricing, and pointed out that nature reserves, as a part of the tourism product, significantly affects the pricing of tourism ancillary services, tourist satisfaction and tourism competitiveness, and therefore need to be given sufficient attention. Literature [19] systematically reviewed the research literature related to hotels and tourism and found that there is less literature on demand studies for tourist hotels and more studies focusing on segmented tourism markets and niche products. Literature [20] combined online data and hedonic analysis model of Sanya hotels to explain that hotel prices and tourism seasonality are highly correlated, where seasonal sensitivity of hotels with higher prices is relatively low. Literature [21] introduced an econometric literature analysis method to reveal the sustainable standards of the current hotel management model, which provides important references and suggestions for the optimization of hotel management standards. Literature [22] reviewed the literature related to tourism and hotel research, empirically explored the legitimacy of the sustainable development of the combination of hotel and tourism, and the study pointed out that the legitimacy qualification of tourism and hotel is very important in the process of promoting the sustainable development of hotel and tourism. Literature [23] examines the potential of tourism in Uzbekistan and the impact of tourism on the hotel industry, and analyzes the challenges and opportunities faced by the hotel industry in Uzbekistan, which provides an important reference for the good development of tourism and hotel industry in Uzbekistan. Scholars’ research on tourism and hotel services covers a wide range of topics, including tourism potential and hotel sustainable development paths, tourism seasons and hotel pricing, hotel demand forecasting, and hotel management optimization, etc., but there is not enough in-depth research on the underlying logic and connections.
The rapid development and wide application of e-commerce around the world, the ability of the hotel to provide a full range of network services has become an important prerequisite for many customers will choose to stay, and the information management of the hotel can also provide managers with a better management platform, which can allow more customers to improve satisfaction with the hotel’s full range of services, which will lead to great economic benefits. Literature [24] envisioned a comprehensive analytical model based on the theory of planned behavior as the basic structure, and based on this model to examine and analyze the hotel customer’s attitude towards service robots, the results of the study show that the hotel customer’s attitude towards robots, the perceived value of robot services and the practicality of robot services significantly affect the hotel user’s attitude towards robots. Literature [25] used qualitative research methods to reveal the positive attitudes of the tourism sector and hotel industry practitioners towards the smart hotel model, and concluded that the smart hotel business model has great economic potential in the tourism and hotel industries, as well as positive significance for the promotion of environmentally sustainable development. Literature [26] tries to use big data technology and Bootstrap resampling technology to analyze the customer profiles of CRM system of hotel chains, and suggests hotel managers to further segment the market and find the positioning of the hotel. Literature [27] talks about the concept of digital marketing, the role and the hotel’s demand for digital marketing, focusing on the analysis of the most suitable digital marketing methods in the hotel field, the study also has a positive significance for the hotel’s information construction. Literature [28] explores the impact of digital channels on hotels from the perspectives of hotel customers and hotel entities, which also paves the way for the positioning and goal realization of hotel marketing strategies. Literature [29] describes the evolution of socio-economic in the context of digitalization is deeply affected by digital information technology, and study and explain the digital technology empowered hotel industry services and accommodation to bring about a transformation, the study for the hotel’s digital high-end route to provide a positive reference. Literature [30] explores and analyzes the digital innovation process in hotels and analyzes the input costs of digital innovation projects in hotels as well as the additional benefits generated, pointing out that digital technological innovations can be used for customer attraction and customer retention, as well as improving customer response efficiency. Scholars’ research on digital technology-enabled hotel industry mainly focuses on the innovation of hotel management mode, marketing mode, etc., and all of them recognize the value and potential of digital information technology in the hotel industry.
This paper prioritizes the customer needs of the hotel industry based on the Kano model, and proposes a strategy proposal for information management innovation in the hotel industry in combination with the main content of information technology construction in the hotel industry. Firstly, the questionnaire was designed to determine the scales of 6 primary indicators and 20 secondary indicators of hotel image, room service, catering service, staff quality, support system and cost-effectiveness, and based on Cronbach’s α coefficient to test the reliability of the scales, and KMO test and Bartlett’s sphere test to realize the validity test. Then, the Kano model is used to calculate and judge the necessary attributes, charming attributes, expectation fulfillment, undifferentiated attributes, reverse attributes, and suspicious attributes of customer needs, so as to provide the basis for the design of information technology management innovation strategy in the hotel industry.
As an industry with a long history of development and a high degree of maturity, the hotel industry, together with the tourist attraction industry and the transportation industry, is one of the three pillars of tourism development. And according to the statistics of the World Tourism Organization (UNWTO), international tourism revenue and arrivals have achieved consecutive years of growth.The expansion of the tourism market has opened up a vast development space for related industries, especially the hotel industry, which is an important part of the tourism infrastructure, and its market demand has also increased.
The rapid development of the tourism market has brought many opportunities for the hotel industry. Firstly, the increase in market demand has provided impetus for the development of the hotel industry. Secondly, the advancement of technology has made the hotel industry’s services more personalized and convenient.
However, behind the opportunities there are also challenges. Increased competition requires hotels to continuously improve their service quality and efficiency. At the same time, the diversification of customer needs also forces the hotel industry to innovate its products and services. Therefore, how to grasp the opportunities and at the same time deal with the challenges has become an issue that cannot be ignored in the development of the hotel industry.
In order to grasp the opportunities brought about by the rapid development of the tourism market and actively respond to the accompanying challenges, the development of the hotel industry should realize further transformation and upgrading, and the construction of information technology has become one of the important ways.
First of all, for customers, information technology construction can be realized to provide customers with more convenient, personalized services, such as online booking, self-service check-in, intelligent room control, etc., to increase the customer’s utility to the hotel.
Secondly, for hotel managers, information technology can provide more efficient operating and management tools and methods, and can be used to quickly solve customers’ difficulties and problems. In addition, hotel informatization construction can also expand the scope of management, so that hotel managers can realize remote management of related subgroups through the information system, and improve the management effectiveness of the whole hotel group.
Finally, information technology is also conducive to improving the comprehensive benefits of the hotel, through information technology means can not only realize the hotel’s manpower, material costs to effectively reduce consumption, increase the hotel revenue, but also can use information technology to provide customers with more diversified ordering channels and richer service content, to help the hotel to build a unique brand image, to enhance brand awareness and reputation, and to enhance the hotel’s market Competitiveness.
The hotel industry’s informationization construction consists mainly of the following content:
The e-commerce platform is an important factor in the information-sharing structure of the hotel industry. Through the e-commerce platform, hotels can realize online booking, payment, evaluation and other functions to provide customers with more convenient services. At the same time, it can also help hotels collect customer data for accurate marketing and customer relationship management.
Intelligent management systems are another important content in the construction of hotel industry information.The system comprises a variety of subsystems, including building equipment control system, security prevention system, computer network system, and so on.It can ensure the scientific management of public resources at the hotel, reduce operating costs, and ensure safe operation of the hotel.
Customer relationship management system (CRM) is the key link in hotel informationization construction.Through a CRM system, the hotel can collect, organize, and analyze customer information, understand customer needs and preferences, and develop personalized services for them.At the same time, the CRM system can also help the hotel to carry out customer segmentation and market positioning, and develop more accurate marketing strategies.
The security of informationized data is a very important issue in the construction of hotel informationization. The hotel should actively take measures to protect the security of information data, to prevent the loss of important data in the informationization system or to be maliciously disturbed.The hotel can create a specialized network data file.Or download the appropriate software to perform timely virus detection, prevention, and control.Strict requirements for employees to prohibit illegal operations of employees.At the same time, the hotel is processing important data backups, so that if data is lost, it can be found in a timely manner.Do not delay the hotel’s normal operation.
To strengthen the information technology infrastructure of the hotel industry and promote management innovation, this paper develops an information technology service platform for the hotel industry.
The service platform is based on online service management for small, medium, and economic hotels, adopting the SAAS software service model to provide users with a full range of hotel informatization services through the Internet. The framework structure of the platform is shown in Figure 1, which mainly includes:
1) Setting up a hotel service center system platform to provide one-stop services such as online hotel booking, tourist attractions, catering and tickets online inquiry booking and purchase. 2) Forming hotel purchasing alliance, setting up hotel system centralized purchasing system platform, providing online centralized purchasing, unified logistics and distribution, unified virtual warehouse management, unified supply chain management, online bidding management and other one-stop services. 3) Set up hotel business training center system platform, provide online audio and video training, including common hotel management software operation process and hotel etiquette and other training. 4) Set up digital hotel system platform, provide online business functions, such as network teleconferencing, video conferencing, meeting minutes and meeting video, network fax, e-commerce and so on. Provide colorful entertainment, such as online movies, on-demand self-help TV programs, popular games, and various online audio and video chats.Provide online ticketing functions such as online inquiry, reservation, and ticket purchase.Provide online service functions, such as secretary services, online attraction guide services, online catering guide services, and online hotel guide services.Provide electronic reading room functions, such as various e-books, videos, and other materials.
The framework of the platform
The enterprise portal system consists of subsystems such as basic management, enterprise internal management, workflow and collaborative office, information system integration, mail management system, schedule management system, newsletter management system, questionnaire survey, meeting management, vehicle management, unified messaging module, website template management, videoconferencing system and digital signature system.
The software architecture of the central reservation system (CRS) is shown in Figure 2. In this system, the lower level for the central database layer, to maintain the operation of all the required data, the subordinate hotel database must be consistent with the central database.The upper layer is the central service layer, which includes central reservation and customer relationship management, which is the entity layer of the whole CRS. The middle layer uses a web service interface as the connection.
Software architecture
The frequent guest management and centralized marketing system is mainly responsible for managing member information and hotel accounts. In order to ensure the security and convenience of large-scale management and operations, all members use a unified magnetic card.All the data of the system is managed by the data center, which provides two-tier access on LAN and WAN, and supports seamless connection of single and group hotels to the system. The data center management software has both C/S and B/S structures. The message server mechanism used in the system effectively reduces the load on the central server, adopts dual-computer fault tolerance to improve data security during implementation, and uses hardware firewalls and technology to prevent external intrusion.
The architecture of the integrated communication system is shown in Figure 3. Within the system, a call center with redundancy and an office system control center are configured, and a related billing and authentication system is provided, which allows for docking with third-party systems. The data bandwidth of the central and stores needs to ensure that voice can occupy at least 1M bandwidth in extreme cases.
Architecture of the integrated communication system
The centralized purchasing system mainly includes supplier management, supplier catalog, purchase price management, purchase contract management, supplier evaluation, procurement management, purchase plan management, purchase order management, invoice calibration, channel management, channel member management, channel management, inventory management, inventory accounting, distribution and transportation management, quality management, statistical report, and solicitation and bidding management system, which are composed of a total of 18 parts.
Personnel management and training system is an important guarantee for the smooth operation of hotel businesses.The system mainly includes modules such as human resource planning, recruitment and hiring, personnel information management, attendance management, and training development, and each module has a close logical relationship with the other.
In order to make the information construction and management innovation of the hotel industry in line with the reality of the rapid development of the tourism market, this paper designs the survey, and the scale and conducts the reliability and validity test, and then analyzes the importance of the hotel customers’ needs using the Kano model.
Reliability is the degree of consistency of a measurement. Reliability itself has nothing to do with the accuracy of the measurement results, but is closely related to the stability of the measurement results. The accuracy of measurement results can be ensured by analyzing the reliability of questionnaire scales, which ensures the reliability and stability of questionnaire data.In general, reliability can be categorised as intrinsic and extrinsic reliability. This study focuses on the internal consistency of the measurement items, i.e., whether it is possible to measure the same concept stably, and thus the intrinsic reliability of the sample is analyzed.
Intrinsic reliability is mainly evaluated using Cronbach’s α, which is given by the formula:
Where k is the number of questions in the quiz,
In this study, Cronbach’s α was chosen to test the reliability of the sample data, and the metric Correct-Item Total Correlation (CITC) was utilized to eliminate spam items [31]. Usually, for social science research, the reliability of the sample data is acceptable when
Validity analysis refers to the validity analysis of the evaluation, which is a questionnaire or other methods to measure the degree to which the results obtained meet the objectives, that is, the degree of proximity of the measurements obtained by the study to the true value. Content validity analysis and structural validity analysis are both part of the general validity analysis.The first step is generally conducted by experts or researchers to evaluate whether the indicators or factors of a questionnaire are representative of the subject or content to be measured.The next step is to conduct factor analysis using statistical analysis software to test whether the measurement results of the questionnaire can better express the meaning of the research subject. To analyze the validity, SPSS software is commonly used to analyze and then measure it with Bartlett’s sphere test and KMO test.
KMO (Kaiser-Meyer-Olkin) test is used to compare the correlation coefficient and partial correlation coefficient between variables [32]. The calculation is shown in equation (2):
Where
The value of KMO is between 0 and 1. The closer the value of KMO is to 1, the stronger the correlation between the variables, which indicates that it is more suitable for factor analysis. the value of KMO is close to 0, the weak correlation between the variables, which indicates that it is not suitable for factor analysis. The commonly used KMO metrics are shown in Table 1.
Require criteria for KMO
| KMO value | Judging criteria | KMO value | Judging criteria |
|---|---|---|---|
| 0.9≤KMO<1.0 | Very suitable | 0.6≤KMO<0.7 | Passable |
| 0.8≤KMO<0.9 | Fit | 0.5≤KMO<0.6 | Not very suitable |
| 0.7≤KMO<0.8 | General | KMO<0.5 | Extremely unsuitable |
The Bartlett test of sphericity starts from the assumption that the correlation coefficient matrix of the original variables is a unit matrix [33]. It is calculated from the determinant of the correlation coefficient matrix to obtain a test statistic and this statistic obeys a chi-square distribution. If the observed value of the calculated statistic is relatively large, and the corresponding p-value is less than the given significance level α (usually taken as 0.05), the null hypothesis is to be rejected, indicating that the correlation matrix of the original variable analyzed is not a unitary matrix, and is suitable for factor analysis. In contrast, the variable is unsuitable for factor analysis.
The Kano model is a product requirement model, which is a tool specialized in user requirement classification and prioritization. By classifying the degree of influence of various functional characteristics of products or services on the overall satisfaction of users, it can provide a reference basis for enterprises to grasp the direction of product optimization [34]. In this paper, the Kano model is used to provide a basis for prioritizing customer demand for management innovation in the hospitality industry.
According to the user’s feedback needs, the Kano model divides the factors into five attributes: required attributes, expected attributes, charming attributes, undifferentiated attributes, and reverse attributes. The Kano model is shown in Figure 4.
Kano model
Must-have attributes (M) are the basic needs that the user must meet, if the product or service lacks these characteristics, the user will be very dissatisfied, but providing these basic needs will not give the product a competitive advantage.
The needs that users expect to receive are the expected attributes (O). When a product or service has them, users will be satisfied. When it is lacking, users are slightly dissatisfied. Satisfying desired needs helps maintain user satisfaction, but does not result in a significant competitive advantage.
Attractive attribute (A) is a need that exceeds the user’s expectations and gives the user an extra surprise; when provided, this need can greatly enhance user satisfaction and can be a competitive advantage for the product or service.
Indifferent attribute (I) is a requirement that the user is not keen on, and user satisfaction remains unchanged regardless of whether it is provided or not.
Reverse Attributes (R) are requirements that cause dissatisfaction when a product or service has them. It is very important to avoid fulfilling the reverse requirement, otherwise it may lead to a decrease in user satisfaction.
The Kano model is able to prioritize user needs and thus prioritize design elements to enhance user satisfaction.Using the Kano model research method can provide a better strategy design for innovation in information technology management in the hospitality industry.
The traditional Kano model attributes Kano categories by counting the highest frequency service attributes, without considering that the Kano model attributes will change over time, as well as the overall distribution of its individual service functional attributes and the scale of its data volume, so the traditional Kano model analysis method has certain limitations. In order to fully explore user needs, a Better-Worse Index Analysis method is also needed to be introduced.
Better-Worse index is used to quantify the impact of the degree of fulfillment of a class of needs on the overall user satisfaction, also known as SI-DSI index.
In the Better-Worse index system, the Better/SI index is used to measure the sensitivity of the impact of the degree of satisfaction of a need being met on the user’s satisfaction, and its focus is on the user’s satisfaction. When the Better index is close to 1, it means that users are extremely sensitive to changes in the degree to which a need is satisfied. That is, the higher the Better value, the more obvious the effect of the degree of fulfillment of that need on increasing user satisfaction. On the contrary, if the Better index gradually approaches 0, it means that users are less sensitive to changes in the degree of fulfillment of this requirement, i.e., the degree of fulfillment of this requirement has a very limited impact on user satisfaction.
The Worse index is used to measure the sensitivity of the unfulfilled level of the requirement to the impact of user satisfaction, with a particular focus on user dissatisfaction. The value of this index ranges from -1 to 0. If the Worse index is close to -1, it indicates that the user is extremely sensitive to the unfulfillment of a need. That is, the lower the Worse value, the more significant the unfulfilled need is in promoting user dissatisfaction. On the contrary, when the Worse index gradually approaches 0, it means that the user’s sensitivity to whether the demand is satisfied or not has been weakened, i.e., the effect of the demand on the user’s dissatisfaction has tended to be weak.
The calculation formula is respectively:
In order to realize the innovation of information technology management in the hospitality industry based on customer needs, this paper utilizes the Kano model to prioritize customer needs.
In order to objectively screen out the many indicators affecting customer satisfaction, this paper understands the structure design of the questionnaire by combing through the existing literature and results, and referring to econometric models such as SCSB and ACSI. In terms of element selection, the satisfaction questionnaire of famous hotels in both home and abroad was borrowed, and interviews were conducted with hotel managers to adjust and supplement some of the measurement elements.Six primary indicators (categories) and 20 secondary indicators were finally identified, including hotel image (X1), room service (X2), catering service (X3), staff quality (X4), support system (X5), and cost-effectiveness (X6). The secondary indicators are brand trust (X11), brand reputation (X12), hotel publicity (X13), room tidiness (X21), product comfort (X22), reasonable and cozy room decorations (X23), reasonable and convenient sanitary facilities (X24), professional competence of the service staff (X31), amicable and cordial attitude of the service staff (X32), accuracy and efficiency of the service provision ( X33), geographic location of the hotel (X41), easy and fast booking (X42), quality of the hotel network (X43), atmosphere of public areas (X44), availability of leisure facilities (X45), sound insulation of the room (X46), rich quality of the breakfast (X51), high quality of the meal (X52), dining experience (X53), and cost-effectiveness of the hotel product (X61).
In accordance with the basic principles of the KANO model, the above 20 secondary indicators were presented in the form of a dyadic questionnaire, which required the respondents to first indicate their attitudes from two very different perspectives (like or dislike), and then evaluate the importance of their subjective feelings. The score from unsatisfied to satisfied is 1-5, which means dislike, tolerate, indifferent, take for granted, and like, respectively. The questionnaire was distributed online, a total of 352 questionnaires were collected, 295 valid questionnaires, effective recovery rate of 83.81%, the data were analyzed using SPSS to improve the effectiveness of the questionnaire as much as possible.
In order to ensure the reliability and validity of the scale, the recovered questionnaires were tested for reliability and validity, respectively.
The reliability of the six sub-dimension scales in the questionnaire was tested, and the results of the reliability test of the scales are shown in Table 2. Table 2 shows that the Cronbach’s alpha coefficients of the subscales under each dimension range from 0.842 to 0.908, which are all greater than 0.8, indicating that the sub-dimension scales of the questionnaire have a more satisfactory reliability.
Reliability test results of scale
| Dimension | Problem number | Cronbach’s α |
|---|---|---|
| Hotel image | 3 | 0.851 |
| Room service | 4 | 0.876 |
| Catering service | 3 | 0.854 |
| Employee quality | 6 | 0.908 |
| Support system | 3 | 0.842 |
| Performance ratio | 1 | 0.873 |
The research needs to test the content validity and structural validity of the collected data to determine whether each question item can effectively predict the corresponding target variable. As the scale in this paper is developed based on the existing mature systematic scale, combining classic literature and consulting relevant experts and scholars in the industry, it has been perfected. And on the basis of the pre-survey, some questions in the questionnaire have been corrected and improved, so it can be considered that the questionnaire in this paper has good content validity.
For the validation of structural validity, SPSS28.0 software was used to test the KMO value and Bartlett’s sphericity of the sub-dimension structure of the scale, and the results of the KMO value and Bartlett’s sphericity test are shown in Table 3.
KMO value and Bartlett’s test of formal items
| Dimension | Sample enough of the KMO metric | Bartlett test of sphericity | ||
|---|---|---|---|---|
| Approximate chi square | df | Sig. | ||
| Hotel image | 0.826 | 8981.537 | 36 | 0.000 |
| Room service | 0.874 | 2785.319 | 12 | 0.000 |
| Catering service | 0.885 | 4614.528 | 58 | 0.000 |
| Employee quality | 0.876 | 4563.441 | 74 | 0.000 |
| Support system | 0.908 | 4511.342 | 35 | 0.000 |
| Performance ratio | 0.872 | 3375.165 | 28 | 0.000 |
As can be seen from Table 3, the KMO values under the six dimensions of hotel image, room service, catering service, staff quality, support system and value for money are 0.826, 0.874, 0.885, 0.876, 0.908 and 0.872 respectively, which are all greater than 0.8. The approximate chi-square of the Bartlett’s test of sphericity is large enough and the significance level is 0.000 <0.05.This indicates that the goodness of fit of the structural validity of the questionnaire scales was preliminarily verified.
The questionnaire data was subjected to validation factor analysis to validate the scale fit.The results of the scale validation factor analysis for fit indicators are shown in Table 4.
Validation factor analysis fitting index results of the scale
| Absolute fitting index | Relative fitting index | |||||||
|---|---|---|---|---|---|---|---|---|
| GFI | RMR | RMSEA | NFI | TLI | CFI | |||
| Judgment standard | <3 | >0.9 | <0.05 | <0.05 | >0.9 | >0.9 | >0.9 | |
| Hotel image | 3062.838 | 2.601 | 0.98 | 0.015 | 0.041 | 0.987 | 0.992 | 0.985 |
| Room service | 2347.426 | 2.811 | 0.959 | 0.017 | 0.035 | 0.917 | 0.945 | 0.908 |
| Catering service | 2216.888 | 1.209 | 0.942 | 0.047 | 0.036 | 0.963 | 0.971 | 0.969 |
| Employee quality | 2399.591 | 2.712 | 0.912 | 0.043 | 0.049 | 0.912 | 0.953 | 0.916 |
| Support system | 1467.463 | 2.638 | 0.971 | 0.031 | 0.036 | 0.936 | 0.959 | 0.971 |
| Performance ratio | 1690.954 | 2.723 | 0.919 | 0.036 | 0.032 | 0.914 | 0.969 | 0.911 |
According to the judgment criteria of the fitting indicators of the validation factors and the test results in Table 4, it can be seen that the fitting indicators of each dimension passed the indicator validation criteria. It indicates that the hotel image, room service, food and beverage service, staff quality, support system and cost-effectiveness dimensions of the scale have a good fit fit, and the reasonableness of the structural validity has been further verified, i.e., the scale has a good structural validity.
Firstly, the content of the scale was adjusted, and the answers in the scale were coded in SPSS, from disliking to liking the scoring value of 1~5, and then each variable representing the degree of functional need was categorized in accordance with the classification table of the KANO model.The classification criteria of the evaluation results of the KANO model are shown in Table 5. Among them, A, O, M, I, R, and Q represent charming attributes, desired attributes, necessary attributes, undifferentiated attributes, reverse attributes, and suspicious attributes, respectively.
Classification criteria for evaluation results of Kano model
| Function/service | Negative problem | |||||
|---|---|---|---|---|---|---|
| Dislike (1 point) | Tolerable (2 point) | Indifferent (3 point) | It should be (4 point) | Like (5 point) | ||
| Positive problem | Dislike (1 point) | Q | R | R | R | R |
| Tolerable (2 point) | M | I | I | I | R | |
| Indifferent (3 point) | M | I | I | I | R | |
| It should be (4 point) | M | I | I | I | R | |
| Like (5 point) | O | A | A | A | O | |
Based on the classification criteria in Table 5, a summary of the KANO model analysis results is obtained as shown in Table 6.
Kano model analysis results
| Secondary indicator | A | O | M | I | R | Q | Classification result | Better | Worse |
|---|---|---|---|---|---|---|---|---|---|
| X11 | 51.00% | 16.00% | 5.00% | 25.00% | 1.00% | 2.00% | A | 69.07% | -21.65% |
| X12 | 37.00% | 24.00% | 15.00% | 21.00% | 3.00% | 0.00% | A | 62.89% | -40.21% |
| X13 | 11.00% | 21.00% | 14.00% | 47.00% | 7.00% | 0.00% | I | 34.41% | -37.63% |
| X21 | 15.00% | 21.00% | 45.00% | 12.00% | 6.00% | 1.00% | M | 38.71% | -70.97% |
| X22 | 48.00% | 13.00% | 16.00% | 14.00% | 8.00% | 1.00% | A | 67.03% | -31.87% |
| X23 | 25.00% | 32.00% | 18.00% | 17.00% | 6.00% | 2.00% | O | 61.96% | -54.35% |
| X24 | 21.00% | 41.00% | 11.00% | 18.00% | 9.00% | 0.00% | O | 68.13% | -57.14% |
| X31 | 21.00% | 43.00% | 12.00% | 17.00% | 6.00% | 1.00% | O | 68.82% | -59.14% |
| X32 | 22.00% | 39.00% | 18.00% | 15.00% | 4.00% | 2.00% | O | 64.89% | -60.64% |
| X33 | 39.00% | 16.00% | 24.00% | 18.00% | 2.00% | 1.00% | A | 56.70% | -41.24% |
| X41 | 22.00% | 11.00% | 44.00% | 15.00% | 7.00% | 1.00% | M | 35.87% | -59.78% |
| X42 | 17.00% | 21.00% | 43.00% | 13.00% | 6.00% | 0.00% | M | 40.43% | -68.09% |
| X43 | 12.00% | 15.00% | 21.00% | 47.00% | 5.00% | 0.00% | I | 28.42% | -37.89% |
| X44 | 19.00% | 24.00% | 12.00% | 42.00% | 3.00% | 0.00% | I | 44.33% | -37.11% |
| X45 | 48.00% | 14.00% | 21.00% | 12.00% | 5.00% | 0.00% | A | 65.26% | -36.84% |
| X46 | 24.00% | 11.00% | 47.00% | 10.00% | 7.00% | 1.00% | M | 38.04% | -63.04% |
| X51 | 16.00% | 13.00% | 48.00% | 21.00% | 2.00% | 0.00% | M | 29.59% | -62.24% |
| X52 | 21.00% | 18.00% | 18.00% | 39.00% | 4.00% | 0.00% | I | 40.63% | -37.50% |
| X53 | 12.00% | 47.00% | 11.00% | 24.00% | 5.00% | 1.00% | O | 62.77% | -61.70% |
| X61 | 12.00% | 18.00% | 42.00% | 21.00% | 5.00% | 2.00% | M | 32.26% | -64.52% |
In Table 6, the classification results are represented by the attribute corresponding to the highest proportion of one of the six attributes. From Table 6, the classification results can be obtained that a total of five features are charismatic attribute A, which are: brand trust, brand reputation, product comfort, accurate and efficient service delivery, and availability of leisure facilities. It indicates that these features are services that exceed guests’ expectations and are highly desired. There are 5 attributes for desired attribute O, which are: reasonable and cozy room decoration, reasonable and convenient bathroom facilities (X24), professional competence of service staff, kind and friendly attitude of service staff, and sense of dining experience, which indicates that these features are expected by the guests, and satisfaction will increase if they are available, and decrease if they are not available. There are six essential attributes M, namely room cleanliness, hotel location, easy and fast booking, room sound insulation, breakfast quality and rich, cost-effective hotel products, which are essential screening conditions for customers when booking a room. The remaining 4 items of hotel publicity, hotel network quality, public area atmosphere, and high quality meals are undifferentiated needs, which have little effect on customers’ needs.
The visualization and control chart of KANO model is shown in Figure 5. From Figure 5, it can be seen that brand trust has the highest value, which indicates that the increase in customer satisfaction is the highest if there is brand trust. Brand trust has the lowest |Worse| value, which indicates that the decrease in satisfaction is the lowest if there is a lack of brand trust, which indicates that many users in China have a higher tolerance for hotels without name recognition compared to name brand hotels. Room tidiness has the highest |Worse| value, which suggests that hotel customers have the highest level of satisfaction decline in the case of untidy rooms.The hotel network quality has the lowest |Better| value, which indicates that the increase in customer satisfaction is the smallest of all variables when the hotel network is available and stable.
Better-|Worse| coefficient
Based on the main content of the hotel industry information construction and the previous customer demand priority analysis of the hotel, this paper designs the following hotel industry information management innovation strategy:
In the highly competitive hospitality market, differentiated positioning is an effective way to enhance competitiveness.Hotels can differentiate themselves by creating a distinctive brand image and providing personalized services.For example, theme hotels, couple hotels, and other special hotel types are designed to meet the different needs of different customers.
Digital services are an important direction of management innovation in the hotel industry. By introducing digital service means such as self-service check-in and intelligent room control, hotels can provide customers with a more convenient and efficient service experience. At the same time, digital services can decrease the hotel’s labor expenses and enhance operational efficiency. Room cleanliness is the key to guest satisfaction, hotels should use intelligent monitoring systems to ensure that the rooms meet the cleanliness standards, and continuously improve the quality of cleaning services through quality sampling and other means.
Customized experiences are key to improving customer satisfaction and loyalty.Hotels can analyze customers’ preferences and behavioral habits through big data to provide personalized services and customized menus.For instance, suggesting food based on customers’ preferences, altering room amenities based on customers’ sleeping habits, and so on. Meanwhile, through investigation, segmentation and positioning, hotels should study the preferences and behavioral characteristics of potential consumer groups, tap into the integration of regional culture and natural resources, and design personalized products that match the target clientele.
Social marketing is an important means for the hotel industry to expand its market and attract customers.Hotels can attract the attention and participation of potential customers by releasing tourism information, sharing customer experiences, and conducting interactive activities through social media platforms.At the same time, social media marketing can also help hotels build their brand image and gain word-of-mouth benefits. In branding, it is important to focus on the synergy of vision and interaction, highlight the visual effect of brand image from representative colors, store labels, environmental design, etc., and strengthen the interactive experience, so that the corporate culture and customer attitudes identify with each other.
Energy saving and environmental protection are inevitable requirements for the sustainable development of the hotel industry.Hotels can reduce energy consumption and emissions through the use of sustainable materials and technologies, optimizing energy use, and other ways to achieve green management.The hotel’s brand image and sense of social responsibility can be enhanced by energy saving and environmental protection at the same time.
This paper realizes the customer demand prioritization in the hotel industry based on Kano model, and designs the innovation strategy of information management in the hotel industry based on the main content of information construction in the hotel industry.
First of all, when designing the questionnaire, this paper determines the customer demand scale, including six primary indicators of hotel image, room service, catering service, staff quality, support system, and cost-effectiveness, as well as 20 secondary indicators. The Cronbach’s α coefficient of the subscales under each dimension is greater than 0.8, indicating that the sub-dimension scales of the questionnaire have a more desirable reliability. The KMO value of each dimension is greater than 0.8, the approximate chi-square in Bartlett’s test of sphericity is large enough, the significance level is 0.000 < 0.05, and the fitting indexes of each dimension have passed the index validation criterion, which indicates that the hotel image, room service, food and beverage service, staff quality, support system, and cost-effectiveness dimensions of the scales have a better fit, i.e., the scales have good structural validity.
The Kano model analysis shows that charm attributes A, expectation attributes O, must-have attributes M, and no-difference attributes I have 5, 5, 6, and 4 items, respectively. Among them, brand trust possesses the highest Better value and the lowest |Worse| value, which indicates that brand trust has the highest increase in customer satisfaction, and the decrease in customer satisfaction is the lowest in the absence of brand trust, which suggests that customers are more tolerant of hotels without name recognition compared to name brand hotels. Room cleanliness has the highest |Worse| value, indicating that hotel customers’ satisfaction decreases to the highest degree when the room is untidy. The hotel network quality is the lowest value, which indicates that customer satisfaction increases the least when the hotel network is used stably. This proposal proposes an innovative strategy for information management in the hotel industry to provide theoretical support and practical guidance for its sustainable development.
This research was supported by the Intermediate Results of the 2021 Shaanxi Higher Education Teaching Reform Research Project - “Research on Deepening the Industry-Education Integration Mechanism Construction in Higher Vocational Education - Taking Hotel Management and Digital Operation Major as an Example” (Project No.: 21GY024).