An online statistical analysis of the hotel management and operation performance model

Hui Fang; Yangli Ou; Tianyi Fu

Journal & Issue Details

Applied Mathematics and Nonlinear Sciences

Journal Details

Format: Journal
eISSN: 2444-8656
First Published: 01 Jan 2016
Publication timeframe: 2 times per year
Languages: English

For the hotel service industry, providing customers with high-quality services and meeting their individual needs has become the key point for enterprises to win in market competition and ensure growth of profit. In the fierce market competition, if a hotel wants to gain a dominant position and achieve long-term development, it must establish a set of effective customer relationship management (CRM) systems to guide the practice. Of these, one of the most critical aspects is to strengthen customer information management [1]. The customer management system CRM is a brand new management concept, which enables enterprises to analyse and mine customer information to accurately identify customer needs; this is of great significance to improve customer service quality, customer satisfaction and hotel profits [2].

The Gartner Group first proposed the concept of CRM: CRM actually helps companies to communicate with customers in an all-round way at the management level, so as to maximise the interests of customers. Since then, many experts and scholars at home and abroad have begun to study CRM [3]. Stanley A. Brown, Jill Dych and Joe Peppard examine the implementation of CRM in the telecommunications, retail and financial industries. On the basis of summarising practical experience, many foreign scholars have expressed their opinions on the problems existing in the implementation of CRM. These research results provide a certain reference point for Chinese enterprises to implement CRM. As a solution, CRM covers the most advanced computer technologies such as data mining, E-Business, data warehouse and related hardware technologies. With the development of information technology and the popularisation of the Internet, CRM has gradually become a new management model. Customer Relationship Management System (Customer Relationship MIS) is an important part of it [4]. CRM, as a professional enterprise management software, integrates the management concepts of sales and publicity. This is especially the case in Western countries. In terms of computer information management and network applications, the United States is ahead of the world in its informatisation construction in multiple industries. On the one hand, the United States has expensive human resources as a representative of Western countries. Because of this, it actively introduces computer information technology to improve the work efficiency. On the other hand, its computer technology is also directly used in the world. The construction of information resources in the United States started early and developed rapidly, and has now reached a fairly high level; whereas the construction of information resources in China has just started and is still in its infancy, but is developing rapidly. According to statistics, the high-end hotel industry (four-star, five-star hotel, etc.) in Western developed countries began in the 1970s, and the latest computer management system was introduced to the design and implementation of the WEB-based hotel information management system and information management in the daily affairs of the hotel. With the popularisation and application of computer network technology (Computing Network, Computer Network), many foreign high-end hotels have provided global reservation services and 24-h Internet reservations for rooms [5]. Compared with developed countries in Europe and the United States, China's business hotel industry, especially the small and medium-sized private business hotels, lags behind in management mechanism and management mode, dealing with the groping state of learning while walking. However, most of the high-end business hotels in China have the background of foreign capital, because the management model and management technology are also related to the management model and software technology introduced abroad [6, 7, 8, 9, 10]. With China's entry into World Trade Organisation (WTO), Chinese enterprises will directly face the competition of foreign multinational corporations [11, 12]. In order to be invincible in the fierce international competition, the Chinese must improve their management and technical levels as soon as possible. One of the most critical issues is how to strengthen management and reduce costs [13, 14, 15].

Therefore, based on the implementation of CRM, this paper aimed to design and develop a set of CRM hotel management system that meets the needs of small and medium-sized hotels to realise the functions of departmental information sharing, customer information sorting and value mining, and improve hotel service quality.

Related overview

2.1

Performance

Performance is a defining term between performance and work effect, efficiency. Literally analysed, ‘performance’ is ‘industry’, which reflects the profit goal of the enterprise, ‘efficiency’ is ‘effect’, ‘efficiency’, ‘attitude’ and ‘practice’ is ‘square’, ‘law’, It reflects the maturity of enterprise management. From the perspective of management, performance is the result of various actions that an organisation or a person adopts in order to achieve certain goals. It includes both direct and indirect results. In these achievements, there are both tangible results and intangible factors [16, 17, 18, 19, 20]. Performance view is a management phenomenon. Performance and effectiveness are two concepts at different levels [21]. Performance is multidimensional, multifactorial and dynamic. The multidimensionality of performance requires evaluators to evaluate from multiple aspects and angles; the multi-factor of performance requires that evaluators must fully consider the external environment, personal wisdom, corporate emotion, corporate technology, corporate knowledge structure, corporate incentives and other influencing factors; the dynamic nature of performance requires that evaluators must evaluate from the perspective of development and contingency [22, 23, 24]. Modern enterprise performance management theory believes that enterprise performance is divided into three levels: individual performance, departmental performance and organisational performance.

2.2

Performance evaluation analysis method

2.2.1

Analytic hierarchy process (AHP)

After the establishment of the performance index system for star-rated hotel managers, the next step is to construct a judgement matrix. It should be noted that the elements are compared to determine their importance, which is the work to be done when judging the matrix [25, 26, 27]. Using the AHP, each evaluation index is first decomposed into a number of basic molecules that are relatively independent and have a certain relationship with each other; then the expert scoring method is used to calculate the weight value of each layer index; finally, the comprehensive evaluation value is obtained through the consistency test. The specific process is to compare the relevant factors at the same level with each other, and analyse the relevant factors at the next level on the basis of the indicators at the previous level. Taking Ai and Aj as the two relevant indicators in the indicator system, and assigning it as Aij according to the influence of Ai on Aj, the judgment matrix T is constructed as follows: (1) $T = (\begin{matrix} A_{11} & \dots & A_{\ln} \\ ⋮ & ⋱ & ⋮ \\ A_{m 1} & \dots & A_{mn} \end{matrix})$ T = \left({\matrix{{{A_{11}}} & \cdots & {{A_{\ln}}} \cr \vdots & \ddots & \vdots \cr {{A_{m1}}} & \cdots & {{A_{mn}}} \cr}} \right)

According to the judgement matrix constructed above, the weight of each evaluation index in the index layer of the star-rated hotel management personnel performance evaluation system is calculated. The calculation steps are as follows:

Step 1: Calculate the eigenvalue λ;

Step 2: Get the feature vector that is the weight;

Step 3: The eigenvector X solved in Step 2 corresponds to each index in the index system, so as to obtain the weight of each evaluation index in the index system. The specific steps for calculating the weight of each indicator are as follows:

Step 1: Find the product of the multiplication of the elements of each row in the judgement matrix T, and the equation is as follows: (2) $S_{i} = \prod_{j = 1}^{n = 1} A_{ij} (i = 1, 2, 3, \dots n)$ {S_i} = \mathop {\prod\limits_{j = 1}^{n = 1}}\limits_ {A_{ij}}\left({i = 1,2,3, \ldots n} \right)

Step 2: Let T be an n-order matrix, then solve the n-th power, and its equation is as follows: (3) ${\bar{V}}_{i} = \sqrt[n]{S_{i}}$ {\bar V_i} = \root n \of {{S_i}}

Step 3: For normalisation, the equation is as follows: (4) $V_{i} = \frac{{\bar{V}}_{i}}{\sum_{i = 1}^{m} {\bar{V}}_{i}}$ {V_i} = {{{{\bar V}_i}} \over {\sum\nolimits_{i = 1}^m {{\bar V}_i}}}

It is very important to do the consistency test. Since the object to be evaluated may have both complex and variable attributes at the same time, the constructed judgement matrix has unreasonable phenomena, and there will be large deviations, so consistency testing must be carried out. Overall consistency is required. Consistency test is an indispensable link, and the operation steps are as follows:

Step 1: Set λ max as the maximum eigenvalue of the judgement matrix T, and combine the consistency equation of the reciprocal judgement matrix given by Saaty: (5) $CI = \frac{λ_{max} - n}{n - 1}$ {\rm{CI}} = {{{\lambda _{\max}} - n} \over {n - 1}}

Step 2: Calculate the test coefficient CR: (6) $CR = \frac{CI}{RI}$ CR = {{CI} \over {RI}}

2.2.2

Fuzzy comprehensive evaluation method

1. Fuzzy set and membership function. Any mapping from the universe X to the closed interval [0, 1]: (7) $μ_{A} : X \to [0, 1] x \to μ_{A} (x)$ {\mu _A}:X \to \left[ {0,1} \right]x \to {\mu _A}\left(x \right)

When the universe of discourse X is a finite set, then the fuzzy set A on X can be written as: (8) $A = {(x, μ_{A} (x)) x \in X}$ A = \left\{{\left({x,{\mu _A}\left(x \right)} \right)x \in X} \right\} (9) $A = \sum_{i = 1}^{n} \frac{μ_{A} (x_{i})}{x_{i}} = \frac{μ_{A} (x_{1})}{x_{1}} + \frac{μ_{A} (x_{2})}{x_{2}} + \dots + \frac{μ_{A} (x_{n})}{x_{n}}$ A = \sum\limits_{i = 1}^n {{{\mu _A}\left({{x_i}} \right)} \over {{x_i}}} = {{{\mu _A}\left({{x_1}} \right)} \over {{x_1}}} + {{{\mu _A}\left({{x_2}} \right)} \over {{x_2}}} + \ldots + {{{\mu _A}\left({{x_n}} \right)} \over {{x_n}}}

2. Ordinal notation: (10) $A = {(x_{1}, μ_{A} (x_{1})), (x_{2}, μ_{A} (x_{2})), \dots, (x_{n}, μ_{A} (x_{n}))}$ A = \left\{{\left({{x_1},{\mu _A}\left({{x_1}} \right)} \right),\left({{x_2},{\mu _A}\left({{x_2}} \right)} \right), \ldots,\left({{x_n},{\mu _A}\left({{x_n}} \right)} \right)} \right\}

3. It is represented by the vector method, as follows: (11) $A = \int_{x \in X} \frac{μ_{A} (x)}{x}$ A = \mathop {\int_{x \in X}}{{{\mu _A}\left(x \right)} \over x}

For a fuzzy set A, B on the universe X.

1. Call the Fuzzy set C(A, B), D(A, B) the “union” and “intersection” of A and B, that is: (12) $C = (A \cup B) (x) = max {A (x), B (x)} = A (x) \lor B (x)$ C = \left({A \cup B} \right)\left(x \right) = \max \left\{{A\left(x \right),B\left(x \right)} \right\} = A\left(x \right) \vee B\left(x \right) (13) $D = (A \cap B) (x) = \min {A (x), B (x)} = A (x) \land B (x)$ D = \left({A \cap B} \right)\left(x \right) = \min \left\{{A\left(x \right),B\left(x \right)} \right\} = A\left(x \right) \wedge B\left(x \right)

The corresponding membership degrees μc(x), μd(x) are defined as: (14) $μ_{C} (x) = max {μ_{A} (x), μ_{B} (x)}$ {\mu _C}\left(x \right) = \max \left\{{{\mu _A}\left(x \right),{\mu _B}\left(x \right)} \right\} (15) $μ_{D} (x) = \min {μ_{A} (x), μ_{B} (x)}$ {\mu _D}\left(x \right) = \min \left\{{{\mu _A}\left(x \right),{\mu _B}\left(x \right)} \right\}

2. Fuzzy set A c is the complement or complement of A, and its membership degree is: (16) $μ_{A^{c}} (x) = 1 - μ_{A} (x)$ {\mu _{{A^c}}}\left(x \right) = 1 - {\mu _A}\left(x \right)

First, quantify each element on R, then establish the degree of membership, and construct the relationship matrix on this basis. (17) $R = [\begin{matrix} (R X_{1}) \\ (R X_{2}) \\ \dots \\ (R X_{n}) \end{matrix}] = {[\begin{matrix} r_{11} & r_{12} & \dots & r_{1 m} \\ r_{21} & r_{22} & \dots & r_{2 m} \\ \dots & \dots & \dots & \dots \\ r_{n 1} & r_{n 2} & \dots & r_{nm} \end{matrix}]}_{nm}$ R = \left[ {\matrix{{\left({R{X_1}} \right)} \cr {\left({R{X_2}} \right)} \cr \ldots \cr {\left({R{X_n}} \right)} \cr}} \right] = {\left[ {\matrix{{{r_{11}}} & {{r_{12}}} & \ldots & {{r_{1m}}} \cr {{r_{21}}} & {{r_{22}}} & \ldots & {{r_{2m}}} \cr \ldots & \ldots & \ldots & \ldots \cr {{r_{n1}}} & {{r_{n2}}} & \ldots & {{r_{nm}}} \cr}} \right]_{nm}}

The resulting vector is obtained from the calculation. Combining matrices U and R yields: (18) $UR = (u_{1}, u_{2}, \dots u_{n}) {[\begin{matrix} r_{11} & r_{12} & \dots & r_{1 m} \\ r_{21} & r_{22} & \dots & r_{2 m} \\ \dots & \dots & \dots & \dots \\ r_{n 1} & r_{n 2} & \dots & r_{nm} \end{matrix}]}_{nm} = (b_{1}, b_{2}, \dots b_{m}) = B$ UR = \left({{u_1},{u_2}, \ldots {u_n}} \right){\left[ {\matrix{{{r_{11}}} & {{r_{12}}} & \ldots & {{r_{1m}}} \cr {{r_{21}}} & {{r_{22}}} & \ldots & {{r_{2m}}} \cr \ldots & \ldots & \ldots & \ldots \cr {{r_{n1}}} & {{r_{n2}}} & \ldots & {{r_{nm}}} \cr}} \right]_{nm}} = \left({{b_1},{b_2}, \ldots {b_m}} \right) = B

2.3

Performance evaluation and performance management

The core of performance management is performance evaluation and performance evaluation, which are the three elements of performance management as we often say [28, 29, 30]. As a bridge and link between performance management and performance evaluation, performance evaluation plays a vital role in the entire performance management process, and its results directly affect the final expected effect. Performance management is a difficult point in modern enterprise management. The difficulty is rooted in the question of performance evaluation, and how to make use of performance evaluation methods to improve both personal performance and organisational performance, so as to improve the realisation of corporate strategic goals and their impact on human resources [31, 32, 33, 34, 35]. It is difficult for managers. Therefore, how to effectively evaluate the performance of employees has become a problem worth exploring. This paper first introduces performance management and its related concepts, then analyses some performance management problems commonly existing in China's enterprises and, finally, proposes solutions.

2.4

Definition and connotation of CRM

First of all, CRM is a management concept that originated from the Western marketing theory and originated and developed in the United States. The main goal of CRM is to provide enterprises with a customer-centred management model, so that enterprises can improve their competitiveness through effective management of customers, and then achieve profitability. CRM emphasises customer satisfaction and value creation of effective communication between enterprises and customers through CRM. It helps enterprises to obtain higher profits, provide customers with better services, and ultimately achieve a win–win situation for enterprises and customers. At the same time, it also brings about good reputation and image to the enterprise. Therefore, CRM has become one of the prime focuses of today's business community. CRM is a brand new concept. Its purpose is to improve the service level of enterprises to customers. It is a complex system which involves many aspects, the most important of which is how to establish an effective management mechanism. Third, CRM can collect more sales data to help business managers better understand customer information. Data modelling and analysis technology can extract useful value information from a large amount of business data, reduce enterprise management costs and can also convert stored information into analysis information. As a solution, CRM covers cutting-edge computer technologies such as Web technology, data analysis and E-Business technology. The connotation of CRM includes information technology, relationship value and customer value.

CRM for hotel management system

3.1

Hotel CRM system mode

The CRM system is mainly designed to collect customer consumption data, which includes the customer itself, and the activity information between the customer and the enterprise. A large amount of data is generated in the process of data consumption. After data processing and integration, these data can help the internal personnel of the enterprise to conduct profit analysis, consumer group analysis and product value-added sales. These data have the characteristics of large amount of data, various types and wide distribution, which pose certain difficulties for data analysis. Traditional data processing methods can no longer meet the needs of modern hotel management, and data mining can effectively solve this problem. The collection of the system is mainly to collect information related to customers through the network, telephone and front desk, and to integrate, analyse and mine the data through the database of the information system, mainly for customer categories, customer value and customer satisfaction. To support the decision-making management of the hotel, Figure 1 shows the CRM analysis process based on the hotel network.

Flow chart of hotel CRM analysis. CRM, customer relationship management

3.2

System database design

The core of performance management is performance evaluation and performance evaluation, which are the three elements of performance management as we often say. As a bridge and link between performance management and performance evaluation, performance evaluation plays a vital role in the entire performance management process, and its results directly affect the final expected effect. Performance management is a difficult point in modern enterprise management. The difficulty is rooted in the question of performance evaluation, and how to make use of performance evaluation methods to improve both personal performance and organisational performance, so as to improve the realisation of corporate strategic goals and their impact on human resources. It is difficult for managers. Therefore, how to effectively evaluate the performance of employees has become a problem worth exploring. This paper first introduces performance management and its related concepts; then analyses some performance management problems commonly existing in China's enterprises and, finally, proposes solutions.

3.3

System user analysis

Before carrying out specific functional analysis on it, it is necessary to clarify the various users of the system and the corresponding functional requirements. This system is mainly aimed at the following types of users: (1) hotel customers, (2) hotel staff, (3) senior management of the hotel and (4) the system administrator. For hotel customers, including those who have already stayed at the hotel and potential customers who can conduct various information inquiries, consultations and reservations for the hotel through the system, the system also provides corresponding customer membership management functions. For the general staff of the hotel, the system can be used for the reception, general customer information and query management, customer check-in and check-out management, the corresponding financial information management and other functions.

3.4

Design of the specific index system for the performance evaluation system of star-rated hotel managers

3.4.1

Constructing the AHP judgement matrix for star-rated hotels

Judging the importance of the elements of the previous level for each element of the star hotel index weight from F11 to F42, and expressing it with numerical values, a judgement matrix is formed. The weight survey scale of the judgement matrix is as follows: assuming X is the element X1 in the layer and is related to the lower layer elements Y1, Y2…Y, then the AHP judgement matrix weight survey scale for star-rated hotels is judged, where dij(i,j,2,3 … m) represents the proportional scale of the importance of the lower layer Di and Dj relative to the upper layer element Ci: (19) $X = {(d_{ij})}_{m \times n}$ X = {\left({{d_{ij}}} \right)_{m \times n}}

Calculate the product m_i of the elements of each row of the judgement matrix X (20) $m_{i} = \prod_{j = 1}^{m} d_{ij}$ {m_i} = \prod\limits_{j = 1}^m {d_{ij}}

Compute the m-root of (21) $m_{i} \bar{W} = \sqrt[m]{m_{i}} (i = 1, 2 \dots m)$ {m_i}\bar W = \root m \of {{m_i}} \left({i = 1,2 \ldots m} \right)

Normalise the vector, that is, (22) $W_{j} = \frac{{\bar{w}}_{j}}{\sum_{j = 1}^{m} {\bar{w}}_{j}} (j = 1, 2, \dots, m)$ {W_j} = {{{{\bar w}_j}} \over {\sum\nolimits_{j = 1}^m {{\bar w}_j}}}\;\left({j = 1,2, \ldots,m} \right)

In order to ensure the credibility of the calculated weights, the consistency test of the star-rated hotel judgement matrix is required.

First, calculate the consistency index: (23) $CI = \frac{λ_{max} - m}{m - 1}$ CI = {{{\lambda _{\max}} - m} \over {m - 1}}

λ_max is the characteristic root of the judgement matrix, and m is the number of elements of the judgement matrix, calculated as: (24) $λ_{max} = \sum_{j = 1}^{m} \frac{{(WD)}_{i}}{mW}$ {\lambda _{\max}} = \sum\limits_{j = 1}^m {{{{(WD)}_i}} \over {mW}}

W D_i represents the i-th element in the W D matrix: (25) $\begin{array}{l} WD & = [\begin{matrix} W_{1} W_{2} & \dots & W_{m} \end{matrix}] \times [\begin{matrix} d_{11} & d_{12} & \dots & d_{1 m} \\ d_{21} & d_{22} & \dots & d_{2 m} \\ \dots & \dots & \dots & \dots \\ d_{ml} & d_{m 2} & \dots & d_{mm} \end{matrix}] \\ W & = [\begin{matrix} W_{1} W_{2} & \dots & W_{m} \end{matrix}] \end{array}$ \matrix{{WD} \hfill & {= \left[ {\matrix{{{W_1}{W_2}} & \ldots & {{W_m}} \cr}} \right] \times \left[ {\matrix{{{d_{11}}} & {\;{d_{12}}} & \ldots & {{d_{1m}}} \cr {{d_{21}}} & {\;{d_{22}}} & \ldots & {{d_{2m}}} \cr \cdots & \cdots & \cdots & \ldots \cr {{d_{ml}}} & {{d_{m2}}} & \ldots & {{d_{mm}}} \cr}} \right]} \hfill \cr {\,\,W} \hfill & {= \left[ {\matrix{{{W_1}{W_2}} & \ldots & {{W_m}} \cr}} \right]} \hfill \cr}

W_i is the i-th element in W. Then, calculate the random consistency ratio: (26) $CR = \frac{CI}{RI}$ CR = {{CI} \over {RI}}

Calculate the product of the elements of each row of the judgement matrix A: (27) $m_{1} = \prod_{j = 1}^{4} d_{1 j} (j = 1, 2, 3, 4)$ {m_1} = \mathop {\prod\limits_{j = 1}^4}\limits_ {d_{1j}}\left({j = 1,2,3,4} \right) (28) $m_{2} = \prod_{j = 1}^{4} d_{2 j} (j = 1, 2, 3, 4)$ {m_2} = \mathop {\prod\limits_{j = 1}^4}\limits_ {d_{2j}}\left({j = 1,2,3,4} \right) (29) $m_{3} = \prod_{j = 1}^{4} d_{3 j} (j = 1, 2, 3, 4)$ {m_3} = \mathop {\prod\limits_{j = 1}^4}\limits_ {d_{3j}}\left({j = 1,2,3,4} \right) (30) $m_{4} = \prod_{j = 1}^{4} d_{4 j} (j = 1, 2, 3, 4)$ {m_4} = \mathop {\prod\limits_{j = 1}^4}\limits_ {d_{4j}}\left({j = 1,2,3,4} \right)

Compute the 4th root of a_i: (31) ${\bar{a}}_{1} = \sqrt[4]{m_{1}} (i = 1, 2, 3, 4)$ {\bar a_1} = \root 4 \of {{m_1}} \left({i = 1,2,3,4} \right) (32) ${\bar{a}}_{2} = \sqrt[4]{m_{2}} (i = 1, 2, 3, 4)$ {\bar a_2} = \root 4 \of {{m_2}} \left({i = 1,2,3,4} \right) (33) ${\bar{a}}_{3} = \sqrt[4]{m_{3}} (i = 1, 2, 3, 4)$ {\bar a_3} = \root 4 \of {{m_3}} \left({i = 1,2,3,4} \right) (34) ${\bar{a}}_{4} = \sqrt[4]{m_{4}} (i = 1, 2, 3, 4)$ {\bar a_4} = \root 4 \of {{m_4}} \left({i = 1,2,3,4} \right)

Consistency check CR = CI/RI. Among them, RI = 0.9; (35) $λ_{max} = \sum_{i = 1}^{4} \frac{{(WD)}_{i}}{4 {\bar{a}}_{i}} (i = 1, 2, 3, 4)$ {\lambda _{\max}} = \sum\limits_{i = 1}^4 {{{{(WD)}_i}} \over {4{{\bar a}_i}}}\left({i = 1,2,3,4} \right)

System use case analysis

4.1

Use cases of customer information and points management

As far as the customer is concerned, it is necessary to provide the customer's online registration and information entry function information first, so that the customer can modify the login name and password, query historical records and points, and so on. Customers can also fill in ID card information, name information and historical check-in records through their mobile phones; the hotel can set the corresponding discount parameters according to different customer categories and category levels, and the hotel management personnel can upgrade the level through points; W means automatic upgrade. The hotel can set room priorities and reservation retention periods that are different from the customer's level, make smart entries for users' violations of laws and regulations, and establish and manage user blacklists and early warning functions for suspicious user information. In addition, there must be a security measure to ensure that the hotel information will not be illegally stolen or tampered with during the transmission process. The design and implementation of the hotel information management system is developed with a star-rated hotel as an example. Use case functional requirements are given in Table 1.

Table 1

Requirement analysis of online registration and input information use case

Use case functional requirements table

Use case description	Online registration and entry information
Use case description	Provide hotel customers with the function of online registration of hotel members and personal check-in information
Detailed analysis of use cases	Fill in the registration information online Fill in the check-in information online Check-in information change Information submission and background processing
Use case usage restrictions	Customers only
Information query instructions	Specifically provided by other use cases
Supplementary description of needs	No

4.2

Analysis of use cases for front office business management

This function is for the exclusive use of the first-class reception staff at the front desk of the hotel. It can enable the hotel front desk staff to quickly grasp the basic situation and needs of the guests during the busy reception process, and make timely and correct responses, thereby improving the efficiency of the hotel, reducing the workload of manual services and simplifying the information management of the hotel saves costs. The system can be divided into two parts: the foreground and the background. The front part includes guest information management module, guest room management module, reservation information management module and so on; while the background part includes customer information management module and information statistics management module. The functions of this system for hotel front desk staff include real-time check-in and reservation status of rooms, registration of customer check-in information, registration of customer check-out information and registration of settlement information (Table 2).

Table 2

Demand analysis of customer status query use case

Use case functional requirements table

Use case description	Online registration and entry information
Use case description	Provide real-time check-in, reservation and other status query of all rooms
Detailed analysis of use cases	Real-time room check-in information query Room recent reservation information query Room rate information query Discount information query
Use case usage restrictions	Hotel management only
Information query instructions	Display brief information of check-in customers
Supplementary description of needs	For customers who have checked out but have not been arranged, so cannot provide instant check-in Rooms are flagged in query results

4.3

Analysis of use cases for guest room configuration management

Room configuration management is to provide hotel managers with the function of configuring and managing all rooms. Specifically, the room configuration work requires hotel management personnel to manage the room number and the control card of the rooms on each floor of the hotel, provide information for different types of rooms, set prices, and set discounts and discounts management of internal item setting information. At present, most hotels in China use a manual configuration management, which is inefficient and prone to errors. With the development of information technology, the computer management system has become an indispensable part of hotel management. The computer management information system can improve management efficiency and quality. For a business hotel, it is necessary to set the corresponding room number according to the floor and the number of rooms, and at the same time register the information about the access control card corresponding to each room. At the same time, different types of rooms have different information marks, price settings and preferential discounts. The hotel management needs to be set and changed uniformly, and the information of all items in the room needs to be registered accordingly, which can be managed in the system.

4.4

Build a performance hierarchy

The hierarchical structure of the department is divided into target layer, dimension layer and assessment layer from top to bottom. Combined with the concept of ‘MBO + BSC + KPI’, the performance management objectives of the catering department are decomposed layer by layer: the target layer is the performance management target, and the dimension layer is based on the balanced scorecard dimension. The financial indicators include basic data (income, profit, etc.) and non-financial data such as customer satisfaction, employee satisfaction and other indicators; non-financial indicators mainly include strategic direction, corporate culture and organisational structure. Finally, each indicator is scored and ranked by means of a questionnaire survey. According to a large number of hotel literature and several management interviews, the four dimensions of the Balanced Scorecard have covered the performance appraisal content of five-star hotels, as shown in Figure 2.

The judgement value aij is set to quantify the weight index of the lower layer to the upper layer, and the expert group of 13 managers of Yindu Hotel is rated. According to their own knowledge and understanding of the target layer, 13 hotel management experts assigned corresponding weights to the most important and reasonable indicators, and based on this, they determined the performance management goals and dimensions of the hotel's catering department tasks to be completed. Second, according to the judgement value and weight of each index, calculate the arithmetic mean of 13 elements, convert it into an integer, and then add the integer and the judgement value of each element to obtain the specific assignment of 13 elements. It constitutes a judgement matrix from the dimension layer to the target layer; each element aij represents the importance of i and j relative to the previous level. For example: 1 = (knowledge and skills) = 9, indicating that knowledge and skills are more important than other factors; second, according to the score of each index, it is decided whether to assign the corresponding weight coefficient. Finally, the obtained results of each evaluation level are, respectively, input into the corresponding database. The proportion of each evaluation item is calculated and sorted. For example, a 11 = (financial dimension, financial dimension) = 1 means that the financial dimension and financial dimension are equally important in the performance management of the catering department. Important, for example a 43 = (learning growth dimension, internal process dimension) = 5 means that learning growth dimension and internal process dimension are equally important in the operation and management of the catering department.

By constructing a judgement matrix based on the judgement values scored by 13 hotel experts, the key performance indicators of the hotel are analysed hierarchically. The main steps to determine the weight of the key performance indicators to the target layer are as follows. The first step is to obtain the weight of the lower layer to the upper layer. For the target layer, determine the importance of each dimension of the dimension layer; for each dimension, determine the weights of the key performance indicators at the appraisal level, as shown in Table 3.

Table 3

Weights of the lower layer to the upper layer

	Financial dimension	Customer dimension	Internal process dimension	Learning and growth dimensions

The weight of the dimension layer to the target layer	0.472257890	0.315819567	0.095429432	0.116897369

The assessment layer has weights for each dimension	0.1045968700.2058464670.5331456780.156409467	0.136011560.1290036890.0537044790.681267224	0.6483287900.1220200740.229651679	0.5499448950.240211350.209843689

On the basis of the proportions of various performance indicators that have been obtained, the original proportions are reasonably adjusted according to the actual situation of the catering department, as shown in Table 4.

Table 4

Weights of various types of hotel indicators

Indicator	Type weight coefficient	Adjusted coefficient

Financial dimension	0.47	0.43
Customer dimension	0.31	0.32
Internal process dimension	0.1	0.1
Learning and growth dimension	0.12	0.15
Total	1.00	1.00

4.5

Establishment of hotel performance appraisal index system

Through the investigation, first-hand information such as the financial situation of the hotel and catering department, customer consumption satisfaction, internal operation status, employee training and current status is obtained, the specific values and ratios of the key indicators of the hotel and catering department are basically determined, and the relevant performance indicators are defined. General assessment standards, and then through interviews with 13 experts, to clarify the target value of the key indicators measured in recent years and the changes in assessment standards, to confirm and adjust the target value and evaluation system of the hotel's key performance indicator system, as shown in Table 5.

Table 5

Hotel performance appraisal index system

Indicator type	Key assessment indicators	Annual target value	Index weight	Assessment criteria

Financial dimension	Annual turnover	During the assessment period, the turnover reached 210 million yuan	0.04	6 points for every 1% increase, 8 points for every 1% decrease
	Return on assets	Return on assets Return on assets reached 13% during the assessment period	0.23	10 points for every 1% increase, 10 points for every 1% decrease
	Planned SalesCompletion Rate	During the assessment period, the planned sales at the beginning of the period were successfully completed	0.06	10 points for every 1 increase, 15 points for every 1% decrease
Customer dimensions	Customer Satisfaction	During the assessment period, customers who received random surveys scored an average of 85 points on the catering segment	0.05	5 points will be added for every 5 points increased, 10 points will be deducted for every 5 points decreased, and no points will be added or decreased if the fluctuation is less than 5 points.
Customer dimensions	Customer Complaint Resolution Rate	Customer complaints are resolved during the assessment period	0.04	15 points for every 1% reduction
Internal business process dimensions	Safety and health compliance rate	During the assessment period, there were no safety incidents and no customer complaints against hygiene	0.06	20 points for a safety incident and 12 points for each health complaint
	Incompleteness rate of low-value consumable items	The low-value consumables in good condition at the end of the assessment period account for 75% of all low-value consumables	0.01	2 points for every 1% increase, 2 points for every 1% decrease
	Incompleteness of fixed assets	Fixed assets that are still in good condition at the end of the assessment period account for 95% of all fixed assets	0.03	5 points for every 1% increase, 10 points for every 1% decrease
Learning and growth dimensions	Employee training pass rate	The employees who participated in the training and were able to work normally during the assessment period accounted for 90% of all employees who participated in the training	0.08	5 points for every 1% increase, 5 points for every 1% decrease
	employee turnover	During the assessment period, employees who have undergone job adjustment and change within the catering department accounted for 45% of all employees	0.03	5 points for every 1% decrease, 10 points for every 1% increase
	Employee turnover rate	Employees who voluntarily resigned during the assessment period accounted for 35% of all employees	0.04	5 points for every 1% decrease, 8 points for every 1% increase

System database design

The system database is responsible for storing all the background data information of the information management system and providing data support functions to the application server. Therefore, the quality of the system database directly affects the efficiency and performance of the entire system. With the continuous development of computer technology, the computer database has become one of the indispensable components of modern information society. It has been widely valued for its high efficiency and reliability. K-means algorithm is used to select K initial cluster centres and calculate the distance between the customer data set and the cluster centres one by one. The minimum clustering method is used to allocate samples to form a certain cluster corresponding to the cluster centre. According to the hotel CRM design process, in order to improve the scalability and maintainability of the hotel management system, the hotel's functional module system is designed. The hotel business module is divided into two parts: front-end service and back-end service, mainly including travel booking, passenger consumption, customer analysis, and so on. Figure 3 is the system function structure diagram.

System functional structure diagram. CRM, CRM, customer relationship management

Assuming that there are n decision-making units (DMUs), and each DMU has m inputs and s outputs, which are represented by input variables x and output variables y, respectively, the general expression of the slacks-based measure (SBM) model based on the assumption of variable returns to scale is: (36) $ρ^{*} = \min ρ = \frac{1 - \frac{1}{m} \sum_{j = 1}^{m} \frac{s_{i}^{-}}{x_{i 0}}}{1 + \frac{1}{s} \sum_{r = 1}^{s} \frac{s_{r}^{+}}{y_{r 0}}}$ {\rho ^*} = \min \rho = {{1 - {1 \over m}\sum\limits_{j = 1}^m {{s_i^ -} \over {{x_{i0}}}}} \over {1 + {1 \over s}\sum\limits_{r = 1}^s {{s_r^ +} \over {{y_{r0}}}}}} (37) $s . t . x_{i 0} = \sum_{j = 1}^{n} λ_{j} x_{ij} + s_{i}^{-}$ {\rm{s}}{\rm{.t}}.\quad {x_{i0}} = \sum\limits_{j = 1}^n {\lambda _j}{x_{ij}} + s_i^ - (38) $y_{r 0} = \sum_{j = 1}^{n} λ_{j} y_{rj} - s_{r}^{+}$ {y_{r0}} = \sum\limits_{j = 1}^n {\lambda _j}{y_{rj}} - s_r^ + (39) $s^{-} \geq 0, s^{+} \geq 0$ {s^ -} \ge 0,\quad {s^ +} \ge 0 (40) $λ \geq 0, \sum_{j = 1, \neq 0}^{n} λ_{j} = 1$ \lambda \ge 0,\quad \sum\limits_{j = 1, \ne 0}^n {\lambda _j} = 1

In equation (36), s⁻ and s⁺ represent the slack vector of input and output respectively; λ is a weight vector; x_ij and y_{r j}, respectively, represent the input and output of the j-th DMU; The optimal solution ρ^* is the efficiency value of SBM, 0 ≤ ρ^* ≤ l. When ρ^* = 1, that is, s⁻ = s⁺ = 0, it means that the DMU is valid, and when 0 ≤ ρ^* < 1, it means that the DMU is invalid. However, in empirical analysis, multiple DMUs may be effective, and the SBM model cannot sort them, so it is impossible to compare and distinguish effective units in-depth. To overcome this defect, Tone proposed a super-efficient SBM model, the basic principle of which is to exclude the evaluated decision unit from the set of decision units. For an invalid DMU, since the frontier of its production will not change, its efficiency value will be the same as that of the SBM model; while for an effective DMU of SBM, since the production frontier will be recalculated and shifted, its efficiency value may be greater than 1. In addition, considering that the hotel operation system is a complex system, it cannot be analysed purely from the perspective of input and output. For this reason, an angle-free super-efficiency SBM model is selected. Its expression is: (41) $δ^{*} = \min δ = \frac{\frac{1}{m} \sum_{j = 1}^{m} \frac{{\bar{x}}_{i}}{x_{i 0}}}{\frac{1}{s} \sum_{r = 1}^{s} \frac{{\bar{y}}_{r}}{y_{r 0}}}$ {\delta ^*} = \min \delta = {{{1 \over m}\sum\limits_{j = 1}^m {{{{\overline x}_i}} \over {{x_{i0}}}}} \over {{1 \over s}\sum\limits_{r = 1}^s {{{{\overline y}_r}} \over {{y_{r0}}}}}} (42) $s . t . \bar{x} \geq \sum_{j = 1, \neq 0}^{n} λ_{j} x_{j}$ {\rm{s}}{.\rm{t}}.\quad \overline x \ge \sum\limits_{j = 1, \ne 0}^n {\lambda _j}{x_j} (43) $\bar{y} \leq \sum_{j = 1, \neq 0}^{n} λ_{j} y_{j}$ \overline y \le \sum\limits_{j = 1, \ne 0}^n {\lambda _j}{y_j} (44) $\bar{x} \geq 0, \bar{y} \leq y_{0}, \bar{y} \geq 0$ \overline x \ge 0,\quad \overline y \le {y_0},\quad \overline y \ge 0 (45) $λ \geq 0, \sum_{j = 1, \neq 0}^{n} λ_{i} = 1$ \lambda \ge 0,\quad \sum\limits_{j = 1, \ne 0}^n {\lambda _i} = 1

In Eq. (41), $\bar{x}$ \overline x and $\bar{y}$ \overline y are the input and output vectors in the new production possibility subset $\bar{P}$ \overline P excluding (x₀, y₀); that is, $(x_{0}, y_{0}) \in \bar{P} (x_{0}, y_{0})$ ({x_0},{y_0}) \in \overline P ({x_0},{y_0}) and δ^* are the efficiency values of the super-efficient SBM. The meanings of other variables are the same as Eq. (36) (46) $K_{t} = I_{t} / P_{t} + (1 - δ) K_{t - 1}$ {K_t} = {I_t}/{P_t} + \left({1 - \delta} \right){K_{t - 1}} (47) $K_{0} = I_{0} / (g + δ)$ {K_0} = {I_0}/\left({g + \delta} \right)

In equation (46), K_t and K_t₋₁ represent the stock of fixed capital in the t and t-1 periods, respectively; I_t is the total fixed capital investment in the t period; P_t is the fixed capital investment price index; δ_t is the depreciation rate in the t period, and generally takes 5%; K₀ is the capital stock in the base period; and I₀ is the fixed capital investment in the base period. Considering that the input redundancy and output deficiency of an invalid DMU are measured based on its slack, this paper defines input inefficiency as the ratio of input slack and actual input, and output inefficiency as the ratio of output slack and actual output. Its calculation equation is: (48) ${Iineff}_{i} = s_{i}^{-} / x_{i}_{0}$ Iineff_{i} = {s_i}^ - /{x_i}_0 (49) ${Oineff}_{r} = s_{i}^{+} / y_{r}_{0}$ Oineff_{r} = {s_i}^ + /{y_r}_0 (50) $Iineff = \frac{1}{m} \sum_{i = 1}^{m} \frac{s_{i}^{-}}{x_{i 0}}$ Iineff = {1 \over m}\sum\limits_{i = 1}^m {{{s_i}^ -} \over {{x_{i0}}}} (51) $Oineff = \frac{1}{s} \sum_{r = 1}^{s} \frac{s_{r}^{+}}{y_{r 0}}$ Oineff = {1 \over s}\sum\limits_{r = 1}^s {{{s_r}^ +} \over {{y_{r0}}}}

In the above equation, Iine f f_i, Oine f f_r, Iine f f and Oine f f represent the i-th input inefficiency, the r-th output inefficiency, the total input inefficiency and the total output inefficiency, respectively. s_i⁻, s_r⁺ represent the i-th input and r-th output slack, respectively, and s_i⁻ ≥ 0, s_r⁺ ≥ 0, and the meanings of other variables are the same as those of Eq. (36). Based on this analysis, the total input inefficiency rate of the hotel industry in China's ineffective provinces and districts is 0.458, and the total output ineffective rate is 0.077, indicating that if the total input of the hotel industry is reduced by 47.8% on average, the total output will increase by 6.9% on average. District hotels are able to achieve relatively effective effects. The total input inefficiency of the hotel industry is 7 times that of the total output inefficiency, indicating that the total input redundancy is the main source of inefficiency in the hotel industry. From the perspective of sub-item input, the mean inefficiency from small to large is the stock of fixed capital (0.356), the number of rooms (0.573), the number of employees (0.478) and the number of hotels (0.678), indicating the number of hotels, employees and rooms. The investment inefficiency of the total investment inefficiency has a greater contribution to the total investment inefficiency. This means that there are generally problems in hotel construction in these areas, which are more important than quantity and less quality. From the side, it reflects that they are still in extensive and non-group development. On the other hand, it also shows that hotels in these areas are relatively bloated, and there is generally a surplus of employees. From the average of sub-item outputs, the operating income inefficiency (0.056) is lower than the occupancy rate (0.08), indicating that the occupancy rate has a relatively larger contribution to the output inefficiency. Compared with the inefficiency of sub-item input, the inefficiency of sub-item output is very small, but it cannot be ignored, and it needs to be improved and adjusted in the future. For example, in 2011, there was no shortage of output in the operating income of Jilin Province, but in 2016, the inefficiency rate of operating income was 0.634, ranking first in the inefficiency of output. From the perspective of sub-output, except for the hotel occupancy inefficiency in the eastern region (0.223) and the operating income inefficiency in the northeast region (0.211), which are greater than 0.1, the hotel industry output inefficiency in the four major regions is very small, and some are 0.

Conclusion

In order to improve the hotel service quality and profitability, CRM hotel management system is proposed, the core of which is customer service quality. For the existing CRM system, there are problems such as lack of effective data analysis tools and decision-making basis. A hotel CRM solution based on data mining theory is proposed, and a CRM hotel management information system model based on data mining is constructed. According to the CRM requirements of the hotel industry, design the core functional modules of the CRM hotel management system, draw on data mining technology and algorithms, effectively process and analyse passenger occupancy data, extract data from massive data, and cluster through data warehouse and K-means. The algorithm accurately divides customer types, obtains customer value data and customer satisfaction evaluation, provides support for hotel managers to make decisions, and improves service quality and hotel operating profit margins. The design and development of CRM-based small and medium-sized hotel management system is a task that combines business management and software technology. Only by understanding the business can it be possible to refine and optimise the business operation process through software design and development technology. As an indispensable part of hotel operation and management, the importance of hotel management system is self-evident. The system is implemented by the J2EE framework, which has the characteristics of high cohesion, low coupling, extensibility and maintainability.

In the process of writing the thesis and developing the system, this thesis visited the hotel, communicated with the hotel staff, made demand analysis and managed the room management, reservation management, membership management, front desk cashier management, item inventory management, statistical analysis management and system management. Set up management and other aspects of design. The main functions of the system include functional modules such as front desk service management, system management, employee information management and hotel information statistics. The system runs stably and has a friendly interface.

This paper has the following characteristics:

Implemented the statistical analysis function.

With perfect data backup function;

The efficiency of hotels in the provinces of mainland China showed a trend of ‘up-down’. From 2006 to 2016, the average efficiency of the hotel industry in China's provinces (regions) was 0.789, with room for improvement of 23.4%. Among them, Beijing, Shanghai, Zhejiang, Hunan, Qinghai and Ningxia have the hotel industry efficiency greater than 1 in each year. During the research period, Beijing, Tianjin, Shanxi, Shanghai, Zhejiang, Hunan, Tibet, Qinghai and Ningxia have the average hotel efficiency greater than 1, indicating that the hotel industry in most provinces (regions) is in a state of inefficiency.

Using SQLServer2005 as the background management system. In order to ensure the safe and stable operation of the system, data security must be guaranteed. In the case of system abnormality and data loss, it can be quickly restored according to the backup data.

Use CRM mode to design and develop the system. In this model, when business functions need to be extended and modified, other functional modules are not affected.

Figures & Tables

Weights of the lower layer to the upper layer

	Financial dimension	Customer dimension	Internal process dimension	Learning and growth dimensions

The weight of the dimension layer to the target layer	0.472257890	0.315819567	0.095429432	0.116897369

The assessment layer has weights for each dimension	0.1045968700.2058464670.5331456780.156409467	0.136011560.1290036890.0537044790.681267224	0.6483287900.1220200740.229651679	0.5499448950.240211350.209843689

Weights of various types of hotel indicators

Indicator	Type weight coefficient	Adjusted coefficient

Financial dimension	0.47	0.43
Customer dimension	0.31	0.32
Internal process dimension	0.1	0.1
Learning and growth dimension	0.12	0.15
Total	1.00	1.00

Demand analysis of customer status query use case

Use case functional requirements table

Use case description	Online registration and entry information
Use case description	Provide real-time check-in, reservation and other status query of all rooms
Detailed analysis of use cases	Real-time room check-in information query Room recent reservation information query Room rate information query Discount information query
Use case usage restrictions	Hotel management only
Information query instructions	Display brief information of check-in customers
Supplementary description of needs	For customers who have checked out but have not been arranged, so cannot provide instant check-in Rooms are flagged in query results

Hotel performance appraisal index system

Indicator type	Key assessment indicators	Annual target value	Index weight	Assessment criteria

Financial dimension	Annual turnover	During the assessment period, the turnover reached 210 million yuan	0.04	6 points for every 1% increase, 8 points for every 1% decrease
	Return on assets	Return on assets Return on assets reached 13% during the assessment period	0.23	10 points for every 1% increase, 10 points for every 1% decrease
	Planned SalesCompletion Rate	During the assessment period, the planned sales at the beginning of the period were successfully completed	0.06	10 points for every 1 increase, 15 points for every 1% decrease
Customer dimensions	Customer Satisfaction	During the assessment period, customers who received random surveys scored an average of 85 points on the catering segment	0.05	5 points will be added for every 5 points increased, 10 points will be deducted for every 5 points decreased, and no points will be added or decreased if the fluctuation is less than 5 points.
Customer dimensions	Customer Complaint Resolution Rate	Customer complaints are resolved during the assessment period	0.04	15 points for every 1% reduction
Internal business process dimensions	Safety and health compliance rate	During the assessment period, there were no safety incidents and no customer complaints against hygiene	0.06	20 points for a safety incident and 12 points for each health complaint
	Incompleteness rate of low-value consumable items	The low-value consumables in good condition at the end of the assessment period account for 75% of all low-value consumables	0.01	2 points for every 1% increase, 2 points for every 1% decrease
	Incompleteness of fixed assets	Fixed assets that are still in good condition at the end of the assessment period account for 95% of all fixed assets	0.03	5 points for every 1% increase, 10 points for every 1% decrease
Learning and growth dimensions	Employee training pass rate	The employees who participated in the training and were able to work normally during the assessment period accounted for 90% of all employees who participated in the training	0.08	5 points for every 1% increase, 5 points for every 1% decrease
	employee turnover	During the assessment period, employees who have undergone job adjustment and change within the catering department accounted for 45% of all employees	0.03	5 points for every 1% decrease, 10 points for every 1% increase
	Employee turnover rate	Employees who voluntarily resigned during the assessment period accounted for 35% of all employees	0.04	5 points for every 1% decrease, 8 points for every 1% increase

Requirement analysis of online registration and input information use case

Use case functional requirements table

Use case description	Online registration and entry information
Use case description	Provide hotel customers with the function of online registration of hotel members and personal check-in information
Detailed analysis of use cases	Fill in the registration information online Fill in the check-in information online Check-in information change Information submission and background processing
Use case usage restrictions	Customers only
Information query instructions	Specifically provided by other use cases
Supplementary description of needs	No

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Applied Mathematics and Nonlinear Sciences

An online statistical analysis of the hotel management and operation performance model

Hui Fang,
Hui Fang,
Yangli Ou and
Yangli Ou and
Tianyi Fu
Tianyi Fu

Published Online: 30 Nov 2022

Volume & Issue: AHEAD OF PRINT

Page range: -

Received: 10 Jun 2022

Accepted: 07 Aug 2022

Journal & Issue Details

Applied Mathematics and Nonlinear Sciences

PDF Preview

Article

Fig. 1

Fig. 2

Fig. 3

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Weights of the lower layer to the upper layer

Weights of various types of hotel indicators

Demand analysis of customer status query use case

Hotel performance appraisal index system

Requirement analysis of online registration and input information use case

References

Recent Articles

Plan your remote conference with Sciendo

Applied Mathematics and Nonlinear Sciences

An online statistical analysis of the hotel management and operation performance model

Hui Fang,Hui Fang,Yangli Ou andYangli Ou andTianyi FuTianyi Fu

Published Online: 30 Nov 2022

Volume & Issue: AHEAD OF PRINT

Page range: -

Received: 10 Jun 2022

Accepted: 07 Aug 2022

Journal & Issue Details

Applied Mathematics and Nonlinear Sciences

PDF Preview

Article

Fig. 1

Fig. 2

Fig. 3

Figures & Tables

Fig. 1

Fig. 2

Fig. 3

Weights of the lower layer to the upper layer

Weights of various types of hotel indicators

Demand analysis of customer status query use case

Hotel performance appraisal index system

Requirement analysis of online registration and input information use case

References

Recent Articles

Plan your remote conference with Sciendo

Hui Fang,
Hui Fang,
Yangli Ou and
Yangli Ou and
Tianyi Fu
Tianyi Fu