CN115115171A - Method for evaluating service quality of expressway service area - Google Patents
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Abstract
The invention discloses a method for evaluating the service quality of a service area of an expressway, which comprises the following steps: s1, selecting the service intensity and location dominance index, and standardizing the index; s2, determining the subjective weight of each index based on a G1 method, determining the objective weight of each index based on a coefficient of variation method, and determining the comprehensive weight of each index according to the subjective weight and the objective weight; and S3, on the basis of the comprehensive weight, calculating a comprehensive index of the service strength and the location dominance degree based on a comprehensive index method, then calculating the coupling degree and the development degree of the service strength and the location dominance degree according to the comprehensive index, then calculating the coordination degree of the server according to the coupling degree and the development degree, and evaluating the service area based on the coupling degree and the coordination degree. The method for evaluating the service quality fully considers the position difference of different service areas, and is favorable for realizing the collaborative development of the expressway service areas and regional economy.
Description
Technical Field
The invention relates to the technical field of traffic infrastructure, in particular to a method for evaluating service quality of a highway service area.
Background
With the increasing economic level of China and the continuous construction of highway infrastructure, the scale and the number of service areas serving as highway auxiliary facilities are also continuously increased. The service area is used as an important content for construction of the strong traffic country, the service quality of the service area is widely concerned by the whole society all the time, and the service area becomes a direct dimension for measuring the service quality of the highway to a certain extent. Therefore, how to better evaluate the operation status and service capability of the service area becomes an important question to be asked of the service area manager.
The existing research on the evaluation of the service quality of the expressway service area only aims at the characteristics of the service area, and evaluates the service area from the perspective of hardware facilities and software facilities, and the relation between the geographical position of the service area and the service capacity of the service area is not considered.
Disclosure of Invention
Based on the above background, the present invention provides the following technical solutions:
a method for evaluating the service quality of a service area of an expressway comprises the following steps:
s1, selecting the service intensity and location dominance index, and standardizing the index;
s2, determining the subjective weight of each index based on a G1 method, determining the objective weight of each index based on a coefficient of variation method, and determining the comprehensive weight of each index according to the subjective weight and the objective weight;
and S3, on the basis of the comprehensive weight, calculating a comprehensive index of the service strength and the location dominance degree based on a comprehensive index method, then calculating the coupling degree and the development degree of the service strength and the location dominance degree according to the comprehensive index, then calculating the coordination degree of the server according to the coupling degree and the development degree, and evaluating the service area based on the coupling degree and the coordination degree.
Further, in S1, selecting and calculating the service strength and the location dominance index;
service strength-demand strength/supply strength;
the demand intensity index comprises service area use intensity, parking space use intensity and toilet use intensity; the service area use intensity is 1/2 passenger flow intensity +1/2 traffic flow intensity, the passenger flow intensity is passenger flow volume/service area building area, and the traffic flow intensity is traffic flow volume/service area floor area; the using intensity of the parking space is equal to the number of vehicles/total parking spaces entering the service area; the using strength of the toilet is equal to the number of people going to toilet/total number of toilet positions in the daily average toilet;
the supply intensity comprises service personnel supply intensity and service function supply intensity; the service personnel supply intensity is equal to the staff/passenger flow; the service function supply intensity is the sum of service items, the service items comprise parking, a gas station, a public washroom, a sewage treatment facility, a restaurant, a business super, a guest room, showers, vehicle maintenance, a mother-baby room, an accessible passage, emergency rescue service and medical health service, the total number is 11, and each service function is 1 point;
the location dominance degree considers social and economic indexes, also considers the trend of the fusion development of a service area and tourism, and selects population, economic GDP, distance from the city center and the number of covered scenic spots above level 4A.
Further, in S1, a range normalization method is adopted to perform non-dimensionalization processing on the original data of the index, and specific processing methods for the positive and negative indicators are as follows:
the forward direction index is as follows:
negative direction index:
in the formula, C k An original value representing a k-th index; x k Represents a normalized standard value; MaxC k 、 minC k Respectively representing the maximum and minimum values of the k-th index.
Further, the S2 specifically includes:
s21, determining an order relation according to the importance of the indexes based on a G1 method, and calculating the subjective weight of the indexes;
the least important index has a subjective weight calculation formula as follows:
the subjective weight of the other kth index can be calculated according to the following formula:
in the formula, m is the total index number; r is k Is the relative degree of importance between adjacent indexes;
s22, calculating a variation coefficient and an objective weight according to the standard deviation and the arithmetic mean of the index sample data;
in the formula, V k Is the coefficient of variation;
is an objective weight; sigma k Is the standard deviation of the kth index;
is the arithmetic mean of the k index;
s23, determining the comprehensive weight by adopting a linear method;
in the formula, β is the ratio of the subjective weight to the comprehensive weight.
Further, the S3 specifically includes:
s31, calculating a comprehensive index of service intensity and location dominance degree by adopting a comprehensive index method;
wherein, b is 1 to represent the service intensity comprehensive index; b is 2 to represent a comprehensive index of the dominance degree of the location; n represents the total number of indexes in the same group;
s32, calculating the coupling degree and the development degree;
T＝aA 1 +bA 2 (10)
in the formula, C represents the coupling degree of the service intensity and the location dominance degree, and the value is between [0,1](ii) a T represents the service intensity and the development degree of the position dominance degree; a. the 1 、A 2 Comprehensive indexes respectively representing service strength and zone bit dominance degree; a. b is a weight and the sum of the two is 1;
s33, calculating the coordination degree;
and carrying out grade division on the service areas according to the coupling degree and the co-scheduling.
The method for evaluating the service quality of the expressway service area has the following advantages that:
1. the service quality of the highway service areas is evaluated based on the coupled co-scheduling of the service strength and the area dominance degree, the area difference of different service areas is fully considered, and the coordinated development of the highway service areas and regional economy is favorably realized.
2. And determining the comprehensive index weight based on the G1-variation coefficient method, fully considering the subjective weight and the objective weight, and more reasonably determining the weight of the evaluation index.
3. The coupling degree grade and the coordination degree grade are refined, so that accurate strategy is facilitated, a basis is provided for a manager, the service quality of the expressway service area is further improved, and the economic benefit and the social benefit of the expressway service area are exerted to the maximum extent.
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FIG. 1 is a schematic general flow chart of an embodiment of the present invention;
FIG. 2 is a selected highway service area layout according to an embodiment of the present invention;
FIG. 3 is a graph illustrating a coupling analysis of a highway service area according to an embodiment of the present invention;
fig. 4 is a coordination degree analysis diagram of the expressway service area in the embodiment of the present invention.
Detailed Description
The technical scheme of the invention is further explained by combining the drawings and the embodiment.
As shown in the figure, the method for evaluating the service quality of the expressway service area comprises the following steps:
s1, selecting the service intensity and location dominance indexes, and carrying out standardization processing on the indexes;
s2, determining the subjective weight of each index based on a G1 method, determining the objective weight of each index based on a coefficient of variation method, and determining the comprehensive weight of each index according to the subjective weight and the objective weight;
and S3, calculating a comprehensive index of the service strength and the location dominance degree based on a comprehensive index method according to the comprehensive weight, then calculating the coupling degree and the development degree of the service strength and the location dominance degree according to the comprehensive index, then calculating the coordination degree of the server according to the coupling degree and the development degree, and evaluating the service area based on the coupling degree and the coordination degree.
For convenience of understanding, the method is split and detailed in the embodiment based on data of a highway service area in the city of west ampere. The attribute of the expressway service area is derived from a national expressway service area information statistical platform; the social economic data (GDP and population data) are all from Shaanxi province statistics yearbook 2019; the longitude and latitude of the scenic area above the level 4A and the expressway service area are all from Baidu map POI data.
First, service intensity and location dominance index determination
And selecting corresponding evaluation indexes from two aspects of service intensity and location dominance degree.
S11, service strength index
Table 1 service intensity evaluation index calculation
S12 locational dominance index
TABLE 2 location dominance evaluation index calculation
S13, index standardization processing
Because the source, unit, dimension and the like of the evaluation index have the problem of inconsistency, in order to facilitate uniform processing, a range standardization method is adopted to carry out non-dimensionalization processing on the original data of the index.
Specific processing methods for positive indicators and negative indicators are as follows:
in the formula: c k An original value representing a k-th index; x k Represents a normalized standard value; MaxC k 、 minC k Respectively representing the maximum and minimum values of the k-th index.
The original value of the service intensity index is from data of a national highway service area information statistical platform, the original value of the location dominance index is from a statistical yearbook, and the distance from a city center and the coverage rate of a 4A-level or higher scenic area are obtained by further processing Baidu map POI data through a GIS.
TABLE 3 service area evaluation index standardization processing
Second, index comprehensive weight determination based on G1-coefficient of variation method
The index subjective weight determination by the G1 method and the index objective weight determination by the coefficient of variation method are used to obtain the comprehensive weight of the index.
S21, index subjective weight determination based on G1 method
1) Each expert evaluates the importance of each level of index;
2) determining an order relation according to the importance of the indexes;
3) determining a neighboring index X k-1 And X k Relative degree of importance r between k ；
4) And calculating index subjective weight.
Evaluation index X 1 ,X 2 ,…,X m Having a relational expression
Scale evaluation index X 1 ,X 2 ,…,X m Have an order relationship established according to ≧ here
The k-th evaluation index (k: 1,2, …, m) after sorting is written on for convenience, and will be described below
Is X k (1,2,…,m)。
The weight calculation formula of the least important index, namely the 9 th index, is as follows:
the weight of the other kth index can be calculated according to the following formula:
TABLE 4 rational assignment reference table of relative importance between adjacent indexes
TABLE 5 evaluation index relative importance calculation results
S22 index objective weight based on coefficient of variation method
1) Calculating the coefficient of variation of the evaluation index
The coefficient of variation refers to the ratio of the standard deviation to the arithmetic mean of the sample data.
In the formula: sigma k Is the standard deviation of the k-th index,
is the arithmetic mean of the k index.
2) Objective weight of evaluation index calculated based on coefficient of variation method
S23, determining comprehensive weight
The linear combination of subjective weight and objective weight is:
in the formula: beta is the proportion of the subjective weight to the comprehensive weight,
is the subjective weight of the k-th index,
is the objective weight of the k index.
The weight calculated by the G1 method focuses on the average of all expert scores, more typically, so β is taken to be 0.6, so that equation (7) can be written as:
TABLE 6 index weight calculation Table
Third, evaluation of expressway service area based on coupling co-scheduling
S31, calculating comprehensive index
The coupling co-scheduling is influenced by multiple factors, and in order to comprehensively analyze the influence factors and the overall situation, a comprehensive index method is adopted to calculate the comprehensive index of the service intensity and the regional dominance degree.
In the formula: b is 1 to represent the service strength comprehensive index; b is 1 to represent a comprehensive index of the dominance degree of the location; n represents the total number of indexes in the same group.
S32, calculating coupling degree and grading
The coupling degree refers to the degree of interdependence and interaction between subsystems by using a specific calculation value, and the formula is as follows:
in the formula: c represents the coupling degree of the service intensity and the location dominance degree, and the value is between [0,1 ]]；A 1 、A 2 Respectively, a comprehensive index of service strength and location dominance.
In order to more accurately represent the coupling degree between the subsystems, the coupling degree is classified into 4 levels as shown in table 7 with reference to the research of the relevant scholars.
Table 7 coupling degree grade division table
S33, co-scheduling calculation and grade division
The degree of interaction between the service strength reflected by the coupling degree and the position dominance degree is analyzed by using a coordination degree model for further analyzing the degree of system operation between the service strength and the position dominance degree, wherein the coordination degree model is expressed by the following formulas (11) and (12):
T＝aA 1 +bA 2 (12)
in the formula: c represents the coupling degree of the service strength and the position dominance degree; t represents the service intensity and the development degree of the position dominance degree; a. b is a weight and the sum of the two is 1; in the present embodiment, a is 0.5, because of the importance of both.
The calculated coordination degree value is divided according to the table 8, and the division result is shown in the table 9.
Will calculate on the basis of the foregoingDerived service Strength (A) 1 ) And degree of locational dominance (A) 2 ) The comparison can be roughly classified into the following three cases: a. the 1 >A 2 Then, it is the zone dominance degree lag type; a. the 1 ＝A 2 If so, the service intensity and the location dominance degree are synchronous and coordinated; a. the 1 <A 2 It is of the service strength hysteresis type.
TABLE 8 coordination degree grade division Table
TABLE 9 calculation of coupling coordination
It can be seen that the service areas of the highway in the city of Xian are in the running-in level coupling and the high level coupling, the level above the primary coordination, and the blue field service area, the high-voltage service area and the Fengjing service area are in the running-in level coupling-primary coordination stage, so that the service quality of the service areas should be improved, and the coordinated development with economy is realized.
The above is a specific embodiment of the present invention, but the scope of the present invention should not be limited thereto. Any changes or substitutions that can be easily made by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention, and therefore, the scope of the present invention is defined by the claims.
Claims (5)
1. A method for evaluating service quality of a service area of an expressway is characterized by comprising the following steps:
s1, selecting the service intensity and location dominance index, and standardizing the index;
s2, determining the subjective weight of each index based on a G1 method, determining the objective weight of each index based on a coefficient of variation method, and determining the comprehensive weight of each index according to the subjective weight and the objective weight;
and S3, on the basis of the comprehensive weight, calculating a comprehensive index of the service strength and the location dominance degree based on a comprehensive index method, then calculating the coupling degree and the development degree of the service strength and the location dominance degree according to the comprehensive index, then calculating the coordination degree of the server according to the coupling degree and the development degree, and evaluating the service area based on the coupling degree and the coordination degree.
2. The method of claim 1, wherein in S1, the selection and calculation of the service strength and the location dominance index;
service strength-demand strength/supply strength;
the demand intensity index comprises service area use intensity, parking space use intensity and toilet use intensity; the service area use intensity is 1/2 passenger flow intensity +1/2 traffic flow intensity, the passenger flow intensity is passenger flow volume/service area building area, and the traffic flow intensity is traffic flow volume/service area floor area; the using intensity of the parking space is equal to the number of vehicles/total parking spaces driving into the service area; the using strength of the toilet is equal to the number of people going to toilet/total number of toilet positions in the daily average toilet;
the supply intensity comprises service personnel supply intensity and service function supply intensity; wherein, the supply intensity of the service staff is equal to the staff/passenger flow; the service function supply intensity is the sum of service items, the service items comprise 11 items in total, and each service function has 1 point, wherein the service items comprise parking, a gas station, a public washroom, a sewage treatment facility, a restaurant, a business super, a guest room, showers, vehicle maintenance, a mother and infant room, an obstacle-free passage, emergency rescue service and medical and health service;
the location dominance degree considers social and economic indexes, also considers the trend of the convergence development of service areas and tourism, and selects population, economic GDP, distance from the urban center and the number of covered scenic spots above level 4A.
3. The method according to claim 1, wherein in S1, the original data of the index is subjected to dimensionless processing by a range normalization method, and the specific processing method for the positive index and the negative index is as follows:
the forward direction index is as follows:
negative direction index:
in the formula, C k An original value representing a k-th index; x k Represents a normalized standard value; MaxC k 、minC k Respectively representing the maximum and minimum values of the k-th index.
4. The method for evaluating service quality according to claim 3, wherein the S2 specifically is:
s21, determining an order relation according to the importance of the indexes based on a G1 method, and calculating the subjective weight of the indexes;
the least important index has a subjective weight calculation formula as follows:
the subjective weight of the other kth index can be calculated according to the following formula:
in the formula, m is the total index number; r is k Is the relative importance degree between adjacent indexes;
s22, calculating a variation coefficient and an objective weight according to the standard deviation and the arithmetic mean of the index sample data;
in the formula, V k Is the coefficient of variation;
is an objective weight; sigma k Is the standard deviation of the kth index;
is the arithmetic mean of the k index;
s23, determining the comprehensive weight by adopting a linear method;
in the formula, β is the ratio of the subjective weight to the comprehensive weight.
5. The method for evaluating service quality according to claim 4, wherein the S3 is specifically:
s31, calculating a comprehensive index of the service intensity and the location dominance degree by adopting a comprehensive index method;
wherein, b is 1 to represent the service intensity comprehensive index; b is 2 to represent a comprehensive index of the dominance degree of the location; n represents the total number of indexes in the same group;
s32, calculating the coupling degree and the development degree;
T＝aA 1 +bA 2 (10)
in the formula, C represents clothesThe coupling degree of the service intensity and the dominance degree of the zone bit is between 0 and 1](ii) a T represents the service intensity and the development degree of the position dominance degree; a. the 1 、A 2 Comprehensive indexes respectively representing service intensity and location dominance; a. b is a weight and the sum of the two is 1;
s33, calculating the coordination degree;
and carrying out grade division on the service areas according to the coupling degree and the co-scheduling.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116523333A (en) * | 2023-04-18 | 2023-08-01 | 四川省疾病预防控制中心 | Comprehensive evaluation method for disease burden |
| CN116957305A (en) * | 2023-09-20 | 2023-10-27 | 安徽互联智库数据技术有限公司 | Regional service resource intelligent adaptation method and system based on big data |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116523333A (en) * | 2023-04-18 | 2023-08-01 | 四川省疾病预防控制中心 | Comprehensive evaluation method for disease burden |
| CN116957305A (en) * | 2023-09-20 | 2023-10-27 | 安徽互联智库数据技术有限公司 | Regional service resource intelligent adaptation method and system based on big data |
| CN116957305B (en) * | 2023-09-20 | 2024-02-27 | 合肥工业大学 | Regional service resource intelligent adaptation method and system based on big data |
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Application publication date: 20220927 |