CN106651116A - Fuzzy comprehensive evaluation method-based bus passenger satisfaction evaluation method - Google Patents
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Abstract
The invention discloses a fuzzy comprehensive evaluation method-based bus passenger satisfaction evaluation method and belongs to the technical field of public traffic control. The method comprises the steps of constructing a bus passenger satisfaction index system; calculating weight vectors of criterion layers and weight vectors of evaluation factor layers through an analytic hierarchy process; dividing satisfaction into L levels and performing value assignment; obtaining the satisfaction of bus passengers for evaluation factors; calculating a satisfaction evaluation matrix of each criterion; calculating the bus passenger satisfaction through a fuzzy comprehensive evaluation method; and establishing a coordinate system by taking the importance of the evaluation factors as horizontal coordinates and the satisfaction evaluation values of the evaluation factors as longitudinal coordinates, and obtaining bus system improvement schemes according to different quadrants in which different evaluation factors are located. According to the method, the more systematic evaluation index system is established; the influence of subjective factors on weights is reduced by applying the analytic hierarchy process; the satisfaction is quantized by applying the fuzzy comprehensive evaluation method; and the improvement measures are proposed through the quadrants in which the evaluation factors are located, so that single and one-sided evaluation of the evaluation factors is avoided.
Description
Technical field
The invention belongs to public transport control technology field, and in particular to a kind of public transport based on Field Using Fuzzy Comprehensive Assessment is taken advantage of
Objective satisfaction evaluation method.
Background technology
Urban public transport has alleviation traffic system pressure as city important infrastructure, improves traffic efficiency
Important function.As urbanization process is constantly advanced, public transportation system increasingly congestion, various problems are constantly presented.In China
The traffic system of micropolis is chronically at Free Development state, little with road network scale and city harmony is good, small investment
Advantage, but, there is also as service level is low, gauze layout is unreasonable, bus routes is high, repeatability is low and site design does not conform to
The problem demanding prompt solutions such as reason；Because public transport company's management mode normality is weaker, when causing vehicle to reach that randomness is strong, waiting
Between not fix the problems such as, the happiness and urban economy development of city dweller are negatively affected.
In recent years, the index of this reflection urban economy quality of passenger satisfaction, due to the importance of its own, increasingly
Paid attention to by everybody.After passenger satisfaction refers to that passenger compares for the expectation of whole riding process with real experiences, produce
A kind of psychological condition.Conventional public transit system overall evaluation method majority is confined to the evaluation of single aspect, such as public transport
Agility is evaluated, public bus network is evaluated etc..And many running statuses of urban mass-transit system can be embodied directly in passenger
For in the satisfaction of public transit system, therefore, it can be the public transit system overall evaluation and improvement that evaluation is carried out to passenger satisfaction
Effectively and targetedly foundation is provided.The characteristics of Chen Qian etc. has merged the various definitions such as existing reliability, satisfaction, never
Reflect impact of the bus running stability to passenger satisfaction with angle, but be confined to intact stability to passenger satisfaction
Impact.
The content of the invention
For the deficiency that above-mentioned prior art is present, the present invention provides a kind of bus passenger based on Field Using Fuzzy Comprehensive Assessment
Satisfaction evaluation method.
Technical scheme：
A kind of bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment, comprises the steps：
Step 1：Bus passenger Satisfaction Index System is built, including：Destination layer is bus passenger satisfaction u, standard
Then layer and evaluation points layer, rule layer includes affecting criterion u of bus passenger satisfactioni, evaluation points layer include each criterion uiIt is right
The evaluation points answeredWherein, i={ 1,2 ..., n }, n be criterion number, ki={ 1,2 ..., Ki, KiFor criterion uiCorrespondence
Evaluation points number；
Step 2：Each rule layer weight vectors a and each criterion u are calculated by analytic hierarchy process (AHP)iMiddle evaluation points layer weight to
Amount wi；The rule layer weight vectors a includes each criterion weight, evaluation points layer weight vectors wiIncluding criterion uiIt is corresponding each
Evaluation points weight：
Step 2-1：Construction rules layer judgment matrixWherein, j={ 1,2 ..., n }, vijIt is relative
For destination layer bus passenger satisfaction u, uiWith ujRelative importance；
Step 2-2：Calculation criterion layer judgment matrix V eigenvalue of maximum λmaxWith characteristic vector A；
Step 2-3：According to eigenvalue of maximum λmaxCoincident indicator CI of calculation criterion layer judgment matrix；
Step 2-4：Rule layer judgment matrix exponent number n correspondence Aver-age Random Consistency Index RI values are searched, and is calculatedIf CR<0.1, rule layer judgment matrix has satisfied uniformity, and execution step 2-5 otherwise, readjusts criterion
Layer judgment matrix；
Step 2-5：Rule layer weight vectors a=(a are obtained to A normalizations1, a2..., ai..., an), wherein, aiFor criterion
uiWeight；
Step 2-6：The corresponding evaluation points layer judgment matrix of each criterion is constructed, each evaluation points layer is calculated successively and is judged square
Coincident indicator CI of battle arrayiAnd CRi, if as CRi<0.1, execution step 2-7 otherwise, is readjusted the evaluation points layer and is judged
Matrix.
Step 2-7：Each evaluation points layer weight vectors w is calculated according to each evaluation points layer judgment matrixi。
Step 3：Satisfaction is divided into into L grade, and respectively to each satisfaction grade assignment；The satisfaction ranking score
Wei not " feel quite pleased, satisfied, general, dissatisfied, very dissatisfied " five grades.
Step 4：Obtain satisfaction of the bus passenger to each evaluation points；
Step 5：Calculation criterion uiSatisfaction evaluation matrixWherein,It is for commenting
The valency factorSatisfaction grade accounts for whole number ratios for the number of l in bus passenger, wherein, l={ 1,2 ..., L }；
Step 6：Using the weight vectors w of satisfaction evaluation matrix, each rule layer weight vectors a and evaluation points layeriIt is logical
Cross Field Using Fuzzy Comprehensive Assessment and calculate bus passenger to each criterion satisfaction evaluation value and bus passenger total satisfaction evaluation of estimate：
Step 6-1：Pass criteria uiSatisfaction evaluation matrix RiWith the weight vectors w of evaluation points layeriSeek rule layer ui
Fuzzy overall evaluation collection Bi：
Step 6-2：To fuzzy overall evaluation collection BiDeblurring score value is carried out, criterion u is obtainediSatisfaction evaluation value Pi；
Step 6-3：Calculate the final grading collection of fuzzy overall evaluation
Step 6-4：Deblurring score value is carried out to final evaluate collection D, bus passenger total satisfaction evaluation of estimate P is obtainedfinal；
Step 6-5：According to satisfaction evaluation matrix computations bus passenger to each evaluation points satisfaction evaluation valueWherein, H=(L ..., l ..., 2,1)；
Step 7：With each evaluation points importance degree as abscissa, each evaluation points satisfaction evaluation value is that ordinate sets up seat
Mark system, according to the difference of different evaluation factor place quadrant, obtains the superiority and inferiority of public transit system, obtain targetedly, have
The improvement project of succession.
Beneficial effect：A kind of bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment and prior art phase
Than with following advantage：
(1) assessment indicator system of three levels is constructed, bus passenger satisfaction evaluation more system is made；
(2) weight coefficient of each evaluation points is determined with analytic hierarchy process (AHP), the impact of subjective factor is reduced；
(3) satisfaction is quantified with Field Using Fuzzy Comprehensive Assessment, evaluation points is carried out with " satisfaction-importance degree " comprehensive
Close and evaluate, the quadrant being located by each evaluation points finds out the defect and inferior position of public transportation system, it is to avoid to evaluation points
Single, unilateral evaluation；
(4) propose effectively, targetedly public transport improvement project.
Description of the drawings
Fig. 1 is the bus passenger satisfaction evaluation method stream based on Field Using Fuzzy Comprehensive Assessment of one embodiment of the present invention
Cheng Tu；
Fig. 2 is the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment of one embodiment of the present invention
Evaluation points satisfaction-importance degree quadrantal diagram.
Specific embodiment
One embodiment of the present invention is elaborated below in conjunction with the accompanying drawings.
As shown in figure 1, a kind of bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment, including following step
Suddenly：
Step 1：Bus passenger Satisfaction Index System is built, including：Destination layer is bus passenger satisfaction u, standard
Then layer and evaluation points layer, rule layer includes affecting criterion u of bus passenger satisfactioni, evaluation points layer include each criterion uiIt is right
The evaluation points answeredWherein, i={ 1,2 ..., n }, n be criterion number, ki={ 1,2 ..., Ki, KiFor criterion uiIt is corresponding
Evaluation pointsNumber.It is low with service level because the public transit system of small and medium cities is chronically at Free Development state,
Site design is unreasonable, the features such as public transport attraction is not enough.Invisible nature again due to bus service product, the difference of passenger's individuality
Property, accordingly, it is determined that public transport passenger satisfaction factor of evaluation it is critical that, the clothes of urban public transport should be met
Business characteristic can comprehensively react the situation that is satisfied with to each factor of passenger again, present embodiment according to universality, reasonability, can
Acquired, metrizability principle, carries out the structure of passenger satisfaction index system, wherein, n=3, K1=6, K2=3, K3=
3, passenger satisfaction index system is as shown in table 1：
The passenger satisfaction index system table of table 1
Step 2：By analytic hierarchy process (AHP) calculation criterion layer weight vectors a and criterion uiCorresponding evaluation points layer weight to
Amount wi；
Step 2-1：Construction rules layer judgment matrixWherein, j={ 1,2 ..., n }, vijIt is relative mesh
For+8++ mark layer bus passenger satisfactions u, uiWith ujRelative importance；In present embodiment,
Step 2-2：Calculation criterion layer judgment matrix V eigenvalue of maximum λmaxWith characteristic vector A, in present embodiment, λmax
=3.0183, A=(0.6512,0.1422,0.485).
Step 2-3：Calculation criterion layer judgment matrix approach index
Step 2-4：The corresponding Aver-age Random Consistency Index RI values of rule layer judgment matrix exponent number n are searched, is calculatedIf CR<0.1, rule layer judgment matrix has satisfied uniformity, and execution step 2-5 otherwise, readjusts criterion
Layer judgment matrix.In present embodiment, CI=0.00915, RI=0.58, CR=0.016<0.1, i.e. judgment matrix have satisfaction
Uniformity, RI values are searched using table 2：
The Aver-age Random Consistency Index RI value tables of table 2
| n | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| RI | 0.00 | 0.00 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.45 |
Step 2-5：Rule layer weight vectors a=(a are obtained to A normalizations1, a2..., ai..., an)；Present embodiment
In, the weight vectors a=of rule layer (0.423,0.092,0.485)；
Step 2-6：The evaluation points layer judgment matrix under each rule layer is constructed, each evaluation points layer is calculated successively and is judged square
Coincident indicator CI of battle arrayiAnd CRi, if as CRi<0.1, execution step 2-7 otherwise, is readjusted the evaluation points layer and is judged
Matrix；
Step 2-7：Each evaluation points layer weight vectors w is calculated according to the corresponding evaluation points layer judgment matrix of each criterioni,
In present embodiment, the corresponding evaluation points layer weight vectors of each criterion u1, u2, u3 are respectively w1=(0.401,0.239,
0.105,0.105,0.105,0.045)、w2=(0.634,0.192,0.174), w3=(0.691,0.149,0.160)；
Step 3：Satisfaction is divided into into L grade, in present embodiment, L=5, satisfaction grade be divided into " feel quite pleased,
It is satisfied, general, dissatisfied, very dissatisfied ", difference assignment 5,4,3,2,1；
Step 4：Bus passenger information and the satisfaction to each evaluation points are obtained, confidence level is carried out to reduced data
Analysis；
Step 4-1：Zones of different obtains the basic letter of the bus passenger for taking different bus routes in small and medium cities
Breath and the satisfaction to evaluation points, wherein, essential information includes sex, age and the occupation of bus passenger；
In present embodiment, 300 parts of questionnaire is provided to Fuxin City zones of different bus passenger, content is filled in into imperfect asking
Volume is considered as invalid questionnaire, obtains 270 parts of effective questionnaire, and efficient 90%.The essential information statistics of bus passenger is as shown in table 3：
The essential information statistical form of the bus passenger of table 3
Step 4-2：The Cronbach α coefficient of reliabilities of bus passenger essential information are obtained by SPSS softwares, is carried out credible
Degree analysis；If coefficient of reliability is in threshold interval [0.5,1], execution step 5, otherwise, questionnaire is reacquired；
In present embodiment, coefficient of reliability α=0.912 shows that questionnaire reliability is good.
Step 5：Calculation criterion uiSatisfaction evaluation matrixWherein,Take advantage of for public transport
To evaluation points in visitorSatisfaction grade account for whole number ratios for the number of l, wherein, l={ 1,2 ..., L }；
In present embodiment, using passenger satisfaction index system and questionnaire each criterion is obtained：Passenger experience u1, base
The satisfaction evaluation matrix that Infrastructure u2, vehicle run u3 is as follows：
Step 6：Using the weight vectors w of satisfaction evaluation matrix, the weight vectors a of rule layer and evaluation points layeriIt is logical
Cross Field Using Fuzzy Comprehensive Assessment and calculate bus passenger to each criterion satisfaction evaluation value and bus passenger total satisfaction evaluation of estimate.
Step 6-1：By each criterion satisfaction evaluation matrix RiWith the weight vectors w of evaluation points layeriSeek the mould of each criterion
Paste overall merit collection Bi：
Bi=wi×Ri=(bi1,bi2,…,biL)
In present embodiment, the fuzzy overall evaluation collection of each criterion is：
B1=w1×R1=(0.152,0.298,0.378,0.116,0.057)
B2=w2×R2=(0.131,0.243,0.348,0.263,0.025)
B3=w3×R3=(0.150,0.400,0.302,0.274,0.020)
Step 6-2：To fuzzy overall evaluation collection BiDeblurring score value is carried out, each criterion satisfaction evaluation value P is obtainedi：
Pi=Bi×HT
Wherein, H=(L ..., l ..., 2,1).In present embodiment, and H=(5,4,3,2,1)；Fuzzy synthesis are commented respectively
Valency collection BiDeblurring score value is carried out, passenger is obtained for the satisfaction that passenger experience, infrastructure, vehicle run three aspects is commented
Value：
p1=5 × b11+5×b12+3×b13+2×b14+1×b15=3.374
p2=5 × b21+4×b22+3×b23+2×b24+1×b25=3.221
p3=5 × b31+4×b32+3×b33+2×b34+1×b35=3.820
Step 6-3：Calculate final evaluate collection D of fuzzy overall evaluation：
D=A × B
Wherein,In present embodiment, and D=A × B=(0.138,0.322,0.317,0.195,0.028)；
Step 6-4：Deblurring score value is carried out to final evaluate collection D, bus passenger total satisfaction evaluation of estimate P is obtainedfinal；
Pfinal=A × HT
In present embodiment, Pfinal=5 × a11+4×a12+3×a13+2×a14+1×a15=3.347；
Step 6-5：According to satisfaction evaluation matrix computations bus passenger to each evaluation points satisfaction evaluation value
Step 6-6：By L ..., l ..., with P in 2,11、P2、P3、And PfinalIt is immediate to be worth corresponding satisfaction grade
Respectively as bus passenger to each criterion uiThe final evaluation of satisfaction and bus passenger total satisfaction.In present embodiment,
Bus passenger satisfaction 3.347 is bus passenger satisfaction between 3 and 4 between " satisfaction " and " general ".
Step 7：With reference to Assessment of Important, " importance degree-satisfaction " overall merit is carried out to each evaluation points layer, and proposed
Improvement project：
Step 7-1：According to bus passenger total satisfaction evaluation of estimate and each evaluation points satisfaction evaluation value, by SPSS
Software calculates the coefficient correlation of every evaluation points and bus passenger total satisfaction, and using coefficient correlation as each evaluation points
Importance degree；Coefficient correlation represents extremely strong correlation between 0.8～1.0；Coefficient correlation represents strong correlation between 0.6～0.8；
Coefficient correlation represents moderate correlation between 0.4～0.6；Coefficient correlation represents weak correlation between 0.2～0.4；Phase
Relation number represents extremely weak correlation or without correlation between 0.0～0.2；
Step 7-2：As shown in Fig. 2 with each evaluation points importance degree as abscissa, each evaluation points satisfaction evaluation value is
Ordinate sets up coordinate system；Different quadrants represent passenger to the cognition of the importance degree of the different evaluation factor and to different evaluation
The satisfaction of the factor.As shown in table 4, according to the difference of different evaluation factor place quadrant, the advantage of public transit system can be obtained
With inferior position, and then targetedly, have the proposition improvement project of succession.
Public transport feature and lose no time scheme table of the table 4 based on " importance degree-satisfaction "
Claims (6)
1. a kind of bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment, it is characterised in that comprise the steps：
Step 1：Bus passenger Satisfaction Index System is built, including：Destination layer is bus passenger satisfaction u, rule layer
With evaluation points layer, rule layer include criterion ui, evaluation points layer include each criterion uiCorresponding evaluation pointsWherein, i=
{ 1,2 ..., n }, n be criterion number, ki={ 1,2 ..., Ki, KiFor criterion uiThe number of corresponding evaluation points；
Step 2：By analytic hierarchy process (AHP) calculation criterion layer weight vectors a and evaluation points layer weight vectors wi；The rule layer power
Weight vector a includes the weight of each criterion, evaluation points layer weight vectors wiIncluding criterion uiThe weight of corresponding each evaluation points；
Step 3：Satisfaction is divided into into L grade, and to each satisfaction grade assignment；
Step 4：Obtain satisfaction of the bus passenger to each evaluation points；
Step 5：Calculation criterion uiSatisfaction evaluation matrixWherein,For in bus passenger
To evaluation pointsSatisfaction grade account for whole number ratios for the number of l, wherein, l={ 1,2 ..., L }；
Step 6：Using each criterion satisfaction evaluation matrix, rule layer weight vectors a and evaluation points layer weight vectors wi, pass through
Field Using Fuzzy Comprehensive Assessment calculates bus passenger to each criterion satisfaction evaluation value and bus passenger total satisfaction evaluation of estimate.
2. the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment according to claim 1, its feature exists
In the step 2 is specially：
Step 2-1：Construction rules layer judgment matrixWherein, j={ 1,2 ..., n }, vijFor relative target layer
For bus passenger satisfaction u, uiWith ujRelative importance；
Step 2-2：Calculation criterion layer judgment matrix eigenvalue of maximum λmaxWith characteristic vector A；
Step 2-3：According to eigenvalue of maximum λmaxCoincident indicator CI of calculation criterion layer judgment matrix；
Step 2-4：The corresponding Aver-age Random Consistency Index RI values of rule layer judgment matrix exponent number n are searched, and is calculatedIf CR<0.1, rule layer judgment matrix has satisfied uniformity, and execution step 2-5 otherwise, readjusts criterion
Layer judgment matrix；
Step 2-5：Rule layer weight vectors a=(a are obtained to A normalizations1, a2..., ai..., an), wherein, aiFor criterion ui's
Weight；
Step 2-6：The corresponding evaluation points layer judgment matrix of each criterion is constructed, each evaluation points layer judgment matrix is calculated successively
Coincident indicator CIiAnd CRi, if as CRi<0.1, execution step 2-7 otherwise, readjusts the evaluation points layer and judges square
Battle array；
Step 2-7：Each evaluation points layer weight vectors w is calculated according to each evaluation points layer judgment matrixi。
3. the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment according to claim 1, its feature exists
In the step 6 is specially：
Step 6-1：Pass criteria uiSatisfaction evaluation matrix RiWith the weight vectors w of evaluation points layeriSeek rule layer uiMould
Paste overall merit collection Bi；
Step 6-2：To fuzzy overall evaluation collection BiDeblurring score value is carried out, criterion u is obtainediSatisfaction evaluation value Pi；
Step 6-3：The final evaluate collection D=a × B of fuzzy overall evaluation is calculated, wherein
Step 6-4：Deblurring score value is carried out to final evaluate collection D, bus passenger total satisfaction evaluation of estimate P is obtainedfinal。
4. the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment according to claim 1, its feature exists
Be respectively in, the satisfaction grade feel quite pleased, it is satisfied, general, dissatisfied, very dissatisfied.
5. the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment according to claim 1, its feature exists
In the step 6 also includes：According to satisfaction evaluation matrix computations bus passenger to each evaluation points satisfaction evaluation valueWherein, H=(L ..., l ..., 2,1).
6. the bus passenger satisfaction evaluation method based on Field Using Fuzzy Comprehensive Assessment according to claim 5, its feature exists
According to each evaluation points satisfaction evaluation value and the every evaluation points weight of bus passenger total satisfaction evaluation of estimate calculating
Spend.With each evaluation points importance degree as abscissa, each evaluation points satisfaction evaluation value sets up coordinate system for ordinate；According to
The difference of different evaluation factor place quadrant, obtains the superiority and inferiority of public transit system.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523311A (en) * | 2018-10-30 | 2019-03-26 | 广东原昇信息科技有限公司 | ' Satisfaction Index weighing computation method |
| CN111369300A (en) * | 2020-03-13 | 2020-07-03 | 浙江师范大学 | Satisfaction evaluation method and device, computer equipment and readable storage medium |
| CN112836959A (en) * | 2021-02-01 | 2021-05-25 | 南京邮电大学 | Data center energy efficiency evaluation method based on service quality |
| CN113222213A (en) * | 2021-04-09 | 2021-08-06 | 中国水产科学研究院东海水产研究所 | Krill fishing net mouth advancing route planning method |
| CN113287144A (en) * | 2019-03-25 | 2021-08-20 | 株式会社日立制作所 | Mobile service system and mobile service providing method |
| CN113658029A (en) * | 2021-08-13 | 2021-11-16 | 北京北大千方科技有限公司 | Bus comfort level query method, system and equipment for intelligent travel study and judgment |
| CN115345685A (en) * | 2022-10-18 | 2022-11-15 | 苏州大学 | Evaluation method and system of shared travel service based on entropy weight method and fuzzy evaluation |
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2016
- 2016-11-02 CN CN201610944970.6A patent/CN106651116A/en active Pending
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523311A (en) * | 2018-10-30 | 2019-03-26 | 广东原昇信息科技有限公司 | ' Satisfaction Index weighing computation method |
| CN113287144A (en) * | 2019-03-25 | 2021-08-20 | 株式会社日立制作所 | Mobile service system and mobile service providing method |
| CN111369300A (en) * | 2020-03-13 | 2020-07-03 | 浙江师范大学 | Satisfaction evaluation method and device, computer equipment and readable storage medium |
| CN112836959A (en) * | 2021-02-01 | 2021-05-25 | 南京邮电大学 | Data center energy efficiency evaluation method based on service quality |
| CN113222213A (en) * | 2021-04-09 | 2021-08-06 | 中国水产科学研究院东海水产研究所 | Krill fishing net mouth advancing route planning method |
| CN113222213B (en) * | 2021-04-09 | 2022-08-12 | 中国水产科学研究院东海水产研究所 | Krill fishing net mouth advancing route planning method |
| CN113658029A (en) * | 2021-08-13 | 2021-11-16 | 北京北大千方科技有限公司 | Bus comfort level query method, system and equipment for intelligent travel study and judgment |
| CN115345685A (en) * | 2022-10-18 | 2022-11-15 | 苏州大学 | Evaluation method and system of shared travel service based on entropy weight method and fuzzy evaluation |
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