# Research on Service Quality of International Tourism Cities in the Context of Intelligent Network: A Case Study of Public Transport in Macao

Authors: Shutong Zhao; Liang Zhao; Nailin Gu
Journal: Wireless Communications and Mobile Computing
 (2022)

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## Abstract

In order to study the service quality of international tourism cities under the intelligent network environment, this paper constructs an evaluation model named “IEP-CSI” for Macao bus service satisfaction according to the questionnaire data of Macao bus passengers. We draw the following conclusions: with the increase of passengers’ expectation of bus service, the actual perceived quality and satisfaction will decrease; in addition, the passengers’ satisfaction can also be affected by perceived value and perceived quality. This research provides some reference and insights for follow-up research.


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## Body

## 1. Introduction

On July 2013, the Macao Transportation Bureau launched the bus service evaluation for the first time, aiming to take it as an important reference to measure the service quality of bus companies, so as to urge bus companies to improve service quality. However, since 2013, the evaluation results show that the service quality of Macao buses has not been able to meet the requirements of passengers. Public transport is an important infrastructure of a city. Its development level directly affects the convenience and happiness of citizens and is of great significance to the construction of a harmonious society and a harmonious city. The state attaches great importance to the development of public transport and has successively issued policies such as the “Internet +” convenient transportation action and the “transit metropolis” construction demonstration project. Local cities have also formulated strategic goals for urban public transport development according to local conditions. “Smart transportation”, “public transport priority”, “microcirculation public transport”, “new energy public transport”, and other keywords frequently appear in government work reports. Meanwhile, as an important public service infrastructure, public transport service plays a positive role in solving urban traffic congestion, saving land resources, improving environmental quality, promoting urban development, optimizing urban spatial structure, promoting industrial development, and improving people’s quality of life [1]. Road transport and air transport include buses and trolleybuses, bus rapid transit, taxis, public bicycles, civil aviation aircraft, and helicopters. Therefore, improving the quality of bus service and improving bus passenger satisfaction has become an urgent problem for Macao bus companies. Starting from the actual characteristics of Macao buses, this study constructs a Macao bus public service evaluation model based on four satisfaction index models (CCSI, ECSI, SCSB, and ACSI), discusses the influencing factors affecting the satisfaction of bus service quality, and provides theoretical support for the development of public transport in Macao.


## 2. Theoretical Analysis and Hypothesis Proposal

### 2.1. Theoretical Analysis

Beltrami [2] put forward the term public service quality, which is used in western countries. As for the quality of public services, it contains certain quantitative requirements. Especially in the case of insufficient supply of basic public services in China, the increase of supply will greatly affect public satisfaction. The factors that affect the quantity of supply are related to the government’s public financial capacity and the importance it attaches to public services. Beltrami once pointed out that (1) quality in the sense of compliance with norms and procedures; (2) quality in the sense of effectiveness (benefit); and (3) quality in the sense of customer satisfaction, three development stages. In the preresearch [3], the factors affecting the bus service quality in Macao are determined as seven aspects: in car environment, bus operation, facilities and systems, driving safety, optimizing services, peak hour services, and increasing bus routes. Service attitude of public services is mostly provided in the form of intangible services, and their quality can only be felt in the process of receiving services. Therefore, the attitude of service personnel in the service process determines the public’s evaluation of the quality of public products. Based on the above results, this study processes the service standard information of Macao public buses and the bus passenger satisfaction data recovered from the survey in recent years and constructs the Macao bus public service evaluation model combined with the four commonly used satisfaction models (CCSI, ECSI, SCSB, and ACSI).At present, the satisfaction evaluation system based on the above model has been applied in many fields. Liu and Sun [4] established a customer satisfaction survey system of scientific instrument sharing platform by using analytic hierarchy process, Richter scale, and other methods. Note that analytic hierarchy process is to decompose the decision-making problem into different hierarchical structures according to the order of the general goal, subgoals of each level, evaluation criteria, and specific alternative investment scheme, and then use the method of solving the eigenvector of the judgment matrix to obtain the priority weight of each element of each level to an element of the upper level, and finally use the method of weighted sum to merge the final weight of each alternative scheme to the general goal in a hierarchical manner. The best scheme is the one with the largest final weight. Jin et al. [5] designed and constructed the dairy customer satisfaction evaluation index system based on ECSI model. Zhou [6] constructed an inpatient satisfaction evaluation model based on ECSI and ACSI models. Revilla-Camacho et al. [7] conducted an in-depth research on corporate responsibility under the European Customer Satisfaction Index (ECSI) model. At the same time, the satisfaction model for urban traffic service quality has also developed rapidly. Based on ACSI and CCSI models, Qiao [8] extracted five potential variables: perceived quality, perceived value, public expectation, public satisfaction, and public loyalty and built the Tianjin Rail Transit Public Satisfaction (RTPSI) model. Cui et al. [9] conducted a questionnaire survey on 267 passengers based on the ACSI model and constructed a passenger satisfaction model of online taxi service. Yan [10] used KMO and Bartlett spherical test to judge the analysis suitability of questionnaire factors and Cronbach’s α coefficient test reliability and CR test validity; using factor analysis and structural equation model, this paper effectively analyzes the influence of existing factors on the cultivation of core values in colleges and universities. Divide the decision-making objectives, the factors considered (decision criteria), and decision-making objects into highest level, middle level, and lowest level according to the relationship between them and draw the hierarchical structure diagram. The highest level refers to the purpose of decision-making and the problem to be solved. The lowest level refers to the alternative when making decisions. The middle tier refers to the factors considered and the criteria for decision-making. For the two adjacent layers, the high layer is called the target layer, and the low layer is called the factor layer. Vinit [11] found through data analysis that consumers’ overall satisfaction with the service quality of catering stores in the study reached the level of psychological acceptance, and consumers’ expectation of service quality was higher than consumers’ perception of service quality.Based on the above articles, it can be found that the influencing variables such as customer expectation and perception are the main factors to be considered when using this kind of model to evaluate satisfaction. Based on the previous research findings, service importance is also an important factor affecting Macao bus satisfaction. Therefore, this study selects service importance, customer expectation, perceived quality, and finance as the influencing factors of Macao bus service quality and constructs a satisfaction evaluation model.


### 2.2. Research Hypothesis and Model

Based on the current research on the evaluation of public transport service quality and the combing of four satisfaction models and referring to the previous research, this paper puts forward the following research assumptions:H0: The gender of passengers has no difference in the evaluation of bus services.H1: The importance of bus service has a related impact on expectation.H2: The importance of bus service has a related impact on perceived quality.H3: The importance of bus service has a relevant impact on perceived value.H4: Customer expectation of bus service has a relevant impact on perceived quality.H5: Customer expectation of bus service has a relevant impact on perceived value.H6: Perceived quality of bus service has a relevant impact on perceived value.H7: Customer expectation of bus service has a relevant impact on satisfaction.H8: Perceived quality of bus service has a relevant impact on satisfaction.H9: Perceived value of bus service has a relevant impact on satisfaction.H10: Bus service satisfaction has a related impact on finance.H11: Bus service satisfaction has a relevant impact on the actual use of buses.To sum up, based on the above assumptions, the influencing factor model of Macao bus service satisfaction is constructed, as shown in Figure1.Figure 1
Influencing factor model of bus service satisfaction in Macao.


## 2.1. Theoretical Analysis

Beltrami [2] put forward the term public service quality, which is used in western countries. As for the quality of public services, it contains certain quantitative requirements. Especially in the case of insufficient supply of basic public services in China, the increase of supply will greatly affect public satisfaction. The factors that affect the quantity of supply are related to the government’s public financial capacity and the importance it attaches to public services. Beltrami once pointed out that (1) quality in the sense of compliance with norms and procedures; (2) quality in the sense of effectiveness (benefit); and (3) quality in the sense of customer satisfaction, three development stages. In the preresearch [3], the factors affecting the bus service quality in Macao are determined as seven aspects: in car environment, bus operation, facilities and systems, driving safety, optimizing services, peak hour services, and increasing bus routes. Service attitude of public services is mostly provided in the form of intangible services, and their quality can only be felt in the process of receiving services. Therefore, the attitude of service personnel in the service process determines the public’s evaluation of the quality of public products. Based on the above results, this study processes the service standard information of Macao public buses and the bus passenger satisfaction data recovered from the survey in recent years and constructs the Macao bus public service evaluation model combined with the four commonly used satisfaction models (CCSI, ECSI, SCSB, and ACSI).At present, the satisfaction evaluation system based on the above model has been applied in many fields. Liu and Sun [4] established a customer satisfaction survey system of scientific instrument sharing platform by using analytic hierarchy process, Richter scale, and other methods. Note that analytic hierarchy process is to decompose the decision-making problem into different hierarchical structures according to the order of the general goal, subgoals of each level, evaluation criteria, and specific alternative investment scheme, and then use the method of solving the eigenvector of the judgment matrix to obtain the priority weight of each element of each level to an element of the upper level, and finally use the method of weighted sum to merge the final weight of each alternative scheme to the general goal in a hierarchical manner. The best scheme is the one with the largest final weight. Jin et al. [5] designed and constructed the dairy customer satisfaction evaluation index system based on ECSI model. Zhou [6] constructed an inpatient satisfaction evaluation model based on ECSI and ACSI models. Revilla-Camacho et al. [7] conducted an in-depth research on corporate responsibility under the European Customer Satisfaction Index (ECSI) model. At the same time, the satisfaction model for urban traffic service quality has also developed rapidly. Based on ACSI and CCSI models, Qiao [8] extracted five potential variables: perceived quality, perceived value, public expectation, public satisfaction, and public loyalty and built the Tianjin Rail Transit Public Satisfaction (RTPSI) model. Cui et al. [9] conducted a questionnaire survey on 267 passengers based on the ACSI model and constructed a passenger satisfaction model of online taxi service. Yan [10] used KMO and Bartlett spherical test to judge the analysis suitability of questionnaire factors and Cronbach’s α coefficient test reliability and CR test validity; using factor analysis and structural equation model, this paper effectively analyzes the influence of existing factors on the cultivation of core values in colleges and universities. Divide the decision-making objectives, the factors considered (decision criteria), and decision-making objects into highest level, middle level, and lowest level according to the relationship between them and draw the hierarchical structure diagram. The highest level refers to the purpose of decision-making and the problem to be solved. The lowest level refers to the alternative when making decisions. The middle tier refers to the factors considered and the criteria for decision-making. For the two adjacent layers, the high layer is called the target layer, and the low layer is called the factor layer. Vinit [11] found through data analysis that consumers’ overall satisfaction with the service quality of catering stores in the study reached the level of psychological acceptance, and consumers’ expectation of service quality was higher than consumers’ perception of service quality.Based on the above articles, it can be found that the influencing variables such as customer expectation and perception are the main factors to be considered when using this kind of model to evaluate satisfaction. Based on the previous research findings, service importance is also an important factor affecting Macao bus satisfaction. Therefore, this study selects service importance, customer expectation, perceived quality, and finance as the influencing factors of Macao bus service quality and constructs a satisfaction evaluation model.


## 2.2. Research Hypothesis and Model

Based on the current research on the evaluation of public transport service quality and the combing of four satisfaction models and referring to the previous research, this paper puts forward the following research assumptions:H0: The gender of passengers has no difference in the evaluation of bus services.H1: The importance of bus service has a related impact on expectation.H2: The importance of bus service has a related impact on perceived quality.H3: The importance of bus service has a relevant impact on perceived value.H4: Customer expectation of bus service has a relevant impact on perceived quality.H5: Customer expectation of bus service has a relevant impact on perceived value.H6: Perceived quality of bus service has a relevant impact on perceived value.H7: Customer expectation of bus service has a relevant impact on satisfaction.H8: Perceived quality of bus service has a relevant impact on satisfaction.H9: Perceived value of bus service has a relevant impact on satisfaction.H10: Bus service satisfaction has a related impact on finance.H11: Bus service satisfaction has a relevant impact on the actual use of buses.To sum up, based on the above assumptions, the influencing factor model of Macao bus service satisfaction is constructed, as shown in Figure1.Figure 1
Influencing factor model of bus service satisfaction in Macao.


## 3. Research Design

### 3.1. Data Source

Combined with the above research, this paper designs two horizontal and vertical dimensions. The horizontal dimensions are service importance, customer expectation, perceived quality, and finance. Customer complaints, especially reasonable complaints, are the most representative and concentrated reflection of customer expectations. Therefore, it is particularly important to analyze, process, summarize, and sort out customer complaint information and evaluate customer expectations. Through the information screening and filtering of customers’ reasonable complaints, the expected information of customers is refined to form the basic information of customers’ expectations. Among them, service importance, customer expectation, and perceived quality are collected in the form of questionnaires, and financial data are collected through interviews and searching the official website. Table1 shows the financial data of Macao bus companies in 2018. The longitudinal dimension is designed through the questionnaire, which is mainly based on the SERVQUAL model scale [12]. From the perspective of the “triangle law of customer satisfaction”, although customer expectation is a reaction to customer satisfaction, it is not the lower the better. If customer expectation is very low, it means that customers have nothing to ask for service or products, let alone satisfaction and loyalty. Therefore, in order to reasonably control customers’ expectations, on the one hand, we should actively face customers’ expectations and constantly improve our own services; on the other hand, we should reasonably guide customers’ expectations, starting from the source and try to avoid the emergence of customers’ unreasonable expectations as much as possible.Table 1
List of financial data of Macao bus companies in 2018 (in MOP).
Expense itemNew benefitsAobaNew eraTotal costPersonnel costs399,639,983258,894,090119,556,487778090560Fuel cost142,826,765106,373,09159,954,406309154262Depreciation and amortization35,659,57955,138,29818,792,478109590355Maintenance and repair53,455,90621,147,18515,568,90290171993Insurance premium11,858,1378,846,6774,877,96325582777Others158,480,46876,905,55436,300,729271686751Total cost801,920,838527,304,895255,050,9651584276698


### 3.2. Questionnaire Design

The questionnaire is divided into three parts as a whole: the first part is the survey of the basic situation of the respondents, which appears in the form of multiple-choice questions; the paper questionnaire survey is the traditional questionnaire survey. The survey company distributes these paper questionnaires by employing workers to collect the answers. This form of questionnaire has some shortcomings, analysis and statistical results are troublesome, and the cost is relatively high. The second part is the respondents’ subjective evaluation of bus service, which appears in the form of 1–5 scoring system, with 22 questions and five dimensions. The third part is an open question, which appears in the form of filling in the blank. Before the formal distribution of the questionnaire, the pretest was carried out (a total of 40 questionnaires were distributed), and the test results of reliability and validity met the requirements. The formal questionnaire was distributed and filled in on site, with a total of 550 copies distributed. The unanswered, missed, and random questionnaires were excluded, and the remaining 411 valid questionnaires could be used for later analysis. Online questionnaire survey means that users rely on some online questionnaire websites, which provide a series of services such as designing questionnaires, issuing questionnaires, and analyzing results. This method has the advantages of no geographical restrictions and relatively low cost, and the disadvantage is that the quality of the answer cannot be guaranteed.


### 3.3. Descriptive Statistics

Through the descriptive statistics of the sample characteristics of 411 questionnaires, it can be seen that the number of men and women respondents are 232 and 179, respectively, with the proportion of 56.4% and 43.6%, respectively. 159 respondents under the age of 20, accounting for 38.7% of the total; 141 people aged 21–30, accounting for 34.4% of the total; the remaining number of people over the age of 30 is 111, accounting for 26.9% of the total. In terms of income, 294 respondents have a monthly income of less than 10000, accounting for 71.5% of the total; there are 83 people with income of 10000–20000, accounting for 20.2%. From the above results, it can be seen that the main passengers of public buses are students and wage earners with a monthly income of less than 10000, and the proportion of male and female passengers is close.


### 3.4. Data Analysis

#### 3.4.1. Reliability and Validity Test

Cronbach’sα is commonly used in reliability analysis and test. The coefficient evaluates the reliability of the data, and the range of the coefficient is 0<Cronbach’sα. The coefficient is less than 1, and the closer the coefficient is to 1, the better the reliability of the questionnaire and related data. Validity analysis usually uses KMO and Bartlett spherical values for observation. The closer the KMO value is to 1, the stronger the correlation between variables, which shows that the questionnaire sample meets the basic requirements of factor analysis. Tables 2 and 3 show the reliability and validity analysis results of this study, respectively. The Cronbach coefficient measures the internal consistency of the test according to a certain formula and is used as an indicator of reliability. It overcomes the shortcomings of the partial halving method and is the most commonly used reliability index in social research. It measures the reliability of a group of synonymous or parallel tests.Table 2
Reliability analysis results.
Project dimensionNumber of itemsCronbach’sα coefficientQuestionnaire as a whole660.929Service importance220.949Customer expectation220.925Customer perceived quality220.941Finance60.783Table 3
Results of validity analysis.
Questionnaire dimensionKMO metricsBartlett sphericity testApproximate square cardDFSigQuestionnaire as a whole0.83920665.59821450.000Service importance0.9126346.4592310.000Customer expectation0.8955918.7142310.000Customer perceived quality0.8914737.0872310.000As can be seen from Table2, the Cronbach’s α of the project dimension, the coefficient is between 0.783 and 0.949, and the overall Cronbach’s α of the coefficient is 0.929 indicating that the questionnaire has good reliability. In Table 3, the KMO value of the questionnaire dimension is between 0.839 and 0.912, and the probability values of Bartlett sphericity test are less than 0.001, reaching a significant level, indicating that it is suitable for factor analysis.


#### 3.4.2. Dimension Reduction and Factor Analysis

Through analysis, dimensionality reduction, factor analysis, and extraction, this study obtains the rotating component matrix of service importance, customer expectation, and perceived quality. The main purpose of factor analysis is to describe some more basic variables hidden in a group of measured variables, but they cannot be directly measured as shown in Table4. In Table 4, the component dimension with the largest explanatory power corresponding to each variable is in italics, which can be summarized into the corresponding longitudinal dimension in turn. After sorting out the relationship between the independent variables in the potential variables, the following dimensionality reduction results are summarized. Service importance includes bus hardware objective service, bus staff software subjective service, safety guarantee service, and personalized service; customer expectation includes bus hardware objective service, bus staff software subjective service, security service, personalized service, and time demand service; and perceived quality includes bus hardware objective service, bus staff software subjective service, security service, and personalized service. Enterprises should focus on basic service items and ensure that the promises made to the customers can reflect the real service level and that they are fulfilled through practical efforts and measures. Excessive promises are difficult to fulfill, which will lose the trust of customers and undermine their tolerance, which is detrimental to the enterprise.Table 4
Rotation component matrix.
VariableService importanceCustomer expectationPerceived qualityIngredientsIngredientsIngredients123412345123410.7960.1930.1010.0210.8200.1620.0570.0810.1540.7820.2420.1660.20920.7760.1610.3050.1060.8160.1520.2530.0880.1350.7780.1440.231-0.03930.7520.332-0.0590.2650.7110.3820.2010.060-0.1320.6230.4440.130-0.06140.7470.2730.1130.1970.6830.2580.2550.1630.0880.6080.4430.2000.14450.7080.2280.2590.1010.6790.3880.0700.294-0.1690.6050.0690.2050.38960.6620.1780.3820.1460.6720.0510.1420.4550.1260.5870.2090.3970.03370.6310.5440.1800.1680.6030.5060.1460.2390.0570.5450.4510.1850.08580.6110.4790.329-0.0260.2750.7940.2440.1130.0490.0860.7930.1490.21490.5830.1460.2250.4280.4200.6500.3340.1290.1440.2240.6590.1250.373100.3890.7180.2230.0780.2790.6410.1900.2470.3700.3090.5800.106-0.065110.2610.714-0.0990.2240.4950.5850.317-0.0030.1560.3370.5280.2170.207120.3140.7010.3820.0580.2910.5240.2940.480-0.3200.4880.5200.1630.364130.1210.6080.3690.2350.3050.516-0.2890.4720.1010.2400.4800.4380.298140.5410.5540.3770.1330.1400.1600.7380.1450.0800.2190.0560.7350.178150.1640.5370.4010.3420.3200.1820.6470.0740.1910.1810.0640.6870.356160.0510.2960.766-0.0810.0940.1050.6410.3080.1590.0960.3100.6850.088170.3830.0750.6640.1110.4440.3460.5470.109-0.0270.2250.1030.5980.013180.0980.0930.6420.3770.1680.0040.2520.8220.0160.2010.1140.5920.505190.3550.1490.6270.2440.0520.4680.3460.5550.1440.1920.4820.5870.026200.3150.3940.4410.4330.1800.3620.1040.5150.3950.0280.2230.0600.693210.1320.2100.2090.8270.2720.3420.3140.4890.275-0.0320.2000.1720.671220.4500.4790.0470.5140.0680.1280.2660.1240.8430.430-0.0730.2480.621


#### 3.4.3. Construction of Perceived Value Relationship Model

Through literature research, it can be seen that perceived value interacts with three dimensions: service importance, customer expectation, and perceived quality, and perceived value will have an impact on satisfaction. Therefore, according to the dimensionality reduction results above, the mean value matrix of the horizontal and vertical dimensions of the questionnaire is obtained after the mean value processing of various factors of the questionnaire as shown in Table5. The essence of customer value is customer perception, that is, customers’ subjective perception of the interaction process and results with an enterprise, including the comparison and balance between customers’ perceived gains and losses. Customer perceived value refers to customers’ subjective perception of the value of products or services provided by enterprises.Table 5
Mean matrix of horizontal and vertical dimensions of questionnaire.
Vertical dimensionService importanceCustomer expectationPerceived qualityBus hardware objective service4.03.93.3Bus staff software subjective service3.93.93.2Security services3.73.93.1Personalized service3.83.72.9Time demand service—3.8—Mean value3.93.83.1In addition, this study introduces the potential variable of finance to integrate with other dimensions. Now, we fit the financial data, mainly sort out six items: personnel expenses, fuel expenses, depreciation and amortization expenses, maintenance and repair, insurance expenses, and other expenses, allocate other expenses to the remaining five items, convert them into a five-point system, and finally get the four-dimensional score table of this study (Table6). The personnel cost rate is a relative indicator that reflects the labor cost-effectiveness. Its reciprocal indicates how much sales revenue can be achieved for each unit of labor cost invested. However, the sales revenue includes the transfer value of materialized labor, which is greatly affected by the organic composition of the enterprise and the structure of products. It is not as good as the labor distribution rate for horizontal comparison.Table 6
Four-dimensional score.
NameScoreService importance3.9Customer expectation3.8Perceived quality3.1Finance1.0It can be seen from Table6 that the score of finance is lower than that of other dimensions, less than 3 points, indicating that the impact of cost on service effect is not obvious in public bus service. Perceived value is significantly affected by service importance, customer expectation, and perceived quality and can be used as a causal variable. Therefore, after excluding the financial dimension, the index pool affecting Macao bus service satisfaction is obtained (Table 7).Table 7
Macao bus service satisfaction index pool.
Horizontal dimensionNumberIndexService importance (F1)F1aBus hardware objective serviceF1bBus staff software subjective serviceF1cSecurity servicesF1dPersonalized serviceCustomer expectation (F2)F2aBus hardware objective serviceF2bBus staff software subjective serviceF2cSecurity servicesF2dPersonalized serviceF2eTime demand servicePerceived quality (F3)F3aBus hardware objective serviceF3bBus staff software subjective serviceF3cSecurity servicesF3dPersonalized service


### 3.5. Satisfaction Regression Analysis

In order to clarify the impact of each index on bus passenger satisfaction, the study will select three horizontal dimensions: service importance, customer expectation, and perceived quality, take the index after extracting the principal component as the independent variable and service satisfaction as the dependent variable, combine the two to analyze and construct the regression equation model, and obtain the results of three-dimensional analysis of variance in Table8. Principal component analysis is a multivariate statistical method to investigate the correlation between multiple variables. It studies how to reveal the internal structure of multiple variables through a few principal components, that is, derive a few principal components from the original variables, so that they retain as much information of the original variables as possible and are not related to each other.Table 8
Results of horizontal dimension analysis of variance.
ModelSum of squaresDFMean squareFSigIndependent variableDependent variableImportanceF1Regression4.55241.1380.922.451BY1F1a, F1b, F1c, F1dResidual500.8644061.234Total505.416410Expectation degreeF2Regression73.319514.66413.744.000BY2F2a, F2b, F2c, F2d, F2eResidual432.0974051.067Total505.416410Perceived qualityF3Regression374.348493.587289.897.000BY3F3a, F3b, F3c, F3dResidual131.0684060.323Total505.416410It can be seen from Table8 that the relationship between dependent variables and independent variables of customer expectation and perceived quality is significant, and a linear regression equation can be constructed. The F value of service importance is 0.922, and the significance (Sig) value is 0.451>0.05, indicating that the relationship between dependent variables and independent variables is not significant, so linear regression equation cannot be constructed. Table 9 shows the regression model of customer expectation and perceived quality.Table 9
Horizontal dimension regression model.
ModelNonstandardized coefficientStandard coefficientTSigBStandard errorTrial versionCustomer expectationF2(Constant)2.8320.05155.5860.000F2a-0.3760.051-0.436-4.5640.000F2b-0.1550.051-0.139-3.0300.003F2c-0.1640.051-0.169-2.2350.026F2d-0.0830.051-0.075-1.6250.105F2e-0.1820.051-0.164-3.5670.000Perceived qualityF3(Constant)2.8320.028101.0520.000F3a0.8680.0280.78230.9280.000F3b0.2690.0280.2429.5700.000F3c0.1840.0280.1666.5680.000F3d0.2320.0280.2098.2640.000The results in Table9 show that in the customer expectation, the sig value meets the requirements. The indexes entering the equation are F2a, F2b, F2c, and F2e, and the regression coefficients are: -0.376, -0.155, -0.164, and -0.182, respectively; in the perception quality, the sig value meets the requirements, and the indexes entering the equation are F3a, F3b, F3c, and F3d. The regression coefficients are 0.868, 0.269, 0.184, and 0.232, respectively.


### 3.6. Structural Equation Model Verification

Based on the above research framework, the model has 7 potential variables and 20 observation variables, and the model is constructed by structural equation processing and analysis. The fitting and adjusted results are shown in Figure2. The analysis of path fitting related indexes is shown in Table 10. Generally, the structural equation model is expressed in the form of path graph, which is the simplest and most intuitive method to describe the model. Researchers can directly and clearly show the relationship between variables in a graphical way with the help of path graph. The popular Amos software can directly use the model setting of the path graph for analysis and directly identify the analysis results in the graph.Figure 2
Structural equation analysis results.Table 10
Correlation index analysis of path fitting.
Influence relationshipEstimateCRPLabelH1: Customer expectationA kind ofservice importance0.278.51∗∗∗SupportH2: Perceived qualityA kind ofservice importance0.056.32∗∗∗SupportH3: Perceived valueA kind ofservice importance-0.076.35∗∗∗SupportH4: Perceived qualityA kind ofcustomer expectation-0.417.11∗∗∗SupportH5: Perceived valueA kind ofcustomer expectation-0.266.21∗∗∗SupportH6: Perceived valueA kind ofperceived quality0.603.84∗∗∗SupportH7: SatisfactionA kind ofcustomer expectation-0.289.69∗∗∗SupportH8: SatisfactionA kind ofperceived quality0.738.04∗∗∗SupportH9: SatisfactionA kind ofperceived value0.646.55∗∗∗SupportH10: FinanceA kind ofsatisfaction0.565.89∗∗∗SupportH11: Actual useA kind ofsatisfaction0.682.84∗∗∗SupportAs can be seen from Figure2, the path coefficient between six variables is greater than 0.1, indicating that the correlation is more significant, and the path coefficient model is basically acceptable. It can be seen from Table 10 that after the model is fitted, each fitting index can reflect a good degree of fit, and the P value meets the standard, which is in line with the significance test. Therefore, the model can better reflect the action relationship between various variables.


### 3.7. Result Analysis

It can be seen from the significance test results that the research hypotheses H1–H11 are supported. Among them, the actual perceived quality has a significant impact on the overall perceived value and final satisfaction and occupies a leading position. In terms of the impact of the three-level indicators on horizontal dimensions, F1a, F1b, F1c, and F1d have a great impact on service importance; F2a, F2b, F2c, and F2e have an impact on customer expectation of more than 0.6; in terms of perceived quality, F3a has the greatest impact on it, F3b and F3c have almost the same impact on perceived quality, while F3d has the least impact on perceived quality. According to the structural equation verification, the following research results can be obtained.Service importance directly affects customer expectation, perceived quality, and perceived value and indirectly affects final satisfaction. Among them, service importance has a positive impact on customer expectation, which is the first link to improve customer satisfaction; service importance has a weak negative correlation with perceived quality and perceived value. It can be seen that service importance has no great impact on passengers’ actual perceived quality and perceived value.Customer expectation has a negative impact on perceived quality, perceived value, and final satisfaction. The higher the expectation of passengers on bus service performance, the lower the actual perceived quality and the lower the satisfaction. Customer expectation is a key factor affecting bus passengers’ perceived quality, perceived value, and satisfaction. It is an important link to improve satisfaction.Perceived quality is positively correlated with perceived value and final satisfaction and so is perceived value and satisfaction. In other words, passengers’ satisfaction with taking the bus is influenced by perceived value and perceived quality. If you want to improve satisfaction, you can improve passengers’ perceived quality and perceived value. The better the customers’ perception is, the higher their satisfaction. To improve customer perceived value, we can start with value exploration, value structure, communication value, organization and training to deliver value, to manage customer payment to improve its perceived value, and enterprises should try their best to maintain the original customers, partners, and employees, so as to ensure that the delivery of value is more effective in economy and productivity.Finance and actual use are the outcome variables of satisfaction. Satisfaction is positively correlated with bus company finance and actual use. It can be shown that improving passenger satisfaction can not only cultivate Macao residents’ public transport travel habits but also improve the financial data of bus companies.


## 3.1. Data Source

Combined with the above research, this paper designs two horizontal and vertical dimensions. The horizontal dimensions are service importance, customer expectation, perceived quality, and finance. Customer complaints, especially reasonable complaints, are the most representative and concentrated reflection of customer expectations. Therefore, it is particularly important to analyze, process, summarize, and sort out customer complaint information and evaluate customer expectations. Through the information screening and filtering of customers’ reasonable complaints, the expected information of customers is refined to form the basic information of customers’ expectations. Among them, service importance, customer expectation, and perceived quality are collected in the form of questionnaires, and financial data are collected through interviews and searching the official website. Table1 shows the financial data of Macao bus companies in 2018. The longitudinal dimension is designed through the questionnaire, which is mainly based on the SERVQUAL model scale [12]. From the perspective of the “triangle law of customer satisfaction”, although customer expectation is a reaction to customer satisfaction, it is not the lower the better. If customer expectation is very low, it means that customers have nothing to ask for service or products, let alone satisfaction and loyalty. Therefore, in order to reasonably control customers’ expectations, on the one hand, we should actively face customers’ expectations and constantly improve our own services; on the other hand, we should reasonably guide customers’ expectations, starting from the source and try to avoid the emergence of customers’ unreasonable expectations as much as possible.Table 1
List of financial data of Macao bus companies in 2018 (in MOP).
Expense itemNew benefitsAobaNew eraTotal costPersonnel costs399,639,983258,894,090119,556,487778090560Fuel cost142,826,765106,373,09159,954,406309154262Depreciation and amortization35,659,57955,138,29818,792,478109590355Maintenance and repair53,455,90621,147,18515,568,90290171993Insurance premium11,858,1378,846,6774,877,96325582777Others158,480,46876,905,55436,300,729271686751Total cost801,920,838527,304,895255,050,9651584276698


## 3.2. Questionnaire Design

The questionnaire is divided into three parts as a whole: the first part is the survey of the basic situation of the respondents, which appears in the form of multiple-choice questions; the paper questionnaire survey is the traditional questionnaire survey. The survey company distributes these paper questionnaires by employing workers to collect the answers. This form of questionnaire has some shortcomings, analysis and statistical results are troublesome, and the cost is relatively high. The second part is the respondents’ subjective evaluation of bus service, which appears in the form of 1–5 scoring system, with 22 questions and five dimensions. The third part is an open question, which appears in the form of filling in the blank. Before the formal distribution of the questionnaire, the pretest was carried out (a total of 40 questionnaires were distributed), and the test results of reliability and validity met the requirements. The formal questionnaire was distributed and filled in on site, with a total of 550 copies distributed. The unanswered, missed, and random questionnaires were excluded, and the remaining 411 valid questionnaires could be used for later analysis. Online questionnaire survey means that users rely on some online questionnaire websites, which provide a series of services such as designing questionnaires, issuing questionnaires, and analyzing results. This method has the advantages of no geographical restrictions and relatively low cost, and the disadvantage is that the quality of the answer cannot be guaranteed.


## 3.3. Descriptive Statistics

Through the descriptive statistics of the sample characteristics of 411 questionnaires, it can be seen that the number of men and women respondents are 232 and 179, respectively, with the proportion of 56.4% and 43.6%, respectively. 159 respondents under the age of 20, accounting for 38.7% of the total; 141 people aged 21–30, accounting for 34.4% of the total; the remaining number of people over the age of 30 is 111, accounting for 26.9% of the total. In terms of income, 294 respondents have a monthly income of less than 10000, accounting for 71.5% of the total; there are 83 people with income of 10000–20000, accounting for 20.2%. From the above results, it can be seen that the main passengers of public buses are students and wage earners with a monthly income of less than 10000, and the proportion of male and female passengers is close.


## 3.4. Data Analysis

### 3.4.1. Reliability and Validity Test

Cronbach’sα is commonly used in reliability analysis and test. The coefficient evaluates the reliability of the data, and the range of the coefficient is 0<Cronbach’sα. The coefficient is less than 1, and the closer the coefficient is to 1, the better the reliability of the questionnaire and related data. Validity analysis usually uses KMO and Bartlett spherical values for observation. The closer the KMO value is to 1, the stronger the correlation between variables, which shows that the questionnaire sample meets the basic requirements of factor analysis. Tables 2 and 3 show the reliability and validity analysis results of this study, respectively. The Cronbach coefficient measures the internal consistency of the test according to a certain formula and is used as an indicator of reliability. It overcomes the shortcomings of the partial halving method and is the most commonly used reliability index in social research. It measures the reliability of a group of synonymous or parallel tests.Table 2
Reliability analysis results.
Project dimensionNumber of itemsCronbach’sα coefficientQuestionnaire as a whole660.929Service importance220.949Customer expectation220.925Customer perceived quality220.941Finance60.783Table 3
Results of validity analysis.
Questionnaire dimensionKMO metricsBartlett sphericity testApproximate square cardDFSigQuestionnaire as a whole0.83920665.59821450.000Service importance0.9126346.4592310.000Customer expectation0.8955918.7142310.000Customer perceived quality0.8914737.0872310.000As can be seen from Table2, the Cronbach’s α of the project dimension, the coefficient is between 0.783 and 0.949, and the overall Cronbach’s α of the coefficient is 0.929 indicating that the questionnaire has good reliability. In Table 3, the KMO value of the questionnaire dimension is between 0.839 and 0.912, and the probability values of Bartlett sphericity test are less than 0.001, reaching a significant level, indicating that it is suitable for factor analysis.


### 3.4.2. Dimension Reduction and Factor Analysis

Through analysis, dimensionality reduction, factor analysis, and extraction, this study obtains the rotating component matrix of service importance, customer expectation, and perceived quality. The main purpose of factor analysis is to describe some more basic variables hidden in a group of measured variables, but they cannot be directly measured as shown in Table4. In Table 4, the component dimension with the largest explanatory power corresponding to each variable is in italics, which can be summarized into the corresponding longitudinal dimension in turn. After sorting out the relationship between the independent variables in the potential variables, the following dimensionality reduction results are summarized. Service importance includes bus hardware objective service, bus staff software subjective service, safety guarantee service, and personalized service; customer expectation includes bus hardware objective service, bus staff software subjective service, security service, personalized service, and time demand service; and perceived quality includes bus hardware objective service, bus staff software subjective service, security service, and personalized service. Enterprises should focus on basic service items and ensure that the promises made to the customers can reflect the real service level and that they are fulfilled through practical efforts and measures. Excessive promises are difficult to fulfill, which will lose the trust of customers and undermine their tolerance, which is detrimental to the enterprise.Table 4
Rotation component matrix.
VariableService importanceCustomer expectationPerceived qualityIngredientsIngredientsIngredients123412345123410.7960.1930.1010.0210.8200.1620.0570.0810.1540.7820.2420.1660.20920.7760.1610.3050.1060.8160.1520.2530.0880.1350.7780.1440.231-0.03930.7520.332-0.0590.2650.7110.3820.2010.060-0.1320.6230.4440.130-0.06140.7470.2730.1130.1970.6830.2580.2550.1630.0880.6080.4430.2000.14450.7080.2280.2590.1010.6790.3880.0700.294-0.1690.6050.0690.2050.38960.6620.1780.3820.1460.6720.0510.1420.4550.1260.5870.2090.3970.03370.6310.5440.1800.1680.6030.5060.1460.2390.0570.5450.4510.1850.08580.6110.4790.329-0.0260.2750.7940.2440.1130.0490.0860.7930.1490.21490.5830.1460.2250.4280.4200.6500.3340.1290.1440.2240.6590.1250.373100.3890.7180.2230.0780.2790.6410.1900.2470.3700.3090.5800.106-0.065110.2610.714-0.0990.2240.4950.5850.317-0.0030.1560.3370.5280.2170.207120.3140.7010.3820.0580.2910.5240.2940.480-0.3200.4880.5200.1630.364130.1210.6080.3690.2350.3050.516-0.2890.4720.1010.2400.4800.4380.298140.5410.5540.3770.1330.1400.1600.7380.1450.0800.2190.0560.7350.178150.1640.5370.4010.3420.3200.1820.6470.0740.1910.1810.0640.6870.356160.0510.2960.766-0.0810.0940.1050.6410.3080.1590.0960.3100.6850.088170.3830.0750.6640.1110.4440.3460.5470.109-0.0270.2250.1030.5980.013180.0980.0930.6420.3770.1680.0040.2520.8220.0160.2010.1140.5920.505190.3550.1490.6270.2440.0520.4680.3460.5550.1440.1920.4820.5870.026200.3150.3940.4410.4330.1800.3620.1040.5150.3950.0280.2230.0600.693210.1320.2100.2090.8270.2720.3420.3140.4890.275-0.0320.2000.1720.671220.4500.4790.0470.5140.0680.1280.2660.1240.8430.430-0.0730.2480.621


### 3.4.3. Construction of Perceived Value Relationship Model

Through literature research, it can be seen that perceived value interacts with three dimensions: service importance, customer expectation, and perceived quality, and perceived value will have an impact on satisfaction. Therefore, according to the dimensionality reduction results above, the mean value matrix of the horizontal and vertical dimensions of the questionnaire is obtained after the mean value processing of various factors of the questionnaire as shown in Table5. The essence of customer value is customer perception, that is, customers’ subjective perception of the interaction process and results with an enterprise, including the comparison and balance between customers’ perceived gains and losses. Customer perceived value refers to customers’ subjective perception of the value of products or services provided by enterprises.Table 5
Mean matrix of horizontal and vertical dimensions of questionnaire.
Vertical dimensionService importanceCustomer expectationPerceived qualityBus hardware objective service4.03.93.3Bus staff software subjective service3.93.93.2Security services3.73.93.1Personalized service3.83.72.9Time demand service—3.8—Mean value3.93.83.1In addition, this study introduces the potential variable of finance to integrate with other dimensions. Now, we fit the financial data, mainly sort out six items: personnel expenses, fuel expenses, depreciation and amortization expenses, maintenance and repair, insurance expenses, and other expenses, allocate other expenses to the remaining five items, convert them into a five-point system, and finally get the four-dimensional score table of this study (Table6). The personnel cost rate is a relative indicator that reflects the labor cost-effectiveness. Its reciprocal indicates how much sales revenue can be achieved for each unit of labor cost invested. However, the sales revenue includes the transfer value of materialized labor, which is greatly affected by the organic composition of the enterprise and the structure of products. It is not as good as the labor distribution rate for horizontal comparison.Table 6
Four-dimensional score.
NameScoreService importance3.9Customer expectation3.8Perceived quality3.1Finance1.0It can be seen from Table6 that the score of finance is lower than that of other dimensions, less than 3 points, indicating that the impact of cost on service effect is not obvious in public bus service. Perceived value is significantly affected by service importance, customer expectation, and perceived quality and can be used as a causal variable. Therefore, after excluding the financial dimension, the index pool affecting Macao bus service satisfaction is obtained (Table 7).Table 7
Macao bus service satisfaction index pool.
Horizontal dimensionNumberIndexService importance (F1)F1aBus hardware objective serviceF1bBus staff software subjective serviceF1cSecurity servicesF1dPersonalized serviceCustomer expectation (F2)F2aBus hardware objective serviceF2bBus staff software subjective serviceF2cSecurity servicesF2dPersonalized serviceF2eTime demand servicePerceived quality (F3)F3aBus hardware objective serviceF3bBus staff software subjective serviceF3cSecurity servicesF3dPersonalized service


## 3.4.1. Reliability and Validity Test

Cronbach’sα is commonly used in reliability analysis and test. The coefficient evaluates the reliability of the data, and the range of the coefficient is 0<Cronbach’sα. The coefficient is less than 1, and the closer the coefficient is to 1, the better the reliability of the questionnaire and related data. Validity analysis usually uses KMO and Bartlett spherical values for observation. The closer the KMO value is to 1, the stronger the correlation between variables, which shows that the questionnaire sample meets the basic requirements of factor analysis. Tables 2 and 3 show the reliability and validity analysis results of this study, respectively. The Cronbach coefficient measures the internal consistency of the test according to a certain formula and is used as an indicator of reliability. It overcomes the shortcomings of the partial halving method and is the most commonly used reliability index in social research. It measures the reliability of a group of synonymous or parallel tests.Table 2
Reliability analysis results.
Project dimensionNumber of itemsCronbach’sα coefficientQuestionnaire as a whole660.929Service importance220.949Customer expectation220.925Customer perceived quality220.941Finance60.783Table 3
Results of validity analysis.
Questionnaire dimensionKMO metricsBartlett sphericity testApproximate square cardDFSigQuestionnaire as a whole0.83920665.59821450.000Service importance0.9126346.4592310.000Customer expectation0.8955918.7142310.000Customer perceived quality0.8914737.0872310.000As can be seen from Table2, the Cronbach’s α of the project dimension, the coefficient is between 0.783 and 0.949, and the overall Cronbach’s α of the coefficient is 0.929 indicating that the questionnaire has good reliability. In Table 3, the KMO value of the questionnaire dimension is between 0.839 and 0.912, and the probability values of Bartlett sphericity test are less than 0.001, reaching a significant level, indicating that it is suitable for factor analysis.


## 3.4.2. Dimension Reduction and Factor Analysis

Through analysis, dimensionality reduction, factor analysis, and extraction, this study obtains the rotating component matrix of service importance, customer expectation, and perceived quality. The main purpose of factor analysis is to describe some more basic variables hidden in a group of measured variables, but they cannot be directly measured as shown in Table4. In Table 4, the component dimension with the largest explanatory power corresponding to each variable is in italics, which can be summarized into the corresponding longitudinal dimension in turn. After sorting out the relationship between the independent variables in the potential variables, the following dimensionality reduction results are summarized. Service importance includes bus hardware objective service, bus staff software subjective service, safety guarantee service, and personalized service; customer expectation includes bus hardware objective service, bus staff software subjective service, security service, personalized service, and time demand service; and perceived quality includes bus hardware objective service, bus staff software subjective service, security service, and personalized service. Enterprises should focus on basic service items and ensure that the promises made to the customers can reflect the real service level and that they are fulfilled through practical efforts and measures. Excessive promises are difficult to fulfill, which will lose the trust of customers and undermine their tolerance, which is detrimental to the enterprise.Table 4
Rotation component matrix.
VariableService importanceCustomer expectationPerceived qualityIngredientsIngredientsIngredients123412345123410.7960.1930.1010.0210.8200.1620.0570.0810.1540.7820.2420.1660.20920.7760.1610.3050.1060.8160.1520.2530.0880.1350.7780.1440.231-0.03930.7520.332-0.0590.2650.7110.3820.2010.060-0.1320.6230.4440.130-0.06140.7470.2730.1130.1970.6830.2580.2550.1630.0880.6080.4430.2000.14450.7080.2280.2590.1010.6790.3880.0700.294-0.1690.6050.0690.2050.38960.6620.1780.3820.1460.6720.0510.1420.4550.1260.5870.2090.3970.03370.6310.5440.1800.1680.6030.5060.1460.2390.0570.5450.4510.1850.08580.6110.4790.329-0.0260.2750.7940.2440.1130.0490.0860.7930.1490.21490.5830.1460.2250.4280.4200.6500.3340.1290.1440.2240.6590.1250.373100.3890.7180.2230.0780.2790.6410.1900.2470.3700.3090.5800.106-0.065110.2610.714-0.0990.2240.4950.5850.317-0.0030.1560.3370.5280.2170.207120.3140.7010.3820.0580.2910.5240.2940.480-0.3200.4880.5200.1630.364130.1210.6080.3690.2350.3050.516-0.2890.4720.1010.2400.4800.4380.298140.5410.5540.3770.1330.1400.1600.7380.1450.0800.2190.0560.7350.178150.1640.5370.4010.3420.3200.1820.6470.0740.1910.1810.0640.6870.356160.0510.2960.766-0.0810.0940.1050.6410.3080.1590.0960.3100.6850.088170.3830.0750.6640.1110.4440.3460.5470.109-0.0270.2250.1030.5980.013180.0980.0930.6420.3770.1680.0040.2520.8220.0160.2010.1140.5920.505190.3550.1490.6270.2440.0520.4680.3460.5550.1440.1920.4820.5870.026200.3150.3940.4410.4330.1800.3620.1040.5150.3950.0280.2230.0600.693210.1320.2100.2090.8270.2720.3420.3140.4890.275-0.0320.2000.1720.671220.4500.4790.0470.5140.0680.1280.2660.1240.8430.430-0.0730.2480.621


## 3.4.3. Construction of Perceived Value Relationship Model

Through literature research, it can be seen that perceived value interacts with three dimensions: service importance, customer expectation, and perceived quality, and perceived value will have an impact on satisfaction. Therefore, according to the dimensionality reduction results above, the mean value matrix of the horizontal and vertical dimensions of the questionnaire is obtained after the mean value processing of various factors of the questionnaire as shown in Table5. The essence of customer value is customer perception, that is, customers’ subjective perception of the interaction process and results with an enterprise, including the comparison and balance between customers’ perceived gains and losses. Customer perceived value refers to customers’ subjective perception of the value of products or services provided by enterprises.Table 5
Mean matrix of horizontal and vertical dimensions of questionnaire.
Vertical dimensionService importanceCustomer expectationPerceived qualityBus hardware objective service4.03.93.3Bus staff software subjective service3.93.93.2Security services3.73.93.1Personalized service3.83.72.9Time demand service—3.8—Mean value3.93.83.1In addition, this study introduces the potential variable of finance to integrate with other dimensions. Now, we fit the financial data, mainly sort out six items: personnel expenses, fuel expenses, depreciation and amortization expenses, maintenance and repair, insurance expenses, and other expenses, allocate other expenses to the remaining five items, convert them into a five-point system, and finally get the four-dimensional score table of this study (Table6). The personnel cost rate is a relative indicator that reflects the labor cost-effectiveness. Its reciprocal indicates how much sales revenue can be achieved for each unit of labor cost invested. However, the sales revenue includes the transfer value of materialized labor, which is greatly affected by the organic composition of the enterprise and the structure of products. It is not as good as the labor distribution rate for horizontal comparison.Table 6
Four-dimensional score.
NameScoreService importance3.9Customer expectation3.8Perceived quality3.1Finance1.0It can be seen from Table6 that the score of finance is lower than that of other dimensions, less than 3 points, indicating that the impact of cost on service effect is not obvious in public bus service. Perceived value is significantly affected by service importance, customer expectation, and perceived quality and can be used as a causal variable. Therefore, after excluding the financial dimension, the index pool affecting Macao bus service satisfaction is obtained (Table 7).Table 7
Macao bus service satisfaction index pool.
Horizontal dimensionNumberIndexService importance (F1)F1aBus hardware objective serviceF1bBus staff software subjective serviceF1cSecurity servicesF1dPersonalized serviceCustomer expectation (F2)F2aBus hardware objective serviceF2bBus staff software subjective serviceF2cSecurity servicesF2dPersonalized serviceF2eTime demand servicePerceived quality (F3)F3aBus hardware objective serviceF3bBus staff software subjective serviceF3cSecurity servicesF3dPersonalized service


## 3.5. Satisfaction Regression Analysis

In order to clarify the impact of each index on bus passenger satisfaction, the study will select three horizontal dimensions: service importance, customer expectation, and perceived quality, take the index after extracting the principal component as the independent variable and service satisfaction as the dependent variable, combine the two to analyze and construct the regression equation model, and obtain the results of three-dimensional analysis of variance in Table8. Principal component analysis is a multivariate statistical method to investigate the correlation between multiple variables. It studies how to reveal the internal structure of multiple variables through a few principal components, that is, derive a few principal components from the original variables, so that they retain as much information of the original variables as possible and are not related to each other.Table 8
Results of horizontal dimension analysis of variance.
ModelSum of squaresDFMean squareFSigIndependent variableDependent variableImportanceF1Regression4.55241.1380.922.451BY1F1a, F1b, F1c, F1dResidual500.8644061.234Total505.416410Expectation degreeF2Regression73.319514.66413.744.000BY2F2a, F2b, F2c, F2d, F2eResidual432.0974051.067Total505.416410Perceived qualityF3Regression374.348493.587289.897.000BY3F3a, F3b, F3c, F3dResidual131.0684060.323Total505.416410It can be seen from Table8 that the relationship between dependent variables and independent variables of customer expectation and perceived quality is significant, and a linear regression equation can be constructed. The F value of service importance is 0.922, and the significance (Sig) value is 0.451>0.05, indicating that the relationship between dependent variables and independent variables is not significant, so linear regression equation cannot be constructed. Table 9 shows the regression model of customer expectation and perceived quality.Table 9
Horizontal dimension regression model.
ModelNonstandardized coefficientStandard coefficientTSigBStandard errorTrial versionCustomer expectationF2(Constant)2.8320.05155.5860.000F2a-0.3760.051-0.436-4.5640.000F2b-0.1550.051-0.139-3.0300.003F2c-0.1640.051-0.169-2.2350.026F2d-0.0830.051-0.075-1.6250.105F2e-0.1820.051-0.164-3.5670.000Perceived qualityF3(Constant)2.8320.028101.0520.000F3a0.8680.0280.78230.9280.000F3b0.2690.0280.2429.5700.000F3c0.1840.0280.1666.5680.000F3d0.2320.0280.2098.2640.000The results in Table9 show that in the customer expectation, the sig value meets the requirements. The indexes entering the equation are F2a, F2b, F2c, and F2e, and the regression coefficients are: -0.376, -0.155, -0.164, and -0.182, respectively; in the perception quality, the sig value meets the requirements, and the indexes entering the equation are F3a, F3b, F3c, and F3d. The regression coefficients are 0.868, 0.269, 0.184, and 0.232, respectively.


## 3.6. Structural Equation Model Verification

Based on the above research framework, the model has 7 potential variables and 20 observation variables, and the model is constructed by structural equation processing and analysis. The fitting and adjusted results are shown in Figure2. The analysis of path fitting related indexes is shown in Table 10. Generally, the structural equation model is expressed in the form of path graph, which is the simplest and most intuitive method to describe the model. Researchers can directly and clearly show the relationship between variables in a graphical way with the help of path graph. The popular Amos software can directly use the model setting of the path graph for analysis and directly identify the analysis results in the graph.Figure 2
Structural equation analysis results.Table 10
Correlation index analysis of path fitting.
Influence relationshipEstimateCRPLabelH1: Customer expectationA kind ofservice importance0.278.51∗∗∗SupportH2: Perceived qualityA kind ofservice importance0.056.32∗∗∗SupportH3: Perceived valueA kind ofservice importance-0.076.35∗∗∗SupportH4: Perceived qualityA kind ofcustomer expectation-0.417.11∗∗∗SupportH5: Perceived valueA kind ofcustomer expectation-0.266.21∗∗∗SupportH6: Perceived valueA kind ofperceived quality0.603.84∗∗∗SupportH7: SatisfactionA kind ofcustomer expectation-0.289.69∗∗∗SupportH8: SatisfactionA kind ofperceived quality0.738.04∗∗∗SupportH9: SatisfactionA kind ofperceived value0.646.55∗∗∗SupportH10: FinanceA kind ofsatisfaction0.565.89∗∗∗SupportH11: Actual useA kind ofsatisfaction0.682.84∗∗∗SupportAs can be seen from Figure2, the path coefficient between six variables is greater than 0.1, indicating that the correlation is more significant, and the path coefficient model is basically acceptable. It can be seen from Table 10 that after the model is fitted, each fitting index can reflect a good degree of fit, and the P value meets the standard, which is in line with the significance test. Therefore, the model can better reflect the action relationship between various variables.


## 3.7. Result Analysis

It can be seen from the significance test results that the research hypotheses H1–H11 are supported. Among them, the actual perceived quality has a significant impact on the overall perceived value and final satisfaction and occupies a leading position. In terms of the impact of the three-level indicators on horizontal dimensions, F1a, F1b, F1c, and F1d have a great impact on service importance; F2a, F2b, F2c, and F2e have an impact on customer expectation of more than 0.6; in terms of perceived quality, F3a has the greatest impact on it, F3b and F3c have almost the same impact on perceived quality, while F3d has the least impact on perceived quality. According to the structural equation verification, the following research results can be obtained.Service importance directly affects customer expectation, perceived quality, and perceived value and indirectly affects final satisfaction. Among them, service importance has a positive impact on customer expectation, which is the first link to improve customer satisfaction; service importance has a weak negative correlation with perceived quality and perceived value. It can be seen that service importance has no great impact on passengers’ actual perceived quality and perceived value.Customer expectation has a negative impact on perceived quality, perceived value, and final satisfaction. The higher the expectation of passengers on bus service performance, the lower the actual perceived quality and the lower the satisfaction. Customer expectation is a key factor affecting bus passengers’ perceived quality, perceived value, and satisfaction. It is an important link to improve satisfaction.Perceived quality is positively correlated with perceived value and final satisfaction and so is perceived value and satisfaction. In other words, passengers’ satisfaction with taking the bus is influenced by perceived value and perceived quality. If you want to improve satisfaction, you can improve passengers’ perceived quality and perceived value. The better the customers’ perception is, the higher their satisfaction. To improve customer perceived value, we can start with value exploration, value structure, communication value, organization and training to deliver value, to manage customer payment to improve its perceived value, and enterprises should try their best to maintain the original customers, partners, and employees, so as to ensure that the delivery of value is more effective in economy and productivity.Finance and actual use are the outcome variables of satisfaction. Satisfaction is positively correlated with bus company finance and actual use. It can be shown that improving passenger satisfaction can not only cultivate Macao residents’ public transport travel habits but also improve the financial data of bus companies.


## 4. Conclusions and Suggestions

### 4.1. Conclusion

Based on the four satisfaction evaluation models of SCSB, ACSI, ECSI, and CCSI, combined with the specific characteristics of Macao public buses, and taking the financial indicators as the dimensional indicators affecting satisfaction for the first time, this paper constructs an “IEP-CSI” model for the satisfaction evaluation of Macao public buses. Empirical analysis shows that customer expectation, service importance, perceived quality, and perceived value have an important impact on passenger satisfaction, while finance is affected by satisfaction as an outcome variable. Customer importance directly affects customer expectation, perceived quality, and perceived value and indirectly affects the final satisfaction; the increase of customer expectation will lead to the decrease of perceived quality, perceived value, and final satisfaction; perceived quality and perceived value have a positive impact on final satisfaction. The improvement of passenger satisfaction will have a positive impact on the finance of bus companies and the number of bus uses.


### 4.2. Suggestion

Based on the above research results, this paper puts forward the following suggestions on the public service of Macao bus companies from the perspective of bus passengers:Pay attention to the quality of bus service during morning and evening commuting. As bus passengers are mainly middle-aged and young people, and the main travel time is in the morning and evening peak period, the bus company needs to take corresponding measures for this time period. For example, increase the temporarily available vehicles in this period; set up traffic control in some sections of the time period; and adjustment of other purpose vehicles shall be included in the public use during this period.Pay attention to the objective service of bus hardware. Service importance is the key factor affecting the expectation of bus passengers and the first link to improve satisfaction. Among them, the objective service of bus hardware is a very important service item for passengers. Passengers attach great importance to whether they can take the bus on time, whether they can reach the destination, and the convenience of bus travel. Therefore, how to set the route more effectively and ensuring the rationality of vehicle time and that the bus company does not fly to the station is one of the main problems considered by the bus company.Timely understand passengers’ needs and expectations for public bus services. Through the research results, it can be found that customer expectation is one of the factors affecting their satisfaction. Therefore, strengthening the communication between passengers and bus companies, understanding passenger needs in time, and improving bus service quality are important measures to improve passenger satisfaction. Macao bus companies need to know the psychological state of passengers in a variety of ways, such as setting up service stations regularly at bus stations and setting up two-dimensional code questions and answers in places such as buses, platforms, or news programs. In addition, the public service evaluation questionnaire is added to the software of APP and WeChat official account.Finally, satisfaction will have a positive effect on the finance of bus companies and the actual use of buses. Meeting the travel needs of passengers will not affect the interests of the company but will improve the financial data of bus companies and cultivate the public transport travel habits of Macao residents.


## 4.1. Conclusion

Based on the four satisfaction evaluation models of SCSB, ACSI, ECSI, and CCSI, combined with the specific characteristics of Macao public buses, and taking the financial indicators as the dimensional indicators affecting satisfaction for the first time, this paper constructs an “IEP-CSI” model for the satisfaction evaluation of Macao public buses. Empirical analysis shows that customer expectation, service importance, perceived quality, and perceived value have an important impact on passenger satisfaction, while finance is affected by satisfaction as an outcome variable. Customer importance directly affects customer expectation, perceived quality, and perceived value and indirectly affects the final satisfaction; the increase of customer expectation will lead to the decrease of perceived quality, perceived value, and final satisfaction; perceived quality and perceived value have a positive impact on final satisfaction. The improvement of passenger satisfaction will have a positive impact on the finance of bus companies and the number of bus uses.


## 4.2. Suggestion

Based on the above research results, this paper puts forward the following suggestions on the public service of Macao bus companies from the perspective of bus passengers:Pay attention to the quality of bus service during morning and evening commuting. As bus passengers are mainly middle-aged and young people, and the main travel time is in the morning and evening peak period, the bus company needs to take corresponding measures for this time period. For example, increase the temporarily available vehicles in this period; set up traffic control in some sections of the time period; and adjustment of other purpose vehicles shall be included in the public use during this period.Pay attention to the objective service of bus hardware. Service importance is the key factor affecting the expectation of bus passengers and the first link to improve satisfaction. Among them, the objective service of bus hardware is a very important service item for passengers. Passengers attach great importance to whether they can take the bus on time, whether they can reach the destination, and the convenience of bus travel. Therefore, how to set the route more effectively and ensuring the rationality of vehicle time and that the bus company does not fly to the station is one of the main problems considered by the bus company.Timely understand passengers’ needs and expectations for public bus services. Through the research results, it can be found that customer expectation is one of the factors affecting their satisfaction. Therefore, strengthening the communication between passengers and bus companies, understanding passenger needs in time, and improving bus service quality are important measures to improve passenger satisfaction. Macao bus companies need to know the psychological state of passengers in a variety of ways, such as setting up service stations regularly at bus stations and setting up two-dimensional code questions and answers in places such as buses, platforms, or news programs. In addition, the public service evaluation questionnaire is added to the software of APP and WeChat official account.Finally, satisfaction will have a positive effect on the finance of bus companies and the actual use of buses. Meeting the travel needs of passengers will not affect the interests of the company but will improve the financial data of bus companies and cultivate the public transport travel habits of Macao residents.



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*Source: 2144944-2022-09-01.xml*