CONSTRUCTION AND ANALYSIS OF SERVICE QUALITY

MODEL FOR BEIJING URBAN MASS TRANSIT

Wang Li

School of Economics & Management, Beijing Jiaotong University, No.3 Shang Yuan Cun, Beijing, China

Keywords: Structural Equation Model (SEM), Service quality, Mass transit.

Abstract: Mass transit systems have many advantages over private transit systems and the Beijing Municipal

Commission of Transport aims to increase the mass transit as the commute mode to 45% to 2015. Public

transit industry of Beijing is accordingly facing more and more strict challenge. Data show that the good

service quality will influence positively on the attitude, emotion and behavior of customers, thus keeping

high-level service quality can bring both economical and social effects for organization. There were a few

attempts on constructing service quality model for Beijing urban mass transit but the paper argues to adopt a

SEM in the construction.

1 INTRODUCTION

Mass transit or public transport refers to municipal

or regional public shared transportation, such as

buses, streetcars, and ferries, open to all on a

nonreserved basis. Mass transit systems have many

advantages over private transit systems such as

offering considerable savings in labor, materials, and

energy. When utilized to any reasonable fraction of

their capacity, mass transit vehicles carry a far

higher passenger load per unit of weight and volume

than do private vehicles. Take Beijing as an

example, mass transit will save nearly 90% road

length, 80% fuel and reduce about 86%, 95% and

90% amount of exhaust emission of carbon

monoxide (CO), hydrocarbon (HC) and nitric oxide

(NO) respectively.

Accompanied with the sustained and rapid

economic growth, Beijing as the representative

metropolitan in China has to bear the great pressure

of traffic congestion. In order to mitigate urban

traffic congestion, Beijing has applied many policies

such as develop public traffic, construct rail transit,

implement bus priority and so on. These policies do

have effects and according to the Beijing Municipal

Commission of Transport, the latest statistics shows

that mass transit accounts for 39.3% in the early half

year of 2010 comparing 29.8% in 2005. But at the

same time, with the urban motorization intensifying,

private car ownership keep increasing, more and

more commuters change their commute mode to

private cars, The percentages of car are from 29.8%

to 34.2% correspondingly. The Beijing Municipal

Commission of Transport aims to increase the mass

transit as the commute mode to 45% to 2015. Public

transit industry of Beijing is accordingly facing more

and more strict challenge.

In the last two decades, practitioners and

academics in the field of service marketing have

noted that the good service quality will influence

positively on the attitude, emotion and behavior of

customers, thus keeping high-level service quality

can bring both economical and social effects for

organization. The importance of service quality has

dramatically accelerated. Given the need to maintain

high quality, researchers have devoted increasing

efforts on how to measure quality but it also

continues to be a challenging research theme. Mass

transit is considered to be an essential public service.

It is essential to construct a service quality model for

Beijing urban mass transit.

2 SERVICE QUALITY

MEASUREMENT

In the literature there are many techniques for

measuring service quality and they can be identified

in two different categories.

541

Li W..

CONSTRUCTION AND ANALYSIS OF SERVICE QUALITY MODEL FOR BEIJING URBAN MASS TRANSIT.

DOI: 10.5220/0003608005410543

In Proceedings of the 13th International Conference on Enterprise Information Systems (IAST-2011), pages 541-543

ISBN: 978-989-8425-55-3

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

The first one includes methods of statistical

analysis such as gap analysis, factor analysis, cluster

analysis, and conjoint analysis. SERVQUAL or

RATER and CSI are the most famous two among

them. The second category of techniques consists in

estimation of the coefficients by modeling. There are

linear models, like multiple regression models, and

non-linear models, like the structural equation model

(SEM).

SERVQUAL or RATER is a multi-item scale of

service quality. SERVQUAL was developed in the

mid 1980s by Zeithaml, Parasuraman & Berry. It

represents service quality as the discrepancy or gap

between a customer's expectations for a service

offering and the customer's perceptions of the

service received, requiring respondents to answer

questions about both their expectations and their

perceptions. The use of perceived as opposed to

actual service received makes the SERVQUAL

measure an attitude measure that is related to, but

not the same as, satisfaction. Q=P-E (Q stands for

perceived service quality, P refers to performance

perception and E stands for performance

expectation). SERVQUAL was originally measured

on 10 aspects of service quality: reliability,

responsiveness, competence, access, courtesy,

communication, credibility, security, understanding

the customer and tangibles. Parasuraman et. al.

presented some revisions to the original

SERVQUAL measure to remedy problems with high

means and standard deviations found on some

questions and to obtain a direct measure of the

importance of each construct to the customer in

1991. This is the RATER: Reliability, Assurance,

Tangibles, Empathy, and Responsiveness.

The Customer Satisfaction Index (CSI) is a

weight average index, it based on the enterprise

customer satisfaction index utilize the econometrics

model to compute the trade customer satisfaction

index, compute the industry customer satisfaction

index by the trade customer satisfaction index, and

then compute the country customer satisfaction

index by the industry customer satisfaction index.

Taking American Customer Satisfaction Index

(ACSI) as a example, it is a scientific standard of

customer satisfaction. Academic research has shown

that the national ACSI score is a strong predictor of

Gross Domestic Product (GDP) growth, and an even

stronger predictor of Personal Consumption

Expenditure (PCE) growth. On the microeconomic

level, academic studies have shown that ACSI data

is related to a firm's financial performance in terms

of return on investment (ROI), sales, long-term firm

value (Tobin's q), cash flow, cash flow volatility,

human capital performance, portfolio returns, debt

financing, risk, and consumer spending. Increasing

ACSI scores has been shown to predict loyalty,

word-of-mouth recommendations, and purchase

behavior. The ACSI measures customer satisfaction

annually for more than 200 companies in 43

industries and 10 economic sectors. In addition to

quarterly reports, the ACSI methodology can be

applied to private sector companies and government

agencies in order to improve loyalty and purchase

intent.

In the second category, the models relate global

service quality (dependent variable) to some

attributes (independent variables). There is no

unique approach to measuring service quality, but, it

is accepted that the quality of service is usually a

function of several particular quality attributes and

determining of each factor weight is the important

moment of measuring quality. For these reasons, it is

important to identify service quality attributes and to

establish their importance and influence on customer

behavior.

3 APPLICATIONS OF

THE SERVICE QUALITY

MEASUREMENT IN THE

MASS TRANSIT

There are some applications of the service quality

measurement in the public service field. As far as

the mass transit is concerned, measurement of the

service quality is rather a new thing. The copyright

form is located on the authors’ reserved area.

1976, Allen & DiCesare discussed transit service

evaluation and its application to medium-sized bus

transit systems. They concluded that transit service

can be quantified and evaluated but that considerable

effort is necessary to achieve a comprehensive and

equitable system. This is the earlier try to measure

the service quality of mass transit. Silcock (1981)

dealt with the problem of measuring the

effectiveness of the running of a bus service along a

particular route to a predetermined schedule and set

of fares. Pullen (1993) concentrated on the definition

and measurement components of quality

management processes for local public transport

services. After reviewing existing methods based on

passengers' waiting times, lost mileage, expanded

ICEIS 2011 - 13th International Conference on Enterprise Information Systems

542

sets of measures and indices, he concluded that a

single measure is unlikely to encompass all aspects

of quality of service. He defined a limited set of

quality of service attributes and argued that both

relevant performance measures and psychometric

measures can be selected as indicators of the defined

set of quality of service attributes.

In the 1950’s, The United States planed to begin

the National Household Travel Survey (NHTS) and

it became into the National Household

Transportation Survey (NHTS) later. It was funded

by Federal Highway Administration and Bureau of

Transportation Statistics and provides information to

assist transportation planners and policy makers who

need comprehensive data on travel and

transportation patterns in the United States. Until

2009, the data reports included 2009 NHTS, 2001

NHTS and prior Nationwide Personal Transportation

Surveys (NPTS) conducted in 1969, 1977, 1983,

1990, and 1995. The 1995 survey included new

questions to measure the public’s perceptions of, or

satisfaction with, the nation’s transportation system

including their reactions to statements about

mobility and congestion, perceived difficulties in

travel and so on. This is the first time to conduct the

service quality of the mass transit and it applied the

CSI technique.

Reeti Agarwal (2008) used the survey method to

find the factors related to Indian Railway services

that have an impact on customer satisfaction. The

major findings of the study depicted that out of the

various factors considered, employee behavior has

the maximum effect on satisfaction level of

customers with Indian Railways as a whole.

In China, Shanghai develops the first CSI for taxi

in the 1990’s and Beijing conducted public’s

satisfaction with the urban transportation system in

2005. Guangzhou and Xi’an also explored these

techniques. Wang Zeyuan et.al (2010) used grey

relational assessment model to assess the urban

public transport service quality.

4 CONCLUSIONS

As far as the author’s know, there is little literature

on measuring customer satisfaction and service

quality in public transport using modeling. The

earlier ones can be found were conducted by

Hensher, David A et.al and Fazlina Waris et.al

applied logistic regression analysis to measure the

customers’ perception towards electric commuter

train services in Malaysia.

But the traditional SERVQUAL and CSI

techniques have shortcomings while applied in the

mass transit field and it is necessary to construct

service quality model for mass transit. This is just

the literature review of the study, the author will

continue to use Structural Equation Model (SEM) to

construct and analyze the service quality of Beijing

urban mass transit.

REFERENCES

Agarwal R, 2008, Public Transportation and Customer

Satisfaction: The Case of Indian Railways, Global

Business Review, 9:2 (2008): 257–272

Allen, W. G. and F. DiCesare. 1976, Transit Service

Evaluation: Preliminary Identification Variables

Characterizing Level of Service. Transportation

Research Record, 606: 47–53.

Fazlina Waris, Jusoh Yacob, Wan Zakiyatussariroh Wan

Husin,Wan Fauzi Wan Mamat, 2010, Customers’

Perception towards Electric Commuter Train Services:

Application of Logistic Regression Analysis,

Proceedings of the Regional Conference on Statistical

Sciences 2010 (RCSS’10) June, 274-282

Gabriella Mazzulla, Laura Eboli, 2006, A Service Quality

experimental measure for public transport, European

Transport 34 (2006): 42-53

Laura Eboli & Gabriella Mazzulla, 2008, A Stated

Preference Experiment for Measuring Service Quality

in Public Transport, Transportation Planning and

Technology, October Vol. 31, No. 5, pp. 509-523

Li Lin-bo; Wu Bing. 2004, Effects of traveler psychology

factors on development of public traffic. Journal of

Chongqing Jiaotong University. 2004.6

Ouyang Chenhai, Wu Haiyan, Zhang Yu, 2007 , Customer

Satisfaction Index Model of Transit Commuterin

Beijing, Road Traffic & Safety, 7(5),

Silcock, D. T. 1981. Measures of Operational Performance

for Urban Bus Services. Traffic Engineering and

Control, 22(12): 645–48.

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CONSTRUCTION AND ANALYSIS OF SERVICE QUALITY MODEL FOR BEIJING URBAN MASS TRANSIT

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