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Refinement of the Customer Satisfaction Index for Mobile Phone Service in

China

Thomas S.C. Sun1, Xia Han

2

1

College of Professional and Continuing Education, The Hong Kong Polytechnic University, Kowloon,Hong Kong (sptsun@speed-polyu.edu.hk)

2Ministry of Industry and Information Technology of the Peoples Republic of China, China

ABSTRACT

This study proposed and tested a refined customer satisfaction index (CSI) for the mobile phone service industry in

China. Data were collected from 1,440 randomly selected mobile phone subscribers through telephone interviewers

using customer lists of the two primary mobile phone service companies. Results showed the validity of adding the

perceived equity construct to the CSI model. Corporate image was found to have a direct positive impact on customer

loyalty; and customer satisfaction was influenced by corporate image, perceived value, and perceived equity. This study

contributed to the continued refinement of CSI and derived practical implications for mobile phone service providers.Keywords: customer satisfaction index, equity, mobile phone, China

1. INTRODUCTION

The numerous studies on customer satisfaction can be

categorized into two groups, those investigating the

determinants of satisfaction and those examining the

consequences of satisfaction. Determinants ofsatisfaction include customers expectation of products

or services (Bosque & Martin, 2008; Ofir & Simonson,

2007; Oliver, 1993; Zeithaml, Berry, & Parasuraman,

1993), the performance of products or services

(Hamilton & Thompson, 2007; He & Song, 2009; Musa,

Pallister, & Robson, 2005), brand or company image

(Martenson, 2007; Silva & Alwi, 2008), and customersperceived equity (Hellier, Geursen, Carr, & Richard,

2003; Hutchinson, Lai, & Wang, 2009). Consequences

of satisfaction include complaint behavior (Lam & Tang,

2003; Tsiros & Mittal, 2000; Zeithaml, Berry, &

Parasuraman, 1996) and customer loyalty (Fuller &Matzler, 2008; Gallarza & Saura, 2006; Kim, 2008;

Loureiro & Gonzalez, 2008).

Various countries have developed their customersatisfaction index based on multiple major industries,

starting from Sweden in 1989, followed by Germany in

1992, USA in 1994, New Zealand in 1995, South Korea

in 1998, Norway and the European Union in 1999, andothers. Figures 1-3 show the constructs included in the

Swedish Customer Satisfaction Barometer, American

Customer Satisfaction Index, and European Customer

Satisfaction Index. Although the structure of the models

varies, they all include determinants and consequences

of customer satisfaction.

The purpose of this study was to refine a customersatisfaction index for the mobile phone service industry

in China. In 2009, the telecommunication services

reached 2,568 billion RMB and mobile phone users

reached 747 million (Ministry of Industry and

Information Technology, 2009). The number of mobilephone service subscribers is growing at a faster rate than

that of fixed line phone subscribers, and the number of

mobile phone users has surpassed that of fixed line

phone users.

Source: Fornell (1992)

Figure 1. Swedish Customer Satisfaction Barometer

Source: Fornell, Johnson, Anderson, Cha, and Bryant (1996)

Figure 2. American Customer Satisfaction Index

The importance of the telecommunication industry in

China can be evidenced in its rapid growth. Between

1998 and 2005, the industry had an average annual

growth rate of 18%, twice the growth rate of thecountrys GDP. In 2005, the telecommunication industry

Perceived

Quality

CustomerExpecta-

tions

CustomerSatisfac-

tion

Customer

Complaints

Perceived

Value

PerceivedPerformance

Customer

Expectation

Customer

Loyalty

Customer

Satisfaction

CustomerComplaints

Customer

Loyalty

978-1-4244-6487-6/10/$26.00 2010 IEEE

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contributed to 2.72% of the GDP (Guangxi News

Network, 2009). However, in the past three years, thegrowth of the telecommunication industry has slowed

down, having an annual growth rate lower than the GDP

growth and the gap between the two growth rates are

widening. In 2007, the telecommunication industry

growth rate was 11.2% and the GDP growth rate was11.9%. However, the rates were 7.0% and 9.0% in 2008,

and 4% and 8.5% in 2009, respectively (China News

Network, 2009).

Source: Grigoroudis and Siskos (2004)

Figure 3. European Customer Satisfaction Index

Due to the rapid development of communication

technology, increased standard of living, and the

Central Governments policy that introduced more

competition in the telecommunication service industry,

customers expectations of mobile phone serviceproviders have increased. The slower growth rate also

signifies more intense competition between serviceproviders. Thus, an understanding of users expectation,

perception of service quality, and satisfaction will

facilitate service providers strategy formation to

enhance their competitiveness.

The development of a Telecommunication Customer

Satisfaction Index (TCSI) in China was commissioned

by the Ministry of Industry and InformationTechnology in 2001 with six constructs (Figure 4),

perceived quality, expected quality, perceived value,

customer satisfaction, customer complaints, andcustomer loyalty (Tang & Cao, 2003); and

subsequently revised in 2002 with the addition of the

corporate image construct (Mao, 2009). Regardless of

the evidence from numerous studies that perceived

equity is positively related to customer satisfaction

(Hellier et al., 2003; Hutchinson et al., 2009),

perceived value (Hutchinson et al., 2009; Musa et al.,

2005), and perceived quality (Berry, Parasuraman, &

Zeithaml, 1994; Hutchinson et al., 2009), the constructis absent from the TCSI. This study adopted the

definition from Hellier et al. (2003) that perceived

equity is customers overall perception of being treated

honestly, fairly, and justly during the purchase and useof services as well as the complaint and service

recovery processes. The theoretical framework of the

study is presented in Figure 4.

2. METHODOLOGY

A questionnaire was developed to collect data on the

constructs included in the model. The ACSI

measurement was used as the base for questionnaire

development. The measurement items for the

constructs were adopted from previous studies:

perceived equity (Hellier et al., 2003), perceivedquality, expected quality, perceived value, customer

satisfaction (Fornell at al., 1996), corporate image

(Andreassen & Lindestad, 1998), customer complaint

(Anderson & Fornell, 2000; Fornell & Wernerfelt,1988), and customer loyalty (Grigoroudis & Siskos,

2004; Geroptt, Rams, & Schindler, 2001). Several

adjustments were made based on unique characteristicsof the telecommunication industry in China.

All measurement items, except customer complaint and

price tolerance under the customer loyalty construct,

used a 10-point scale. Customer complaint was

measured with three items using either a yes or no

answer. Price tolerance level was measured as a

percentage in price increase.

Telephone interviews were used as the data collection

method due to the advantages of speed of feedback,

low cost, and wide coverage. A tiered random sampling

method was used to draw a representative sample frommobile phone users in China. User lists of the two

Customer

Expectations

Perceived Quality of

Service/Software

Perceived

Value

Perceived Quality of

Product/Hardware

Customer

Satisfaction

Customer

LoyaltyImage

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major mobile phone service providers in China, China

Mobile and China Unicom, were used as samplingframes. Of the 31 provinces, prefectures, and

municipalities covered by each of the companies, 12

were randomly selected for each company. From each

of the provinces and prefectures selected, two cities

were randomly drawn. The target sample size fromeach city was 30 (thus 60 per province and prefecture)

and from each municipality was 60.

Figure 4. Theoretical framework based on Telecommunication Customer Satisfaction Index

CATI system was used for the telephone interviews,

with 30 stations. Interviewers were professional callcenter employees. A training session was provided to

those employees specifically for this project. Mock

interviews were conducted prior to the actual datacollection. The interviews were completed in atwo-week period on weekday evenings and weekend

day time. Mobile phone subscribers registered fixed

line numbers were dialed due to the potential concern of

costs to participants (some subscribers are charged byusage). A total of 6,842 telephone numbers were used,

with a success rate of 21% (1,440/6,842). Of the

unsuccessful numbers, 7% refused to participate, 45%

did not answer the phone, 19% cannot be reached (e.g.,

wrong number), and others included unqualified

respondents, bad connection, and language barriers.

3. RESULTS

With data in 10-point scale, percentage, and 0-1, data

were standardized first before further analysis. SPSS

and AMOS were used as the analysis software. Before

testing the proposed model fit, constructs were

examined to establish their reliability and validity.

Cronbachs alpha was calculated for each construct to

assess internal consistency. Construct reliability values

of .7 or higher indicate good reliability, and between .6

and .7 are acceptable (Hair, Black, Babin, Anderson, &Tatham, 2006). Results showed that other than customer

complaints (=0.35), all constructs showed good oracceptable reliability: perceived equity (=0.80),

perceived quality (=0.62), expected quality (=0.78),

corporate image (=0.76), perceived value (=0.78),customer satisfaction (=0.81), and loyalty (=0.74).

According to Campbell and Fiske (1959), there are twomain components of construct validity: convergent anddiscriminant validity. Convergent validity can be

assessed in several ways. The minimum is for each

indicators estimated pattern coefficient on its posited

underlying factor to be significant (Anderson & Gerbing,1988). Hair et al. (2006) suggested that standardized

factor loading should be at least .5 and ideally .7 or

higher. Factor analyses using the principal component

method and varimax rotation were applied to each

construct. Of all the constructs included in the study,

standardized factor loadings were all above .7, except

one item under customer complaint having a loading of

0.66. Another indicator of convergent validity isconstruct reliability (Hair et al., 2006). The above

reported construct reliabilities indicated good or

acceptable values. Therefore, the convergent validity

was established.

Validity of latent factors can be examined by checking

their correlation matrix. Normally, low correlations

among latent constructs are preferred to provideevidence of discriminant validity. Johnson, Gustaffasson,

Andreassen, Lervik, and Cha (2001) also suggested

exploring whether each construct shares more variance

with its indicators than it does with other constructs in

the model. This is examined by looking at thepercentage of measurement variable loadings that

exceed the construct correlations. For this study, the

Perceived

Quality

Expected

Quality

Perceived

Value

Corporate

Image

Customer

Loyalty

Customer

Satisfaction

Customer

Complaint

Telecommunication CustomerSatisfaction Index

Source: Mao (2009)

PerceivedEquity

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percentage was 26%, which shows acceptable

discriminant validity.

The overall measurement model including all latent

constructs was tested using a confirmatory factor

analysis. The results of the test are presented in Table 1.

All fit indices (RMR=0.124, GFI=0.927, AGFI=0.907,CFI=0.930, RMSEA=0.056) showed a well-fitting

model, which could be used as a baseline to test the

theoretical relations among constructs.

Table 1. Overall measurement model (n=1,440)

Construct Item Std. Factor

Loading

S.E. C.R.

Perceived

Equity

Being treated honestly 0.707 0.039 25.248

Being treated justly (compared to what should one receives) 0.834 0.040 29.390

Being treated fairly (compared to other customers) 0.735

PerceivedQuality

Overall quality 0.558 0.040 18.315

Reliability 0.546 0.054 17.976

Meeting personal needs 0.638

ExpectedQuality

Overall quality 0.584 0.039 19.625

Reliability 0.687 0.045 22.587

Meeting personal needs 0.660

Corporate

Image

Overall perception of image 0.744 0.026 29.700

Contribution to society 0.620 0.035 23.903Overall liking 0.806

PerceivedValue

Appropriateness of pricing 0.771 0.032 28.594

Quality based on price paid 0.655 0.029 24.151

Price based on quality received 0.802

Customer

Satisfaction

Overall satisfaction 0.828

Gap between needed and actual service 0.725 0.033 29.973

Gap between desired and actual service 0.742 0.033 30.867

CustomerComplaint

Formal complaint 0.325

Negative word-of-mouth 0.821 0.051 6.532

Switching intention 0.274 0.101 6.923

CustomerLoyalty

Repeat purchase intention 0.640 0.066 20.521

Trust in company 0.790 0.046 24.052

Forgiving service failure 0.640

*all p

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*p

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