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SMM 210

Assessing Quality and Customer Satisfaction with service delivery of mobile telecommunication networks in the UK.

Dissertation

Student Number: 0847416

MBA International Business

ABSTRACTDeadline: Monday 16th August 2010

Market Research on Service Quality and Customer Satisfaction 2010

Purpose - There are a lot of service quality dimensions derived from the Service

Quality models and frameworks. The aim of this dissertation is to find out the

significance of these dimensions as perceived by the customers and compare it with

the level of service offered by the UK’s Mobile Service Providers.

Review/Methodology – A review was conducted on the relevant models and the gaps

were found using the Qualitative (Focus Group Interview) and Quantitative research

(Questionnaire) methods.

Findings – Five attributes of service quality are found to be deemed with high

importance by the customers and lacks attention from the Mobile Service Providers.

Limitations/Implications – As this research has been conducted using limited time

and resources, the Mobile Networks could conduct research specific to their market

potential and offered service level.

Keywords – Service Quality, customer satisfaction, mobile telecommunication

networks, customer expectations and SERVQUAL

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Table of contents

1. INTRODUCTION.............................................................................................5

1.1. Background of the study……………………………………………....5

1.2. Overview of Telecommunications Market……………………...…....6

1.3. The current state of telecommunication industry in the UK……….6

1.4. Problem Identification & Purpose of the Study……………………..8

1.5. Research Questions……………………………………………………9

1.6. Research Objectives…………………………………………………...9

1.7. Significance and Limitations of this dissertation……………………10

2. LITERATURE

REVIEW.................................................................................11

2.1. Purpose of Literature review………………………………………….11

2.2. Customer Psychology………………………………………………….11

2.3. Role of Customer Satisfaction………………………………………...12

2.4. Measuring Customer Satisfaction…………………………………….13

2.5. Customer Satisfaction Indices (CSI)……………………………………..13

2.6. Disconfirmation Models………………………………………………..15

2.7. Service Quality………………………………………………………….16

2.8. Relationship between Service Quality and Customer Satisfaction…18

2.9. Service Quality Dimensions……………………………………………19

2.10. Service Quality Models…………………………………………………19

2.11. SERVQUAL…………………………………………………………….20

2.12. Gronroos’ Model of SERVQUAL……………………………………..23

2.13. Addressing the Research Questions…………………………………...24

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3. RESEARCH METHODOLOGY.................................................................26

3.1. Research Purpose ……………………………………………………...26

3.2. Research Philosophy…………………………………………………...26

3.3. Research Approach……………………………………………………27

3.4. Research Method ………………………………………………………27

3.5. Operationalisation of Concepts………………………………………….30

3.5.1. Minnesota Customer Satisfaction Index (MnCSI)…………..30

3.5.2. Defining Hypothesis…………………………………………....32

3.5.3. Disconfirmation Models……………………………………….33

3.5.4. Over-all Satisfaction…………………………………………...33

3.5.5. Procedures to test Hypotheses………………………………..34

3.6. Sample Selection and Data Collection………………………………..37

3.7. Reliability………………………………………………………………38

3.8. Validity…………………………………………………………………39

4. DATA ANALYSIS AND DISCUSSION………………………………….41

4.1. Introduction……………………………………………………………41

4.2. Demographic profile…………………………………………………..41

4.3. Assessing Customer Satisfaction with the Service Quality…………41

4.3.1. Results of Minnesota Customer Satisfaction Index…………42

4.3.2. Results of Disconfirmation Models and Over-all

Customer Satisfaction Measure……………………………...43

4.3.2.1. Irrespective of cellular network……………………...43

4.3.2.2. With respect to cellular networks…………………....47

4.4. Customer satisfaction with each service quality dimension………..57

5. SUMMARY AND CONCLUSION.............................................................65

6. BIBLIOGRAPHY........................................................................................69

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1. INTRODUCTION

1.1 Background to the study:

During the last few years, the Telecom industry has experienced an enormous

growth across the world and there has been a rapid growth in the wireless technology

(Bharat Book Bureau, 2008). According to an industry market study, by 2013 the

telecommunications industry is anticipated to attain revenue of $2.7 trillion with an

average growth rate of 10.3 percent an year (Bharat Book Bureau, 2008). In the

present dynamic and interactive market place, the organisations are proposing various

strategic methods to achieve effective Customer Satisfaction (CS) strategy decisions

and eventually increase the CS success rates to sustain long term relationship with the

profitable customers (Chien and Su, 2003; Gronroos, 1994). “Loyal customers are

reported to have higher customer retention rates, commit a higher share of their

category spending to the firm, and are more likely to recommend others to become

customers of the firm.” (Keiningham et al., 2007, p. 362). Hence the organisations are

becoming more customer centric, giving more importance to retaining old customer as

the business would end up spending an approximate of five times more in attracting

new customers than retaining the existing customers in terms of time, money and

resources (Reichheld, 1996; Pizam and Ellis, 1999).

As the growth of the organisation and its survival in the market is driven by

customer loyalty and customer retention, each of these companies is continually

improving on their service quality standards to survive in this highly competitive

market (Keiningham et al., 2007). Hence, in order to maintain these service quality

standards, organisations frequently adopt new measures to check if the customers are

satisfied with the service quality provided. For e.g. by conducting customer surveys

and analysing the acquired data statistically, which would help them make the right

decision to increase customer satisfaction and eventually customer loyalty among

their customers (SPSS White Paper, 1996). Organisations adopt both quantitative and

qualitative methodologies to evaluate CS and the data obtained from these measures

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provide constructive feedback to help the organisation know the satisfactory level of

its customers with its products, which would help the organisation to: i) take reliable

steps to improve the quality of service, ii) adding more value to its customers and iii)

achieving high customer satisfaction rates (Amaratunga et al., 2002).

1.2 Overview of the UK Telecommunications Market:

Telecommunications is one of the best growing sectors of the UK economy.

The competition developed strongly in 1984 after the privatisation of British Telecom

(BT) and as of 2004, the UK had an approximate of 170 fixed telecommunications

provider and 59 mobile service providers (CWU research, 2004). The market for fixed

telephone network has been declining since the evolution of mobile / cellular phone

networks and in 2003 due to flat call volumes and pricing competition, it fell by

£400m (CWU research, 2004). Eventually, the consumers preferred the cellular phone

networks as the mode of communication which was faster and easier than the fixed

telephones (CWU research, 2004).

According to the UK Mobile Operator Subscriber Data, Statistics and Market

Share 2006 - 2008, there are five primary cellular network operators in the UK:

Vodafone, Telefonica O2, T-Mobile, Orange and 3 UK and it was reported to have

73.1 million cellular service subscribers in the last quarter of 2007, which represents

almost 9% of the total European mobile subscriber market and another statistical

report from IE market research Corp reveals that the wireless market is anticipated to

achieve 126% by 2010 and gradually the total subscribers would also reach 78 million

by 2010 (Telecoms Market Research, 2008).

1.3 The current state of telecommunication industry in the UK:

Today, the telecommunication industry has undergone a rapid transformation

creating a lot of new challenges for infrastructure and service providers. The rapid

advances in technology and increased market turbulences have added a lot of value to

the telecom industry (Lia and Whalley, 2002).

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Recently T-Mobile and Orange merged becoming a giant in the telecom

industry having 28.4 million customers and now they are the largest cellular service

provider in the UK with an approximate of 37% of the entire mobile market (BBC

News, 2009; The Register, 2010).

The 3G network is up to 40 times faster in data than the 2g or the GSM

networks. This high connection speed adds on more features such as sending Pictures,

MMS (Multimedia Messaging Service) or video clips and also promotes high quality

sound (Robins, 2003).

However this rapid growing mobile market is expected to face capacity-crunch

i.e. due to the increasing existence of several MVNOs (Mobile Virtual Network

Operators), the mobile data traffic has gradually increased 200% in 2009 and

according to the reports of Ofcom, few service providers such as O2 are about to hit

that capacity (Xln Business Community, 2010). Hence, this capacity-crunch may

bring down the quality of service delivery necessitating the network operators to take

precautions in order to maintain their service delivery standards.

The market share of mobile telecom industry in the UK as of September 2009:

Fig 1.3a Market Share of Mobile telecom industry in the UK

(Source: Guardian News, 2009)

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The Fig 1.3a indicates that, as of September 2009, T-Mobile / Orange had

37% of market share being the highest, followed by O2 with 28%, Vodafone with

23% and 3-mobile with the least at 5.8%.

The total number of subscribers for the UK’s mobile telecom industry as on

September 2009:

Fig 1.3b Number of subscribers for the UK’s mobile telecom industry

(Source: Guardian News, 2009)

The Fig 1.3b indicates that, as of September 2009, T-Mobile / Orange had

28.4 million customers being the highest followed by O2 having 21.5 million

customer, Vodafone with 17.7 million customers and 3-mobile having the least at 4.5

million customers.

1.4 Problem Identification & Purpose of the Study:

Though majority of the customers for UK mobile telecommunication networks

use all of their mobile services like text, data and mobile internet services, they are

dissatisfied with the service-availability and it’s quality; especially the network

coverage is a crucial concern to all of its consumers. (Telecom paper, 2009) Due to

the existence of several MVNOs, customers switch to different service providers

frequently and they are also concerned about the self-regulatory schemes by their

network providers (Telecom paper, 2009).

Customers are known to have reported that there is no network clarity and

coverage. They are not being told if they would have network coverage in their area

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before they could sign a contract with the company and they are unhappy with the

after sales service that is being provided to them (Poulter, 2009). “A study on 5,000

people revealed the telecom giants are nearly twice as bad at dealing with issues and

complaints compared with their successors British Gas.” (Xln Business Community,

2009). The customers don’t get reliability and assurance in the services they are being

offered, as they have to go through a sequence of inconsistencies such as waiting in

long queues to speak to representative, incompetent employees who do not understand

the correct issue that is being faced and bear with their rude behaviour at times (Xln

Business Community, 2009). These situations create a bad impression in the

customer’s mind and lead them to change the service provider. Also, this word of

mouth communication can spoil the image or reputation of the company.

Hence the main research aim of this study would be: To measure and critically

analyse the level of customer satisfaction with regards to service delivery among

different mobile service providers (Mobile Telecommunication Networks) within the

UK.

1.5 Research Questions:

How the customers’ satisfaction with the service quality is described in the UK’s

MTNs with and without respect to the customer’s service providers?

Which attributes of service quality do the customers perceive to be of more

importance that lacks attention from the service providers in the UK?

1.6 Research Objectives:

To find out the level of customers’ satisfaction with the service quality offered to

them by the UK’s MTNs with and without respect to which network customers

subscribe to.

To find out which dimensions of service quality are the customers

satisfied/dissatisfied with in the UK’s MTNs.

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To identify the Service Quality dimensions that the customers perceive to be of high

importance in the UK’s MTNs.

1.7 Significance and Limitations of this dissertation:

This study is significant in various ways to business consultants and business

partners. The results and findings of this study would be helpful to the management of

UK’s cellular service providers, as it provides a reliable scientific measure to evaluate

customer satisfaction level with the services delivered by them. It will reveal the

dimensions of service quality which are considered more important from the

customer’s perspective, which would provide them with a priceless empirical support

to make right strategic decisions in the required areas of operations and over-all it

would act as reliable guide to improve their service delivery standards and create

customer-value. This dissertation would provide enormous valuable information to

business partners such as share-holders and investors which would help them provide

useful suggestions to their respective mobile service providers to improve their

service delivery standards. The dissertation enables the customers to analyze the

ratings of the various dimensions with respect to the service providers so that bringing

in awareness among customers.

The limitations of this dissertation are that, the research would not have access to

every locality in the UK and as the research is mostly done in the city of London. But

London, being a cosmopolitan city, gives us a gist of UK and a right place to conduct

the research. It doesn’t allow us to conduct the analysis on large samples, which is a

prerequisite to have more reliability on surveys (Saunders et al., 2007). But, as the

MTNs are a public service and have millions of users, the samples are obtained from a

much diversified respondents to obtain the best possible results.

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2. LITERATURE REVIEW

2.1 Purpose of Literature review:

The literature review aims at critically exploring the existing knowledge and

theories that are relevant to the research objectives, so that we can develop and refine

the key areas of our research (Saunders et al, 2007). To generate and refine the

research ideas the ‘Relevance Tree’ technique is used in this review of literature i.e. a

broad concept is studied from the view of various authors via which a new sub-

concept is developed and as we proceed deep into the subject new ideas are

formulated (Saunders et al, 2007). The customer satisfaction is measured through the

service quality dimensions defined for that particular product or service. These

dimensions are based on different models created by academics which I critically

analyse in the literature and adopt those that best suit the aim of this dissertation.

2.2 Customer Psychology:

A ‘Customer’ is usually the final user of any product where the purpose of it

being made gets fulfilled (Hayes, 1997). Understanding the psychology of customers

plays a very important role in determining their satisfaction over a product or service.

This includes designing a product according to the needs of the customer. The

satisfaction of a customer starts well before manufacturing the product rather than the

moment after sale. During the service encounters the customers’ values, perceptions,

beliefs and expectations motivate them to choose one service provider rather than

another (Lynch, 1992; Pizam and Ellis, 1999).

At any point of sale, there are four options available for the customer to

choose: Purchase – where the customer is convinced to buy a product or service,

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Rejection – where the customer rejects the offer, Postponement – where the customer

is partly convinced and postpones the offer to think at a later date and substitution –

where the customer compares the product with other contemporary offers. Hence

influencing the customer’s choice to purchase a product is very crucial (Lynch, 1992;

Pizam and Ellis, 1999). Therefore, it is very essential for us to know the customer

expectations and their requirements, to understand customer’s view and perspective

about the quality of services and products they need (Pizam and Ellis, 1999).

2.3 Role of Customer Satisfaction:

Customer Satisfaction (CS) is said to be the customer’s post-purchase

evaluation of services or a product. When the CS level of an organisation is high,

even the market share and profits of the organisation grow higher leading the

company to a stronger competitive position in the market place (Turkyilmaz and

Ozkan, 2007). The customer satisfaction is built on the varied experiences, positive

and negative that the customer has come across at different points of time (Satari,

2007).

The impact of customer care in service quality system would maximize profits

and help the organisations grow by providing customer satisfaction and building great

customer experiences. Customer care is therefore a key to gain the competitive

advantage among the competitors (Lynch, 1992).

“Satisfaction of customers also happens to be the cheapest means of

promotion and therefore, customer satisfaction is recognized as of great importance to

all commercial firms because of its influence on repeat purchases and word-of mouth

recommendations.” (Pizam and Ellis, 1999, p. 326). Hence, it becomes important for

the organisation to offer customers a good experience that exceeds their expectation

and if the customers have bad experiences, then the reputation of the company

reduces rapidly due to word-of-mouth communication.

Satisfaction of customers over a telecommunication product can be two

dimensional: i) It can be component specific – i.e. service specific, over the MMS

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services, 3G services, speed etc. and ii) It can be product specific – satisfaction on the

overall performance and responsiveness of the mobile service provider (Cronin and

Taylor, 1992). These dimensions require us to measure the satisfaction level of the

customers in different particular components as well as on the whole.

2.4 Measuring Customer Satisfaction:

In order to take managerial decisions, the CS needs to be measured in an

organisation and this Customer Satisfaction Measurement (CSM) is used to determine

the customer satisfaction level based on the valuable feedback from the customers and

identifying the customer expectations (Crosby, 1991). The service quality can be

achieved only by knowing the customer’s total needs or customer expectations and

with the help of this data, the service standards and processes may be altered to

achieve customer satisfaction (Crosby, 1991).

After in depth research on CSM, nine distinct theories were developed such

as: Expectancy disconfirmation (Parasuraman et al, 1988), Assimilation contrast,

Comparison level (Gronroos, 2001), Value precept (Zeithaml, 1988), Cognitive

dissonance, Equity, Generalised negativity, Contrast and Attribution (Kauppinen et

al., 2007). Most of these theories were based on cognitive psychology, but they were

developed with no empirical research. However, among these, only two of them were

widely accepted i.e. the expectancy disconfirmation theory and customer satisfaction

indices (Pizam and Ellis, 1999) because all the theories mentioned above use these

two models as a common base (Parasuraman et al, 1988; Gronroos, 2001; Zeithaml,

1988; Kauppinen et al., 2007). Therefore, we would review the customer satisfaction

indices and disconfirmation models which would form the crux of this study.

2.5 Customer Satisfaction Indices (CSI):

This model focuses more on customer’s overall satisfaction with a product or

the services offered to them till date and it is based on a cumulative view of

satisfaction (Turkyilmaz and Ozkan, 2007). “The CSI model is a structural model

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based on the assumptions that customer satisfaction is caused by some factors such as

perceived quality (PQ), perceived value (PV), expectations of customers, and image

of a firm.” (Turkyilmaz and Ozkan, 2007, p. 673). It is equally important to

understand the customer perceived value and their expectations to attain high degree

of customer satisfaction.

The Swedish Customer Satisfaction Barometer (SCSB) is reported to be the

first national customer satisfaction index (NCSI) which was developed in 1989, then

the model was followed by the Germans, they named it as German Customer

Barometer (Fornell, 1992).

The Americans adapted this model in 1993, it was developed by Claes Fornell,

who was the founder of SCSB and they named it as the American Customer

Satisfaction Index (ACSI). The ACSI is a cause and effect model using the responses

from the respondents to form a ‘Multi-Equation Econometric’ model. The responses

were collected according to different variables in a 0-100 scale (Turkyilmaz and

Ozkan, 2007; Fornell, 1992). The European Organisation for Quality (EOQ) and

European Foundation for Quality Management (EFQM) jointly developed the

European Customer Satisfaction Index (ECSI) in 1999. Then gradually many other

countries followed the CSI model (Turkyilmaz and Ozkan, 2007). The ECSI model

included the ‘Corporate Image’ as a component on top of the ASCI model. But, these

indices do not measure the CS levels for specific components and overall CS together

(Turkyilmaz and Ozkan, 2007).

The Workforce Centre developed the Minnesota Customer Satisfaction Index

(MnCSI). The MnCSI model is specifically used to evaluate over-all customer

satisfaction with service delivery of the MTNs on a single scale (Positively

Minnesota, 2007). This model uses the variables of disconfirmation models: both

desire disconfirmation as well as expectation disconfirmation and it combines three

questions which includes the disconfirmation models also (As discussed earlier

disconfirmation models are the second CSM tool which was widely accepted) It also

gets more stable when there are three questions instead of one. In addition, it is

comparatively flexible and best suited for any number of responses (Positively

Minnesota, 2007).

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2.6 Disconfirmation Models:

According to Parasuraman et al. (1988), customer expectations are one of the

most important factors of CS, as they play a major role of ascertaining customer

satisfaction. Even the SERVQUAL model uses the disconfirmation model as its base

and it is basically used for conceptualizing service quality (Parasuraman et al., 1988).

The disconfirmation model was tested and confirmed in a lot of studies conducted

across the world and there are two different types of disconfirmation models - Desire-

Disconfirmation model and Expectancy disconfirmation model (Pizam and Ellis,

1999; Parasuraman et al., 1988). The expectancy disconfirmation model states that

quality is assessed by comparing perceived and expected performance i.e. to examine

if the customer expectations were met during the service delivery process (Oliver and

DeSarbo, 1988; Kang and James, 2004).

According to Oliver (1980), the expectancy disconfirmation model has got

two internal attributes, which are known as positive disconfirmation and negative

disconfirmation. If the performance of the product or service exceeds the customer

expectations and when the customer is highly satisfied with the product or service

delivered, then it is called as value disconfirmation. However, if the customer’s

expectations are met and he/she is satisfied with the product or services offered, then

it is positive disconfirmation and finally if the product or service perceived is below

his/her expectations, then it is called negative disconfirmation (Oliver, 1980). This

theory focuses more on the antecedents of satisfaction, which occurs at the initial

stages of the service-delivery process (Oliver, 1980; Oliver and DeSarbo, 1988; Kang

and James, 2004).

Recently Khalifa and Liu (2002) built a theory that embedded both desire as

well as expectancy disconfirmation theory. They have proved that both these factors

impact the over-all customer satisfaction, as they both are of cognitive standards and

it is hard to evaluate which one of these factors explains CS better.

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2.7 Service Quality:

Service Quality means the service that meets all the customers’ expectation

and satisfies their needs and requirements or it is defined as “a consumer’s judgment

about an entity’s overall excellence or superiority.” (Kang and James, 2004, p. 267)

This term is purely customer oriented. Hence excellence in service requires an

understanding of customer needs and expectation (Edvardsson, 1998).

As there was an enormous growth in mobile telecommunications market in the

last few years, the customers are more conscious about the quality of services being

offered to them (Kumar and Lim, 2008). According to Kumar and Lim (2008), the

service quality in MTNs can be perceived through the technical as well as the

functional attributes of mobile services in which the technical attributes include the

pricing/tariff plan, the network quality & data services and the functional attributes

include the customer service quality and the billing system. “Overall perceptions of

service quality are formed by a consumer’s evaluation of multiple quality

dimensions.” (Kumar and Lim, 2008, p. 569). Hence in order to enhance the

customer’s perceived value and their satisfaction level, it is important for the

organisations to create positive perceptions of service quality among its customers

(Kumar and Lim, 2008).

Service quality enhances the organisation’s operational efficiency as well as

improving the retention rate of its firm (Edvardsson, 1998). The customers assess the

product quality in various tangible ways such as its colour, style and feel. But in most

of the cases only few of these tangibles exist and meet the customers’ expectation

(Parasuraman et al., 1985).

According to Parasuraman et al. (1985), as the services being intangible in

nature, most of it cannot be measured and their heterogeneous nature makes them

vary from time to time and customer to customer. Hence because of these natures, it

becomes hard to evaluate the service quality of an organisation.

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Gronroos (2001) introduced the concept of Consumer Perceived Quality

(CPQ), which evaluates to what extent the service delivered, meets the customer’s

expectation. It compares the consumer’s expectations and the customer’s perception

of service received. According to this theory, over-all satisfaction of the customer

with the organisation is based on every encounter or experience he had with that

organisation. Hence they claim that service quality and customer satisfaction are

distinct conceptually but they are closely related constructs (Kang and James, 2004;

Sureshchandar et al., 2002). A recent study has proved that “the CPQ influences

profitability directly as well as indirectly through market share.” (Crosby, 1991, p. 6).

Hence it is equally important to take CPQ under consideration for this research.

According to Parasuraman et al. (1988), the long term and global evaluation of

a service is related to the service quality perceived by the customers and the customer

satisfaction can be obtained by evaluating specific service transactions and they have

also clearly pointed out that the customer experience with the provided service,

influence the perceptions of service quality. Hence, it could be said that both service

quality and CS are closely related terms.

2.8 Relationship between Service Quality and Customer Satisfaction:

The relationship between service quality and customer satisfaction has gained

a lot of attention in the last few years and they are considered to be the two core

components that frame a crux of the marketing theories (Sureshchandar et al, 2002).

In the current competitive market, the companies can sustain its competitive

advantage by providing service quality of higher standards, which would result in

satisfied customers (Sureshchandar et al, 2002).

Customers are one of the important assets of an organisation as they are the

only ones who keep the business running. As it was already discussed earlier that

retaining existing customers is more essential than generating new ones, it is

important to have service quality in every stroke to build a long term relationship with

the customers, which adds more value to the consumers as well as the company

(Nguyen et al, 2007). Based on the quality of service delivered, is the consumer’s

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commitment to renew/continue our service consistently in the future (Nguyen et al,

2007).

Figure 2.8: Five critical factors of customer perceived service quality

Source: (Sureshchandar et al., 2002)

The figure 2.8 indicates the five critical factors of customer perceived service

quality, in which the core services refer to the content of the services i.e. the different

features offered in a service. The human element of services refers to the empathy,

assurance, reliability and responsiveness i.e. includes the factors that affect the human

behaviour. Standardisation of services refers to the systematizing and simplifying the

systems, processes and the procedures. The tangibles refer to the physical facilities

available, equipments and the appearance of their workers and finally the social

responsibility refers to encouraging ethical behaviour in every aspect, which would

improve the image of the company and also promote customer loyalty and overall

customer satisfaction (Sureshchandar et al., 2002).

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2.9 Service Quality Dimensions:

According to Johnston (1995), it is crucial to identify the determinants of

service quality before we proceed with the service research. Hence this becomes a

central concern, as it is necessary to find out the determinants of service quality to

define measures and control customer perceived service quality.

In 1980s, Parasuraman et al. (1985, 1988, 1994) developed the SERVQUAL

model to determine what service quality meant to the consumers, followed by the

measures they developed strategies to meet customer’s expectations. It is considered

to be the most popular instrument, which is widely used by many researchers and

practitioners to measure service quality (Sureshchandar et al., 2002).

2.10 Service Quality Models:

Many models were developed to capture the quality of service at different

points of time to suit different business objectives (Nitin et al, 2005). The earliest ones

were that of Gronroos’, (1984) ‘Technical and Functional Quality Model’ where the

perceived quality was compared with the Expected Service with reference to the

Functional and Technical dimensions. The next popular model was Parasuraman et

al.’s (1985) GAP model. This model analysed the gaps between the customers’

expected and perceived service forming a base for the SERVQUAL model with

several dimensions like Tangibles, Reliability etc. However, the SERVQUAL model

has been subjected to a lot of criticisms and there have been many scholars who had

tried to modify or restructure this model conceptually (Kang and James, 2004). The

next model designed by Haywood (1998) called as ‘Attribute ServQual Model’

incorporated 3 attributes: ‘Physical facilities and process’, ‘People’s Behaviour’ and

‘Professional Judgement’ into the SERVQUAL components. Haywood (1998) also

said that all the three attributes needs to have a balance and if not leads to fall in

quality. The ‘Synthesized ServQual Model’ by Brogwicz et al. (1990) explained the

importance of the customer’s perception of the brand and image before even the

product launched. This model added up the ‘Company Image’ component and its

elements to the SERVQUAL model.

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Meanwhile, Cronin and Taylor (1992) developed ‘SERVPERF’, the

‘Performance Only Model’ which states that the consumers’ perceptions on the brand

actually predict the service quality and the perception index is a worthy indicator of

the Service Quality. It also criticises that the SERVQUAL model mixes satisfaction

with perception. But the perception cannot always be a proper service quality

indicator because perceptions do change with time, and the organisation that provide

unmatched service excellence always lead even when started with comparatively

lesser brand awareness and marketing system. The Mattson’s (1992) ‘Ideal Value

Model’ calculates the Service Quality in comparison with the Ideal Industry Standard

rather than the Customers’ perceptions. This model may strive to provide the best

service in line with the technological capability but the innovation may not be

focussed on the customer’s requirements. The ‘IT Alignment Model’ (Berkley and

Gupta, 1994) introduced Information Technology for improving the service quality.

Meanwhile, Dabholkar (1996) introduced the ‘Attribute and Overall Affect Model’

which examines the technology used self service options to minimize labour costs.

The PCP Attribute (Philip and Hazzlet, 1997) egg prioritized the dimensions as

Pivotal, Core and Peripheral. Oh (1999) depicted the importance of Customer Value.

Frost and Kumar (2000) proposed the ‘Internal Service Quality’ dimensions based on

the GAP model for the Internal Customers of the organisation. In the ‘Internal Service

Quality DEA model’ (Soteriou and Starvinide, 2000), the Data Envelope Analysis

maps the depreciation in service quality from the client base to branches. Santos’

(2003) ‘e-Service Quality’ is developed on the antecedents of service quality using e-

commerce.

2.11 SERVQUAL:

SERVQUAL is a multiple item scale developed to measure the Service quality

and this instrument illuminates the different dimensions of customer’s perception and

helps assessing the service quality (Parasuraman et al., 1985, 1988).

It has illuminated five dimensions via which customers perceive and assess service

quality of the organisation and each dimension has a sub-set called ‘items’ via which

20 | P a g e


the dimensions are being measured (Parasuraman et al., 1988). The five dimensions

are:

1. Tangibles: This includes the physical facilities available, equipments and the

appearance of their workers.

2. Assurance: This includes the courteous nature and the product knowledge of

the employees and also if they are confident and trust worthy.

3. Responsiveness: Providing quick service and their willingness to help the

customers.

4. Empathy: Caring for the customers with more individualised attention.

5. Reliability: Providing accurate service and performing the promised

commitments (Parasuraman et al., 1988).

The required data is collected via structured questionnaire or surveys from a

sample of customers in which many questions are formulated based on the key service

quality dimensions (Parasuraman et al., 1988, 1994). Before reviewing other models

based on SERVQUAL, it is better to look into the advantages and disadvantages of

SERVQUAL.

Advantages and Disadvantages of SERVQUAL:

SERVQUAL has overlooked at some of the important factors of service

quality such as the social responsibility of the organisation, core service and

standardisation of service delivery and there is also a general agreement towards the

22 items scale, that they are reasonably good predictors of service quality

(Sureshchandar et al., 2002). Most of the research models till date have used

SERVQUAL as its base for development (Sureshchandar et al., 2002).

The SERVQUAL model has also been severely criticized in many cases. The

contents of the service quality dimensions obtained from the SERVQUAL model has

not been accepted by everyone, as service quality is generally viewed as a multi-

dimensional construct and it focuses mainly on the service delivery aspects and there

are many additional factors also to be considered for e.g. Considering only the

functional attributes to predict customer’s behaviour may have low predictive

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validity, the semantic differences are not being withstanded in each dimension, etc.

(Kang and James, 2004; Sureshchandar et al., 2002). The criticisms also include “the

use of difference scores, dimensionality, applicability and the lack of validity of the

model, especially with respect to the dependence or independence of the five main

variables” (Kang and James, 2004, p. 267). Hence considering all these criticisms that

SERVQUAL is renowned for its widespread use by other researchers and scholars

and it also has got lot of disadvantages it is advisable to look into other models based

on SERVQUAL.

In 1992, Cronin and Taylor developed the Performance only model, which

they called it SERVPERF. It states that service quality can only be assessed by

perceptions and it is not necessary to measure expectations (Cronin and Taylor, 1992).

The author views service quality as a link between purchase intentions and customer

satisfaction and they challenged the SERVQUAL framework by Parasuraman et al.

(1985), that perceptions are the only predictors of service quality where as

SERVQUAL model confuses consumer satisfaction with attitude of the consumers

(Cronin and Taylor, 1992).

Similarly, Brogowicz et al. (1990) argued that there are many chances for the

service quality gap to occur well before the customer experiences the service, as the

customer may learn through various ways such as word-of-mouth communication and

advertisements. It integrates the traditional managerial framework to the service

quality which comprises of three factors: image, traditional marketing activities and

external influences and the model was called synthesized model of service quality

(Brogowicz et al., 1990).

Another study by Haywood-Farmer (1988) suggests that the attributes has to

be separated into three groups: professional judgement, processes & facilities and

consumer’s behaviour and each of the attributes comprises of various factors. It also

states that all the three groups must be given equal importance, in case if any one of

the attribute is given more importance than others, then it may lead to a disaster

(Haywood-Farmer, 1988).

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Similarly, Parasuraman et al. (1985) had stated that service quality cannot be

assessed only with service outcomes but even the service delivery process needs to be

evaluated, the SERVQUAL is composed of only functional dimension of service

quality and they lack technical dimension and corporate image. Both these dimensions

are inter correlated.

The attributes of functional quality refers to the American perspective of

service quality but however according to the European perspective, the service quality

needs two more attributes in addition, which are technical quality and the corporate

image (Kang and James, 2004). The Gronroos SERVQUAL model includes all the

three attributes i.e. necessary from the European perspective. Moreover, the

Gronroos’ ServQual model was used in an empirical research in the

telecommunications field, which had proved that Gronroos model is more appropriate

to represent service quality in telecommunications industry (Kang and James, 2004).

2.12 Gronroos’ Model of SERVQUAL:

It is a multi dimensional model. According to this model there are two service

quality dimensions, firstly the technical aspect (what kind of service is provided) and

the functional aspect (how is the service being provided).They introduced the

corporate image concept, as one of the other important element in the perceived

service-quality model, as the customers would bring their perceptions and past

experiences with the firm in each encounter with the organisation (Kang and James,

2004). If a positive image about the firm is created in the mind of a customer, then

they wouldn’t bother much about the minor mistakes that happens and in case there is

a negative image about the firm, then the mistakes would be magnified in their mind

(Gronroos, 1994; Kang and James, 2004).

In the mobile telecommunications industry the customers look for both – How

they are being served (functional dimension) as well as the nature of services and

service outcomes which constitute the technical dimension (Kang and James, 2004).

Hence these three dimensions (technical dimension, functional dimension and

corporate image) are considered the most important.

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2.13 Addressing the Research Questions

As discussed earlier in the ‘current state of telecommunication industry in the

UK’ and ‘Problem Identification’ in the introduction (section 1.3 and 1.4), the

network operators are likely to face capacity crunch which induces network coverage

and clarity issues. This in turn shall reduce the service quality standards to a new low.

Moreover, even the reliability, assurance and responsiveness factors are not addressed

with proper concern increasing the customer’s switching intention.

At this juncture it is important to know the service quality dimensions valued

more by the customers and to give more attention towards those in order to achieve

positive customer service experience. These problems led to the main research

objectives specified. Based on the reviewed literature the research objectives can be

obtained using the following theoretical models which has been justified in this

chapter:

i) The MnCSI model, Disconfirmation models (both desire and expectation) and

over-all satisfaction measure is used to assess and describe the level of customers’

satisfaction with the service quality offered to them by the UK’s MTNs with and

without respect to which network customers subscribe to.

ii) The expectation disconfirmation model is used in order to find which dimensions of service quality the customers are satisfied or dissatisfied with in the UK’s MTNs.

iii) The Gronroos’ Servqual model is used to identify the service quality dimensions that the customers perceive to be of high importance in the UK’s MTNs.

The research question one: ‘How the customers’ satisfaction with the service

quality is described in the UK’s MTNs with and without respect to the customer’s

service providers?’ is answered by critically analysing the results obtained from the

first research objective and the research question two: ‘Which attributes of service

quality do the customers perceive to be of more importance and lacks attention from

the service providers in the UK?’ is answered by critically analysing the results

obtained from objectives two and three.

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3. RESEARCH METHODOLOGY

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3.1 Research Purpose:

According to Saunders et al. (2007), research is a systematic or a step by step

procedure to increase the knowledge of a new or an existing subject. The purpose of

this research is to key out the main service quality dimensions/attributes as perceived

by the customers and find out how satisfied they are with these attributes and also to

explore the reasons for their the intention to change their service providers (Saunders

et al., 2007).

3.2 Research Philosophy:

Research philosophy brings up different philosophical assumptions and beliefs that

would support this research and help us selecting the appropriate research strategy and

phenomenon. It has two core traditions: ‘Positivism’ and ‘phenomenological approach’

(Saunders et al., 2007). Positivism deals with the fundamental laws perceived by us and

their scientific explanations. ‘Phenomenological’ helps in trying to understand a

particular phenomenon (Saunders et al., 2007). The three main characteristics of

positivism are:

The explanations and knowledge attained in this method are similar to that of

natural science.

The ‘hypothetico deductive methodology’ which is followed by positivism is

same as natural science.

It treats its’ subject matter (i.e. mobile telecom networks in UK, in this study) just

like how a natural scientist would treat the world (of natural forces/things)

(Saunders et al., 2007).

Hence, it implies that positivism deals with observable social reality. So, this research is

built on this approach as it involves customer perceptions and identifying relationships

through different theoretical frameworks.

3.3 Research Approach:

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According to Saunders et al., (2007), there are two broad methods of reasoning:

deductive approach and inductive approach. The deductive approach is based on the top-

down approach mode where a theory is developed and subjected to more observation

after hypothesis as shown in the fig 4.3. It works from more general to specific reasoning

(Saunders et al., 2007). Conversely, the inductive approach is based on the bottom-up

approach model i.e. the theory is developed based on the data collected during research.

However, the deductive approach is also said to have degrees of uncertainty (Saunders et

al., 2007) and moreover, as this research is based on theoretical considerations, our

research employs the deductive approach.

Fig 3.3: Deductive Approach

3.4 Research Method:

There are two different groups of research methods: ‘quantitative’ and

‘qualitative’. In quantitative analysis, we obtain statistical data that represents the

concepts empirically. This data is further measured using the quantitative statistical

methods which links the data to concepts (Neuman, 2006). On the other hand,

qualitative analysis explains the social phenomena which involve interviews and

observations from real life situations (Saunders et al., 2007) and the data here includes

written/spoken words, physical objects, sounds or visual images measured

simultaneously while collecting the data (Neuman, 2006).

This research uses both quantitative as well as qualitative methods to get

accurate results. The quantitative measurement uses the following models as justified

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THEORY

HYPOTHESIS

OBSERVATION

CONFIRMATION


in the literature review: Gronroos’ SERVQUAL model (Gronroos, 1994) to evaluate

CS with the Service Quality dimensions (functional dimensions, Technical dimension

and Corporate Image); ‘Disconfirmation models’ to analyse and evaluate customer’s

desires and expectations both with and without respect to their service provider

(Oliver 1980; Parasuraman et al., 1988) and the MnCSI model to evaluate the over-all

customer satisfaction with service delivery of the UK’s MTNs with and without

respect to which Mobile Telecom Network customers subscribe to (Positively

Minnesota, 2007).

According to Neuman (2006, pg. 412), “Researchers often combine focus group

with quantitative research, and the procedure has its own specific strengths and

weaknesses”. The strengths are: the lively setting that allows respondents to express

their opinions or ideas freely and interpretation of ideas is facilitated (Neuman, 2006).

This helps in bridging rich ideas and data in a continuing and interactive manner via

which we could have a better understanding of the subject in a bigger view and these

strengths overwrites the weaknesses which are: ‘polarization effect’ and limitation in

the number of topics discussed in a session (Neuman, 2006). Hence focus group

interview is the chosen Qualitative method as the research also includes quantitative

measurement. The focus group interview uses the Delphi technique to refine the

research ideas. This process involves employing a group of people who can contribute

some more value to the research idea (Saunders et al., 2007). The members of the

group were initially briefed about the research idea and were asked to suggest other

important elements to measure the service quality. According to respondents, among

these attributes they consider the balance between quality and cost as the most

important. It was then derived as another dimension to the Gronroos SERVQUAL

model called as ‘Value for Money (VFM)’. This focus group interview lasted for 60

minutes and the details of which is described in Appendix-A.

All the Service Quality Dimensions and its items (variables) used are listed in

table 3.4. Each dimension is represented with indicators as shown in the table below.

For e.g., Tangibles is TN, Reliability is RE, etc. A set of 3 items were added for every

dimension based on its properties except VFM which has 2 items. The items/variables

under each dimension are defined in the Appendix-H.

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Table 3.4: Service Quality dimensions and its comprising items

No. of

Items

Service Quality Dimensions No. of

Items

Service Quality Dimensions

3 TANGIBLES (TN) 3 ASSURANCE (AR)

3 RELIABILITY (RE) 3 TECHNICAL QUALITY (TQ)

3 RESPONSIVENESS (RP) 3 CORPORATE IMAGE (CI)

3 EMPATHY (EP) 2 VFM (Value for Money) (VM)

According to Neuman (2006), structured questionnaire is the most viable option

for quantitative measurement to get precise information in all respective areas and

also because of its ease of use nature. Since this research analyses several areas of

service quality, the quantitative method is used via closed-ended survey or structured

questionnaire designed based on all the items mentioned in Table: 3.4 to evaluate

customer satisfaction with service delivery.

A questionnaire was deployed for capturing the perceptions of customers about

their mobile service provider. The questionnaire consists of three sections with several

items as represented in Appendix-B: The first section includes age, sex and service

provider to get variety of responses, and help us set a pattern for that specific group.

The pattern analysis helps in satisfying the needs of specific groups in the society.

The second section consists of disconfirmation measures (desire and

expectation) derived from ‘Disconfirmation Models’, ‘Over-all customer satisfaction’

measure and ‘Service quality’ dimensions derived from Gronroos’ SERVQUAL

model and focus group interview (VFM). The third section includes all Service

Quality dimensions and asks the customer to rate the importance of each dimension

from their perspective, which is measured on a five-point likert scale ranging from

‘Least Important’ to ‘Most important’. The items in section 2 and 3 extensively

analyzes the requirements of all groups of customers ranging from basic to advanced

mobile services as well as the after sales service provided by their service provider.

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3.5 Operationalisation of Concepts:

3.5.1 Minnesota Customer Satisfaction Index (MnCSI):

This index may have up to 5 responses for 3 questions by which the customer

satisfaction levels are evaluated. The responses are measured using a likert scale of 1

to 5 i.e. ‘1’ being least satisfied and ‘5’ being highly satisfied.

The three questions asked to the customers are:

Overall, how satisfied or dissatisfied you are with the services being provided by

your network?

How well does the service fulfil your expectations?

To what extent did the services you received from them match your desired set of

services?

The questions mentioned above are rated on a five point likert scale i.e. each response

would have a value from ‘1’ to ‘5’.

Table 3.5.1a: Measuring MnCSI model on 5-point Likert scale

RESPONSES

1 2 3 4 5

Question 1 Very

dissatisfied

Dissatisfied Neutral Satisfied Very

Satisfied

Question 2 Much worse

than

expected

Much better

than

expected

Equal to

expectation

Better than

expected

Much better

than

expected

Question 3 Much worse

than desired

Worse than

desired

Equal to my

desire

Better than

desired

Much better

than desired

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The table 3.5.1a indicates the three questions with its corresponding values

ranging between 1 and 5 where ‘1’ indicates the customer’s very dissatisfaction with

the services and ‘5’ indicates the very satisfaction with the services.

Then the answers to these three questions are then calculated using this

formula (Positively Minnesota, 2007):

Further, it is calculated using the following procedure:

Step A: Frequency of each scale has to be found for all three answers.

Step B: The weight of each response must be calculated as shown in table

3.5.1b

Table 3.5.1b: Weight of each response

Responses 1 2 3 4 5

Weight 0 8.32 16.65 24.97 33.30

Step C: The frequency of each response obtained from the customer is then

multiplied with the response weight for all the three answers.

Step D: The Sum of the values for all three answers is then evaluated

Step E: The total sum is divided by (sample size-1) i.e. in our case it is 4.

The Minnesota Customer Satisfaction index is evaluated using these steps.

Then a description for customer satisfaction level is given to the derived value as

shown in the table below:

Table 3.5.1c: Description for each MnCSI value

MnCSI Value Description

81-100 Very High

61-80 High

51-60 Fair

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31-50 Low

Below 30 Very Low

Table 3.5.1c indicates that MnCSI value between 81-100 is marked ‘Very High’

implying the high level of customer satisfaction, and subsequently low as the range

decreases until Below 30 which is marked ‘Very Low’ implying the low level of

customer satisfaction level (Positively Minnesota, 2007).

3.5.2 Defining Hypothesis:

Now we explain how the research objectives are transformed into hypotheses

and executed. The following hypotheses are being used for this study:

H1: Customers dissatisfied with services offered by cellular network in the UK

with and without respect to which cellular network customers subscribe to.

Sub-Hypotheses Dissatisfied with

H1a Vodafone

H1b O2

H1c T-Mobile/Orange

H1d 3-Mobile

H2: The Disconfirmation models impact the over-all CS positively in UK’s

MTNs.

H2a: Expectancy disconfirmation impacts the over-all CS positively.

H2b: Desire disconfirmation impacts the over-all CS positively.

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3.5.3 Disconfirmation Models:

As justified in the literature review we use both desire as well as expectation

disconfirmation models to measure satisfaction. The table 3.5.3 shows the indicators

for these variables.

Table 3.5.3: Variables for Disconfirmation models

DD Desire Disconfirmation

To what extent did the services you received from them match your desired set of

services?

ED Expectation Disconfirmation

How well does the service fulfil your expectations?

Both these variables are measured using a 5-point likert scale. For DD, the

scales vary from ‘Much worse than desired’ to ‘Much better than desired’. Similarly,

for ED the scales varied from ‘Much worse than expected’ to ‘Much better than

expected’.

3.5.4 Over-all Satisfaction:

It refers to the customer’s over-all judgement on the service quality delivered

by their service provider. Here, we use only one indicator as shown in table 3.5.4

below, using a single question, to which the respondents rate their over-all satisfaction

with service quality on the 5-point likert scale which vary from very dissatisfied to

very satisfied.

Table 3.5.4: Variable for over-all Satisfaction Measure

OCS Over-all Customer Satisfaction

Overall, please rate how satisfied or dissatisfied you are with the services

being provided by your network.

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3.5.5 Procedures to test Hypotheses:

The following describe how the research objectives are met and tested with the

hypotheses.

Research Objective One (RO 1)

To find out the level of customers’ satisfaction with the service quality offered to

them by the UK’s MTNs with and without respect to which network customers

subscribe to.

The procedure outlined for MnCSI model (as described in section 3.5.1) is used.

3.5.5a Testing Hypotheses 1a to 1d (as mentioned in 3.5.2) under RO 1

One-Sample T test is used to test hypothesis H1a to H1d with and without

respect to the subscribed cellular network. Cut-off points 3 and 4 are chosen for

disconfirmation measure and Over-all customer satisfaction measure respectively with

significance level of 0.05. The null hypothesis assumes that customers are satisfied for

both with respect to and irrespective of cellular network. We take 3 as the cut-off

value for DD and ED because in disconfirmation scales, any rating between 3 and 5

indicates that the customer is satisfied. However, 1 and 2 indicates the customer’s

dissatisfaction. Cut-off point 4 is chosen for OCS measure, because in over-all

satisfaction scale, ratings from 1 to 3 indicates the customer’s dissatisfaction and

ratings 4 and 5 indicate that the customer is satisfied with the service delivery.

Procedure to test first hypothesis:

Step1: The Null hypothesis:

H0: x ≥ 3 (Equal to / Better than desired or expected)

H1: x < 3 (Worse than / Much worse than desired or expected)

H0: x ≥ 4 (Satisfied / Very Satisfied)

H1: x < 4 (Neither dissatisfied nor satisfied, dissatisfied / very dissatisfied)

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Step2: One-Sample T test is conducted at significance level 0.05

Step3: The t-statistics, confidence intervals and p-value (Critical value) is extracted

from SPSS output.

Step4: The null hypothesis is rejected under the following 2 conditions. Firstly, in

case the mean difference is significantly negative and secondly, if the confidence

interval is showing negative. It is not rejected if the mean difference is significantly

positive or any value under confidence interval includes a positive value.

3.5.5b Testing Hypothesis two and sub hypotheses (as mentioned in 3.5.2)

Here a linear regression is used as each sub hypothesis involves one

independent and one dependent variable. The three models that have to be tested are

as follows:

M1: Over-all CS = n + ED + DD + x

M2: Over-all CS = n + DD + x

M3: Over-all CS = n + ED + x

Where ‘n’ is a constant and ‘x’ is the error-term and here the null hypothesis states

that there is no significant relationship between both the disconfirmation models (DD

and ED) together and OCS.

The procedure to test these three models is mentioned below:


H0: DD ≤ 0 Variable DD is not significantly greater than 0

H1: DD > 0 Variable DD is significantly greater than 0

H0: ED ≤ 0 Variable ED is not significantly greater than 0

H1: ED > 0 Variable ED is significantly greater than 0

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Step2: Linear regression F test is conducted at significance level 0.05

Step3: p-value (critical value) is extracted from the SPSS output

Step4: The null hypothesis is rejected under following two conditions: If the p-value

is less than the significance value 0.05 and if the co-efficient is positive.

3.5.5c Research Objective Two (RO 2)

To find out which dimensions of service quality are the customers

satisfied/dissatisfied with in the UK’s MTNs?

As discussed earlier in Research Method (in section 3.4), customer satisfaction

is measured for four service quality dimensions: functional, technical, image and

VFM dimensions. Items under each dimension are defined in Appendix-H. One-

Sample T test is used to verify the significance of the mean differences with

significance level of 0.05 and test-value 3 in order to split the entire sample into

satisfied and dissatisfied customers for each of the items in each dimension of service

quality.

The following procedure is being used:


H0: x ≥ 3 (Equal / better than expected)

H1: x < 3 (Worse than / Much worse than expected)

Step2: One-Sample T test is conducted at significance level 0.05

Step3: Confidence intervals and p-value (Critical value) is extracted from SPSS

output.

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Step4: The null hypothesis is rejected under the following two conditions: If the mean

difference is significantly negative and if the confidence interval is showing negative.

It should not be rejected if the related mean difference is significantly positive or any

value under confidence interval includes a positive value.

3.5.5d Research Objective Three (RO 3)

What Service Quality dimensions do the customers perceive to be of high importance

in the UK’s MTNs?

One-Sample T test is conducted at significance level 0.05 with a cut-off value 3

to split the service quality dimensions that are considered important by the customers

from those that are unimportant. Then each service quality dimension is ranked in an

order of magnitude to point out the importance of each dimension from the

customer’s point of view.

3.6 Sample Selection and Data Collection:

According to Neuman (2006), the sample size for focus group interview must

range from 6 to 12 people. Hence, initially a sample size of 12 respondents are

selected to conduct a focus group interview, the selection was based on purposive

sampling method because the respondents had to pass the eligibility criteria before

they could participate (Neuman, 2006). All the respondents were students doing their

masters and they all were mobile telecom users, who had wide subject knowledge

regarding the quality concerns in mobile telecom networks in the UK.

The data was also collected via structured questionnaire which targeted only the

mobile telecom users. In this survey-process, emphasis was given to include people of

all groups within the UK (age groups, sex, etc), but more attention was given to the

younger generation and student sector, as they are considered to be one of the most

active cell phone users (Clickz, 2005). From the sample frame of 78 million cellular

service subscribers in the UK (Telecoms Market Research, 2008), a sample size of 100

respondents are selected due to the time and cost constraints. The time limit provided

37 | P a g e


to complete this research was very less and using a larger sample size may require

huge financial resources, which was unaffordable. Two different types of survey

instruments are used here for the collection of data. Firstly, out of the total sample

size of 100 respondents, 33 respondents responded via simple random sampling

method. This method was chosen because the population is comprised for mobile

service providers in the UK, each constituting a stratum. All these respondents were

students of UEL using UK cellular service. The survey was hosted on survey monkey

website and the link <http://www.surveymonkey.com/s/SGVRP5X> was sent to all

the students of UEL via university’s webmail and the link was also posted on several

social networking sites such as Facebook, Twitter and Orkut. Secondly, the remaining

67 respondents were selected randomly using the ‘personal contact’ approach from

different areas of London (Stratford, Bow Road, East Ham and Barking). In this

method, the respondents from the different areas are approached in person and they

are explained in detail about this survey. Out of the total 100 questionnaires collected

through various survey instruments, 17 are partially filled and hence it is being

rejected for data analysis. Overall there are 83 questionnaires that are usable for

further analysis.

3.7 Reliability:

Reliability refers to the consistency of measurements. A test is considered

reliable, if the test yields similar results repeatedly for similar set of inputs. In this

study we use the Cronbach’s Alpha test is used to assess the internal consistency of

the chosen likert scale and measure reliability of different service quality dimensions.

It is calculated using the formula mentioned below

Where ‘K’ is the number of items or components in the questionnaire and is the

mean of (Pallant, 2005).

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http://www.surveymonkey.com/s/SGVRP5X


With the help of reliability co-efficient Cronbach’s alpha we are checking the internal

consistency of each scale.

Table 3.7: Results of Chronbach’s α test

Service Quality

Dimensions

Chronbach’s α value No. of items/components

Tangibles 0.972 3

Reliability 0.963 3

Responsiveness 0.967 3

Empathy 0.975 3

Assurance 0.964 3

Technical-Quality 0.966 3

Corporate Image 0.981 3

VFM(Value for Money) 0.930 2

Importance of dimensions 0.973 8

Table 3.7 indicates that all the items under each dimension are above the

minimum scale of 0.7. Hence these values indicate that all of these dimensions are

reliable and internally consistent.

3.8 Validity:

Validity is concerned with accuracy of the measurements. It is one of the most

important factors for an experimental research. In other words, it is about testing the

data analysis procedure, if it is measuring in a right way and in an accurate manner.

Validity is of two types: Internal and external validity (Saunders et al., 2007). To

ensure validity in this research, there were many steps taken:

All the relevant theoretical frameworks, models and literature were examined in

an exhaustive manner i.e. viewed from different author’s/researcher’s perspective.

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Most of the questions are based on the theoretical frame works and literature, except

the service quality dimension- ‘VFM (Value for Money)’ derived from the focus

group interview. Still to ensure criterion validity, the structured questionnaire was

compared with other validated SERVQUAL models, which are similar to the one

created.

Pilot testing:

According to Saunders et al (2000) and Malhotra et al., (2007) the structured

questionnaire must be pre-tested before final administration. Hence the preliminary

draft of the questionnaire was pre-tested by the members of focus group interview to

check the clearness and significance of the questions and it was also checked

thoroughly by 3 employees and 2 managers who work for different mobile telecom

networks in the UK. Most of the parameters and wordings were changed based on

their advice, so that respondents can understand the questions clearly. Then it was

pre-tested to a sample size of ten telecom users who were selected through simple

random method. This sample size was suggested by Fink (2003b in Saunders et al

2007), who had mentioned that it is adequate to have a minimum of ten members for

the pre-testing. Before giving the questionnaire, each of these members were

described about the purpose of the questionnaire and ensured confidentiality and

anonymity.

It was also ensured that the questionnaire was filled by the mobile telecom

users of UK only, in both via e-survey as well as personal contact approach.

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4. DATA ANALYSIS AND DISCUSSION

4.1 Introduction:

This chapter focuses on statistical analysis of quantitative data which was

collected during the process of surveying. It comprises of data presentation that

covers demographic profile of respondents, measurement of customer satisfaction,

customer satisfaction with different service quality dimensions and relative

importance of those dimensions. The discussion includes analysis of different

hypotheses and their relative results and findings in order to answer the research

questions.

4.2 Demographic profile:

This shows the demographic grouping of all the respondents who participated

in the surveying process. It indicates that among the total of 83 respondents more than

half are males i.e. 67.5% are male respondents and the remaining 32.5% are the

female respondents and as mentioned previously in the research methodology,

majority of the respondents are youngsters, between 21 – 30, as they are the

economically active-group constituting 77.1%, whilst the rest constituting 22.9%

includes respondents of age group below 20, 31 – 50 and above 51.

4.3 Assessing Customer Satisfaction with the Service Quality:

To assess customer satisfaction with service quality four different measures are

used namely: MnCSI model, Desire and Expectation Disconfirmation models and

Over-all Satisfaction. All these models are supported by theory in the literature review

and also mentioned in the sections 3.5.1, 3.5.3 and 3.5.4 of research methodology.

Here the customer satisfaction is assessed with respect to cellular network and

irrespective of cellular network.

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4.3.1 Results of Minnesota Customer Satisfaction Index

The result for MnCSI model was arrived from the formula and steps that was

mentioned earlier in section 3.5.1. The raw data for this model was obtained from the

structured questionnaire, which is based on 83 responses.

Table 4.3.1: Customer satisfaction index using MnCSI

Cellular Network MnCSI value Description

Irrespective of cellular

network

52.2 Fair

Vodafone 46.3 Low

O2 54.8 Fair

T-Mobile / Orange 51.5 Fair

3-Mobile 51.3 Fair

The table 4.3.1 indicates the satisfaction index for all the four mobile service

providers (Vodafone, O2, T-Mobile / Orange and 3-mobile) and also index for the

total sample population without respect to which network the subscriber has

subscribed to.

Firstly, for all the mobile networks together the MnCSI value is 52.2, which is

represented as ‘Fair’ as it is above the satisfactory index of 50. This result shows that

in general the customer satisfaction in the UK’s cellular telecom market is

substantially fair.

Secondly, The MnCSI value for Vodafone, O2, T-Mobile / Orange and 3-

Mobile were 46.3, 54.8, 51.5 and 51.3 respectively. This implies that Vodafone has

got considerably low customer satisfaction with service quality, but it is fair for O2,

T-Mobile / Orange and 3-Mobile. The customer satisfaction index gives the

perception of a customer over the mobile service providers. The satisfaction score

reflects the past experiences of the customer with the providers, both positive and

negative and the result draws on the average of their experiences. Hence, we could

42 | P a g e


say that except Vodafone customers, the individual experiences of customers of all

other networks have been fair with their respective service providers.

4.3.2 Results of Disconfirmation Models and Over-all Customer Satisfaction

Measure:

4.3.2.1 Irrespective of cellular network:

The descriptive statistics for all three dimensions is mentioned below:

Table 4.3.2.1a: Descriptive-statistics of DD, ED and OCS

N MeanStd. Deviation

Std. Error Mean

OCS 83 3.33 1.138 .125

The details of this descriptive statistics is available in Appendix-E and the table

4.3.2.1a indicates the ratings by the 83 respondents for all the three measures i.e., for

DD measure the customers mean rating was 2.98 with standard deviation (SD) of

1.126, for ED measure the customers mean rating was2.96 with SD of 1.234 and for

OCS measure, the customers mean rating was 3.33 with SD of 1.138, being the

highest. The mean rating for ED and DD measures are very close to the cut-off value

3 and for OCS measure, it was below the cut-off value 4 and has a wider deviation

than the other two attributes (ED & DD).

Fig 4.3.2.1b: Customer satisfaction rating irrespective of cellular network

43 | P a g e

One-Sample Statistics

N MeanStd. Deviation

Std. Error Mean

Desire 83 2.98 1.126 .124

expectation 83 2.96 1.234 .135


Table 4.3.2.1c: Customer satisfaction rating irrespective of cellular network

1 2 3 4 5

DD 12 18.1 39.8 20.5 9.6

ED 15.7 19.3 28.9 25.3 10.8

OCS 7.2 18.1 22.9 38.5 13.3

In the fig 4.3.2.1b the x-axis indicates the measurement models: Desire

Disconfirmation(DD), Expectation Disconfirmation(ED) and Over-all Customer

Satisfaction(OCS) and the y-axis indicates Percentage(%) of customer satisfaction

rating, the details of these frequencies is given in Appendix-C and the table 4.3.2.1c

indicates that applying DD measure we could assess that 12% and 18.1% (a total of

30.1%) rated their satisfaction level as much worse than desired and worse than

desired respectively. 39.8% of the respondents rated that the service delivery is equal

to what they desire and 30.1% (20.5 + 9.6) rated that the services were better than or

much better than what they desired.

Applying ED measure we could assess that 15.7% and 19.3% (a total of 35%)

rated their satisfaction level as much worse than expected and worse than expected

respectively. 28.9% of the respondents rated that the service delivery is equal to what

they expected and 36.1% (25.3 + 10.8) rated that the services were better than or

much better than what they expected.

44 | P a g e


The first hypothesis and its sub hypotheses are tested as per the procedure

shown in section 3.5.5a in order to verify if the mean values are significant or not,

one-sample t test is conducted to test their significance level. The result obtained from

the test is presented in the table 4.3.2.1d below and the descriptive statistics is

available in Appendix-E.

Table 4.3.2.1d: One-Sample T test for ED & DD irrespective of cellular network

One-Sample Test

Test Value = 3

95% Confidence Interval of

the Difference

t df Sig. (2-tailed)

Mean

Difference Lower Upper

Desire -.195 82 .846 -.024 -.27 .22

expectation -.267 82 .790 -.036 -.31 .23

The table 4.3.2.1d indicates that, with the cut off point 3 the mean differences

are -0.24 and -0.36 for DD and ED respectively and the observed significance level

(p-value) being 0.846 and 0.790 for DD and ED respectively, which are more than the

significance level of 0.05 and the upper limit of their confidence intervals provides a

strong support towards not rejecting the null hypothesis. Therefore with 95%

confidence it can be concluded that the provided services are at least equal to their

desire and expectation.

Applying OCS measure we could assess that 7.2% and 18.1% (a total of 25.3%)

rated their satisfaction level as very dissatisfied and dissatisfied respectively. 22.9%

of the respondents rated that they were neither satisfied nor dissatisfied with the

service delivery and 51.8% (38.5 + 13.3) rated that they were satisfied / very satisfied

with the services.

45 | P a g e


The first hypotheses are tested as per the procedure shown in section 3.5.5a to

verify if the mean value is significant or not, one-sample t test is conducted to test

their significance level. The result obtained from the test is presented in the table

4.3.2.1e below.

Table 4.3.2.1e: One-Sample T test for OCS irrespective of cellular network

One-Sample Test

Test Value = 4

T df Sig. (2-tailed)

Mean

Difference

95% Confidence Interval of

the Difference

Lower Upper

OCS -5.401 82 .000 -.675 -.92 -.43

The table 4.3.2.1e indicates that, with the cut off point 4, the mean difference

for OCS measure is -.675 and the observed significance level (p-value) being .000,

which means that the mean is significantly lesser than 4. This provides a strong

support towards rejecting the null hypothesis. Therefore with 95% confidence it can

be concluded that customers are not over-all satisfied with the service delivery from

their service providers irrespective of cellular networks in the UK however, they are

at equal to their desire and expectation.

The CS in general with the UK’s cellular network is deemed to be fair as

obtained from the MnCSI value which is 52.2, slightly greater than the satisfaction

index of 50. It is at least equal to the customers’ desire and expectation. However, the

overall satisfaction of the customers with the service quality of the operators is

significantly low.

4.3.2.2 With respect to cellular networks:

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The details of frequencies with respect to cellular network is available in Appendix-D

4.3.2.2a Testing significance of the OCS measures for all cellular networks:


verify if those mean values are significant or not, one-sample t test is conducted to test


4.3.2.2b below and the descriptive statistics is presented in Appendix-E.

Table 4.3.2.2b: One-Sample T test to measure OCS with respect to cellular

networks

One-Sample Test

Test Value = 4

Company

t df Sig. (2-tailed)Mean Difference

95% Confidence Interval of the Difference

Lower Upper

Vodafone

OCS -1.941 8 .038 -.778 -1.70 -.15

O2 OCS -2.832 21 .010 -.682 -1.18 -.18

T-Mobile/ Orange

OCS -3.291 32 .002 -.667 -1.08 -.25

3-Mobile OCS -2.364 18 .030 -.632 -1.19 -.07

The Table 4.3.2.2b above shows that, having a cut off value 4, the mean

differences for over-all customer satisfaction are -0.778, -0.682, -0.667 and -0.632

and their p-values are 0.038, 0.010, 0.002 and 0.030 for Vodafone, O2, T-Mobile /

Orange and 3-Mobile respectively.

Their respective p-values show that all of their mean satisfaction is

significantly lesser than the cut off value 4 (as the p-value is less than 0.05 in all

cases) and even all of their confidence intervals are negative, providing a strong

support to reject the null hypothesis. Therefore, we can conclude with 95%

47 | P a g e


confidence that, the customers of all the four service providers are not satisfied with

the service quality provided by each of these companies and moreover, the over-all

satisfaction of the customers is very much worse with service quality of Vodafone

than the other cellular networks because it holds the highest negative mean difference.

Vodafone:

Table 4.3.2.2c: Mean satisfaction rating for Vodafone

DD ED OCS

2.22 3.11 3.22

Fig 4.3.2.2d: Satisfaction rating for Vodafone

The table 4.3.2.2c and the fig 4.3.2.2d indicate the mean ratings of the

customers of Vodafone for all the three models used. The mean rating for desire

disconfirmation and expectation disconfirmation are 2.22 and 3.11 respectively and

the mean for over-all satisfaction is 3.22.



48 | P a g e



4.3.2.2e below and the descriptive statistics is presented in Appendix-E.

Table 4.3.2.2e: One-Sample T test to measure DD & ED for Vodafone

Test Value = 3

Company 95% Confidence Interval of the Difference

t df Sig. (2-tailed)Mean


Vodafone DD -2.800 8 .023 -.778 -1.42 -.14

ED .286 8 .782 .111 -.79 1.01

The Table 4.3.2.2e above indicates that the mean differences using DD and ED

for Vodafone are -.778 and .111 respectively. The p value for DD measure is 0.023

(less than 0.05) which implies that the mean is significantly lesser than the cut off

value 3 which provides a strong support towards rejecting the null hypothesis. The p

value or significance for ED is 0.782 and as the mean is more than the test-value 3,

the null hypothesis is being considered positive in this case. Hence, we can conclude

with 95% confidence that, the customer satisfaction for Vodafone is at least equal to

their expectation and worse than the customer’s desire. With the evidence obtained

from section 4.3.2.2a, the over-all satisfaction of the customers is much worse than all

other service providers and even the satisfaction index in Table 4.3.1, indicated that

the CS is considerably low (with MnCSI value of 46.3) only for Vodafone, whereas

all other networks had their satisfaction index above 50, which indicates that CS is

fair for all other service providers. There are many inconsistencies faced by its

customers in terms of software updates, process delays, bad handoffs, etc. For

instance, Vodafone has still not attempted to take any measures to improve their

service delivery standards, as recently the company has angered many of its’

customers because they failed to test the software updates before pushing it to the

customers (Wattanajantra, 2010) Hence, Vodafone has to take some serious measures

in order to build their service delivery standards and customer satisfaction level.

O2:

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http://www.cnet.co.uk/search/date/asavin+wattanajantra.htm


Table 4.3.2.2f: Mean satisfaction rating for O2

DD ED OCS

3.09 3.18 3.32

Fig 4.3.2.2g: Satisfaction rating for O2

The table 4.3.2.2f and the fig 4.3.2.2g indicate the mean ratings of the

customers of O2 for all the three models used. The mean rating for desire






4.3.2.2h below and the descriptive statistics is presented in Appendix-E.

Table 4.3.2.2h: One-Sample T test to measure DD & ED for O2

Test Value = 3




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Test Value = 3

O2 DDED

.370

.6782121

.715

.505.091.182

-.42-.38

.60

.74

The p-values are 0.715 and 0.505 for DD and ED respectively, which are more

than 0.05 (significance level) which implies that the mean is significantly more than

the cut off value 3. The mean differences using DD and ED measures are 0.091 and

0.182 respectively. Hence the null hypothesis is being considered positive in both the

cases. Hence, we can conclude with 95% confidence that, the customer satisfaction

for O2 is at least equal to the customers’ expectation and desire. Even the satisfaction

index in Table 4.3.1, indicated that the CS is fair for O2. However, the evidence

obtained from section 4.3.2.2a states that still the customers are not satisfied with the

overall service quality provided by their network.

T – Mobile / Orange:

Table 4.3.2.2i: Mean satisfaction rating for T – Mobile / Orange

DD ED OCS

2.94 2.91 3.33

Fig 4.3.2.2j: Satisfaction rating for T – Mobile / Orange

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The table 4.3.2.2i and the fig 4.3.2.2j indicate the mean ratings of the customers

of T-Mobile / Orange for all the three models used. The mean rating for desire






4.3.2.2k below and the descriptive statistics is presented in Appendix-E.

Table 4.3.2.2k: One-Sample T test to measure DD & ED for T-Mobile/Orange

Test Value = 3




T-Mobile/

DD -.297 32 .768 -.061 -.48 .35

Orange ED -.415 32 .681 -.091 -.54 .36

The mean differences for DD and ED are -0.061 and -0.091 respectively but however

the p-values are 0.768 and 0.681 which are more than 0.05 (significance level). Here

though the mean differences are not significant, the corresponding upper limits of the

confidence intervals are positive (0.35 and 0.36), providing a strong support to

52 | P a g e


consider the null hypothesis. Hence, we can conclude with 95% confidence that, the

customer satisfaction for T-Mobile / Orange is at least equal to the customers’

expectation and desire. Even the satisfaction index in Table 4.3.1, indicated that the

CS is fair for T-Mobile/Orange. However, the evidence obtained from section 4.3.2.2a

states that still the customers are not satisfied with the overall service quality provided

by their network.

3 – Mobile:

Table 4.3.2.2l: Mean satisfaction rating for 3-Mobile

DD ED OCS

3.05 2.74 3.37

Fig 4.3.2.2m: Satisfaction rating for 3-Mobile

The table 4.3.2.2l and the fig 4.3.2.2m indicate the mean ratings of the

customers of 3-Mobile for all the three models used. The mean rating for desire



The first hypotheses are tested as per the procedure shown in section 3.5.5a to verify

if those mean values are significant or not, one-sample t test is conducted to test their

53 | P a g e


significance level. The result obtained from the test is presented in the table 4.3.2.2m

below and the descriptive statistics is presented in Appendix-E.

Table 4.3.2.2m: One-Sample T test to measure DD & ED for 3-Mobile

Test Value = 3




3-Mobile DD .213 18 .834 .053 -.47 .57

ED -.925 18 .367 -.263 -.86 .33

For 3-Mobile, the mean differences for DD and ED are 0.053 and -0.263 with p-

values 0.834 and 0.367 respectively. For DD measure, the mean is significantly more

than the cut off value 3, providing a strong support to consider the null hypothesis. In

the case of ED measure the mean difference of -0.263 is not significant but however,

the corresponding upper limit of the confidence intervals is positive (0.33), providing

a strong support to not to reject the null hypothesis i.e., satisfaction level is at least

equal to expectation. Hence, we can conclude with 95% confidence that, the customer

satisfaction for 3-Mobile is at least equal to the customers’ desire and expectations.

Even the satisfaction index in Table 4.3.1, indicated that the CS is fair for 3-Mobile.

However, the evidence obtained from section 4.3.2.2a states that still the customers

are not satisfied with the overall service quality provided by their network.

Though the services provided by O2, T-Mobile/Orange and 3-Mobile is at

least equal to customer’s desire and expectation, the Over-all Customer Satisfaction

with service delivery is considerably low. This could be very low because of the

following reasons:

i) The customers are very diversified with varied requirements on the Value Added

Services (Mobile Internet – 3G, e-mail services, News Updates, etc) and the Tariff

plans (Free Local Minutes/Texts Limits, Data Limits) etc, virtually having to

customize the plans to suit their particular needs. The people interviewed in the focus

group emphasized that they do not get the plan customized, for eg. One respondent

54 | P a g e


said ‘I need more call minutes and don’t need texts, but there is no plan where I can

reduce the text limit and increase the call limit for the same amount I pay’ and the

other said ‘I don’t need minutes and all I need is Data, but I have a plan where I pay

unnecessarily for minutes which I don’t use’. The service providers don’t usually let

the customers decide on what and exactly how much they want of these services,

letting down their satisfaction at the very stage of purchase.

ii) There exists a severe inconsistency between physical hardware capability and the

service capability. The technology is rapidly growing to enable supreme features in

the handsets but the service providers are unable to cope up with that growth. For eg.

The latest handsets are capable of transferring data at 7.2 Mbps while the real time 3G

speed is much lesser than 1 Mbps. The revolutionary 4G featured handsets Evo and i

phone 4G has no better use in the market where no provider has a 4G service.

The second hypothesis and its sub hypotheses are tested as per the procedure

shown in section 3.5.5b in order to find the relationship between disconfirmation

models and Overall satisfaction measure. The detailed results of this regression

analysis are presented in Appendix-G.

Table 4.3.2.2n: Result of regression analysis for Disconfirmation models

Models

Unstandardized Co-efficients

R² Std Error of the Estimate

Sig. F-TestBeta R

M1(constant)DDED

.652

.377

.563

.928 .861 .429

.000

.000

M2(constant)DD

.587

.910

.910 .829 .474

.000

55 | P a g e


M3(constant)ED

.810

.920

.920 .847 .448

.000

The Table 4.3.2.2n, points out that in the first model, DD & ED together affect

customer satisfaction positively, as the coefficients are greater than zero i.e. .377

and .563 for DD and ED respectively and it is significant as the P-value is also less

than 0.05, hence the null hypothesis is being rejected. In the second model, the co-

efficient is greater than zero (.910) and it is significant as the P-value is .000. In the

third model again the co-efficient is greater than zero (.920) and it is also significant,

as the P-value is .000. Hence we can conclude that all the three models significantly

and positively affect the over-all customer satisfaction.

Firstly, in model 1, the R (0.928) indicates that there exists a strong relationship

between desire disconfirmation, expectation disconfirmation and over-all satisfaction.

The R² (strength of the relationship): 0.861 shows that variations of about 86% in

over-all customer satisfaction are caused/explained by DD & ED collectively. Hence

we can conclude with 95% confidence that desire disconfirmation model and

expectation disconfirmation model together impacts OCS significantly. The results of

disconfirmation models for all the network operators were at least equal to the

customers’ desire and expectation except Vodafone, as their service quality was worse

than what they desired though it is at least equal to their expectation. Hence, if the

satisfaction level for disconfirmation models had been better than or much better than

desired or expected, then definitely the customers’ overall satisfaction with the service

delivery would have resulted positive.

Secondly, in models 2 & 3 (Table 4.3.2.2n) both the P-values are .000 (less than

0.05) and R values are .910 and .920 for DD & ED respectively, which shows that

both these models impact OCS. The outputs for R² (strength of the relationship)

56 | P a g e


are .829 and .847 for DD & ED respectively, which shows that variations of about

83% and 85% in over-all customer satisfaction are caused by DD and ED

respectively. Hence, it is validated that ED impacts OCS stronger than DD in the

UK’s cellular networks. So priority must be given to customers’ expectations than

their desires. Therefore, all the service providers must aim at determining what

exactly the customers expect from them in order to keep their customers overall

satisfied with their service delivery and eventually gain customer loyalty.

4.4 Customer satisfaction with each service quality dimension

A detailed descriptive statistics is found in Appendix-F which has got customer

satisfaction ratings for all the four service quality dimensions. One-Sample T test is

used to verify the significance of the mean differences. In this case, null hypothesis

(H0) states that the customer satisfaction level is least equal to his/her expectation and

the alternative hypothesis (H1) states that the customer satisfaction level is worse or

much worse than their expectation. The results of this test are presented in Table 4.4a

and it is tested as per the procedure presented in section 3.5.5c.

Table 4.4a: One-Sample T test for all the SERVQUAL dimensions

57 | P a g e


One-Sample Test

Test Value = 3


t df Sig. (2-tailed)Mean Difference Lower Upper

TN1 3.933 82 .000 .422 .21 .63

TN2 2.356 82 .021 .265 .04 .49

TN3 1.694 82 .094 .205 -.04 .45

RE1 5.524 82 .000 .530 .34 .72

RE2 -3.484 82 .001 -.410 -.64 -.18

RE3 -2.373 82 .020 -.289 -.53 -.05

RP1 1.504 82 .137 .169 -.05 .39

RP2 -.094 82 .926 -.012 -.27 .24

RP3 -5.477 82 .000 -.614 -.84 -.39

EP1 .366 82 .715 .048 -.21 .31

EP2 2.556 82 .012 .325 .07 .58

EP3 1.228 82 .223 .145 -.09 .38

AR1 3.942 82 .000 .434 .21 .65

AR2 -1.341 82 .184 -.169 -.42 .08

AR3 -.107 82 .915 -.012 -.24 .21

TQ1 -3.866 82 .000 -.446 -.68 -.22

TQ2 1.341 82 .184 .169 -.08 .42

TQ3 3.203 82 .002 .325 .12 .53

CI1 1.341 82 .184 .169 -.08 .42

CI2 1.706 82 .092 .193 -.03 .42

CI3 1.454 82 .150 .169 -.06 .40

VM1 -3.385 82 .001 -.398 -.63 -.16

VM2 1.382 82 .171 .205 -.09 .50

The items in the table 4.4a are indicators of different service quality

dimensions used in this research and the details of what each indicator stands for is

available in Appendix-H. In the table 4.4a, three different colour codes are given for

each item under the service quality dimensions. Green represents those items in which

the customer satisfaction level is better than or much better than their expectation.

Yellow represents those items in which the customer satisfaction level is at-least equal

58 | P a g e


to their expectation and Red represents those items in which the customer satisfaction

level is worse than or much worse than their expectation.

The Table 4.4a shows that both the mean difference and confidence intervals

(both lower and upper) are negative for six items, they are: RE2, RE3, RP3, TQ1 and

VM1. For these items the customer satisfaction level is worse or much worse than

their expectation. According to Borzorgi M. M. (2007), the customers mainly look for

technical quality and reliability than the others in the public sector industry. However,

the results show that two items of reliability and one item of Technical quality have

been rated very poor by the customers. Hence, the network providers must focus on

developing their technical quality in terms of network coverage and reliability by

resolving the customers’ issues on time.

There are twelve items in which either the mean difference or any one of their

confidence intervals include a positive value, which means that customer satisfaction

level is at-least equal to their expectation, they are: TN3, RP1, RP2, EP1, EP3, AR2,

AR3, TQ2, CI1, CI2, CI3 and VM2. The remaining six items includes TN1, TN2,

RE1, EP2, AR1 and TQ3 in which both the mean difference as well as confidence

intervals are positive, which states that the customer satisfaction level is better than or

much better than their expectation.

As presented in the fig 4.4b below, precisely six of the items under different

service quality dimension had their means significantly equal to the test-value 3.

Twelve items were rated equal to expectation and eight items were rated below the

test-value 3. Over-all eighteen items have been given a satisfaction rating as at-least

equal to or better than their expectation

Fig 4.4b: Satisfaction level with the SERVQUAL dimensions

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Therefore, we can conclude with 95% confidence that, the customer’s are

dissatisfied with the 5 items of service quality dimension (RE2, RE3, RP3, TQ1 and

VM1) and at-least satisfied with 18 items of service quality (TN1, TN2, TN3, RE1,

RP1, RP2, EP1, EP2, EP3, AR1, AR2, AR3, TQ2, TQ3, CI1, CI2, CI3 and VM2).

Though these items meet the customers’ expectation in order to create a tremendous

(Wow!) experience, the organisations have to develop strategies to go an extra mile

and diversely satisfy its’ customers.

In order to find the importance of each of these dimensions as perceived by the

customers, they were also asked to rate the importance of each service quality

dimension from their perspective (or point of view) on a five point likert scale. The

values ranged from ‘Least Important’, ‘Not so important’, ‘Important’, ‘Very

Important’ and ‘Most Important’. A descriptive statistics of all the dimensions and its

corresponding substituted values is given in the table 4.4c below.

Table 4.4c: Descriptive Statistics for importance of service quality dimensions

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Descriptive Statistics

N Mean

Std.

Deviation

Std. Error

Mean

TECHNICAL

QUALITY

83 3.93 .712 .078

CORPORATE

IMAGE

83 3.04 1.163 .128

VFM 83 4.48 .755 .083

TANGIBLES 83 2.76 1.100 .121

RELIABILITY 83 3.93 1.124 .123

RESPONSIVENESS 83 3.98 .715 .079

EMPATHY 83 2.98 .975 .107

ASSURANCE 83 3.40 .855 .094

In the table 4.4c, six dimensions have mean above ‘3’ and the remaining two

have the mean below ‘3’. One-Sample T test is used in order to key out the important

and unimportant dimensions with 0.05 as its significance level and 3 as its test-value.

The results of this test are shown in the table 4.4d below.

Table 4.4d: One-Sample T test for importance of service quality dimensions

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One-Sample Test

Test Value = 3


t dfSig. (2-tailed)

Mean Difference Lower Upper

TECHNICAL QUALITY

11.871 82 .000 .928 .77 1.08

CORPORATE IMAGE

.283 82 .778 .036 -.22 .29

VFM 17.886 82 .000 1.482 1.32 1.65

TANGIBLES -1.996 82 .049 -.241 -.48 .00

RELIABILITY 7.521 82 .000 .928 .68 1.17

RESPONSIVENESS

12.430 82 .000 .976 .82 1.13

EMPATHY -.225 82 .822 -.024 -.24 .19

ASSURANCE 4.239 82 .000 .398 .21 .58

The table 4.4d shows that all the dimensions are significantly important to the

customers. However, when it comes to the degree of importance for each service

quality dimension, Tangibles, Empathy and Corporate Image are significantly less

important to the respondents than the others because: either the mean difference or

any one of their confidence intervals include a positive value and the other five

dimensions of service quality (Technical Quality, VFM, Reliability, Responsiveness

and Assurance) have been rated with high degree of importance as it has got positive

mean difference as well as positive confidence intervals.

The rankings as to which dimensions are perceived to be more important than

the others is shown in Table 4.4e. These rankings are given to the service quality

dimensions with respect to their mean difference values i.e., the dimension with the

highest mean difference would be ranked one and correspondingly, the dimension

with the lowest mean difference would be ranked last.

Table 4.4e: Prioritized Service quality dimensions

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Service Quality Dimensions Rankings (Ascending Order)

VFM (Value for Money) 1

Responsiveness 2

Technical Quality 3

Reliability 4

Assurance 5

Corporate Image 6

Empathy 7

Tangibles 8

Table 4.4e indicate that VFM (Value for Money) is considered to be one of the

most important service quality dimensions, which is then followed by

Responsiveness, Technical Quality, Reliability, Assurance, Corporate Image,

Empathy and Tangibles.

The satisfaction matrix displayed in Table 4.4f below is designed after a careful

analysis of satisfied and dissatisfied dimension items of service quality in relation to

the prioritized dimensions in order to analyze which of the items of service quality

dimensions need more attention.

Table 4.4f: Satisfaction Matrix

Better / Much

better than

expected

At-least equal to

expectation

Worse / Much

worse than

expected

VFM VM2 VM1

Responsiveness RP1, RP2 RP3

Technical Quality TQ3 TQ2 TQ1

Reliability RE1 RE2, RE3

Assurance AR1 AR2, AR3

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Corporate Image CI1, CI2, CI3

Empathy EP2 EP1, EP3

Tangibles TN1, TN2 TN3

The Table 4.4f indicates the following:

Firstly, out of the six dimension items that has CS much better than or better

than expected (derived from Table 4.4a), three items are of high degree of

importance: TQ3, RE1 and AR1 while another three are considered to be of less

importance: EP2, TN1 and TN2. Hence, the focus on these particular attributes could

be shifted to those that are more significant but lacks attention.

Secondly, out of the twelve dimension items that has CS at least equal to their

expectations (derived from Table 4.4a), six items are considered very important:

VM2, RP1, RP2, TQ2, AR2 and AR3; while the remaining six items are of less

importance: CI1, CI2, CI3, EP1, EP3 and TN3. Hence the network providers need to

maintain the same service delivery standards for these attributes and eventually

increase it in order to achieve competitive advantage. Finally, under the dimension

items that has CS worse than or much worse than expected (derived from Table 4.4a),

all the items are considered very important VM1, RP3, TQ1, RE2 and RE3. Hence,

the attributes of service quality those customers perceive to be of high importance and

lacks attention from the service providers in the UK are mentioned in the table 4.4g

below:

Table 4.4g: The Service quality dimension items and their description which are

considered to be of high importance and lacks attention by network providers

VM1 How economical is the call charge per minute?

RP3 Ability of the employees to communicate clearly with the customers

TQ1 The network coverage

RE2 Dependability and consistency to resolve customer issues (or complaints)

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RE3 Ability to perform the service request on time

The description for each item is derived from the Appendix-H.

This gives the operators a note on what to concentrate to improve their CS

scores. The most important factor, Value for Money on how economical the charges

are; is mainly collected in comparison with other service providers, but the complaint

is that, the operators do not price the components equally, for e.g. if the call cost is

low, the data charge is high, and if both are low the roaming charges soar. Even if

these are considered to be business strategies, the hidden costs (fair usage guidelines,

starred conditions apply, etc) fuel the customers’ dissatisfaction. The incremental

usage of Virtual Networks (MVNOs) reasons the signal and clarity issues (Xln

Business Community, 2010). Hence, there has to be some limits set for these MVNOs

and gradually reduce their number in order to avoid capacity-crunch and by doing so

even the switching attitude of the customers can be brought under control, as the

customer’s may have limited service providers to choose. However, the

responsiveness, dependability and consistency factors are with respect to the

particular network and still no network operator has very satisfied customers on those

factors.

5. Summary & Conclusion

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The main purpose of this dissertation was to measure the level of customer

satisfaction with regards to service quality delivered by the UK’s MTNs with and

without respect to which network customer subscribes to; via four models: The

MnCSI model, Disconfirmation models (Desire & Expectation) and Over-all

Customer satisfaction model that was developed. This dissertation examined the

customer’s satisfaction level with several service quality dimensions and also finds

the dimensions that the customers perceive to be of very important.

Data for analysis was derived from Eighty three (83) survey responses. The following

summary of major findings & conclusions are based on the data analysis and the

discussions made:

Irrespective of cellular network in the UK, three models (MnCSI, DD and ED)

indicated that Customer Satisfaction is fair and at-least equal or equal to the

customer’s desire and expectation but one model (OCS) pointed out that

customer’s are dissatisfied. So considering the results of all the four models,

we can conclude that customers are neither satisfied nor dissatisfied with the

service quality delivered by cellular networks in the UK.

With respect to cellular networks, for the customers of Vodafone, their

satisfaction level is worse than desired and at-least equal to expectation. For

the customers of O2, their satisfaction level is at-least equal to desire and

expectation. For the customers of T-Mobile/Orange, their satisfaction level is

at-least equal to desire and expectation and for the customers of 3-Mobile,

their satisfaction level is at-least equal to desire and expectation.

The Over-all customer satisfaction has been rated as dissatisfied by the

customers of all the four networks. The ratings obtained are approximately

same for all the four companies.

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Regarding Customer-Satisfaction with various service quality dimensions, the

customer’s satisfaction level is better than expectation for the following six

items of service quality dimensions: TN1, TN2, RE1, EP2, AR1 and TQ3. The

customer’s satisfaction level is at-least equal to expectation for the following

twelve items: TN3, RP1, RP2, EP1, EP3, AR2, AR3, TQ2, CI1, CI2, CI3 and

VM2. The customers rated the following five items as dissatisfied: RE2, RE3,

RP3, TQ1 and VM1.

According to the customer’s priority, VFM is the most important dimension

followed by Responsiveness, Technical Quality, Reliability, Assurance and

Corporate Image, which scores the least importance. Tangibles and Empathy

are unimportant to the customers.

Most of the service quality dimension items which have been rated ‘satisfied’

by the customers are less important to them, while most of the service quality

dimension items which has been rated dissatisfied are more important to them.

Both the disconfirmation models (Desire and Expectation) collectively impact

OCS. However, ED impacts OCS stronger than DD in the UK’s cellular

networks.

A significance matrix was developed to gather data on the most important

dimensions that the respondent’s perceive and lacks attention from the service

providers in the UK. It is found that some items under the ‘Value for Money’,

‘Responsiveness’ and ‘Technical Quality’ are highly valued high by the

customers but the network providers have failed to achieve them.

Conclusion

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The mobile networks in the UK must acquire superior measures to increase the

quality of service in order to gain competitive advantage. The level of customer

satisfaction delivered by the mobile networks in the UK is considerably low and not

up to the mark. The process of amending the service quality standards begins from

identifying the customers’ needs and then taking required actions to satisfy them.

However, all the network providers have problems in identifying their customers’

needs. In most cases, the service quality provided is at least equal to the customers’

desire and expectation. The mean score just meets the threshold and significant

improvements have to be made on certain areas. As a result, it is highly essential for

all the cellular network providers to understand how the customers estimate the

quality of services. This research has identified five key attributes of service quality

which are considered to be of high importance by the customers and lacks attention

from network providers, they are: pricing issues, communication problems, network

coverage and lack of ability to resolve complaints and service requests on time.

Hence, it is crucial for the network service providers to concentrate on these five areas

to improve their service standards and eventually gain competitive advantage.

Recommendations for Future Research

This dissertation has primarily measured and analyzed the customer satisfaction level

with service quality in the UK’s cellular networks. Hence it is recommended that

future research could:

Analyze customer satisfaction in particular service areas such as Internet Services,

Video calls, SMS, MMS and other value added services.

Compare customer satisfaction level and Service quality with the current

technology (3G network) and the upcoming technology (4G network).

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Analyze customer satisfaction with fixed line services for e.g. with BT (British

Telecom) customers.

Verify the models and theories used in this dissertation with different industry

settings.

Finally, this study comprises a mixture of both qualitative as well as quantitative

models. Therefore, it is recommended that other models and approaches could be used

for a similar study and the results could be compared.

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