1

1. INTRODUCTION

1.1 Introduction

The dramatic growth in the recent years has changed cellular phone industry and the

cellular phones have moved beyond their fundamental role of communication. In

today’s scenario, consumers continuously want more out of their phone i.e. they use

their phones to listen music, play games, read news headlines, access the internet,

check their bank balance and more (Kavita and Chopra, 2011). Due to this dramatic

growth, the cellular industry all over the world has been witnessing fall in the costs of

cellular services, very high growth rates in subscriber base, and increasing competition

and deregulation. For developing countries in particular, cellular services are becoming

a very significant proportion of the overall telecom infrastructure (Dutta and Sridhar,

2003). The increasing competition in cellular service industry may be for the purpose of

attracting consumers towards the firms because consumers are the main source of

profitability of the firm (Parhizgar, 2002).

According to Rahman, et al. (2010), the service providers are offering most

sophisticated mobile services with an expanding number of value added services such

as Short Message Service (SMS), Wireless Application Protocol (WAP), subscription

services (SS), General Packet Radio Services, and Third Generation services, which

will help to attract consumers and the influence their buying behaviour. This value

added services are increasing the level of consumers’ expectations from service

provider and if the service provider is unable to meet these expectations then, the

consumers considers switching to competitors services. The switching behaviour of the

consumers will significantly affect the revenues, service continuity, and market share of

the firm (Oyeniyi and Abiodun, 2010). Therefore, in order to prevent consumers from

switching to competitors, the service providers are forced to add new schemes, offers,

technological advancements, and benefits with the services (Satish, et. al., 2011).

Cellular services have become the main source of growth in telecommunication sector

in India. The flexibility offered in communications and falling tariffs are playing a

significant role in popularising mobile communications (Rao, 2007). According to

Paulrajan and Rajkumar (2011), in the last decade, the mobile revolution has played a

significant role in the growth and development of Indian economy. As the number of

cellular service providers are continuously increasing, it is expected that the Indian

telecom industry will grow at a compound annual growth rate (CAGR) of 15.8 percent

between 2010 and 2014 and will touch revenues of $82 billion (377,683 crore INR)

(telecomleads.com). The Indian cellular consumer market is expected to double its

2

subscription base by 2015 when compared to present subscriptions (press trust of

Indian, 2011).

According to Kumar, et. al. (2011), the earnings and profitability of the company will be

highly affected, if it loses even a single consumer, as it can cost five times more to

acquire new customer than to retain an old customer. Therefore, in order to retain the

old consumers and reduce the rate of consumers from switching to competing service

providers, it is very important to study the factors that influence consumer behaviour in

terms of switching between the cellular service providers.

1.2 Problem statement

As the telecom sector is rapidly growing in India, due to the industry attractiveness,

new players are entering into the industry and making it more competitive, adding more

options for the consumers to switch between the cellular service providers. As the

study of Oyeniyi and Abiodun (2010) indicates that, the consumer switching behaviour

will affect the cellular service providers in terms of lowering market share, revenues

and consumer base of the firm. Therefore, the research is carried out on the topic of

consumer switching behaviour which could help the cellular service providers to

understand the reasons or rationale behind switching behaviour of consumer in cellular

services.

This research is targeting young adults aged between 18 to 35 years because India

has one of the largest youth population in the world and cellular services are one of the

services which would be interesting to them (Levi, 2007). Young adults are in general

more frequent mobile phone users than elderly people (Weslund, 2006). According to

Ericson (2004), young people are showing again and again that they are willing to

experiment with new services and that they define new uses for mobile services. It has

been indicated that young people are the heaviest users of mobile technology and are

highly desirable demographics because of their discretionary buying power (Miller,

2004). Therefore, it becomes very important for the cellular service providers to

understand the factors which influence this group of consumers to switch their service

provider because understanding this factors can help the company to maintain existing

consumers and win the new consumers which increase the consumer base of the firm

which in turn provides the opportunity to increase profitability and market share of the

firm.

In this research, sample is selected from Bangalore city located in Karnataka, South

India because it has a strong base in telecommunications and other industries. It is

also known as the science and technology capital of India, (Yue, et al., 2001). Due to

3

the rapid increase in telecom industry in India, the major cities including Bangalore

have registered new records in the sale of telecom services. Bangalore is one of the

cities with leading telecom directory in India and also one among the cities which are

the main telecom business centre of India (indiahousing.com). The major cellular

service providers in India such as BSNL (Bharat Sanchar Nigam Limited, MTNL

(Mahanagar Telecom Nigam Limited), Reliance communications limited, Tata Docomo

limited, Bharti Airtel, Vodafone Essar, Aircel and others have initially targeted big cities

including Bangalore for the launch of new telecom services such as third generation

(3G) mobile services (articles.economictimes.indiatimes.com). Therefore, this research

carried out in Bangalore city could help the cellular service providers to understand the

factors responsible for consumers switching behaviour. It will help the service providers

to offer the services according to consumer requirements, which in turn will help the

companies to prevent consumers from switching the cellular service provider and gain

loyalty and competitive advantage in order to compete in the rapidly increasing

competition scenario in Bangalore city.

1.3 Justification of the study

This study will make several contributions to the marketing literature from both a

theoretical and a managerial. Firstly, this study will contribute to the marketing literature

by providing an empirical examination of several service marketing constructs. The

results of this research can help the cellular service providers to have the deep

understanding about the factors that influence the consumers to switch between the

different service providers in cellular service industry.

Secondly, this study will benefit marketers and practitioners in the cellular service

industry. This research will identify the most important factors that cause customers to

switch or stay with a cellular service provider. This knowledge can make a contribution

to enhancing long-term customer relationships with customers. In addition, the

managers of the cellular service company can utilise this knowledge to prevent

potential customers from switching service providers. From the perspective of the

cellular service providers, that are attempting to attract new customers, this information

will enable cellular service providers to develop strategies to overcome switching

barriers and gain market share (Colgate & Lang, 2001). As Hennig-Tharau and

Hansen, (2000) states that, learning from the consumer switching stories, companies

can improve the services to avoid future switching behaviours.

4

1.4 Research Aim and Objectives

The research is designed to address the following aims and objectives. The broad aim

of the research is to explore and examine the factors that determine the consumers

switching behaviour of young adults (aged 18-35 years) in cellular service providers.

The objectives of the research are as follows.

1. To investigate the factors that influence consumers to switch the cellular service

providers.

2. To critically evaluate the most and the least significant factors that influence

consumers switching behaviour in cellular services?

3. To investigate the likeliness of consumers to switch from current cellular service

provider to another.

1.5 Research questions

The desired objectives of the research will be accomplished by addressing the

following research questions.

What are the situations which influence consumers to switch their cellular

service provider?

What is the effect of consumers switching behaviour on the cellular service

providers?

What is the percentage of customers who are willing and unwilling to switch

their current service provider?

What measures have to be taken to reduce the rate consumers switching

behaviour?

What are the steps to be taken to retain and gain customers?

1.6 Research Overview

This research has been split into five main chapter; Introduction, literature review,

methodology, findings and analysis, and conclusion and suggestions. The overview of

each chapter is given below.

1.6.1 Chapter 1: Introduction

In this chapter, firstly the telecommunications industry has been introduced indicating

the impact of development and change on cellular service providing companies in

relation to the consumers. Then the justification has been given about how this

5

research contributes to business or management. Lastly, the aim, objectives and

questions has been explained in this chapter.

1.6.2 Chapter 2: Literature review

In this chapter, the existing literature on relevant theories and researches has been

explored. The key theories and researches relating to the topic of ‘consumer switching

behaviour in cellular service provider’ have been discussed in order to gain both

theoretical and practical knowledge of this research. The main purpose of discussing

relevant theories and researches is to explore the factors that help to achieve the

objectives of this research. The literature review includes studies of many researchers

such as Richard Lee and Jamie Murphy (2005), Inger Roos, Bo Edvardsson, and

Anders Gustafsson (2004), and others. The discussion is based on marketing concepts

relating to the topic of consumer behaviour in terms of switching cellular services. The

major factors including service quality, price, switching costs, technological

advancements, advertising, social influence (reference groups), and involuntary

switching, that are mainly responsible for consumers switching behaviour in cellular

services have been discussed. Then, on the basis of these factors, the hypotheses

have been developed in this chapter.

1.6.3 Chapter 3: Research Methodology

This chapter explains and justifies the research methodology undertaken to carry out

this research. The different research methods have been discussed in this chapter and

the one which are assumed to be appropriate to achieve the objectives are chosen and

its impact on this research has been explained. The research methodology includes the

studies of many researchers such as Denscombe (2003), Saunders (2009),

Denscombe (2003), Kumar (2005), and more. The research methodology starts with

explaining the meaning of business research, then the research

paradigms/philosophies (interpretivism and positivism), research methods (quantitative,

qualitative, and triangulation), sampling (probabilistic and non-probabilistic), and data

collection (primary data and secondary data) have been discussed simultaneously with

chosen methods and its impact on this research. And then the undertaken data

analysis method and limitations of this research has been discussed in this chapter.

1.6.4 Chapter 4: Findings and Analysis

This chapter explains the findings drawn from the collected data through

questionnaires and presented in the form of tables and charts. Then those findings

have been analysed using different statistical tests such as descriptive statistics,

6

regression analysis, and correlation analysis in order to show the relationship between

the variables and draw the results. Then, on the basis of the tests and results, the

hypotheses have been tested followed by discussion and implication of the results of

each hypothesis in order to answer research question. Finally, the results of the

hypotheses are summarised and different switching factors have been ranked in terms

of their significance level in order to achieve research objectives.

1.6.5 Chapter 5: Conclusion and Suggestions

This chapter provides the brief summary of the whole research and also provides the

suggestions for further research, which can help the other fellow researchers who wish

to take this research to further end. The suggestions may also be helpful for the cellular

service providing companies operating in the area where the research has been carried

out.

7

2. LITERATURE REVIEW

2.1 Introduction

This chapter explores the literature on relevant theories and researches which help to

gain both practical and theoretical knowledge and understanding of the topic of

consumer switching behaviour in cellular services. The theoretical concepts and

researches explored in this chapter also includes the debates made by previous

researchers on similar topics, which significantly contributes to have better

understanding about the objectives of this research i.e. the factors that influence

switching behaviour and decisions of consumers in terms of cellular service providers.

The literature review firstly explains impact of marketing in relation to cellular service

industry, and then the main concept of this study has been discussed i.e. consumer

switching behaviour including the major factors that determine consumers’ switching

behaviour (switching determinants) in cellular services such as service quality, price,

switching costs, change in technology, advertising, social influences and involuntary

switching. Lastly, the hypothesis has been developed on the basis of the literature.

2.2 Marketing

According to Kotler, et al. (2009:6), ‘’marketing is a customer focus that permeates

organisational functions and processes, and is geared towards marketing promises

through value proposition, enabling the fulfilment of individual expectations created by

such promises and fulfilling such expectations through support to customers’ value-

generating processes, thereby supporting value creation in the firm’s as well as its

customers’ and other stakeholders’ processes’’.

Today, Marketing must not be understood in the old sense of making a sale – ‘’ telling

and selling’’, but in the new sense of satisfying customer needs (Kotler and Armstrong,

2008:7). This implies that, if the companies want to gain long-term benefits from its

customers, they have to understand marketing in the new sense of satisfying customer

needs. If the companies are able to satisfy the needs and expectations of its

customers, then customers will repurchase the products or services of a particular

company i.e. they exhibit loyalty towards the company, regardless of competitors’

efforts to distract customer attention towards them.

With respect to service marketing, Lovelock and Wirtz (2007), defines services as the

economic activities which one party offers to another, most commonly employing time-

based performances in order to bring about desired results in recipients themselves or

in objects or other assets for which purchasers have responsibility. Customers of

8

service expect to obtain value from access to goods, facilities, professional skills,

network, and systems; but there is no transfer of ownership of any physical elements is

involved.

Muddie and Pirrie (2006), identified four basic characteristics of services i.e.

intangibility, inseparability (simultaneous production and consumption), variability

(heterogeneity) and perishability. He also argued that marketing activity is normally

structured around the ‘4Ps’ i.e. product, price, promotion and place; but the distinctive

characteristics of services requires 3 more Ps in addition i.e. people, physical evidence

and process.

Considering the cellular services Kapoor, et al. (2011:337) states that, the services

provided by several companies are generally similar in their nature, therefore the only

way a service provider can make a mark on the consumers is by way of distinguishing

the physical evidence, people, and process attached to services of the company. For

example, the customer needs has to be served differently in terms of non-disruptive

connectivity, value additions in physical evidences, and the courteous services by the

people involved in rendering these services.

In regards to the current scenario of telecom services marketing in India, Kapoor, et al.

(2011:344) asserted that, the telecom services are facing a very dynamic marketing

situation with the international and global companies making their presence felt in the

Indian telecom markets. For example, with the entry of Virgin mobiles, Vodafone, and

many other international players, the customer has suddenly been placed as the main

beneficiary in the telecom scenario.

Schiffman, et al. (2008) stated that, consumer behaviour is a root of marketing concept.

Therefore, the concept of consumer behaviour in terms of switching in cellular service

industry has been discussed below because it may be significantly important for the

cellular service providers to understand the grounds in which consumers’ exhibit

switching behaviour in order to gain understanding on consumers’ needs and

expectations, and the ways for satisfying them. It can enable cellular service providers

to reduce the risk of customers switching from one cellular service provider to another,

as the success or failure of the company may depend on its consumers.

9

2.3 Consumer switching behaviour

2.3.1 Consumer behaviour

According to Loudon and Betta (1993), consumers are those individuals who purchase

goods or services for the individual or household consumption purpose. They defines

consumer behaviour as ‘’the decision process and physical activity individuals engage

in when evaluating, acquiring, using, or disposing of goods and services’’. Similarly,

Hoyer and Macinnis (2010:3), defines consumer behaviour as ‘‘the totality of

consumers’ decisions with respect to the acquisition, consumption and disposition of

goods, services, activities, experiences, people and ideas by decision-making over

time’’. A simplified framework proposed by Khan (2007), in the figure 2.1 helps to

understand the concept of consumer behaviour more clearly.

Figure 2.1: Simplified framework of consumer behaviour

Adapted from Khan (2002), Consumer Behaviour.

The study of consumer behaviour helps the companies to improve their marketing

strategies by understanding the issues described as follows

(consumerpsychologist.com).

How the psychology of consumers thinks, feel, reason, and select between

different alternatives.

How the psychology of consumers is influenced by the environment (for

example; family, friends, etc).

How the behaviour of consumers while making buying decisions.

10

How marketers can adapt and improve their marketing campaigns and

marketing strategies in order to reach consumers more effectively etc.

Therefore, the above discussion on consumer behaviour implies that, in order to fulfil

the objectives of this research, it is very important to understand consumer behaviour

because in cellular services, different consumers behave differently under the same

situation, which can directly or indirectly make positive or negative impact on profits,

market share, etc. Consumer behaviour in terms of switching is an important aspect for

the service companies. Due to the fast changing nature cellular telecommunications

industry, the cellular services consumers are often switching from one service provider

to another. Hence, it can be said that it is very important for the companies to

understand the reason behind consumers’ switching behaviour in order to compete,

gain market share, increase profitability and consumer base.

2.3.2 Switching behaviour

Switching in the context of consumer behaviour is referred to the times when consumer

chooses a competing choice rather than the previously purchased choice on the next

purchase occasion (Babin and Haris, 2011). Switching behaviour reflects the decision

that a consumer makes to stop purchasing a particular service or patronising the

service firm completely (Boote, 1998).

Satish, et al. (2011) argued that, consumers exhibits switching behaviour based on

their satisfaction level with the service provider. Conversely, the study of Roos (1998)

indicates that, even though customers may express their dissatisfaction, they

nevertheless frequently seem to switch service provider. Consumer satisfaction is

developed on the information from all previous experiences with service provider.

Customer wants and expectations are changing or increasing all the time (Paulrajan

and Rajkumar, 2011). In telecommunications industry customer bring high expectations

from its service providers Roos (1998) and if the service providers are unable to meet

these expectations then customers will take their business to somewhere else.

Therefore, it can be argued that the cellular service providing companies need to

consistently monitor and fulfil the changing wants and expectations in order to satisfy

them and prevent them from switching.

Customer satisfaction does not necessarily lead to loyalty. However, customers’ loyalty

is strengthened towards the service provider, when they are satisfied (Satish, et al.,

2011). Similarly, Fill (2005) argues that, if there is decrease in the consumers’

satisfaction level then loyalty may be lost and the complex switching behaviour occurs.

According to Brown and Chen (2001), some studies suggest that customer satisfaction

11

is an important antecedent of loyalty. Customer loyalty is influenced by customer

satisfaction and a loyal customer base is the real asset for a company.

Customer loyalty has a powerful impact on organisation’s performance and most of the

companies consider it as a source of competitive advantage. It increases revenue,

reduces customer acquisition costs, and lowers the costs of serving repeat purchasers,

which leads to greater profitability. Customers may avoid switch and remain loyal to

service provider, if they feel that they are receiving greater value than they would

receive from competitors (Lam, et. al., 2004). Oliver, (1999) stated that consumer

loyalty is a deeply held commitment to re-buy or repurchase a preferred service

consistently, regardless of situational influences and marketing efforts that have the

potential to cause switching behaviour. Customer loyalty is an important factor that

contributes to the firm’s profits, earnings and reduces defection rates (Duncan and

Elliot, 2002).

Considering the points raised by researchers relating to customers satisfaction and

loyalty which is discussed above, it can be noted that customer satisfaction is very

important factor and high responsible for gaining customers loyalty towards the firms.

Hence, cellular service providers have to to satisfy its consumers in every aspect

relating to their services and because if they fail to satisfy its consumers, then

consumer loyalty may be lost and they may consider switching their service provider

which in turn may bear loses for the firm. The impact of consumer switching or

defection on the firm is discussed below.

The study of Oyeniyi and Abiodun (2010) indicates that, the revenues and service

continuity could be significantly affected by customers’ defection or switching.

Reichheld and Sasser (1990) states that reducing customer defections by five per cent

increased profit by seventy five per cent. Defections have stronger impact on

profitability than unit costs, market share and more.

According to Bansal and Taylor (1999), the service providers are becoming more

concerned about customer retention because of the negative effects of customer

switching such as reduced market share, impaired profitability, and increased costs.

The service providers should carefully manage consumer retention because on the one

hand it is costly to retain a customer and on the other hand, all customers do not

generate same value to the firm and therefore it is not efficient to retain all customers

(Lopez, et. al., 2006). Thus, it can be understood that, for the cellular service providers

it is very important to carefully retain consumers because they are the main source to

generate potential profits and add value to the firm. If the firm fails to manage

12

consumer retention then, it may result in losing consumers loyalty towards the firm and

the rate consumers switching between the cellular service providers will be increased.

According to Colgate and Danaher (2000), relationship marketing has gained

increasing importance due to its benefits for both firms and the customers. The

strength of relationship between the service provider and consumer may encourage

consumers to switch or to stay with current service provider. For example Gwinner, et.

al. (1998), argued that consumer will commit themselves to service provider by

establishing, developing and maintaining relationships that provides superior valued

benefits. Similarly, the study of Colgate and Lang, (2001), shows that if consumers

switch from one service provider to another, then they may lose the benefits that are

available from the current service provider. Conversely, the study of Lopez, et. al.

(2006) indicates that building long-term relationships with consumers increases

profitability and their future viability for the firms. Hence it can be said that, the service

provider should give careful consideration to maintain long-term relationship with

consumers in order to reduce the risk of consumer switching from one service provider

to another.

Bansal and Taylor (1999) states that switching leads to negative outcome for the firm

which also involves replacing or changing the current service provider with another

service provider. Similarly, the study of Lee and Murphy (2005) indicate that,

consumers with negative service experience switch or consider switching to another

service provider. Therefore, it is significantly important to understand the major factors

that influence or determine consumers’ behaviour to switch cellular service providers

and decisions to buy cellular services for the purpose of retaining consumers and

reducing the rate of consumers switching from one service provider to another. It

enables the cellular service provider to gain competitive advantage which in turn helps

to generate revenues, increase market share and consumer base of the firm.

2.3.2.1 Switching determinants

According to Lee and Murphy (2005), there are several factors that determine

consumers to stay with their current service providers or to switch. Some of the

important factors which determine switching are:

Price is rated as the most important reason for switching.

Brand trust leads to commitment towards brand, which then reduces the

consumers’ behaviour to switch the service provider.

13

Switching costs are also important switching determinant because switching

costs such as monetary loss and uncertainties with new service provider deter

switching regardless of dissatisfaction.

Reference Groups which plays a significant role in influencing consumer to

switch the service provider in order to conform to others, norms, broad values

and behaviour.

Roos and Gustafsson (2007) states that, customers switch the service providers for

many reasons such as existing service provider no longer meets its customers’ needs

because of their changing circumstances or customers are getting better offers from

the competitors or customers wanting some variables. According to Mallikarjuna, et al

(2011) these reasons/determinants for consumer switching behaviour can be classified

into eight general categories – inconvenience, pricing, core service failure, service

encounter failure, response to service failure, competition, ethical problems and

involuntary switching. According to a classification given by Bruhn and Georgi (2006),

reasons for switching can be divided into three groups:

1. Customer-related switching reasons are concerned with customer characteristics

with a more or less direct connection with the service provider. Characteristics

concerns customers age, sex, preferences, lifestyles, etc and are directly connected

to customers’ needs (Bhrun and Georgi, 2006)

2. Provider-related switching reasons are closely connected to cause customer

retention and it is concerned with perceived service quality and customer

satisfaction. Service prodders can easily manage this category of reasons. It is the

most important source for avoiding customer defection (Bhrun and Georgi, 2006).

3. Competition-related switching reasons lead to customer defection because

consumer behaviour not often depends on the current service provider and its

service but also on its competitors. For example, when a mobile phone customer’s

basic criterion of buying is price, and then they compare the price system of their

current service provider and other provider (Bhrun and Georgi, 2006).

Roos, et al. (2004) stated that, customers own expressions of reasons for switching are

known as switching determinants. The reason for switching may be due the service

provider’s poor knowledge about how customers changing situations influence their

needs. The study of Lee and Murphy (2005) indicates that, in subscription market such

as telecommunications, consumers exhibit complete loyalty to one service provider and

often over long period. They also state that consumer subscribe to mobile services with

no initial intention to switch and remain completely loyal until triggers change them from

being loyal to switching or intending to switch the service provider. As there are number

14

of determinants which relates to loyalty and switching, this transitions may be due to

changes in underlying determinants, new determinants coming into play, or both (Lee

and Murphy, 2005). Some of the important factors that determine consumer switching

behaviour in cellular service industry have been discussed below to gain the

knowledge about underlying facts of those factors for the purpose of achieving the

objectives of this research.

2.3.2.1.1 Service quality and its dimensions

2.3.2.1.1.1 Service quality

Service quality as perceived by customers is defined by Zeithaml, et. al., (1990), as

‘’the extent of discrepancy between customers expectations or desires and their

perceptions’’. Bansal and Taylor (1999), favourably available that service quality is the

consumer’s judgement about a firm’s overall excellence or superiority. Perceived

service quality is obtained from the viewpoint of a consumers’ attitude towards to judge

the overall service prevision (Spathis, et. al., 2004). Lewis (1989) argued that,

perceived service quality is the judgement of consumers which is derived after

comparing between their expectations of service and the perceptions of actual service

performance.

Many researches revealed that there is a close relationship between service quality

and customer satisfaction which leads in influencing consumer behaviour. For instance,

according to Lee and Murphy (2005), existing literature suggests that improving service

quality satisfies customers and retains their loyalty. And the customers with negative

service experience may switch their service providers.

With regards to Cellular services, the study of Paulrajan and Rajkumar (2011)

indicates, that service providers are expected to compete on service quality and price,

as it is very important for service providers to meet consumers’ expectations in terms of

service quality. Services mainly depend on some factors and consumers buy services

which has many attributes in order to fulfil their desires. In cellular mobile markets,

customers carry high level of expectations from its cellular service providers in terms of

communication and if the service providers are unable to meet customers’

expectations, then it could result in customers switching their cellular service providers.

For example, the study of Paulrajan and Rajkumar (2011) indicates that, in today’s

scenario, cellular mobile has became a very important part for our daily communication

and customers buy the cellular mobile for instant communication and various services.

However, many researches indicate that the dimensions of service quality play a

significant role in determining service quality of the firm.

15

2.3.2.1.1.2 Dimensions of service quality

According to Cronin and Taylor (1992), service quality is a multi-dimensional or multi-

attribute construct. However, Gronoos (1990) noted that, there are three dimensions of

service quality i.e. functional dimension (process), technical dimension (outcome), and

image (corporate image). According to the study of Kang and James (2004), the

customers perceives service quality as what they receives as the outcome of the

process in which the resources are used i.e. technical dimension. But more often and

importantly customers perceives service quality as how the process itself functions i.e.

functional dimension. Customers bring their past experiences and overall perceptions

of a service firm to each encounter because they often have continuous contact with

the same service firm i.e. image dimension (Gronoos, 2001). Brady and Cronin (2001)

argued that, there is no general agreement as to the nature of the dimensions of

service quality.

Service quality dimensions with regards to cellular services providers include call

quality, call drop rate, geographical coverage, call forwarding and waiting, short

message service, mobile entertainment, complaint redressal system and others

(Paurajan and Rajkumar, 2011).

Considering the above discussion on service quality and its dimensions, it can be

therefore understood that, in the scenario of increasing competition in cellular service

industry, it is very important for the cellular service providers to continuously monitor

and improve service quality in order to meet the changing expectations, desires or

wants of consumers in terms of service quality for the purpose of satisfying consumers.

It is also very important for the cellular service providers to understand the impact of

service quality which is playing a significant role in consumers’ switching behaviour in

cellular service industry. This helps to gain consumers loyalty towards the company. It

can also help cellular service providers to reduce the rate of consumers’ switching from

one service provider to another, and retain and attract consumers towards the firm.

Ignorance of understanding the impact of the factors relating to service quality may

lead to lose the potential consumers, which in turn will have negative impact on the

firm.

16

2.3.2.1.2 Price

From the marketing point of view, researchers have recognised the importance of price

in affecting the behaviour of existing customers (Lemon, 1999). In most of the studies it

was found that price is the most important factor which affects customer to switch

loyalties to competing service provider (Satish, et al., 2011). Roos, et al. (2004)

favourably argued that price play a key role in consumers decision making to switch

service provider. Similarly, the study of Krishna, et al., (2002) indicate that, comparing

the price charged by current service provider with that of competitors, consumers

influences perceived savings. For example (Polo and Sese, 2009), when the price of

current service provider is high, consumers perceived savings from switching will be

high, as they would benefit from better pricing offered by competitors. The consumers

monetary saving will be high from switching the service providers when the

competitors’ prices are low (Polo and Sese, 2009). Polo and Sese (2009) also argued

that, competitors will use price to stimulate consumer switching behaviour. Hence, it

implies that the cellular service providers are more interested in attracting customers of

their competitors in order to increase market share, profitability, and consumer base of

the firm. Due to the competitor’s prices, the consumers are encouraged to switch the

cellular service provider by which the consumers can save money. However, this type

of competition may affect the revenues of not only one but both the competiting firms.

According to Bolton (1998), and Drew (1991), price is one of the most important

determinant which influence switching intentions in telecommunications industry.

Pricing factor include all critical switching behaviour that involved rates, fees, service

charges, price promotions, and others (Keaveney, 1995). For example, in

telecommunications sector, price may include call rates, subscription fees, roaming

charges, etc. The study of Keaveney (1995) revealed that, more than half of the

customers switched because of the poor price perceptions and suggested that

unfavourable price perceptions directly influence customers’ intentions to switch.

Therefore, in the context of cellular service industry, it can be assumed that, high price

or unfavourable price if the services (the price, which the consumers do not agree or

perceives it as unworthy to pay for the particular services or firm) can have negative

effect on consumers and may influence them to switch between the cellular service

providers.

The study of Lehtinen and Lehtinen (1991) indicates that, price plays a vital role in

telecommunications market, especially in cellular service providers. They also stated

that a price dominated mass market leads to customers having more choices and

opportunities to compare the pricing structures of different service providers. Hence, it

17

indicates that the companies which offers low price for the services may be able to

attract more customers, gain loyalty, and retain lost consumers. This can also help to

reduce or prevent consumers from switching their cellular service providers.

In the study carried out by Paulrajan and Rajkumar (2011), it was found that price has

significant positive impact on consumer perception in terms of selecting the

telecommunication service providers. However, Dutta and Sridhar (2003) argued that

price has both positive and the negative effects such as, in price-cap regulated market

the service providers use appropriate pricing strategy to win customers and market

share on one side. And on the other side, for example, in India which is highly price-

elastic market the cellular service providers reduce prices which may lead to increase

in subscribers base and so is the network traffic. This increased network traffic

decreases the performance and lowers service quality, inviting customers to switch the

service provider (Dutta and Sridhar, 2003). Hence, it can be understood that price

plays a significant role in influencing consumers buying decisions of cellular services

and it can also influence consumers switching intentions. It implies that cellular service

providers have to pay careful attentions on pricing their services because on the basis

of the above discussion, it can be said that consumers are very sensitive to price.

According to Pan (2009), Bharti Airtel, the biggest mobile operator in India, has

requested that TRAI (Telecom Regulatory Authority of India) to explore the business

models of companies that provide low-cost service to attract the new users. This was

the first time when the company has expressed the concerns over the ongoing low-

tariff initiated by Tata DoCoMo, one of the major competitor, when it had launched per

second billing plan in India. Bharti Airtel has urged the regulator to investigate the

predatory pricing plans adopted by telecom operators, which are increasing

competition in the country. For example, Indian cellular service providers, are offering a

variety of service plans as a means to attract new customers such as pre-paid calling

schemes, discounted call rates at evening and night time, discounted roaming charges,

free or minimum activation fee, discounted mobile-to-mobile call rates for long distance

calling, and free SMS messaging service (Dutta and Sridhar, 2003). Therefore, it can

be said that this might be one of the reason for increased competition among cellular

service providers to win customers by offering services on reduced prices which

therefore influence customers to switch the service providers because if the consumers

perceive that the competitor’s price is better than the current cellular service provider,

they considers switching. So, the cellular service providers have to way out the non-

pricing competition strategies to win customers.

18

2.3.2.1.3 Switching costs

Burnham, et al., (2003), defines switching costs as ‘the onetime costs that customers

associate with the process of switching from one service provider to another’. Switching

costs can be categorised in different ways such as Fornell, (1992) summarises

switching costs into search costs, transaction costs, learning costs, loyal customer

discounts, customer habit, emotional cost and cognitive effort, coupled with financial,

social and psychological risk. Similarly, Burnham, et al. (2003), classified switching

costs into procedural switching costs, financial switching costs and relational switching

costs. And Klemperer, (1995), describes switching costs as artificial costs, learning

costs and transactional costs. Switching costs protect firms from short-term fluctuations

in service quality and provide flexibility to charge prices above marginal costs, to a

certain point without fear of losing customers (Shy, 2002).

There are many researches that investigated the relationship between switching cost

and consumer switching behaviour. For example, Fornell (1992) states that switching

cost can help to prevent switching behaviour by making it costly for consumers to

change the service providers. High switching costs discourage consumers to leave the

current service provider because the consumers may perceive switching costs to be

higher than the expected benefits of switching the service provider (Lee, et. al., 2007).

Cross-industry findings of Burnham, et. al. (2003), indicate that switching costs, such

as monetary loss and uncertainties with the new service provider, deter switching

despite dissatisfaction. Similarly Gronhaug and Gilly, (1991), states that high switching

costs may tend even the dissatisfied customers to remain loyal.

An alternative to increasing customer retention and improving profits is to create

switching costs that make it difficult for customers to switch to competing service

providers (Klemperer, 1995). It was noted that if the switching costs are too high then

consumers prefers to stay with current service provider even if they are dissatisfied

(Gronhaug and Gilly, 1991). Hauser, et al. (1994) stated that when switching costs are

high, consumers become less sensitive to satisfaction level. Therefore, it can be

understood that switching costs in terms of time, money and efforts acts as a significant

barrier to switching when the consumers are dissatisfied with current service provider.

With regards to cellular telecommunication services, switching costs are defined as

loss cost, adaptation cost and move-in cost. Loss cost refers to the perception of loss

in social status or performance, when cancelling a contract with current service

provider; adaptation cost refers to perceived cost of adaptation, such as search cost

and learning cost; and move-in cost refers to the economic cost which is involved in

19

switching to a new service provider, such as purchase of SIM card and subscribers fee

(Kim, et al., 2004).

According to Paul de Bijl and Peitz (2002), switching costs with regards to

telecommunications market, the subscription of a consumer is valuable beyond the

profits stemming from that consumer in the current period, because there are lock-in

effects. Namely, a consumer suffers monetary or non-monetary disutility from switching

service providers. Switching costs may be advantageous to early arrivals and

disadvantageous to late arrivals, because initial market share is valuable. The

presence of consumer switching costs might lead to higher profits. If consumers are

aware of the lock-in effects then the companies possibly have to attract consumers by

low prices and if the consumers are ignorant about lock-in effects then the companies

have an advantage to build up market share as soon as possible because this allows

them to extract profits from these consumers (Paul de Bijl and Peitz, 2002).

In India the costs of switching from one cellular service provider to another is going

down rapidly. In the beginning, changing the service provider also meant losing the

number. But now, Mobile Number Portability (MNP) service was recently launched in

India in January 2011. It allows consumers to switch from their current service provider

to new service provider by retaining their current mobile number by paying just 19

Indian Rupees (telecomtalk.info). Therefore, it can be implied that switching cost is very

low and consumers can easily afford to switch, if they feel so. It leads to increase in

numbers alternatives and also added flexibility to the consumer to switch between the

service providers with low switching costs. These low switching costs are also forcing

cellular service providers to become more competitive in order to win the customers,

market share, and profitability.

2.3.2.1.4 Changes in Technology

As technology is advancing at a rapid pace, cellular service providers are scrambling to

keep up with customer needs and in the process trying to distinguish themselves from

the competitors. According to Sindhu (2005), offering new services not only helps to

retain and gain customers but it also provides a means of generating greater revenue

from one customer. He also states that companies which do not offer services in

keeping with the technological trend ultimately end up with losing the customer to the

competitor that does offer the service. For example, MTNL (Mahanagar Telecom

Nigam Limited) was the first provider to launch 3G mobile service in India

(telecomtalk.info). It might have helped MTNL company to retain and gain customers

from its competitors through its new service, as the customers may be keen to use new

20

services that are in trend in the market. It is also able to generate more revenues by its

value added service i.e. 3G mobile service was not available from any other service

provider in India except MTNL.

Sindhu (2005) states that, not only service providers but cellular manufactures are also

trying to keep up with the trend by offering latest devices to the customers. For

example, the new technologies in smart phones in which there are number of

applications are made available by the manufacturers but the cellular service providers

should make the services available to its customers by which they can be access the

applications available in their phones or devices which were offered by the

manufacturers. Sindhu (2005) states that, the cellular service providers that tie up with

these manufacturers to offer the latest equipment along with enhanced services appear

to emerge as winners in today’s market.

In today’s scenario of rapid advancements in technology, as the cellular phone

manufacturers are adding advanced options or applications in the phones, the cellular

service providers are also forced to upgrade their services because of the increasing

needs and wants of customers. If the cellular service providing firm ignore this fact,

then the consumers may prefer switching to another service provider due to the

unavailability of value added services or advanced services despite the availability of

the core service which leads the company to lose its potential customers and may bear

potential losses for the firm in terms of revenues, market share, etc.

2.3.2.1.5 Advertising

According to Lee and Johnson (2005), advertising is a paid, non-personal form of

communication about the organisation and its products or services that is transmitted to

the target audience through mass media such as television, radio, newspaper,

magazines, direct mails, outdoor displays, etc. Cengiz, et al. (2007) states advertising

as the activities undertaken to increase sales or enhance the image of a service, firm or

business, and the primary aim of advertising is to inform the potential consumers about

the characteristics of products or services. In the scenario of intense competition,

effective advertising may help organisation to communicate to the target customers

more easily, effectively, and successfully.

According to Davies (1996), Advertising can strengthen the communication between

organisations and the consumers’, and help to reduce consumers’ perceived risks

effectively. Advertising can also affect consumers’ behaviour because it can provide

information to guide consumers’ purchasing decision. Similarly, Zou and Fu (2011),

states that advertising aims to influence the way consumers view themselves and how

21

buying certain products or service can prove to be beneficial for them. The message is

conveyed through advertising and tries to influence consumers’ purchasing decision.

Steuernagel (2000), states that advertising for cellular services can be found on radio

and television, and increasingly in national as well as local commercials, because of

the consolidation of the carriers and participation of national companies. Most of the

companies invest in ‘brand ambassadors’ for spreading positive message of the brand

(Yeshin, 2006). For example, in India, most of the cellular service providers are

investing on brand ambassadors and most of the brand ambassadors are famous

television actors for promoting their brands. These brand ambassadors are influencing

the audience to buy a particular brand by which most of the consumers are highly

influenced and switch from one service provider to other irrespective of its price,

quality, costs and other benefits. This may lead to increase in the rate consumer

switching the current service provider to the competitor by the influence of favourite

actors i.e. brand ambassadors.

However, the literature indicates the several effects of advertising on switching

behaviour, such as the study of Balmer and Stotvig (1997), indicates that effective

advertising competition may stimulate consumer switching behaviour because of

cellular service consumers’ have been informed about more opportunities for their

purchasing choices. Hence, efficient advertising could enhance consumers’ loyalty and

help retain consumers’ (Cengiz, et. al., 2007).

On the basis of above discussion relating to advertising, it can be understood that

advertising plays a significant role from influencing consumers decisions in terms of

buy cellular services, and it also influence consumers intentions in terms of switching

cellular service providers, as advertising makes consumers aware about the products,

offerings, benefits, and others factors which act as the source of influencing or

attracting consumers’ behaviour in favour of the firm.

2.3.2.1.6 Social influences (reference groups)

According to Rodriguez (2009), social influence is the widely accepted factor which

determines consumer behaviour. The members of social network heavily influence

most of the consumers in choosing the mobile service provider. Rodriguez (2009), in

her studies found that most of the consumers chose the same service provider as their

friends, family members or colleagues were using. Similarly, the study of Kasande,

(2008), indicates that social/reference groups which force consumer to match to others

expectations or standards, affects broad values, and other factors and influence

switching behaviour.

22

The study of Dasgupta, et al. (2008) indicates that, there is a relationship between

social networks or groups and switching behaviour in mobile telecommunications. They

used call graphs which was developed from a large amount of Call Data Records, and

showed that the tendency of subscriber to switch the service provider was influenced

by the number of members of social group who had already switched. It is likely that

the other members of social group of the switcher will also get defected.

Kasande, (2008), stated that the dissatisfied customers may express their feelings by

complaining, looking for alternatives or negative word of mouth. The study of

Wangenheim (2005), has explored customer behaviour after having switched a service

provider. It says that the customers express their disappointment about a dropped

service provider to others (social groups) in the form of negative word of mouth. The

word of mouth (WOM) has been recognised as an important force in marketplace,

influencing attitudes, preferences, purchase intention and decision making. He also

indicates that, it is important for the service provider to understand why or in what

situations the customers spread negative WOM after switching. Hence, it can help

cellular service providers to predict which customers are most likely to spread negative

WOM and represents ‘dangerous’ customer group if lost, because negative WOM

prevent potential new customers of the social group of dissatisfied customer from

choosing the service provider and it can also increases defection rate of current

customers.

Therefore, social influence or reference groups should be considered as one of the

important factor which influence switching behaviour and buying decisions of

consumers in cellular services. These are the groups which can influence the

consumers to buy cellular services of a company by expressing positive feeling or

experience with the service provider. They can also influence consumer switching

behaviour by expressing negative experience with the service provider. Hence, it can

be said that, the cellular service providers should be able effectively maintain the

relationships with its existing consumers, which could help the company to decrease

the rate of switching behaviour and also attract the social groups of existing

consumers. This increases the firm’s consumer base, revenues, and also its market

share.

23

2.3.2.1.7 Involuntary switching

According to Rajeev (2008) states that, there are three types of switching

determinants; influential triggers, situational triggers, and reactional triggers. He also

states that involuntary switching falls under the category of situational triggers. He

defined situational triggers as the changes in customers own lives which are not

essentially related to service provider and therefore consumers decide to switch when

they perceive that the service provider no longer reflects their reality. Therefore, it can

be said that the different changes may act as situational triggers such as changes in

work hours, financial status, location, and others which tend the consumers to switch

their service provider unintentionally.

Switching behaviour is occurred not only with the intentions to switch but also due to

the involuntary factors (Roos, 1999). The involuntary switching factors are not under

the control of both parties i.e. consumers and the service providers (Keaveney, 1995).

Hence, it can be implied that for example, relocation of house in area where the

services of current service provider are not available then the consumer is forced to

switch the service provider unintentionally because it is beyond the control of consumer

and service provider and it can put an end to service relationship despite satisfaction.

The latest wave of acquisition and mergers within this industry is another factor leading

to involuntary switching (Sidhu, 2005). For instance, the cellular service provider in

India, Idea cellular has acquired Spice telecommunications in 2008

(articles.timesofindia.indiatimes.com) by which the entire consumer base of Spice

telecommunications was forced to switch to Idea cellular. Therefore, it indicates that the

consumers are forced for switch their cellular service providers due to the

circumstances which are neither in the control of service provider, nor in the control of

consumers. Under this situation, both the cellular service provider and the consumer

will be unable help each other from exhibiting consumer switching behaviour.

2.4 Hypothesis Development

On the basis of the above discussed literature relating to the topic of this research,

following hypotheses have been developed to satisfy the objectives of the study.

H1: Service quality has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

H2: Price has a direct and significant effect on consumers’ switching behaviour in terms

of switching cellular service provider.

24

H3: Switching costs has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

H4: Changes in technology has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

H5: Advertising has a direct and significant effect on consumers’ switching behaviour in

terms of switching cellular service provider.

H6: Social Influence (reference groups) has a direct and significant effect on

consumers’ switching behaviour in terms of switching cellular service provider.

H7: Involuntary switching has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

2.5 Chapter summary

The above discussion has been aimed to provide the thorough understanding about

the factors that influence consumer behaviour in terms of switching cellular service

providers. For the purpose achieving the objectives of this study, seven most important

factors that can influence consumers switching behaviour in cellular service has been

explored on the basis of the literature. These factors are; service quality, price,

switching costs, change in technology, advertising, social influence, and involuntary

switching. In addition, the key arguments made by several researchers such as Lee

and Murphy (2005), Roos, Edvardsson and Gustafsson (2004), Keanvey (1995), etc

relating to these factors have been explored for the purpose of satisfying the objectives

of this research and making this research more reliable. Furthermore, the methodology

undertaken to carry out this research is discussed in the next chapter.

25

3. RESEARCH METHODOLOGY

3.1 Introduction

This chapter will elaborate the methodology employed to carry out this research. It

firstly defines the business research and then highlight research philosophies which

include interpretivism philosophy and positivism philosophy and then discusses the

chosen research philosophy i.e. positivisim philosophy. Then the types of research

methods including qualitative method, quantitative method, and triangulation method

have been explained and method taken for this research i.e. quantitative method has

been justified. Furthermore, the types of sampling methods which include probabilistic

and non-probabilistic sampling are explained and then the chosen sampling method i.e.

simple random sampling has been justified. Then, the types of data collection used in

this research (primary data and secondary data) have been discussed. Lastly, the data

analysis method undertaken for this research and the limitations of this research has

been discussed.

3.2 Business Research

Research can be defined as something undertaken in a systematic way to increase

and enhance knowledge (Saunders, et al., 2009). Cooper and schindler (2006), defines

business research as ‘’a process of planning acquiring, analysing, and disseminating

the relevant data, information and insight to decision makers in ways that mobilize the

organisation to take appropriate actions which in turn maximise business

performance’’. In relation to this, there are several things to be considered when

someone is undertaking a research, including research philosophies/paradigms.

3.3 Research Philosophy/Paradigm

According to Saunders, et al. (2009), research paradigm is defined as ‘basic belief

system or world view that guides the investigation, not only in choices of method but in

ontologically and epistemologically fundamental ways’. Research method is defined as

methods or techniques used by a researcher when performing the action of research.

However, research methodology is a way to systemically solve the research question

(Kumar, 2005). Methods refer only to the various means by which data can be

collected and/or analysed (Collis and Hussey, 2003).

26

According to Denscombe (2003), there are two types of research

philosophies/paradigms; interpretivism (phenomenology y) and positivism.

Interpretivism philosophy can be defined as 'an approach that focuses how life

is experienced'. This research approach examines human experiences, and is

also 'characterised by a particular interest in the basics of social science'.

(Denscombe, 2003). Intrepretivism also refers to the construction of social

reality, seeing things from others' eyes, in which it has several significances in

social research. In this type of research, the researchers assumes access to

social reality and people experiences through social constructions i.e. language,

consciousness, shared meanings and instruments (Michel and Myers, 2008).

This type of research includes ethnography, interviews, participant

observations, conversational analysis, focus groups, and case studies (Lincoln

and Denzin, 2000).

Positivism philosophy argues that knowledge of social world can be obtained

objectively and only the measureable data should be taken into account. Davies

and Parker, (2007) argues that, positivist research is a scientific method in

which after identification of problem data is collected. Furthermore, during the

positivist research, human behaviour is predicted on the basis of universal laws

and phenomenon. Positivist research includes questionnaires, secondary data,

and quantitative statistics.

Easterby-Smith et al. (1997), identify three reasons why the exploration of philosophy

may be significant with particular reference to research methodology: First, it would

help the researcher to refine and specify the research methods utilised in a study. This

is intended to clarify the overall research strategy used. This would include the type of

evidence gathered and its origin, the way in which such evidence is interpreted, and

now it helps to answer the research questions posed.

Understanding of research philosophy will enable and help the researcher to evaluate

different methodologies and methods and avoid inappropriate use and unnecessary

work by identifying the limitations of particular approaches at an early stage. Finally, it

may help the researcher to be creative and innovative in either selection or adaptation

of methods that were previously outside his or her.

The table 3.1 shows the differences between positivism and interpretivism

(phenomenological) research philosophy.

27

Positivist philosophy Interpretivism

(Phenomenological)

philosophy

Basic Beliefs

The world is external and

objective

The world is socially

constructed and subjective

Observer is independent Observer is part of what is

observed

Science is value-free Science is driven by human

interests

Researchers’ Focus

Focus on facts Focus on meanings

Look for causality and

fundamental laws

Try to understand what is

happening

Reduce phenomena to

simplest events

Look at the totality of each

situation

Formulate hypotheses and

then test them

Develop ideas through

induction from data

Preferred Methods Include

Operationalising concepts

so that they can be

measured

Using multiple methods to

establish different views of

phenomena

Taking large samples Small samples investigated

in depth or over time

Table 3.1: Difference between positivism and interpretivism research philosophies

Adapted from: Mangan, (2004)

Positivism research philosophy is chosen for this study, due to the nature of data which

has been collected after identifying the problem in this research. This is particularly

relevant because the factors to determine consumers switching behaviour used in this

study are based on theoretical concepts and previous researches. Another reason for

28

choosing positivism philosophy is to obtain the data that can be easily measured in

order to convey the reliable results. Positivism philosophy is also chosen because of

the nature of this research, which is based on achieving the main aim of this research

by satisfying the objectives. Hence, it means that the research is objective rather than

subjective which is the theme of positivism philosophy. Therefore, on the basis of

theories and previous researches, seven hypotheses have been developed relating to

seven factors that were identified as the major factors that can make significant effects

on consumers switching behaviour. Then the hypotheses have been tested in order to

achieve the objectives of this research focussing on facts to gain the more specific

information relating to the situations in which consumers are influenced to exhibit

switching behaviour. Whereas, the interpretivism philosophy may be risky to adopt for

this research and may sometimes deliver inaccurate and unreliable results, if the

researcher makes even a negligible mistake in understanding the situations.

3.4 Research Methods

Research methods can be divided into three categories; quantitative methods,

qualitative methods, and triangulation methods.

Quantitative research is based on the measurement of quantity or amount

(Kumar, 2005). This type of research is applicable to phenomena that can be

expressed by terms of quantity. On the other hand, qualitative research is

concerned with qualitative phenomena, phenomena relating to quality or kind.

Quantitative research falls under empirical studies; which include more

traditional ways in conducting psychological and behavioural studies and it has

been a dominant method in researching social sciences (Kumar, 2005).

Quantitative designs include experimental studies, quasi-experimental studies,

etc in which control of variables, randomisation, as well as valid and reliable

measures are necessary if the research aim is to reach generalisability among

the research samples (Campbell and Stanley, 1963).

Quantitative data can range from a short list of responses to open-ended

questions in an online questionnaire to more complex data such as transcripts

of in-depth interviews or entire policy documents. Qualitative data analysis

procedures including deductive and inductive approaches are used to assist

understanding the meanings. Qualitative approach allows researcher to have

“deeper understanding of organisational experiences and situations of

individuals” (Ticehurst and Veal, 2000). Observation, informal and in-depth

interviews altogether with observation can provide qualitative data. Qualitative

29

methods make use of limits the number of observations allowing deeper

understanding of the study.

Whereas, in triangulation method, a mixture of both qualitative and quantitative

methods is used (Cooper and Schindler, 2006). First a qualitative data is used

interviewing a sample of respondents to achieve the key questions and then

these are used to design and evaluate survey questionnaires for the second

stage. As Binsardi, (2008) states that, qualitative methods informs quantitative

analysis.

The comparison between qualitative and quantitative research can be found in the

table 3.2.

Qualitative Quantitative

Focus on Research Understand and interpret. Describe, explain and predict.

Researcher

Involvement

High-researcher is

participant or catalyst.

Limited; controlled to prevent

bias.

Research Purpose In-depth understanding,

theory-building.

Describe and predict; build

the real theory.

Sample Design Non-probability, purposive. Probability.

Sample size Small. Large.

Research Design

May evolve or adjust

during the course of the

project.

Often uses multiple

methods simultaneously

or sequentially.

Consistency is not

expected

Involves longitudinal

approach.

Determined before

commencing the project.

Uses single method or

mixed methods.

Consistency is critical

Involves either a cross-

sectional or longitudinal

approach.

Participant Preparation Pre-tasking is common. No preparation desired to

30

avoid biasing the participant.

Data type and

Preparation

Verbal or pictorial

descriptions.

Reduced to verbal codes

(sometimes with

computer assistance).

Verbal descriptions.

Reduced to numerical

codes for computerised

analysis.

Data analysis

Human analysis

following computer or

human coding, primarily

non-quantitative.

Forces researcher to

see the contextual

framework of the

phenomenon being

measured-distinction

between facts and

judgments less clear.

Always on-going during

the project.

Computerised analysis—

statistical and

mathematical methods

dominate.

Analysis may be ongoing

during the project.

Maintains clear distinction

between facts and

judgements.

Insights and Meaning

Deeper level of

understanding in the

norm, determined by

type and quantity of free-

response questions.

Researcher participation

in data collection allows

insights to form and be

tested during the

process.

Limited by the opportunity

to probe the respondents

and the quality of the

original data collection

instrument.

Insights follow data

collection and data entry,

with limited ability to re-

interview participants.

Research Sponsor

Involvement

May participate by

observing research in real

time or via taped interview.

Rarely has either direct or

indirect contact with

participant.

31

Feedback Turnaround

Smaller sample sizes

make data collection

faster for shorter

possible turnaround.

Insights are developed

as the research

progresses, shortening

data analysis.

Large sample sizes

lengthen data collection;

internet methodologies are

shortening turnaround but

inappropriate for many

studies.

Insight development

follows data collection and

entry, lengthening research

process; interviewing

software permits some

tallying of responses, so

data collection progresses.

Data Security

More absolute given use

of restricted access

facilities and smaller

sample sizes.

Act of research in progress is

often known by competitors,

insights may be gleaned by

competitors for some visible,

field-based studies.

Table 3.2: Comparison between Qualitative and Quantitative Research

Source: (Anggraeni, 2010).

Quantitative research method has been used for this research because it permits to

obtain the views of large audience in less time as compared to qualitative method,

which in turn can help to generalise the results of this research and make sure that the

outcome is reliable. Quantitative method is also chosen to avoid favouritism of the

participants in order to reduce the risk of unreliability in results. As the objectives of this

research is based on seven determinants of consumers switching behaviour,

quantitative method helps to know the significance level of each determinant by

analysing the influence of factors on switching behaviour of the proportion of

participants. As quantitative method measures consumers’ behaviour, opinions, and

attitudes, it is be appropriate to choose this method because it is more relevant to this

research and deliver more reliable outcome. This type of data can range from simple

counts such as the frequency of occurrences to more complex data such as scores,

prices or rental costs. Data obtained in this method is through questionnaire, surveys,

or from secondary sources (Ticehurst and Veal, 2000). Therefore, the survey

questionnaire has been designed to evaluate the factors influencing consumers’

switching behaviour in cellular services. On the other hand, the qualitative method for

32

this research may incur biasing of participants and may not provide the appropriate

information on significance level of each determinant or factor that influence consumer

switching behaviour because the number of participants will be less as compared to

quantitative method.

3.5 Sampling

According to Denscombe (2003), there are two kinds of sampling techniques that can

be used by researchers. The first is known as ‘probability’ sampling and the second is

known as ‘non-probability’ sampling.

Probability sampling is based on the idea that people or events that are chosen

as the sample are chosen because the researcher has some notion of the

probability that these will be the representative cross-section of people or

events in the whole population being studied (Denscombe, 2003). Probability

sampling is the most utilised sampling method for social research purpose

(Babbie, 2008). Probability sampling can be divided into different types which

include simple random sampling, interval or systematic sampling, stratified

sampling, cluster or multi-stage sampling (Bless, et al., 2006).

Non-probability sampling is often conducted in social research where the

situations do not permit probability samples used in large scale basis (Babbie,

2008). Non-probability sampling includes accidental or availability sampling,

purposive or judgemental sampling, and quota sampling (Bless, et al., 2006).

This type of sampling can also be used where no probability sampling method

is appropriate. Non-probability sampling can be further divided into purposive

sampling, snowball sampling, and quota sampling.

The objectives of this research are to explore the factors that influence consumers

switching behaviour of young adults in regards to cellular service providers. Therefore,

in order to achieve these objectives specifically, the mobile phone users in Bangalore

who are aged between 18 to 35 years are to be chosen, so the appropriate method for

sampling is ‘simple random sampling’. It helps to obtain the opinions of respondents

with different characteristics and can also help to add some extent of generalisability in

the results. This method is also used for this research, for the purpose of providing the

greater flexibility in collecting the primary data. Sample has been collected by sending

questionnaires electronically to respondents via e-mail and the purpose of this research

has also been explained to the respondents, so that they can feel free and secure to

participate and respond genuinely to the questions that has been asked to them for the

purpose of evaluating the influence of factors on switching behaviour. This will add

33

more reliability to results of this research. The questionnaires were emailed to 100

respondents in Bangalore but out of 80, only 60 of them responded. Hence, 60

questionnaires are used for the analysis.

3.6 Data Collection

There are mainly two types of data: primary data and secondary data. The primary data

can be collected through various methods like personal interviews, questionnaires and

direct observations etc. Thus, researchers may obtain the original data from the

respondents. Furthermore, the primary data can provide the current and realistic views

about the research questions. The secondary data is mainly gathered from internal

company information, government agents, books, journals and trade associations. This

type of data is easily available and accessible. In addition to that, secondary data can

aid primary data collection and make the results more specific and reliable.

Both primary data and secondary data are used for this study. Primary data will be

collected using questionnaire which is distributed electronically to respondents via

internet in Bangalore, India. The respondents are mobile phone users, with age ranging

from 18-35 years old. As Garbarino and Johnson (1999) asserted, customers’

evaluation of a supplier’s or service provider’s offerings would shape their behaviours.

Hence, this questionnaire aims to assess the most prominent perception with regards

to relationship; commitment towards the service providers (Moorman et al, 1992).

Satisfaction and payment equity are important factors in affecting customer’s

evaluation towards the service provider’s offering and hence should be included

(Bolton and Lemon, 1999).

Questionnaires method is chosen for this research because it has advantages over

other methods of data collection. Although the advantages can vary according to the

methods with which they are being compared, the primary advantages of using

questionnaire as data collection method are efficiency, large sample size, cheap costs,

assured confidentiality, sampling of many topics, and having a permanent original copy

of the responses (Downs and Adrian, 2004).

Questionnaire is one of the most popular used research techniques in social research.

The main part in questionnaire is question. First type is open questions, which ‘leave

the respondent to decide the wording of the answer, the length of the answer and the

kind of matters to be raised in the answer’ (Denscombe, 2004:155). Another type is

close question, which needs respondent to select answers from a range of options

designed on the questionnaire. This question may generate a number of quantitative

34

data. Thus, researchers should know well about what kind of quantitative data will be

collected and what statistic procedures will be adopted in order to avoid generating

pool analysis. Figure 3.1 shows the different types of questionnaire based on how they

are administered

Figure 3.1: Types of Questionnaire

Source: (Saunders, et al., 2009)

Types of questionnaire are also classified basing on the structure of the questions

asked. Normally, they are divided into several classifications; such as free-response

questions, dichotomous questions, multiple-choice questions (Cooper and Schindler,

2006). Dichotomous questions are questions which divide the respondents into two or

more groups according to the attributes, such as male and female, different age

groups, education group, and others. Multiple choice questions would allow the

respondents to have more choices and select the one that fits within a possible frame

of answers. These answers are usually designed by the researcher by using scoring

method such as 1 to 5 or giving options, etc. Open-ended questions are meant to

gather unstructured responses from the respondents.

The type of questionnaire used in this research was self administered questionnaire.

This was that type of questionnaire where there was no guidance to the respondents

by the researcher (Saunders et al., 2007). The questionnaire has closed ended

questions and for the main research questions, 5-point likert scale has been used. It is

frequently used variation of the summated rating scale which consists of statements

that express either a favourable or unfavourable attitude towards the object of interest

(Cooper and Schindler, 2006). The scale presents a set of statements where

respondents are asked to express their level of agreement or disagreement on five-

35

point scale. Each degree of agreement or disagreement was provided 5 options

ranging from strongly disagree to strongly agree.

The questions has been designed on the basis of the literature to assess the major

factors influencing switching behaviour and are divided into 23 questions in total and

the questionnaire has been divided into two sections.

Section 1 has 4 questions which deal with the behavioural and demographic

characteristics of the respondents. The questions are on the gender, age group,

educational level, and occupation of the respondents.

Section 2 has 19 questions which include one general question on switching behaviour

and eighteen questions on that were classified on the basis of seven factors that were

identified as the major factors in influencing consumer switching behaviour in cellular

services. The seven factors on which questions are divided include service quality,

price, switching costs, change in technology, advertising, social influence, and

involuntary switching.

Secondary data was also used to achieve the objectives of this research and it has

been collected from various textbooks and journals related to marketing, customer

relationship management, and customer behaviours, as well as previous relevant

researches.

3.7 Data Analysis

This study have utilised Microsoft word to design the questionnaire and SPSS 19 to

analysis the primary data. Microsoft word is first used to design the questionnaire, and

then SPSS 19 to generate tables and diagrams from the findings. The data from the

respondents has been coded under several categories such as ‘price’, ‘service quality’,

‘switching costs’ etc. Furthermore, the findings will be statistically analysed to draw a

conclusion using SPSS 19. Firstly, the descriptive statistics has been used to describe

the basic features of the data in a study and to provide simple summaries about the

sample and the measures and also to provide quantitative analysis of collected data.

Then, regression analysis and correlation analysis has been used to investigate the

statistical significance and relationships between the variables (independent and

dependent variables) that were designed to test the hypotheses and to achieve the

objectives of the research which is to evaluate the factors influencing consumers

switching behaviour in cellular services..

36

3.8 Limitations

It is accepted that the focus on mobile phone services users in Bangalore, India would

impose limitations on this research’s ability to arrive at conclusive findings in relation to

the switching behaviours of mobile phone users in general. Given the time available to

finish this study and the geographical as well as funding limitations, biases may occur

in the favour of generalising the research findings.

In order to counter the limitations with regards to the focus of this study, the

respondents were asked in details when they fill up the questionnaire. The variables

used in this research are service good variables (service by mobile phone service

providers). This can bring limitations to the study as it is possible that different type of

services has many different ways in retaining customers and customers of different

type of services will possess different customer behaviours.

Due to the time constraint and access availability, the sample size of this study is also

limited. Having more respondents for the primary data would increase the validity and

reliability of the findings. In terms of data, it is acknowledged that both qualitative and

quantitative data have their own strengths and weaknesses.

3.9 Chapter summary

The research methods that have greater relevance to the topic of this study has been

highlighted and discussed in order to achieve the objectives more evidently. In this

chapter, the theoretical concepts and studies of known researchers such as Saunders

(2007), Descombe (2003, 2004), Bolton and Lemon (1999), etc has been considered

which has relevance with this research. It can help to select appropriate research

method for this research and gain more reliability. The main focus of this chapter was

aimed to provide the clear idea about the methods adopted in this research by

illuminating the reasons for adopting the respective methods. The discussion on

appropriate research methods has been made for the purpose of gaining the valuable

insight for the chosen methods in order to achieve the objectives of this research. It

includes the discussion on research philosophy, research methods, sampling, data

collection, data analysis and limitations of this research. Furthermore, the next chapter

will discuss key findings identified from the data collected and then analysed using

statistical tests. Primary data in this study will be collected by the means of

questionnaires, which are expected to be 60.

37

4. FINDINGS AND ANALYSIS

4.1 Introduction

After collecting information from the data i.e. primary and the secondary data, the

next step is to analyse the data. In this chapter, firstly the findings from the collected

will be drawn and explained in terms of tables and graphs representing frequency

and percentage of respondents by using SPSS for the purpose of bringing the ease

in representation. Then the analysis of the collected data will be done by using

descriptive statistics, regression analysis and correlation analysis. Then the

Hypotheses testing and discussion has been given. The results will highlight, if there

is any effects of service quality, price, switching costs, change in technology,

advertising, social influence, and involuntary switching, with consumers switching

behaviour. The subsequent results gained from this research will be used to underpin

the research questions in order to achieve the objectives of this research.

The total number of questionnaires sent out to mobile phone users in Bangalore city

was 100 and only 60 has been received completely which can be interpreted. This

indicates that the response rate is only 60 percent. If response rate is taken into

consideration, high response rate points to the importance of what a researcher is

doing (Gillham, 2000).

4.2 Findings of the data

The findings of the data collected have been divided into two sections. The first section

is related to the demographics of the respondents. The second section is related to the

respondents’ opinion about the factors which have/can influence their decision to

switch the cellular service provider.

38

4.2.1 Section 1

4.2.1.1 Demographics

As according to Block & Roering (1976), demographic characteristics have been

regarded as a basis for understanding customer characteristics and behaviour in the

marketing area. Therefore, the following questions on demographics of respondents

have been designed in order to understand the role of particular demographics in

switching behaviour and to satisfy the aim of this research.

4.2.1.1.1 Gender

This question was about the gender of the respondents. The table 4.1 and the graph

below show the finding of this question.

What is your gender?

Frequency Percent

Valid

Percent Cumulative Percent

Male 46 76.7 76.7 76.7

Female 14 23.3 23.3 100.0

Total 60 100.0 100.0

Table 4.1: Gender

Chart 4.1: Gender

Noel (2009) indicates that, consumers with different gender exhibit different behaviour

in the same situation and they also have different spending powers. For example, 25%

of women in United States are earning more than others and can spend more. Hence,

76.70%

23.30% 0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

Male Female

Gender

39

it becomes important to understand the forces that influence switching behaviour of

both genders i.e. male and female. The findings of this question on gender shows that,

46 respondents were male which makes 76.7% and 14 respondents were female

making 23.3% of the total respondents.

4.2.1.1.2 Age group

The second question in the questionnaire was to know the age group of respondents.

The table 4.2 and chart 4.2 below shows the findings of this question.

Table 4.2: Age group

Chart 4.2: Age group

Age group is plays a very important role in determining the consumers switching

behaviour. The consumers with different age groups have different needs and interests

and also different buying powers (Noel, 2009). The young consumers are more

frequent mobile phone users than elderly people and they also frequently switch their

cellular service providers because they are always willing to experiment new services

38.30%

33.30%

28.30%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

18-24 Years 25-29 Years 30-35 Years

Age group

What is your age group?

Frequency Percent

Valid

Percent

Cumulative

Percent

18-24 Years 23 38.3 38.3 38.3

25-29 Years 20 33.3 33.3 71.7

30-35 Years 17 28.3 28.3 100.0

Total 60 100.0 100.0

40

(Ericson, 2004). Hence, the forces that influence young consumers are needed to be

understood as the objective of this research is evaluate the factors influencing young

adults to switch cellular service providers. The findings of this question on age group

shows that, it was found that majority of respondents belong to the age group of 18-24

years i.e. 23 respondents which make 38.30% of the total respondents. Whereas the

respondents with the age group of 25-29 were 20 making 33.30% of the total

respondents. And the respondents with the age group of 30-35 were 17 making

28.30% of the whole sample size.

4.2.1.1.3 Occupation

The third question in the questionnaire was to enquire about the occupation of the

respondents. The table 4.3 and chart 4.3 shows the findings of this question.

What is your occupation?

Frequency Percent Valid Percent

Cumulative

Percent

Student 22 36.7 36.7 36.7

Professional 18 30.0 30.0 66.7

Self-employed 6 10.0 10.0 76.7

Labourer 10 16.7 16.7 93.3

Unemployed 4 6.7 6.7 100.0

Total 60 100.0 100.0

Table 4.3: Occupation

Chart 4.3: Occupation

36.70%

30.00%

10.00%

16.70%

6.70% 0.00% 5.00%

10.00% 15.00% 20.00% 25.00% 30.00% 35.00% 40.00%

Occupation

41

The consumers with different occupation have different level of income and so as the

spending powers and they make their buying decisions on the basis of their status

(Noel, 2009). Hence, this question has been designed to understand the behaviour

consumers with different occupations in order to enquire which factors influence them

to switch cellular service providers. The findings of this question shows that, the

respondents participated in this research were from different occupational

backgrounds. It has been found that majority of respondents were students 22

respondents which makes 36.70% of the total respondents. Whereas, 18 respondents

were professionals and 10 were labourers making 30% and 16.70% respectively.

Remaining 6 were self-employed and 4 were unemployed, making 10% and 6.70% of

the total respondents.

4.2.1.1.4 Educational level

The fourth question in the questionnaire was to enquire the educational level of the

respondents. The table 4.4 and 4.4 shows findings of this question.

What is the highest level of education level of education you have

achieved?

Frequency Percent

Valid

Percent

Cumulative

Percent

Primary education 6 10.0 10.0 10.0

High school education 11 18.3 18.3 28.3

Diploma/certification 10 16.7 16.7 45.0

Bachelor degree 13 21.7 21.7 66.7

Post-graduate degree 20 33.3 33.3 100.0

Total 60 100.0 100.0

Table 4.4: Educational level

42

Chart 4.4: Educational level

Consumers with different educational levels perceive services differently and also have

different level of information and knowledge about the products and services due to the

trend in schools, colleges, universities, etc ( Noel, 2009). Different factors influence the

decision of consumers with different educational level to switch cellular service provider

and therefore, this question is designed to understand those factors. The findings of

this question shows that, the respondents have achieved different educational levels

i.e. 20 respondents were post-graduates making 33.30% of the total respondents and

13 were bachelor degree holders making 21.70% of the total. Whereas, 11

respondents has achieved high school education which makes 18.30% and 10 and 6

has achieved diploma/certification and primary education making 16.70% and 10% of

the total sample respectively.

10%

18.30% 16.70% 21.70%

33.30%

0% 5%

10% 15% 20% 25% 30% 35%

Educational Level

43

4.2.2 Section 2

4.2.2.1 Likeliness of switching service provider

The fifth question in the questionnaire was to find out the likeliness of consumers to

switch from current cellular service provider to another. This question helps to enquire

what percentage of respondents are likely to switch their cellular service provider and

the reasons for switching which has been asked in the following question in order to

satisfy the aim and objectives of this research. The finding of this question is shown in

the table 4.5 and chart 4.5.

Are you likely to switch from current cellular service provider to

another?

Frequency Percent

Valid

Percent Cumulative Percent

Very Unlikely

Unlikely

Neutral

Likely

Very Likely

11

12

5

19

13

18.3

20

8.3

31.7

21.7

18.3

20

8.3

31.7

21.7

18.3

38.3

46.7

78.3

100.0

Total 60 100.0 100.0

Table 4.5: Likeliness of switching service provider

Chart 4.5: Likeliness of switching service provider.

18.30% 20%

8.30%

31.70%

21.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Very Unlikely

Unlikely Neutral Likely Very Likely

Likeliness of switching service provider

44

The findings of this question shows that, 19 respondents are likely to switch which

makes 31.70% and 13 are very likely which makes 21.70% of the total respondents.

Whereas, 12 respondents are unlikely and 11 are very unlikely making 20% and

18.30% respectively and remaining 5 respondents are neutral, which makes 8.30% of

the total respondents. This question was aimed at understanding the rate of

respondents likely to switch their cellular services providers and the situations which is

influencing them to switch. Understanding the situations and factors can helps to

cellular service providers to reduce the likely of consumers who are willing to switch

and to attract consumer of competitors who are about to switch. This question was also

aimed at satisfying the third objective of this research which is to investigate the

likeliness of respondents to switch from current cellular service provider to another.

However, the measures as to how the cellular service providers can prevent or reduce

the rate of likeliness of the switching has been tested and discussed in the analysis

part of this chapter.

45

4.2.2.2 Service quality

It was indicated that, improving service quality satisfies customers and retains their

loyalty and the customers with negative service experience may consider switching

their service providers (Lee and Murphy, 2005). Therefore, in order to determine the

effect of service quality on consumers’ switching behaviour, following questions relating

to service quality has been designed to address the research objectives.

4.2.2.2.1 (SQ1): Customer service

The sixth question was to find out the level of customer service provided by the current

cellular service provider to respondents. The finding of this question is shown in the

table 4.6 and chart 4.6.

The level of customer service provided by the current cellular service

provider is good.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly disagree 13 21.7 21.7 21.7

Disagree 30 50.0 50.0 71.7

Neutral 4 6.7 6.7 78.3

Agree 10 16.7 16.7 95.0

Strongly agree 3 5.0 5.0 100.0

Total 60 100.0 100.0

Table 4.6: Level of customer service

Chart 4.6: Level of customer service

21.70%

50%

6.70% 16.70%

5% 0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Strngly disagree

Disagree Neutral Agree Strongly agree

Level of customer service

46

The importance of customer service cannot be underestimated. It requires constant

effort to maintain good relations with the customers of the company. It is a critical

element in all growth and retention strategies (Gershon, 2009). Therefore, this question

helps to understand the impact of customer service on switching behaviour. The

findings of this question shows that, from the whole sample size, 30 respondents i.e.

50% disagree with the statement and 13 respondents strongly disagree which makes

21.70% of the total respondents. Whereas, 10 respondents agree with the statement

and 3 respondents strongly agree making 16.70% and 5% respectively. Remaining 4

respondents are neutral with the statement which makes 6.70% of the total

respondents. It implies that majority of consumers are towards the negative side when

it comes the customer service provided by their cellular service providers which means

that consumers service is also influencing the likeliness of consumers switching

behaviour.

4.2.2.2.2 (SQ2): Network coverage

The seventh question in the questionnaire was to enquire about the network coverage

of the current cellular service provider of the respondents. The finding of this question

is shown in the table 4.7 and chart 4.7.

The network coverage of the current cellular service provider is

good.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly disagree 18 30.0 30.0 30.0

Disagree 13 21.7 21.7 51.7

Neutral 8 13.3 13.3 65.0

Agree 12 20.0 20.0 85.0

Strongly agree 9 15.0 15.0 100.0

Total 60 100.0 100.0

Table 4.7: network coverage

47

Chart 4.7: Network coverage

The major feature of mobile telecommunications is its coverage. Consumers evaluate

network coverage of the cellular service providers differently according to the utility

they drive from completed calls (Madden, 2003). The impact of network coverage on

consumers switching behaviour can be evaluated through this question. The findings of

this question shows that, 18 respondents strongly disagree to the above statement

about network coverage which makes 30% of the total respondents and 13

respondents disagree making 21.70% of the total sample. And 12 respondents agree

and 9 respondents strongly agree with the statement which makes 21% and 15% of the

total respondents respectively. The remaining 8 respondents are neutral with the

statement making 13.30% of the total respondents. The finding of the above question

relating to network coverage of the cellular service provider is based on achieving the

objectives of this research. This implies that most of the respondents expressed

negative opinion when it comes to network coverage and therefore may be likely to

switch their cellular service provider.

30.00%

21.70%

13.30%

20%

15.00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Network coverage

48

4.2.2.2.3 (SQ3): Network problems

The eighth question in the questionnaire was to enquire about the network problems

with the current cellular service provider. The finding of this question is given in the

table 4.8 and chart 4.8.

There are frequent network problems with the services of the current

cellular service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly disagree 8 13.3 13.3 13.3

Disagree 15 25.0 25.0 38.3

Neutral 5 8.3 8.3 46.7

Agree 20 33.3 33.3 80.0

Strongly agree 12 20.0 20.0 100.0

Total 60 100.0 100.0

Table 4.8: Network problems

Chart 4.8: Network problems

Frequent network problems refer to weak connectivity and frequent disconnections in

the services provided by cellular service providers (Avresky and Diaz, 2009). This

question helps to evaluate the effect of network problems on switching behaviour of

consumers. The findings of this question shows that, 20 respondents agree and 12

respondents strongly agree to the above statement about network problems which

makes 33.3% and 20% of the total respondents, whereas, 15 respondents disagree

and 8 respondents strongly disagree to the statement making 25% and 13.30% of the

13.30%

25%

8.30%

33.30%

20%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Network problems

49

total respondents respectively. Remaining 5 respondents are neutral to this statement

about network problems making 8.30% of the total respondents. It implies that the

majority of respondents have experienced frequent network problems and therefore

this might be one of the factors which is influencing likeliness of respondents to switch

their cellular service provider.

4.2.2.2.4 (SQ4): Call quality

The ninth question was to enquire about the call quality of the current cellular service

provider of the respondents. The finding of this question is given in the table 4.9 and

chart 4.9.

The call quality provided by the current cellular service provider is

good.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly disagree 14 23.3 23.3 23.3

Disagree 17 28.3 28.3 51.7

Neutral 4 6.7 6.7 58.3

Agree 11 18.3 18.3 76.7

Strongly disagree 4 6.7 6.7 100.0

Total 60 100.0 100.0

Table 4.9: Call quality

Chart 4.9: Call quality

The cellular service providers should pay greater attention on call quality because it

is the one of the major factors driving customer satisfaction (Irizzary, 2007).

23.30%

28.30%

6.70%

18.30%

6.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Strongly disagree

Disagree Neutral Agree Stongly agree

Call quality

50

Therefore, in order to determine the impact of call quality on consumer switching

behaviour, this question has been designed. The findings of this question show that,

17 respondents disagree with the above statement about call quality which makes

28% of the total respondents and 14 respondents strongly disagree. And, 11

respondents agree and 4 respondents strongly agree with the statement making

18.30% and 6.70% of the total respondents. Remaining 4 respondents are neutral to

the statement making 6.70% of the total respondents. This implies that, as the

cellular service providers are not providing good call quality and hence majority of

respondents are dissatisfied and also are likely to switch.

4.2.2.2.5 (SQ5): Billing error

The tenth question was to enquire about the billing errors from the side of the current

cellular service provider of the respondents. The finding of this question is given in the

table 4.10 and chart 4.10.

There is/was error/s in billing from the side of current cellular

service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly disagree 8 13.3 13.3 13.3

Disagree 16 26.7 26.7 40.0

Neutral 9 15.0 15.0 63.3

Agree 15 25.0 25.0 88.3

Strongly agree 12 20.0 20.0 100.0

Total 60 100.0 100.0

Table 4.10: Error in billing

Chart 4.10: Error in billing

13%

26.70%

15%

25%

20.00%

0%

5%

10%

15%

20%

25%

30%

Strongly disagree

Disagree Neutral Agree Strongly agree

Error/s in billing

51

Errors in billing refer to multiple charges for SMS, value added services, and others,

which will cause financial distress to the consumers and force them to switch their

cellular service provider (Ezenezi, 2011). This question has been designed to evaluate

the effect of billing errors on switching behaviour. The findings of this question shows

that, 15 respondents agree with the above statement about errors in billing which

makes 26.70% of the total respondents and 12 respondents strongly agree that there

is/was error/s from the side of their current cellular service provider making 20% of the

total respondents, whereas 16 respondents disagree and 8 respondents strongly

disagree to the statement making 26.70% and 13% of the total respondents

respectively. Remaining 9 respondents were neutral with the above statement making

15% of the total respondents. It implies that the respondents also have the billing

problems which may be causing due the ignorance or improper services of the current

cellular service providers of the dissatisfied respondents which can be reason for

likeliness of switching.

52

4.2.2.3 Price

As according to Keaveney (1995), more than half of the customers switched because

of the poor price perceptions and suggested that unfavourable price perceptions

directly influence customers’ intentions to switch. Price includes call rates, service

charges, etc (Keaveney, 1995). Therefore, following questions relating to price will help

to study the impact of price factor in influencing the consumer switching behaviour in

cellular services in order to achieve the objectives of this research.

4.2.2.3.1 (P1): Tariffs

The eleventh question was to enquire about the tariffs offered by the current cellular

service provider of the respondents. The finding of this question has been shown in the

table 4.11 and graph 4.11.

The current cellular service provider offers suitable tariffs for different

age groups.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 9 15.0 15.0 15.0

Disagree 16 26.7 26.7 41.7

Neutral 4 6.7 6.7 48.3

Agree 19 31.7 31.7 30.0

Strongly Agree 12 20.0 20.0 100.0

Total 60 100.0 100.0

Table 4.11: Tariffs

Chart 4.11: Tariffs

15%

26.70%

6.70%

31.70%

20%

0%

5%

10%

15%

20%

25%

30%

35%

Strongly disagree

Disagree Neutral Agree Strongly agree

Tariffs

53

The findings of this question shows that, 19 respondents agree and 12 respondents

strongly agree to the statement that their current cellular service provider offers suitable

tariffs for different age groups which makes 31.70% and 20% of the total respondents

respectively and whereas, the 16 respondents and 9 respondents disagree and

strongly disagree with the statement which makes 26% and 15% of the total

respondents. Remaining 4 respondents are neutral with the statement making 6.70% of

the total respondents. It implies that majority of the respondent have expressed their

opinion positively for this question. However, on the other hand some of the

respondents expressed their opinion negatively and it may the reason which can lead

to their switching behaviour.

4.2.2.3.2 (P2): Call rates

The twelfth question in the questionnaire was to enquire about the call rates of the

current cellular service provider of respondents. The finding of this question has shown

in the table 4.12 and chart 4.12.

The call rates offered by the current cellular service provider are

high.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 8 13.3 13.3 13.3

Disagree 10 16.7 16.7 30.0

Neutral 4 6.7 6.7 36.7

Agree 22 36.7 36.7 73.3

Strongly Agree 16 26.7 26.7 100.0

Total 60 100.0 100.0

Table 4.12: Call rates

54

Chart 4.12: Call rates

Call rates are the charges incurred to make calls. This question helps to evaluate the

effect of call rates on switching behaviour. The findings of this question shows that, 22

respondents agree and 16 respondents strongly agree to the statement that their

current cellular service provider offers high call rates which makes 36.7% and 26.7% of

the total respondents, whereas 10 respondents disagree and 8 respondents strongly

disagree with the statement, making 16.7% and 13.3% of the total respondents.

Remaining 4 respondents are neutral with the statement, making 6.7% of the total

respondents. This implies that call rates are the main reason responsible for switching

behaviour of the respondents as the majority of respondents expressed their opinion

negative relating to call rates which means that the call rates are unfavourable and

causing the likeliness of switching.

13.30% 16.70%

6.70%

36.70%

26.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Call rates

55

4.2.2.3.3 (P3): Value-added services

The thirteenth question in the questionnaire was to enquire about cost of value-added

services offered by the current cellular service provider of the respondents. The finding

of this question is shown in the table 4.13 and chart 4.13.

The value-added services offered by the current cellular service

provider are costly.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 10 16.7 16.7 16.7

Disagree 3 5.0 5.0 21.7

Neutral 14 23.3 23.3 45.0

Agree 17 28.3 28.3 73.3

Strongly Agree 16 26.7 26.7 100.0

Total 60 100.0 100.0

Table 4.13: Value-added services

Chart 4.13: Value-added services

Bohlin, et al. (2004) indicate that, value added services can become an important

driving force in increasing a customers’ positive behaviour. It has some lock-in effects

and the service providers use value added services as a differentiator in order to

compete and retain customers. This question has been designed to evaluate the effect

of value-added services on switching behaviour. The findings of this question show

that, 17 respondents agree and 16 respondents strongly agree to the statement that

the value-added services offered by the current cellular service provider of the

respondents are costly which makes 28.3% and 26.7% of the total respondents

whereas, 10 respondents strongly disagree and 3 respondents disagree making 16.7%

16.70%

5%

23.30%

28.30% 26.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Value added services

56

and 5% of the total respondents. Remaining 14 respondents are neutral to the

statement which makes 23.3% of the total respondents. The finding of this question

implies that the majority of the respondents think that the value added services are high

and it is also the reason responsible for switching behaviour of the respondents.

4.2.2.3.4 (P4): High service charges

The fourteenth question in the questionnaire was to enquire about the service charges

on recharges/top-ups. The finding of this question is shown in the table 4.14 and chart

4.14.

The current cellular service provider charges high service

charges on top-ups/recharges.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 7 11.7 11.7 11.7

Disagree 10 16.7 16.7 28.3

Neutral 12 20.0 20.0 48.3

Agree 18 30.0 30.0 78.3

Strongly Agree 13 21.7 21.7 100.0

Total 60 100.0 100.0

Table 4.14: Charges on top-ups/recharges

Chart 4.14: Charges on top-ups/recharges

The findings of this question shows that, 18 respondents agree and 13 respondents

strongly agree to the statement that their current cellular service provider charges high

11.70%

16.70%

20%

30%

21.00%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Charges on recharges/top-ups

57

service charges on recharges/top-ups which makes 30% and 21.7% of the total

respondents whereas, 10 respondents disagree and 7 respondents strongly disagree

to the statement making 16.7% and 11.7% of the total respondents. Remaining 12

respondents are neutral with the statement making 20% of the total respondents. It

implies that the majority of respondents are dissatisfied with the service charges that

the cellular service providers are charging on top-ups/recharges and therefore

influenced to switch their cellular service provider.

58

4.2.2.4 Switching costs

4.2.2.4.1 (SC1): Switching time

The fifteenth question in the questionnaire was to enquire the time it will take for the

respondents to switch to new cellular service provider. The finding of this question is

shown in the table 4.15 and chart 4.15.

It will take too much time to switch to new cellular service

provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 16 26.7 26.7 26.7

Disagree 15 25.0 25.0 51.7

Neutral 6 10.0 10.0 61.7

Agree 19 6.7 31.7 93.3

Strongly Agree 4 31.7 6.7 100.0

Total 60 100.0 100.0

Table 4.15: Switching time

Chart 4.15: Switching time

The findings of this question shows that, 16 respondents strongly disagree and 15

respondents disagree with the statement that switch cellular service provider will take

lot of time making 26.7% and 25% of the total respondents respectively whereas, 19

respondents agree and 4 respondents strongly agree with the statement making 31.7%

and 6.7% of the total respondents respectively. Remaining 6 respondents are neutral

with the statement which makes 10% of the total respondents. Therefore, it implies that

the majority respondents feels that the time it will take to switch cellular service

26.70% 25%

10%

31.70%

6.70% 0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Switching time

59

providers is less which also implies that this factor is also influencing the likeliness of

consumers switching behaviour.

4.2.2.4.2 (SC2): Switching cost

The sixteenth question was to enquire about the cost it will take for the respondents to

switch to new cellular service provider. The finding of this question is shown in the table

4.16 and chart 4.16.

It will cost lot of money to switch to new cellular service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 20 33.3 33.3 33.3

Disagree 17 28.3 28.3 61.7

Neutral 6 10.0 10.0 71.7

Agree 5 8.3 8.3 80.0

Strongly Agree 12 20.0 20.0 100.0

Total 60 100.0 100.0

Table 4.16: Switching costs

Chart 4.16: Switching cost

The findings of this question shows that, 20 respondents strongly disagree and 17

respondents disagree with statement that it will cost lot of money to switch to new

cellular service provider which makes 38.3% and 28.3% of the total respondents

respectively whereas, 12 respondents strongly agree and 5 respondents agree with the

statement making 20% and 8.3% of the total respondents respectively. Remaining 6

respondents are neutral with the statement making 10% of the total respondents. It

implies that, the majority of respondents do not think it will cost more money to switch

their cellular service provider. Therefore, the cost in terms of money is also influencing

33.30%

28.30%

10% 8.30%

20%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Switching cost

60

the consumers to switch service providers, because they can switching their cellular

service providers without worrying about cost, as it is very low and affordable.

4.2.2.5 Change in technology

4.2.2.5.1 (CIT1): Service upgrade

The seventeenth question was to enquire about the upgrades or advancements in the

services of the current cellular service provider to the respondents. The finding of this

question is shown in the table 4.17 and chart 4.17.

The current cellular service provider continuously upgrade it services

according to trend. (Eg. 3G mobile service)

Frequency Percent Valid Percent Cumulative Percent

Strongly Disagree 9 15.0 15.0 15.0

Disagree 13 21.7 21.7 36.7

Neutral 7 11.7 11.7 48.3

Agree 17 28.3 28.3 76.7

Strongly Agree 14 23.3 23.3 100.0

Total 60 100.0 100.0

Table 4.17: Service upgrade

Chart 4.17: Service upgrade

The findings of this question shows that, 17 respondents agree and 14 respondents

strongly agree with statement that their current cellular service provider continuously

upgrade its services according to the trend which makes 28.3% and 23.3% of the total

respondents whereas, 13 respondents disagree and 9 respondents strongly disagree

with the statement making 21.7% and 15% of the total respondents. Remaining 7

respondents are neutral with the statement making 11.7% of the total respondents. It

15%

21.70%

11.70%

28.30%

23.30%

0%

5%

10%

15%

20%

25%

30%

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Service upgrade

61

implies that, majority of respondents feel that their cellular service providers upgrade it

services whereas, some of the respondents do not feel so and are influenced to switch

their cellular service providers. Hence, it can be said that failure to upgrade services is

also influencing switching behaviour as sindhu (2005) indicates that providing new

service will retain and gain consumer loyalty.

4.2.2.5.2 (CIT2): New devices with services

The eighteenth question was to enquire that whether or not the current cellular service

provider of the respondents offers advanced technology devices with their services.

The finding of this question is shown in the table 4.18 and chart 4.18.

The current cellular service provider offers new technology and trendy

phones with its services enabling the consumers to use wide range of

applications on the phone through the services of cellular service

provider. (Eg. use of skype on iPhone4)

Frequency Percent

Valid

Percent Cumulative Percent

Strongly Disagree 20 33.3 33.3 33.3

Disagree 18 30.0 30.0 63.3

Neutral 5 8.3 8.3 71.7

Agree 10 16.7 16.7 88.3

Strongly Agree 7 11.7 11.7 100.0

Total 60 100.0 100.0

Table 4.18: New devices with services

Chart 4.18: New devices with services

33.30% 30%

8.30%

16.70%

11.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly Disagree

Disagree Neutral Agree StronglY Agree

New devices with services

62

The findings of this question shows that, 20 respondents strongly disagree and 18

respondents disagree with the above statement of new devices with services which

makes 33.3% and 30% of the total respondents whereas, 10 respondents agree and 7

respondents strongly agree with the statement making 16.7% and 11.7% of the total

respondents. Remaining 5 respondents are neutral with the statement making 8.3% of

the total respondents. It implies that, majority of respondents’ think that their cellular

service provider offers latest cellular devices and hence it may be the reason by which

the respondents are likely to switch their cellular service providers, as Sindhu (2005)

indicates that, cellular service providers who do not offer latest equipments with its

services are likely to lose its consumers and also the market share.

63

4.2.2.6 Advertising

4.2.6.1 (A1): Advertisements

The nineteenth question was to enquire that whether or not the advertisements are

encouraging the respondents to switch their current cellular service provider. The

finding of this question is shown in the table 4.19 and chart 4.19.

The advertisements of the competitors are encouraging me to switch from

current cellular service provider.

Frequency Percent Valid Percent Cumulative Percent

Strongly Disagree 11 18.3 18.3 18.3

Disagree 11 18.3 18.3 36.7

Neutral 3 5.0 5.0 41.7

Agree 24 40.0 40.0 81.7

Strongly Agree 11 18.3 18.3 100.0

Total 60 100.0 100.0

Table 4.19: Advertisements

Chart 4.19: Advertisements

Advertisements tries to influence consumers purchase decisions and also intended to

switch loyalties of consumers of the competitors’ (Zou and Fu, 2011). This question

helps to evaluate the effect of advertisements on switching behaviour of respondents.

The findings of this question shows that, 24 respondents agree and 11 respondents

strongly agree with the statement that advertisements of the competitors are

encouraging them to switch current cellular service provider, which makes 40% and

18.3% of the total respondents whereas, 11 respondents disagree and 11 respondents

18.30% 18.30%

5%

40%

18.30%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

40.00%

45.00%

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Advertisments

64

strongly disagree with the statement making 18.3% and 18.3% respectively. Remaining

3 respondents are neutral with the statement making 5% of the total respondents. It

implies that, most of the respondents feel that the competitors advertising of cellular

services is influencing the likeliness of consumers to switch from current cellular

service provider.

4.2.2.6.2 (A2): Brand ambassadors

The twentieth question was to enquire whether or not the brand ambassadors are

influencing them to switch current cellular service provider. The finding of this question

is shown in the table 4.20 and chart 4.20.

The brand ambassadors of the competitor are influencing to

switch current cellular service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 18 30.0 30.0 30.0

Disagree 7 11.7 11.7 41.7

Neutral 16 26.7 26.7 68.3

Agree 11 18.3 18.3 86.7

Strongly Agree 8 13.3 13.3 100.0

Total 60 100.0 100.0

Table 4.20: Brand ambassadors

Chart 4.20: Brand ambassadors

Companies invest in brand ambassadors for spreading positive message of the brand

or company to stimulate the behaviour of competitors’ consumers (Yeshwin, 2006).

This question helps to evaluate the effect of effect of brand ambassadors on switching

30%

11.70%

26.70%

18.30%

13.30%

0%

5%

10%

15%

20%

25%

30%

35%

Strongly Disagree

Disagree Neutral Agree Strongly Agree

Brand ambassadors

65

behaviour of respondents. The findings of this question show that, 18 respondents

strongly disagree and 7 respondents disagree to the statement that the brand

ambassadors of the competitors are influencing them to switch current cellular service

provider, which makes 30% and 11.70% of the total respondents whereas, 11

respondents agree and 8 percent respondents strongly agree with the statement

making 18.3% and 13.3% of the total respondents respectively. Remaining 16

respondents are neutral with the statement making 26.7% of the respondents. It implies

that the brand ambassadors are also influencing the likeliness of respondents to switch

cellular service provider, as some of the brand ambassadors of competitors may be the

idols of some of the respondents and hence they are influenced to switch. However,

majority of respondents expressed negative opinion that brand ambassadors do not

influence them to switch.

66

4.2.3.7 Social influence

4.2.2.7.1 (SI): Social groups

The twenty first question was to enquire the influence of the respondents’ family and

friends to switch current cellular service provider. The finding of this question is shown

in the table 4.21 and chart 4.21.

My family and friends are influencing me to switch current

cellular service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 8 13.3 13.3 13.3

Disagree 12 20.0 20.0 33.3

Neutral 10 16.7 16.7 50.0

Agree 17 28.3 28.3 78.3

Strongly Agree 13 21.7 21.7 100.0

Total 60 100.0 100.0

Table 4.21: Social groups

Chart 4.21: Social groups

Dasgupta et al. (2008) indicates that, there is a relationship between social networks

and switching behaviour in mobile telecommunications and according to Wangenheim

(2005), the consumers express their disappointment or dissatisfaction in their social

group about a dropped service provider. This question helps to evaluate the effect of

social groups on switching behaviour of respondents. The findings of this question

show that, 17 respondents agree and 13 respondents strongly agree to the statement

13%

20% 16.70%

28.30%

21.70%

0%

5%

10%

15%

20%

25%

30%

Strongly disagree

Disagree Neutral Agree Strongly agree

Social groups

67

that their family and friends are influencing them to switch current cellular service

provider, which makes 28.3% and 21.7% of the total respondents respectively

whereas, 12 respondents disagree and 8 respondents strongly disagree to the

statement making 20% and 13% of the total respondents respectively. Remaining 10

respondents are neutral with the statement making 16.7% of the total respondents.

4.2.2.8 Involuntary switching

4.2.2.8.1 (IS1): Geographic location

The twenty second question in the questionnaire was to enquire about the geographic

location in determining switching behaviour. The finding of this question is shown the

table 4.22 and chart 4.22.

I am likely to switch because I am/may be moving outside the

geographic location where the services of current cellular

service provider are not available.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 16 26.7 26.7 26.7

Disagree 17 28.3 28.3 55.0

Neutral 8 13.3 13.3 68.3

Agree 10 16.7 16.7 85.0

Strongly Agree 9 15.0 15.0 100.0

Total 60 100.0 100.0

Table 4.22: Geographic location

Chart 4.22: Geographic location

26.30% 28.30%

13.30% 16.70%

15%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

Strongly disagree

Disagree Neutral Agree Strongly agree

Geographic location

68

The findings of this questions shows that, 17 respondents disagree and 16

respondents strongly disagree to the above statement about geographic location in

determining their switching behaviour, which makes 26.3% and 28.3% of the total

respondents whereas, 10 respondents agree and 9 respondents strongly agree with

the statement making 16.7% and 15% of the total respondents. Remaining 8

respondents are neutral with the statement making 13.3% of the total respondents.

Switching behaviour is caused not only with the intentions to switch but also due the

involuntary factors including relocation of geographic region of the consumers (Roos,

1999). The finding of this question helps to evaluate the effect of geographic re-location

of consumers on the firm.

4.2.2.8.2 (IS2): Acquisition

The twenty third question in the questionnaire was to enquire respondents’ likeliness of

switching due to acquisition of the current cellular service provider. The finding of this

question is shown in the table 4.23 and graph 4.23.

I am likely to switch because some other firm has

acquired/acquiring my current cellular service provider.

Frequency Percent

Valid

Percent

Cumulative

Percent

Strongly Disagree 19 31.7 31.7 31.7

Disagree 16 26.7 26.7 58.3

Neutral 6 10.0 10.0 68.3

Agree 12 20.0 20.0 88.3

Strongly Agree 7 11.7 11.7 100.0

Total 60 100.0 100.0

Table 4.23: Acquisition

69

Chart 4.23: Acquisition

As Sindhu (2005) indicate that, acquisition and mergers within the cellular industry is

one of the factors leading to involuntary switching. This question helps to assess the

effect of switching due to acquisition on the company. The findings of this questions

shows that, 19 respondents strongly disagree and 16 respondents disagree to the

above statement the they are likely to switch due to acquisition of the current cellular

service provider, which makes 31.7% and 26.7% of the total respondents whereas, 12

respondents agree and 7 respondents strongly agree with the statement making 20%

and 11.7% of the total respondents. Remaining 6 respondents are neutral with the

statement making 10% of the total respondents. It implies that, majority of respondents

do not think they are likely to switch due to acquisition of their cellular service provider.

It may be because the majority of respondents may be the subscribers of leading

cellular service providers which have no risk of acquisition. But, some of the

respondents feel that they are likely to switch due to acquisition.

31.70%

26.70%

10%

20%

11.70%

0.00%

5.00%

10.00%

15.00%

20.00%

25.00%

30.00%

35.00%

Strongly agree Agree Neutral Agree Strongly agree

Acquisition

70

4.3 Analysis

4.3.1 Descriptive statistics

Descriptive statistics are applied on 18 items related to 7 switching determinants. It is

carried out in order to find out the importance of the statements used to evaluate the

factors influencing switching behaviour in cellular service industry. The table below

shows the descriptive statistics applied on the 18 items.

Items N Mean

Factor

mean

Service quality

1. Level of customer service (S1) 60 4.12

2. Network coverage (S2) 60 4.31

3. Network problems (S3) 60 4.15

4. Call quality (S4) 60 4.23

5. Error/s in billing (S5) 60 3.56 4.07

Price

6. Suitable tariffs for different age groups

(P1)

60 4.01

7. Call rates (P2) 60 4.42

8. value-added services (P3) 60 4.31

9. Charges on top-ups/recharges (P4).

60

3.78

4.13

Switching costs

10. Time to switch (SC1) 60 3.92

11. Money to switch (SC2). 60 3.53 3.72

71

Change in technology

12. Services upgrade (CIT1) 60 4.07

13. New technology and trendy phones

with services (CIT2)

60 3.88 3.97

Advertising

14. Advertisements such as commercial

ads, leaflets, etc (A1)

60 3.98

15. Brand ambassadors (A2) 60 3.24 3.61

Social influence

16. Influence from family, friends,

colleagues etc (SI)

60 3.82 3.82

Involuntary switching

17. Geographic location (IS1). 60 3.71

18. Switching due to acquisition (IS2) 60 3.42 3.56

Valid N (list wise) 60

Table 4.24: Descriptive statistics

Looking at the results above after applying the descriptive statistics, following results

can be drawn after analysis;

All the 18 items (100%) have been scored above 3 on a scale of 5 (1 indicating

strongly disagree to 5 indicating strongly agree), indicating that the majority of

the respondents have responded their opinion favouring that the factors have

positive effect on switching behaviour.

The 7th item i.e. call rates has the highest mean of 4.42 which indicates that

respondents strongly agree to the fact that high call rates influence consumers

switching behaviour.

The 18th item (brand ambassadors) has the lowest mean of 3.24 which

indicates that the respondents were neutral (neither agree nor disagree) to the

fact that brand ambassadors influence consumers switching behaviour in

cellular service industry.

The 7 switching factors and their respective mean scores are: service quality

(4.07), price (4.13), switching costs (3.72), change in technology (3.97),

advertising (3.61), social influence (3.82), and involuntary switching (3.56).

72

4.3.2 Regression Analysis

In this section, regression analysis has been carried out on all the factors in order to

evaluate the level of relationship between the factors (independent variable) and

consumers switching behaviour (dependent variable). There are two tables i.e. the first

table shows the variables entered (independent and dependent variables) to evaluate

the level of relationship and the second table shows the values regression relationship

i.e. R, R square, adjusted R square, and standard error of the estimate.

4.3.2.1 Service quality and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Service

qualitya . Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour.

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

1 .885a .783 .021 .647

a. Predictors: (Constant), Service quality

Table 4.25: Service quality and switching behaviour

It can be observed from the regression value tables 4.25 that the value of R for the

regression relationship between service quality and switching behaviour is .885 and the

value of R square is .783. Therefore, from the value of R Square of it can be

interpreted that 78.3% of the variants of service quality can influence the switching

behaviour.

73

4.3.2.2 Price and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Pricea . Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .916a .839 .289 0.546

a. Predictors: (Constant), Price

Table 4.26: Price and switching behaviour

It can be observed from the regression value table 4.26, that the value of R for the

regression relationship between Price and switching behaviour is .916 and the value of

R square is .839. Therefore, from the value of R Square of it can be interpreted that

83.9% of the variants of price can influence the switching behaviour.

74

4.3.2.3 Switching costs and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Switching

costsa

. Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .798a .636 .043 .723

a. Predictors: (Constant), Switching Costs

Table 4.27: Switching costs and switching behaviour

From the above regression value table 4.27, it can be observed that the value of R for

the regression relationship between switching costs and switching behaviour is .798

and the value of R Square is .636. Therefore, from the value of R Square it can be

interpreted that 63.6% of the variants of switching costs can influence the switching

behaviour.

75

4.3.2.4 Change in technology and Switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Change in

Technologya

. Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .834a .695 .028 .774

a. Predictors: (Constant), Change in technology

Table 4.28: Change in technology and switching behaviour

The regression value table 4.28 indicates that, the value of R for the relationship

between change in technology and switching behaviour is .834 and the value of R

Square is .695. Therefore, from the value of R Square, it can be interpreted that the

69.5% of the variants of change in technology can influence the switching behaviour.

76

4.3.2.5 Advertising and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Advertisinga . Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .782a .611 .031 .634

a. Predictors: (Constant), Advertising

Table 4.29: Advertising and switching behaviour

The regression value table 4.29 for relationship between advertising and switching

behaviour indicates that the value of R is .782 and the value of R Square is .611. It can

be interpreted from the value of R Square that 61.1% of the variants of advertising can

influence switching behaviour.

77

4.3.2.6 Social influence and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Social

Influencea

. Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .825a .680 .016 .763

a. Predictors: (Constant), Social Influence

Table 4.30: Social influence and switching behaviour

From the above regression value table 4.30, it can be observed that the value of R for

regression relationship between social influence and switching behaviour is .825 and

the value of R Square is .68 which can be interpreted that 68% of the variants of social

influence can influence switching behaviour.

78

4.3.2.7 Involuntary switching and switching behaviour

Variables Entered/Removedb

Model

Variables

Entered

Variables

Removed Method

1 Involuntary

switchinga

. Enter

a. All requested variables entered.

b. Dependent Variable: Switching behaviour

Model Summary

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 .721a .519 .028 .851

a. Predictors: (Constant), Involuntary switching

Table 4.31: Involuntary switching and switching behaviour

From the above regression value table 4.31, it can be observed that the value of R for

the regression relationship between involuntary switching and switching behaviour is

.721 and R Square is .519. Therefore, from the value of R Square, it can be interpreted

that 51.9% of the variants of involuntary can influence switching behaviour.

79

4.3.3 Correlation analysis

In order to test whether and how strongly the pair of variables (dependent and

independent variables) are related, correlation analysis has been carried out using

SPSS 19. The independent variables are service quality, price, switching costs, change

in technology, advertising, social influence, and involuntary switching, and the

dependent variable is switching behaviour. In correlation analysis, if the value falls in

between 0.1 and 0.5, it means that there is a weak correlation between the variables

and if the value falls in between 0.5 to 1, then it indicates that there is strong

relationship between the variables. The correlations between the switching

determinants and the switching behaviour have been shown in the following table.

Correlations

(Dependent variable)

Switching behaviour

(In

de

pe

nd

en

t v

ari

ab

les)

Service quality .798

Price .854

Switching costs .662

Change in technology .761

Advertising .598

Social influence .719

Involuntary switching .551

Table 4.32: Correlation analysis

80

4.3.4 Hypothesis testing, and Discussion and implications

The hypothesis will be tested and its implications will be discussed on the basis of the

above analysis and theoretical concepts, in order to answer research questions and to

satisfy the objectives of this research. The hypotheses and the following discussion

and implications are as follows.

4.3.4.1 Service quality

4.3.4.1.1 Hypothesis testing

(H1): Service quality has a direct significant effect on consumers’ switching behaviour

behaviour in terms of switching cellular service provider.

(H0): Service quality has no direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

The above regression analysis shows that the value of R square has been proved to be

.783 which has been interpreted as 78.3% of the variations in service quality are

influencing the likeliness of switching behaviour of the respondents. The correlation

analysis has also revealed that the correlation value between the service quality and

switching behaviour is .798, which means that there is a direct and significant

relationship between service quality and switching behaviour, as the value is above

0.5, that is 0.798>0.5, hence H1 is proved and H0 is rejected.

4.3.4.1.2 Discussion and implications

After statistically analysing and testing the hypotheses relating to service quality and

switching behaviour, it is proved that the service quality has an important role in

influencing the young adults of Bangalore city to switch their cellular service provider.

As the study of Lee and Murphy (2005) point out that, improving service quality

satisfies customers and retains their loyalty, and the customers with negative service

experience consider switching their service providers. Hence, in the case of this study,

it implies that, the cellular service providers has to continuously improve and should be

able to provide high level of overall service quality in both technical and functional

terms as indicated by Groonos (1995). In this study, the variable included to assess

service quality are customer service, network coverage, frequent network problems,

billing errors, and call quality. The majority of respondents who are likely to switch are

not satisfied with the service quality of their current cellular service provider, because

they expects that service providers to compete on service quality (Paulrajan and

Rajkumar, 2011). This will make significant negative impact on the revenues, market

81

share, and corporate image of the firm. Thus, it is found to be one of significant factor

influencing the consumers switching behaviour, and therefore, the cellular service

providers should improve and provide high quality of service, and satisfy consumers’

expectations, in order to gain loyalty and new consumers that will in turn help to

increase the consumer base, profitability, market share, and enhance corporate image

of the firm. This discussion and implication is aimed at achieving the objectives of this

research and the relationship between service quality and switching behaviour has

been ranked according to its significance in Table 4.34.

82

4.3.4.2 Price

4.3.4.2.1 Hypothesis testing

(H2): Price has a direct and significant effect on consumers’ switching behaviour in

terms of switching cellular service provider.

(H0): Price has no direct and significant effect on consumers’ switching behaviour in

terms of switching cellular service provider.

The above analysis shows that the regression value of R square is .839 and has been

interpreted that 83.9% of the variations in price is influencing the likeliness of switching

behaviour of respondents and the correlation analysis has also revealed that the

correlation value between the price and switching behaviour is .854, which means that

there is a direct and significant relationship between price and switching behaviour, as

the value is above 0.5, that is 0.854>0.5, hence H2 is proved and H0 is rejected.

4.3.4.2.2 Discussion and implications

The results after statistically analysing and testing the hypothesis relating to price and

its effect on consumers switching behaviour has proved that price has the most

significant effect on influencing the switching behaviour of respondents. This implies

that the majority of respondents are affected by price, as they perceive that price

offered by current cellular service provider is higher than the competiting service

providers and therefore likely to switch to the competitors. Satish, et al. (2011) also

identified that price is the most important factor which effects consumers to switch

loyalties to competitor. As Polo and Sese (2009) asserted that, competitors will use

price to stimulate consumers switching behaviour, it implies that the cellular service

providers in Bangalore should give the most careful consideration to price including call

rates, cost of value-added services, overall tariffs, service charges on top-ups, etc,

while making pricing decisions of their services i.e. they should offer services in the

price which is favourably perceived by the consumers in order to prevent the

consumers from switching loyalties to the competitor, gain loyalty and attract new

consumers. As there is increased level of competition in Bangalore’s cellular service

market, consumers are likely to switch to the service provider who is offering service on

low prices in order to save their money. This will bear lose to firm by significantly

affecting negatively to the consumer base, market share, and corporate image. Hence,

it can be said that the lower the price of the cellular service, the lower the chances of

consumers switching their loyalties and higher the chances of attracting new

customers, gaining loyalty, and retaining lost customers (Lehtinen and Lehtinen, 1991).

The rank of price has been shown in the table 4.34 for the purpose of clearly

83

demonstrating its significance and impact on switching behaviour and achieving the

objectives of this research.

4.3.4.3 Switching costs

4.3.4.3.1 Hypothesis testing

(H1): Switching costs has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

(H0): Switching costs has no direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

The above analysis shows that the regression value of R square has been proved to be

.636 and has been interpreted that 63.6% of the variations in switching costs is

influencing the likeliness of switching behaviour of the respondents. Whereas the

correlation analysis, has also proved that the correlation between switching costs and

switching behaviour is significant as the correlation value between the two of these

factors is .662 which is above 0.5, that is 0.662>0.5. Hence H3 is proved and H0 is

rejected.

4.3.4.3.2 Discussion and implications

The statistical tests and hypotheses relating to switching costs and switching behaviour

clearly demonstrate that the switching costs also play a significant role in influencing

the young adults in Bangalore city to switch their cellular service providers. It implies

that the costs of switching are encouraging the consumers to switch their current

cellular service, if they are not satisfied with the one. Costs of switching cellular service

provider in Bangalore are low due to the launch MNP (Mobile Number Portability)

service that has been recently launched in India which costs only 19 INR (Indian

National Rupees) (telecomtalk.info). Hence, the statistical tests and hypothesis

confirms that switching costs are also influencing the dissatisfied respondents to the

respondents to switch their current cellular service providers by just incurring 19 INR

which is very less amount and easily affordable, and utilise MNP service which enables

them to switch to desired cellular service provider without the risk of losing the existing

number. As Fornell (1992) states that switching cost can help to prevent switching

behaviour by making it costly for consumers to change the service providers and

Gronhaug and Gilly, (1991) states that, high switching costs may tend even the

dissatisfied customers to remain loyal. It implies that in the case of this study, the

cellular service provider should try to make switching costly in order to prevent

switching behaviour of consumers and gain loyalty which will in turn. It is also clear

from the results of descriptive statistics that it will take very less time to switch cellular

84

service. Hence, it can be said that cellular service providers operating in Bangalore

should give careful consideration to increase switching costs in terms of both the time

and money and should plan strategies for locking-in the consumers at the very first

time they subscribe to the services of the company such as attracting consumers by

offering low prices and making a contract for specific period. It will help to prevent even

the dissatisfied consumers to switch cellular service provider which in turn enable the

firm to build market share, extract high level of profits from these consumers (Paul de

Bijl and Peitz, 2002). To achieve the objectives of this research, switching costs has

been ranked and presented in table 4.34 according to its significance in influencing

consumers switching behaviour.

85

4.3.4.4 Change in technology

4.3.4.4.1 Hypothesis testing

(H1): Changes in technology has a direct and significant effect on consumers’

switching behaviour in terms of switching cellular service provider.

(H0): Change in technology has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

The regression analysis has showed that the regression value i.e. R square is .695

which means that 69.5% of the variations in change in technology are influencing

switching behaviour of the respondents. The correlation analysis has revealed that

change in technology and switching behaviour are significantly correlated, as the

correlation value is .761 which is above 0.5, that is 0.761>0.5. Hence, H4 is proved and

H0 is rejected.

4.3.4.4.2 Discussion and implications

The statistical tests and hypothesis relating to change in technology it has been proved

that change in technology is also making the significant effect on the likeliness of

respondents to switch their cellular service providers. As according to Sindhu (2005),

offering new services not only helps to retain and gain customers but also provides a

means of generating greater revenue from one customer. The cellular service

providers that tie up with these manufacturers to offer the latest equipment along with

enhanced services appear to emerge as winners in today’s market (Sindhu, 2005).

Hence, it implies that, the cellular services providers should try to bring continuous

technological advancements in their services and also tie up with the leading

manufacturers of the cellular devices who manufacture the latest, trendy, and branded

devices, in order to provide consumers with improved services and latest devices or

equipments. This helps the cellular service providers to reduce the rate of consumer

switching behaviour, retain customers, and also to win new customers enabling to

generate higher profits, and increase market, and add increased consumer base to the

firm. The significance of change in technology on consumers switching behaviour of

cellular services has been shown in table 4.34.

86

4.3.4.5 Advertising

4.3.4.5.1 Hypothesis testing

(H5): Advertising has a direct and significant effect on consumers’ switching behaviour

in terms of switching cellular service provider.

(H0): Advertising has no direct and significant effect on consumers’ switching

behaviour in terms switching cellular service provider.

The results of the regression analysis showed that the regression value i.e. R square

between advertising and the switching behaviour is .611 which means that 61.10% of

the variations in advertising are influencing the likeliness switching behaviour of

consumers. The correlation analysis has also revealed that the advertising and

switching behaviour are also significantly correlated, as the correlation value is .598

which is above 0.5 i.e. 0.598>0.5. Hence, H6 is proved and H0 is rejected.

4.3.4.5.2 Discussion and implications

After testing the hypothesis relating to advertising and its effect on switching behaviour,

it has been proved that advertising also plays a significant role in influencing the

likeliness of respondents to switch the cellular service providers. The significance of

advertising has been presented in table 4.34 by ranking it accordingly on the basis of

statistical tests. Balmer and Stotvig (1997) states that, effective advertising competition

may stimulate consumer switching behaviour because of cellular service consumers’

have been informed about more opportunities for their purchasing choices. Most of the

companies invest in ‘brand ambassadors’ for spreading positive message of the brand

(Yeshin, 2006). In Bangalore city, the competitors of the cellular service providers are

using advertising as a medium to influence purchasing decisions and to stimulate

switching behaviour of the respondents. Therefore cellular service providers should

monitor which type of advertising is influencing consumers more. As there are several

methods of advertising, but the cellular service providers should adopt the method

through which the message conveyed to the consumers can reach more effectively

such as brand ambassadors in television ads of the company can effectively

communicate and influence consumer behaviour in terms of purchasing decisions and

switching intentions than normal ads. This helps the cellular service providers to gain

loyalty, increase profitability and market share of the firm by attracting large number of

audience by creating awareness among consumers about the benefits that are made

available with the services of the company.

87

4.3.4.6 Social influence

4.3.4.6.1 Hypothesis testing

(H6): Social Influence (reference groups) has a direct and significant effect on

consumers’ switching behaviour in terms of switching cellular service provider.

(H0): Social Influence (reference groups) has no direct and significant effect on

consumers’ switching behaviour in terms of switching cellular service provider.

The results of the regression analysis have showed that the regression value of R

square is .680 which means that 68% of variations in social influence is influencing the

likeliness of switching behaviour of the respondents and the results of the correlation

analysis reveals that there is a significant correlation between social influence and

switching behaviour of respondents, as the correlation value is .719 which is above 0.5

i.e. 0.719>0.5. Hence, H6 is proved and H0 is rejected.

4.3.4.6.2 Discussion and implications

After testing the above hypothesis in order to answer research questions and achieve

research objectives, it is proved that, social influence also has a significant role in

influencing the likeliness of respondents to switch cellular service provider. As

Rodriguez (2009) points out that, social influence determines consumer behaviour and

the members of the social network heavily influence most of the consumers to choose

the cellular service provider. The members such as family, friends, colleagues, etc are

found to be one of the significant factor by which the respondents are forced or

influenced to switch their service provider. It might be due to meeting the expectations

of the members of the social groups in order to maintain their standards or reputation in

the group or society. Therefore, it implies that the cellular service providers should

maintain the corporate image of the firm because the consumers in order to maintain

their social image will switch their cellular service provider if the image of the firm is

unfavourable among the social group or society of the consumers. According to

Kasande (2008), dissatisfied customers may express their feelings by complaining,

looking for alternatives or negative word of mouth. Hence, it implies that the cellular

service providers should be able to satisfy their customers in terms of every aspect

relating to their services such as service quality, price, brand image, etc in order to

influence existing consumers to spread positive word of mouth among their social

groups in order to prevent potential consumers from switching loyalties to the

competitors. It will in turn also help to increase the consumer base of the firm, generate

increased revenues, and also build corporate image of the firm. Table 4.34

demonstrates the position of social influence according to its significance in

88

determining the switching behaviour of young adults to switch their cellular service

providers which has been specifically designed to achieve the research objectives.

4.3.4.7 Involuntary switching

4.3.4.7.1 Hypothesis testing

(H7): Involuntary switching has a direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

(H0): Involuntary switching has no direct and significant effect on consumers’ switching

behaviour in terms of switching cellular service provider.

The regression analysis showed that the regression value of R square is .519 which

means that 51.90% of the variations in involuntary switching are influencing the

likeliness of switching behaviour of the respondents. The correlation analysis has also

showed that the correlation value between the involuntary switching and the likeliness

of switching behaviour is .551 which means that there is a direct and significant

relationship between the involuntary switching and likeliness of switching behaviour, as

the value is above 0.5 i.e. 0.551>0.5. Hence, H7 is proved and H0 is rejected.

4.3.4.7.2 Discussion and implications

As according to Rajeev (2008), involuntary switching is categorised under situational

triggers. After statistically analysing and testing hypothesis relating to involuntary

switching in order to achieve the objectives of this study, it is proved that involuntary

switching is also making a significant impact on the likeliness of switching behaviour of

the respondents. Switching behaviour is occurred not only with the intentions to switch

but also due to the involuntary factors (Roos, 1999). In this research, it implies that, the

likeliness of switching behaviour of the respondents to switch cellular service providers

is also causing due to the relocation of their geographic region which might be due to

jobs, studies, or any other purpose and the respondents are forced to switch their

cellular service providers without any intentions to switch. On the other hand, the

respondents are also forced to switch the cellular service provider because it has been

acquired by some other firm. This is resulting in the cellular service providers losing the

consumer base of the firm due to involuntary factors such as consumers’ relocation of

geographic region, firms’ acquisition, etc which in turn also significantly affects the

revenues and market share of the firm. This situation is caused unintentionally from

either of both parties and is uncontrollable. As indicated by Keaveney (1995),

involuntary switching factors are not under the control of consumers and the service

providers. Hence, it implies that cellular service providers should try to expand the

geographic location of their service in order to avoid consumers switching due

89

relocation of geographic region which in turn will maintain the market share and

revenues of the firm and prevent the chances of acquisition of the firm due to loses or

low market share. The importance of this involuntary switching in determining

consumer switching behaviour has been ranked and present in table 4.34 for the

purpose of answering the research objectives more clearly.

The results of the hypothesis are summarised in the table 4.33.

Hypotheses Supported Not supported

H1: Service quality has a direct and significant effect

on consumers’ switching behaviour in terms of

switching cellular service provider.

√

H2: Price has a direct and significant effect on

consumers’ switching behaviour in terms of switching

cellular service provider.

√

H3: Switching costs has a direct and significant effect

on consumers’ switching behaviour in terms of

switching cellular service provider.

√

H4: Changes in technology has a direct and

significant effect on consumers’ switching behaviour

in terms of switching cellular service provider.

√

H5: Advertising has a direct and significant effect on

consumers’ switching behaviour in terms of switching

cellular service provider.

√

H6: Social Influence (reference groups) has a direct

and significant effect on consumers’ switching

behaviour in terms of switching cellular service

provider.

√

H7: Involuntary switching has a direct and significant

effect on consumers’ switching behaviour in terms of

switching cellular service provider.

√

Table 4.33: Summary of hypotheses tests

90

All the above statistical tests and hypotheses tests have satisfied the objective one of

this study i.e. to investigate the factors that influences the consumers to switch their

cellular service providers and it was found that all predicted factors are statistically

significant.

The table 4.34 shows the ranking of factors from most significant factors to least

significant which influences the switching behaviour of the respondents on the basis of

the above tested hypotheses and statistical tests in order to satisfy the second

objective of this study.

Factors Ranking

Price 1

Service quality 2

Change in technology 3

Social influence 4

Switching costs 5

Advertising 6

Involuntary switching 7

Table 4.34: Ranking of factors according to its significance

With regards to the third objectives of this research i.e. to investigate the likeliness of

consumers switching from current cellular service provider to another, it has been

satisfied and demonstrated in the findings part of this chapter under the heading

4.2.2.1.

This shows that all the research questions have been answered and the objectives of

this research have been satisfied and in turn the main aim of this research has been

successfully achieved.

91

4.4 Chapter summary

This chapter presented the findings that have been extracted from the survey

questionnaires which were filled in by the respondents. Then all the findings have been

analysed using three statistical tests i.e. descriptive statistics, regression analysis and

correlation analysis in order to draw the results and test the hypotheses. Descriptive

statistics unfolded the basic features and simple summaries of the collected data and

the regression analysis has shown the relationship between switching behaviour and

the factors i.e. service quality, price, switching costs, change in technology, advertising,

social influence and involuntary switching. The correlation analysis has determined the

extent to which dependent variable and independent variables are linked. All the

hypotheses have been proved to be correct and the null hypotheses were rejected. The

discussion and implications that made after testing each hypothesis has answered all

research questions and in turn satisfied the objectives of this research. The next

chapter will look at the overall conclusion of this research and suggestion for the further

research.

92

5. CONCLUSION AND SUGGESTIONS

5.1 Introduction

This chapter presents the overall conclusion of this research and also the suggestions

for further research to enable the cellular service providers and the fellow researchers

to take benefit from this research and also to take this research to further end.

5.2 Conclusion of the study

This research has explored some of the major factors that are influencing the

consumers’ behaviour to switch their cellular services providers, through an exploratory

investigation. However there may be some other factors that have impact on

consumers’ switching behaviour but only the factors which are most important and

relevant to cellular services were examined. The results of this study have proved that

all the seven factors are significantly influencing the switching behaviour of consumers.

An understanding of these influencing factors allows managers to direct efforts and

resources in the most effective and efficient way to prevent consumers’ switching

behaviour, and reduce business losses in the long run that results from consumers’

switching behaviour.

All the research questions of this study have been answered and in turn achieved the

objectives of this research. For the purpose of achieving the objectives of this research,

similar studies of several researches has been taken into account such as Roos (1998,

1999), keanvey (1995), paulrajan and Rajkumar (2011), Bansal and Taylor (1999),

Rahman, Haque, and Amed (2010), and many others. This has significantly contributed

identify the major switching factors and bringing the reliable outcome for this research

and achieving the research objectives.

The results have disclosed that amongst all factors, price was the most influential factor

that influences the behaviour of young adults in Bangalore to switch from their current

cellular service provider to another. The cellular service providers should pay attention

to all factors and especially towards the price of the services, because the consumers’

switching intentions were found to be most significantly influenced by the price,

followed by service quality, change in technology, social influence, switching costs,

advertising, and involuntary switching which is least important. The unfavourable price

perceptions are the principally affecting consumers to switch loyalties to competing

service provider (Satish, et al. 2011). Favourable price for the cellular services is very

important in order to gain loyalty, market share, and corporate image of the firm. As it

has been acknowledged that majority of respondents are likely to switch from their

93

current cellular service provider i.e. around 53 percent. Hence, the cellular service

provider can make use of the information provided in this research to gain loyalty by

meeting their expectations and satisfying needs and desires because, if the service

providers are unable to meet the expectations then consumers will take their business

to somewhere else (Roos, 1998).

Cellular service providers who try to attract new consumers from their competitors will

also benefit from an understanding of what factors cause consumers to switch cellular

service providers. The management can make use of such information to develop

appropriate strategies to attract new consumers and retain lost consumers.

In general, the greater the knowledge, the management has about the factors

influencing their consumers to exhibit switching behaviour, the greater their ability to

develop appropriate strategies to reduce consumers switching their loyalties to the

competitors.

5.3 Suggestions for further research

The purpose of this research was to evaluate to effect of switching factors on

consumers’ switching behaviour in cellular services. The outcome of this research

supported the hypotheses show the positive relationship between the factors and

switching behaviour. The suggestions for further research are as follows.

This research was carried out only on consumers with specific age group i.e.

young adults aged between 18-35 years. It can be suggested, similar study can

be conducted on consumers with other age groups as well.

This study was conducted only on the consumers’ of Bangalore city. It can be

suggested that, a more extended geographic sample may reveal differences in

customers’ attitudes towards switching behaviour in cellular services, which

would also have managerial implications.

This study empirically examined seven factors that may influence consumers’

switching behaviour in cellular services. However, there may be some other

factors that can have an impact on consumers’ switching behaviour but were

not examined in this study. Further empirical research is required to examine

the other factors that can impact or influence consumers’ switching decisions.

This research was conducted on overall service industry in Bangalore,

regardless of particular service provider. Therefore, it can be suggested that,

similar research can be carried out on particular cellular service provider in

order to obtain company specific knowledge about the factors responsible for

consumers’ switching behaviour.

94

For this research the questionnaires from only 60 respondents were collected

due to time constraints. Therefore, it can be suggested that studying the

consumers’ switching behaviour with higher number of respondents by involving

interviews and other methods can help to generate more accurate results.

It can be concluded that the management should give careful consideration to all seven

factors influencing consumers switching behaviour in cellular, that were explored and

examined in this research in order to develop appropriate strategies for reducing the

rate of consumers’ switching the cellular service providers.

95

References and Bibliography

Anggraeni, A. (2010), Cross-Cultural Analysis of UK FMCG Advertising Content from

Non-UK Perspectives. MBA Thesis, Glyndwr University.

Au, K., Hui, M. K., & Leung, K. (2001), ‘Who should be responsible? Effects of voice

and compensation on responsibility attribution, perceived justice, and post complaint

behaviour across cultures’. The International Journal of Conflict Management, Vol. 2,

No. 4, 350-364.

Babbie, Earl R. (2008), The Basics of Social Research USA: Cengage Learning.

Babin, b.J. and Haris, E.G. (2011), CB2, p 271. USA, South-Western Cengage

learning.

Balmer, J. M. T., & Stotving, S. (1997). Corporate identity and private banking: A

review and case study. International Journal of Bank Marketing, 15(5), 169-184.

Bansal, H.S. and Taylor, S.F. (1999), ‘The Service Provider Switching Model (SPSM):

A model of consumer switching behaviour in service industry’. Journal of service

research, Vol. 2(2), 200-218.

Binsardi, A. (2008), Research methods for management, pedagogic Teaching series,

Vol. 1.

Bless, C., Higson-Smith, C. and Kagee, A. (2006), Fundamentals of Social Research

Methods: An African Perspective (4th edn.). South Africa, Juta and co. Ltd.

Block, C. & Roering, K. J. (1976), Essential of customer behaviour: Based on engel,

kollat, and blackwell’s consumer behaviour. The Dryden Press.

Bohlin, E., Levin, S.L., Sung, N. and Yoon, C.H. (2004), Global Economy and Digital

Society, p223, Netherlands, Elservier.

Bolton, R.N. (1998), ‘A Dynamic model of the duration of the customer’s relationships

with the continuous service provider: The role of satisfaction. Marketing Science, Vol.

17(1), 45-65.

Bolton, R. and Lemon, K. (1999) “A Dynamic Model of Customers’ Usage of Services:

Usage as an Antecedent and Consequence of Satisfaction,” Journal of Marketing

Research 36 (May) 171-86.

96

Boote, J. (1998), ‘Towards a comprehensive taxonomy and model of consumer

complaining behaviour’. Journal of Consume Satisfaction, Dissatisfaction and

Complaining Behaviour, Vol. 11, 141-149.

Bowen, J. T., and Chen, S. L., (2001), ‘The relationship between customer loyalty and

customer satisfaction’. International Journal of Contemporary Hospitality Management,

Vol. 13 (4/5), 213-217.

Brady, M.K. and Cronin, J.J. Jr (2001), “Some new thoughts on conceptualizing

perceived service quality: a hierarchical approach”. Journal of Marketing, Vol. 65, 34-

49.

Bruhn, M. and Georgi, D. (2006), Service Marketing: Managing the service value chain,

pp127-28. England, Prentice Hall.

Burnham, T.A., Frels, J.K. and Mahajan, V. (2003), ‘Consumer switching costs: A

typology, antecedents, and consequences’. Journal of the Academy of Marketing

Science, Vol. 31(2), 109-126.

Cengiz, E., Ayyildiz, H., & Er. B. (2007), ‘Effects of image and adverting efficiency on

customer loyalty and antecedents of loyalty: Turkish banks sample’. Banks and Bank

Systems, Vol. 2(1), 56-80.

Colgate, M. and Danaher, P. (2000), ‘Implementing a consumer relationship strategy:

the asymmetric impact of poor versus excellent execution’. Journal of Academic

Marketing Science, Vol. 28(3), 375-87.

Colgate, M. and Lang, B. (2001), ‘Switching Barriers in Consumer Markets: an

investigation of the financial services industry’. Journal of Consumer Marketing, Vol.

18(4), 332-347.

Cooper, D.R. and Schindler, P.S. (2006), Business Research Methods (9th edn.).

United States, McGraw Hill.

Cronin, J.J. Jr and Taylor, S.A. (1992), “Measuring service quality: a re-examination

and extension”. Journal of Marketing, Vol. 56, 55-68.

Dasgupta, K., Singh, R., Vishwanath, B., Mukherjea, S., and Nanavati, A. (2008),

‘Social Ties and their Relevance to Churn in Mobile Telecom Networks’. In Proceeding

of 11th International Conference on extending database technology: Advances in

database technology Nantes, France.

97

Davies, B. and Parket, C. (1997), Writing the doctoral dissertation: a systematic

approach, Barron’s Educational Series.

Denscombe, Martyn (2003) The Good Research Guide: For Small Scale Social

Research Projects. United Kingdom, Open University Press

Drew, J.H. (1991), ‘A Multistage model of customer assessments of service quality and

value’. Journal of Consumer Research, Vol. 17, 375-84.

Duncan, E. and Elliot, G. (2002), ‘Customer service quality and financial performance

among Australian retail financial institution’. Journal of Financial Services Marketing, 7

(1), 25-41.

Dutta, A. and Sridhar, V. (2003), ‘Modelling Growth of Cellular Services in India: A

Systems Dynamics Approach’ [papers presented at proceeding of the 36th Hawaii

International Conference on system sciences, 2003]. Hawaii.

Ezenezi, R.E. (2011), Impact of Cellphone Techonology User, p58. United States,

Xlibris Corporation.

Fill, C. (2005), Marketing Communications: engagement, strategies and practices (4th

edn.), p612. England, Prentice Hall.

Fornell, C. (1992), ‘A National Customer Satisfaction Barometer: The Swedish

Experience’. Journal of Marketing, Vol. 56, 6-21.

Frangos, C.C. (2009), Proceedings of the 2nd international conference: qualitative and

quantitative methodologies in economic and administrative sciences, p165. Greece,

Athens.

Garbarino, Ellen, and Johnson, Mark (1999) “The Different Roles of Satisfaction, Trust

and Commitment in Customer Relationships” Journal of Marketing, Vol. 63 (April), 70-

87.

Gershon, R.A. (2009), Telecommunications and Business Strategy, p109. New York,

Routledge.

Gillham, B., (2000), Developing a Questionnaire. London, Continuum Books.

Gronhaug, K., & Gilly, M. C. (1991), ‘A transaction cost approach to customer

dissatisfaction and complaint actions’. Journal of Economic Psychology, Vol. 12, 165-

183.

98

Gronroos, C. (1990), Service Management and Marketing. Lexington Books, Lexington,

MA.

Gronroos, C. (2001), “The perceived service quality concept – a mistake?”. Managing

Service Quality, Vol. 11(3), 150-2.

Gwinner, K.P., Gremler, D.D. and Briner, M.J. (1998), ‘Relational benefits in services

industries: the customers’ perspective’. Journal of Academic Marketing Science, Vol.

26(2), 101-14.

Hauser, J.R., Simester, D.I., & Wernerfelt, B. (1994), ‘Customer satisfaction incentives’.

Journal of Marketing Science, Vol. 13(4), 327-350.

Hennig-Tharau, T. and Hansen, U. (2000), Relationship Marketing: gaining advantage

through customer satisfaction and customer retention, p166. New York, Springer.

Hoyer, W.D. and Macinnis, D.J. (2010), Consumer behaviour (5th edn.), p3. USA,

South-Western, Cengage Learing.

Irizzary, M.S (2007), Wireless Network Call Quality: A Quantitative Investigation into

the Correlation between Network Call Quality and Subscribers Perceived Call Quality,

p35. United states, ProQuest Information and Learning Company.

Kapoor, R., Paul, J. and Halder, B. (2011), Services Marketing: Concepts and

Practices, pp337-344. India, Tata-McGraw-Hill.

Kang, G. and James, J. (2004), ‘’Service quality dimension: an examination of Gronoos

service quality model’’. Managing service quality, Vol. 14(4), 266-277.

Kasande, S.P. (2008), ‘An investigation of switching costs and customer loyalty in the

Indian cellular telephony industry’, Proceeds of 2nd IIMA conference on Research in

Marketing, pp7-13. India, Labdhi R. Bhandari Memorial Fund.

Kavita and Chopra, S. (2011), ‘Impact of value added service on telecom service

providers - A study on Altruist technologies’. International journal of research in finance

and marketing, Vol. 1(1), 1-11.

Keaveney, S.M. (1995), ‘Customer behaviour in services industries: An exploratory

study’. Journal of Marketing, Vol. 59(2), 71-82.

Khan, M. (2007), Consumer Behaviour, p3. India, New Age International.

99

Kim, M.K., Park, M.C. and Jeong, D.H. (2004), ‘The effects of customer satisfaction

and switching barrier on customer loyalty in Korean mobile telecommunication

services’, Telecommunications Policy, Vol. 28, 145-159.

Klemperer, P. (1995) ‘Competition When Consumers Have Switching Costs: An

Overview with Applications to Industrial Organisation, Macroeconomics and

International Trade’. Review of Economics Studies, Vol. 62, 515-539.

Kotler, P. and Armstrong, G. (2008), Principles of Marketing (12th edn.), pp4-5. New

Jersey, Prentice Hall.

Kotler, P., Keller, K. L., Brady, M., Goodman, M., and Hansen, T. (2009), Marketing

Management, pp6-7. England, Prentice Hall.

Kumar, R. (2005), Research Methodology. India, APH Publishing.

Lam, S.Y., Shanker, V., Erramilli, M.K. and Murthy, B. (2004), ‘Customer Value,

Satisfaction, Loyalty, and Switching Costs: An Illustration From a Business-to-Business

Service Context’. Journal of Academy of Marketing Science, Vol. 32(3), 293-311.

Lee, M. and John, C. (2005), Principles of Advertising: A Global Perspective (2nd edn.),

p3. New York, Haworth Press.

Lee, R. and Murphy, J. (2005) "From Loyalty to Switching: Exploring Determinants in

the Transition," ANZMAC 2005, Perth, Australia, December.

Lees, G., Garland, R., & Wright, M. (2007), ‘Switching banks: Old bank gone but not

forgotten’. Journal of Financial Services Marketing, Vol. 12 (2), 146-157.

Lehtinen, U. and Lehtinen, J.R. (1991), ‘Two Approaches to Service Quality

Dimensions’. The Service Industries Journal, Vol. 11(3), 287-305.

Lemon, K.N. (1999), ‘A Dynamic Model of Customers’ Usage of Services: Usage as an

Antecedent and Consequence of Satisfaction’. Journal of Marketing Research, 36, 171-

186.

Levi, J.B. (2007), Market Entry Strategies of Foreign Telecom Companies in India,

p208. Germany, Deutscher Universitats-Verlag.

Lewis, B. R (1989). Quality in the service sector: A review. International Journal of

Bank Marketing, Vol. 7(5), 4-12.

100

Lincoln, Eds. and Denzin, K.G. (2000), Emerging Confluences: Handbook of

Qualitative Research, Sage Publications Limited.

Lopez, J.P.M., Redondo, Y.P. and Olivan, F.J.S. (2006), ‘The impact of customer

relationship characteristics on customer switching behaviour: Differences between

switchers and stayers’. Managing Service Quality, Vol. 16(6), 556-574.

Lovelock, C. and Wirtz, J. (2007), Services Marketing: People, Technology, Strategy

(6th edn.), p15. Singapore, Prentice Hall.

Madden, G. (1993), Emerging Telecommunications Networks: The International

Handbook of Telecommunications Economics (vol. ii), p106, United Kingdom, Edward

Elgar.

Mallikarjuna, V., Mohan, G.K., and Kumar, D.P. (2011), ‘Customer switching of mobile

industry: An analysis of prepaid mobile customers in AP circle of India’. International

Journal of Research in Computer Application and Management, Vol. 1(3), 63-66.

Mangan, J., et al. (2004), “Combining quantitative and qualitative methodologies in

logistics research”, International Journal of Physical Distribution & Logistics

Management, Vol. 34(7), 565-578.

Michael, D. and Myers (2008), Qualitative research in Business and Management,

Sage Publications Limited.

Moorman, Christine et al (1992) “Relationships Between Providers and Users of

Marketing Research: The Dynamics of Trust Within and Between Organizations”,

Journal of Marketing Research, Vol. 29 (August), 314-28.

Mudie, P. and Pirrie, A. (2006), Services Marketing Management (3rd edn.), pp3-6.

USA, Elsevier.

Noel, H. (2009), Consumer Behaviour, AVA Publishing, Switzerland.

Oyeniyi, O. J. and Abiodun, A. J. (2010), ‘Switching Cost and Customers Loyalty in the

Mobile Phone Market: The Nigerian Experience’. Business Intelligence Journal, Vol.

3(1), 111-121.

Parhizgar, K.D. (2002), Multicultural Behaviour and Global Business Environment,

p117. New York, Haworth Press.

101

Pan, H. (2009), ‘India Weekly Telecom Newsletter’. Information Gatekeepters, Vol.

6(49), 1-8, December 4.

Paul de Bijl and Peitz, M. (2002), Regulation and Entry into Telecommunications

Markets, pp27-28. Cambridge, Cambridge University Press.

Paulrajan, R. and Rajkumar, H. (2011) ‘Service quality and customers preference of

cellular mobile service providers’. Journal of technology management and innovation,

Vol. 6(1), 38-45.

Polo, Y. and Sese, F.J. (2009), ‘How to make switching costly: The role of marketing

and relationship characteristics’. Journal of service research, Vol. 12(2), 119-137.

Press trust of India (2011), ‘India to outpace China on growth front by 2015: ICICI

Bank’. PTI: New Delhi.

Rahman, S., Haque, A. and Ahmad, I.S. (2010), ‘Exploring influencing factors for the

selection of mobile phone service providers: A structural equational modelling (SEM)

approach on consumers’. African Journal of Business Management, Vol. 4(13), 2885-

2898.

Rajeev, K. (2008), ‘Lost Customers Complaint Behaviour and Trigger: An Exploratory

Study’, Proceeds of 2nd IIMA conference on Research in Marketing, p5. India, Labdhi

R. Bhandari Memorial Fund.

Rao, C.S. (2007) ‘Equity vs Efficiency in Telecom Spectrum Management in India’.

Margin: The journal of applied economic research, Vol. 1(3), 321-335.

Rodriques, T. (2008), Impact of Switching Barriers, Perceived Fairness, Perceived

Service Quality and Socio-economic Classification on Intentions to Switch and

Switching Behaviour. Master’s Thesis, National Cheng Kung University, Taiwan.

Roos, I. (1998), “Customer Switching Behavior in Retailing,” Research Report No. 41,

Swedish School of Economics and Business Administration, Helsinki, Finland.

Roos, I., (1999), ‘Switching processes in customer relationships’. Journal of Service

Research, Vol. 2(1), 376-393.

Roos, I. and Gustafsson, A. (2007), ‘Understanding frequent switching patterns: A

crucial element in managing customer relationships’. Journal of service research, Vol.

10(1), 93-108.

102

Roos, I., Edvardsson, B., and Gustafsson, A. (2004), ‘Customer switching patterns in

competitive and non-competitive service industries’. Journal of service research, Vol.

6(3), 256-271.

Reichheld, F. F. and Sasser, W. E. (1990), ‘Zero Deflections: Quality Comes to

Services’. Harvard Business Review, Vol. 68, 105-111.

Satish, M., Kumar, K. S., Naveen, K.J. and Jeevanantham, V. (2011) ‘A study on

consumer switching behaviour in cellular service provider - A study with reference to

Chennai’. Far East Journal of Psychology and Business, Vol. 2(2), 71-81.

Saunders et al. (2009) Research Methods for Business Students. United States,

Financial Times/Prentice Hall.

Schiffman, L.G., Kanuk, L.L. and Hansen, H. (2008), Consumer Behaviour: A

European Outlook, p4. England, Prentice Hall.

Sidhu, A. (2005), Canadian Cellular Industry: Consumer Switching Behaviour. MBA

thesis, Simon Fraser University.

Shy, O. (2002), ‘A quick and easy method for estimating switching costs’. International

Journal of Industrial Organization, Vol. 20, 71-87.

Spathis, C., Petridou, E., and Glaveli, N. (2004). Managing service quality in banks:

Customers’ gender effects. Managing Service Quality, Vol. 14(1), 90.

Steuernagel, R.A. (2000), The Cellular Connection: A Guide to Cellular Telephones (4th

edn.), p23. New York, John Wiley and Sons.

Ticehurst, G.W., and Veal, A.J. (2000) Business Research Methods. Essex, Longman.

Wangenheim, F.V. (2005), ‘Postswitching negative word of mouth’. Journal of service

research, Vol. 8(1), 67-78.

Westlund, O. (2006), ‘Beyond time and space Sweden and their Mobile Internet News

Users (MINU)’. Paper presented at AOIR 7.0 conference “Internet and convergence”,

Brisbane 27-30, September 2006.

Yeshin, T. (2006), Advertising, p378. London, Thomson Learning.

Yue, C.S., Freeman, N.J., Venkatesan, R. and Malvea, S.V. (2001), Growth and

Development of IT Industry in Bangalore and Singapore: A Comparative Study, p4.

New Delhi, Sterling Publishers Private Limited.

103

Zeithaml, V., Parasuraman, A. and Berry, L. L. (1990), Delivering service quality, p19.

New York, Free Press.

Zou, S. and Fu, H. (2011), International Marketing: Emerging Markets, p116. United

Kingdom, Emerald Group Publishing Limited.

Electronic source

http://articles.economictimes.indiatimes.com/2011-03-04/news/28657609_1_offer-3g-

services-mobile-operator-bharti-airtel (electronically accessed on 29-07 2011).

http://articles.timesofindia.indiatimes.com/2011-07-06/telecom/29742480_1_telecom-

sector-punjab-and-karnataka-circles (electronically accessed on 31-07-2011).

http://www.consumerpsychologist.com/ (electronically accessed on 22-07-2011).

http://www.indiahousing.com/infrastructure-in-india/telecom-industry-india.html

(electronically accessed on 29-07 2011).

http://www.telecomlead.com/inner-page-details.php?id=846&block= (electronically

accessed on 30-06-2011).

http://telecomtalk.info/mobile-number-portability-launched-in-haryana-pan-india-by-

january-20/49150/ (electronically accessed on 30-06-2011).

http://telecomtalk.info/mtnl-launches-new-3g-prepaid-plan-in-delhi/27566/

(electronically accessed on 02-08-2011).

104

Appendix A

Survey questionnaire

I am Mohammed Abdul Raheem, an MBA student from Glyndwr University, Wales,

United Kingdom. I am currently conducting a research towards my MBA dissertation on

the topic of ‘consumer switching behaviour in cellular service providers’. This

questionnaire survey is conducted for the purpose of data collection. We ensure that

your identity will remain strictly confidential. Thank you for your kind consideration. If

you have any further questions, feel free to contact me by emailing at

maraheemp@gmail.com.

Please tick (X) in the bracket to give your opinion

Section 1

Demographics

1. What is your gender?

( ) Male ( ) Female

2. What is your age group?

( ) 18-24 ( ) 25-29 ( ) 30-35

3. What is your occupation?

( ) Student ( ) professional ( ) Self-employed ( ) labourer

( ) Unemployed ( ) Retired

4. What is the highest level of education you have achieved?

( ) Primary education ( ) High school education ( ) Diploma/certification

( ) Bachelor degree ( ) Post-graduate degree ( ) PhD

SECTION 2

5. Are you likely to switch from current cellular service provider to another?

( ) Very unlikely ( ) Unlikely ( ) Neutral ( ) Likely ( ) Very likely

Service quality

6. The level of customer service provided by the current cellular service provider is

good.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

105

7. The network coverage of the current cellular service provider is good.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

8. There are frequent network problems with the services of the current cellular service

provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

9. The call quality provided by the current cellular service provider is good.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

10. There was an error/s in billing from the side of the current cellular service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

Price

11. The current cellular service provider offers suitable tariffs for different age groups.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

12. The call rates offered by the current cellular service provider are high.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

13. The value-added services offered by the current cellular service provider are costly

(Eg. Voicemail, internet)

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

14. The current cellular service provider charges high service charges for

recharges/top-ups.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

Switching costs

15. It will take too much time to switch to new service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

16. It will cost lot of money to switch to new service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

106

Change in technology

17. The current cellular service provider continuously upgrades its services according

to the trend (eg. 3G mobile service)

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

18. The current cellular service provider offers new technology and trendy phones with

its services enabling the customers to use wide range of applications on their phone

through the services of cellular service provider (eg. use of skype on iPhone 4).

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

Advertising

19. The advertisements of the competitors are encouraging me to switch the cellular

service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

20. The brand ambassadors of the company are influencing me to switch the cellular

service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

Social influence

21. My family and friends are influencing me to switch current cellular service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

Involuntary switching

22. I am likely to switch because I will be moving outside the geographic location where

the services of current service provider are not available.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree

23. I am likely to switch because some other firm has acquired/acquiring my current

cellular service provider.

( ) Strongly Agree ( ) Agree ( ) Neutral ( ) Disagree ( ) Strongly Disagree