Eric and bright

UNIVERSITY OF CAPE COAST

DEPARTMENT OF MATHEMATICS AND STATISTICS

A STUDY ON FACTORS THAT DETERMINE THE CHOICE OF

BRANDS OF MOBILE PHONE

(A CASE STUDY IN KUMASI METROPOLIS)

BY

AIDOO ERIC

NYAMEDOR BRIGHT

APRIL, 2008

i



A STUDY ON FACTORS THAT DETERMINE THE CHOICE OF


(A CASE STUDY IN KUMASI METROPOLIS)

BY

AIDOO, ERIC

NYAMEDOR, BRIGHT

STA499 (PROJECT WORK)

A dissertation submitted to the Department of Mathematics and Statistics,

University of Cape Coast in partial fulfillment of the requirement for the

award of Bachelor of Science Degree in Statistics.

APRIL, 2008

ii

DECLARATION

We do hereby declare that project entitled “FACTORS THAT DETERMINE THE

CHOICE OF BRANDS OF MOBILE PHONE” was done entirely by us under the

supervision of Mr. B. K. Nkansah.

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DEDICATION

To our beloved parents (Mr. & Mrs. Aidoo, Mr. & Mrs. Nyamedor)

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ABSTRACT

The whole world has now become a global village where people can now reach

others in different parts of the world within a short period with the advent of mobile

phones. As a result of its importance numerous factors need to be considered when

choosing mobile phone. It is against these challenges that the topic “factors that determine

the choice of brands of mobile phone” was chosen for study.

The main objective of this paper is to determine the factors that determine choice of

brand of mobile phone among residents of Kumasi metropolis. To identify these factors, a

questionnaire survey was carried out among the people of Kumasi. Three hundred

respondents were sampled for the study.

The chi-square and factor analysis, were the main statistical tools used for the

analysis. Also, a combination of statistical software (SPSS and Minitab) was used for the

analysis.

From the primary analysis, it was found that 76% of the respondents owned mobile

phone and also most people do not use mobile phone because of its high cost. The analysis

also reveals that the most used mobile phone is Nokia and the affordable mobile phone

price ranges from GH¢50 – GH¢100. From the test of hypothesis, it was also revealed that

brand of mobile phone used by the consumer is associated with educational level

attainment and occupational status of the consumer.

In further analysis, two factors were obtained as being the number of factors

underlying choice of brand of mobile phone. The first most important factor is reliable

quality of the mobile phone brand and the other factor is user-friendliness of the brand of

the mobile phone.

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ACKNOWLEDGEMENT

Mr. B.K. Nkansah our supervisor deserves a special word of appreciation. Who despite his

heavy schedule has rendered us immeasurable supports by reviewed the manuscript. His

comments and suggestions immensely enriched the content of this work.

We are also grateful to the lectures and entire staffs of Department of Mathematics and

Statistics, University of Cape Coast.

Finally we want to thanks the 2008 year group of Statistics Students of Department

Mathematics and Statistics.

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TABLE OF CONTENTS

DECLARATION............................................................................................................... ii

DEDICATION..................................................................................................................iii

ABSTRACT...................................................................................................................... iv

ACKNOLEDGEMENT.................................................................................................... v

TABLE OF CONTENTS........................................................................................... vi-vii

LIST OF TABLES .........................................................................................................viii

LIST OF FIGURES ......................................................................................................... ix

1 INTRODUCTION.......................................................................................................... 1

1.1 Background ............................................................................................................... 1

1.2 Statement of the Problem.......................................................................................... 3

1.3 Objectives of the study.............................................................................................. 3

1.4 Hypothesis................................................................................................................. 4

1.5 Significance of the Study .......................................................................................... 4

1.6 Data Collection.......................................................................................................4-6

1.7 Literature Review...................................................................................................... 6

1.7.1 Definition of Mobile Phone/Cellular Phone....................................................6-7

1.7.2 Generations of Mobile Phones.........................................................................7-8

1.7.3 Consumer Choice Behavior...........................................................................8-10

1.7.4 Mobile Phone Choice ..................................................................................10-11

1.7.5 Brand Preference and Product Attribute........................................................... 11

2 REVIEW OF METHODS........................................................................................... 12

2.1 Factor Analysis ..................................................................................................12-14

2.2 Chi-Square Analysis ..........................................................................................14-16

3 PRELIMINARY ANALYSIS ..................................................................................... 17

3.1 Mobile Phone Distribution by Gender .................................................................... 17

3.2 Brand of Mobile phone Distribution....................................................................... 18

3.3 Reasons by Respondents who do not use Mobile Phone ...................................18-19

3.4 Reasons by Respondents who use More Than One Mobile Phone....................19-20

3.5 Mobile Phone Cost.................................................................................................. 20

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3.6 Test of Hypothesis – 1 ............................................................................................ 21

3.7 Test of Hypothesis – 2 ............................................................................................ 22

3.8 Test of Hypothesis – 3 .......................................................................................23-24

4 FURTHER ANALYSIS............................................................................................... 25

4.1 Correlation Analysis...........................................................................................25-26

4.2 Total Variance Explained...................................................................................26-27

4.3 The Component Matrix and Interpretation of Extracted Factors .......................27-29

5 SUMMARY, DISCUSSION AND CONCLUSION .................................................. 30

5.1 Summary ................................................................................................................. 30

5.2 Discussion ..........................................................................................................30-31

5.3 Conclusion .........................................................................................................31-32

5.4 Recommendation..................................................................................................... 32

REFERENCE .............................................................................................................33-34

APPENDIX A: Specimen of the Questionnaire.......................................................35-38

APPENDIX B: The Chi-square Probability Tables..................................................... 39

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LIST OF TABLES

Table 2.1: A cr × Contingency Table .............................................................................15

Table 3.1: Distribution of Mobile phone Ownership by Gender .....................................17

Table 3.2: Distribution of Mobile phone Cost .................................................................20

Table 3.3: Cross-tabulation of level of education against the owned of mobile phone ...21

Table 3.4: Cross-tabulation of occupational status against mobile phone usage .............22

Table 3.5: Cross-tabulation of Mobile phone brands against Gender ..............................23

Table 4.1: Correlation Matrix...........................................................................................25

Table 4.2: Results of KMO and Bartlett’s Test of Significance.......................................26

Table 4.3: Total Variance Explain ................................................................................... 26

Table 4.4: Component Matrix ..........................................................................................26

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LIST OF FIGURES

Figure 3.1: Distribution of Brands of Mobile phone .......................................................18

Figure 3.2: Reasons by Respondents for not using Mobile phone...................................18

Figure 3.3: Reasons why respondents use more than one Mobile phone ........................19

Figure 4.2: Scree Plot of Eigenvalue against Number of components ............................27

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CHARPTER ONE

INTRODUCTION

1.1 Background

The whole world has now become a global village where people can now reach

others in different parts of the world within a short period. This global village was brought

by the introduction of information and communication technology (ICT) tools. These tools

include mobile phones. Mobile phones have become a fundamental part of personal

communication across the globe during the past ten years. This great technology has

brought in its wake a lot of challenges.

Two decades ago, the telecommunications market in Ghana was dominated and

monopolize by Ghana Telecom (GT). GT formally known as Ghana Post &

telecommunication (GP&T) was incorporated in 1994. The enactment of the statutory

corporation in June 1995, transformed what had been a telecommunication device into

Ghana Telecom Company, with the Ghana government being the majority shareholder.

Until 1992, cross-border and internal corporation between Ghana post and

telecommunication, and telecommunication providers elsewhere was all but none

existence. Typically, regulations prohibited foreign firms from entering the country’s

telecommunication market to compete with the domestic provider. Most of the traffic

carried by GP&T was voice traffic, almost all of it was carried over wires, and customers

were charged a hefty premium to make long distance and international calls. Besides, the

few telephone lines available were all centered in the regional capital and metropolitan

areas. Only the government ministries, universities, hospitals and few other important

government and private institutions had that opportunity of enjoying this facility. The

facility was also accessible to the privileged in the society who could afford to pay for

services.

A little more than a decade ago (since 1992) the landscape of telephone system in

Ghana has changed. New competitors have emerged to take on the dominant provider,

Ghana -Telecom. The state-owned monopoly has been privatized. New wireless and

cellular technologies have facilitated the emergence of competitors such as TiGo, MTN,

Westel and Kasapa, which now compete head to head with the former state monopoly,

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Ghana Telecom. Much of the voice traffic by these telecommunication providers is being

transmitted over digital networks that utilize fiber optics, digital switches and protons to

send the voice around at the speed of light.

The first cellular phone service was initiated in 1992 by Millicom Ghana limited-

mobitel (now TiGo). Scancom Ghana Limited –Spacefon (now MTN) joined Mobitel in

1994 in the provision of mobile telephone services. One-Touch (Ghana Telecom) mobile

telephone operator was the next competitor in the cellular phone market in the year 2000.

A local cellular phone operator, Kasapa, followed. It is worthy of note that in 1992 about

19,000 Ghanaians owned mobile phones. In 1998 the number of mobile phone users in the

country increased to 43,000 and by the middle of 1999 the number increased to 68,000.

The usage rose from 22,000 to 130,000 subscribers between 1999 and 2000. From the year

2000 up to date, the subscribers’ base has increased to about 3,500,000. Between 1992 and

the year 2001, mobile phone usage seemed limited to some categories of people in the

country. These include businessmen, managers in reputed companies, government

officials, diplomatic corps, wealthy individuals and some very important personalities.

These may be attributed to the fact that cellular phone usage was new and their coverage

was limited to the country’s main cities. Now, due to the nation-wide coverage of the

mobile phone service providers, every category of people owned mobile phone. It has

helped bring about a source of employment to a section of the populace. It has also become

fashionable to own a mobile phone. The need for the acquisition of mobile phone by all

has brought about some challenges. This is because people go to all extent to acquire them.

In recent times, the acquisition of the phone alone is not the issue. The issue now is the

type of phone one possesses. It is the latest fashion to see persons of all age groups and

professions boasting about the features their mobile phones possess. The need for

fashionable phones has also caught up with the mobile phone manufactures as they also

manufacture new and fashionable mobile phones within short interval of time. In a way,

there seems to be a competition among the mobile phone manufacture as they must

provide latest and fashionable mobile phones to satisfy their customers.

In Ghana, there is substantial population of mobile phone users. Mobile services in

Ghana have advanced to the stage where, in addition to traditional service such as voice

call and SMS, most users can freely enjoy the latest mobile technologies such as mobile

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Internet, e-mailing, e-learning, e-banking and video-conferencing. Consumer research has

devoted little specific attention to factors underlying the mobile phone buying decision

process. There are numerous factors that need to be taken into account when exploring

mobile phone buying decision process. These factors may include conditions that affect the

evolution of mobile phone market in general and individual consumer’s motives in

particular.

The study seeks to know the factors that underlying a person’s decision in choosing

brand of mobile phone(s) to use. At the end of this study, we will be able to know the most

common brand of mobile phone in use among the study population. Also, we will be able

to determine among other things if there are certain consumer-based indicators

(educational status, occupational status and gender) have influence in the purchasing of

mobile phone.

1.2 Statement of the Problem

The use of mobile phones has become a fundamental part of personal

communication across the globe during the past ten years. In Ghana mobile phone usage

has become common, but there are numerous factors that need to be taken into account

when choosing a brand of mobile phone. Consumer research has devoted little specific

attention to factors that determine choice of brand of mobile phones. Conversely, only a

few published academic researches were focused on comparative studies. It is against this

background that the topic “factors that determine the choice of brands of mobile phone”

was chosen for study.

1.3 Objectives of the Study

The objectives of the study has been categorize into two: main objective and specific

objectives.

The main objective of this study is to examine the important factors that determine choice

of brand of mobile phone.

The specific objectives of the study are as follows.

1. To determine the most used mobile phone brand.

2. To determine the reasons why some people don’t use mobile phone.

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3. To determine whether there is a relationship between mobile phone usage and

educational level


occupational status.


gender.

6. To determine the reasons why some consumers choose to use more than one mobile

phone.

1.4 Hypotheses

The null hypotheses formulated for the study were as follows:

1. There is no relationship between mobile phone usage and educational level

2. There is no relationship between mobile phone usage and occupational status.

3. There is no association between gender and the brand of mobile phone used.

1.5 Significance of the Study

The significance of this study is to extend previous studies conducted in different

parts of the world. It is hope that the findings will not only inform factors that determine

choice of brand of mobile phone, it will also bring to light the brand of mobile phone that

is mostly used by consumers in Ghana. An awareness of factors that determine choice of

brand of mobile phone might ultimately guide or influence manufacturers in the kind of

mobile phones to produce. Conversely, it will also guide mobile phone importers in Ghana

to know the kind of mobile phones to import into the country.

1.6 Data Collection

The target population for the project comprised the total population of Kumasi, a

capital city of Ashanti Region. A sample of size 300 was drawn from the study area for

this research.

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Kumasi is Ghana’s second city and it is about 300 km from the national capital,

Accra. It centrally located in the Ashanti Region of Ghana. It has an approximate area of

254 square kilometers and it is the second largest metropolis after Accra in Ghana. Being

strategically located on the cross roads of the northern parts of the country, Kumasi is also

the capital of ancient Asante Kingdom and presently Ashanti Region. Politically Kumasi is

divided into four (4) sub-metropolitan areas namely; Manhyia, Asokwa, Bantama and

Subin.

In terms of population, it has been estimated in 2000 population census to be

1,170,270 out of which 587,012 are males representing 50.16% and 583,258 were females

representing 49.84% of the entire population of the metropolis. As a cosmopolitan city, it

contains members of most ethnic groups from West Africa although the indigenous

Ashanti people dominate life in general. Although these migrants’ communities maintain

their language and cultural identity, Ashanti Twi is universally spoken and understood.

The people in the metropolitan are mostly businessmen and women. A sizeable

percentage of the populations engage in vocational trade such as fitting, carpentry etc. with

Adum, Central market, Suame Magazine and Anloga as the major areas where these

activities takes place. Others are in the Government establishment such as education,

health, financial institutions and so on. The road network in the metropolitan is first class

(tarred with bitumen) and almost all of them have streetlights.

The economic of the Kumasi metropolis comprises the agriculture, industrial and services

sectors. Like any urban economy the agricultural sector is very small, accounting for only

about ten (10) percent of its Gross Domestic Product (GDP). The services sector is the

largest and the most important sector which contributes about 60 percent of the metropolis

GDP follow by industrial sector accounting for about 30 percent of the GDP.

The contribution of Agriculture to the metropolitan economy is moderate and it is mostly

practiced in the peripheral areas like Appiadu, Deduako, Kokoben, Ohwin and Sokoban

etc. Most of the crops grown are stables and include maize, cassava, plantains, cocoyam

and vegetables.

The Kumasi metropolis is endowed with many varied industrial activities. This is

mainly due to its linkage to all parts of the country. The industrial activities in the

metropolis may be classified into the three scale industries. The medium and large-scale

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industrial activities include pharmaceutical and medical accessories, mechanical and

electrical engineering works, logging and saw milling. The small-scale industrial activities

include footwear, cosmetics, soap making, carpentry and joinery, foam and plastics,

printing and stationery and metal works. The central of industrial activities are Kaase,

Ahinsa, Asokwa, Anloga and Suame Magazine areas. An important innovation in the

metropolis economy in recent times is a wide variety of predominantly informal economy

enterprises and home-base industries which are springing up with most of their operations

in the residential areas. This may be partly due to the shrinking public and formal sector

and the recent encouragement of the private sector as an engine of growth of the country’s

economy.

In this research, seven variables were considered to measure the factors that

determine the choice of brand of mobile phone(s). These variables are as follows:

X1 – Affordability

X2 – Fashionable

X3 – More features in the mobile phone

X4 – Reliability of the reception

X5 – High quality

X6 – Popularity

X7 – Portability

The main instrument of data collection was questionnaire. The questionnaire was in

three sections consisting of sixteen items in all. The first section of the questionnaire

contains items which enabled us to group the respondents. The second and third section of

the questionnaire also enabled us to measure the variables of interest.

To ensure accuracy of responses, the research instrument was self-administered by

the researchers to the subjects of the study. During the administration of the research

instrument, convenient sampling was introduced in the selection of the research objects.

The analysis of the data gathered from this research was in two parts. The first part,

which is the preliminary analysis made use of descriptive statistics tools such as bar chart,

pie chart and frequency tables. The second part, which is the further analysis made use of

inferential statistics tools such as chi-square analysis and factor analysis.

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Also, a combination of statistical software (SPSS and Minitab) and others software

were used during data processing, and others.

1.7 Literature Review

1.7.1 Definition of Mobile/Cellular Phone

The Cellular telephone (commonly “mobile phone” or “cell phone” or “hand

phone”) is a long-range, portable electronic device used for mobile communication

(www.wikipewdia.com definition of mobile phone). In addition to the standard voice call

of a telephone, current mobile phones can support many additional services such as SMS

(Short Message Service) for text messaging, email, packet switching for access to the

Internet, and MMS (Multimedia Messaging Service) for sending and receiving photos and

video in a single messaging. Cellular telephone is also defined as a type of short-wave

analog or digital telecommunication in which a subscriber has a wireless connection from a

mobile telephone to a relatively nearby transmitter. The transmitter’s span of coverage is

called a cell. Generally, cellular telephone service is available in urban areas and along

major highways. As the cellular telephone user moves from one cell or area of coverage to

another, the telephone is effectively passed on to the local cell transmitter.

1.7.2 Generations of Mobile Phones

The evolution in mobile phone and advancement technology started from the first

generation phones (1G). We are currently experiencing a shift from the second generation

(2G) to the third generation (3G) mobile phones, which is expected to change the way

people use their mobile phones. The rise of the 3G network and its consumer acceptance is

said to be one of the toughest marketing challenges in recent history (Benady, 2002). In

general terms, the success of 3G depends primarily on how the real benefits of the

technology are marketed to consumers on one hand and on pricing policy of the services

on the other hand (Benady, 2002). If we look beyond the hype around 3G it is obvious that

we are not experiencing a revolution in mobile phone markets, rather an evolution where

consumers are able to do the same things they could with 2G and 2.5G examples are the

GPRS (General Pocket for Radio Services) and EDGE (Enhance Data rate for Global

Evolution) technology, but only better and faster in terms of download times (Drucker,

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2004; Sehovic, 2004). The mobile phone industry is currently using many standards among

are the Japanese PDC (Personal Division Code), European GSM (Global System for Mobil

Telecommunication) and American CDMA (Code Division Multiple Access), which has

made it difficult for users traveling to utilize their phones extensively. The evolution of 3G

is expected to simplify this as only two standards are competing, the WCDMA (Wide-

Code Division Multiple Access) that will become the European UMTS (Universal Mobile

Telecommunications System), CDMA2000 (Code Division Multiple Access), and the

Chinese TD-SCDMA (Time Division-Synchronous Code Division Multiple Access). The

WCDMA standard is said to dominate the global market for the next five years (Sehovic,

2003). Consumer shift from 2G to 3G means that in order to be able to use the services

offered by the faster network consumers need to acquire new mobile handsets equipped

with Internet access like GPRS (General Pocket for Radio Services), WAP (Wireless

Application Protocol) and new features such as possibility to receive and send multimedia

messages. Although recent news indicates a strong demand for new mobile phones

equipped with color displays and built-in camera, there still is plenty of skepticism in the

media, as well as in the market itself, towards the technological development. The

development of mobile phones is leading the market into a situation where the basic need,

communication, is actually broadened to new means.

1.7.3 Consumer Choice Behaviour

Consumers engage in information search before making choice. Consumer decision

making process is usually guided by already formed preferences for a particular

alternative. In close relation to information search, evaluation of alternatives has also

gained a momentum in recent research (Laroche et al 2003). Their study on consumer’s

use of five heuristics (conjunctive, disjunctive, lexicographic, linear additive, and

geometric compensatory) in the consideration set formation found that conjunctive

heuristics is the most often used decision model in the consideration set formation for two

product classes in the study (beer brands and fast food outlets). Conjunctive heuristics

means that a consumer selects a brand only if it meets acceptable standards, the so-called

cutoff point on each key attribute consumer regards as important. In this non-compensatory

method of evaluation, a consumer would eliminate a brand that does not fulfill the

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standards on one or two of the most important attributes, even if it is positive on all other

attributes.

It is widely accepted that the traditional problem solving approach involving rational

decision making to the study of consumer choice may not be suitable for all situations, or

is at least incomplete to understand choice behavior.

Quite similarly, consumer choice can also be approached from the perspective of

conscious and nonconscious choice (Fitzsimons et al., 2002). Quite many choice situations

occur outside of conscious awareness and with limited information search (Kivetz and

Simonson, 2000) and it can be stated that many choices have both conscious and

nonconscious motives. Fitzsimons et al. (2002) found that in many cases, nonconscious

influences affect choice much more than is traditionally believed by researchers.

The acquisition of a new mobile phone follows this traditional view of buying

process, but is in many situations also affected by symbolic values related to brands. With

the advent of globalization and high tech production methods, a large variety of mobile

phones has almost overwhelmed the mobile market. This has changed the visual standards

of many consumers over the world. For instance, according to a China Business Weekly

Yan Xianpu (2004), mobile phone production and sales in China in 2003 reached 158

million and 151million with growth rates of 48% and 49% respectively. With references to

the Yan Xianpu report for example, Chinese consumers are always chasing after new

mobile phones with more functions, and more reliable quality. According to the report,

different age groups have different preferences for mobile phone brands. The report further

stated that generally, with the increase of age, Motorola is more widely accepted than

Samsung, Nokia is more popular in the youth range from 16 to 24 years. Nokia and

Motorola are popular among middle-aged consumers (45 to 60 years). The report further

established that men and women also have different tastes when purchasing mobile

phones. Men prefer Motorola and Bird whilst women prefer flip phones. Nokia and

Samsung are roughly the same for both sexes. Yan Xianpu also revealed that Nokia,

Motorola and Samsung are in the top three. Samsung has emerged later and become

popular among the youth, surpassing Nokia and Motorola in several areas, including

ranking first in future purchase potential.

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In wider perspective, the Daily Graphic (December 2004) reported that the number

of mobile phone subscribers around the world totaled nearly 1.5 billion by the middle of

2004. The report also pointed out that in Ghana, industry experts put the figure around 1.5

million subscribers, representing about 7% of the population, compared to 1% in the year

2002.

According to British Broadcasting Corporation (BBC) report (June 2005), in their

different ways, user demand and market forces, in different countries and regions, are

leading to the spread of mobile phones, at a rate which is almost certainly greater than any

other invention in history. In the report the mobile is said to be one of the most democratic

inventions in history, because it is accessible to all parts of the population ultimately in all

countries.

For example, there are major problems in making cars, personal computers or even

fixed line phones available to everyone in the world. But there are no insurmountable

barriers; technical or commercial, in the way of everyone on the planet having a mobile

phone of his preference.

1.7.4 Mobile Phone Choice

Previous literature on mobile phone choice is meager. Couple of academic articles

have dealt with mobile phone usage and grasped the consumer decision making process.

To begin with, a survey conducted by E-Belarus.org (2001-2006) revealed that out of 400

respondents, 33% said they used Nokia, 25% used Samsung, 8% Siemens, 13% Motorola

whiles 5% used Sony-Ericsson.

According to a survey conducted by British Broadcasting Corporation in 2004,

Nokia is the most popular handset in Europe. In another survey, Brandstock (2004),

Samsung is the most popular in Korea. The results of a survey carried out by TV3, a

television station in Ghana, in 2005, also indicate that Nokia is the most popular brand in

Ghana. One of the reasons being the different brand power: in terms of durability, coverage

and reception, and battery capacity in these countries.

Further research by the Nokia Company also reveals that user interface styles are

regarded as a competitive asset in the race for market dominance (Lindholin et al 2003).

However, all the different mobile handset manufactured have its own user interface and

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conventions. It can therefore be argued that different mobile brands are popular in different

countries, each with its own user interface. In the same sense, it is anticipated that different

mobile brands will be popular among different groups and individuals.

In addition, it seems that size and brand play to some extent an important role in

decision making. Liu (2002) for instance, surveyed Asian mobile phone users and found

that the size of the phone had no impact on mobile phone choice, but this finding might be

due to the fact that all competing brands have quite similar sized phones that are small

enough. Liu continues that the trend will actually be not towards smaller phones but

towards phones with better capability and larger screens. While companies are advertising

new models and services that do not yet exist, it according to the paper signals to the

market that the company is at the cutting edge of technology and shows what will be

available in the very near future. The sales of new phones will then be driven by

replacement rather than adoption. Price of the phone has been identified as a critical factor

in the choice of the mobile phone brand, especially among younger people (Karjaluoto et

al., 2003a; Karjaluoto et al., 2003b). By the use of a survey involving a sample size of 397,

they found that besides new technological advances, price was the most influential factor

affecting the choice of a new mobile phone model.

1.7.5 Brand Preference and Product Attribute

Attributes are the characteristic or features that an object may or may not have and

includes both intrinsic and extrinsic. Benefits are the positive outcomes that come from the

attributes. People seek products that have attributes that will solve their problems and

fulfills their needs. Understanding a consumer choose a product based upon its attributes

helps marketers to understand why some consumers have preferences for certain brands.

The Lancaster model of consumer demand (1966, 1979), also referred to as the product

attributes model, was used to evaluate brand positioning. This model assumes that

consumer choice is based on the characteristics (or attributes) of a brand. Each product is a

bundle of attributes and that choice is based on maximizing utility/satisfaction from the

attributes subject to budget constraints. Both tangible and intangible attributes of a product

are equally important in choosing a product or brand.

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CHAPTER TWO

REVIEW OF METHODS

Various statistical analysis tools have been used during the analysis of the data. Some of

the statistical tools were used in preliminary analysis as well as in further analysis. The

main statistical tools used are the chi-square analysis and factor analysis.

2.1 Factor Analysis

Factor Analysis is a statistical tool used to reduce the number of factors needed to explain

the variability in data. The major aim of factor analysis is the orderly simplification of a

large number of intercorrelated measures to a few representative constructs or factors

which can then be used for subsequent analysis. In other words, the latent factors

determine the values of the observed variables. Each observed variable (y) can be

expressed as a weighted composite of a set of latent variables (f's) such that

ikikiii efafafaY ++++= ...2211 (2.1)

Where

iy - the thi observed variable on the factors

ija - the loadings of the variables

jf - the factors

ie the residual of iy on the factors.

Given the assumption that the residuals are uncorrelated across the observed variables, the

correlations among the observed variables are accounted for by the factors. Factor analysis

is based on the assumption that all variables are correlated to some degree. Those variables

that share similar underlying dimensions should be highly correlated, and those variables

that measure dissimilar dimensions should yield low correlations. Analysis of variables

that share the same underlying dimensions should yield high correlation coefficient,

whereas test of different dimension should yield low correlation coefficient. These high

and low correlation coefficients will become apparent in the correlation matrix because

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they form clusters indicating which variables “hang” together. The primary function of

factor analysis is to identify these clusters of high intercorrelations as independent factors.

As factor analysis is based on correlations between measured variables, a

correlation matrix containing the intercorrelation coefficients for the variables must be

computed.

Determining the Number of Factors to be Extracted

There are two conventional criteria for determining the number of initial unrotated factors

to be extracted. These are the Eigenvalues greater than one criterion and the Scree test

criterion.

Eigenvalues: Only factors with eigenvalues of 1 or greater are considered to be

significant; all factors with eigenvalues less than 1 are disregarded. An eigenvalue is a

ratio between the common (shared) variance and the specific (unique) variance explained

by a specific factor extracted. The rationale for using the eigenvalue criterion is that the

amount of common variance explained by an extracted factor should be at least equal to

the variance explained by a single variable (unique variance) if that factor is to be retained

for interpretation. An eigenvalue greater than 1 indicates that more common variance than

unique variance is explained by that factor.

Scree Test: This test is used to identify the optimum number of factors that can be

extracted before the amount of unique variance begins to dominate the common variance

structure. The Scree test is derived by plotting the eigenvalues (on the Y axis) against the

number of factors in their order of extraction (on the X axis). The initial factors extracted

are large factors (with high eigenvalues), followed by smaller factors. Graphically, the plot

will show a steep slope between the large factors and the gradual trailing off of the rest of

the factors. The point at which the curve first begins to straighten out is considered to

indicate the maximum number of factors to extract. That is, those factors above this point

of inflection are deemed meaningful, and those below are not. As a general rule, the scree

test results in at least one and sometimes two or three more factors being considered

significant than does the eigenvalue criterion.

14

Interpreting Factors

In interpreting factors, the size of the factor loadings will help in the interpretation. As a

general rule, variables with large loadings indicate that they are set of indicators of the

factor, while small loadings suggest that they are not. In deciding what is large or small, a

cutoff point must be set such that a factor loadings greater than the cutoff point are

considered to meet the minimal level of practical significance. The grouping of variables

with high factor loadings should suggest what the underlying dimension is for that factor.

2.2 Chi–Square Analysis

The chi-squared test which is denoted by the Greek symbol2χ , is probably the most

commonly used test of statistical significance. It is a non-parametric test, since for the chi-

squared test there are no underlying assumptions that must be made about a normally

distributed population before the test can be considered to be appropriate.

Assumptions of Chi-square Analysis

One underlying assumption the chi-square has is that, observations are randomly

selected from some large population. If the observations are not randomly selected, then a

researcher must be very cautious about generalizing from the data set’s results back to the

larger population. A second assumption is that the number of expected observations within

a given category should be reasonably large, and more importantly, for a better

Chi – square approximation, no more than 20% of the expected frequencies should be less

than 5. The distribution depends on a number of degrees of freedom denoted by ν. It has a

mean v and variance 2v.

Tests for Independence/Association/Relationship

This application of the chi-squared test in testing of independence between two variables in

which one of the variable is classified into r classes and the other into c classes, gives a

cr × contingency table. A cr × contingency table format is a test of association between

mutually exclusive categories of one variable (given in the rows of the table) and mutually

exclusive categories of another variable (given in the columns of the table). It is a table of

frequencies showing how the total frequency is distributed among the cr × cells in the

15

table. The expected frequency for the cell in the i th row and j th column is( )

N

CR ii ×. The

2χ statistic is the sum of all ( )

E

EO 2− values for all the cr × cells.

The table below is an example of cr × contingency table with the number of degrees of

freedom ( )( )11 −−= crDF

TABLE 2.1: A cr × Contingency Table

The hypothesis which is tested is

H0: No relationship or association exists between the two variable classifications.

against

H1: Relationship or association exists between the two variable classifications.

The test statistic is given by

( )

ij

ijijc

j

r

i E

EO 2

11

2−

ΣΣ===

χ (2.2)

Where

ijO is the observed cell frequency for the (ij) th cell.

ijE is the expected cell frequency for the (ij) th cell.

16

The statistic under the null hypothesis has an approximately chi-square distribution with

the degrees of freedom given by( )( )11 −− cr . The critical region for the test at 00α

significance level is therefore, ( )( )[ ]1122 −−≥ crαχχ .

Table 1 in Appendix B gives the critical region for a particular α level and the various

corresponding degrees of freedom.

To chose between H0 and H1 we determine the critical region of the test. The critical region

is the set of values of the test statistic that will enable us to reject H0. The region is

determined using a pre-set level of significance. The level of significance, denoted byα , is

the probability of committing Type I error (that is, the probability of rejecting H0 when in

fact, it is true. Also, from computer output, the decision to reject or fail to reject H0 is

based on the valuep − of the test. The valuep − is the probability of observing a value of

the test statistic at least as extreme as that observed under the null hypothesis. Generally,

we reject H0 at level of significanceα , if valuep − less than α and fail to reject H0 if

valuep − greater thanα .

17

CHAPTER THREE

PRELIMINARY ANALYSIS

This chapter of the report presents how tables and graphs were used to analyze the data of

this research. The chapter also describes how the stated hypotheses in this research were

tested.

3.1 Mobile Phone Distribution by Gender

The table below displays the distribution of mobile phone used in terms of gender.

Table 3.1 Distribution of Mobile phone Ownership by Gender

It is shown in table 4.1 that, there is wide variation in the distribution of owned of mobile

phone. Out of the 300 respondents surveyed, 228 of them representing 76% owned mobile

phone, while 72 of the respondents representing 24% don’t own mobile phone.

The table also indicates that out of the 300 interviewed, 168 and 132 are males and

females respectively. Out of the 228 respondent who owned mobile phone, 130 of them

were males and 98 were females.

GENDER

Mobile Phone Ownership Male Female Total Percentage

Yes

No

130

38

98

35

228

73

76

24

TOTAL 168 132 300 100

18

3.2 Brand of Mobile phone Distribution

The figure below displays the distribution of mobile phone users among the various mobile

phone brands.

Figure 3.1: Distribution of Brands of Mobile phone

From Figure 3.1 above, the most used mobile phone among the respondents is Nokia

which represent 39.2% of all brands of mobile phone used by respondents. Motorola is the

next most used mobile phone which represents 16.7%. Also from the figure, the least

mobile phone used is LG with a percentage of 2.3.

The common mobile phone brands which were specified by the respondents who use none

of the listed brands of mobile phones are NEC and Alcatel.

3.3 Reasons by Respondents who do not use Mobile Phone

The figure below displays the most common reasons given by respondents who do not use

mobile phone.

0

5

10

15

20

25

30

35

40

45

Reason 1 Reason 2 Reason 3 Reason 4

REASONS FOR NOT USING MOBILE PHONE

NUMBER O

F R

ESPONSES (%)

Figure 3.2: Reasons by Respondents for not using Mobile phone

19

Reason 1 – High cost of purchasing mobile phone

Reason 2 – High cost of recharging units

Reason 3 – No need

Reason 4: Others

From Figure 3.2, it is shown that the most of the reasons why some of the respondents

don’t use mobile phone were “high cost of purchasing mobile phone” and “No need”.

These two reasons form a percentage of 38.6 and 35.6 respectively. Thus, many people do

not use mobile phone because of its high cost. Some also find it not necessary/important

for them to use mobile phone. The common reasons specified by the respondents include

unemployed and low income.

3.4 Reasons by Respondents who use More Than One Mobile Phone

The figure below displays the most common reasons given by respondents who use more

than one mobile phone.

2318

0

1217

35

0

5

10

15

20

25

30

35

40

Reason 1 Reason 2 Reason 3

REASONS FOR USING MORE THAN ONE MOBILE PHONE

NU

MB

ER

OF

RESPO

NSES

Ticked Not Ticked

Figure 3.3 Reasons why respondents use more than one Mobile phone

Reason 1 – To be in touch always

Reason 2 – To have access to different mobile phone network

Reason 3 – Others

20

It can be seen from Figure 3.3 that, out of the 35 respondents who use more than one

mobile phone, 23 of them use more than one mobile phone just because they want to be in

touch always. Also out of the 35 respondents who use more than one mobile phone 18 of

them use more than one mobile phone just because they want to have access to different

mobile phone networks. None of the respondents specified any other reasons why they

use more than one mobile phone.

3.5 Mobile Phone Cost

The table below displays the distribution of cost of mobile phone

Table 3.2: Distribution of Mobile phone Cost

From Table 3.2, it can be seen that, the modal class of mobile phone cost is “GH¢50 to

100” with a frequency of 111. Thus, the affordable mobile phone price ranges from GH¢50

to GH¢100.

Also, only few people purchased mobile phones that are expensive. This clearly

shows that, most people purchase mobile phone that is affordable.

Mobile phone cost (GH¢) Frequency

Below 50 36

50 – 100 111

110 – 150 49

160 – 200 16

210 – 250 11

260 and above 5

Total 228

21

3.6 Test of Hypothesis – 1

Statement of Hypothesis

H0: There is no relationship between mobile phone usage and educational level

H1: There is a relationship between mobile phone usage and educational level.

The contingency table below indicates the observed and expected frequencies for the

categories. Within each cell, the expected frequency is placed under the observed

frequency.

Table 3.3: Cross-tabulation of level of education against the owned of mobile phone.

Do you own Mobile phone

Level of Education Yes No Total

No School 9

20.52

18

6.48

67

First Cycle 48

51.68

20

16.32

68

Second Cycle 50

57.76

26

18.24

76

Third Cycle 121

98.04

8

30.96

129

Total 228 72 300

Chi-Square = 54.787 DF = 3 valuep − = 0.000

Decision and Conclusion

At 5% level of significance we reject the null hypothesis, since the valuep − of

0.000 is less than value−α of 0.05. We therefore conclude that, there is a relationship

between mobile phone usage and educational level. Thus, either a person use or does not

use mobile phone depends on his/her level of education.

22



H0: There is no relationship between mobile phone usage and occupational status.

H1: There is relationship between mobile phone usage and occupational status.



frequency.

Table 3.4: Cross-tabulation of occupational status against mobile phone usage

Chi-Square = 34.440, DF = 3, valuep − = 0.000


At 5% level of significance we reject the null hypothesis, since the valuep − of 0.000 is

less than value−α of 0.05. We therefore conclude that, there is a relationship between

mobile phone usage and occupational status. Thus, either a person use or does not use

mobile phone depends on his/her occupational status.

Do you own Mobile phone

Occupation Status Yes No Total

Student 90

82.84

19

26.16

109

Self-employed 48

47.12

14

14.88

62

Employee 85

82.08

23

25.92

108

Unemployed 5

15.96

16

5.04

21

Total 228 72 300

23



H0: There is no association between gender and brand of mobile phone used.

H1: There is association between gender and brand of mobile phone used.



frequency.

Table 3.5: Cross-tabulation of Mobile phone brands against Gender


GENDER Nokia Motorola Sony

Erickson

Samsung Siemens LG Others Total

Male 67

59.92

23

25.60

12

12.22

15

18.62

15

13.38

2

3.49

19

19.78

153

Female 36

43.08

21

18.40

9

8.78

17

13.38

8

9.62

4

2.51

15

14.22

110

Total 103 44 21 32 23 6 34 263

Chi-Sq = 6.382, DF = 6, valuep − = 0.382


At 5% level of significance we fail to reject the null hypothesis, since the valuep − of

0.382 is greater than value−α of 0.05. We therefore conclude that, there exist no

association between gender and the brand of mobile phone used by consumers. Thus,

either a person is male or female has nothing to do with the brand of mobile phone used.

24

Summary of Preliminary Analysis

The preliminary analysis of the data reveals that out the 300 respondents surveyed, 76% of

them owned mobile phone and also most people do not use mobile phone because of its

high cost. Others also finds the use of mobile phone not need/important.

The analysis also reveals that the most used mobile phone is Nokia and the affordable

mobile phone price ranges from GH¢50 to GH¢100. Most of the consumers use more than

one mobile phone just because they want to have access to different mobile phone

networks.

The hypothesis testing under this chapter revealed the following:

1. Gender of the consumer may not be an indicator of a factor that influences choice

of mobile phone brand.

2. Employment status may be an indicator of the factor that influences the use of

mobile phone.

3. Educational level attainment may be an indicator of a factor that influences the use

of mobile phone.

25

CHARPTER FOUR

FURTHER ANALYSIS

In this chapter we perform Factor Analysis to determine the major factors that influence

the choice of brand of mobile phone. The analysis under this chapter has been grouped in

various sub headings such as correlation analysis, total variance explained etc.

4.1 Correlation Analysis

The table below displays the correlation between the seven variables written to measure

the reasons for the choice of mobile phone brand.

Table 4.1: Correlation Matrix

X1 X2 X3 X4 X5 X6 X7

X1

X2

X3

X4

X5

X6

X7

1.000

0.350

0.121

0.127

0.079

0.137

0.154

.350

1.000

0.041

0.082

-0.047

0.149

0.041

0.121

0.041

1.000

0.189

0.139

0.052

0.233

0.127

0.082

0.189

1.000

0.260

0.120

0.394

0.079

-0.047

0.139

0.260

1.000

0.040

0.377

0.137

0.149

0.052

0.120

0.040

1.000

0.039

0.154

0.041

0.233

0.394

0.377

0.039

1.000

From the introduction, the variables were defined as follows:

X1 – Affordability

X2 – Fashionable

X3 –More features in the mobile phone

X4 – Reliability of the reception

X5 – High quality

X6 – Popularity

X7 – Portability

26

In considering a correlation coefficient of 0.2 or greater as being high, then we can see

from the matrix above that, there is a high correlation between the variables X1 and X2,

thus, as mobile phone becomes affordable, it also tend to be fashionable. Similarly,

variables X4, X5 and X7 has a high intercorrelation coefficient.

Table 4.2: Results of KMO and Bartlett’s Test of Significance

Kaiser-Meyer-Olkin Measure

of Sampling Adequacy.

Bartlett's Test of Sphericity

Approx. Chi-Square df Sig.

0.650 140.720 21 0.000

From table 4.2, the Bartlett’s test of Sphericity yield a value 140.720 and an associated

level of significance( )valuep − of 0.000 which is smaller than alpha (α) value of 0.05.

Thus, the hypothesis that the correlation matrix is an identity matrix is rejected, that is, the

correlation matrix has significant correlation among at least some of the variables and thus

supports the use of factor analysis.

4.2 Total Variance Explained

Although seven factors have been computed as shown in Table 4.3, it is obvious that not

all the seven factors will be useful in representing the list of all seven variables.

Table 4.3: Total Variance Explained Initial Eigenvalues Rotation Sums of Squared Loadings Component Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% Cumulative

% 1 2 3 4 5 6 7

1.953 1.346 0.920 0.871 0.734 0.620 0.557

27.902 19.223 13.143 12.440 10.480 8.850 7.962

27.902 47.126 60.269 72.709 83.188 92.038 100.000

1.834 1.464

26.205 20.921

26.205 47.126

1.834 1.464

27

Using the criterion of retaining only factors with eigenvalues of 1 or greater, the first two

factors will be retained for interpretation. These two factors accounted for 27.90% and

19.22% of the total variance, respectively. That is, 47.13% of the total variance is

attributable to these two factors. The remaining five factors together accounted for 52.87%

of the total variance.

The figure below show the scree plot of the eigenvalues of the seven variables against the

number of factors

Figure 4.1: Scree Plot of Eigenvalue against Number of components.

From the scree plot shown by Figure 4.1 above, the plot however, suggests a model with

three factors since the elbow of scree is on the third factor. But in considering the rule of

parsimony, we decided to use two factors instead of three factors.

28

4.3 The Component Matrix and Interpretation of Extracted Factors

The Component Matrix below represents the unrotated component analysis factor matrix,

and presents the correlations that relate the seven variables under study to the extracted

factors. In the table below, the coefficients, called factor loadings, indicate how closely the

variables are related to each factor. The correlation coefficients of 0.4 or greater are

considered to be high and otherwise low.

Table 4.4 Component Matrix

COMPONENT

VARIABLE 1 2 3

X7

X4

X5

X3

X2

X1

X6

0.729

0.679

0.581

0.485

0.298

0.468

0.281

-0.297

-0.163

-0.405

-0.097

0.741

0.590

0.401

-0.739

0.145

0.0813

-0.263

-0.206

-0.291

0.831

In Table 4.4 above, factor 1 contains four items (portability, more features in the mobile

phone, high quality and reliability of the reception) that has coefficient more than 0.4. This

clearly reflects a motive of reliable quality. Factor 2 also contains three items

(affordability, popularity and fashionable) that has coefficient more than 0.4. This clearly

reflects a motive of user-friendliness.

Thus, we can say that two factors determine customer choice of brand of mobile phone.

Although variable X6 has a higher factor loading of 0.831 under the third factor, but since

variable X6 has already been captured under factor two, consideration of the third factor is

not necessary.

29

Summary of Further Analysis

Based on the criterion of eigenvalues of 1 or greater, the decision of two factors model

from the list of seven variables was made.

Based on the component matrix in Table 4.4, conclusion on the factors that determine the

choice of brand of mobile phone(s) was made. This conclusion is that, consumer’s choice

on mobile phone brand is determine by

1. Reliable quality of the mobile phone brand

2. User-friendliness of the mobile phone brand

30

CHAPTER FIVE

SUMMARY, DISCUSSION, CONCLUSION AND RECCOMMENDATION

This chapter presents a general discussion on the results on the analysis of the preceding

two chapters. The chapter also assesses how far the objectives of the research have been

achieved. Comparison and contrasting of the findings in relation to the previous findings

are also presented.

5.1 Summary

The preliminary analysis of the data reveals that out the 300 respondents surveyed,

76% of them owned mobile phone and also most people do not use mobile phone because

of its high cost. Others also find the use of mobile phone is not a need. The analysis also

reveals that the most used mobile phone is Nokia and the affordable mobile phone price

ranges from GH¢50 to GH¢100. Most of the consumers use more than one mobile phone

just because they want to have access to different mobile phone networks. It was also

observed that gender of the consumer may not be an indicator of a factor that influences

choice of mobile phone brand. But employment status and educational level attainment

may be indicators of a factor that influence the use of mobile phone.

Finally, based on the results obtained from further analysis, consumers purchase

mobile phone based on two factors. That is reliable quality and user-friendliness of the

brand of mobile phone.

5.2 Discussion

The most predominant mobile phone brand used by the populace in Kumasi is

Nokia. The result is in agreement with the survey carried out by a television station in

Ghana (TV3 Network) in the year 2005, which indicated that Nokia is the most popular

brand in Ghana, also with Yan Xianpu (2004) report.

Contrary to the perception that different sex groups have interest in some mobile

phone brand, it was found out that, that perception is not entirely true since the test for

association could not confirm this. In fact, it was found out that males and females do not

differ in mobile phone preference. This is in sharp contrast to the report by the Chinese

31

Weekly, Yan Xianpu (2004) that when it comes to choice of brand of mobile phones, men

and women have different tastes.

From the results in the further analysis, the first factor (reliable quality) was also in

agreement with the study carried out by Laroche et al 2003. Thus, consumer selects a

brand which meets acceptable standards.

The results from both preliminary analysis and further analysis were also in line on

the basis of consumer based indicator. The preliminary analysis revealed that education

attainment and occupational status influence the choice of brand of mobile phone, while

the further analysis also reveals that user-friendliness (affordability, popularity and

fashionable) is a factor that determines the choice of brand of mobile phone.

In relation to the second factor, we can also say that mobile phone brands which are

affordable are more popular. The preliminary analysis which reveals that affordable mobile

phone price is between GH¢50 and GH¢100 suggest that for a mobile phone to be popular

within the public, price must also be affordable.

Although variable X6 has a higher factor loading of 0.831 under the third factor, but

since variable X6 has already been captured under factor two, then consideration of the

third factor is not necessary. So the suggestion made by the scree plot on the addition of

the third factor was rejected.

5.3 Conclusion

The objective of this research was to investigate the underlying factors that

determine the choice of brand of mobile phone. The study found that two factors influence

consumer’s choice of mobile phone brand. The first most important factor is reliable

quality of the mobile phone brand and the other factor is user-friendliness of the brand of

the mobile phone.

The theoretical part of the study outlined two hypotheses that were supported by

the empirical studies. Hypothesis 2 argued that occupational status has an influence on the

choice of brand of mobile phone. This was verified in the preliminary analysis in which we

showed that specifically occupation are significant variables affecting choice.

Hypothesis 3 claimed that educational level attainment influences consumer choice of the

mobile phone model. This hypothesis got strong support in the studies.

32

From a theoretical viewpoint, this study contributed to the buying decision making

process for mobile phones by looking at consumer motives and examining the importance

of different attributes affecting the actual choice.

5.4 Recommendation

We therefore recommend that, as manufacturers of different mobile brands are improving

on the quality of the brand, they should also consider the price of selling it so as to make it

affordable to all persons.

Also, the most remarkable implication for mobile phone manufactures, sellers and other

value chain members is that advertising of the new mobile phone brands should go beyond

highlighting its properties to assured the quality and the user-friendliness of the mobile

phone.

33

REFRENCES

Assael, H. (1995). Consumer Behavior and Marketing Action. 5th ed. Cincinnati, Ohio: ITP, South-Western College Publishing. Benady, D. (2002). As simple as one-two-3G. Marketing Week, 26-29. Drucker, E. (2004). Perceived speed key to 3G success. 3G’s commercial success depends on carriers’ ability to deliver coverage and account for channel loading. Dorsch, M.J., Grove, S.J. and Darden, W.R. (2000). Consumer intentions to use a service category. Journal of Services Marketing, 14 (2), 92-117. Fitzsimons, G.J., Hutchinson, J.W., Williams, P., Alba, J.W., Chartrand, T.L., Huber, J., Kardes, F.R., Menon, G., Raghubir, P., Russo, J.E., Shiv, B. and Tavassoli, N.T. (2002). Non-conscious influences on consumer choice. Marketing Letters, 13 (3), 269-279. Gordor B.K., Innocent G.A., Howard N.K. (2006). A Guide to Questionnaire Surveys. Ghana Mathematics Group. Accra, Ghana. Gordor B.K., Innocent G.A., Howard N.K. (2006). Introduction to Statistical Methods. Ghana Mathematics Group. Accra, Ghana. Graham U., Ian C. (2004). Oxford Dictionary of Statistics. Oxford University Press Inc., New York. Heikki K., Jari K., Manne K., Timo K., Marjukka M., Jukka P., Annu R. (2005). Factors Affecting Consumer Choice of Mobile Phones. The Haworth Press, Inc. Hianchi, W. (2004). Mobile Usage in Korea. Brandstock.

Hansen, L. (2003). Service layer essential for future success. Ericsson Mobility World, General article, (June), available at: http://www.ericsson.com/mobilityworld/sub/articles/other_articles/nl03jun05.

Karjaluoto, H., Karvonen, J., Pakola, J., Pietilä, M., Salo, J. and Svento, R. (2003a). Exploring consumer motives in mobile phone industry: An investigation of Finnish mobile phone users. Proceedings of the 1st International Conference on Business Economics, Management, and Marketing (Athens, Greece), 3, 335-342.

Karjaluoto, H., Pakola, J., Pietilä, M. and Svento, R. (2003b). An exploratory study on antecedents and consequences of mobile phone usage in Finland. Proceedings of the AMA Summer Marketing Educators’ Conference (Chicago, USA), 14, 170-178. Lindholin et al (2003). The Mobile Technology: www.mobile.tech.com

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Loehlin, J.C. (1992) Latent Variable Models. Erlbaum Associates, Hillsdale NJ. Marcus G. (2002).Global Mobile Phone usage. www.norkia.com. Matilda, A. (2004). Mobile Phone Subscription in Ghana. Daily Graphic.136754, pp13. Nagel, A. (2003). Beyond Knut Holt’s Fusion model, balancing market pull and technology push. International Journal of Technology Management, 25 (6-7), 614-622. Nokia (2004). Nokia closes 2003 with excellent fourth quarter. Press Release 2004, (January), available at: http://press.nokia.com/PR/200401/931562_5.html Philip, J. (2006). Mobile Phone Preferences in Belarus. E – Belarus.org Sehovic, A. (2003). The whole world in 3G: The right choice ... GSMBOX, Ltd., Mobile News, Third Generation, available at http://uk.gsmbox.com/news/mobile_news/all/ 95639.gsmbox. Sehovic, A. (2004). The end of the beginning? GSMBOX, Ltd., Mobile News, Third Generation, available at: http://uk.gsmbox.com/news/mobile_news/all// 97957.gsmbox Solomon, M.R. (2001). Consumer Behavior. Buying, Having, and Being. 5th ed. NJ: Prentice-Hall. Slovic, P. (1995). The construction of preference. American Psychologist, 50 (August), 364-371. Vaananen–Vinu–Mattila and Ruuska. (1999). Mobile Phone user Interface Development. www.samsung.com. Wireless Week, (February), available at: http://www.wirelessweek.com/article/CA381643. Yan Xianpu (2004). Mobile Phone Production and Sales in China. China Business Weekly

35

APPENDIX A

SPECIMEN OF THE QUESTIONNAIRE USED



QUESTIONNAIRE ON:

FACTORS THAT DETERMINE CHOICE OF BRANDS OF MOBILE

PHONE(S)

The questionnaire is being used to find out factors that determine choice of brand of

mobile phone(s).Your responses will be used purely for academic purpose; hence

confidentiality and anonymity are assured.

INSTRUCTIONS:

Please read the following questions carefully – Tick [√] appropriate answer(s) in the

boxes provided and specified where necessary. Thank you

SECTION A

1. Gender Male [ ]

Female [ ]

2. Age Under 18 years [ ] 18 – 30 years [ ] 31 – 40 years [ ] 41 – 50 years [ ] Over 50 years [ ]

3. Level of education

No school [ ] First cycle [ ] Second cycle [ ] Third cycle [ ]

36

4. Occupational status Student [ ] Self-employed [ ] Employee [ ] Unemployed [ ]

5. What is your income level on the average? Below GH¢100 [ ] GH¢100 – GH¢199 [ ] GH¢200 – GH¢299 [ ] GH¢300 – GH¢399 [ ] GH¢400 – GH¢499 [ ] GH¢500and above [ ]

6. Do you own a mobile phone?

Yes [ ] No [ ]

If No, please go to section C

SECTION B

Mobile phone users only

7. Which brand of mobile phone do you use? Tick as many as apply. Nokia [ ]

Motorola [ ] Sony Erickson [ ] Samsung [ ] Siemens [ ] LG [ ] Other (specify)…………………………………………..……………….

If you use only one mobile phone, please don’t answer question 8.

8. What is or are the reason(s) for using two or more mobile phone? Tick as many as apply.

To be in touch always [ ] To have access to different mobile network [ ] Others (specify)……………………………………………….……….

37

9. What is or are the reason(s) for your chose in question 7 above? Tick as many as apply.

Affordability [ ] Fashionable [ ] More features in the mobile phone [ ] Reliability of the reception [ ] High quality [ ] Popularity [ ] Portability [ ] Others (specify)……………………………………………………………

10. How much does your mobile phone cost?

Below GH¢50 [ ] GH¢50 – GH¢100 [ ] GH¢110 – GH¢150 [ ] GH¢160 – GH¢200 [ ] GH¢210 – GH¢250 [ ] GH¢260 and above [ ]

11. Do you have any intention of changing your brand of mobile phone?

Yes [ ] No [ ]

If No, please don’t answer question 12 and question 13.

12. What is or are the weakness(s) of your present mobile phone used that necessitates a change to another mobile phone brand? Tick as many as apply.

Few features [ ] Low quality [ ] Outmoded [ ] Unreliability of reception [ ] Not portable [ ] Not popular [ ] Others (specify)……………………….…………………………………

13. Which mobile phone brand do you wish to change to?

Nokia [ ] Motorola [ ] Sony Erickson [ ] Samsung [ ] Siemens [ ] LG [ ] Other (specify)…………………………..………………………………..

38

SECTION C

Non users of mobile phone only

14. What is or are the reason(s) for not using a mobile phone? Tick as many as apply. High cost of purchasing mobile phone [ ]

High cost of recharging units [ ] No need [ ] Others (specify)……………………………………………….……….

15. If you decide to own a mobile phone today, which brand of mobile phone will you

purchase? Nokia [ ] Motorola [ ] Sony Erickson [ ] Samsung [ ] Siemens [ ] LG [ ] Other (specify)…………………………………….…………………..

16. What is or are the reason(s) for your chose in question 15 above? Tick as many as

apply. Affordability [ ] More features in the mobile phone [ ] Fashionable [ ] Reliability of the reception [ ] High quality [ ] Portability [ ] Popularity [ ] Others (specify)…………………………………………………………….

39

APPENDIX B

Table 1: The Chi-Square Probability Table

α

Degrees of

Freedom 0.95 0.90 0.70 0.50 0.30 0.20 0.10 0.05 0.01 0.001

1 0.004 0.016 0.15 0.46 1.07 1.64 2.71 3.84 6.64 10.83

2 0.10 0.211 0.71 1.39 2.41 3.22 4.61 5.99 9.21 13.82

3 0.35 0.584 1.42 2.37 3.67 4.64 6.25 7.82 11.35 16.27

4 0.71 1.064 2.20 3.36 4.88 5.99 7.78 9.49 13.28 18.47

5 1.15 1.610 3.00 4.35 6.06 7.29 9.24 11.07 15.09 20.52

6 1.64 2.204 3.83 5.35 7.23 8.56 10.65 12.59 16.81 22.46

7 2.17 2.833 4.67 6.35 8.38 9.80 12.02 14.07 18.48 24.32

8 2.73 3.490 5.53 7.34 9.52 11.03 13.36 15.51 20.09 26.13

9 3.33 4.168 6.39 8.34 10.66 12.24 14.68 16.92 21.67 27.88

10 3.94 4.865 7.27 9.34 11.78 13.44 15.99 18.31 23.21 29.59

Eric and bright

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