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ABSTRACT

Consumer preference toward music channels. The report studies the music industry and

identifies the reason of surges and its future potential. The research looks at factors such increase

in variety of programs, make the timing of programs which is suitable to viewers, introducing of

good anchors/VJs, organize different events etc. to determine the consumer preferences toward

music channels. Questionnaires were distributed to general public, managers and student to find

out their preferences toward music channels. The data was collected from the four different

towns of Karachi (New Karachi, Gulshan-e-Iqbal, Saddar, North Nazimabad). The finding of the

research is base on cross tabs and according to this the results I found is that there is a correlation

between timing, anchors/VJs, loyalty variety of shows quality of programs and organize differentevents variables but the strength of relationship is weak.

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INTRODUCTION

In this report I study about the consumer preference toward the music channels. To prepare a

report I have to describe the objective about this report, which contains a detailed view of the

tasks, which have been undertaken to analyze the industry of music channels. Various sets of

questionnaire have been prepared to know the preferences of consumers about the music

channels.

The main data collection techniques which are being used for this research project are

questionnaire and secondary data which is literature review.

Pakistani music has certainly proved to be the food of love - and so it plays on. It appears as if

the floodgates have been opened for foreign entertainment and news channels. The last couple of

years have seen an invasion by cable channels, which can be seen wherever you go, from

restaurants and homes to shops. This is all part of the phenomenon called globalization.

Pakistani viewers, noticeably, are losing interest in local channels because of the glitz and

glamour of the foreign media. It is easy to see that the majority of images beaming out of

television sets are of foreign films and shows. Viewers countrywide prefer Indian music, films

and Hollywood flicks and this has resulted in the local channels being relegated to thebackground.

Well, out of all the Pakistani music, drama and film channels, only the music channels have

emerged as competition for these foreign channels. Channels like AAG, THE MUSIK, PLAY

TV, IM/MTV and OXGENE are fighting hard to hold on to the dwindling number of their

viewers, who are now more interested in soaps on Indian or other foreign music channels.

However, Pakistani music channels are not only fighting off competition from abroad, but

actually winning new audiences day by day. Today, because of these music channels, local bands

and singers like Atif, Jal, Noori and Junoon are more popular than any foreign band or singer.

The concerts of these artists and bands are well attended and their albums gross well because

their videos are shown on local music channels. The loyal viewers of these channels are helping

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pop musicians win the war and push out western and Indian music.

The music industry has come a long way in a very short span of time (considering the fact that

six years ago there were no music channels). Today, it is a complete industry with local music

channels dedicated to bringing forward Pakistani talent and the channels websites helping

expose several local bands and artists doing various genres of music from rock to classical. A

testament to the music channels evolution is the type of colourful graphics and programming.

Vast audiences from India, Canada and North America watch two of the leading music channels

of Pakistan, Indus Music/MTV and The Musik. These days, the most requested videos on several

Indian channels are those of Pakistani artists. This is a great sign, which shows that the countrys

music channels are all doing well internationally.

These channels have promoted pop music so well that channels like HUM TV and Geo TV now

air Pakistani artists music videos during prime time viewing. This clearly shows a change in the

trend of viewing, which has now shifted from dramas and sitcoms to music videos. The rise of

music as a viably commercial pursuit of art has given Pakistani talent an avenue towards which

they can direct their energies. The Pakistani youth can now express themselves through music

videos. At the moment, young music directors are producing visually stunning work.

Today local music channels stand out among all the private Pakistani channels. With witty and

educated presenters and colorful sets, Indus Music/MTV, The Musik, Aag, Play TV, and

Oxygene. One can proudly say that Pakistani music channels industry can now match foreign

music channels.

The Key players in the music industry in Pakistan.

1. AAG TV

2. PLAY TV

3. IM/MTV

4. THE MUSIK

5. OXYGENE

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OVERVIEW OF MUSIC CHANNELS:

ABOUT AAG TV

Launched on September 1, 2006, AAG exudes infinite energy. It is a youth based television

channel that is all set to educate, encourage and entertain its viewers with programs that are

thought provoking and provide an ultimate viewing experience while empowering the youth.

AAG is truly a platform where the youth has the prerogative to voice its opinion and speak the

mind. The youth of AAG is no ordinary youth, it is the one that has the courage to "question"

and also find answers. AAG is exclusively and essentially a youth based television channel with

a primary target audience ranging between the ages 15 and 25. However, age does not become an

impediment; AAG also grips those young at heart! The youth of AAG is firmly focused on its

dreams and aspirations; it is the progressive youth that thinks beyond boundaries. It has thedesire and propensity to "question". The youth of AAG stands out! AAG is the space for high-

spirited youth who has the audacity to discover themselves by taking up challenges, bonding

with the fraternity, and being real, while forming a strong community of youth with a passion

that is relentless. AAG provides refreshing and energized televiewing and endeavors to offer its

viewers 'viewing that grips' through a diverse range of programs that are meant to captivate

viewers. One of AAG's distinctive features is it offers a wide range of genres including music,

sitcoms, VJ shows, talk shows, debate shows, to name a few. AAG speaks the language of youth

and it does that eloquently. With programs like Cell 224, Pappu Yaar, Aaminah Haq Show,

Music Mastermind and many more, which are AAG's channel drivers, AAG has a

multidimensional relationship with the youth. It has all the tenderness to become a third parent, it

can serve as an institution to act as a teacher and it has the affection and trustworthiness to

become a close friend.

AAG's VJs, popularly known as the NAUJAWANS, represent different segments of the society.

These Naujawans are anything but your average, ordinary, everyday youngsters. In fact. The

Naujawans represent the channel committee for AAG and act as a council of advisors. Since

these Naujawans are the youth and also represent them, Naujawans are in a better position to

understand their hopes, dreams and aspirations.

ABOUT INDUS MUSIC(MTV)

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INDUS TV entered the Pakistani market in 2000 with the launch of its flagship channel INDUS

VISION - the first independent satellite channel and Pakistans favorite entertainment channel.

We captured the imagination of Pakistani viewers, primarily the youth of Pakistan. INDUS

VISION has been credited with many firsts and produced some of the most memorable content

in Pakistans entertainment industry. INDUS VISIONs morning transmission, childrens

programming, dramas, and tributes have received wide acclaim. INDUS VISION also boasts a

variety of popular live interactive shows of different genres. The overwhelming response from

our audience brought about INDUS MUSIC - Pakistans premiere music channel. INDUS

MUSIC or IM, as it is popularly known, has an ever growing enthralled interactive audience

domestically and internationally. INDUS MUSIC represents the music scene from Pakistan. In

November 2006, MTV Networks International, owned by Viacom Inc. (NYSE: VIA, VIA.B),

announced the launch of one of its most popular brands, MTV in Pakistan. MTV has been

launched through a Licensing agreement with INDUS TV, one of the leading satellite channel

groups in the country. MTV PAKISTAN replaced INDUS MUSIC to represent the music scene

from Pakistan.

ABOUT PLAY TV

Play is a music and lifestyle channel geared towards the youth of today. We believe that

entertainment is not limited to mindless eye candy: there's enough of that around, and everyone'shungry for more. Our programs are geared to engage the audience, to be informative while

challenging norms, sharing new perspectives and inspiring change, whether it's through the

content of a program or its creative visualization. Our directors come from all over the world,

and each one has a unique vision which translates into innovative, aesthetically strong

programming, from comedy to motivational talk shows to live jams featuring known and

unknown artists.

Content, however, has no weight without context. Our programs remain relevant to the interests

of today's youth, who make up more than half the nation's population. We believe in diversity,

and therefore encourage cultural exchange, whether it's through sponsoring foreign musicians to

perform in Pakistan, or promoting our own lesser known talent. Thus, PLAY actively provides

new and potential talent with a platform on which they can explore their flair for becoming

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involved in the rapidly growing field of media in Pakistan, either as musicians, producers,

directors or hosts.

ABOUT OXYGENE TV

Launched on January 24,2009, Oxygene exudes infinite energy. It is Music & Lifestyle based

television channel that is all set to provide quality entertainment on a continuous basis through

superior song selection and placement to its viewers. Oxygene is truly a platform where the

music lovers have the prerogative to voice its opinion and speak the mind. The viewer of

Oxygene is no ordinary viewer, it is the one that has the courage to "question" and also find

answers. Oxygene is exclusively and essentially Music & Lifestyle based television channel with

a target audience ranging between the ages 15 and 45. However, age does not become an

impediment; Oxygene also grips those young at heart! The viewer of Oxygene stands out!

Oxygene is the space for high-spirited people who have the audacity to discover themselves by

taking up challenges, bonding with the fraternity, and being real, while forming a strong

community of people with a passion that is relentless.

ABOUT THE MUSIK

ARY MUSIK launched from Dubai in 2003 under the leadership of the CEO Salman Iqbal and

multiple Award Winner VP Wiqar Ali Khan. It is now under the leadership of Danish Khawaja,

who once headed the ARY Creative Workshop, ARY Musik focuses especially on South Asian

communities throughout the world, particularly in Pakistan, Middle East and Europe. It is a part

of the ARY Digital Network.

ARY Musik channel is famous for being the first Pakistani channel to start pure youth reality

based shows that are groundbreaking.

In terms of format, ARY Musik caters to all age audiences, offering round-the-clock-music in all

genres such as pop, rock, Bhangra, Classical, and folk. It has interactive shows, celebrity

interviews, comic fillers, theme shows, imaginative animations, live concerts, and exclusive

unplugged performances. The channel's longest running international music based show was

"Music Hour with Wiqar Ali Khan" hosted in English and Pushtu, Rock On is also the longest

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running rock music based show in the Pakistan. Another popular reality show is "Living on the

Edge".

ARY Musik also broadcasts debates on current affairs, talk shows, live interactive request shows,

countdown programs and music videos. ARY Musik features Pakistani, Arabic, English and

international music with weekly and daily shows including chartbusters, countdowns, gossip,

behind-the-scenes (Hollywood and Bollywood), fashion around the world, as well as requests

and dedications from viewers around the globe.

ARY Musik is one of the first Satellite channels having live link-ups between its studios based in

London UK, USA, Pakistan, India and Dubai.

LITERATURE REVIEW

Consumer preference analysis involves the concept of utility, which refers to individual

customers satisfaction from achieving a definite structure of consumption. Since a direct

measurement of satisfaction level is not possible, theory of economics applies the concept of

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consumer preference instead, to quantify utility to some extent (Andrzej Bak & Aneta

Rybicka).

The literature on how people value nontraditional and New Urbanism characteristics provides a

valuable view of the topic, but an alternative methodology may allow us to add to our

understanding of peoples choices. We provide an alternative way of looking at the market for

some of these character tics by using a specialized survey design:

Choice-based conjoint analysis (Louviere 1988). This approach allows us to give people

randomized hypothetical combinations of characteristics of potential neighborhoods (but hold

house characteristics constant) and to analyze choices in the context. This methodology is similar

to the standard hedonic price model in that we can estimate the implicit prices that people are

willing to pay for certain characteristics of the housing bundle (Sheppard 1999).

Instruments for analyzing consumer preferences and integrating this information into the product

development process are indeed available, the question on a possible role for consumer policy in

furthering consumer-oriented innovation will be addressed. It is widely accepted that there is a

role for public policy in furthering innovation, but it is usually restricted to technology

development and knowledge transfer between research organizations and companies and does

not take consumer issues into account. It will be shown that the classical instruments of

innovation policy support of R&D, education of a qualified workforce, support of knowledge

transfer are at least more important for consumer-driven innovation than for technology-

driven innovation. In addition, it will be argued that consumer policy and its classical

instruments can have a role in furthering information as well. Examples of classical

instruments with an innovation aspect are consumer access to complaint handling, which

generates data that can be fruitfully exploited in innovation processes, and product tests, that

have a direct impact on manufactures product development. Such as classic instrument could

be expend by new forms of dialogue for a that have the aim of facilitating the information flowbetween consumers and producers in such a way that the consumer-oriented development of

new products is facilitated (Grunert, K.G. 2006).

Market research often focuses on determining consumer preferences in a variety of dimensions

and matching those preferences with product and service feature changes and enhancements. The

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purpose of this project is to develop a system of cooperating agents which can by continuously

searching for emerging consumer preference patterns in an on-line, dynamic, and informational

rich database. Research by one of the authors provides the data collection apparatus which is

used for the agent society in the current research. That apparatus is detailed briefly below

followed by a description of the agent society (Basil Englis & Rob Nehmer).

The requests of the consumer and the counter offers of the producer are represented as vectors,

where each element in the vector corresponds to the value of a feature. The requests of the

consumers represent individual wine products whereas their preferences are constraints over

service features. For example, a consumer may have preference for red wine. This means that the

consumer is willing to accept any wine offered by the producers as long as the color is red.

Accordingly, the consumer generates a request where the color feature is set to red and otherfeatures are set to arbitrary values (Reyhan & Pinar).

Consumer research often discusses the impact of variety in choice set on consumer preferences.

Extant studies have put forward two different perspectives. One perspective is that the choice set

with larger variety will enhance consumer preferences. For example, there will be more chances

to match the individual's preferences (Lancaster, 1990), a proposition consistent with the view

that larger variety might influence preferences by creating a perception of freedom of choice

(Brehm, 1972) and there will be less chance that the potential alternative will not be in the

choice set (Greenleaf & Lehmann, 1995; Kami & Schwartz, 1977).

However, the conflicting perspective is presented that more variety will have a negative effect on

consumer choice, and will weaken consumer preferences. For example, to evaluate the

attractiveness of a large variety of alternatives requires more effort, and increases the needs of

individual's cognitive resources (Huffman & Kahn, 1998; Scammon, 1977; Shugan, 1980).

The two different perspectives imply that the impact of variety on consumer preferences is

decided by whether information overload happens. Before information overload happens, the

greater the variety, the better. However, after information overload occurs, increasing the amount

of variety will confuse consumers and weaken the preferences.

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If the impact of variety on consumer preference varies with different people, then obviously the

strategy that marketers adopt to achieve maximum consumer preferences will be an important

research topic. The present study proposed that a large variety with partial alternatives

recommended would better enhance consumer preferences than simply a large or small variety.

This is because if a large variety has a positive effect on consumer preferences but cannot avoid

the negative effect of information overload, then a large variety with partial alternatives

recommended is expected to have the advantages of a large variety, and yet is expected to avoid

disadvantages caused by a large variety through limited recommendation. The impact on

consumer preferences is also expected to be positive. In addition, relevant research has also

lacked discussion on the impact of recommended variety (Chien-Huang & Pei-Hsun 2006).

From the perspective of resource matching (Anand & Sternthal, 1989), the level of variety thatwill cause information overload varies for different people. People with a high need for cognition

(NFC) have more available cognitive resources, and are more likely to use systematic rules to

process information when facing a large variety than when dealing with a small variety. People

with a low NFC have fewer cognitive resources, and most probably use systematic rules to

process information when facing a small variety rather than a large variety. An individual using a

systematic information process carefully conducts a tradeoff among attributes, and is expected to

have confidence in the chosen option. This may cause NFC to become the important factor that

moderates the impact of variety on consumer preferences.

Relevant literature on the consumer's strategy of using recommendations, has pointed out that

consumers can obtain the recommended alternatives from some resources and form the intention

of purchasing this recommended brand, without considering the information of the attributes'

value (Olshavsky & Granbois, 1979). This strategy is more likely to be adopted when the

consumer feels that the decision making time is limited or when those making the

recommendations are a special knowledge resource.

Consumer preference denotes consumers ability to evaluate, prioritize and choose goods offered

on the market on specific terms. In case the evaluation refers to goods or services of the same

class, it may be possible to quantify relations between those products. In theory of economics

those relations are referred to as preferences since they provide information on customers

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attitudes toward specific products which allows building product hierarchy from the least to the

most preferred (ordinal scale measurement) or quantitative evaluation of each product (interval

scale measurement). Preference analysis makes it possible to describe and account for consumer

behavior with reference to marketed goods or services (Andrzej Bak & Aneta Rybicka).

The satisfaction of social and psychological consumers needs is increasingly driving the product

development process, owing mainly to changes in the consumption patterns of the population

and the optimization of physiological needs (Sijtsema et al., 2002). In high income countries it

has been determined that a complex set of factors has changed consumer buying patterns

(Senauer, 1995; 2001; Kinsey et al., 1996). Changes in demographic and socio-cultural

variables, consumer attitudes and the development of new lifestyles define the consumer

preferences.

ANALYSIS OF CONSUMER PREFERENCES

Conjoint analysis (CA) was the method used to investigate consumer preferences; this is defined

as a decomposition method that disaggregates the structure of consumer preferences into utility

values. As well, the method allows for estimating the relative importance of the attributes of a

product (Green and Srinivasan, 1978; Harrison et al., 1998; 2001). CA is currently being used

broadly in market research (Cattin and Wittink, 1982; Wittink and Cattin, 1989; Wittinket

al., 1994; Green et al., 2001). The main reason for the recent popularity of CA is its high degree

of flexibility to study a wide range of purchasing decisions involving many attributes (Harrison

et al., 2001). The method allows for estimating part-worth utilities for each level of an attribute.

In other words, this technique provides a utility function for each level of each attribute (Green

and Wind, 1975). The estimated part-worth utilities indicate how influential each attribute level

is in the formation of consumer preferences for a particular combination, that is, they represent

the degree of consumer preference for each level of each attribute ( Wang and Sun, 2003). To be

valid in an analysis of preferences, the total utilities of each combination (product profile) should

be highly correlated with the observed preferences, in other words, they should correspond to the

original ranks as closely as possible (Green and Wind, 1975; Aaker et al., 2003).

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CONSUMER ATTITUDE

An attitude is a positive or negative evaluation of a social object or action. A social object in the

present context might mean the water company, water regulations, supply system and service, or

the water itself. Many theories of attitudes (theory of planned behavior, Ajzen, 1985) have

attitude as a factor involved in determining behavioral choices however there is considerable

continuing debate about when, and in what circumstances, attitudes are important determinants

of behavior. An attitude toward something should thus not be taken to imply that attitude-

consistent behavior will automatically follow.

EFFECT OF RECOMMENDATION

Based on the advantageous and disadvantageous factors put forward by past studies on

the effect of variety on consumer preferences, we expected that a large variety with

partial alternatives recommended would significantly affect consumer preferences. This

is because this strategy not only keeps the advantages of large variety on consumer

preferences, but also, through limited recommended alternatives, avoids the

disadvantages of information overload caused by large variety. Therefore, after choice,

the preferences expectation for the chosen option will be stronger than when choosing

purely from a large or small variety (Chien-Huang & Pei-Hsun 2006).

PREFERENCE LEARNING

As an alternative, we propose an architecture in which the service providers learn the relevant

features of a service for a particular customer over time. We represent service requests as a

vector of service features. We use ontology in order to capture the relations between services and

to construct the features for a given service. By using a common ontology, we enable the

consumers and producers to share a common vocabulary for negotiation. The particular service

we have used is a wine selling service. The wine seller learns the wine preferences of the

customer to sell better targeted wines. The producer models the requests of the consumer and its

counter offers to learn which features are more important for the consumer. Since no information

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is present before the interactions start, the learning algorithm has to be incremental so that it can

be trained at run time and can revise itself with each new interaction (Reyhan & Pinar).

In the operations literature, postponement has long been proposed as a strategy to mitigate the

high cost of offering large product variety (Lee 1996, Lee and Tang 1997, Swami Nathan and

Tayur 1998, Swami Nathan and Lee 2003). Our mass customization is based on delayed

product differentiation and we explicitly include customer preferences, which are not considered

in the postponement literature. Krishnan and Ulrich (2001) reviewed the product development

literature, which includes product design and variety problems.

THE VEBLEN EFFECT: PERCEIVED CONSPICUOUS VALUE

Several researchers conducted studies based on the original work of Bourne (1957), whichfocused on the influence of reference groups on the consumption of prestige brands

(Mason 1981 and 1992; Bearden and Etzel 1982). These authors found that the

conspicuousness of a product was positively related to its susceptibility to reference-group

influence. For instance, Bearden and Etzel (1982) concluded that publicly consumed luxury

products were more likely to be conspicuous products than privately consumed luxury

products.

Conspicuous consumption still plays a significant part in shaping preferences for many

products which are purchased or consumed in public contexts (Braun and Wicklund 1989;

Hong and Zinkhan 1995; Bagwell and Bernheim 1996; Corneo and Jeanne 1997).

Thorstein Veblen (1899) many years ago suggested that conspicuous consumption was used

by people to signal wealth and, by inference power and status. Thus, the utility of prestige

products may be to display wealth and power and one could consider that highly visible

prestige brands would dominate the conspicuous segment of the consumers.

Several authors have also demonstrated that the price of products may have a positive role

in determining the perception of quality (Erickson and Johansson 1995; Lichtenstein,

Bloch, and Black 1988; Tellis and Gaeth 1990). These studies revealed that consumers

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often used the price cue as evidence for judging quality when choosing between different

brands. In practice, a higher price would infer a higher level of quality. In addition,

research which suggested that consumers who perceived price as a proxy for quality, also

perceived high prices as a positive indicator suggesting a certain degree of prestige

(Lichtenstein, Ridgway, and Netemeyer 1993). Thus, consumers would use a price cue as

a surrogate indicator of prestige.

THE PERFECTIONISM EFFECT: PERCEIVED QUALITY VALUE

In addition, the studies exploring issues related to luxury consumption often underline the

specific function of quality. "Excellent quality is a sine qua non, and it is important that thepremium marketer maintains and develops leadership in quality" (Quelch 1987). Prestige brands

are expected to show evidence of greater quality, and luxury or premium brands should display

even greater levels of quality (Garfein 1989; Roux 1995). In practice, "high prices may even

make certain products or services more desirable" (Groth and McDaniel 1993,) because people

perceive higher prices as evidence of greater quality (Rao and Monroe 1989). Based on these

studies and on the available literature on luxury products, it was proposed that the quality cue

might also be used by consumers to evaluate the level of prestige of brands. For example, we

assume that a low level of quality would play a negative role over the perception of prestige.

PRICE DISCOUNT

To counter fierce competition, businesses often use promotions to stimulate purchase

intention and Increase sales considers that promotion is a combination of various

incentives to stimulate Consumers or retailers to stir up immediate purchasing reaction

toward a product or service within a short period of time. McCarthy and Perrault (1984)

think promotion is different from advertisement or public report and eventually can stir

up interest or intention among (potential) buyers to make a purchase. Thus, promotion

aims to create product exposure, stimulate desires, maintain consumer loyalty and raise

sales Consumers respond to the incentive of saving when they see products are being sold

at a lower price, and increase their purchase intention. Since consumers usually make an

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immediate purchase, when being seduced by economic incentives, the greater the

promotion is, the more response it generates. (Rehamn, 2009) Have proven that when

facing various brand products with similar functions and qualities, promotional items

usually end up selling better and even attract loyal consumers of other brands. Thisindicates promotion has great incentive values. When consumers are presented with great

incentives, they are likely to choose promotional items.

PURCHASE INTENTION

Prior to purchasing, consumers begin by collecting product information based on personal

experience. And external environment. When the amount of information reaches a certain level,

consumers start the. Assessment and evaluation process, and make a purchase decision after

comparison and judgment. Therefore, purchase intention is often used to analyze consumer

behavior in related studies. The so-called purchase intention means a subjective inclination

consumers have towards a certain product, and has been proven to be a key factor to predict

consumer behavior(Bruks, 2009).

Chen et al. (1998) study a product line design problem with one physical attribute defined on a

line segment. Joint inventory and product selection problems have been studied by Van Ryzin

and Mahajan (1999) and Smith and Agrawal (2000). The marketing and manufacturingcoordination problem under flexible manufacturing system was first considered by de Groote

(1994). The focus is on the flexibility of the manufacturing system and the breath of the product

line; customization is not considered. Research in design for variety provides practical

methodologies using index-based measures to quantify a wide range of costs of offering variety.

The goal is to reduce those costs early in the Design phase of the product life cycle

(Ishii et al. 1995,Martin and Ishii 2000). Also in the operations literature, a series of empirical

studies in the bicycle industry and the automotive industry provides valuable insights on the

relationship between product variety and manufacturing and supply chain costs (Fisher and

Ittner 1999, McDuffie et al. 1996, Randall and Ulrich 2001, Ulrich et al. 1998). Randall and

Ulrich (2001) note that the effectiveness of high variety strategies of mass customization or

variety postponement depends not only on a supply chains ability to deliver variety, but also on

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the ability to successfully reach its target Market. Our model of mass customization coincides

with this notion. Mass customization has been considered with price discrimination in the recent

literature of economics of information technology.

Ulph and Vulkan (2001) demonstrate that mass customization and price discrimination are

complementary. Our mass customization model indeed allows price discrimination.

Hair et al (1998:388) state that the application of conjoint analysis in the United States has been

paralleled in other parts of the world including Europe. In Pakistan, however, it appears to have

only recently attracted the attention of a local research community.

RESEARCH METHODOLOGY

This research is conducted in Karachi. It is a descriptive research. The research describes all the

variables and their characteristic of consumer preferences toward music channels.

RESPONDENTS OF THE STUDY

The music industry offers variety of entertainments to consumers or viewers. In this research I

found the consumer preferences toward the music channels.

For this purpose I had distributed 137 questionnaires. I receive only 126 out of 137 and out of

126, 9 questionnaire were discarded so I have taken only 117 questionnaire from various

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respondents from different backgrounds like managers, students(youngster) and general public.

Respondents were selected from different towns of Karachi. They are namely:

Sadder town

North nazimabad town

Gulshan-e-Iqbal town

New Karachi town

RESEARCH INSTRUMENTS

The data gathered for the reliability of the study are from the primary data and secondary data.

Thus a variety of instruments were employed. The details of the instruments are as follows;

QUESTIONNAIRES

Questionnaires were distributed to people to find out the consumer preferences toward music

channels.

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SOURCES OF DATA

Primary Data

The method adopted in the primary data collection comprise only questionnaire. The

questionnaires which were presented to managers, students(youngster) and general public to find

the consumers preferences toward music channels.

Secondary Data

Secondary sources of data collection included

1. Internet

2. Books

3. Magazine

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SAMPLING

Following formula has been used for sampling calculation:

n = p% x q% x [z/e%]21

Where n is the minimum sample size required

p% is the proportion belonging to the specified category

q% is the proportion not belonging to the specified category

zis the z value corresponding to the level of confidence required (95%=1.96)

e% is the margin of error required.

If our population is less than 10,000 a small sample size can be used without affecting the

accuracy. This is called adjusted minimum sample size. It is calculated using the following

formula:

n = n / [1+(n /N)]

Where nis adjusted minimum sample size

n is minimum sample size (as calculated above)

Nis total population.

Logic of selecting the p% as the proportion belong to the specified category

My selected towns among Karachi (see above) = 4 (ALREADY EXPLAINED

ABOVE)

My selected towns estimated population = 3,753,726 in all 4 towns

1 Saunders M, Lewis P and Thornhill A. (2003) Research Methods for Business Students,3e, FT Prentice Hall, Harlow.

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# TOWNS POPULATION (see

appendix for details)

1 Gulshan-e-Iqbal 969,107

2 New Karachi 1,060,484

3 Sadder 955,034

4 North nazimabad 769,101

Single town on average has = 938431.5 people living in it

(estimated)

Total selected towns population = 3,753,726

1/4th of above population is adult,

Aware and, educated to fill the questionnaire

And not counting the children = 938,432 (3,753,726 x 0.25)

As the above population is too large for me to cover within the timeframe and budget of my

project so I resort to further fine-tuning (scale-down) of the population.

My selected/desired percentage = 0.8% (this is NOT 5%) (on convenience)

So, logical population for me = 7,508 (938,432 x 0.008)

P% defined:

Now desiredp% from

Logical population p% = 10%

Minimum sample size calculation

n = minimum sample size

p% = 10%

q% = 90%

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z = 1.96 (level of confidence)

e% = 5% (tolerated margin of error)

n = p% x q% x [z/e%]2

= 10 x 90 x [1.96/5]2

= 10 x 90 x 0.154

= 138.6

N = 139 (approximately).

Adjusted minimum sample size calculation

Since our logical population (7,508) is less than 10,000 so we will calculate the adjusted

minimum sample size based on the formula given above (also given here):

n = n / [1+(n /N)]

we have n = 139

N = 7,508

So, n = 139 / [1+(139 / 7,508)]

= 139 / 1.029537

n = 136.5 OR 137 respondents approx.

SATISTICAL TOOL APPLIED

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I have used cross tabs and frequency analysis as a statistical tool. In The cross tabs I have

determined the correlation between the two variables with the help of chi square and also find out

the strength of relationship in the light of phi and crammers v.

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ANALYSIS

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CROSS TABS

A LITTLE WORD ABOUT CROSS TABS

The Cross tabs procedure forms two-way and multi way tables and provides a variety of tests and

measures of association for two-way tables. The structure of the table and whether categories are

ordered determine what test or measure to use.

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Cross tabs statistics and measures of association are computed for two-way tables only. If you

specify a row, a column, and a layer factor (control variable), the Cross tabs procedure forms one

panel of associated statistics and measures for each value of the layer factor (or a combination of

values for two or more control variables). For example, ifgenderis a layer factor for a table of

married(yes, no) against life (is life exciting, routine, or dull), the results for a two-way table for

the females are computed separately from those for the males and printed as panels following

one another.

Statistics and measures of association. Pearson chi-square, likelihood-ratio chi-square, linear-

by-linear association test, Fishers exact test, Yates corrected chi-square, Pearsons r,

Spearmans rho, contingency coefficient, phi, Cramers V.

Data. To define the categories of each table variable, use values of a numeric or short string

(eight or fewer characters) variable. For example, forgender, you could code the data as 1 and 2

or as male andfemale.

Assumptions. Some statistics and measures assume ordered categories (ordinal data) or

quantitative values (interval or ratio data), as discussed in the section on statistics. Others are

valid when the table variables have unordered categories (nominal data). For the chi-square-

based statistics (phi, Cramers V, and contingency coefficient), the data should be a random

sample from a multinomial distribution.

CROSSTABS # 1

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hen you watch TV, you highly preferred to watch music channels * Q3 The timing of programs in your preferred music channel absolutely

suit you Crosstabulation

9 6 3 3 3 24

5.1 7.8 4.5 4.1 2.5 24.0

7.7% 5.1% 2.6% 2.6% 2.6% 20.5%

6 11 9 7 3 36

7.7 11.7 6.8 6.2 3.7 36.0

5.1% 9.4% 7.7% 6.0% 2.6% 30.8%

2 6 4 2 2 16

3.4 5.2 3.0 2.7 1.6 16.0

1.7% 5.1% 3.4% 1.7% 1.7% 13.7%

3 6 2 5 3 19

4.1 6.2 3.6 3.2 1.9 19.0

2.6% 5.1% 1.7% 4.3% 2.6% 16.2%

5 9 4 3 1 22

4.7 7.1 4.1 3.8 2.3 22.0

4.3% 7.7% 3.4% 2.6% .9% 18.8%25 38 22 20 12 117

25.0 38.0 22.0 20.0 12.0 117.0

21.4% 32.5% 18.8% 17.1% 10.3% 100.0%

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of TotalCount

Expected Count

% of Total

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Q1 When you watch

TV, you highly

preferred to watch

music channels

Total

HIGHLYAGREE AGREE

I AMNEUTRAL DISAGREE

HIGHLYDISAGREE

Q3 The timing of programs in your preferred music channel

absolutely suit you

Total

Case Processing Summary

117 100.0% 0 .0% 117 100.0%

Q1 When you watch TV,

you highly preferred towatch music channels *

Q3 The timing of

programs in your

preferred music channel

absolutely suit you

N Percent N Percent N Percent

Valid Missing Total

Cases

Chi-Square Tests

10.813a 16 .821

10.551 16 .836

.025 1 .874

117

Pearson Chi-Square

Likelihood Ratio

Linear-by-LinearAssociation

N of Valid Cases

Value df

Asymp. Sig.

(2-sided)

16 cells (64.0%) have expected count less than 5. The

minimum expected count is 1.64.

a.

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Symmetric Measures

.304 .821

.152 .821

117

Phi

Cramer's V

Nominal by

Nominal

N of Valid Cases

Value Approx. Sig.

Not assuming the null hypothesis.a.

Using the asymptotic standard error assuming the null

hypothesis.

b.

INTERPRETATION:

The statistics discussed here are designed to analyze two nominal or dichotomous variables. Chi-

square (2) or phi/Cramers V are good choices for statistics while analyzing two nominal

variables.

Chi-square requires a relatively large sample size because the expected counts in 80% cells

should be greater than 5. Fishers exact test for 2x2 cross tabs should be reported instead of chi-

square for small samples. Chi-square and the Fishers exact test provide similar information

about relationships among variables; however, they only tell us whether the relationship is

statistically significant. They do not tell the effect size (i.e. the strength of the relationship).

Phi and Cramers Vprovide a test of statistical significance and also provide information about

the strength of the association between the two variables and can be used as a measure of the

effect size. If there is a 2x2 cross tabulation, phi is the appropriate statistic. For larger cross tabs

(larger than 2x2), Cramers Vis used.

RESULTS:

Chi-square Tests table above is used to determine there is a statistically significant relationship

between two dichotomous nominal variables. Pearson Chi-Square was used for small samples

orFishers Exact Test was used to interpret the results of the test. They are NOT statistically

significant (p > 0.05), which indicates that the two variables under discussion are not

independent to each other and both of them are correlated or have an influence to each other.

The Symmetric Measures table as shown above provides the strength of relationship or effect

size. The negative sign does not mean anything here because it shows the direction of the

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association or effect size of variable from variable to another. However, low values here indicate

weak association.

So on the basis of above explanation and results output tables it is proven that the relationship or

association does exist among the two variables but it is also a fact highlighted by the test results

that the association however among them is weak.

CROSSTABS # 2


117 100.0% 0 .0% 117 100.0%

Q4 You watch yourpreferred music

channel just because

of anchors/VJs * Q5

You have high loyalty

toward your preferred

music channel


Valid Missing Total

Cases

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4 You watch your preferred music channel just because of anchors/VJs * Q5 You have high loyalty toward your preferred music channel

Crosstabulation

4 4 3 4 4 19

3.6 5.7 3.4 2.6 3.7 19.0

3.4% 3.4% 2.6% 3.4% 3.4% 16.2%

4 6 3 5 5 23

4.3 6.9 4.1 3.1 4.5 23.0

3.4% 5.1% 2.6% 4.3% 4.3% 19.7%

2 11 4 7 5 29

5.5 8.7 5.2 4.0 5.7 29.0

1.7% 9.4% 3.4% 6.0% 4.3% 24.8%

6 8 6 0 5 25

4.7 7.5 4.5 3.4 4.9 25.0

5.1% 6.8% 5.1% .0% 4.3% 21.4%

6 6 5 0 4 21

3.9 6.3 3.8 2.9 4.1 21.0

5.1% 5.1% 4.3% .0% 3.4% 17.9%

22 35 21 16 23 117

22.0 35.0 21.0 16.0 23.0 117.0

18.8% 29.9% 17.9% 13.7% 19.7% 100.0%

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Q4 You watch your

preferred music

channel just because

of anchors/VJs

Total

HIGHLY

AGREE AGREE

I AM

NEUTRAL DISAGREE

HIGHLY

DISAGREE

Q5 You have high loyalty toward your preferred music channel

Total

Chi-Square Tests

17.142a 16 .37623.238 16 .108

2.218 1 .136

117

Pearson Chi-SquareLikelihood Ratio

Linear-by-Linear

Association

N of Valid Cases

Value df

Asymp. Sig.

(2-sided)



a.

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Symmetric Measures

.383 .376

.191 .376

117

Phi

Cramer's V

Nominal by

Nominal

N of Valid Cases

Value Approx. Sig.



hypothesis.

b.

INTERPRETATION:



variables.










RESULTS:








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weak association.




CROSSTABS # 3

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6 The music channel you watch always show variety * Q7 Your preferred music channel regularly updates on new music release

Crosstabulation

7 16 8 4 8 43

5.9 15.4 9.9 5.1 6.6 43.0

6.0% 13.7% 6.8% 3.4% 6.8% 36.8%

1 7 2 1 5 16

2.2 5.7 3.7 1.9 2.5 16.0

.9% 6.0% 1.7% .9% 4.3% 13.7%

3 6 8 5 1 23

3.1 8.3 5.3 2.8 3.5 23.0

2.6% 5.1% 6.8% 4.3% .9% 19.7%

3 10 3 3 3 22

3.0 7.9 5.1 2.6 3.4 22.0

2.6% 8.5% 2.6% 2.6% 2.6% 18.8%

2 3 6 1 1 131.8 4.7 3.0 1.6 2.0 13.0

1.7% 2.6% 5.1% .9% .9% 11.1%

16 42 27 14 18 117

16.0 42.0 27.0 14.0 18.0 117.0

13.7% 35.9% 23.1% 12.0% 15.4% 100.0%

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Q6 The music

channel you

watch always

show variety

Total

HIGHLYAGREE AGREE I AMNEUTRAL DISAGREE HIGHLYDISAGREE

Q7 Your preferred music channel regularly updates on new music

release

Total

Chi-Square Tests

17.373a 16 .362

17.076 16 .381

.171 1 .680

117

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear

Association

N of Valid Cases

Value df Asymp. Sig.

(2-sided)



a.

Symmetric Measures

.385 .362

.193 .362

117

Phi

Cramer's V

Nominal by

Nominal

N of Valid Cases

Value Approx. Sig.



hypothesis.

b.

Symmetric Measures

.385 .362

.193 .362

117

Phi

Cramer's V

Nominal by

Nominal

N of Valid Cases

Value Approx. Sig.



hypothesis.

b.


117 100.0% 0 .0% 117 100.0%

Q6 The music channel

you watch always show

variety * Q7 Your

preferred music channel

regularly updates on

new music release


Valid Missing Total

Cases

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INTERPRETATION:



variables.










RESULTS:






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weak association.




CROSSTABS # 4

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6 The music channel you watch always show variety * Q1O Your preferred music channel organizes more events than other music

channels Crosstabulation

12 10 8 8 5 43

8.8 10.3 7.4 9.2 7.4 43.0

10.3% 8.5% 6.8% 6.8% 4.3% 36.8%

2 4 4 2 4 16

3.3 3.8 2.7 3.4 2.7 16.0

1.7% 3.4% 3.4% 1.7% 3.4% 13.7%

4 3 4 9 3 23

4.7 5.5 3.9 4.9 3.9 23.0

3.4% 2.6% 3.4% 7.7% 2.6% 19.7%

2 7 3 4 6 22

4.5 5.3 3.8 4.7 3.8 22.0

1.7% 6.0% 2.6% 3.4% 5.1% 18.8%

4 4 1 2 2 13

2.7 3.1 2.2 2.8 2.2 13.0

3.4% 3.4% .9% 1.7% 1.7% 11.1%

24 28 20 25 20 117

24.0 28.0 20.0 25.0 20.0 117.0

20.5% 23.9% 17.1% 21.4% 17.1% 100.0%

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

Count

Expected Count

% of Total

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Q6 The music

channel you

watch always

show variety

Total

HIGHLY

AGREE AGREE

I AM

NEUTRAL DISAGREE

HIGHLY

DISAGREE

Q1O Your preferred music channel organizes more events than

other music channels

Total

Chi-Square Tests

14.647a 16 .551

14.464 16 .564

.689 1 .406

117

Pearson Chi-Square

Likelihood Ratio

Linear-by-Linear

Association

N of Valid Cases

Value df

Asymp. Sig.

(2-sided)



a.


117 100.0% 0 .0% 117 100.0%

Q6 The music channel

you watch always showvariety * Q1O Your

preferred music

channel organizes

more events than other

music channels


Valid Missing Total

Cases

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Symmetric Measures

.354 .551

.177 .551

117

Phi

Cramer's V

Nominal by

Nominal

N of Valid Cases

Value Approx. Sig.



hypothesis.

b.

INTERPRETATION:



variables.










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RESULTS:



orFishers Exact Test was used to interpret the results of the test. They are NOT statisticallysignificant (p > 0.05), which indicates that the two variables under discussion are not





weak association.




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FREQUENCY ANALYSIS

FREQUENCY ANALYSIS

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Q1 When you watch TV, you highly preferred to watch music channels

HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

Percent

40

30

20

10

0


Q1 When you watch TV, you highly preferred to watch music channels.

Statistics

Q1 When you watch TV, you highly preferre

to watch music channels 117

0

2.82

1.424

Valid

Missing

N

Mean

Std. Deviation


24 20.5 20.5 20.5

36 30.8 30.8 51.3

16 13.7 13.7 65.0

19 16.2 16.2 81.2

22 18.8 18.8 100.0

117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Total

Valid

Frequency Percent Valid Percent

Cumulative

Percent

INTERPRETATION:

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Above graph and table shows that 30.8% respondents agree that when they watch TV they

preferred to watch music channels.

Q2 You have high family influence to watch your preferred music channel.

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Q2 You have high family influence to watch your preferred music channel


Perce

nt

25

20

15

10

5

0


Statistics

Q2 You have high family influence to watch

your preferred music channel

117

0

3.06

1.434

Valid

Missing

N

Mean

Std. Deviation


23 19.7 19.7 19.7

20 17.1 17.1 36.8

28 23.9 23.9 60.7

19 16.2 16.2 76.9

27 23.1 23.1 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREETotal

Valid


Cumulative

Percent

INTERPRETATION:

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Above graph and table shows that 23.9% of respondents have neutral decision on that they have

high family influence to watch their preferred music channel.

Q3 The timing of programs in your preferred music channel absolutely suit you.

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Q3 The timing of programs in your preferred music channel absolutely suityou

HIGHLY DISAGREEDISAGREEI AMNEUTRALAGREEHIGHLY AGREE

Pe

rcent

40

30

20

10

0

Q3 The timing of programs in your preferred music channel absolutely suityou

Statistics

Q3 The timing of programs in your preferred

music channel absolutely suit you

117

0

2.62

1.278

Valid

Missing

N

Mean

Std. Deviation

Q3 The timing of programs in your preferred music channel absolutely suit you

25 21.4 21.4 21.4

38 32.5 32.5 53.8

22 18.8 18.8 72.6

20 17.1 17.1 89.7

12 10.3 10.3 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

43


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The above graph and table shows that 32.5% respondents agree that the timing of programs in

their preferred music channel suit them.

Q4 You watch your preferred music channel just because of anchors/VJs.

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Q4 You watch your preferred music channel just because of anchors/VJs


Percent

25

20

15

10

5

0


Statistics

Q4 You watch your preferred music channel

just because of anchors/VJs

117

0

3.05

1.338

Valid

Missing

N

Mean

Std. Deviation


19 16.2 16.2 16.2

23 19.7 19.7 35.9

29 24.8 24.8 60.7

25 21.4 21.4 82.1

21 17.9 17.9 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 24.8% respondents have neutral decision that they watch

their preferred music channel because of anchors/VJs.

Q5 You have high loyalty toward your preferred music channel.

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Percent

30

20

10

0


Statistics


117

0

2.85

1.404

Valid

Missing

N

Mean

Std. Deviation


22 18.8 18.8 18.8

35 29.9 29.9 48.7

21 17.9 17.9 66.7

16 13.7 13.7 80.3

23 19.7 19.7 100.0

117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Total

Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 29.9% respondents agree that that have high loyalty

toward their preferred music channel.

Q6 The music channel you watch always show variety.

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Q6 The music channel you watch always show variety


Perce

nt

40

30

20

10

0


Statistics


117

0

2.54

1.430

Valid

Missing

N

Mean

Std. Deviation


43 36.8 36.8 36.8

16 13.7 13.7 50.4

23 19.7 19.7 70.1

22 18.8 18.8 88.9

13 11.1 11.1 100.0

117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE

HIGHLY DISAGREE

Total

Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 36.8% respondents highly agree on that the music channel

they watch always shows variety.

Q7 Your preferred music channel regularly updates on new music release.

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Q7 Your preferred music channel regularly updates on new music release


Pe

rcent

40

30

20

10

0


Statistics

Q7 Your preferred music channel regularly

updates on new music release

117

0

2.79

1.270

Valid

Missing

N

Mean

Std. Deviation


16 13.7 13.7 13.7

42 35.9 35.9 49.6

27 23.1 23.1 72.6

14 12.0 12.0 84.6

18 15.4 15.4 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 35.9% respondents agree that their preferred music

channel regularly updates on new music release.

Q8 The quality of programs in your preferred music channel is excellent.

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Q8 The quality of programs in your preferred music channel is excellent


Percent

40

30

20

10

0


Statistics

Q8 The quality of programs in your preferred

music channel is excellent

117

0

2.81

1.252

Valid

Missing

N

Mean

Std. Deviation


24 20.5 20.5 20.5

20 17.1 17.1 37.6

39 33.3 33.3 70.9

22 18.8 18.8 89.7

12 10.3 10.3 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 33.3% respondents have neutral decision on that the

quality of program in their preferred music channel is excellent.

Q9 The music channel which you watch provides more entertainment than others.

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Q9 The music channel which you watch provides more entertainment than

others


Percent

40

30

20

10

0

Q9 The music channel which you watch provides more entertainment thanothers

Statistics

Q9 The music channel which you watch

provides more entertainment than others

117

0

2.81

1.377

Valid

Missing

N

Mean

Std. Deviation

Q9 The music channel which you watch provides more entertainment than others

21 17.9 17.9 17.9

39 33.3 33.3 51.3

19 16.2 16.2 67.5

17 14.5 14.5 82.1

21 17.9 17.9 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

55


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The above graph and table shows that 33.3% agree that the music channel they watch provides

more entertainment than others.

Q1O Your preferred music channel organizes more events than other music channels.

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Q1O Your preferred music channel organizes more events than other music

channels


Percent

25

20

15

10

5

0

Q1O Your preferred music channel organizes more events than other musicchannels

Statistics

Q1O Your preferred music channel organizes

more events than other music channels

117

0

2.91

1.402

Valid

Missing

N

Mean

Std. Deviation

1O Your preferred music channel organizes more events than other music channe

24 20.5 20.5 20.5

28 23.9 23.9 44.4

20 17.1 17.1 61.5

25 21.4 21.4 82.920 17.1 17.1 100.0

117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREEHIGHLY DISAGREE

Total

Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 23.9% respondents agree that their preferred music

channel organize more events than other music channels.

Q11 You are highly satisfied that your preferred music channel fulfill your demands

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Q11 You are highly satisfied that your preferred music channel fulfill yourdemands


Percent

40

30

20

10

0

Q11 You are highly satisfied that your preferred music channel fulfill yourdemands

Statistics

Q11 You are highly satisfied that your

preferred music channel fulfill your demands

117

0

3.17

1.255

Valid

Missing

N

Mean

Std. Deviation

11 You are highly satisfied that your preferred music channel fulfill your demands

16 13.7 13.7 13.7

20 17.1 17.1 30.8

24 20.5 20.5 51.3

42 35.9 35.9 87.2

15 12.8 12.8 100.0117 100.0 100.0

HIGHLY AGREE

AGREE

I AM NEUTRAL

DISAGREE


Valid


Cumulative

Percent

INTERPRETATION:

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The above graph and table shows that 35.9% respondents disagree that their preferred music

channel fulfills their demands.

CONCLUSION

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The first cross tab shows that there is a correlation among the two variables but it indicates

that the strength among the variables is weak. In The second cross tabs there is a correlation

between the two variables with a weak strength of relationship. According to the third cross

tabs there is a correlation between the two variables but there is a presence of weak

relationship between them. Similarly the fourth cross tab also shows a correlation between

the two variables but there exists a weak strength of relationship between them.

From the result of all the above four cross tabs we can easily conclude that there is a

correlation between the variables exists but the strength of relationship between them is

weak.

RECOMMENDATIONS

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Finally I would like to recommend this research work to all those who want to establish their

new music channels and they can take help from my report. Following are the variables that

they can take as a guideline:

Viewers loyalty

Family influence

Timing of programs

Quality of programs

Fulfill demands

REFERENCES

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Brennan, T. 1994. Markets, Information and Benevolence,Economics and Philosophy 10:

15168.

Brennan, T. 2001. The California Electricity Experience, 2000-2001: Education or Diversion?

(Washington, DC: Resources for the Future).

Brown, M., J. Eisenberg, and L. Hill. 1998. Restructuring and Small Electric Customers, paper

presented at National Conference of State Legislatures (July).

Flaim, T. 2000. The Big Retail Bust: What Will It Take to Get True Competition?Electricity

Journal13 (March): 4154.

Joskow, P. 2000. Why Do We Need Electricity Retailers? Or Can You Get It Cheaper

Wholesale? revised discussion draft (February 13) (Cambridge, MA: Harvard Electricity Policy

Group).

Jurewitz, J. 2002. The Right Safety Net,Electric Perspectives 27 (March/April): 24.

Littlechild, S. 2000. Why We Need Electricity Retailers: A Reply to Joskow on Wholesale Spot

Price Pass-Through, Working Paper 21/2000, Judge Institute for Management Studies,

University of Cambridge (Aug. 22)

Littlechild, S. 2005. How Much and What Kind of Regulation Will Be Needed in the

Networked World of Tomorrow? paper presented at the Transatlantic SymposiumWashington,

DC (April 15).

Implications for New Service Development and Forecasting. Telecommunications Policy, 21,

743-760.

Search Engine:

www.google.com.pk

APPENDICES

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Pakistan: Karachi City PopulationSource:

2007-08-16 HTTP://WWW.CITYPOPULATION.DE THOMAS BRINKHOFF

The city districts ("towns") of the Karachi City District and the cantonments inKarachi.

Name Status CD C 1981-03-01 CD C 1998-03-01

Extrapolated

Population

@5% per

annum and up

to 2009 after

1998 almost

55%

Baldia CDist ... 406,165 629,556

Bin Qasim CDist ... 316,684 490,860

Clifton Cantonment Ct ... ...

Faisal Cantonment (Drigh Road Ct.) Ct 56,742 ...

Gadap CDist ... 289,564 448,824Gulberg CDist ... 453,490 702,910

Gulshan CDist ... 625,230 969,107

Jamshed CDist ... 733,821 1,137,423

Karachi Cantonment Ct 181,981 ...

Kiamari CDist ... 383,378 594,236

Korangi CDist ... 546,504 847,081

Korangi Cantonment (Korangi Creek Ct.) Ct 10,222 ...

Landhi CDist ... 666,748 1,033,459

Liaquatabad CDist ... 649,091 1,006,091

Lyari CDist ... 607,992 942,388

Malir CDist ... 398,289 617,348

Malir Cantonment Ct 47,588 ...

Manora Cantonment Ct 9,972 ... New Karachi CDist ... 684,183 1,060,484

North Nazimabad CDist ... 496,194 769,101

Orangi CDist ... 723,694 1,121,726

Saddar CDist ... 616,151 955,034

Shah Faisal CDist ... 335,823 520,526

Sindh Industrial Trading Estate (SITE) CDist ... 467,560 724,718

* (1981) provided by Ulrich Buys, (1998) Urban Resource Center Karachi (web).

Note: The cantonments are not under the jurisdiction of the Karachi City District Government

and are not part of the listed towns.

The last column is added by me using the simple extrapolation. This is just an approximation.

Use with care.

Raja Rub Nawaz (August 2009)

QUESTIONNAIRE

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Please answer each item as carefully and accurately as you can by placing a number by each one

as follows

1 2 3 4 5

Highly Agree agree I am neutral Disagree Highly Disagree

# Statements Rating

1 When you watch TV, you highly preferred to watch music channels. 1 2 3 4

2 You have high family influence to watch your preferred music channel. 1 2 3 4

3 The timing of programs in your preferred music channel absolutely suit you. 1 2 3 4

4 You watch your preferred music channel just because of anchors/VJs. 1 2 3 4

5 You have high loyalty toward your preferred music channel. 1 2 3 4

6 The music channel you watch always show variety. 1 2 3 4

7 Your preferred music channel regularly updates on new music release. 1 2 3 4

8 The quality of programs in your preferred music channel is excellent. 1 2 3 4

9 The music channel which you watch provides more entertainment than others. 1 2 3 4

10 Your preferred music channel organizes more events than other music channels. 1 2 3 4

11 You are highly satisfied that your preferred music channel fulfill your demands. 1 2 3 4

RESUME

IMRAN KHAN

B-76 BLOCK B KAZIMABAD MODEL COLONY KARACHI

65


66/66

Cell# 0300-2523565

E-Mail: [email protected]

OBJECTIVE:

TO ATTAIN THE BEST WORKING EXPERIENCE

PERSONAL PROFILE:

Fathers Name: Mushatq Ahmwd KhanDate & Place of Birth: 12 sep 1986, Karachi

Nationality: PAKISTANI

ACADEMIC EDUCATION:

2005-2009 PAF-KIET KARACHI, PAKISTAN

Bachelors Degree

2003-2005 CAMS COLLEGE KARACHI, PAKISTAN

Intermediate PRE-ENG

2001-2003 KARACHI MODEL SCHOOL KARACHI, PAKISTAN

Metric science

SPOKEN LANGUAGES:

ENGLISHURDU

EXTRACURRICULAR ACTIVITIES:

PLAYING CRICKET, WATCHING TV, READING NEWSPAPER

ACHIEVEMENTS:

COORDINATOR FINAL YEAR PROJECT EXHIBITION 2008 [PAF-KIET]
mailto:[email protected]:[email protected]

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