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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

    Case Processing Summary

    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

    N Percent N Percent N Percent

    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)

    17 cells (68.0%) have expected count less than 5. The

    minimum expected count is 2.60.

    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.

    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 # 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)

    15 cells (60.0%) have expected count less than 5. The

    minimum expected count is 1.56.

    a.

    Symmetric Measures

    .385 .362

    .193 .362

    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.

    Symmetric Measures

    .385 .362

    .193 .362

    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.

    Case Processing Summary

    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

    N Percent N Percent N Percent

    Valid Missing Total

    Cases

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    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.

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    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

    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 # 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)

    18 cells (72.0%) have expected count less than 5. The

    minimum expected count is 2.22.

    a.

    Case Processing Summary

    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

    N Percent N Percent N Percent

    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.

    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.

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    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 statisticallysignificant (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

    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.

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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

    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

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

    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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Perce

    nt

    25

    20

    15

    10

    5

    0

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

    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

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

    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

    Frequency Percent Valid Percent

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Percent

    25

    20

    15

    10

    5

    0

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

    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

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

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    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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    Q5 You have high loyalty toward your preferred music channel

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Percent

    30

    20

    10

    0

    Q5 You have high loyalty toward your preferred music channel

    Statistics

    Q5 You have high loyalty toward your preferred music channel

    117

    0

    2.85

    1.404

    Valid

    Missing

    N

    Mean

    Std. Deviation

    Q5 You have high loyalty toward your preferred music channel

    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

    Frequency Percent Valid Percent

    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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Perce

    nt

    40

    30

    20

    10

    0

    Q6 The music channel you watch always show variety

    Statistics

    Q6 The music channel you watch always show variety

    117

    0

    2.54

    1.430

    Valid

    Missing

    N

    Mean

    Std. Deviation

    Q6 The music channel you watch always show variety

    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

    Frequency Percent Valid Percent

    Cumulative

    Percent

    INTERPRETATION:

    49

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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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Pe

    rcent

    40

    30

    20

    10

    0

    Q7 Your preferred music channel regularly updates on new music release

    Statistics

    Q7 Your preferred music channel regularly

    updates on new music release

    117

    0

    2.79

    1.270

    Valid

    Missing

    N

    Mean

    Std. Deviation

    Q7 Your preferred music channel regularly updates on new music release

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    Percent

    40

    30

    20

    10

    0

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

    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

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

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    Cumulative

    Percent

    INTERPRETATION:

    53

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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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    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

    Frequency Percent Valid Percent

    Cumulative

    Percent

    INTERPRETATION:

    57

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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

    HIGHLY DISAGREEDISAGREEI AM NEUTRALAGREEHIGHLY AGREE

    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

    HIGHLY DISAGREETotal

    Valid

    Frequency Percent Valid Percent

    Cumulative

    Percent

    INTERPRETATION:

    59

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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

    63

    http://www.google.com.pk/http://www.google.com.pk/
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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

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    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]