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Effect Of Movie Review And Star Cast Media Essay

INTRODUCTION

“Bollywood is becoming a big business, said the opening line of the lead story in the Business Standard on January 14, 2011

This was a report on 3 Idiots making business history in Indian cinema, grossing Rs 240 crore (Rs 2.40 billion) in the first ten days. The business of cinema in India has undergone significant changes. Banks & business houses are into financing movies. Marketing companies are thriving not just to selling movies but a whole range of products linked to movies and actors. And, increasingly, the business is becoming global.

Estimation by FICCI and E&Y says that Indian entertainment industry was worth more than Rs. 400,000 million in 2008. Numerous positive developments such as accordance of 'industry' film industry, increasing satellite channel penetration, retail boom, music sales (Music World & Planet M), use of digital technology in all spheres of entertainment and the growth of multiplexes have contributed to the growth of the sector.

The future of entertainment industry in India looks extremely good. As India's profile rises on the global stage outside interest in India's culture and entertainment industry is rapidly growing.

Entertainment industry is currently in a consolidation phase because boundary lines between films, music and television are fast disappearing. Skills and resources are being pooled extensively. The entertainment industry is witnessing rapid development of state-of-the-art studios and post production facilities. Acting, Sets, Music, Dialogues, etc. are all major and integral part of a movie which basically drives this form of art and take it to another level. For example, the background score of a movie reflects the emotional state of the characters or actions on the celluloid. Similarly, the genre or period of a movie reflects the sentiments or the behaviours of an individual entity or a group during some particular occasions or circumstances. These all have a substantial effect on the behaviour of viewers.

This research basically aims to find out the intentions/logic/rationale/behind in the mindset of an individual(s) before s/he decides to watch a particular movie.

RESEARCH OBJECTIVE

The objective of this research is to determine the impact of “movie review” and “star cast” on the “movie watching preference” (purchasing behavior) of Indian youth.

PROJECT MODEL

Independent Variables:

 Star Cast

Mediating Variable:

 Review

Dependent Variable:

 Movie Watching Preference

Hypothesis

We came up with the following 3 hypothesis :

Hypothesis 1- There is a positive relationship between star cast and movie watching preferences

Hypothesis 2- There is a positive relationship between star cast and movie review

Hypothesis 3– There is a positive relationship between movie reviews, star cast and movie watching preferences

LITERATURE REVIEW

This research study is aimed at studying a consumer’s preferences to a movie in a similar fashion as he decides for when spending money or selecting any other product or service. There is sufficient literature which shows that movies are perceived in different ways by different set of people at different times.

7 Cooper-Martin,1991 refers to performing arts like movies, theatres etc different from normal products since the consumption experience here, is an end in itself here. We have captured the various attributes and variables through below observations:

Critics:

In the context of our research, we define critics as professionals, who watch a movie, and study its subtleties without any personal biases. They then document their opinions by giving the movie a rating, demonstrating how favorable or unfavorable their opinion was about it, after watching it. This rating is then made available to the people who may decide to agree or disagree to it.

Opinion

Opinion of the critics in the scope of this research is as captured from the ratings given by the critics in form of a professional movie review.

Reviews:

 The effect of reviews is divided in two parts: influence and prediction effect, former is causal effect of review of on demand 32(Eliashberg and Shugan 1997) while latter is spurious effect. However it not possible to measure the effect of reviews as products getting good reviews are good products in terms of feature etc. 33(Christopher and David 2005). The reviews are categorized into positive, neutral, mixed and negative reviews. Positive reviews are found to have significant impact on movie’s success, while negative and mixed reviews are discounted by the audience. (Wyatt and Badger 1984)

 The impact of positive reviews have been found to be significant on the box office collections

33 (Christopher and David 2005), yet some studies have found that movie success are not impacted by expert reviews. It is only after some time of movie’s release there is some relation between the reviews and collections 32 (Eliashberg and Shugan 1997).

The effect of reviews is captured in the following hypothesis

1A

H0: Viewers follow reviews from an expert about movies and decide to watch a movie according to the

reviews

H1: Viewers do not follow reviews from an expert about movies and decide to watch a movie according to the reviews

The hypothesis has been successfully captured in the survey by means of questions like “You decide to watch after considering the Expert reviews” and “You decide to watch by considering only promotions that are on display”

1B

H0: Viewers decide to watch movie on the basis of an expert’s positive advice

H1: Viewers decide to watch movie on the basis of an expert’s positive advice

The Hypothesis has been successfully by “You watch the Movie only if the expert give it positive reviews” and “You refrain from watching the movie if experts give it negative reviews”

1C

H0: Viewers accept expert review only when they match their own perception about movie in deciding to watch movies

H1: Viewers accept expert review only when they match their own perception about movie in deciding to watch movies

The hypothesis has been successfully by “You will go to watch the movie even if the reviews do not match with your perception”.

Starcast (crew)

The effect of starcast (crew) is captured in the following hypothesis

2A

H0: People prefer to watch movies of their favorite actor/actresses

H1: People do not have such preferences

One of the questions for which still many of us are clueless is that why people give the status of demi - gods to a few actors and actresses? A simple reason could be that they all in a due course of time become a larger than the life figure or the scenes, the roles they portray on the celluloid resembles in one or the other manner to them. It makes sense to suppose that certain artistic styles would lean more toward realistic preferentiality or easy accessibility versus formalist abstraction or difficult complexity 3(Holt 1998, p. 4; Nichols 1976, pp. 221-309). On the contrary, these stars know that a simple person who goes for watching a movie to a theatre is the ultimate ruler of their destiny. It is he who decides the fate of a movie. Stars like RajniKant, Amitabh Bachchan and a few others have such a fan following that even if each of them watch the movie once, it becomes a block-buster. So, people watching the movies of their favorite actors do play an important role in deciding the outcome of a movie. This is why our research hypothesis takes this fact into consideration. We will try to gauge it by asking two sets of question. First, we will ask “Who is your favorite actor?” and then “Which Star’s movie would you like to watch?”

2B

H0: Celebrity status plays an important role in final outcome of a movie

H1: Celebrity status does not play an important role in final outcome of a movie

“He is a good Actor, Kind, Generous, a Constant public figure, friendly with co-stars and above all is just like me”, says one of the respondent when asked about his views on Salman Khan “So, I don’t miss his single movie”. This is not the case of a single person but most of us compare ourselves to celebrities.

Celebrities become idols of young people because they are more attractive than other ordinary individuals. 1 (Yue and Cheung, 2000) and may stem from a developmental need for identification and intimacy 29 (Josselson, 1991). Young people attempt to imitate them in every way they can. 9 Caughey (1984) found that individual’s develop strongly emotions for media celebrities without having any face-to-face interaction with them. He also concluded that people’s ‘‘imaginary’’ relationships with celebrities shapes their own self-identities and their evaluation of self-worth. This made us include the effect of Celebrity as an important factor of a movie in our hypothesis. We are gauging the effect of celebrity on a four point scale in comparison with other factors like Genre, Reviews and Music.

2C

H0: The past record of a star has the direct relation to the success of his upcoming movie

H1: The past record of a star has no direct relation to the success of his upcoming movie

In taking into consideration the artistic knowledge and the aesthetic sensibilities, it appears logical to

include a formalized industry opinion about the quality of the movie or a yardstick to measure excellence. 6(Levy 1990, p. 330). This can be in form of Annual Academy awards or Filmfare Awards. It is true that these awards are basically a mean to market the movie but they exert a measurable effect on short market success 5(Dodds and Holbrook 1988). People treat these as a bench-mark and assume these movies to be a must watch. Even if a star is having his last movie a hit one, people tend to associate his past success with the current one. If these movies turn out to be of their favourite stars, it has a multiplying effect and a sense of accomplishment for them. Hence, we will include this part in two questions of our survey, “If the last movie of a movie star was a hit on box office, you will go and watch it” and “If a star has recently won a national award/Filmfare award, will you consider going and watching the movie”. We are capturing this on a 5-point scale.

We have used research papers which have studied celebrity worshipping trends in the Chinese culture because Chinese society has long-standing values concerning families and human relations 17 (Zhao, 1997) and is very similar to the Indian society in this respect.

Movie Watching Preference

The effect on Movie Watching Preference is captured in the following hypothesis

Young individuals have varied movie watching preferences. . They basically try to mimic each and every bit of their favorite star’s style, how he talks, how he speak, how he behave in public appearance, etc. Imitation of movie actors was measured by asking respondents to rate several items:

‘‘I want to be as smart like movie stars’’, ‘‘I want to be as stylish as people appearing in movies’’, ‘‘I

want to be as trendy as actors/actresses in movies’’ and ‘‘I am not keen to the lifestyle of celebrities

(reverse coded)’’. These statements were modified according to the concept of ‘‘exposure to materialistic models’’ 12( Kasser et al.’s (2004) framework). Behavior of a young individual is quite influenced by the fact that they think they are in a ‘‘real’’ relationship with the celebrities. Celebrity worship influences their followers’ values, behaviors and attitudes 13 (Schultze et al., 1991). An ethnographic analysis was used by 9,10,11 Caughey (1984, 1985, 1994) used to find that young followers consider celebrities as their idols and as their idealized themselves. Admirers want to imbibe in them the personality traits similar to their idols. Youth want to have the same version of their in terms of their physical appearance, values, attitudes and abilities as that of their idols. When surveyed, a majority feels that their attitude, beliefs, desires, work ethic and morality are influenced by their idols 14 (Boon and Lomore, 2001). Empirical research indicates that that direct role models viz. family (e.g. fathers, mothers, brothers, sisters) and vicarious role models (e.g. fav. entertainers) have a significant effect on young individuals in terms of brand switching, brand selection and lodging consumer complaints 15 (Martin and Bush, 2000). People agreed to the fact that they are more inclined towards a product if it is being endorsed by their favorite star/idols 16 (Lafferty and Goldsmith, 1999).

3A

H0: There is a positive relationship between star cast and movie watching preference

H1: There is no positive relationship between star cast and movie watching preference

ANALYSIS:

90 % of our questions were projected in the form of a Likert scale to respondents.

McIver and Carmines (1981), (pp. 22-23) describe the Likert scale as follows:

“A set of items, composed of approximately an equal number of favorable and unfavorable statements concerning the attitude object, is given to a group of subjects. They are asked to respond to each statement in terms of their own degree of agreement or disagreement.”

Typically, they are instructed to select one of five responses: strongly agree, agree, undecided, disagree, or strongly disagree. The specific responses to the items are combined so that individuals with the most favorable attitudes will have the highest scores while individuals with the least favorable (or unfavorable) attitudes will have the lowest scores. While not all summated scales are created according to Likert’s specific procedures, all such scales share the basic logic associated with Likert scaling.

Data Analysis with Likert Scales

The reliability test we have used is Cronbach's alpha (Cronbach, 1951). Cronbach's alpha (Cronbach,

1951) is one of the most popular reliability statistics which can be used to determine the average

correlation or internal consistency of items in a survey and gaze their reliability. Variables derived from test instruments are assumed to be reliable only when they provide stable responses over a repeated administration of the test. Underlying constructs are measured by the assembly of interrelated items or summated scales and therefore, it is important to find if the same questions are reframed and given to individuals, would they elicit the same responses/interest. It is imperative to calculate and report Cronbach’s alpha coefficient whenever using Likert type Scale for internal consistency reliability from scales or sub-scales. Data analysis is done on these summated scales. Cronbach’s alpha does not provide reliability estimates for single items.

Normal Range of Cronbach’s alpha reliability coefficient is between 0 and 1 without any lower limit. The closer Cronbach’s coefficient is to 1, the greater is the internal consistency of the items in the scale. George and Mallery (2003) provided the following:

α > 0.9

Excellent

0.8 < α < 0.9

Good

0.7 < α < 0.8

Acceptable

0.6 < α < 0.7

Questionable

0.5 < α < 0.6

Poor

α < 0.5

Unacceptable

Analysis for the Reliability of Scales

1. Review

The value of Cronbach’s alpha in this case comes out to be 0.832 which is considered to be decent enough value showing significant amount of consistency between the eight items, we chose for our construct “Review”.

2. Star Cast

For this particular construct, the Cronbach’s coefficient is coming out to be 0.841 for the 6 items for which we are calculating the internal consistencies.

3. Movie Watching Preference

Among all the four constructs, Movie Watching Preference has the highest Cronbach’s coefficient of 0.851. This shows that all the 8 items or the questions included have a high degree of internal consistencies among them.

A gist of the Cronbach’s analysis:

CONSTRUCT

No. of Items

Cronbach’s Alpha

Mean

Standard Deviation

Review

8

0.832

23.157

0.188

Star Cast

6

0.841

15.867

0.163

Movie Watching Preference

8

0.851

37.421

0.127

DESIGN:

Data Collection Methodology

A questionnaire was constructed to find the desired movie attributes from amongst the ones identified from our extensive literature review. Respondents were asked to rate the variables either on a five point Likert’s scale or on a seven point preference scale so that higher item scores indicate a more favorable attitude.

For e.g. star cast, review etc are some of the variables which we got to know in secondary research. Consumers were asked to rate how important they are while deciding which movie to go.

Example:

Rate the following attributes on the basis of their importance while selecting a movie on a five point scale as follows: (Where 5 = Most Important and 1 = Least Important).

SNO

ATTRIBUTE

SA

AGREE

NEUTRAL

DISAGREE

SD

1

The results of this survey helped us in identifying important factors in order of preference

Sampling

We will do non probabilistic sampling where respondents were selected from the population in non

random manner. This was done subjectively keeping our problem statement in mind. Hence we restricted ourselves to teenagers -youth. Given our constraints we also did convenience sampling in which sample comprises of the individuals that are easiest to reach.

Since we had a particular target segment in mind we used email and telephone surveys to gather data also.

We gave the questionnaire to be filled up by the respondents and for those who were not very comfortable with reading English we interviewed them using the same questions as in the questionnaire.

The sample size we used was 159 valid data points. It consisted of Indian youth aged between 20-27

years. The male to female ratio among the respondents was 110:49.

DATA PREPARATION

Data Editing

During the data editing stage, the data was checked for any mistakes made by the interviewer or the

interviewee. We checked that

 All questions are properly filled.

 There are no improbable answers. E.g. some respondent reporting her age as 200 years

 There is no ineligible respondent. Say incidentally one of the respondents turns out to be a kid in our survey

 The Responses are consistent. An example of Inconsistent responses might be the following case. A respondent reports that his name as Shalini and gender ‘Male’

 We did not have to edit any data, as all responses were found consistent

DATA CODING

Since most of the analysis was done by using SPSS, the responses were classified with numerical

scores to feed it directly to the SPSS tool.

Some of the examples of the legends used were:

Strongly Agree - 5

Agree - 4

Neutral - 3

Disagree - 2

Strongly Disagree - 1

Open ended responses like ‘Immaterial” were treated as neutral and coded 3.

DATA ANALYSIS:

The goal in multiple regressions is to predict scores on a dependent on the basis of scores on multiple independent or predictor variables. According to Aron & Aron, 1994’ Francis ,2003, Researchers are usually also interested in determining the amount of variance in the dependent variable that is explained by the predictor variables (i.e., R2) and in identifying the most efficient predictors in the multiple regression model

Ŷ = β1X1 + β2X2 + β3X3 + β4X4 …….+ βiXi

where Ŷ = the predicted value of the dependent variable

and β1…i = the standardized regression weights derived from the SPSS analyses

DEPENDENT VARIABLE

INDEPENDENT VARIABLE

β

Significance

R2

β CHANGE (STEP 2 TO 3)

Movie Watching Preference

Star Cast

0.553

0.0005

0.605

Movie Review

Star Cast

0.837

0.0005

0.701

Movie Watching Preference

Star Cast + Movie Review

0.924

-0.221

0.0005

0.0242

0.561

0.774*

* Partial mediating effect as significance < 0.05, with value=0.553-(-0.221)=0.774

FINDINGS:

The primary findings of the research are as follows:

 Effect of celebrity on movie watching preference is significant (celebrity test)

 Effect of movie review on movie watching preference is significant (review test)

We found the mediation effect to be present with movie reviews acting as the mediating variable. The Mediation effect was found to be equal to 77.4% (partial mediation)

Difference between β coefficients = 0.553 + 0.221 = 0.774

As the independent variable (star cast) was significant in the multi-variate regression and its corresponding β value was less than that observed when it was considered alone

Using Sobel’s calculator, the significance of mediation was confirmed.

There is a significant impact of movie reviews and star cast

on movie watching preferences

LIMITATIONS:

Some of the shortcomings of our study could be:

 Sampling methodology

We should have ideally done our study on a representative sample of the population. However,

considering the time and resource constraints we did what is best suited for a pilot survey and chose

convenience sampling wherein only probable target customers a possible movie watch would be surveyed.

 Questionnaire

The questions were administrated through an online survey instead of personal interviews. It would have been more useful to conduct personal interviews with opportunity to ask open ended questions and gather more information.

 Geographical scope is limited

Ideally we would have liked to conduct our research pan India but due to constraints of time and resources we were not be able to conduct a widespread survey.

 Effect of extraneous variables

There may be other factors affecting movie watching preference.

SCOPE FOR FUTURE WORK

1. The study can be made more exhaustive by taking into consideration external factors such as economic conditions, multiplex prices etc., which also influence and may drive purchase decision.

2. Also, a study can be conducted investigating the optimum pricing of the tickets and the influence of movie price on the purchasing decision of the consumers.

3. The degree of correlation between the external factors and internal movie attributes can be studied for example, during recession/high rates of unemployment ticket price would be a more important decision making factor as compared to a time when economy is booming.

4. Finally, factors such as advertising, sales promotion, after sales service and brand perception can be studied which may also affect the purchasing decision, before movies being launched by production houses.

CONCLUSION

From this research, we can conclude that star cast and review do have a significant impact

on the decision to watch a movie.

Other small findings according to us are that when it comes to actresses, people usually tend to go and watch an actresses movie if they have a personal liking for her. But when it comes to actors people tend to go more by the story line and the acting capabilities of the actors than going only by their liking for the specific actor. Out of the 159 respondents for the survey conducted by us, only 32 respondents said that they will go to watch a movie only because the actor which they like is in that movie whereas in the case of actresses, 112 respondents said they will go to watch a particular movie just because the actress which they like is in that particular movie. Taking a cue from this result we can say that while choosing an actress for a movie the producer should go by her popularity whereas in case of an actor he should go by his acting skills.

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