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Facebook and the Cinema:

              Assessing the Value of Facebook Fan
               Pages and its Impact on Facebook
                Users' Behaviors toward Movie
                         Consumption


Thesis Report by Florence Poirel     IESEG, International Business School
Master Graduate December 2011                           Lille-Paris, France
"The characteristics of all successful
communities: broadly shared, accessible set
    of opportunities, a shared sense of
responsibility for the success of the common
     enterprise, and a genuine sense of
                  belonging."
          (Bill Clinton, TED2007)
Introduction

Social networking is one of the largest actual
  trends and Facebook is one of its stages.

“Brands can take directions in social media
 today that would have been unlikely if not
         impossible five years ago”
       (Mignon, et al., 2011 p. 21)
Purpose
Assess the impact of the Facebook Movie Fan
Page in influencing Facebook users' attitudes
 and behaviors toward movie consumption

Understand the users' decision making process that
takes place from the movie awareness on the Facebook
page to the movie consumption, and how the behavior
of the Facebook users toward a movie can be influenced
by marketers via the related Facebook Movie Fan Page
Methodology

Using an inductive approach, constructs were
identified from a comprehensive literature
review and data was collected from survey
questionnaires administrated to students
(N=200).
Research Questions
• Do Facebook users visit Facebook movie Fan Pages?
   – Do Facebook users find Facebook Fan Pages useful?
   – How do they engage with the movie on Facebook?
   – How this technology platform and its social richness impacts on their decision making
     process regarding the movie legal consumption?

• How do they form their attitudes toward the movies?
   – Do Facebook users process information as other consumers?
   – What options do they consider when they intend to consume a movie?

• How are their intentions [to consume the movie] influenced?
   – How are their intentions influenced by their Facebook personal networks?
   – How are their intentions influenced by the different types of content that the Facebook
     Fan Page provides?

• How can companies drive Facebook users toward legal movie
  consumption?
Theoretical Model




Theory of Planned Behavior in the context of Facebook
Hypotheses

• H1: The more positive the perceived value of the FB Fan Page,
  the more favorable the attitude toward the behavior.

• H2: The more positive the perceived value of the FB Fan Page,
  the higher the perceived pressure.

• H3: The more positive the perceived value of the FB Fan Page,
  the lower the perceived risk.

• H4: The more positive the perceived value of the FB Fan Page,
  the more likely the intention to behave.
Hypotheses (cont.)

• H5: The more favorable the attitude toward the behavior, the
  more likely the intention to behave.

• H6: The higher the perceived pressure, the more likely the
  intention to behave.

• H7: The lower the perceived risk toward the behavior, the
  more likely the intention to behave.
Statistical Analysis

• VFP: Perceived Value of the Facebook Fan Page

• AB: Attitude Toward Behavior

• P: Perceived Pressure

• R: Perceived Risk

• IB: Intention To Behave

• f: function of
Reliability Analysis
• Alpha coefficient for the four items:
  αVFP = 0.843, higher than 0.7.
   Items have relatively high internal consistency.
  α²VFP = 0.711, then the perceived value of the FB fan page is
  explained by 71.1% of inner variance.

• Alpha coefficient for the ten items:
  αAB = 0.935, higher than 0.7
   Homogeneity is high (high internal consistency). α²AB =
  0.87, then the attitude toward the behavior is explained by
  87% of inner variance.
Simple Regression H1:
                  AB as a function of VFP

• Hyp 1: AB = f(VFP)
  AB= B0 + BVFP.VFP  AB= 1.307+ 0.212VFP

• R²=0.025: Perceived Value of the FB Page explains 2.5% of
  Attitude toward Behavior

• P-value =0.026, lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 1 is verified: the value that people see in the Facebook
  Fan page of movies does influence, or change, their attitude
  toward consuming the movie
Simple Regression H2:
                   P as a function of VFP

• Hyp 2: P = f(VFP)
  P= B0 + BVFP.VFP  P= 1.301+ 0.210VFP

• R²=0.024: Perceived Value of the FB Page explains 2.4% of
  Perceived Pressure

• P-value = 0.027: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 2 is verified: the value that people see in the Facebook
  Fan page of movies does influence, or change, the pressure
  perceived toward consuming the movie
Simple Regression H3:
                   R as a function of VFP

• Hyp 3: R = f(VFP)
  R= B0 + BVFP.VFP  R = 1.684 + 0.255 VFP

• R²=0.054: Perceived Value of the FB Page explains 5.4% of
  Perceived Risk

• P-value = 0.001: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 3 is verified: the value that people see in the Facebook
  Fan page of movies does influence, or change, the risk
  perceived toward consuming the movie
Simple Regression H4:
                   IB as a function of VFP

• Hyp 4: IB = f(VFP)
  IB= B0 + BVFP.VFP  IB = 1.213 + 0.219 VFP

• R²=0.092: Perceived Value of the FB Page explains 9.2% of
  Intention To Behave

• P-value = 0.000: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 4 is verified: the value that people see in the Facebook
  Fan page of movies does influence, or change, the Intention
  to consume the movie
Simple Regression H5:
                   IB as a function of AB

• Hyp 5: IB = f(AB)
  IB = B0 + BAB.AB  IB = 1.119 + 0.259 AB

• R²=0.235: Attitude Toward the Behavior explains 23.5% of
  Intention To Behave

• P-value = 0.000: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 5 is verified: the Attitude Toward consuming movies does
  influence, or change, the Intention to consume the movie
Simple Regression H6:
                    IB as a function of P

• Hyp 6: IB = f(P)
  IB = B0+ BP.P  IB = 1.120 + 0.260 P

• R²=0.235: Perceived Pressure explains 23.5% of Intention To
  Behave

• P-value = 0.000: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 6 is verified: the pressure perceived toward consuming
  movies does influence, or change, the Intention to consume
  the movie
Simple Regression H7:
                    IB as a function of R

• Hyp 7: IV = f(R)
  IB = B0+ BR.R  IB = 0.534 + 0.534 R

• R²=0.655: Perceived Risk explains 65.5% of Intention To
  Behave

• P-value = 0.000: lower than 0.05, so the variable coefficient β
  is different from zero, then the result is statistically significant

• Hyp 7 is verified: the risk perceived toward consuming movies
  does influence, or change, the Intention to consume the
  movie
Multiple Regression:
         IB as a function of VFP, AB, P, and R

• IB = f(VFP; AB; P; R)
  IB = B0 + BVFP.VFP + BAB.AB + BP.P + BR.R
   IB = 0.316 + 0.082.VFP + 0.064.AB + 0.011.P + 0.474.R

• R²=0.685: the different constructs explains 68.5% of the
  Intention To Behave

• The Attitude Toward the Behavior and the Perceived Pressure
  are in fact not significant since p-valueAB = 0.957 and p-valueP
  = 0.993.
Reduced Model:
             IB as a function of VFP and R

• IB = f (VFP ; R)
  IB = B0 + BVFP.VFP + BR.R  IB = 0.345 +0.087VFP +0.515R

• P-value = 0.000: lower than the agreed level of significance of
  5%, therefore the relationships are statistically significant

• The Perceived Value of the Facebook Fan Page and the
  Perceived Risk are pertinent explainers and predictors of the
  intention to behave formed in Facebook users' minds.
Conclusion
• Facebook users do not consider the consumption of
  free copies as very risky.

• Therefore increasing scary messages about illegal
  consumption might have less impact than increasing
  positive messages about the legal consumption.

• Creating an entertaining, trustworthy and practical
  page may then push people to legally consume
  movies.
For more information, please contact me at
     florencepoirel[at]gmail[dot]com

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Facebook and the Cinema Presentation

  • 1. Facebook and the Cinema: Assessing the Value of Facebook Fan Pages and its Impact on Facebook Users' Behaviors toward Movie Consumption Thesis Report by Florence Poirel IESEG, International Business School Master Graduate December 2011 Lille-Paris, France
  • 2. "The characteristics of all successful communities: broadly shared, accessible set of opportunities, a shared sense of responsibility for the success of the common enterprise, and a genuine sense of belonging." (Bill Clinton, TED2007)
  • 3. Introduction Social networking is one of the largest actual trends and Facebook is one of its stages. “Brands can take directions in social media today that would have been unlikely if not impossible five years ago” (Mignon, et al., 2011 p. 21)
  • 4. Purpose Assess the impact of the Facebook Movie Fan Page in influencing Facebook users' attitudes and behaviors toward movie consumption Understand the users' decision making process that takes place from the movie awareness on the Facebook page to the movie consumption, and how the behavior of the Facebook users toward a movie can be influenced by marketers via the related Facebook Movie Fan Page
  • 5. Methodology Using an inductive approach, constructs were identified from a comprehensive literature review and data was collected from survey questionnaires administrated to students (N=200).
  • 6. Research Questions • Do Facebook users visit Facebook movie Fan Pages? – Do Facebook users find Facebook Fan Pages useful? – How do they engage with the movie on Facebook? – How this technology platform and its social richness impacts on their decision making process regarding the movie legal consumption? • How do they form their attitudes toward the movies? – Do Facebook users process information as other consumers? – What options do they consider when they intend to consume a movie? • How are their intentions [to consume the movie] influenced? – How are their intentions influenced by their Facebook personal networks? – How are their intentions influenced by the different types of content that the Facebook Fan Page provides? • How can companies drive Facebook users toward legal movie consumption?
  • 7. Theoretical Model Theory of Planned Behavior in the context of Facebook
  • 8. Hypotheses • H1: The more positive the perceived value of the FB Fan Page, the more favorable the attitude toward the behavior. • H2: The more positive the perceived value of the FB Fan Page, the higher the perceived pressure. • H3: The more positive the perceived value of the FB Fan Page, the lower the perceived risk. • H4: The more positive the perceived value of the FB Fan Page, the more likely the intention to behave.
  • 9. Hypotheses (cont.) • H5: The more favorable the attitude toward the behavior, the more likely the intention to behave. • H6: The higher the perceived pressure, the more likely the intention to behave. • H7: The lower the perceived risk toward the behavior, the more likely the intention to behave.
  • 10. Statistical Analysis • VFP: Perceived Value of the Facebook Fan Page • AB: Attitude Toward Behavior • P: Perceived Pressure • R: Perceived Risk • IB: Intention To Behave • f: function of
  • 11. Reliability Analysis • Alpha coefficient for the four items: αVFP = 0.843, higher than 0.7.  Items have relatively high internal consistency. α²VFP = 0.711, then the perceived value of the FB fan page is explained by 71.1% of inner variance. • Alpha coefficient for the ten items: αAB = 0.935, higher than 0.7  Homogeneity is high (high internal consistency). α²AB = 0.87, then the attitude toward the behavior is explained by 87% of inner variance.
  • 12. Simple Regression H1: AB as a function of VFP • Hyp 1: AB = f(VFP) AB= B0 + BVFP.VFP  AB= 1.307+ 0.212VFP • R²=0.025: Perceived Value of the FB Page explains 2.5% of Attitude toward Behavior • P-value =0.026, lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 1 is verified: the value that people see in the Facebook Fan page of movies does influence, or change, their attitude toward consuming the movie
  • 13. Simple Regression H2: P as a function of VFP • Hyp 2: P = f(VFP) P= B0 + BVFP.VFP  P= 1.301+ 0.210VFP • R²=0.024: Perceived Value of the FB Page explains 2.4% of Perceived Pressure • P-value = 0.027: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 2 is verified: the value that people see in the Facebook Fan page of movies does influence, or change, the pressure perceived toward consuming the movie
  • 14. Simple Regression H3: R as a function of VFP • Hyp 3: R = f(VFP) R= B0 + BVFP.VFP  R = 1.684 + 0.255 VFP • R²=0.054: Perceived Value of the FB Page explains 5.4% of Perceived Risk • P-value = 0.001: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 3 is verified: the value that people see in the Facebook Fan page of movies does influence, or change, the risk perceived toward consuming the movie
  • 15. Simple Regression H4: IB as a function of VFP • Hyp 4: IB = f(VFP) IB= B0 + BVFP.VFP  IB = 1.213 + 0.219 VFP • R²=0.092: Perceived Value of the FB Page explains 9.2% of Intention To Behave • P-value = 0.000: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 4 is verified: the value that people see in the Facebook Fan page of movies does influence, or change, the Intention to consume the movie
  • 16. Simple Regression H5: IB as a function of AB • Hyp 5: IB = f(AB) IB = B0 + BAB.AB  IB = 1.119 + 0.259 AB • R²=0.235: Attitude Toward the Behavior explains 23.5% of Intention To Behave • P-value = 0.000: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 5 is verified: the Attitude Toward consuming movies does influence, or change, the Intention to consume the movie
  • 17. Simple Regression H6: IB as a function of P • Hyp 6: IB = f(P) IB = B0+ BP.P  IB = 1.120 + 0.260 P • R²=0.235: Perceived Pressure explains 23.5% of Intention To Behave • P-value = 0.000: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 6 is verified: the pressure perceived toward consuming movies does influence, or change, the Intention to consume the movie
  • 18. Simple Regression H7: IB as a function of R • Hyp 7: IV = f(R) IB = B0+ BR.R  IB = 0.534 + 0.534 R • R²=0.655: Perceived Risk explains 65.5% of Intention To Behave • P-value = 0.000: lower than 0.05, so the variable coefficient β is different from zero, then the result is statistically significant • Hyp 7 is verified: the risk perceived toward consuming movies does influence, or change, the Intention to consume the movie
  • 19. Multiple Regression: IB as a function of VFP, AB, P, and R • IB = f(VFP; AB; P; R) IB = B0 + BVFP.VFP + BAB.AB + BP.P + BR.R  IB = 0.316 + 0.082.VFP + 0.064.AB + 0.011.P + 0.474.R • R²=0.685: the different constructs explains 68.5% of the Intention To Behave • The Attitude Toward the Behavior and the Perceived Pressure are in fact not significant since p-valueAB = 0.957 and p-valueP = 0.993.
  • 20. Reduced Model: IB as a function of VFP and R • IB = f (VFP ; R) IB = B0 + BVFP.VFP + BR.R  IB = 0.345 +0.087VFP +0.515R • P-value = 0.000: lower than the agreed level of significance of 5%, therefore the relationships are statistically significant • The Perceived Value of the Facebook Fan Page and the Perceived Risk are pertinent explainers and predictors of the intention to behave formed in Facebook users' minds.
  • 21. Conclusion • Facebook users do not consider the consumption of free copies as very risky. • Therefore increasing scary messages about illegal consumption might have less impact than increasing positive messages about the legal consumption. • Creating an entertaining, trustworthy and practical page may then push people to legally consume movies.
  • 22. For more information, please contact me at florencepoirel[at]gmail[dot]com