Analysis: Commercials at the

Royal TheaterKen Chapman, Ph. D.

K & C consultants: Complex Solutions to Simple Problems

Agenda Legal Issues

Background The Case for Fraud

Measuring Public Opinion Survey Goals Survey Results

Strategy Public Perceptions Possible Strategies Conclusions & Recommendations

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Background Royal Theater Patron (Tommy) Dissatisfied

20 minutes of commercials

Allegation of fraud on Royal Theater’s part

Threatens to file class action lawsuit.

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Presenter: K. Chapman

The Case for Fraud Misrepresentation Vs. Fraud

Prima Facie Case for Fraud A representation was made The representation was false When made, the representation was known to be false The plaintiff relied on the representation The plaintiff REASONABLY relied on the representation The plaintiff suffered damage (economic loss) as a result

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Presenter: K. Chapman

Simple Issues Assertion of Fact

The ticket did mention a 1:00 start time Knowledge of Falsity

The theater knew the movie began at 1:20 Intent to deceive

The theater made money from the ads

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Presenter: K. Chapman

Reliance Actual Reliance

Tommy made sure he was seated by 1 pm

Justifiable (Reasonable) Reliance Starting time specified in:

Newspaper ad Marquee Employee Movie ticket

General public knowledge

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Presenter: K. Chapman

Damage – Economic Loss Damage resulting from reliance:

20 minutes of lost time• Nominal• Punitive Damages

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Presenter: K. Chapman

The Case for Fraud Conclusion:

First four elements easy to establish

Difficulty establishing reasonable reliance and damage

Tommy HAS A WEAK case for fraud.

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Presenter: K. Chapman

Class Action Law Suit To participate, patrons must show

Reasonable Reliance Economic Damages

Conclusion: Most patrons won’t sue

Presenter: K. Chapman

9

The Main Issue: Customer Service Tommy’s complaints

He was lied to and forced to watch ads He didn’t like the movie

Customer Service Send the customer away happy

Refund Apology Coupon Outcome: No Lawsuit, No bad word of mouth.

How many patrons resent the ads? Your reputation depends on your patron’s

opinions of this behavior.

Objective – estimate the percentage of all theater patrons resenting commercials.

If less than 10% resent the commercials: Don’t adjust the policy on commercials

If 10% or more resent the commercials: Eliminate the commercials.

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Presenter: K. Chapman

Survey 1 Results 100 responses: 6% resent commercials.

95% confident that between 1.35% and 10.65% of moviegoers resent commercials.

We can’t rule out the possibility that 10% or more of the population resents commercials.

A bigger sample may be desirable

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Presenter: K. Chapman

Survey 2 Results 300 responses: 6% resent commercials

95% confident: The percentage of moviegoers who resent commercials is between 3.31% and 8.69%

Strong evidence that less than 10% resent commercials

Consortium’s rule: Take Tommy to Court

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Presenter: K. Chapman

Advertising & the Seating Period Adjusting the seating period

Eliminating the seating: The bad news Less popcorn sales Seating during the movie

Distinguish between seating time and show time

Eliminate ads & keep the seating period 3.31-8.69% will like eliminating the ads Lost Advertising Revenues Some patrons will miss the ads

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Presenter: K. Chapman

Strategic Issues: The Whole Picture Which customers resent commercials?

Would they pay more for special shows? Can ads be made more entertaining?

Can upset customers be treated differently? A free ticket to a future show might have

prevented a lawsuit

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Presenter: K. Chapman

Recommendations Apologize to Tommy and offer some free

tickets If he wants more, let him go to court.

Improve the accuracy of advertisements Premium shows with fewer ads

Don’t let customers leave angry Training Refund money if customers leave early

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Presenter: K. Chapman

Questions?

Appendix Slides:

16-21: Sampling Error 22-26: Confidence Interval Calculations

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Hypothesis Testing Errors Testing the population proportion:

H0: Settle p > 0.1H1: Go to trial p < 0.1

Risks of Taking Samples

Type I Error – Going to trial when the consortium should try to settle the case.

Type II Error – Avoiding going to trial by negotiating a settlement when the consortium should actually fight the case in court.

Larger survey sample sizes reduce the probability of both types of error.

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Estimating Confidence Interval for Population Proportion

point estimate + margin of error

.)ˆ1)(ˆ(ˆ 2/ nppzp a

Factors Effecting Sampling Error the sample size the level of confidence the estimated percentage of patrons who

resent the ads.

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Sample Size and Confidence Level The larger the sampling size, the smaller

the error. The greater the level of confidence, the

larger the sampling error that must be tolerated.

With a fixed sample size, an increase in the level of confidence will increase the width of the interval. The wider the interval, the less precise is our estimate.

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Sample Proportion The further away the estimated percentage is

from 50%, the smaller the sampling error. The sampling error is maximized when the

estimated percentage who resent the ads is 50%.

2405/03/23 24

The 95% Confidence Interval

6

ads of showing resent the whosample in the patrons ofnumber x

100 size sample

x

n

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Sample Proportion and 95% z

1.96

on)distributi normal standard of percentile(97.5th on distributi normal

standard theof each tailin .025 of area off cuts that table)normal (from value

.06

adsresent whosamplein patrons of proportionˆ

`025.

zz

nxp

05/03/23 26

Confidence Interval Calculation

.)ˆ1)(ˆ(ˆ 2/ nppzp a

.1065.0,0135.0

0465.06.

)0237(.96.106.

100)94)(.06(.96.106.

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Confidence Interval Calculation

Interval is 1.35% - 10.65%. With 95% confidence, the proportion of all

movie patrons who resent commercials is between 1.35% and 10.65%.

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