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Assignment Marketing Analysis

Autor:   •  May 11, 2018  •  1,012 Words (5 Pages)  •  759 Views

Page 1 of 5

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movie.con = rbind(con1,con2,con3,con4,con5,con6,con7,con8)

movie.dir = c("=",">=",">=")

movie.rhs = c(1,1,1,1,1,1,1,1)

movie.sol = lp("max",movie_obj,movie.con,movie.dir,movie.rhs,all.bin=TRUE)

movie.sol

movie.sol$solution

The results shown in R is as follows:

- movie.sol$solution

- [1] 1 0 0 0 1 0 0 0 1 1 0 0 0 1 0

Demand (Given)

160

160

80

Movie/Screen

Doctor Strange

The Arrival

The Accountant

A

120

B

120

C

80

D

40

E

40

Total Attendance

160

160

80

In R, the results show:

- movie.sol

- Success: the objective function is 6036

This is how the total revenue of $6063 came about:

Total Revenue = (120 x 19.99) + (120 x 12.99) + (80 x 12.99) + (40 x 12.99) + (40 x 12.99)

= $6036.00

2.3

Discuss what you would do if the demand is uncertain, as in Question I of this assignment

If demand is uncertain as shown in Question 1, movie theatres ought to incorporate demand uncertainty into their production-planning processes by factoring in multiple demand scenarios to more accurately assess their resource allocation. By considering a variety of situations, theatres can optimize its sales revenue at the lowest level of risk.

Theatres can achieve informational advantage by investing in new demand forecasting technology to predict the performance of movies. For an example, on average, moviegoers consult 13 sources before they make a decision about what movie to watch. This active research and engagement is reflected in search query volume. Google can use search volume to predict with 94% accuracy the success of upcoming movies as much as four weeks ahead of their release dates.

2.4

In reality, what factors complicate this scheduling problem? List out as many factors as you can and organize them in your discussion. Briefly discuss how you could solve such a real problem.

There are several factors that may complicate the movie scheduling process:

- Unpredictable Demand

- Under-performing demand

- Unfulfilled demand

- Variance in customer behavior

- Customers may stick around for a different movie or the same movie at a different time if their first choice is no longer available

- Contractual Restraints

- Movie theatre hours

- Movie studio partnerships

- Theatres must show certain movies regardless of demand.

- Movie Specifications

- Length of each movie

- Pricing of each movie

- Availability in IMAX format

- Other Intangible Factors

- Weather condition

- Customer’s spending power

While contractual restraints lack adjustment flexibility and are outside the scope of our control, we can levitate the stress of schedule planning by acquiring more information. With additional research, movie theatre owners gain significant accuracy in predicting the demand for each movie. For instance, movie theatre owners can gain insight by comparing movie selection data from other theatres in areas with similar demographics.

Past data is often the best predictor of future data. Movie theatre owners may also approximate demand based specifications like on time of day, time of year, movie type, time elapsed since release date, movie performance/perceptions in other regions, etc. For more sophisticated calculations, one can assign probabilities to each possible scenario and utilize it as the basis to approximate prospective profit.

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