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日期:2020-11-21 10:10

DYNAMIC PRICING AT K-FASHION

MSBA7003

K-Fashion is a boutique store for women’s fashion apparel located in a big shopping mall at the

Causeway Bay. The store is targeting young female white-collar who care less about brand but

more about fashion and price.

For the next season (10 weeks), K-Fashion has ordered 200 different stock keeping units1

(SKUs) from a foreign supplier. Due to the long production and order lead time, K-Fashion can

place the order only once. Given the large store traffic at Causeway Bay, the store ordered 10

pieces for each SKU.

Your job is to focus on the pricing of the three SKUs—A, B, and C—of a particular style. The

sale of this style is independent of other styles. To simplify the analysis, we also assume that

the demand for each SKU is independent. For example, customers that suit size L will never buy

size M. The goal is to maximize the total revenue, given the fixed amount of inventory over the

1 An SKU is defined by the style, color, and size of a product. For example, a blue, size-M shirt of a unique style.

next 10 weeks. Any unsold inventory after the tenth week will be discarded with zero salvage

value. The constraint is that you must set the same price for all the three SKUs as they differ

only in color or size. The price can be adjusted every Monday. You must pick a price from the

set: {999, 899, 799, 699, 599, 499, 399, 299, 199, 99}.

Customers arrive randomly. Historical data suggests that the traffic is smaller in the first two

months or 8 weeks and larger in the last 2 weeks. For the first 8 weeks, the weekly total

number of visits to the store approximately follows normal distribution with a mean of 1000

and a standard deviation of 200; for the last 2 weeks, the weekly total visits also follows normal

distribution with a mean of 2000 and a standard deviation of 400. The number of visits will be

an integer.

According to past experience, about one out of fifty (1/50) customers on average will show

interests in the focal style (i.e., ask about the price and/or try it on). There is a 1/3 probability

that each of these customers who show interests will like one of the three SKUs, but they will

never like two or more SKUs of the same style. Nevertheless, showing interests does not mean

necessarily buying the product. A customer will buy a product only when his/her willingness-topay

is higher than or equal to the price. A customer’s willingness-to-pay for the focal style is

random and follows a uniform distribution between 0 and 1000 during the first 6 weeks; during

the last 4 weeks, the willingness-to-pay will be uniformly distributed between 0 and 600.

Please collaborate with your teammates to find out a scientific way of setting the price of

each week in order to maximize the total revenue. You can use Monte Carlo Tree Search or

other methods.

Your strategy will be tested in class (the last session). On that day, you will make decisions

on the fly, and your performance (total revenue) will be compared against other teams. The

team that achieves the highest total revenue will receive an award. The score of each team will

be determined according to a comparison against the highest possible total revenue. The team

that does not show up or participate in the competition will receive a score of zero.

Table: The Scoring Scheme

Your total revenue / The highest possible revenue Your Score

0.9 or above 10/10

0.7 or above 9/10

0.5 or above 7/10

Below 0.5 5/10


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