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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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