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The model simulates the reserve prices dynamic according to the consumers’ characteristics and the consequent reactions of the customers to the shop reserve price variations and the sales.
In the model there are two types of consumers, that we characterize from different reserve prices and a shop characterized by a reserve price variable
The agents acts in the world in a random way and they purchase when they get in touch with the shop and their reserve price is less than the shop reserve price.
Consumers increase their reserve price according to the times when they purchase. Instead it decreases if come to contact with the shop and don't purchase.
The shop modifies your reserve price according to the prearranged objective attainment(sales numbers in a certain period).
The shop will apply to sales percentage adjustable thanks to a slider twice a year.
The users can make a choice before the simulation:
The total number of consumers for each one categories.
The shop reserve price.
The reserve price of each one categories of consumers.
The multiplier that imposes the objective of least sales period to be reached for the shop.
The maximum number of times when consumers enter into the shop and don't purchase, therefore, it will bring to the reserve price change.
The discounts percentage applicable in the two reference periods.
The movement extent that the consumers makes.
Go rewards for beginning the simulation.
The consumers purchase and modify their reserve price, contemporarily the shop modifies his own price in base to the attainment or less than the preset least objective.
The graphs will show the average of purchases that reflects the two consumers typologies and the prices average consumers and shop.
1)Simulation with means values
quant_careful_people 30
quant_uncareful_people 30
choose_shop_reserve_price 50
choose_reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 1
no_buy 3
discount 50
no_buy 3
movement 0,3
2)Increase of population
quant_careful_people 60
quant_uncareful_people 60
choose_shop_reserve_price 50
choose_reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 1
no_buy 3
discount 50
no_buy 3
movement 0,3
3)Decrase of shop's reserve price
quant_careful_people 50
quant_uncareful_people 50
choose_shop_reserve_price 20
choose_reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 1
no_buy 3
discount 50
no_buy 3
movement 0,3
4)Increase of shop's reserve price
quant_careful_people 60
quant_uncareful_people 60
choose_shop_reserve_price 100
choose_reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 1
no_buy 3
discount 50
5)Increase of sell target
quant_careful_people 30
quant_uncareful_people 30
choose_shop_reserve_price 50
choose reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 1
no_buy 3
discount 50
no_buy 3
6)Decrase of sell target
quant_careful_people 30
quant_uncareful_people 30
choose_shop_reserve_price 50
choose reserve_price_careful 50
choose_reserve_price_uncareful 60
multiplier 0,5
no_buy 3
discount 50
moviment 0,3
The model has been created after attending the course “Informatica e simulazione per l’economia”, held by Professor Pietro Terna, at the Faculty of Economics, University of Turin.