Node Description

Geographic Feature

The Geographic Feature node calculates the ‘Lost Value’ of each Product due to shipping costs, waiting time, and pickup hassle. This ‘Lost Value’ is calculated from the perspective of each Virtual Customer. The node considers the Location of each Virtual Customer and the Location of each Product, then uses the shipping cost between the two locations to calculate ‘Lost Value’.

The node first places each Virtual Customer in a geographic ‘Location’ according to its ‘Population’. Customers can be located in different cities across the country, or in different districts within a city. Customers can be systematically located in blocks, or can be randomly scattered across all locations according to the relative populations at each. The node then compares the Location of each Customer against the Location of each Product.

A lookup table is used to determine the shipping cost from all Origins to all Destinations. The lookup table can be rate card that has been uploaded from a third-party shipping company. Or the lookup table can be generated upstream by calculating the physical distance or travel time between all Locations.

Finally, the node creates a ‘Lost Value’ Customer Distribution for each Product. If there a Customer can get a Product from many Locations, then the node automatically selects the Location that is most convenient for the Customer. That is, the Location which causes the Customer to suffer the least ‘Lost Value’. These ‘Lost Value’ Customer Distributions can be integrated with the Features of each Product by a downstream ‘Product Generator’ node.

‘Lost Value’ is subjective and will vary by Customer. Some Customers have an urgent need for rapid delivery, while others place a higher value on minimizing the cost of shipping. Customers may also have varying opinions about the reliability of each Product shipper. And Customers who are able to buy a Product directly from within a nearby store enjoy instant gratification and suffer no such ‘Lost Value’. Hence the weight of the ‘Lost Value’ suffered by each Virtual Customer can be varied by the node.

This Community Node documentation assumes you have already downloaded the open-source KNIME analytics platform and installed the free Market Simulation (Community Edition) plugin. If not, start by returning to Getting Started.

#1 Lost Value

Calculates the ‘Lost Value’ due to shipping costs and delays. The ‘Lost Value’ is calculated for each Customer and is therefore a Customer Distribution Feature that can be aggregted to the Products in the Market.


Customer Locations

The ratio of Customer ‘Population’ at each ‘Location’. In this case, the Populations have been listed as millions of people living in each city.

Product Locations

The ‘Location’ of each point of sale for each ‘Product’ in the Market. In this case, Products are only shipped out of New York, Los Angeles, and San Francisco.

Shipping Costs

The shipping ‘Cost’ from each ‘Origin’ to each ‘Destination’ in the Market. The shipping cost can be monetary rate card that has been uploaded from a third-party shipping company, or can be calculated as the physical distance or travel time between all Locations.



The Lost Value Variation is the degree of variation in weight a Virtual Customer may place upon ‘Lost Value’ compared to other Virtual Customers for all Products shipped from the same ‘Location’. A value of 0.2 indicates that some Customers will increase their ‘Lost Value’ by +/- 20%.



Customer Distributions

Two ‘Lost Value’ Customer Distributions are generated: one for the ‘Easy East’ Product that is shipped out of New York, the other for the ‘Wacky West’ Product which is shipped out of both Los Angeles and San Francisco (whichever is the least inconvenient).

Customers are distributed ‘In Small Blocks’. The first small block of Customers are located in New York, then Los Angeles, then Chicago, then San Francisco. The pattern repeats according to the Population ratio.

Average Lost Value

The average ‘Lost Value’ is calculated with the GroupBy node by Customer Location cities.