Market Simulation nodes by Scientific Strategy for KNIME - Community Edition version 4.0.0.v202007040653 by Decision Ready, LLC
The 'Tune Scenarios' node generates a single tuned 'Output WTP Matrix' based upon observations from a number of Market Conditions.
The 'Input Market Array' contains the Competitive Scenarios of different Market Conditions, along with the Products, Prices, and Quantities sold within each Scenario. The different Market Conditions might include historic observations from different sales seasons. Or the different Market Conditions might include Product Sensitivity data observed when Prices of the different Products are altered. Market Conditions vary when there are different competitive Products in the Market selling at Prices that change over time. As a result, the Quantity sold of each Product will typically be different under each Competitive Scenario.
The number of Products in each Competitive Scenario can vary. Products that are not included in one or more Market Conditions: (i) may not yet have entered, (ii) may have exited, or (iii) may be Out-of-Stock.
This node assumes the level of Customer Demand is constant, with only the nature of the Competition in the Market changing. When Competitors change their Prices or Product Assortment, Customers will make different Purchase decisions even when their underlying preferences remain constant.
As a result, this 'Tune Scenarios' node is not designed to interpret seasonality. Only one Output Willingness To Pay (WTP) Matrix is generated, and this must represent the unchanging Willingness to Pay of Customers across all Market Conditions. To simulate seasonality, start with the Output WTP Matrix from this node, then scale the Mean (and SD) of the WTP Matrix with the 'Scale Distributions' node.
This node is designed to find three values:
But individual Product Mean, SD, and Correlation values can be varied by the user according to the 'Input Product Attributes' table and the 'Conformity Boosters' in the Configuration Dialog. See below for more details.
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