incentivizeWoM: Calculates the impact of incentivizing WoM communication

In WordOfMouth: Estimates Economic Variables for Word-of-Mouth-Campaigns

Calculates the impact of incentivizing WoM communication

Description

Calculates the impact of incentivizing WoM communication. Given a start forward probability and an expected end forward, probability this function calculates changes in demand, consumer surplus, profit, cost for incentivizing and economic welfare for i) keeping the optimal price for the start forward probability or ii) setting the optimized price for the expected forward probability.

Usage

incentivizeWoM(campaign, expProb, rewardCost = 0, keepStartPrice = FALSE)

Arguments

campaign	Word-of-Mouth campaign as instance of class WoMCampaign.
expProb	Expected forward probability when incentivizing WoM.
rewardCost	Cost per consumer acquired through the incentivization strategy.
keepStartPrice	Logical value indicating whether or not (default) the optimized price for the start forward probability will also used for the expected forward probability.

Value

Data frame containing the profit-maximizing price, the resulting demand, profit, consumer surplus and economic welfare for the start WoM intensity and the expected WoM intensity.

Author(s)

Michael Scholz [e-mail]

Thomas Woehner [e-mail]

Ralf Peters [e-mail]

See Also

computeOptimalPrice computeProfit computeConsumerSurplus

Examples

network <- new("WoMNetwork", size = 1000, avgConnections = 5)
campaign <- new("WoMCampaign", network = network, seedingSize = 10, forwardProbability = 0.2)
incentivization <- incentivizeWoM(campaign = campaign, expProb = 0.25, rewardCost = 0.05)
print(incentivization)

WordOfMouth documentation built on June 8, 2025, 1:47 p.m.