@misc{10481/97247,
year = {2017},
url = {https://hdl.handle.net/10481/97247},
abstract = {Marketers have to constantly make decisions on how to implement word-of-mouth (WOM)
programs and a well-developed decision support system (DSS) can provide them with valuable
assistance. The authors propose an agent-based framework that aggregates social network-level
individual interactions to guide the construction of a successful DSS for WOM. The framework
presents a set of guidelines and recommendations to: (1) involve stakeholders, (2) follow a
data-driven iterative modeling approach, (3) increase validity through automated calibration, and
(4) understand the DSS behavior. This framework is applied to build a DSS for a freemium app,
where premium users discuss the product with their social network and promote the viral
adoption. After its validation, the agent-based DSS forecasts the aggregate number of premium
sales over time and the most likely users to become premium in a near future. The experiments
show how the DSS can help managers by forecasting premium conversions and increasing the
number of premiums via targeting and reward policies.},
title = {Building agent-based decision support systems for managing word-of-mouth programs: a freemium application},
doi = {https://doi.org/10.1509/jmr.15.0443},
author = {Chica Serrano, Manuel and Rand, William},
}