| Summary: | Applying Agent-Based Modeling and Simulation (ABMS) methodology, this paper
analyzes the impact of alternative production-sales policies on the diffusion of a new
product and the generated NPV of profit. The key features of the ABMS model, that
captures the marketplace as a complex adaptive system, are: (i) supply chain capacity is
constrained; (ii) consumers' new product adoption decisions are influenced by marketing
activities as well as positive and negative word of mouth (WOM) between consumers; (iii)
interactions among consumers taking place in the context of their social network are
captured at the individual level; and (iv) the new product adoption process is adaptive.
Conducting over 1 million simulation experiments, we determined the "best" productionsales
policies under various parameter combinations based on the NPV of profit generated
over the diffusion process. The key findings are as follows: (1) on average, the build-up
policy with delayed marketing is the preferred policy in the case of only positive WOM as
well as the case of positive and negative WOM. This policy provides the highest expected
NPV of profit on average and it also performs very smoothly with respect to changes in
build-up periods. (2) It is critical to consider the significant impact of negative word-of-mouth
on the outcomes of alternative production-sales policies. Neglecting the effect of
negative word-of-mouth can lead to poor policy recommendations, incorrect conclusions
concerning the impact of operational parameters on the policy choice, and suboptimal
choice of build-up periods. (authors' abstract)
|
|---|
