Title
Alternative supply chain production-sales policies for new product diffusion: An agent-based modeling and simulation approach.
Abstract
Applying agent-based modeling and simulation (ABMS) methodology, this paper analyzes the impact of alternative production-sales policies on the diffusion of a new generic 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" production-sales 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 in choosing 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. Published by Elsevier B.V.
Year
DOI
Venue
2012
10.1016/j.ejor.2011.07.040
European Journal of Operational Research
Keywords
Field
DocType
Supply chain management,Agent-based simulation,New product diffusion,Word-of-mouth
Economics,Social network,Modeling and simulation,Word of mouth,Supply chain management,Supply chain,Generic Product,Complex adaptive system,Operations management,New product development
Journal
Volume
Issue
ISSN
216
2
0377-2217
Citations 
PageRank 
References 
20
0.93
16
Authors
4
Name
Order
Citations
PageRank
Mehdi Amini1453.78
Tina Wakolbinger214310.04
Michael Racer3425.03
Mohammad G. Nejad4200.93