Title

Agent-Based Modeling Simulation And Its Application To Ecommerce

Keywords

Agent-based simulation; Consumer-to-consumer ecommerce; Neural networks; Peer-to-peer lending

Abstract

In the past decade, ecommerce created new business models. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. We investigate how actions of stakeholders (represented by agents) in an ecommerce system affect system performance. Viewing consumer-to-consumer ecommerce from a systems perspective calls for integration of different levels of behaviors. Complex interactions exist among stakeholders, the environment and available technology and agents is the best paradigm to mimic these behaviors. The presence of continuous and discrete behaviors coupled with stochastic and deterministic behaviors present challenges for using standalone simulation tools to simulate the business model. This research takes into account dynamic system complexity and risk. By combining system dynamics at the strategy level with agentbased models of consumer behaviors, and neural networks to find historical relationships, a representation of the business model that makes for sound basis of decision making can be achieved. The case study is based on a peer-to-peer lending environment.

Publication Date

1-1-2017

Publication Title

Artificial Intelligence: Advances in Research and Applications

Number of Pages

255-276

Document Type

Article; Book Chapter

Personal Identifier

scopus

Socpus ID

85044664127 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85044664127

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