Garlick, Michael and Chli, Maria (2010). Agent-based simulation of lock-in dynamics in a duopoly. IN: 9th International Joint Conference on Autonomous Agents and Multiagent Systems. 2010-05-10 - 2010-05-14.
Abstract
Lock-in is observed in real world markets of experience goods; experience goods are goods whose characteristics are difficult to determine in advance, but ascertained upon consumption. We create an agent-based simulation of consumers choosing between two experience goods available in a virtual market. We model consumers in a grid representing the spatial network of the consumers. Utilising simple assumptions, including identical distributions of product experience and consumers having a degree of follower tendency, we explore the dynamics of the model through simulations. We conduct simulations to create a lock-in before testing several hypotheses upon how to break an existing lock-in; these include the effect of advertising and free give-away. Our experiments show that the key to successfully breaking a lock-in required the creation of regions in a consumer population. Regions arise due to the degree of local conformity between agents within the regions, which spread throughout the population when a mildly superior competitor was available. These regions may be likened to a niche in a market, which gains in popularity to transition into the mainstream.
Divisions: | ?? 50811700Jl ?? |
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Additional Information: | © IFAAMAS |
Event Title: | 9th International Joint Conference on Autonomous Agents and Multiagent Systems |
Event Type: | Other |
Event Dates: | 2010-05-10 - 2010-05-14 |
Uncontrolled Keywords: | simulation and modelling,model development,modelling methodologies,economics,sociology,experimentation,human factors,agent-based simulation,consumer behaviour,lock-in |
Last Modified: | 14 Nov 2024 08:18 |
Date Deposited: | 05 Aug 2013 10:18 |
Full Text Link: |
http://www.cse. ... u.ca/AAMAS2010/ |
Related URLs: | PURE Output Type: | Paper |
Published Date: | 2010 |
Authors: |
Garlick, Michael
Chli, Maria ( 0000-0002-2840-4475) |