Market Choices Driven by Reference Groups: A Comparison of Analytical and Simulation Results on Random Networks

Area of Science:

• Computational Social Science
• Network Science
• Behavioral Economics

Background:

• Reference groups significantly influence consumer choices, including brand selection.
• Theoretical models exist for understanding this influence but often lack network considerations.

Purpose of the Study:

• To simulate a model of reference group influence on market choices.
• To extend theoretical findings to network structures.
• To investigate conditions for market bistability.

Main Methods:

• Simulation of a reference group influence model on three random graph types: Erdos-Renyi, Barabasi-Albert, and Watts-Strogatz.
• Comparison of simulation-based equilibrium estimates with theoretical model equilibria.
• Analysis of model behavior across different network connectivities and clustering coefficients.

Main Results:

• Simulations qualitatively matched the theoretical model's behavior.
• Quantitative predictions were viable approximations for graphs with high connectivity and low clustering.
• Increasing positive response towards a reference group can create bistable market situations with two equilibria.
• Market dominance by respective brands is achievable at these equilibria.
• The task of creating bistability is facilitated by larger reference groups.

Conclusions:

• Simulation results validate and extend the theoretical model of reference group influence to network contexts.
• Network properties, specifically connectivity and clustering, impact the accuracy of quantitative predictions.
• Strategic manipulation of reference group influence can lead to predictable market states (bistability).
• The size of the reference group is a critical factor in achieving market control through influence.