BCAT Model: Agent-Based Simulation Parameters for Innovation Diffusion

BCAT model and simulation system parameters by Chung-Yuan Huang, last updated on 2026-05-19. The dataset contains parameters from an agent-based model combining adoption thresholds and opinion dynamics to study why high-quality products fail commercially. It includes results from sensitivity analyses run on four theoretical network structures.

Use Cases

• Calibrating agent-based models for innovation diffusion based on the described adoption threshold and opinion dynamics mechanisms.
• Analyzing the influence of network structure on product adoption based on the four theoretical networks (regular lattice, random, small-world, scale-free) mentioned.
• Conducting sensitivity analysis for social simulation models based on the identified key factors like adoption threshold mean and bounded confidence.
• Studying the testimony effect and opinion-adoption gaps in theoretical models of social coordination.

Strengths

• Model parameters are derived from a series of sensitivity analysis simulation experiments, as described.
• The dataset is licensed under CC-BY-4.0, permitting open sharing and adaptation.
• The underlying research examines four distinct theoretical network structures for social interactions.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small at 13.5 KB, indicating limited scope, likely containing only model parameters and summary results.

Provenance

Source

Chung-Yuan Huang via figshare

Collection Method

Parameters generated from agent-based simulation experiments.

Freshness

Last updated 2026-05-19 18:00:10; freshness should be verified.