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697. The heterogeneity effect in modeling innovation diffusion: Findings from an agent-based simulation experiment

Invited abstract in session TA-43: Simulation in innovation, stream Agent-based Models in Management, Economic and Organisation Sciences.

Tuesday, 8:30-10:00
Room: 99 (building: 306)

Authors (first author is the speaker)

1. Theresa Elbracht
Department of Business Administration and Economics, Bielefeld University
2. Christian Stummer
Department of Business Administration and Economics, Bielefeld University

Abstract

Analytical models of innovation diffusion need to reduce real-world complexity in order to be numerically tractable. The seminal Bass model, for example, assumes (i) that consumers are fully connected to each other and thus are correctly informed about the share of adopters in the population at each point in time and (ii) that consumers are identical in their innovativeness and their propensity to conform with others. Both assumptions are counterfactual with respect to real consumers, who can only oversee the behavior of a limited set of peers and have individual traits (e.g., some are innovators in adopting new products and do not care much about the share of adopters among their immediate peers, while others are laggards). In our research, we investigate whether accounting for consumer heterogeneity makes a difference with respect to a better fitting of computed sales to real-world sales (with data taken from Bass's work).

As a means of introducing consumer heterogeneity in an innovation diffusion model, we exploit the strengths of agent-based modeling, which allows us to connect consumers through a realistic social network and assign them individual attitudes (drawn from a normal distribution around the population's mean values provided by Bass). Our talk details the setup of four simulation experiments in which we vary consumer heterogeneity in the two above-mentioned dimensions, and discuss our findings.

Keywords

Status: accepted

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