Application of Simulation and Optimization Approaches in Supply-Constrained Innovation Diffusion
Type of DegreeDissertation
Industrial and Systems Engineering
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When introducing a new product, firms face a hierarchy of decisions at the strategic and operational levels including capacity sizing, time to market or starting sales, initial inventory required by the product's release time, and production management in response to changes in the demand. Firms also face the dilemma of how to support a fast and substantial take-off by targeting the right population of potential consumers for seeding. This dissertation explores the above inter-dependent decisions using a diverse set of analysis tools, namely agent-based modeling and simulation, Monte Carlo simulation, continuous-time mathematical models, and parametric and nonparametric statistical approaches. This work contributes to the marketing and operations management literature in five significant ways: (1) it shows that ignoring supply and demand uncertainties may lead to potentially incorrect decisions and that the optimal decision may change if risk is used as the primary performance measure instead of the commonly used expected (mean) profit; (2) it provides insights about the optimal introduction time of a new generation of a new product under market expansion and cannibalization; (3) it provides a joint analysis of marketing and production strategies and shows that a sequential decision-making process would lead to suboptimal decisions and reduced profit; (4) it explores the importance of the social network structure and individuals' interactions on the optimal combination of seeding and build-up policies; and, (5) it presents a more realistic analysis by relaxing many of the assumptions of previous studies and provides empirical evidence by a successful application to the case of the diffusion of Sony's PlayStation3 game console in Europe. The findings of this work and its future extensions along the lines discussed in the dissertation have important implications for innovation diffusion research and can potentially help companies make better decisions regarding production and marketing of their new products.