This paper proposes a novel model-based approach to technology planning and roadmapping, consisting of two complementary steps: technology forecasting and game-theoretic planning. The inherent uncertainty of target technology performances, timelines and risks impact the roadmapping process. Reducing this uncertainty is a major challenge and allows elaborating different options and scenarios. A formal methodology is proposed for quantitative forecasting in a multi-dimensional space (different performance metrics and time) based on past technology development trend information. The method adopts concepts and approaches from econometrics and is formulated as a convex optimization problem with different constraints on the frontier's shape. It provides useful product line assessment benchmarks and helps to set reasonable goals for future technology developments.

Game-theoretic planning allows addressing the strategic decisions to take, considering the technology landscape, markets, and competition. The strategic decisions affect in turn other companies as well, which is the basis for the application of game theory, in the form of best-response functions to determine the subsequent reactions and movements of rivals in a technological landscape. The result is a simulation of a sequential game in technology space, allowing evaluating possible technological development pathways and determining optimal models on the Pareto frontiers, potential targets for technology roadmapping.

本文提出了一种新的基于模型的技术规划和路线图方法，包括两个互补的步骤：技术预测和博弈论规划。目标技术性能、时间表和风险的固有不确定性会影响路线图制定过程。减少这种不确定性是一项重大挑战，并允许详细说明不同的选项和情景。基于过去的技术发展趋势信息，提出了一种在多维空间（不同的性能指标和时间）中进行定量预测的正式方法。该方法采用计量经济学的概念和方法，将其表述为对边界形状具有不同约束的凸优化问题。

考虑到技术格局、市场和竞争，博弈论规划允许解决要采取的战略决策。战略决策反过来也会影响其他公司，这是博弈论应用的基础，以最佳响应函数的形式确定竞争对手在技术领域的后续反应和动作。结果是模拟技术空间中的顺序博弈，允许评估可能的技术发展途径并确定帕累托前沿的最佳模型，技术路线图的潜在目标。