Optimizing the Abandonment of a Technological Innovation

The primary objective of this study is to reveal macro-level knowledge aid the optimization, evaluation, and strategic planning technological innovation abandonment. This research uses an exploratory data analysis (EDA) approach extract directional associative patterns (macro-level knowledge) assess abandonment optimization. Deterministic stochastic simulations are employed impact three factors on namely, a innovation’s diffusion rate, probability achieving given point insights revealed through graphical examination simulation provide optimization innovation. These enable decision-makers develop assessment framework for optimizing, evaluating, proactively at macro level.