TY - JOUR
T1 - Optimizing the abandonment of a technological innovation
AU - Parvin, Albert Joseph
AU - Beruvides, Mario G.
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021
Y1 - 2021
N2 - The primary objective of this study is to reveal macro-level knowledge to aid the optimiza-tion, evaluation, and strategic planning of technological innovation abandonment. This research uses an exploratory data analysis (EDA) approach to extract directional and associative patterns (macro-level knowledge) to assess technological innovation abandonment optimization. Deterministic and stochastic simulations are employed to reveal the impact of three factors on abandonment optimiza-tion, namely, a technological innovation’s diffusion rate, a technological innovation’s probability of achieving a given diffusion rate, and the point of abandonment. The patterns and insights revealed through the graphical examination of the simulation provide associative and directional knowledge to assess the abandonment optimization of technological innovation. These revealed patterns and insights enable decision-makers to develop an abandonment assessment framework for optimizing, evaluating, and proactively planning abandonment at the macro level.
AB - The primary objective of this study is to reveal macro-level knowledge to aid the optimiza-tion, evaluation, and strategic planning of technological innovation abandonment. This research uses an exploratory data analysis (EDA) approach to extract directional and associative patterns (macro-level knowledge) to assess technological innovation abandonment optimization. Deterministic and stochastic simulations are employed to reveal the impact of three factors on abandonment optimiza-tion, namely, a technological innovation’s diffusion rate, a technological innovation’s probability of achieving a given diffusion rate, and the point of abandonment. The patterns and insights revealed through the graphical examination of the simulation provide associative and directional knowledge to assess the abandonment optimization of technological innovation. These revealed patterns and insights enable decision-makers to develop an abandonment assessment framework for optimizing, evaluating, and proactively planning abandonment at the macro level.
KW - Abandonment optimization
KW - Diffusion rate
KW - Macro-level
KW - S-curve
KW - Technological innovation
KW - Technological innovation diffusion
UR - http://www.scopus.com/inward/record.url?scp=85105428079&partnerID=8YFLogxK
U2 - 10.3390/systems9020027
DO - 10.3390/systems9020027
M3 - Article
AN - SCOPUS:85105428079
VL - 9
JO - Systems
JF - Systems
SN - 2079-8954
IS - 2
M1 - 27
ER -