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Heuristic decision-making in the green energy context:Bringing together simple rules and data-driven mathematical optimization

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  • Krawinkler, Andreas
  • Breitenecker, Robert J.
  • Maresch, Daniela

Abstract

Heuristic decision-making based on simple rules can help managers to address a venture's most critical bottlenecks to seize business opportunities, especially in highly complex and dynamic contexts such as green energy activity. Unleashing that potential requires the simple rules to be accountable. However, identifying and addressing the bottleneck necessitates choosing the right evidence base, and choosing the evidence base is only possible when the bottlenecks are known beforehand. Due to this challenge, managers face a dilemma in developing simple rules. We suggest a novel approach to address this dilemma that integrates the principles of simple rules and data-driven mathematical optimization, and demonstrate its feasibility in the highly complex and dynamic context of green energy. Based on the results of this study, we develop and discuss far-reaching implications for theory, practice, and policy, and provide attractive avenues for future research.

Suggested Citation

  • Krawinkler, Andreas & Breitenecker, Robert J. & Maresch, Daniela, 2022. "Heuristic decision-making in the green energy context:Bringing together simple rules and data-driven mathematical optimization," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    • Handle: RePEc:eee:tefoso:v:180:y:2022:i:c:s0040162522002220
    DOI: 10.1016/j.techfore.2022.121695
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    3. agarwal, shekhar, 2022. "India’s Rising Technology Economy: Sources and Consequences," OSF Preprints x6yzm, Center for Open Science.

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