Título:
A market-driven algorithm for the assessment of promising bio-based chemicals.
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Autor:
Helal, Agustín
Kreimerman, Roberto
Gutiérrez, Soledad
Torres, Ana I.
Kreimerman, Roberto
Gutiérrez, Soledad
Torres, Ana I.
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Tipo de documento:
Artículo
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Palabras clave:
Biorefineries
Five Forces (Porter) analysis
PLA
Product portfolio
Five Forces (Porter) analysis
PLA
Product portfolio
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Año de publicación:
2019
Contenido:
Resumen:
Actors willing to participate in biomass-based value chains need to screen through a vast number of product options to identify the most promising ones. This is challenging as (a) processes for biomass-based chemicals/materials are still in development stage, thus do not perform well in techno-economic evaluations, (b) factors as which and how many links of the value chain should be uptaken, are not fully addressed by techno-economic analysis. Inspired by the Five Forces framework for industry analysis, this work presents an algorithm-like approach for assessing the attractiveness of biomass-based products. The algorithm relies on market data to classify the different sources as posing a low, medium, or high threat to the profit of a company that is considering production of a certain chemical/material. The approach is exemplified by analyzing the attractiveness of the biomass-lactic acid-polylactic acid route in the context of defining pathways for development of a biomass-based industry in Uruguay.
Descripción:
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Editorial:
American Institute of Chemical Engineers (AIChE)
EN:
AIChE Journal, vol. 65, no 12, dec. 2019, pp. 1-16.
Financiadores:
Agencia Nacional de Investigación e Innovación, Uruguay, Número de concesión de la subvención : FSE_1_2015_1_109976.
Citación:
Helal, A., Kreimerman, R., Gutiérrez, S. y otros. "A market-driven algorithm for the assessment of promising bio-based chemicals". AIChE Journal. [en línea]. 2019, vol. 65, no 12, pp. 1-16. DOI: 10.1002/aic.16775
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Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| HKGT19.pdf | Versión no definitiva | 4.41 MB | Adobe PDF |