Assessing emerging sustainability-oriented technologies: the case of precision agriculture

The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs involves a wide range of emerging technologies, some of which are highly uncertain and may have the potential to transform an existing industry....

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Published inScientometrics Vol. 129; no. 6; pp. 2969 - 2998
Main Authors Rennings, Michael, Baaden, Philipp, Block, Carolin, John, Marcus, Bröring, Stefanie
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.06.2024
Springer Nature B.V
Subjects
Agriculture
Cluster analysis
Clusters
Computer Science
Information Storage and Retrieval
Library Science
New technology
Precision agriculture
Sustainability
Sustainability transitions
Sustainable development
Precision agriculture
Emerging technology
Spectral clustering
Sustainability-oriented innovation
Technology assessment
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Abstract The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs involves a wide range of emerging technologies, some of which are highly uncertain and may have the potential to transform an existing industry. Thus, the identification and assessment of emerging technologies is pivotal for established companies to evaluate business opportunities as well as for researchers and policy makers to support the transition to a more sustainable economy. Therefore, we aim to contribute by offering a new approach that seeks to assess such emerging technologies that contribute to sustainability transition (i.e., sustainability-oriented technologies (SOTs)) by means of spectral cluster analysis based on the semantic similarities of scientific research articles in the field of precision agriculture (PA); a case example where multiple SOIs occur. Our analyses reveal that spectral cluster analysis is a suitable approach for assessing emerging SOTs. In addition, multi-perspective assessments based on, inter alia , related United Nations Sustainable Development Goals, Web of Science subject categories, strategic diagrams, and business models allows to render a holistic assessment of a scientific research area (in this case PA) and its emerging SOTs as well as their evolution into commercial SOIs.
AbstractList The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs involves a wide range of emerging technologies, some of which are highly uncertain and may have the potential to transform an existing industry. Thus, the identification and assessment of emerging technologies is pivotal for established companies to evaluate business opportunities as well as for researchers and policy makers to support the transition to a more sustainable economy. Therefore, we aim to contribute by offering a new approach that seeks to assess such emerging technologies that contribute to sustainability transition (i.e., sustainability-oriented technologies (SOTs)) by means of spectral cluster analysis based on the semantic similarities of scientific research articles in the field of precision agriculture (PA); a case example where multiple SOIs occur. Our analyses reveal that spectral cluster analysis is a suitable approach for assessing emerging SOTs. In addition, multi-perspective assessments based on, inter alia , related United Nations Sustainable Development Goals, Web of Science subject categories, strategic diagrams, and business models allows to render a holistic assessment of a scientific research area (in this case PA) and its emerging SOTs as well as their evolution into commercial SOIs.
The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs involves a wide range of emerging technologies, some of which are highly uncertain and may have the potential to transform an existing industry. Thus, the identification and assessment of emerging technologies is pivotal for established companies to evaluate business opportunities as well as for researchers and policy makers to support the transition to a more sustainable economy. Therefore, we aim to contribute by offering a new approach that seeks to assess such emerging technologies that contribute to sustainability transition (i.e., sustainability-oriented technologies (SOTs)) by means of spectral cluster analysis based on the semantic similarities of scientific research articles in the field of precision agriculture (PA); a case example where multiple SOIs occur. Our analyses reveal that spectral cluster analysis is a suitable approach for assessing emerging SOTs. In addition, multi-perspective assessments based on, inter alia, related United Nations Sustainable Development Goals, Web of Science subject categories, strategic diagrams, and business models allows to render a holistic assessment of a scientific research area (in this case PA) and its emerging SOTs as well as their evolution into commercial SOIs.
Author Rennings, Michael
Baaden, Philipp
Block, Carolin
Bröring, Stefanie
John, Marcus
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Emerging technology
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Snippet The pressing need for a transition towards a more sustainable economy has given rise to sustainability-oriented innovations (SOIs). The development of SOIs...
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SubjectTerms Agriculture
Cluster analysis
Clusters
Computer Science
Information Storage and Retrieval
Library Science
New technology
Precision agriculture
Sustainability
Sustainability transitions
Sustainable development
Title Assessing emerging sustainability-oriented technologies: the case of precision agriculture
URI https://link.springer.com/article/10.1007/s11192-024-05022-2
https://www.proquest.com/docview/3075277841
Volume 129
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