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Cited by 204

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Technological innovation for sustainable growth: An ontological perspective

Open access
Cancino, Christian A., La Paz, Ariel I., Ramaprasad, Arkalgud, Syn, Thant·2018·Journal of Cleaner Production

Abstract

Abstract Technological innovations are seen as means to optimize the efficient and clean use of vital resources in social-biological-economic systems. However, partial theoretical perspectives and experiences of their effects can lead to significant oversight of their potential and limitations. There is a need to manage technological innovations for sustainable growth from a holistic perspective, systemically and systematically. To do so, we present and validate an ontological framework, map the current body of knowledge, and identify the emphases and gaps in the domain. The ontological framework is constructed from the common terminology of the domain. The analysis is based on a map of 375 research papers published in the most prestigious journals relevant to the domain. The results show significant gaps in the research to fulfil the potential. Future research can be directed to fill these gaps.

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Crossref · 10.1016/j.jclepro.2018.01.059

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Metadata

Authors
Cancino, C. A., La Paz, A. I., Ramaprasad, A., & Syn, T.
Venue
Journal of Cleaner Production
Publisher
Elsevier BV
Published
2018-04
Volume
179
Pages
31-41
ISSN
0959-6526 (ISSN-L)
OpenAlex
W2788007503
Cited by
204
References
3
FWCI
22.81
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Technological innovation for sustainable growth: An ontological perspective. https://app.cochat.ai/papers/10.1016/j.jclepro.2018.01.059
The paper
Cancino, C. A., La Paz, A. I., Ramaprasad, A., & Syn, T. (2018). Technological innovation for sustainable growth: An ontological perspective. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2018.01.059

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.