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@article{Reyes2023,

title = {Bibliometric Analysis and Comprehensive Review of Stormwater Treatment Wetlands: Global Research Trends and Existing Knowledge Gaps},

author = {Reyes, Nash Jett D. G. and Geronimo, Franz Kevin F. and Guerra, Heidi B. and Kim, Lee-Hyung},

url = {https://www.mdpi.com/2071-1050/15/3/2332},

doi = {10.3390/su15032332},

issn = {2071-1050},

year  = {2023},

date = {2023-01-27},

journal = {Sustainability},

volume = {15},

number = {3},

abstract = {Stormwater treatment wetlands are widely recognized as efficient and cost-effective solutions to growing stormwater problems. This study presented a new approach to evaluating the current status and trends in stormwater treatment wetlands research. The annual scientific productivity of different states was identified using a bibliometric analysis approach. The number of publications related to stormwater treatment wetlands has exhibited an increasing trend since the earliest record of publication. USA and China were among the states that had the most number of stormwater treatment wetlands-related publications and international collaborations. In terms of the population-to-publication ratio, Australia, Canada, and South Korea were found to have a higher level of scientific productivity. Analysis of frequently used keywords and terms in scientific publications revealed that the efficiency of stormwater treatment wetlands and the processes involved in the removal of nutrients and trace elements were adequately investigated; however, inquiries on the removal of organic micropollutants and emerging pollutants, such as pharmaceuticals and personal care products, microplastics, and industrial compounds, among others, are still lacking. Through the comprehensive review of related scientific works, the design, components, and primary factors affecting the performance of stormwater treatment wetlands were also identified. Future works that address the aforementioned knowledge gaps are recommended to optimize the benefits of stormwater treatment wetlands.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Milia2022,

title = {Local emergence, global expansion: understanding the structural evolution of a bi-lingual national research landscape},

author = {Matias Federico Milia and Ariadna Nebot Giralt and Rigas Arvanitis},

url = {https://link.springer.com/article/10.1007/s11192-022-04403-9},

doi = {10.1007/s11192-022-04403-9},

year  = {2022},

date = {2022-06-21},

urldate = {2022-06-21},

journal = {Scientometrics},

abstract = {Research institutions organize their scientific activities in an increasingly diverse landscape. In matters of global interest, research relies on an ever-more cross-disciplinary background, which reveals intriguing questions concerning the local dynamics vs. global audiences. This paper proposes new methodological tools to assess, from a strategic perspective, the evolution of a given research landscape. It relies on the Global Research Institute of Paris’ recent experience, a new interdisciplinary Institute focusing on globalization topics beyond the usual economic meaning. The Institute leans on a broad and diverse set of research units of the Université de Paris and relates to the broad landscape of social sciences in France. This article charts the evolution of French authors’ scientific publications on the Institute’s thematic interests in French and English. It focuses on the structural features of the debate, namely the volume, the underlying historical semantic structure, and its main thematic domains. The paper offers significant evidence to understand knowledge circulation dynamics and links that non-speaking countries’ scientific literature builds with the English one.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Franco2022,

title = {Producing and using artificial intelligence: What can Europe learn from Siemens’s experience?},

author = {Sebastián Fernández Franco and Juan M Graña and David Flacher and Cecilia Rikap},

url = {https://www.researchgate.net/profile/Juan-Grana-2/publication/360759657_Producing_and_using_artificial_intelligence_What_can_Europe_learn_from_Siemens's_experience/links/62a739f955273755ebe9963b/Producing-and-using-artificial-intelligence-What-can-Europe-learn-from-Siemenss-experience.pdf},

doi = {10.1177/10245294221097066},

year  = {2022},

date = {2022-06-10},

journal = {Competition & Change},

volume = {0},

pages = {1–30},

abstract = {This paper examines the innovation strategy of Siemens, a key player in Europe’s digital economy, by performing network and lexical analyses using data derived from Siemens’s patents and scientific publications since 1998. We observe that the company’s innovation efforts evolved from a broader attempt to develop internal information and communication technology (ICT) capabilities – alongside its historical industrial priorities – to a strategy focused on developing artificial intelligence (AI) for sector-specific and niche applications (such as life and medical sciences). As a result, it became dependent on tech giants’ clouds for accessing more general AI services and digital infrastructure. We build on the intellectual monopoly literature focusing on the effects of tech giants on other leading corporations, to analyse Siemens’s experience. By abandoning the development of general ICT and given the emergence of tech giants as digital economy intellectual monopolies, we show that Siemens is risking its technological autonomy towards these big tech companies. Our results provide clues to understand the challenges faced by Europe and its firms in relation to US and Chinese tech giants.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bordignon2021,

title = {Dataset of search queries to map scientific publications to the UN sustainable development goals},

author = {Frederique Bordignon},

url = {http://www.sciencedirect.com/science/article/pii/S2352340921000172},

doi = {https://doi.org/10.1016/j.dib.2021.106731},

issn = {2352-3409},

year  = {2021},

date = {2021-02-01},

journal = {Data in Brief},

volume = {34},

pages = {106731},

abstract = {The dataset includes search queries that can be used to identify scientific publications related to the United Nations Sustainable Development Goals (SDGs). We propose a new approach to mitigate the polysemy of terms as much as possible by targeting the most relevant subject areas for each SDG. In addition, we also used a text-mining tool to identify as many relevant phrases as possible. Publications identified through this process cannot be considered as evidence of the commitment of authors and their institutions to actions towards the targets established by the UN. However, they can be an accurate indicator of which research is relevant to the issues addressed by the SDGs, whether or not it is a direct contribution.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rikap2020,

title = {Amazon: A story of accumulation through intellectual rentiership and predation },

author = {Cecilia Rikap},

doi = {https://doi.org/10.1177/1024529420932418},

year  = {2020},

date = {2020-06-17},

journal = {Competition & Change},

abstract = {This article elaborates on intellectual monopoly theory as a form of predation and rentiership using Amazon as a case study. By analysing Amazon’s financial statements, scientific publications and patents, we show that Amazon’s economic power heavily relies on its systematic innovations and capacity to centralize and analyse customized data that orients its business and innovations. We demonstrate how Amazon’s innovation activities have evolved over time with growing importance of technologies related to data and machine learning. We also map Amazon’s innovation networks with academic institutions and companies. We show how Amazon appropriates intellectual rents from these networks and from technological cooperation with other intellectual monopolies. We argue that Amazon, as other data-driven monopolies, predates value from suppliers and third-party companies participating in its platform. One striking characteristic of Amazon is the low rate of reported profits. The centrality of innovations leads us to suggest an alternative calculation that shows that Amazon’s profits are not as low as they appear in Annual Reports. We also argue that lower profits are coherent with Amazon’s rentiership and predatory strategy since they contribute to the avoidance of accusations of excessive market power. Finally, the paper offers preliminary observations on: (i) the complementarities between financial and intellectual rentierism and (ii) how data-driven intellectual monopoly expands big corporations’ political power. Going beyond the specific case of Amazon, we thus contribute to a better understanding of the role of lead firms and power dynamics within innovation networks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rikap2019,

title = {Asymmetric Power of the Core: Technological Cooperation and Technological Competition in the Transnational Innovation Networks of Big Pharma},

author = {Cecilia Rikap},

url = {https://www.tandfonline.com/doi/abs/10.1080/09692290.2019.1620309},

year  = {2019},

date = {2019-06-26},

urldate = {2019-06-26},

journal = {Review of International Political Economy},

volume = {26},

number = {5},

pages = {987-1021},

abstract = {This article theoretically and empirically analyzes leader corporations’ innovation processes in contemporary capitalism. We highlight three characteristics: their transnational scope, the primacy of power or asymmetric relations exercised by leaders over the participants of their innovation circuits or networks, and the relevance of what we called technological competition and technological cooperation between leaders. Focusing on the latter, our theoretical contribution integrates the concepts of innovation circuit, global innovation network and modularity of knowledge production in order to elaborate a preliminary model for synthesizing leader’s technological competition and collaboration behaviors. This model is the general framework used for studying three big pharma’s innovation networks (Roche, Novartis and Pfizer). In particular, we study those networks by considering two outputs: scientific publications and patents. Network maps are constructed based on institutions’ co-occurrences, thus looking at who is co-authoring their publications and co-owning these corporations’ patents. We find that big pharmaceuticals co-produce together mainly generic knowledge modules, thus develop a strong technological cooperation. Simultaneously, to succeed in their technological competition they outsource stages of their innovation networks to subordinate institutions that, even if they contribute to achieve the innovation, will not be co-owners of the resulting patents, while big pharmaceuticals enjoy associated innovation rents.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}