A research infrastructure for the social sciences & humanities

@article{Lundvall2022,

title = {China's catching-up in artificial intelligence seen as a co-evolution of corporate and national innovation systems},

author = {Bengt-Åke Lundvall and Cecilia Rikap},

url = {https://www.sciencedirect.com/science/article/pii/S0048733321001918},

doi = {https://doi.org/10.1016/j.respol.2021.104395},

issn = {0048-7333},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Research Policy},

volume = {51},

number = {1},

pages = {104395},

abstract = {Inspired by Christopher Freeman's work on how radical technical change opens up for shifts in world leadership and on the role of innovation systems in this process, this paper explores China's emergence as a lead country in artificial intelligence as reflecting a co-evolution of Corporate and National Innovation Systems. Taking Freeman's (1987) work on Japan as our lead, we focus on the domestic interaction within and on the openness of China's national innovation system. To follow up on his prediction of the increasing importance of big companies as network leaders, we introduce the concept “corporate innovation system” with special attention to two Chinese tech giants: Alibaba and Tencent.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{朱晓峰2022,

title = {国外政府数据开放研究的主题关联结构与演化态势},

author = {朱晓峰 and 葛 锐 and 蒋 勋},

editor = {情报科学},

url = {http://journal12.magtechjournal.com/jwk3_qbkx/CN/Y2022/V39/I1/109},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {情报科学},

volume = {39},

number = {1},

pages = {109-120},

abstract = {摘要： 【目的/意义】数字时代“开放政府数据”热潮产出了丰硕成果，对其研究主题结构和演化脉络进行全面、精 准的可视化揭示，有助于进一步丰富和完善该领域研究，科学地指导我国实践开展。【方法/过程】以 2000-2019 年 WOS数据库中“开放政府数据”主题文献为基础，借助新型SLM算法探测主题社区，梳理研究主题分布；同时嵌入 SNA方法，引入“传导率”指标定量评估主题社区成熟度和内外部关联，并利用Cortext平台构建时序演进过程。【结 果/结论】国外开放政府数据研究已形成四类主题社区：健康社区、开放数据社区、管理社区以及安全社区，目前仍 存在“主题遍布粒度不够细化、新兴主题社区亟需成长、演化脉络断续明显”等问题。【创新/局限】嵌入新型算法 SLM 划分主题社区，结合 LDA 模型对国外 OGD 研究主题关联与演化进行了完整阐释。但本文仅选取 WOS核心 库的相关主题文献作为数据源,存在进一步扩充的空间。



Abstract: 【Purpose/significance】The upsurge of“Open Government Data”in the digital era has produced fruitful results.A compre⁃hensive and accurate visualization of the thematic structure and evolution of its research will help to further enrich and improve the re⁃search and scientifically guide the practice in China.【Method/process】Firstly.literature on "Open Government Data" from the WOS database from 2000 to 2019 was selected.and keywords co-occurrence network was extracted.Secondly.the new SLM algorithm is used to detect the thematic community.and the distribution of the research is organized.At the same time.the Social Network Analysis meth⁃od is embedded and the "conductivity" index is introduced to quantitatively evaluate the maturity and internal and external relevance of the thematic community.Finally.the Cortext platform is used to construct the time series evolution process【. Result/conclusion】For⁃eign OGD research has formed four types of themed communities:Health communities.Open Data communities.Management communi⁃ties and Security communities. At present.there are still some problems.such as the granularity of the theme spread is not fine enough.the emerging theme community needs to grow up urgently.and the evolution line is obviously discontinuous【. Innovation/limitation】A new algorithm SLM is embedded to divide the thematic community.and then the thematic relevance and evolution of OGD research abroad are fully explained combined with LDA model.But this article only selects related subject literatures in the WOS core collection as the data source and there is room for further expansion.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Malanski2021,

title = {Labor in agrifood value chains: a scientometric review from Scopus},

author = {Priscila Duarte Malanski and Sandra Mara de Alencar Schiavi and Benoît Dedieu and Julio Cesar Damasceno},

url = {https://www.wageningenacademic.com/doi/pdf/10.22434/IFAMR2021.0066},

doi = {10.22434/IFAMR2021.0066},

year  = {2021},

date = {2021-12-24},

urldate = {2021-12-24},

journal = {International Food and Agribusiness Management Review},

pages = {1-20},

abstract = {Addressing labor issues is crucial to agrifood value chain analysis, improvements and sustainability.

However, the specific contribution of value chain approaches to discussions on labor in agriculture is still a research gap. To fill this gap, we reviewed the international literature on labor in agrifood value chains. We performed a scientometric analysis of the articles indexed in Scopus, which was composed by a bibliometric, diachronic and synchronic analysis. The main results show that labor in agrifood value chains is a relative new scientific community. Researchers’ interest evolved around three hotspots over the past 20 years, and five consolidated research domains. Our review provides an overview about the main characteristics of a rising scientific community, and a synthesis of knowledge produced to support scientific innovation on labor in agrifood value chains. Regarding chain agents, our results stress the importance of governance for improving employment and working conditions to promote chain sustainability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jaramillo2021,

title = {Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks},

author = {Andres F. Moreno Jaramillo and David M. Laverty and D. John Morrow and Jesús Martinez del Rincon and Aoife M. Foley},

url = {https://www.sciencedirect.com/science/article/pii/S0960148121010612},

doi = {https://doi.org/10.1016/j.renene.2021.07.056},

issn = {0960-1481},

year  = {2021},

date = {2021-12-01},

urldate = {2021-12-01},

journal = {Renewable Energy},

volume = {179},

pages = {445-466},

abstract = {In many countries distributed energy resources (DER) (e.g. photovoltaics, batteries, wind turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic appliances) are part of the ‘Green Deal’ to deliver a climate neutral society. Policy roadmaps, despite providing a framework and penetration targets for DER, often lack the network planning strategies needed to transition from passive to active distribution networks. Currently, DER's dynamic performance parameters and location identification techniques are not fully standardised. In fact, it can be very ad hoc. Standardised distributed load modelling and non-intrusive load monitoring (NILM) for equipment manufacturers, installers and network operators is critical to low and medium voltage network management in order to facilitate better balancing, flexibility and electricity trading across and within the power system for mass DER deployment. The aim of this paper is to fill this load modelling and NILM knowledge gap for DERto inform the ‘Green Deal’ transition and support standardisation. In the paper, existing load modelling techniques and NILM methodologies are critically examined to inform and guide research activity, equipment development and regulator thinking, as well as network operators. Seven key findings that need urgent attention are identified to support a smooth power system reconfiguration.},

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pubstate = {published},

tppubtype = {article}

}