e-infrastructure Roadmap for Open Science in Agriculture

A bibliometric study

The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.

This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.

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A Data Mining Perspective of the Newsvendor Problem


This study examined a modified newsvendor problem. The modified newsvendor problem concerned with how wholesalers can achieve maximum profits. Instead of building a profit function for the wholesalers and finding the optimal solutions as previous studies would do, this study proposed a novel, data mining approach to address the problem. Specifically, the modified newsvendor problem were transformed into a classification problem. According to a set of relevant attributes, we used the regularized multiple criteria linear programming (RMCLP) model to classify dealers into two categories, namely Type A and Type B, according to the associated order quantity of dealers. Experiments showed that the RMCLP model gave high accuracy in predicting to which type a dealer belong to. One important implication of this study is to provide insights into the design and development of supply chain coordination policy. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of the organizers of the 2013 international Conference on Information Technology and Quantitative Management

  • CN
  • US
  • CAS_Chinese_Acad_Sci (CN)
  • Capital_Normal_Univ (CN)
  • Univ_Nebraska_Omaha (US)
Data keywords
  • information technology
Agriculture keywords
  • supply chain
Data topic
  • big data
  • modeling
Document type

Inappropriate format for Document type, expected simple value but got array, please use list format

Institutions 10 co-publis
  • CAS_Chinese_Acad_Sci (CN)
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e-ROSA - e-infrastructure Roadmap for Open Science in Agriculture has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 730988.
Disclaimer: The sole responsibility of the material published in this website lies with the authors. The European Union is not responsible for any use that may be made of the information contained therein.