Tag Archives: R&D Management


The practice of using technology monitoring to keep track of technological advances is increasingly valued, and its systematic use is understood as essential to business in the new knowledge economy. The structuring of the technological monitoring process has become a growing need for organizations to keep up with the significant and rapid changes of technology in their core business and to better understand its business impact in order to support the decision‐making process of companies. An effective technology monitoring process should be based on a company’s business needs and on the information required for the fitting to strategic guidelines. This encompasses the right selection of databases, the establishment of the search strategy and keywords to be applied, the screening of the retrieved information, the analysis and consolidation of this information, and the right format and display of the relevant data and future trends to help the management decision. Photovoltaic solar energy reached the capacity of 139 GW in 2013, being an expanding market with a high number of government funding projects in the United States and in the European Union. Therefore, a survey was carried out about the new technologies and related business scenarios for this kind of power generation, using technology monitoring tools. Energy generation via photovoltaic cells has been known for a long time, since the Becquerel studies in the XIX century. Solar photovoltaic energy enables the generation of distributed electric energy, preventing long transmission and distribution lines, besides being a silent energy source that can be easily integrated into buildings without the need of additional installation areas; for these reasons, its application is being fostered by government programs.   The main step of the technology monitoring methodology is discussed, and the peculiarities and difficulties encountered in the process are pointed out. A survey of the scientific and technological developments in this area of knowledge was carried out, using patents and scientific papers with the time frame from the beginning of 2008 to the end of 2013. The lessons learned in this process and the major facilitating factors and difficulties for the retrieval, screening and analysis of the information collected are reported.

Author(s): Luiz Fernando Leite , Flavia Maria Lins Mendes, and Suzanne De Oliveira Rodrigues Schumacher
Organization: Federal University of Rio de Janeiro
Source: IAMOT 2015 Conference Proceedings http://iamot2015.com/2015proceedings/documents/P310.pdf
Year: 2015

2004 DISSERTATION: A Text Mining Framework for Discovering Technological Intelligence

In this thesis, a framework based on text mining techniques is proposed to discover useful intelligence implicit in large bodies of electronic text sources. This intelligence is a prime requirement for successful R&D management. This research extends the approach called “Technology Opportunities Analysis” (developed by the Technology Policy and Assessment Center, Georgia Institute of Technology, in conjunction with Search Technology, Inc.) to create the proposed framework. The commercialized software, called VantagePoint, is mainly used to perform basic analyses. In addition to utilizing functions in VantagePoint, this thesis also implements a novel text association rule mining algorithm for gathering related concepts among text data. Two algorithms based on text association rule mining are also implemented. The first algorithm called “tree-structured networks” is used to capture important aspects of both parent-child (hierarchical structure) and sibling relations (non-hierarchical structure) among related terms. The second algorithm called “concept-grouping” is used to construct term thesauri for data preprocessing. Finally, the framework is applied to Thai xvi S&T publication abstracts toward the objective of improving R&D management. The results of the study can help support strategic decision-making on the direction of S&T programs in Thailand.

Doctoral candidate: Alisa Kongthon
Committee: Alan L. Porter, Xiaoming Huo, Donghua Zhu, Jye-Chyi Lu, and Susan E. Cozzens
University: Georgia Tech
Degree program: Doctor of Philosophy in Industrial Engineering
Year: 2004

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