Перспективные направления исследований в области бизнес-информатики: Материалы XI международной конференции
This volume contains a set of dedicated scientific contributions to the 11th International Conference on Perspectives in Business Informatics Research. The peer-reviewed and tentatively selected papers cover a broad scope of modern research in Business Informatics, and include new results in such domains as: Knowledge Management and Semantic Web, Business and information systems development, Business, people and systems interoperability and Business intelligence.
In 2012 the conference is hosted by National Research University Higher School of Economics (NRU HSE) in Nizhny Novgorod. Our university is Russia’s leader in the field of scientific research conducted at the junction of Management, Economics and Governance of IT. In particular, NRU HSE is the originator and the promoter of Business Informatics in Russia. Therefore NRU HSE pays particular attention to sustainable international cooperation and leverages scientific research in that area.
We strongly believe that materials presented will contribute to further advances in Business Informatics and will foster intensive scientific cooperation between researchers.
This article is dedicated to the analysis of effectiveness of special economic zones (SEZ), a rather new, but promising phenomenon in Russian Federation economy. It includes general analysis of SEZ, its reaction to the world financial crisis, analysis of innovation implementation SEZ (II SEZ), and, in particular, its IT-potential. At the end, the cases related to IT products realized in these zones are described and some economic and financial indicators suitable to describe the dynamics of development of these agglomerations of IT enterprises are given.
In a crowdsourcing project several participants discuss and solve one common problem, propose their ideas, evaluate ideas of each other, etc. We propose the novel instrument CrowDM for analyzing data generated by collaborative platforms. The initial version of the system combines several innovative techniques for structured and unstructured data analysis. Formal Concept Analysis, multimodal clustering and association rule mining are the key instruments for identifying patterns in object-oriented data. Keyword and colocation extraction methods are also included for mining unstructured texts. We _rst describe the overall methodology underlying CrowDM and then showcase results of initial experiments on data obtained from the company Witology.
Software development process nowadays faces many challenges and risks. In order to manage risks we need to understand the scope and objectives of the software developments and use the appropriate automated risk management tool. The study addresses software risk management in software development area and an approach to analysis, structuring, and evaluating risk with the help of specialized automated tools. The author provides recommendations on how to define a set of selection criteria for automated tools and analyses the growing demand for service hosting solutions and web-applications, stressing that almost any software including risk management tools can be successfully run using this method.