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Local and Global Measures for Success and Reconstructive Determination of the Optimal Number of Partners in European Educational Projects

Author

Listed:
  • Matilda Alexandrova

    (University of National and World Economy, Sofia, Bulgaria)

  • Daniela Staneva

    (Executive Agency of Transplantation, 112 Bratja Miladinovi Str., 1202 Sofia,Bulgaria)

  • George Petkov

    (College of Engineering, Mathematics and Physical Sciences, Innovation Centre, University of Exeter, Exeter, Devon EX4 4QF, UK)

Abstract

The present study is based on real data of 306 project proposals submitted for funding in 2013. The distribution of the project proposals by the countries of initiation and partnering countries is specifically considered in relation to the quality of the established consortia. A quality indicator is defined that determines whether a given project has the appropriate quality/characteristics to meet the predefined quality requirements/criteria. On the basis of this indicator local and global measures for quantification of the project’s success are introduced. The local and global measures for success along with the results obtained by "Quality of the consortium" evaluation criterion are used to calculate the statistical evaluation and the reconstruction of the optimal number of partners in a consortium, ensuring success of the project application. The presented data were analysed by methods of applied statistics and relevant findings were made about the discussed topic and guidelines for further research and development are given.

Suggested Citation

  • Matilda Alexandrova & Daniela Staneva & George Petkov, 2014. "Local and Global Measures for Success and Reconstructive Determination of the Optimal Number of Partners in European Educational Projects," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 63-76, January.
  • Handle: RePEc:nwe:eajour:y:2014:i:1:p:63-76
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    References listed on IDEAS

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    1. Blume Lawrence E., 1993. "The Statistical Mechanics of Strategic Interaction," Games and Economic Behavior, Elsevier, vol. 5(3), pages 387-424, July.
    2. Mike Bresnen & Nick Marshall, 2000. "Partnering in construction: a critical review of issues, problems and dilemmas," Construction Management and Economics, Taylor & Francis Journals, vol. 18(2), pages 229-237.
    3. Barnes, Tina & Pashby, Ian & Gibbons, Anne, 2002. "Effective University - Industry Interaction:: A Multi-case Evaluation of Collaborative R&D Projects," European Management Journal, Elsevier, vol. 20(3), pages 272-285, June.
    4. Dvir, D. & Lipovetsky, S. & Shenhar, A. & Tishler, A., 1998. "In search of project classification: a non-universal approach to project success factors," Research Policy, Elsevier, vol. 27(9), pages 915-935, December.
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    Cited by:

    1. Matilda Alexandrova & Liliana Stankova & Angel Gelemenov, 2015. "The Role of Project Office for Project Portfolio Management," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 19-30, March.

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    More about this item

    Keywords

    monitoring; evaluation; European projects; success measures; mathematical modelling;
    All these keywords.

    JEL classification:

    • O22 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Project Analysis
    • H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

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