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Assessing Commercial Viability of Technology Start-up Businesses in a Government Venture Capital under Intuitionistic Fuzzy Environment

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Abstract

Governments around the world are increasingly showing keen interests in venture capital investments in technology start-up businesses. However, determining the commercial potential of a new Technology start-up business is generally seen as a complex exercise especially in a government-controlled setting where selection of candidates can be clouded by several peripheral considerations. To generate more interests in decision-making models aimed at assessing the commercial viability of candidate start-up businesses in a government-run venture capital, this study (1) provides a modified form of the Strategic Technology Evaluation Program (STEP) called G-STEP as a new selection criteria for a government-controlled venture capital scheme (2) adopts a comprehensive intuitionistic fuzzy TOPSIS framework with a sensitivity analysis component for the assessment of early stage but high potential tech start-up firms and (3) demonstrates its applicability with a numerical example assessing the commercial potential of start-up businesses in a Government technology venture capital program. The proposed decision-making framework could be useful in the assessment and selection problems in other government priority areas.

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Acknowledgments

This work was supported by Grant Agency of the Czech Republic–GACR P103/15/06700S, further by financial support of research project NPU I no. MSMT-7778/2014 by the Ministry of Education of the Czech Republic and also by the European Regional Development Fund under the Project CEBIA-Tech No. CZ.1.05/2.1.00/03.0089. Further, this work was supported by Internal Grant Agency of Tomas Bata University under the project nos. IGA/FAI/2015/054 and IGA/FaME/2014/007, IGA/FaME/2015/023.

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Afful-Dadzie, E., Afful-Dadzie, A. & Oplatková, Z.K. Assessing Commercial Viability of Technology Start-up Businesses in a Government Venture Capital under Intuitionistic Fuzzy Environment. Int. J. Fuzzy Syst. 19, 400–413 (2017). https://doi.org/10.1007/s40815-016-0141-9

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