@article{SultanowVladovaWeber2009,
  author    = {Sultanow, Eldar and Vladova, Gergana and Weber, Edzard},
  title     = {Overcoming communication barriers for CMC in enterprises},
  isbn      = {978-0-615-30358-1},
  year      = {2009},
  language  = {en}
}
@article{VladovaBahrs2014,
  author    = {Vladova, Gergana and Bahrs, Julian},
  title     = {Wissenstransfer als Mittel der internen Unternehmenskommunikation},
  series = {Handbuch prozessorientiertes Wissensmanagment},
  journal   = {Handbuch prozessorientiertes Wissensmanagment},
  publisher = {GITO},
  address   = {Berlin},
  isbn      = {978-3-95545-026-7},
  pages     = {37 -- 47},
  year      = {2014},
  language  = {de}
}
@article{VladovaBahrs2009,
  author    = {Vladova, Gergana and Bahrs, Julian},
  title     = {Wissenstransfer als Mittel der internen Unternehmenskommunikation : eine explorative Untersuchung in neun internationalen Unternehmen},
  isbn      = {978-3-88579-239-0},
  year      = {2009},
  language  = {de}
}
@article{VladovaAdelhelm2009,
  author    = {Vladova, Gergana and Adelhelm, Silvia},
  title     = {Informal knowledge flows in open innovation : both a blessing and a curse?},
  isbn      = {978-952-214-767-7},
  year      = {2009},
  language  = {en}
}
@article{VladovaWeber2009,
  author    = {Vladova, Gergana and Weber, Edzard},
  title     = {Bedarf von KMU f{\"u}r anwendergerechte Aufbereitung von Norminhalten},
  issn      = {0722-2912},
  year      = {2009},
  language  = {de}
}
@article{BahrsVladova2009,
  author    = {Bahrs, Julian and Vladova, Gergana},
  title     = {Produktpiraterie : Pr{\"a}vention statt Reaktion},
  issn      = {1438-4426},
  year      = {2009},
  language  = {de}
}
@article{EppingerVladova2013,
  author    = {Eppinger, Elisabeth and Vladova, Gergana},
  title     = {Intellectual property management practices at small and medium-sized enterprises},
  series = {International journal of technology management},
  volume    = {61},
  journal   = {International journal of technology management},
  number    = {1},
  publisher = {Inderscience Enterprises Ltd},
  address   = {Geneva},
  issn      = {0267-5730},
  doi       = {10.1504/IJTM.2013.050244},
  pages     = {64 -- 81},
  year      = {2013},
  abstract  = {Small and medium-sized enterprises (SME) contribute to innovation and economic growth, despite their resource shortages and lack of professional intellectual property (IP) management practices. Drawing on social practice theory and combining insights from recent scholarship on IP strategies and its management, this paper examines the cases of three pharmaceutical SME providing insights into how they appropriate returns on research and development (R\&D) investments. It discusses their IP strategies and management practices, examining how the IP management practices are embedded in the firm's organisational structure. Moreover, this paper develops recommendations for SME regarding the professionalisation of their IP management practices.},
  language  = {en}
}
@article{UllrichVladova2016,
  author    = {Ullrich, Andre and Vladova, Gergana},
  title     = {Weighing the Pros and Cons of Engaging in Open Innovation},
  series = {Technology Innovation Management Review},
  volume    = {8},
  journal   = {Technology Innovation Management Review},
  publisher = {Carleton University Graphic Services},
  address   = {Ottawa},
  issn      = {1927-0321},
  pages     = {34 -- 40},
  year      = {2016},
  abstract  = {The positive aspects of open innovation projects are widely discussed in innovation management research and practice by means of case studies and best practices. However, enterprises, particularly small and medium-sized enterprises (SMEs) also face miscellaneous challenges in open innovation practice, leading to uncertainty and even renunciation of open innovation project participation. Thus, it is essential for SMEs to find the right balance between possible positive effects and negative consequences - the latter being the less studied "dark sides" of open innovation. However, appropriate methods of finding this balance are still lacking. In this article, we discuss the assessment of open innovation project participation by presenting a weighing and decision process framework as a conceivable solution approach. The framework includes an internal, external, and integrated analysis as well as a recommendation and decision phase. Piece by piece, we investigate the current situation and the innovation goals of the enterprise as an initial point for a decision for or against engaging in open innovation. Furthermore, we discuss the development of a software tool that automatically applies this framework and allows self-assessment by SMEs.},
  language  = {en}
}
@misc{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  number    = {160},
  issn      = {1867-5808},
  doi       = {10.25932/publishup-58907},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-589077},
  pages     = {18},
  year      = {2022},
  abstract  = {Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.},
  language  = {en}
}
@article{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Discover artificial intelligence},
  volume    = {2},
  journal   = {Discover artificial intelligence},
  publisher = {Springer},
  address   = {Cham},
  issn      = {2731-0809},
  doi       = {10.1007/s44163-022-00031-7},
  pages     = {18},
  year      = {2022},
  abstract  = {Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.},
  language  = {en}
}