@article{TiberiusSiglowSendraGarcia2020,
  author    = {Tiberius, Victor and Siglow, Caroline and Sendra-Garc{\´i}a, Javier},
  title     = {Scenarios in business and management},
  series = {Journal of business research},
  volume    = {121},
  journal   = {Journal of business research},
  publisher = {Elsevier},
  address   = {New York},
  issn      = {0148-2963},
  doi       = {10.1016/j.jbusres.2020.08.037},
  pages     = {235 -- 242},
  year      = {2020},
  abstract  = {The scenario technique is widely used to cope with uncertainties plan for alternate future situations. The extensive research led to a scattered literature landscape. To organize the field quantitatively, we conduct bibliometric performance analyses and a bibliographic coupling analysis. Results show an increased interest in scenario research since 2009 and clear distinctions between strategic and operational as well as methodological and applied research. Future research can be expected to further enhance the method towards robust decision making and to combine it with methods searching for most likely scenarios, such as prediction markets, crowdsourcing, and superforecasting. Additionally, cognitive and behavioral aspects of using the scenario technique might draw further attention. The scenario technique is expected to be applied across all industries and will probably play an increasing role in currently underrepresented business functions such as marketing and innovation.},
  language  = {en}
}
@article{HoehneTiberius2020,
  author    = {H{\"o}hne, Stefan and Tiberius, Victor},
  title     = {Powered by blockchain},
  series = {International journal of energy sector management},
  volume    = {14},
  journal   = {International journal of energy sector management},
  number    = {6},
  publisher = {Emerald Group Publishing Limited},
  address   = {Bingley},
  issn      = {1750-6220},
  doi       = {10.1108/IJESM-10-2019-0002},
  pages     = {1221 -- 1238},
  year      = {2020},
  abstract  = {Purpose: The purpose of this study is to formulate the most probable future scenario for the use of blockchain technology within the next 5-10 years in the electricity sector based on today's experts' views. Design/methodology/approach: An international, two-stage Delphi study with 20 projections is used. Findings: According to the experts, blockchain applications will be primarily based on permissioned or consortium blockchains. Blockchain-based applications will integrate Internet of Things devices in the power grid, manage the e-mobility infrastructure, automate billing and direct payment and issue certificates regarding the origin of electricity. Blockchain solutions are expected to play an important big role in fostering peer-to-peer trading in microgrids, further democratizing and decentralizing the energy sector. New regulatory frameworks become necessary. Research limitations/implications: The Delphi study's scope is rather broad than narrow and detailed. Further studies should focus on partial scenarios. Practical implications: Electricity market participants should build blockchain-based competences and collaborate in current pilot projects. Social implications: Blockchain technology will further decentralize the energy sector and probably reduce transaction costs. Originality/value: Despite the assumed importance of blockchain technology, no coherent foresight study on its use and implications exists yet. This study closes this research gap.},
  language  = {en}
}
@misc{KuehnSchoene2017,
  author    = {K{\"u}hn, Michael and Sch{\"o}ne, Tim},
  title     = {Multivariate regression model from water level and production rate time series for the geothermal reservoir Waiwera (New Zealand)},
  series = {Energy procedia},
  volume    = {125},
  journal   = {Energy procedia},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {1876-6102},
  doi       = {10.1016/j.egypro.2017.08.196},
  pages     = {571 -- 579},
  year      = {2017},
  abstract  = {Water management tools are necessary to guarantee the preservation of natural resources while ensuring optimum utilization. Linear regression models are a simple and quick solution for creating prognostic capabilities. Multivariate models show higher precision than univariate models. In the case of Waiwera, implementation of individual production rates is more accurate than applying just the total production rate. A maximum of approximately 1,075 m3/day can be pumped to ensure a water level of at least 0.5 m a.s.l. in the monitoring well. The model should be renewed annually to implement new data and current water level trends to keep the quality.},
  language  = {en}
}