@article{JashariTiberiusDabić2021,
  author    = {Jashari, Arbrie and Tiberius, Victor and Dabić, Marina},
  title     = {Tracing the progress of scenario research in business and management},
  series = {Futures \& foresight science},
  volume    = {4},
  journal   = {Futures \& foresight science},
  number    = {2},
  publisher = {John Wiley \& Sons},
  address   = {Hoboken, NJ},
  issn      = {2573-5152},
  doi       = {10.1002/ffo2.109},
  pages     = {9},
  year      = {2021},
  abstract  = {Business and management research on scenarios has been highly productive over the decades but led to a complex literature that is hard to oversee. To organize the field and identify distinguishable research clusters, we conducted a co-citation analysis focusing on the long-term history of research. We compare our findings with a previously published bibliographic coupling, focusing on the more recent research to trace its development over time. Our study revealed six research clusters: (1) Planning the Future with Scenarios, (2) Scenario Planning in Strategic Management, (3) Reinforcing the Scenario Technique, (4) Integration of Scenario Planning and MCDA, (5) Combination of Different Methods, and (6) Decision-making through Stochastic Programming, whereas the bibliographic coupling generated 11 clusters. Some former research clusters were divided into separate new clusters, while others were united. Additionally, completely new clusters emerged. Future research on scenarios is expected (1) to further differentiate into strategy and operations, (2) to be based on "behavioral futures" or "behavioral foresight" as a new research stream, (3) to advance the scenario technique methodically and include new specific scenario generation methods, and (4) to put forth new application areas.},
  language  = {en}
}
@article{TiberiusStillerDabić2021,
  author    = {Tiberius, Victor and Stiller, Laura and Dabić, Marina},
  title     = {Sustainability beyond economic prosperity},
  series = {Technological forecasting and social change},
  volume    = {173},
  journal   = {Technological forecasting and social change},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0040-1625},
  doi       = {10.1016/j.techfore.2021.121093},
  year      = {2021},
  abstract  = {Family businesses strive not only for economic prosperity but also for social and environmental values and achievements. In an ever-changing business environment, dynamic capabilities are required to sustain performance across these areas. To understand these mechanisms in order to proactively manage them, it is necessary to identify their specific microfoundations and uncover how these relate to sustainability. However, research on sustainability dynamic capabilities in family businesses and their microfoundations is scarce. To address this research gap, we conducted semi-structured interviews with 11 German and Swiss family businesses from different industries of different ages and sizes. Our findings suggest that the majority of dynamic capability microfoundations relate to economic sustainability, with a specific focus on future orientation, traditional mindsets, rapid decision-making, intuition, speed, and resource slack. Further, we find the social aspects of innovative mindsets, human capital investments, and participation to be the specific microfoundations that strongly link with social and, eventually, economic sustainability. However, we did not find specific microfoundations for environmental sustainability.},
  language  = {en}
}
@article{TiberiusGojowyDabic2022,
  author    = {Tiberius, Victor and Gojowy, Robin and Dabic, Marina},
  title     = {Forecasting the future of robo advisory},
  series = {Technological forecasting \& social change},
  volume    = {182},
  journal   = {Technological forecasting \& social change},
  publisher = {Elsevier},
  address   = {New York},
  issn      = {0040-1625},
  doi       = {10.1016/j.techfore.2022.121824},
  pages     = {15},
  year      = {2022},
  abstract  = {Robo advisors represent a digital financial advice solution challenging traditional wealth and asset management, investment advice, retirement planning, and tax-loss harvesting. Based on algorithms, big data analysis, machine learning, and other technologies, these services minimize the necessity for human intervention. Based on an international three-stage Delphi study, we provide a plausible forecast of the development of the robo advisor industry, with regards to market development, competition, drivers of growth, customer segments, challenges, services, technologies, and societal change. The results suggest that the financial advice market will experience a further increase in the number of robo advisor services available. Existing and traditional financial advice players will be forced to adjust to the changing environment of the market. Due to low fees and ease of use, robo advisors will be made available to a broad cross section of society, and will cause significant market losses for traditional investment advice companies. Ten years from now, the predominant investment class will remain Exchange Traded Funds (ETFs). Even though degrees of human intervention are expected to vary considering the complexity of advice, automation will increase in significance when it comes to the development of robo advisors.},
  language  = {en}
}