Academic research

Bayes X will develop a framework with specific research projects and foster academic collaborations within Bayes Business School, City, University of London and across other institutions (universities, organisations and companies).

The aim is threefold. First, to disseminate our results through regular presentations at major conferences and highly rated refereed journals. Second, to create deep and unprecedented databases on innovation and disruption (e.g. Dynamic Innovation Indices). Third, to increase the number and enhance the quality of PhD researchers in the area of innovation.

Given the research background and interests of current faculty, potential areas may include:

  • How do new technologies emerge? How can we identify which ones will take off?
  • What is the impact of new technologies (e.g. Artificial Intelligence, Virtual Reality, Fintech) to economic growth and the nation’s reputation as a leading global innovation player?
  • How can companies in high-velocity markets excel at both incremental (exploiting current capabilities) and breakthrough (exploring into new space) innovation?
  • How can corporates maintain a culture of relentless innovation?
  • How can family businesses generate breakthrough innovations?
  • How will Fintech bring deep changes into payments, trading and regulation?
  • What will be the impact of the VC industry on innovation and economic growth?
  • How does innovation help VC firms to identify promising start-ups to invest in?
  • How do entrepreneurs transform existing structures to create new organizational forms (e.g. Uber, Amazon)?
  • How can innovative technologies (e.g. blockchain technology) be used for social impact?
  • How do organizations leverage the potential of crowd-based models (e.g., crowdsourcing and crowdfunding) for innovation?
  • How do advances in digital technologies transform the innovation practices of organizations?
  • What are the behavioural factors influence adoption of breakthrough innovations (e.g., products and solutions that are based on machine intelligence such as self-driving cars, digital assistants)?