Nils Brede Moe, PhD, Research manager, SINTEF Group – email@example.com
Johan Elvemo Ravn, PhD, Professor, Nord University – firstname.lastname@example.org (main contact)
Eva A. Seim, PhD, Senior Research Scientist, Læringsliv – Eva@laeringsliv.no
Viktoria Stray, PhD, Associate professor, University of Oslo – email@example.com
This special issue aims to present research on the autonomy of teams in companies in digital transformation. Especially in focus are key factors challenging the autonomy, and attempts at coping with such challenges. Team autonomy has a range of implications and is challenged by a number of factors, such as knowledge complexity and decision-making, learning, large-scale problems, environmental turbulence, management and leadership challenges, product and technical interdependencies, the use of platforms, virtual collaboration, and diversity. Early studies of agile development used the term ‘agile adoption’ to coin the uptake of agile methods by an organisation (Dybå et al. 2008), focusing uptake at team level, while later studies use ‘agile adoption’ about the uptake of agile methods in the whole organization. Thus, there is a need for new knowledge on how companies scale the concept of autonomous teams beyond their design or development teams, how non-tech companies can adopt the knowledge from software development teams and how new technology can support such teams in order to attain better performance, productivity, innovation and value creation.
Contributions to the special issue may include manuscripts that address the following themes:
What authority and support do teams in digital transformation need? How to balance crossfunctionality/transdisciplinarity and autonomy? What is the role of leadership, responsibility, power and authority? What are the barriers for networks of autonomous teams? What are the management and leadership challenges for autonomous teams in a multi-team setting? What technology is needed for intra- and inter-team coordination in autonomous teams? How will AI, machine learning and automation impact autonomous teams? How to adapt agile development practices used by autonomous teams with data science and machine learning? How does autonomy condition knowledge creation within and among teams? How may the team’s learning process be integrated in the learning of the organization? How may formerly hierarchic-bureaucratic sectors succeed in digital transformation and the use of autonomous teambased organisational designs? How can one provide increased operational transparency, which minimizing exposure to underlying complexities particular to the different units?
Submission of full manuscripts: March 31, 2020
Review and decision: June 3, 2020
Final paper submission: October 30, 2020
Ready for publication: Approx. November 13, 2020
Contributors are asked to submit a paper between 10 and 25 pages in the AI & Society’s manuscript format. You can find more information about formatting under the section “Instructions for Authors” https://www.springer.com/journal/146.
For inquiries please contact: firstname.lastname@example.org