השוואת שיטות

	Innovation System Functions Analysis	Transition Management
תחום	Science Technology Studies	Science Technology Studies
משפחה	Process / pipeline	Process / pipeline
שנת המקור	2007	2001
הוגה השיטה	Marko Hekkert, Roald Suurs and colleagues	Jan Rotmans, René Kemp & Derk Loorbach
סוג	Functional analysis framework with event-history method	Prescriptive, complexity-based governance framework
מקור מכונן	Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: a new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413-432.	Loorbach, D. (2010). Transition management for sustainable development: a prescriptive, complexity-based governance framework. Governance, 23(1), 161-183.
כינויים	Functions of innovation systems, Seven functions approach, Event-history innovation analysis	TM, Transition governance framework, Transition arena approach
קשורות	4	4
תקציר	Functions of Innovation Systems analysis explains technological change by examining how well an innovation system performs seven key functions—entrepreneurial activities, knowledge development, knowledge diffusion, guidance of the search, market formation, resource mobilisation, and the creation of legitimacy. Associated with Hekkert, Suurs, and colleagues at Utrecht, the approach operationalises these functions through event-history analysis: a chronological dataset of innovation events is coded, functional performance is tracked over time, and the reinforcing feedback loops—the 'motors' of cumulative causation—that drive a system's rise or stagnation are identified.	Transition Management (TM) is a prescriptive, complexity-based governance framework for deliberately steering long-term, structural change in sociotechnical systems toward sustainability. Rather than predicting or controlling outcomes, it organises a cyclical, participatory process—strategic, tactical, operational, and reflexive activities—through which a small group of frontrunners develops shared long-term visions, translates them into agendas and coalitions, mobilises experiments, and continuously monitors and learns. It applies insights from transitions research to the question of how societies might govern their own transformations.