Multi-level multi-stage efficiency measurement: the case of innovation systems

Efficiency measurement has been receiving significant attention the last years especially after the recent economic crises and the need of efficient use of public money. Although single step efficiency measurement is usually applied, taking into account the internal structure of the system is expected to provide more meaningful and informative results. This could be done in two axes: decomposition of the process into sub‐processes and hierarchical modeling among system components. In this framework we extend the Data Envelopment Analysis approach by examining efficiency through multi‐level and multi‐stage modeling. The proposed modeling approach (1) can give a better insight in sub‐processes compared to single‐stage ones and (2) can take into account functional/systemic characteristics (e.g., a Decision Making Unit operating as a part of a greater system). Through a ‘soft’ integration approach, not only different stages can be introduced but also hierarchies can be easily accommodated. Analysis of the efficiency of national/regional innovation systems is used as an illustrative example. The innovation process is modeled as a multi‐stage process including knowledge production and knowledge commercialization and multi‐level one, where regional innovation is achieved within a national innovation system.