Modelling knowledge production performance of research centres with a focus on triple bottom line benchmarking

We demonstrate a portable process for developing a triple bottom line model to measure the knowledge production performance of individual research centres. For the first time, this study also empirically illustrates how a fully units-invariant model of Data Envelopment Analysis (DEA) can be used to measure the relative efficiency of research centres by capturing the interaction amongst a common set of multiple inputs and outputs. This study is particularly timely given the increasing transparency required by governments and industries that fund research activities. The process highlights the links between organisational objectives, desired outcomes and outputs while the emerging performance model represents an executive managerial view. This study brings consistency to current measures that often rely on ratios and univariate analyses that are not otherwise conducive to relative performance analysis.

Continuous variable tripartite entanglement and Einstein-Podolsky-Rosen correlations from triple nonlinearities

We compare theoretically the tripartite entanglement available from the use of three concurrent x(2) nonlinearities and three independent squeezed states mixed on beamsplitters, using an appropriate version of the van Loock-Furusawa inequalities. We also define three-mode generalizations of the Einstein-Podolsky-Rosen paradox which are an alternative for demonstrating the inseparability of the density matrix.