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Living labs, as a methodology to enhance user-centric innovation, have large potentials in bringing inventions to the marketplace, but their performance can benefit more from evaluation. This article develops a novel framework for evaluation of living labs, including (1) a system approach providing an analytical view on living labs’ performance and results; (2) a focus on actor-complexity and boundary-spanning needs; (3) a set of questions concerning, e.g. absorption of user-feedback, satisfaction among actors, and openness and connecting with larger networks; (4) a list of key performance factors; and (5) a focus on participatory evaluation. The design of this evaluation framework rests on a comprehensive literature search and case studies representing different actor complexity, namely home-solutions in healthcare, reconstruction of large (multi)functional buildings, and multiple combinations of activity (university campuses). Key performance factors are found to be: an early involvement of adequately skilled users in multiple learning processes, including absorption of feedback, and a broader but balanced set of actors connecting with upscaling and acceptance in the market. Also, boundaries need to be better bridged by learning how to handle conflicts and deal with intermediation, while respecting shared goals and interests. Specifically, university living labs call for maintaining a solid relation with cities and their actors. Overall, an explicitly designed evaluation framework is a key part of the working plan of living labs. The results also indicate a need for stronger attention for boundary-spanning in evaluation, because living labs are increasingly applied in comprehensive multi-activity settings.

International research interactions (IRIs), specifically co-invention, co-assignment and the international appropriation of inventions, are increasing as a result of globalization and rising technological complexity. Yet the impact of IRIs on national innovation performance is ambiguous. In this study patent-based bibliometric indicators are developed to investigate the influence of IRIs on innovation performance using bibliometric and statistical data covering six knowledge intensive sectors and 32 countries during the 2003-2008 period. This sector-based approach avoids some of the problems of using patents as innovation indicators, notably varying patenting propensities across sectors. The study uses patent grants published by the United States Patent & Trademark Office (USPTO) and statistical data from the OECD to estimate a patent production function. The use of patent-based bibliometric indicators is partially validated using the statistical data and published outcomes from the literature. The results suggest that IRIs have no or a statistically significant negative influence on national innovation performance, especially in the case of the international appropriation of inventions, which can be seen as a proxy for the presence of international organisations such as multinational corporations (MNCs) in a particular sector and country. The potential policy implications and theoretical relevance of these findings are also discussed.

Ill predictability is often a problem in decision making in the domain of traffic and transport. Especially posing problems are the uncertainty of short-term processes in the traffic process, such as congestion, and of long-term forecasts. Results are reported from a study of the limits to predictability. The sources of uncertainty are described: on the one hand, uncertainty and incompleteness of data and models, and, on the other hand, intrinsic uncertainties due to the complexity of the processes, such as chaos and nonlinearity, human behavior, and changing values and goals. The role of uncertainties in decision making is highlighted, and suggestions are given for improving the decision-making process. The role of forecasts in different kinds of decision making, with different kinds of information requirements, is described.

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