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This paper provides a psychology perspective on the human factors that should be taken into consideration when designing behaviour-based energy-saving interventions for non-residential buildings. We review psychological theories used to explain energy-related behaviours and discuss their limitations as well as additional hindrances that interfere with employees' energy conservation. Furthermore, we highlight the features that distinguish residential from non-residential buildings and discuss how these factors may affect peoples' efforts to save energy. In conclusion, we argue that it is ineffective to promote energy-saving behaviours through top-down communication (e.g. information campaigns) but that decision-makers should rather rely on participatory designs, since these facilitate consumers' involvement, increase intrinsic motivation to save energy, take consumers' social environment into account, establish new energy-consumption norms, and encourage overt commitment of individuals to energy savings. Furthermore, we outline how participatory interventions could be strengthened by using motivational interviewing (MI) techniques, a conversation style that could be utilised to evoke users' motivation to engage in energy-conversation behaviours in non-residential buildings. Since basic MI skills can be learned within few days, we recommend that energy managers receive such a training in order to conduct in-house participatory MI-based interventions.

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In today's fast-changing world, teams need to develop a sound capacity for finding new ideas. However, we know little about the behavioral microdynamics that are at the core of creativity in teams. To overcome these shortcomings, we present a new behavioral coding system for analyzing idea finding interactions (AIFI). The AIFI system aims to help researchers study fine-grained creative team processes. In terms of practical application, the AIFI system can serve to visualize the patterns of Idea finding over time. The codes of the AIFI system were derived both inductively (analyzing videos of innovation teams) and deductively (consulting existing coding systems). A first application of the AIFI system showed moderate agreement among coders, speaking to its interrater reliability. Further, we examined distinct relationships between the codes of the AIFI system and (1) ratings of idea quality provided by external raters and (2) team members' perceived effectiveness.