Sustainability and Social Justice

Bounded Socio-Technical Experiments as Agents of Systemic Change: The Case of a Zero-Energy Residential Building

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Large-scale shifts in dominant technologies are the necessary components of a transition toward sustainability. Such shifts are difficult because, in addition to technological innovation, they require changes in the existing institutions, professional norms, belief systems and, in some cases, also lifestyles. In the languages of cognitive and policy sciences, higher order learning on a scale ranging from individuals to professional and business communities, to the society at large, is needed. Higher order learning is especially crucial in the types of innovations that depend mainly on synthesis of existing technologies and know-how to achieve radical reductions in energy and material consumption, as is the case with high performance buildings. One way to facilitate this type of learning is through experimentation with new technologies and services. Drawing on our earlier concept of a Bounded Socio-Technical Experiment, in this paper we propose a four-level conceptual framework for mapping and monitoring the learning processes taking place in a BSTE, and apply it to an empirical case study of a zero-fossil-fuel residential building in Boston. Three major conclusions are that: learning took place both on the individual and team level, that individual learning primarily (but not exclusively) involved changes in problem definitions; and that team learning consisted of participant turnover until congruence in worldviews and interpretive frames was achieved. This case study also shows that we must think of innovating in building design as both a process and a product, and that both must be considered in the future efforts to replicate this building. This study highlights that technological innovation about technology as much as about people, their perceptions, and their interactions with each other and with the material world. Sustainability will not be reached by technology alone, but by deep learning by individuals, groups, professional societies and other institutions. © 2007.

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Technological Forecasting and Social Change

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green buildings, higher order learning, small-scale experiment, socio-technical regime, technological innovation