Behavioral scientists contend that individuals, and organizations rarely make decisions solely on the basis of economic factors. Decisions are also shaped by perceived risk, social interactions, currency and salience of information, and other value propositions. Social diffusion of information on consumer experiences, entrance of new business models better aligned with customers’ concerns when evaluating investments, and perceived improving economic conditions are all factors in consumers’ decisions to adopt a new technology, such as solar photovoltaics (PV). We describe a new conceptual agent-based model, BE-Solar, that incorporates a social and behavioral decision framework for technology adoption decisions. We demonstrate the feasibility of including heterogeneity and behavioral factors into an agent-based model of the solar PV market, which is being applied to the Southern California market.

The availability of online documents coupled with emergent text mining methods has opened new research horizons. To achieve their potential, mining technologies need to be theoretically focused. We present data theory as a crucial component of text mining, and provide a substantive proto- theory from the synthesis of complex multigames, prototype concepts, and emotio-cognitive orientation fields. We discuss how the data theory presented informs the application of text mining to mining discourse(s) and how, in turn, this allows for modeling across contextual thresholds. Finally, the relationship between discourse mining, data theory, and thresholds is illustrated with an historical example, the events surrounding the 1992 civil war in Tajikistan.