Streamlining explanatory variables for household decision-making of low-carbon technologies (LCT) into a coherent decision framework.

Abstract

Around the world, strategies are put in place to facilitate the adoption of low-carbon technologies (LCT) on the household level, yet, individual decision-making is complex. Despite information about driver and barrier related to adoption decisions for specific LCTs is abundant, its usefulness for understanding household adoption decisions is limited, because studies lack theoretical coherence and results are fragmented. This thesis aims to develop a decision framework by deriving universal mechanisms governing household adoption behavior from literature. First, related theoretical concepts are merged to a theoretical decision framework. Following an inductive approach, explanatory variables utilized in studies on decision-making concerning exemplary LCTs are clustered to superordinate explanatory variables (SEV) in the framework structure. Focussing on behavioral studies only, key SEVs, their interrelations and dynamics are analysed and combined in a practical decision framework. In the framework, the expression of general dispositions in a decision unit, and the expression of LCT traits in a technology are combined to explain behavioral driver and barrier which are predictive of behavior. A construct of hypothesis proposes explicit effects of specific general dispositions and LCT traits on behavioral driver and barrier in a functional (personal-functional), normative (environmental) and symbolic (social interaction) dimension. From a practical viewpoint, the framework offers a starting point for consumer-specific intervention strategies directly targeting general dispositions or LCT traits to enhance drivers or reduce barriers for adoption. Yet it doesn’t offer explanations as to why decision units enter the decision process, and future confirmatory research is needed to empirically test the proposed decision framework.