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Examining the barriers and motivators affecting European decision-makers in the development of smart and green energy technologies

Abstract The nature of the utility market is changing. Developing smart and green technologies are essential to overcoming the challenges in the decades to come. Moreover, smart and green technologies are vital to reducing carbon emissions, achieving future goals of sustainability, and assuring electric stability to cities and their citizens. Hence, development of these energy-related technologies have become an important priority across Europe. To this end, this study examines the literature on interactions between several social actors regarding the advancement of smart and green energy technologies. The analysis is based on the identification of three levels of formal social decision-making units, namely, Formal Social Units, Collective Decision-Making Units, and Individual Consumers engaging in joint contracts. The attitude dimensions, motivators and barriers concerning the energy behaviors of the three decision-making units are identified through a comprehensive literature review. Similarities and differences in decision-making processes related to each level and the reasons for delays in achieving targets are identified. Moreover, a policy framework for involved stakeholders of smart and green energy technologies is presented.
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).48 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
