Now showing 1 - 1 of 1
  • Publication
    Generic customer segments and business models for smart grids : Empirical evidence from a cross-European country study
    The implementation of smart grids - one of the urgent goals to meet international policy expectations for energy efficiency and CO2 reduction targets - is not a technological issue alone, as it also requires social acceptance by various stakeholders (Wolsink 2011). It is of particular interest that smart grid products and services provide value to the customer. On the one hand, customer value of smart grid technologies is crucial to customer acceptance. On the other hand, as customer value is a key driver for economic value creation and competitive advantage (DeSarbo et al. 2001; Porter 1985), it is also important for companies and investors and thus will affect market acceptance of smart grid technologies. In the literature, business models address the bridge between customers and company needs and serve as mediators between technology and economic success by providing a value proposition to customers and a revenue model for companies (Chesbrough and Rosenbloom 2002). However, we know from the literature that a one-size-fits-all business model may not lead to the best results as it might fail to address heterogeneous customer value perceptions (DeSarbo et al. 2001; Morris et al. 2005; Ruiz et al. 2007; Wiedmann et al. 2009). Thus, different business models providing different customer value propositions need to be developed to fit the different market segments in an optimal way. On the basis of a cross-European country study, we explore three generic B2C customer segments for smart grid products and services based on different value perceptions (Supporters, Ambiguous and Skeptics). Based on the segmentation we conceptually derive four generic business model designs with different customer value propositions best suited for approaching those segments (Saver, Smart+, Trader, Smart Camouflage). Implications for energy policy, research and smart grid management are derived from the findings.
    Type:
    Journal:
    Volume:
    Issue: