The diffusion of clean technologies: A review with suggestions for future diffusion analysis

By René Kemp, M. Volpi. 2008

261 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/0b063c7e84a257ef068e1f35a1b2661dcce2cad2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Ernst Worrell
2. Jiyong Eom
3. Florian Lüdeke‐Freund
4. Simon Hirzel
5. Yusak O. Susilo
6. Saman Hassanzadeh Amin
7. T. Fleiter
8. Pralit Patel

In Management Science and Operations Research

1. Ernst Worrell
2. Simon Hirzel
3. Saman Hassanzadeh Amin
4. T. Fleiter
5. Guoqing Zhang
6. Frank Boons

Citations in the corpus

• The characteristics of energy-efficiency measures – a neglected dimension (2012, background): “Profitability is often found among the most important characteristics for technology adoption (Kemp, Volpi 2008; Oster 1982; Rogers 2003; Stoneman 2002 necessary to explicitly consider energy savings in the classification scheme.”
• Distributed solar and environmental justice: Exploring the demographic and socio-economic trends of residential PV adoption in California (2019, background): “non-adoption of clean energy technologies (Braito et al., 2017; Caird et al., 2008; Kemp and Volpi, 2008; Wilson and Dowlatabadi, 2007; Li and Yi, 2014), or on developing predictive models of consumer behavior (Robinson and Rai, 2015; Rai and Robinson, 2015; Sultan et al.”
• A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return (2013, background): “Clean technology consists of renewable and recycling energy such as solar power [34].”
• Total cost of ownership and its potential implications for battery electric vehicle diffusion (2016, background): “Kemp&Volpi(2008) describe technological diffusion as the adoption of a technology by a population over time.”
• Business Models for Sustainable Innovation: State of the Art and Steps Towards a Research Agenda (2013, background): “Examples are studies on the adoption and diffusion of clean technologies (Kemp and Volpi, 2008).”
• Diffusion of low-carbon technologies and the feasibility of long-term climate targets (2015, background): “Diffusion rates are also influenced by how risk-averse stakeholders are about technology decisions and their preferences for a new technology (Isoard and Soria, 2001; Kemp and Volpi, 2008).”