Prediction of photovoltaic and solar water heater diffusion and evaluation of promotion policies on the basis of consumers' choices

Applied Energy

Volumn 102, Issue , 2013, Pages 1148-1159

  Yamaguchi, Yohei ^a   Akai, Kenju ^b   Shen, Junyi ^c   Fujimura, Naoki ^d   Shimoda, Yoshiyuki ^a   Saijo, Tatsuyoshi ^a,e,f  

^a OSAKA UNIVERSITY   (Japan)

^b UNIVERSITY OF TOKYO   (Japan)

^c HIROSHIMA CITY UNIVERSITY   (Japan)

^d Dentsu Public Relations Inc   (Japan)

^e UNIVERSITY OF CALIFORNIA   (United States)

^f KOCHI UNIVERSITY OF TECHNOLOGY   (Japan)

Author keywords

Bass diffusion model; Choice experiment; Consumers' preference; Photovoltaic; Residential sector; Solar water heater

Indexed keywords

COSTS; DIFFUSION; EMISSION CONTROL; ENERGY EFFICIENCY; SOLAR WATER HEATERS; TECHNOLOGY;

BASS DIFFUSION MODEL; CHOICE EXPERIMENTS; CONSUMERS' PREFERENCE; PHOTOVOLTAIC; RESIDENTIAL SECTORS;

CARBON DIOXIDE;

CARBON DIOXIDE; DIFFUSION; EMISSION CONTROL; PHOTOVOLTAIC SYSTEM; POLLUTION POLICY; PREDICTION; ANALYTICAL FRAMEWORK; CONSUMER-RESOURCE INTERACTION; PERCEPTION; RESIDENTIAL LOCATION; SOLAR POWER; SPATIOTEMPORAL ANALYSIS;

JAPAN;

EID: 84870741107     PISSN: 03062619     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apenergy.2012.06.037     Document Type: Article

References (24)

1. Jager W. Stimulating the diffusion of photovoltaic systems: a behavioural perspective. Energy Policy 2006, 34:1935-1943.
2. Banfi S., Farsi M., Filippini M., Jakob M. Willingness to pay for energy-saving measures in residential buildings. Energy Econ 2008, 30:503-516.
3. Ku S.J., Yoo S.H. Willingness to pay for renewable energy investment in Korea: a choice experiment study. Renew Sustain Energy Rev 2010, 14:2196-2201.
4. ShenJ Saijo.T. Does an energy efficiency label alter consumers' purchasing decisions? A latent class approach based on a stated choice experiment in Shanghai. J Environ Manage 2009, 90:3561-3573.
5. Shen J., Sakata Y., Hashimoto Y. The influence of environmental deterioration and network improvement on transport modal choice. Environ Sci Policy 2009, 12:338-346.
6. Bass F. A new product growth model for consumer durables. Manage Sci 1969, 15:215-227.
7. Mahajan V., Muller E., Bass F.M. New product diffusion models in marketing: a review and directions for research. J Marketing 1990, 54:1-26.
8. Bass F.M., Krishnan T.V., Jain D.C. Why the bass model fits without decision variables. Marketing Sci 1994, 13:203-223.
9. Matsumoto M., Kondoh S., Fujimoto J., Umeda Y., Tsuchiya H., Masui K., et al. A diffusion model for clean energy vehicles. J Jpn Soc Energy Resour 2008, 29(3):49-55.
10. Shimoda Y., Yamaguchi Y., Okamura T., Taniguchi A., Yamaguchi Y. Prediction of greenhouse gas reduction potential in Japanese residential sector by residential energy end-use model. Appl Energy 2010, 87:1944-1952.
11. Davis Langdon Management Consulting. Life cycle costing (LCC) as a contribution to sustainable construction: a common methodology-literature review; 2007. P. 22-57. [10.06.12]. http://ec.europa.eu/enterprise/sectors/construction/files/compet/life_cycle_costing/llitera_review_en.pdf.
12. NEDO (New Energy and Industrial Technology Development Organization). Data regarding new energy. [30.01.08]. http://www.nedo.go.jp/nedata/index.html.
13. NEF (New Energy Foundation) Japan. [30.01.08]. http://www.solar.nef.or.jp/josei/zissi.htm.
14. Kimura O. Why is the solar thermal system diffusion declining in Japan?, CRIEPI Research, Report; 2008. P. 1-46 [in Japanese].
15. SSDA (Solar System Development Association). Number of installed solar water heater unit. [30.01.08]. http://www.ssda.or.jp/energy/result.html.
16. NEF (New Energy Foundation) Japan. [30.08.09]. http://www.solar.nef.or.jp/system/html/taiyou_sys080421.pdf.
17. Uchida S., Higano Y. Diffusion model of renewable energies considering the learning effect and environmental value. J Jpn Soc Energy Resour 2008, 29(3):15-21. [in Japanese].
18. Yamaguchi Y, Fujimoto T, Shimoda Y. Occupant behavior model for households to estimate high-temporal resolution residential electricity demand profile. In: The proceedings of international conference on building performance simulation 2011, Sydney, Australia; 2011. P. 1546-55.
19. Broadcasting Culture Research Institute of Japan. National Time Use Survey in 2000; 2001.
20. 2 reduction effect by introducing new residential water heaters. Energy 2010, 35:4880-4891.
21. Shimoda Y., Asahi T., Taniguchi A., Mizuno M. Evaluation of city-scale impact of residential energy conservation measures using the detailed end-use simulation model. Energy 2007, 32:1617-1633.
22. Van den Bulte C., Lilien G.L. Biased and systematic change in the parameter estimates of macro-level diffusion models. Marketing Sci 1997, 16:338-353.
23. Lund P.D. Fast market penetration of energy technologies in retrospect with application to clean energy futures. Appl Energy 2010, 87:3575-3583.
24. Geels F.W. From sectoral systems of innovation to socio-technical systems: insights about dynamics and change from sociology and institutional theory. Res Policy 2004, 33:897-920.