Opinion Leadership in the Diffusion of Photovoltaic Systems

Chapter

Abstract

According to diffusion theory, opinion leaders—through interpersonal communication with potential adopters—play an important role in the diffusion of new technologies. The purpose of this chapter is to examine whether this is the case for a solar photovoltaic (PV) power generation system and to investigate the role and utility of opinion leadership in the diffusion of PV systems. Specifically, the study proposes, examines, and considers the implications of the hypothesis that there is a positive relationship between willingness to pay (WTP) for a PV system and opinion leadership on the adoption of PV systems in the residential sector. The study employed an internet-based questionnaire survey to assess the use of interpersonal communication in decision-making on adoption, to identify opinion leaders with respect to adoption and to characterize their WTP. The response pool consisted of 488 individuals who lived in detached houses in Japan, owned a residential PV system and were responsible for making the decision to adopt their PV system. The results support the hypothesis stated above. Considering that subsidization preferentially incentivizes households with greater WTP to adopt PV systems, the results suggest that subsidization is more effective than purchases of PV electricity under a feed-in tariff system in promoting the diffusion of PV systems in the residential sector through interpersonal communication.

Keywords

Residential photovoltaic system Diffusion Opinion leadership Willingness to pay Questionnaire survey 

References

  1. Antonelli M, Desideri U (2014) The doping effect of Italian feed-in tariffs on the PV market. Energy Policy 67:583–594CrossRefGoogle Scholar
  2. Bollinger B, Gillingham K (2012) Peer effects in the diffusion of solar photovoltaic panels. Market Sci 31:900–912CrossRefGoogle Scholar
  3. Campoccia A, Dusonchet L, Telaretti E, Zizzo G (2014) An analysis of feed’in tariffs for solar PV in six representative countries of the European Union. Sol Energy 107:530–542CrossRefGoogle Scholar
  4. Cherrington R, Goodship V, Longfield A, Kirwan K (2013) The feed-in tariff in the UK: a case study focus on domestic photovoltaic systems. Renew Energy 50:421–426CrossRefGoogle Scholar
  5. David P (1966) The mechanization of reaping in the ante-bellum Midwest. In: Rosovsky H (ed) Industrialization in two systems. Harvard University Press, Cambridge, pp 3–39Google Scholar
  6. Faiers A, Neame C (2006) Consumer attitudes towards domestic solar power systems. Energy Policy 34:1797–1806CrossRefGoogle Scholar
  7. Griliches Z (1957) Hybrid corn: an exploration in the economics of technical change. Econometrica 48:501–522CrossRefGoogle Scholar
  8. Guo X, Liu H, Mao X, Jin J, Chen D, Cheng S (2014) Willingness to pay for renewable electricity: a contingent valuation study in Beijing, China. Energy Policy 68:340–347CrossRefGoogle Scholar
  9. Jaffe AB, Newell RG, Stavins RN (2003) Technological change and the environment. In: Mäler KG, Vincent JR (eds) Handbook of environmental economics. Elsevier Science, Amsterdam p, pp 461–516Google Scholar
  10. Jager W (2006) Stimulating the diffusion of photovoltaic systems: a behavioral perspective. Energy Policy 34:1935–1943CrossRefGoogle Scholar
  11. JPEA (2014) Statistics www.jpea.gr.jp/pdf/150219_deployment.pdf. Accessed 8 Apr 2015 (In Japanese)
  12. Kramer D, Bigelow P, Vi P, Garritano E, Carlan N, Wells R (2009) Spreading good ideas: a case study of the adoption of an innovation in the construction sector. Appl Ergon 40:826–832CrossRefGoogle Scholar
  13. Labay DG, Kinnear TC (1981) Exploring the consumer decision process in the adoption of solar energy. J Consum Res 8:271–278CrossRefGoogle Scholar
  14. Lesser J, Su X (2008) Design of an economically efficient feed-in tariff structure for renewable energy development. Energy Policy 36:981–990CrossRefGoogle Scholar
  15. Martin N, Rice J (2013) The solar photovoltaic feed-in tariff scheme in New South Wales, Australia. Energy Policy 61:697–706CrossRefGoogle Scholar
  16. Mendonça M (2007) Feed-in tariffs: accelerating the development of renewable energy. Earthscan, LondonGoogle Scholar
  17. METI (2013) A report on the diffusion of photovoltaic systems. http://www.meti.go.jp/meti_lib/report/2013fy/E002502.pdf. Accessed 30 Nov 2017 (In Japanese)
  18. Moor GA (2014) Crossing the chasm: marketing and selling disruptive products to mainstream customers, 3rd edn. Harper Business, New YorkGoogle Scholar
  19. Noll D, Dawes C, Rai V (2014) Solar community organizations and active peer effects in the adoption of residential PV. Energy Policy 67:330–343CrossRefGoogle Scholar
  20. Parker P (2008) Residential solar photovoltaic market stimulation: Japanese and Australian lessons for Canada. Renew Sust Energy Rev 12:1944–1958CrossRefGoogle Scholar
  21. Rai V, Robinson SA (2013) Effective information channels for reducing costs of environmentally-friendly technologies: evidence from residential PV markets. Environ Res Lett 8(014044):1–8Google Scholar
  22. Rigter J, Vidican G (2010) Cost and optimal feed-in tariff for small scale photovoltaic systems in China. Energy Policy 38:6989–7000CrossRefGoogle Scholar
  23. Rogers EM (2003) Diffusion of innovations, 5th edn. Free Press, New YorkGoogle Scholar
  24. Statistics Bureau of Japan (2010) Population census of Japan. www.stat.go.jp/data/kokusei/2010/index.htm. Accessed 21 Mar 2015 (In Japanese)
  25. Schelly C (2014) Residential solar electricity adoption: what motivates, and what matters? A case study of early adopters. Energy Res Soc Sci 2:183–191CrossRefGoogle Scholar
  26. Shirai N, Masaoka K, Ohno K, Tokai A (2012) Analysis of residential photovoltaic generation, attention to characteristic of installed persons and factors of installation. J Jpn Soc Energy Resour 33:1–9 (In Japanese with English abstract)Google Scholar
  27. Stern PC (1992) What psychology knows about energy conservation. Am Psychol 47:1224–1232CrossRefGoogle Scholar
  28. Sultan F, Winer RS (1993) Time preferences for products and attributes and the adoption of technology-driven consumer durable innovations. J Econ Psychol 14:587–613CrossRefGoogle Scholar
  29. Wilson C, Dowlatabadi H (2007) Models of decision making and residential energy use. Annu Rev Env Resour 32:169–203CrossRefGoogle Scholar
  30. Zhai P, Williams ED (2012) Analyzing consumer acceptance of photovoltaics (PV) using fuzzy logic model. Renew Energy 41:350–357CrossRefGoogle Scholar
  31. Zhang L, Wu Y (2012) Market segmentation and willingness to pay for green electricity among urban residents in China: the case of Jiangsu Province. Energy Policy 51:514–523CrossRefGoogle Scholar
  32. Zorić J, Hrovatin N (2012) Household willingness to pay for green electricity in Slovenia. Energy Policy 47:180–187CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Takasaki City University of EconomicsTakasakiJapan

Personalised recommendations