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A Behavior theory integrated ANN analytical approach for understanding households adoption decisions of residential photovoltaic (RPV) system

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  • Zhang, Nan
  • Hwang, Bon-Gang
  • Lu, Yujie
  • Ngo, Jasmine

Abstract

As residential photovoltaic (RPV) system gradually replaces fossil energy, it is imperative to conduct the RPV adoption decision analysis to investigate factors that drive RPV growth. Non-linear relationships are common in analyzing adoption behaviors, but they are often ignored in the existing studies due to the limitations of conventional data analysis approaches. On the other hand, Artificial Neural Networks (ANNs) are robust in dealing with non-linear relationships, but they lack interpretation capability, making ANNs unsuitable for RPV adoption analysis. To resolve the interpretation issue when considering non-linear relationships, this study proposes a six-step analytical procedure based on hybrid ANNs. The behavior theory was first integrated into the ANN to improve the model's performance. Afterward, the network weight-based method is implemented to calculate the importance of factors from the trained ANN. The proposed approach was used to analyze RPV adoption in Singapore, and the results indicated that the hybrid-ANN outperforms existing models in predicting and explaining adoption behaviors. The study demonstrates the suitability of adopting ANNs in decision analysis by developing a novel way to construct the hybrid ANN in considering non-linear relationships. In addition, the case study has identified that unfamiliarity with RPV hinders the adoption, emphasized the role of social support in promoting RPV, and proposed three practical policy implications for RPV development in Singapore, which can be extended to residential buildings across the globe.

Suggested Citation

  • Zhang, Nan & Hwang, Bon-Gang & Lu, Yujie & Ngo, Jasmine, 2022. "A Behavior theory integrated ANN analytical approach for understanding households adoption decisions of residential photovoltaic (RPV) system," Technology in Society, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:teinso:v:70:y:2022:i:c:s0160791x22002032
    DOI: 10.1016/j.techsoc.2022.102062
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    as
    1. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    2. Hill, Tim & Marquez, Leorey & O'Connor, Marcus & Remus, William, 1994. "Artificial neural network models for forecasting and decision making," International Journal of Forecasting, Elsevier, vol. 10(1), pages 5-15, June.
    3. Rebane, Kaja L. & Barham, Bradford L., 2011. "Knowledge and adoption of solar home systems in rural Nicaragua," Energy Policy, Elsevier, vol. 39(6), pages 3064-3075, June.
    4. Sovacool, Benjamin K., 2009. "Rejecting renewables: The socio-technical impediments to renewable electricity in the United States," Energy Policy, Elsevier, vol. 37(11), pages 4500-4513, November.
    5. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 20(2), pages 183-230, June.
    6. Kamal, Syeda Ayesha & Shafiq, Muhammad & Kakria, Priyanka, 2020. "Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)," Technology in Society, Elsevier, vol. 60(C).
    7. Palm, Jenny, 2018. "Household installation of solar panels – Motives and barriers in a 10-year perspective," Energy Policy, Elsevier, vol. 113(C), pages 1-8.
    8. Kwan, Calvin Lee, 2012. "Influence of local environmental, social, economic and political variables on the spatial distribution of residential solar PV arrays across the United States," Energy Policy, Elsevier, vol. 47(C), pages 332-344.
    9. Bhandari, Amit K. & Jana, Chinmoy, 2010. "A comparative evaluation of household preferences for solar photovoltaic standalone and mini-grid system: An empirical study in a costal village of Indian Sundarban," Renewable Energy, Elsevier, vol. 35(12), pages 2835-2838.
    10. Bao, Qifang & Sinitskaya, Ekaterina & Gomez, Kelley J. & MacDonald, Erin F. & Yang, Maria C., 2020. "A human-centered design approach to evaluating factors in residential solar PV adoption: A survey of homeowners in California and Massachusetts," Renewable Energy, Elsevier, vol. 151(C), pages 503-513.
    11. Zoellner, Jan & Schweizer-Ries, Petra & Wemheuer, Christin, 2008. "Public acceptance of renewable energies: Results from case studies in Germany," Energy Policy, Elsevier, vol. 36(11), pages 4136-4141, November.
    12. Heras-Saizarbitoria, Iñaki & Zamanillo, Ibon & Laskurain, Iker, 2013. "Social acceptance of ocean wave energy: A case study of an OWC shoreline plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 515-524.
    13. Pi-Chuan Sun & Hsueh-Mei Wang & Hsien-Long Huang & Chien-Wei Ho, 2020. "Consumer attitude and purchase intention toward rooftop photovoltaic installation: The roles of personal trait, psychological benefit, and government incentives," Energy & Environment, , vol. 31(1), pages 21-39, February.
    14. Paschen, Jeannette & Wilson, Matthew & Ferreira, João J., 2020. "Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel," Business Horizons, Elsevier, vol. 63(3), pages 403-414.
    15. Saqib Ali & Petra Poulova & Ahsan Akbar & Hafiz Muhammad Usama Javed & Muhammad Danish, 2020. "Determining the Influencing Factors in the Adoption of Solar Photovoltaic Technology in Pakistan: A Decomposed Technology Acceptance Model Approach," Economies, MDPI, vol. 8(4), pages 1-20, December.
    16. Xiong, Hang & Payne, Diane & Kinsella, Stephen, 2016. "Peer effects in the diffusion of innovations: Theory and simulation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 63(C), pages 1-13.
    17. Korcaj, Liridon & Hahnel, Ulf J.J. & Spada, Hans, 2015. "Intentions to adopt photovoltaic systems depend on homeowners' expected personal gains and behavior of peers," Renewable Energy, Elsevier, vol. 75(C), pages 407-415.
    18. Parkins, John R. & Rollins, Curtis & Anders, Sven & Comeau, Louise, 2018. "Predicting intention to adopt solar technology in Canada: The role of knowledge, public engagement, and visibility," Energy Policy, Elsevier, vol. 114(C), pages 114-122.
    19. Wustenhagen, Rolf & Wolsink, Maarten & Burer, Mary Jean, 2007. "Social acceptance of renewable energy innovation: An introduction to the concept," Energy Policy, Elsevier, vol. 35(5), pages 2683-2691, May.
    20. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    21. Claudy, Marius C. & Michelsen, Claus & O'Driscoll, Aidan & Mullen, Michael R., 2010. "Consumer awareness in the adoption of microgeneration technologies: An empirical investigation in the Republic of Ireland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2154-2160, September.
    22. Zhu, Bing & Zhang, Wenjun & Du, Jian & Zhou, Wenji & Qiu, Tong & Li, Qiang, 2011. "Adoption of renewable energy technologies (RETs): A survey on rural construction in China," Technology in Society, Elsevier, vol. 33(3), pages 223-230.
    23. Train, Kenneth E & McFadden, Daniel L & Goett, Andrew A, 1987. "Consumer Attitudes and Voluntary Rate Schedules for Public Utilities," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 383-391, August.
    24. Vaidya, Omkarprasad S. & Kumar, Sushil, 2006. "Analytic hierarchy process: An overview of applications," European Journal of Operational Research, Elsevier, vol. 169(1), pages 1-29, February.
    25. Rogers, Everett M, 1976. "New Product Adoption and Diffusion," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(4), pages 290-301, March.
    26. Jeffrey Walters & Jessica Kaminsky & Lawrence Gottschamer, 2018. "A Systems Analysis of Factors Influencing Household Solar PV Adoption in Santiago, Chile," Sustainability, MDPI, vol. 10(4), pages 1-17, April.
    27. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2021. "Residential solar photovoltaic adoption behaviour: End-to-end review of theories, methods and approaches," Renewable Energy, Elsevier, vol. 170(C), pages 471-486.
    28. Alipour, M. & Salim, H. & Stewart, Rodney A. & Sahin, Oz, 2020. "Predictors, taxonomy of predictors, and correlations of predictors with the decision behaviour of residential solar photovoltaics adoption: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 123(C).
    29. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    30. Sovacool, Benjamin K., 2009. "The cultural barriers to renewable energy and energy efficiency in the United States," Technology in Society, Elsevier, vol. 31(4), pages 365-373.
    31. Nam, KiJeon & Hwangbo, Soonho & Yoo, ChangKyoo, 2020. "A deep learning-based forecasting model for renewable energy scenarios to guide sustainable energy policy: A case study of Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 122(C).
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