IIMS Journal of Management Science
issue front

Archana Nag1, Rupal Chowdhary1 and Amulya Gurtu2

First Published 11 Dec 2024. https://doi.org/10.1177/0976030X241291626
Article Information
Corresponding Author:

Archana Nag, Prestige Institute of Management and Research (PIMR) 2, Education & Health Sector, Scheme No 54, Indore, Madhya Pradesh 452010, India.
Email: archananag2712@gmail.com

Prestige Institute of Management and Research (PIMR) 2, Education & Health Sector, Indore, Madhya Pradesh, India
Department of Maritime Business Administration, College of Marine Sciences & Maritime Studies, Texas A&M University, Texas, USA

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Abstract

Increased awareness about environmental conservation and global well-being has given way to many initiatives in renewable energy. Hydro, wind, tidal, geothermal, biomass, and solar are the main forms of renewable energy. Solar energy has the largest share of renewable energy and is rapidly increasing because it is feasible and competitive. Many studies have been undertaken to understand the adoption and diffusion of solar energy. This article is a systematic literature review using the TCCM (Theory, Context, Characteristics, Methods) model. It reviewed 95 studies (from 2000 to mid-2023) indexed in top journals on small solar energy installations, primarily in the residential sector. This study discussed well-established product adoption theories, which helped identify various drivers and facilitators affecting solar energy adoption, such as sociocultural, technological, economic, market, and policy. The authors tried to map the facilitators with countries based on income groups, and it was found that the characteristics of solar adoption are similar among countries in an income group.

Keywords

Sustainable development, renewable energy, solar photovoltaic systems, diffusion models, solar energy adoption, TCCM review

References

Adekoya, O. B., Kenku, O. T., Oliyide, J. A., & Al-Faryan, M. A. S. (2023). On the COP26 and coal’s phase-out agenda: Striking a balance among the environmental, economic, and health impacts of coal consumption. Journal of Environmental Management, 328, 116872.

Aggarwal, A. K., Syed, A. A., & Garg, S. (2019). Factors driving Indian consumer’s purchase intention of roof top solar. International Journal of Energy Sector Management, 13(3), 539–555.

Ahmed, Y. A., Rashid, A., & Khurshid, M. M. (2022). Investigating the determinants of the adoption of solar photovoltaic systems—citizen’s perspectives of two developing countries. Sustainability, 14(18), 11764.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Alam, S. S., Ahmad, M., Othman, A. S., Shaari, Z. B. H., & Masukujjaman, M. (2021). Factors affecting photovoltaic solar technology usage intention among households in Malaysia: Model integration and empirical validation. Sustainability, 13(4), 1773.

Ali, I., & Yadav, M. (2019). Factors influencing the consumer intention towards solar rooftop system at household level. IIMS Journal of Management Science, 10(1and2), 1–19.

Alipour, M., Salim, H., Stewart, R. A., & Sahin, O. (2021). Residential solar photovoltaic adoption behaviour: End-to-end review of theories, methods and approaches. Renewable Energy, 170, 471–486.

Alizadeh, R., Soltanisehat, L., Lund, P., & Zamanisabzi, H. (2019). Improving renewable energy policy planning and decision-making through a hybrid MCDM method. Energy Policy, 137, 111174.

Alyousef, A., Adepetu, A., & de Meer, H. (2017). Analysis and model-based predictions of solar PV and battery adoption in Germany: An agent-based approach. Computer Science – Research Development, 32, 211–223.

Aravindan, K. L., Thurasamy, R., Raman, M., Ilhavenil, N., Annamalah, S., & Rathidevi, A. S. (2022). Modeling awareness as the crux in solar energy adoption intention through unified theory of acceptance and use of technology. Mathematics, 10(12), 2045.

Arroyo-López, P., & Carrete, L. (2019). Motivational drivers for the adoption of green energy: The case of purchasing photovoltaic systems. Management Research Review, 42(5), 542–567(26).

Balcombe, P., Rigby, D., & Azapagic, A. (2014). Investigating the importance of motivations and barriers related to microgeneration uptake in the UK. Applied Energy, 130, 403–418.

Balta-Ozkan, N., Yildirim, J., Connor, P. M., Truckell, I., & Hart, P. (2021). Energy transition at local level: Analyzing the role of peer effects and socio-economic factors on UK solar photovoltaic deployment. Energy Policy, 148, 112004.

Bang, H., Ellinger, A., Hadjimarcou, J., & Traichal, P. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy: An application of the reasoned action theory. Psychology and Marketing, 17, 449–468.

Bao, Q., Sinitskaya, E., Gomez, K. J., MacDonald, E. F., & Yang, M. 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, 151, 503–513.

Bass, F. M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215–227.

Best, R., Burke, P. J., & Nishitateno, S. (2019). Understanding the determinants of rooftop solar installation: evidence from household surveys in Australia [CCEP Working Paper 1902], April 2019, Crawford School of Public Policy, The Australian National University.

Billanes, J., & Enevoldsen, P. (2021). A critical analysis of ten influential factors to energy technology acceptance and adoption. Energy Reports, 7, 6899–6907.

Blenkinsopp, T., Coles, S. R., & Kirwan, K. (2013). Renewable energy for rural communities in Maharashtra, India. Energy Policy, 60, 192–199.

Bollinger, B., & Gillingham, K. (2012). Peer effects in the diffusion of solar photovoltaic panels. Marketing Science, 31(6), 900–912.

Brohmann, B., Feenstra, Y. Heiskanen, E., Hodson, M., Mourik, R., & Prasad, G. (2006). Factors influencing the societal acceptance of new, renewable and energy efficiency technologies: Meta-analysis of recent European projects. International Journal of Energy, 20, 191–207.

Cheam, W. Y., Lau, L. S., & Wei, C. Y. (2021). Factors influencing the residence’s intention to adopt solar photovoltaic technology: A case study from Klang Valley, Malaysia. Clean Energy, 5(3), 464–473.

Claudy, M. C., Michelsen, C., O’Driscoll, A., & Mullen, M. R. (2010). Consumer awareness in the adoption of microgeneration technologies: An empirical investigation in the Republic of Ireland. Renewable and Sustainable Energy Reviews, 14(7), 2154–2160.

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340.

Ellegård, A., Arvidson, A., Nordström, M., Kalumiana, O., & Mwanza, C. (2004). Rural people pay for solar: Experiences from the Zambia PV-ESCO project. Renewable Energy, 29, 1251–1263.

Etongo, D., & Naidu, H. (2022). Determinants of household adoption of solar energy technology in Seychelles in a context of 100% access to electricity. Discover Sustainability, 3(1), 38.

Faiers, A., & Neame, C. (2006). Consumer attitudes towards domestic solar power systems. Energy policy, 34(14), 1797–1806.

Fauzi, M. A., Abidin, N. H. Z., Suki, N. M., & Budiea, A. M. A. (2023). Residential rooftop solar panel adoption behavior: Bibliometric analysis of the past and future trends. Renewable Energy Focus, 45, 1–9. https://doi.org/10.1016/j.ref.2023.02.002

Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research. Philosophy and Rhetoric, 10(2).

Gilbert, N. (2007). Agent-based models. The centre for research in social simulations. Quantitative Applications in the Social Sciences, 153. Sage Publications.

Gurtu, A., & Goswami, A. (2022). Emissions in different stages of economic development in nations. Smart and Sustainable Built Environment, 11(3), 608–621. https://doi.org/ 10.1108/SASBE-04-2020-0052

Guta, D. (2018). Determinants of household adoption of solar energy technology in rural Ethiopia. Journal of Cleaner Production, 204. https://doi.org/10.1016/j.jclepro. 2018.09.016.

Halder, P., & Parvez, Md. (2015). Financial analyses and social impact of solar home systems in Bangladesh: A case study. International Journal of Renewable Energy Research, 5, 398–403.

Hamadeh, N., Catherine, V.R., Metreau, E., & Eapen, S.G. (2022). New World Bank country classifications by income level: 2022-2023. Retrieved on March 14, 2024 from https://blogs.worldbank.org/opendata/new-world-bank-country-classifications-income-level-2022-2023

Harish, S., Iychettira, K., Raghavan, S., & Kandlikar, M. (2013). Adoption of solar home lighting systems in India: What might we learn from Karnataka? Energy Policy, 62, 697–706. https://doi.org/10.1016/j.enpol.2013.07.085.

Haselip, J. A., Nygaard, I., Hansen, U. E., & Ackom, E. (2011). Diffusion of renewable energy technologies: Case studies of enabling frameworks in developing countries (Technology Transfer Perspectives Series). Technical University of Denmark.

Heiskanen, E., & Matschoss, K. (2017). Understanding the uneven diffusion of building-scale renewable energy systems: A review of household, local and country level factors in diverse European countries. Renewable and Sustainable Energy Reviews, 75, 580–591.

Irfan, M., Zhao, Z. Y., Rehman, A., Ozturk, I., & Li, H. (2021). Consumers’ intention-based influence factors of renewable energy adoption in Pakistan: a structural equation modeling approach. Environmental Science and Pollution Research, 28, 432–445.

Iskin, I., Taha, R.A., & Daim, T.U. (2013). Exploring the adoption of alternative energy technologies: A literature review. International Journal of Sustainable Society, 5, 43–61. https://doi.org/10.1504/IJSSOC.2013.050534

Jacksohn, A., Grösche, P., Rehdanz, K., & Schröder, C. (2019). Drivers of renewable technology adoption in the household sector. Energy Economics, 81, 216–226.

Jager, W. (2006). Stimulating the diffusion of photovoltaic systems: A behavioural perspective. Energy Policy, 34, 1935–1943. https://doi.org/10.1016/j.enpol.2004.12.022.

Jayaweera, N. (2018). Local factors affecting the spatial diffusion of photovoltaic adoption in Sri Lanka. Energy Policy, 119.

Kabir, E., Kim, K. H., & Szulejko, J. E. (2017). Social impacts of solar home systems in rural areas: A case study in Bangladesh. Energies, 10(10), 1615.

Kajikawa, Y., Yoshikawa, J., Takeda, Y., & Matsushima, K. (2008). Tracking emerging technologies in energy research: Toward a roadmap for sustainable energy. Technological Forecasting and Social Change, 75(6), 771–782.

Kalish, S. (1985). A new product adoption model with pricing, advertising, and uncertainty, Management Science, 31, 1569–1585.

Kamakura, W. A., & Balasubramanian, S. (1988). Long-term view of the diffusion of durables: A study of the role of price and adoption influence processes via tests of nested models. International Journal of Research in Marketing, 5, 1–13.

Karakaya, E., Hidalgo, A., & Nuur, C. (2014). Diffusion of eco-innovations: A review. Renewable and Sustainable Energy Reviews, 33, 392–399.

Khandker, S. R., Samad, H. A., Sadeque, Z. K., Asaduzzaman, M., Yunus, M., & Haque, A. E. (2014). Surge in solar-powered homes: Experience in off-grid rural Bangladesh. World Bank Publications.

Kim, H., Park, E., Kwon, S. J., Ohm, J. Y., & Chang, H. J. (2014). An integrated adoption model of solar energy technologies in South Korea. Renewable Energy, 66, 523–531.

Klaus J., Marian B., Jürgen M. B., Dietmar E., Rüdiger H., Martin J., Thomas L., Ulrich P., & Klaus R. (2006). Lead markets for environmental innovations. ZEW Economic Series.

Komatsu, S., Kaneko, S., Shrestha, R. M., & Ghosh, P. P. (2011). Nonincome factors behind the purchase decisions of solar home systems in rural Bangladesh. Energy for Sustainable Development, 15, 284–292.

Korcaj, L., Hahnel, U. J. J., & Spada, H. (2015). Intentions to adopt photovoltaic systems depend on homeowners’ expected personal gains and behavior of peers. Renewable Energy, 75, 407–415.

Kowalska-Pyzalska, A. (2018). What makes consumers adopt to innovative energy services in the energy market? A review of incentives and barriers. Renewable and Sustainable Energy Reviews, 82, 3570–3581.

Macabebe, E. Q. B., Guerrero Jr, R. C., Domdom, A. C., Garcia, A. S., Porio, E. E., Dumlao, S. M. G., & Perez, T. R. (2016). A review of community-based solar home system projects in the Philippines. MATEC Web of Conferences, 70, 12002.

Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. Journal of Marketing, 54(1), 1–26.

Mahajan, V., & Peterson, R.A. (1985). Models for innovation diffusion. Sage Publications.

Müller, S., & Rode, J. (2013). The adoption of photovoltaic systems in Wiesbaden, Germany. Economics of Innovation and New Technology, 22(5), 519–535.

Olson, E. L. (2014). Green innovation value chain analysis of PV solar power. Journal of Cleaner Production, 64, 73–80.

Painuly, J. P. (2001). Barriers to renewable energy penetration: A framework for analysis. Renewable Energy, 24, 73–89.

Palm, A. (2020). Early adopters and their motives: Differences between earlier and later adopters of residential solar photovoltaics. Renewable and Sustainable Energy Reviews, 133, 110142.

Palmer, J., Sorda, G., & Madlener, R. (2015). Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation. Technological Forecasting and Social Change, 99, 106–131.

Pasten, C., & Santamarina, J. C. (2012). Energy and quality of life. Energy Policy, 49, 468–476.

Pathania, A.K., Goyal, B., & Saini, J.R. (2017). Diffusion of adoption of solar energy – A structural model analysis. Smart and Sustainable Built Environment, 6(2), 66–83.

Paul, J., & Criado, A. R. (2020). The art of writing literature review: What do we know and what do we need to know? International Business Review, 29(4), 101717.

Paul, J., & Rosado, A. (2019). Gradual Internationalization vs Born-Global/International new venture models: A review and research agenda. International Marketing Review, 36(26). https://doi.org/10.1108/IMR-10-2018-0280

Po, K. (2014). Evaluating renewable energy policy: A review of criteria and indicators for assessment.

Pradhan, B. R., & Kar, S. K. (2019). Energy inclusion through renewable energy adoption and livelihood improvement in India. IIMS Journal of Management Science, 10(1and2), 52–63.

Qureshi, T.M., Ullah, K., & Arentsen, M. (2017). Factors responsible for solar PV adoption at household level: A case of Lahore, Pakistan. Renewable and Sustainable Energy Reviews, 78, 754–763.

Rai, R., & Allada, V. (2002). Adaptive-agent based simulation model to study diffusion of eco-innovation strategies. In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 36223, 495–503.

Rai, V., Reeves, D. C., & Margolis, R. (2016). Overcoming barriers and uncertainties in the adoption of residential solar PV. Renewable Energy, 89, 498–505.

Rai, V., & Robinson, S. (2015). Agent-based modeling of energy technology adoption: Empirical integration of social, behavioral, economic, and environmental factors. Environmental Modelling & Software, 70, 163–177.

Rao, K. U., & Kishore, V. V. N. (2010). A review of technology diffusion models with special reference to renewable energy technologies. Renewable and Sustainable Energy Reviews, 14(3), 1070–1078.

Rogers, E. M. (1962). Diffusion of Innovations (First Printing). ISBN 10: 002926670X / ISBN 13: 9780029266700. Published by The Free Press of Glencoe, NY.

Rogers, E. M., Singhal, A., & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432–448). Routledge.

Schelly, C., & Letzelter, J. (2020). Examining the key drivers of residential solar adoption in upstate New York. Sustainability, 12, 2552.

Schulte, E., Scheller, F., Sloot, D., & Bruckner, T. (2022). A meta-analysis of residential PV adoption: The important role of perceived benefits, intentions and antecedents in solar energy acceptance. Energy Research & Social Science, 84, 102339.

Sharif, I., & Mithila, M. (2013). Rural electrification using PV: The success story of Bangladesh. Energy Procedia, 33, 343–354.

Simpson, G., & Clifton, J. (2017). Testing diffusion of innovations theory with data: Financial incentives, early adopters, and distributed solar energy in Australia. Energy Research & Social Science, 29, 12–22.

Singh, S., & Dhir, S. (2019). Structured review using TCCM and bibliometric analysis of international cause-related marketing, social marketing, and innovation of the firm. International Review on Public and Nonprofit Marketing, 16, 335–347.

Smith, A., Kern, F., Raven, R., & Verhees, B. (2014). Spaces for sustainable innovation: Solar photovoltaic electricity in the UK. Technological Forecasting and Social Change, 81, 115–130.

Smith, A., & Raven, R. (2012). What is protective space? Reconsidering niches in transitions to sustainability. Research Policy, 41(6), 1025–1036.

Thiede, D. J. (2014). Exploring the power of consumer attitudes and actions on the adoption of solar and wind energy in Minnesota. University Digital Conservancy. https://hdl.handle.net/11299/166765

Tigabu, A. (2017). Analyzing the diffusion and adoption of renewable energy technologies in Africa: The functions of innovation systems perspective. African Journal of Science, Technology, Innovation and Development, 10, 1–10.

UNSDG. (2015). United Nations’ Sustainable Development Goals retrieved from https://www.un.org/sustainabledevelopment/development-agenda on April 4, 2024

Vasseur, V., & Kemp, R. (2015). The adoption of PV in the Netherlands: A statistical analysis of adoption factors. Renewable and Sustainable Energy Reviews, 41, 483–494.

Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46, 186–204.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 425–478.

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178.

Venkateswaran, J., Solanki, C., Werner, K., & Yadama, G. (2018). Addressing Energy Poverty in India: A systems perspective on the role of localization, affordability, and saturation in implementing solar technologies. Energy Research & Social Science, 40, 205–210.

Walters, J., Kaminsky, J., & Huepe, C. (2018). Factors influencing household solar adoption in Santiago, Chile. Journal of Construction Engineering and Management, 144(6). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001483

Wolske, K., Stern, P., & Dietz, T. (2017). Explaining interest in adopting residential solar photovoltaic systems in the United States: Toward an integration of behavioral theories. Energy Research & Social Science, 25, 134–151.

Wüstenhagen, R., Wolsink, M., & Bürer, M. J. (2007). Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy, 35(5), 2683–2691.

Zhang, N., Lu, Y., Chen, J., & Hwang, B. G. (2022). An agent-based diffusion model for Residential Photovoltaic deployment in Singapore: Perspective of consumers’ behaviour. Journal of Cleaner Production, 367, 132793.

Zhao, J., Mazhari, E., Celik, N., & Son, Y. J. (2011). Hybrid agent-based simulation for policy evaluation of solar power generation systems. Simulation Modeling Theory and Practice, 19, 2189–2205.

Zulu, S., Zulu, E., & Chabala, M. (2022). Factors influencing households’ intention to adopt solar energy solutions in Zambia: insights from the theory of planned behaviour. Smart and Sustainable Built Environment, 11(4), 951–971.


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