1. bookVolume 26 (2022): Issue 1 (January 2022)
Journal Details
First Published
26 Mar 2010
Publication timeframe
2 times per year
access type Open Access

Factors Affecting Photo Voltaic Solar Energy Usage Intention in Rural Households in Bangladesh: A Structural Equation Modelling Approach

Published Online: 22 May 2022
Volume & Issue: Volume 26 (2022) - Issue 1 (January 2022)
Page range: 276 - 293
Journal Details
First Published
26 Mar 2010
Publication timeframe
2 times per year

This research examines the factors that affect Photo Voltaic (PV) solar technology’s usage intention in rural households in Bangladesh. The conceptual model for this research was developed according to past studies. There were five hypotheses developed and verified in this study. Cross sectional quantitative method was used in this research. The model was tested using empirical data collected from 209 households. This research mentions that PV solar technology usage intention was predicted by environmental concern, environmental knowledge, adoption cost, awareness, and government initiatives. The model shows a larger proposition (95 %) in the variance of PV solar technology usage in rural households in Bangladesh. According to the results of this study, we have accepted all hypotheses (H1–H5). From a practical perspective, this study’s results provide a guideline for investment decisions for the usage of PV solar technology in Bangladesh.


[1] Uddin M. N., et al. Renewable energy in Bangladesh : Status and prospects. Energy Procedia 2019:160:655–661. https://doi.org/10.1016/j.egypro.2019.02.21810.1016/j.egypro.2019.02.218 Search in Google Scholar

[2] Islam S. A review on recent growth of electrical power generation and power demand in Bangladesh and some suggestions for combating the upcoming challenges. Energy Procedia 2019:160:60–67. https://doi.org/10.1016/j.egypro.2019.02.11910.1016/j.egypro.2019.02.119 Search in Google Scholar

[3] Rahman A. BD to import 1,000MW hydro-power from Myanmar, China. Dhaka Tribune, 2017. Search in Google Scholar

[4] Crago C. L., Chernyakhovskiy I. Residential solar photovoltaic technology adoption: An empirical investigation of state policy effectiveness. Presented on the 2014 at the Agricultural & Applied Economics Association’s Annual Meeting, Minneapolis, USA, 2014. Search in Google Scholar

[5] Hoen B., et al. An analysis of the effects of residential photovoltaic energy systems on home sales prices in California. Denver: EETD, 2011.10.2172/1013074 Search in Google Scholar

[6] Graziano M., Gillingham K. Spatial patterns of solar photovoltaic system adoption: the influence of neighbors and the built environment. J. Econ. Geogr. 2015:15(4):815–839. https://doi.org/10.1093/jeg/lbu03610.1093/jeg/lbu036 Search in Google Scholar

[7] Lobel R., Perakis G. Consumer choice model for forecasting demand and designing incentives for solar technology. Sloan: MITSloan, 2011. http://dx.doi.org/10.2139/ssrn.174842410.2139/ssrn.1748424 Search in Google Scholar

[8] Hughes J. E., Podolefsky M. Getting green with solar subsidies: evidence from the California solar initiative. J. Assoc. Environ. Resour. Econ. 2015:2(2):235–275. https://doi.org/10.1086/68113110.1086/681131 Search in Google Scholar

[9] Sulaiman J., Azman A., Saboori B. Development of solar energy in Sabah Malaysia: The case of Trudgill’s Perception. Int. J. Sustain. Energy Environ. Res. 2014:3:90–99. Search in Google Scholar

[10] W. Mann. Solar Renewable Energy Certificate Markets: Assessing the Volatility Impact. Springer, 2014(73). Search in Google Scholar

[11] Hirth L. Market value of solar power: Is photovoltaics cost-competitive? IET Renew. Power Gener. 2014:9:37–45. https://doi.org/10.1049/iet-rpg.2014.010110.1049/iet-rpg.2014.0101 Search in Google Scholar

[12] Huo M., Zhang X., He J. Causality relationship between the photovoltaic market and its manufacturing in China, Germany, the US, and Japan. Front. Energy. 2011:5:43–48. https://doi.org/10.1007/s11708-010-0135-510.1007/s11708-010-0135-5 Search in Google Scholar

[13] Palage K., Lundmark R., Söderholm P. Public policies and solar PV innovation: an empirical study based on patent data. Presented at the 37th IAEE Int. Conf. on Energy Econ. New York, USA, 2014 Search in Google Scholar

[14] Adachi C., Rowlands I. H. The role of policies in supporting the diffusion of solar photovoltaic systems: Experiences with Ontario, Canada’s Renewable Energy Standard Offer Program. Sustainability 2010:2:30–47. https://doi.org/10.3390/su201003010.3390/su2010030 Search in Google Scholar

[15] Resch R., Solar Energy Industries Association. US Solar Industry Continues Rapid Growth. Washington: SEIA, 2014. Search in Google Scholar

[16] Vorrath S. One-quarter of Australian homes now have solar. Renew Economy, 2017. Search in Google Scholar

[17] International Trade Administration. United Arab Emirates - Renewable Energy. Washington: U.S. Department of Commerce, 2018. Search in Google Scholar

[18] Masukujjaman M., et al. Purchase Intention of Renewable Energy Technology in Rural Areas in Bangladesh: Empirical Evidence. Renew. Energy 2021:170:639–651. https://doi.org/10.1016/j.renene.2021.01.12510.1016/j.renene.2021.01.125 Search in Google Scholar

[19] Kabir E., et al. Solar energy: Potential and future prospects. Renew. Sustain. Energy Rev. 2018:82:894–900. https://doi.org/10.1016/j.rser.2017.09.09410.1016/j.rser.2017.09.094 Search in Google Scholar

[20] Spanos Y. E., Prastacos G. P., Poulymenakou A. The relationship between information and communication technologies adoption and management. Information & Management 2002:39:659–675. https://doi.org/10.1016/S0378-7206(01)00141-010.1016/S0378-7206(01)00141-0 Search in Google Scholar

[21] Dewan S., Kraemer K. L. Information technology and productivity: evidence from country-level data. Manag. Sci. 2000:46:548–562.10.1287/mnsc.46.4.548.12057 Search in Google Scholar

[22] Davies S., Davies G. The diffusion of process innovations. Campbridge University Press, 1979.10.1016/0014-2921(79)90023-0 Search in Google Scholar

[23] Dunlap R. E., Scarce R. Poll trends: Environmental problems and protection. Public Opin. Q. 1991:55:651–672.10.1086/269288 Search in Google Scholar

[24] Leonidou C. N., Leonidou L. C. Research into environmental marketing/management: a bibliographic analysis. Eur. J. Mark. 2011:45(1/2):68–103. https://doi.org/10.1108/0309056111109560310.1108/03090561111095603 Search in Google Scholar

[25] Plouffe C. R., Hulland J. S., Vandenbosch M. Richness versus parsimony in modeling technology adoption decisions— understanding merchant adoption of a smart card-based payment system. Inf. Syst. Res. 2001:12(2):208–222. https://doi.org/10.1287/isre. Search in Google Scholar

[26] Agarwal R., Prasad J. The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decis. Sci. 1997:28(3):557–582. https://doi.org/10.1111/j.1540-5915.1997.tb01322.x10.1111/j.1540-5915.1997.tb01322.x Search in Google Scholar

[27] Moore G.C., Benbasat I. Development of an instrument to measure the perceptions of adopting an information technology innovation. Inf. Syst. Res. 1991:2(3):192–222. https://doi.org/10.1287/isre.2.3.19210.1287/isre.2.3.192 Search in Google Scholar

[28] Fishbein M., et al. Predicting and understanding family planning behaviors. Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice Hall, 1980. Search in Google Scholar

[29] Davis F. D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q. 1989:13(3):319–340. https://doi.org/10.2307/24900810.2307/249008 Search in Google Scholar

[30] Davis R., et al. User Acceptance of Computer Technology: A Comparison of Two Theoretical Models. Manage. Sci.1989:35(8):982–1003. https://doi.org/10.1287/mnsc.35.8.98210.1287/mnsc.35.8.982 Search in Google Scholar

[31] Ajzen I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991:50:179–21110.1016/0749-5978(91)90020-T Search in Google Scholar

[32] Falko F. S., Presseau J., Araújo-Soares V. Time to retire the theory of planned behaviour. Heal. Psych. Rev. 2014:8(1):1–7. https://doi.org/10.1080/17437199.2013.86971010.1080/17437199.2013.86971025053004 Search in Google Scholar

[33] Hai L. C., Alam Kazmi S. H. Dynamic support of government in online shopping. A. Soc. Sci, 2015:11(22):1–9. https://doi.org/10.5539/ass.v11n22p110.5539/ass.v11n22p1 Search in Google Scholar

[34] Karatu V. M. H., Mat N. K. N. The mediating effects of green trust and perceived behavioral control on the direct determinants of intention to purchase green products in Nigeria. Mediterr. J. Soc. Sci. 2015:6(4):256. https://doi.org/10.5901/mjss.2015.v6n4p25610.5901/mjss.2015.v6n4p256 Search in Google Scholar

[35] Jaiswal D., Kant R. Green purchasing behaviour: A conceptual framework and empirical investigation of Indian consumers. J. Retail. Consum. Serv. 2018:41:60–69. https://doi.org/10.1016/j.jretconser.2017.11.00810.1016/j.jretconser.2017.11.008 Search in Google Scholar

[36] Anderson K. Australia leads the way in small scale solar installs. Solar Guide [Online]. [Accessed 02.04.2022] Available: https://www.solarguide.co.uk/australia-leads-the-way-in-small-scale-solar-installs#/ Search in Google Scholar

[37] Sang Y.-N., Bekhet H. A. Exploring factors influencing electric vehicle usage intention: an empirical study in Malaysia. Int. J. Bus. Soc. 2015:16(1):57–74. https://doi.org/10.33736/ijbs.554.201510.33736/ijbs.554.2015 Search in Google Scholar

[38] Alam S. S. Adoption of internet in Malaysian SMEs. J. Small Bus. Enterp. Dev. 2009:16(2):240–255. https://doi.org/10.1108/1462600091095603810.1108/14626000910956038 Search in Google Scholar

[39] Borenstein S. Electricity Rate Structures and the Economics of Solar PV: Could Mandatory Time-of-Use Rates Undermine California’s Solar Photovoltaic Subsidies? Berkeley: CSEM, UCEI, 2007. Search in Google Scholar

[40] Yadav R., Pathak G. S. Young consumers’ intention towards buying green products in a developing nation: Extending the theory of planned behavior. J. Clean. Prod. 2016:135:732–739. https://doi.org/10.1016/j.jclepro.2016.06.12010.1016/j.jclepro.2016.06.120 Search in Google Scholar

[41] Mostafa M. M. Gender differences in Egyptian consumers’ green purchase behaviour: the effects of environmental knowledge, concern and attitude. Int. J. Consum. Stud. 2007:31(3):220–229. https://doi.org/10.1111/j.1470-6431.2006.00523.x10.1111/j.1470-6431.2006.00523.x Search in Google Scholar

[42] Setyawan A., et al. Green product buying intentions among young consumers: Extending the application of theory of planned behavior. Probl. Perspect. Manag. 2018:16(2):145–154. https://doi.org/10.21511/ppm.16(2).2018.1310.21511/ppm.16(2).2018.13 Search in Google Scholar

[43] Fransson N., Gärling T. Environmental concern: Conceptual definitions, measurement methods, and research findings. J. Environ. Psychol. 1999:19(4):369–382. https://doi.org/10.1006/jevp.1999.014110.1006/jevp.1999.0141 Search in Google Scholar

[44] Howard J., Moore W. Changes in consumer behavior over the product life cycle. Readings in the management of innovation. Boston: Pitman. 1982. Search in Google Scholar

[45] Sathye M. Adoption of Internet banking by Australian consumers: an empirical investigation. Int. J. Bank Mark. 1999:17(7):324–334. https://doi.org/10.1108/0265232991030568910.1108/02652329910305689 Search in Google Scholar

[46] Fishbein R. E., Sanghvi A. P., Unit A. E. Survey of productive uses of electricity in rural areas. Washington, 2003. Search in Google Scholar

[47] Zografakis N., et al. Assessment of public acceptance and willingness to pay for renewable energy sources in Crete. Renew. Sustain. Energy Rev. 2010:14:1088–1095. https://doi.org/10.1016/j.rser.2009.11.00910.1016/j.rser.2009.11.009 Search in Google Scholar

[48] Wüstenhagen R., Wolsink M., Bürer M. J. Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy 2007:35(5):2683–2691. https://doi.org/10.1016/j.enpol.2006.12.00110.1016/j.enpol.2006.12.001 Search in Google Scholar

[49] Cohen W. M., Levinthal D. A. Absorptive capacity: A new perspective on learning and innovation. Adm. Sci. Q. 1990:35(1):128–152. https://doi.org/10.2307/239355310.2307/2393553 Search in Google Scholar

[50] Pagiaslis A., Krontalis A. K. Green consumption behavior antecedents: Environmental concern, knowledge, and beliefs. Psychol. Mark. 2014:31(5):335–348. https://doi.org/10.1002/mar.2069810.1002/mar.20698 Search in Google Scholar

[51] Mark N., Law M. Encouraging green purchase behaviours of Hong Kong consumers. Asian J. Bus. Res. 2015:5(2). https://doi.org/10.14707/ajbr.15001310.14707/ajbr.150013 Search in Google Scholar

[52] Basha M. B., et al. Consumers attitude towards organic food. Procedia Econ. Financ. 2015:31:444–452. https://doi.org/10.1016/S2212-5671(15)01219-810.1016/S2212-5671(15)01219-8 Search in Google Scholar

[53] Suki N. M. Investigating the measurement of Consumer ecological behaviour, environmental knowledge, healthy food, and healthy way of life. Int. J. Soc. Ecol. Sustain. Dev. 2014:5(1):12–21. https://doi.org/10.4018/ijsesd.201401010210.4018/ijsesd.2014010102 Search in Google Scholar

[54] Peter R., Dickie L., Peter V. M. Adoption of photovoltaic power supply systems: A study of key determinants in India. Renew. Energy 2006:31(14):2272–2283. https://doi.org/10.1016/j.renene.2005.11.00110.1016/j.renene.2005.11.001 Search in Google Scholar

[55] Alam S. S., et al. A survey on renewable energy development in Malaysia: Current status, problems and prospects. Environ. Clim. Technol. 2016:17:5–17. https://doi.org/10.1515/rtuect-2016-000210.1515/rtuect-2016-0002 Search in Google Scholar

[56] Sarker S. R., Roy P. P., Zuberi M. I. Home Garden: A Genetic Resource of Jackfruit (Artocarpus heterophyllus Lam) in Semi Arid Region of Bangladesh. Gene Conserv. 2015:14(57):1–28. Search in Google Scholar

[57] Hair J. F., et al. Multivariate Data Analysis. 5th edition. New York: Pearson, 1998. Search in Google Scholar

[58] Chen K., Deng T. Research on the green purchase intentions from the perspective of Product knowledge. Sustain. 2016:8(9):943. https://doi.org/10.3390/su809094310.3390/su8090943 Search in Google Scholar

[59] Yang M., Al-Shaaban S., Nguyen T. B. Consumer attitude and purchase intention towards organic food: A quantitative study of China. 2014. Search in Google Scholar

[60] Alam S. S., et al. Factors affecting e-commerce adoption in the electronic manufacturing companies in Malaysia. Int. J. Commer. Manag. 2007:17(1/2):125–139. https://doi.og/10.1108/1056921071077650310.1108/10569210710776503 Search in Google Scholar

[61] Alam S. S., et al. An empirical study of factors affecting electronic commerce adoption among SMEs in Malaysia. J. Bus. Econ. Manag. 2011:12(2):375–399. https://doi.org/10.3846/16111699.2011.57674910.3846/16111699.2011.576749 Search in Google Scholar

[62] Ahmad A., et al. Perceptions on Renewable Energy Use in Malaysia : Mediating Role of Attitude. J. Pengur. 2014:41:123–131. https://doi.org/10.17576/pengurusan-2014-41-1110.17576/pengurusan-2014-41-11 Search in Google Scholar

[63] Moghavvemi S., et al. An empirical study of IT innovation adoption among small and medium sized enterprises in Klang Valley, Malaysia. Soc. Technol. Technol. 2011:1:267–282. Search in Google Scholar

[64] Lo S. M., Power D. An empirical investigation of the relationship between product nature and supply chain strategy. Supply Chain Manag. 2010:15(2):139–153. https://doi.org/10.1108/1359854101102874110.1108/13598541011028741 Search in Google Scholar

[65] Ryans A. B. Estimating Consumer Preferences for a New Durable Brand in an Established Product Class. J. Mark. Res. 1974:11(4):434–443. https://doi.org/10.2307/315129010.2307/3151290 Search in Google Scholar

[66] Podsakoff P. M., et al. Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. J. Appl. Psychol. 2003:88(5):879–903. https://doi.org/10.1037/0021-9010.88.5.87910.1037/0021-9010.88.5.87914516251 Search in Google Scholar

[67] Alexander N., Colgate M. Retail financial services: transaction to relationship marketing. Eur. J. Mark. 2000:34(8):938–953. https://doi.org/10.1108/0309056001033143210.1108/03090560010331432 Search in Google Scholar

[68] Malhotra N. K. Marketing research, An applied orientation, 3rd Edition. New York: Pearson, 1999. Search in Google Scholar

[69] Hair J. F., et al. A premier on partial least squares structural equation modeling (PLS-SEM). Newbuty Park: Sage Publications, 2014. Search in Google Scholar

[70] Bryman A., Cramer D. Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Oxford: Routledge, 2002. Search in Google Scholar

[71] Kline R. B. Convergence of structural equation modeling and multilevel modeling. The SAGE Handbook of Innovation in Social Research Methods. Newbury Park: SAGE, 2011. https://dx.doi.org/10.4135/9781446268261.n3110.4135/9781446268261.n31 Search in Google Scholar

[72] Bagozzi R. P., Yi Y. On the evaluation of structural equation models. J. Acad. Mark. Sci. 1988:16:74–94. https://doi.org/10.1007/BF0272332710.1007/BF02723327 Search in Google Scholar

[73] Holbert R. L., Stephenson M. T. Structural Equation Modeling in the Communication Sciences, 1995–2000. Hum. Commun. Res. 2002:28:1995–2000. https://doi.org/10.1111/j.1468-2958.2002.tb00822.x10.1111/j.1468-2958.2002.tb00822.x Search in Google Scholar

[74] Bentler P. M., Bonett D. G. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull. 1980:88:588–606. https://doi.org/10.1037/0033-2909.88.3.58810.1037/0033-2909.88.3.588 Search in Google Scholar

[75] Jöreskog K. G., Sörbom D. LISREL 8: Structural equation modeling with the SIMPLIS command language. US: Scientific Software International, 1993. Search in Google Scholar

[76] Fornell C., Larcker D. F. Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics. J. Mark. Res. 1981:18(3):382–388. https://doi.org/10.2307/315098010.2307/3150980 Search in Google Scholar

[77] McDonald R. P., Ho M.-H. R. Principles and practice in reporting structural equation analyses. Psychol. Methods. 2002:7(1):64–82. https://doi.org/10.1037/1082-989x.7.1.6410.1037/1082-989X.7.1.6411928891 Search in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo