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

Environmental and Climate Technologies
Volume 26 (2022): Issue 1 (January 2022)
By:
Open Access
|May 2022

References

  1. [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 ScholarBack to article
  2. [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 ScholarBack to article
  3. [3] Rahman A. BD to import 1,000MW hydro-power from Myanmar, China. Dhaka Tribune, 2017.
    Search in Google ScholarBack to article
  4. [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 ScholarBack to article
  5. [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 ScholarBack to article
  6. [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 ScholarBack to article
  7. [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 ScholarBack to article
  8. [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 ScholarBack to article
  9. [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 ScholarBack to article
  10. [10] W. Mann. Solar Renewable Energy Certificate Markets: Assessing the Volatility Impact. Springer, 2014(73).
    Search in Google ScholarBack to article
  11. [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 ScholarBack to article
  12. [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 ScholarBack to article
  13. [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 ScholarBack to article
  14. [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 ScholarBack to article
  15. [15] Resch R., Solar Energy Industries Association. US Solar Industry Continues Rapid Growth. Washington: SEIA, 2014.
    Search in Google ScholarBack to article
  16. [16] Vorrath S. One-quarter of Australian homes now have solar. Renew Economy, 2017.
    Search in Google ScholarBack to article
  17. [17] International Trade Administration. United Arab Emirates - Renewable Energy. Washington: U.S. Department of Commerce, 2018.
    Search in Google ScholarBack to article
  18. [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 ScholarBack to article
  19. [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 ScholarBack to article
  20. [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 ScholarBack to article
  21. [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 ScholarBack to article
  22. [22] Davies S., Davies G. The diffusion of process innovations. Campbridge University Press, 1979.10.1016/0014-2921(79)90023-0
    Search in Google ScholarBack to article
  23. [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 ScholarBack to article
  24. [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 ScholarBack to article
  25. [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.12.2.208.969710.1287/isre.12.2.208.9697
    Search in Google ScholarBack to article
  26. [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 ScholarBack to article
  27. [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 ScholarBack to article
  28. [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 ScholarBack to article
  29. [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 ScholarBack to article
  30. [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 ScholarBack to article
  31. [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 ScholarBack to article
  32. [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 ScholarBack to article
  33. [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 ScholarBack to article
  34. [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 ScholarBack to article
  35. [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 ScholarBack to article
  36. [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 ScholarBack to article
  37. [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 ScholarBack to article
  38. [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 ScholarBack to article
  39. [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 ScholarBack to article
  40. [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 ScholarBack to article
  41. [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 ScholarBack to article
  42. [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 ScholarBack to article
  43. [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 ScholarBack to article
  44. [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 ScholarBack to article
  45. [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 ScholarBack to article
  46. [46] Fishbein R. E., Sanghvi A. P., Unit A. E. Survey of productive uses of electricity in rural areas. Washington, 2003.
    Search in Google ScholarBack to article
  47. [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 ScholarBack to article
  48. [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 ScholarBack to article
  49. [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 ScholarBack to article
  50. [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 ScholarBack to article
  51. [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 ScholarBack to article
  52. [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 ScholarBack to article
  53. [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 ScholarBack to article
  54. [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 ScholarBack to article
  55. [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 ScholarBack to article
  56. [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 ScholarBack to article
  57. [57] Hair J. F., et al. Multivariate Data Analysis. 5th edition. New York: Pearson, 1998.
    Search in Google ScholarBack to article
  58. [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 ScholarBack to article
  59. [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 ScholarBack to article
  60. [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 ScholarBack to article
  61. [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 ScholarBack to article
  62. [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 ScholarBack to article
  63. [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 ScholarBack to article
  64. [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 ScholarBack to article
  65. [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 ScholarBack to article
  66. [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 ScholarBack to article
  67. [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 ScholarBack to article
  68. [68] Malhotra N. K. Marketing research, An applied orientation, 3rd Edition. New York: Pearson, 1999.
    Search in Google ScholarBack to article
  69. [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 ScholarBack to article
  70. [70] Bryman A., Cramer D. Quantitative data analysis with SPSS release 10 for Windows: A guide for social scientists. Oxford: Routledge, 2002.10.4324/9780203471548
    Search in Google ScholarBack to article
  71. [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 ScholarBack to article
  72. [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 ScholarBack to article
  73. [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 ScholarBack to article
  74. [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 ScholarBack to article
  75. [75] Jöreskog K. G., Sörbom D. LISREL 8: Structural equation modeling with the SIMPLIS command language. US: Scientific Software International, 1993.
    Search in Google ScholarBack to article
  76. [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 ScholarBack to article
  77. [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 ScholarBack to article
DOI: https://doi.org/10.2478/rtuect-2022-0021 | Journal eISSN: 2255-8837 | Journal ISSN: 1691-5208
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Language: English
Page range: 276 - 293
Published on: May 22, 2022
Published by: Riga Technical University
In partnership with: Paradigm Publishing Services
Publication frequency: 2 times per year
Keywords:
Bangladesh,
empirical study,
PV solar technology,
rural households
Related subjects:
Life sciences,
Life sciences, other

© 2022 Syed Shah. Alam, Mohammad Masukujjaman, Chieh-Yu Lin, Nor Asiah. Omar, Meng Na, Abdullah Sanusi Othman, published by Riga Technical University
This work is licensed under the Creative Commons Attribution 4.0 License.

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