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May 26, 2024
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July 3, 2024
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August 15, 2024
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Abstract

Adopting energy-efficient home appliances is one of the critical strategies for supporting environmental protection through reducing energy consumption. This study aims to identify factors contributing to consumers’ intentions to adopt energy-efficient household appliances (EEHA) in Indonesia, particularly in Java, a representative area of energy consumption in the country. Adopting the Theory of Planned Behavior (TPB) as the main theoretical framework, the study expands the model to include media publicity (MP) variables as external factors. The survey method was applied to 200 respondents, and the collected data were analyzed using the Structural Equation Modeling (SEM) technique through Smart-PLS 4. The results revealed that consumer attitudes (CA), perceived behavioral control (PBC), and subjective norms (SN) significantly affected consumers’ intentions in adopting EEHA. Furthermore, the study found that MP significantly influences CA. Likewise, as we expected, MP significantly affected PBC and SN, marking the first time this relationship has been identified in the context of the adoption of EEHA. Based on these findings, we discuss some of the implications for policymakers, marketers, and environmental practitioners in promoting the adoption of EEHA to accelerate the transition to more sustainable energy consumption in households.

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Media publicity theory of planned behavior energy-efficient home appliances intention to buy

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Copyright (c) 2024 Andika Andika, Muinah Fadhilah, Della Nanda Luthfiana, Nadia Nadia, Malik Abd Karim Amirullah

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Andika, A., Fadhilah, M., Luthfiana, D. N., Nadia, N., & Amirullah, M. A. K. (2024). Enhancing energy-efficient home appliance adoption: Media publicity strategies and planned behavior theory. Asian Management and Business Review, 4(2), 241–259. https://doi.org/10.20885/AMBR.vol4.iss2.art5
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References

  1. Abrahamse, W. (2019). Understanding the Drivers of Human Behaviour. In Encouraging Pro-Environmental Behaviour: What Works, What Doesn't, and Why (pp. 11–25). London: Academic Press. https://doi.org/10.1016/b978-0-12-811359-2.00002-0
  2. Ajzen, I. (1985). From Intentions to Actions: A Theory of Planned Behavior. In Kuhl J., & Beckmann, J. (Eds.), Action Control: From Cognition to Behavior (pp. 11-39). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-69746-3
  3. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.47985/dcidj.475
  4. Ajzen, I., & Madden, T. J. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453–474. https://doi.org/https://doi.org/10.1016/0022-1031(86)90045-4
  5. Akadiri, S. Saint, Adebayo, T. S., Nakorji, M., Mwakapwa, W., Inusa, E. M., & Izuchukwu, O. O. (2022). Impacts of globalization and energy consumption on environmental degradation: What is the way forward to achieving environmental sustainability targets in Nigeria? Environmental Science and Pollution Research, 29(40), 60426–60439. https://doi.org/10.1007/s11356-022-20180-7
  6. Ali, M. R., Shafiq, M., & Andejany, M. (2021). Determinants of consumers’ intentions towards the purchase of energy efficient appliances in pakistan: An extended model of the theory of planned behavior. Sustainability (Switzerland), 13(2), 1–17. https://doi.org/10.3390/su13020565
  7. Ali, S., Ullah, H., Akbar, M., Akhtar, W., & Zahid, H. (2019). Determinants of consumer intentions to purchase energy-saving household products in Pakistan. Sustainability (Switzerland), 11(5), 1–20. https://doi.org/10.3390/su11051462
  8. Andika, Luthfiana, D. N., Nadia, & Kartinah. (2023a). Green purchase behavior: The role of green advertising, green awareness, and eco-literacy. IOP Conference Series: Earth and Environmental Science, 1181(1), 1–6. https://doi.org/10.1088/1755-1315/1181/1/012025
  9. Andika, Nadia, Najmudin, M., & Hasibuan, A. B. (2023b). Green cosmetics in Indonesia: Unraveling attitude-behavior gap and gender moderation. Jurnal Aplikasi Bisnis, 21(4), 1134–1152. https://doi.org/http://dx.doi.org/10.21776/ub.jam. 2023.021.04.20.
  10. Apipuchayakul, N., & Vassanadumrongdee, S. (2020). Factors affecting the consumption of energy-efficient lighting products: Exploring purchase behaviors of Thai consumers. Sustainability (Switzerland), 12(12), 1–16. https://doi.org/10.3390/SU12124887
  11. Ashraf Fauzi, M., Hanis Zainal Abidin, N., Mohd Suki, N., & Mokhtar Albshir Budiea, 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/https://doi.org/10.1016/j.ref.2023.02.002
  12. Baldini, M., Trivella, A., & Wente, J. W. (2018). The impact of socioeconomic and behavioural factors for purchasing energy efficient household appliances: A case study for Denmark. Energy Policy, 120(October 2017), 503–513. https://doi.org/10.1016/j.enpol.2018.05.048
  13. Bamberg, S., Hunecke, M., & Blöbaum, A. (2007). Social context, personal norms and the use of public transportation: Two field studies. Journal of Environmental Psychology, 27(3), 190–203. https://doi.org/10.1016/j.jenvp.2007.04.001
  14. Bhutto, M. Y., Liu, X., Soomro, Y. A., Ertz, M., & Baeshen, Y. (2021). Adoption of energy‐efficient home appliances: Extending the theory of planned behavior. Sustainability (Switzerland), 13(1), 1–23. https://doi.org/10.3390/su13010250
  15. Bhutto, M. Y., Soomro, Y. A., & Yang, H. (2022). Extending the theory of planned behavior: Predicting young consumer purchase behavior of energy-efficient appliances (Evidence from developing economy). SAGE Open, 12(1). https://doi.org/10.1177/21582440221078289
  16. Cattaneo, C. (2019). Internal and external barriers to energy efficiency: Which role for policy interventions? Energy Efficiency, 12(5), 1293–1311. https://doi.org/10.1007/s12053-019-09775-1
  17. Cheng, E. W. L. (2019). Choosing between the theory of planned behavior (TPB) and the technology acceptance model (TAM). Educational Technology Research and Development, 67(1), 21–37. https://doi.org/10.1007/s11423-018-9598-6
  18. Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In Marcoulides, G. A. (Ed.), Modern Methods for Business Research. New Jersey: Lawrence Erlbaum Associates, Inc. https://doi.org/10.4324/9781410604385-10
  19. Daroch, B., Nagrath, G., & Gupta, A. (2021). A study on factors limiting online shopping behaviour of consumers. Rajagiri Management Journal, 15(1), 39–52. https://doi.org/10.1108/ramj-07-2020-0038
  20. EIA. (2023). Electricity consumption in the United States was about 4 trillion kilowatthours (kWh) in 2022. Retrieved from https://www.eia.gov/energyexplained/electricity/use-of-electricity.php
  21. Enerdata. (2022). Indonesia Energy Information. Retrieved from https://www.enerdata.net/estore/energy-market/indonesia/
  22. Enerdata. (2023). Germany Energy Information. Retrieved from https://www.enerdata.net/estore/energy-market/germany/
  23. Finlay, K. A., Trafimow, D., & Moroi, E. (1999). The importance of subjective norms on intentions to perform health behaviors. Journal of Applied Social Psychology, 29(11), 2381–2393. https://doi.org/10.1111/j.1559-1816.1999.tb00116.x
  24. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, Massachusetts: Addison-Wesley Publishing Company.
  25. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi/abs/10.1177/002224378101800104
  26. Gayatri, G., Alversia, Y., & Astuti, R. D. (2021). The influence of attitude and subjective norms on student’s (future) intention and future decision of higher level studies: A case study of five universities with BHMN status in Indonesia. ASEAN Marketing Journal, 2(1), 4. https://doi.org/10.21002/amj.v2i1.1991
  27. Hair, Hult, Ringle, & Sarstedt. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), second edition. California, USA: SAGE Publications, Inc.
  28. Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
  29. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  30. Hair, J., Hair Jr, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2023). Advanced Issues in Partial Least Squares Structural Equation Modeling, second edition. USA: SAGE Publications, Inc.
  31. Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3(February), 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
  32. Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  33. Hesselink, L. X. W., & Chappin, E. J. L. (2019). Adoption of energy efficient technologies by households – Barriers, policies and agent-based modelling studies. Renewable and Sustainable Energy Reviews, 99(March 2018), 29–41. https://doi.org/10.1016/j.rser.2018.09.031
  34. Hossain, I., Fekete-Farkas, M., & Nekmahmud, M. (2022). Purchase behavior of energy-efficient appliances contribute to sustainable energy consumption in developing country: Moral norms extension of the theory of planned behavior. Energies, 15(13), 4600. https://doi.org/10.3390/en15134600
  35. Hua, L., & Wang, S. (2019). Antecedents of consumers’ intention to purchase energy-efficient appliances: An empirical study based on the technology acceptance model and theory of planned behavior. Sustainability (Switzerland), 11(10), 2994. https://doi.org/10.3390/su11102994
  36. Ivancevich, J. ., Konopaske, R., & Matteson, M. (2008). Organizational Behavior and Management, 10th edition. United Kingdom: Irwin, McGraw-Hill Education.
  37. JinRu, L., & Qamruzzaman, M. (2022). Nexus between environmental innovation, energy efficiency, and environmental sustainability in G7: What is the role of institutional quality? Frontiers in Environmental Science, 10(May), 1–21, 860244. https://doi.org/10.3389/fenvs.2022.860244
  38. Kang, H. (2021). Sample size determination and power analysis using the G*Power software. Journal of Educational Evaluation for Health Professions, 18, 1–12. https://doi.org/10.3352/JEEHP.2021.18.17
  39. Karunarathna, W. K. S., Jayaratne, W., Dasanayaka, S., Ibrahim, S., & Samara, F. (2023). Factors affecting household’s use of energy-saving appliances in Sri Lanka: An empirical study using a conceptualized technology acceptance model. Energy Efficiency, 16(3), 15. https://doi.org/10.1007/s12053-023-10096-7
  40. Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of E-Collaboration, 11(4), 1–10. https://doi.org/10.4018/ijec.2015100101
  41. Kreiterling, C. (2023). Digital innovation and entrepreneurship: A review of challenges in competitive markets. Journal of Innovation and Entrepreneurship, 12(1), 49. https://doi.org/10.1186/s13731-023-00320-0
  42. Li, S., Meng, J., Zheng, H., Zhang, N., Huo, J., Li, Y., & Guan, D. (2021a). The driving forces behind the change in energy consumption in developing countries. Environmental Research Letters, 16(5), 054002. https://doi.org/10.1088/1748-9326/abde05
  43. Li, Y., Siddik, A. B., Masukujjaman, M., & Wei, X. (2021b). Bridging green gaps: The buying intention of energy efficient home appliances and moderation of green self-identity. Applied Sciences (Switzerland), 11(21), 9878. https://doi.org/10.3390/app11219878
  44. Lin, C. C., & Dong, C. M. (2023). Exploring consumers’ purchase intention on energy-efficient home appliances: Integrating the theory of planned behavior, perceived value theory, and environmental awareness. Energies, 16(6), 2669. https://doi.org/10.3390/en16062669
  45. Liu, X., Liu, X., Luo, X., Wang, M., Fu, H., Wang, B., Sun, Y., & Hu, W. (2020a). Analysis on the influencing mechanism of informational policy instrument on adopting energy consumption monitoring technology in public buildings. Energy Efficiency, 13(7), 1485–1503. https://doi.org/10.1007/s12053-020-09895-z
  46. Liu, X., Wang, Q., Wei, H. H., Chi, H. L., Ma, Y., & Jian, I. Y. (2020b). Psychological and demographic factors affecting household energy-saving intentions: A TPB-based study in northwest China. Sustainability (Switzerland), 12(3), 1–20. https://doi.org/10.3390/su12030836
  47. Luthfiana, D. N., Andika, A., & Bidayati, U. (2024). Unraveling the complexity of the organic food market : Indonesian consumer perspective on price and product knowledge. Asian Management and Business Review, 4(1), 73–89. https://doi.org/https://doi.org/10.20885/AMBR.vol4.iss1.art5
  48. Muzayanah, I. F. U., Lean, H. H., Hartono, D., Indraswari, K. D., & Partama, R. (2022). Population density and energy consumption: A study in Indonesian provinces. Heliyon, 8(9), e10634. https://doi.org/10.1016/j.heliyon.2022.e10634
  49. Nadel, S., & Ungar, L. (2019). Halfway There: Energy Efficiency Can Cut Energy Use and Greenhouse Gas Emissions in Half by 2050. Report U1907 American Council for an Energy-Efficient Economy. Washington DC: ACEEE.
  50. Nejat, P., Jomehzadeh, F., Taheri, M. M., Gohari, M., & Muhd, M. Z. (2015). A global review of energy consumption, CO2 emissions and policy in the residential sector (With an overview of the top ten CO2 emitting countries). Renewable and Sustainable Energy Reviews, 43, 843–862. https://doi.org/10.1016/j.rser.2014.11.066
  51. Osobajo, O. A., Otitoju, A., Otitoju, M. A., & Oke, A. (2020). The impact of energy consumption and economic growth on carbon dioxide emissions. Sustainability (Switzerland), 12(19), 1–16. https://doi.org/10.3390/SU12197965
  52. Paneru, C. P., & Tarigan, A. K. M. (2023). Reviewing the impacts of smart energy applications on energy behaviours in Norwegian households. Renewable and Sustainable Energy Reviews, 183(June), 113511. https://doi.org/10.1016/j.rser.2023.113511
  53. Pernice, G. F. A., Orso, V., & Gamberini, L. (2023). Is this right for you?: The key role of shop assistants in promoting energy-efficient household appliances. Sustainability, 15(24), 16630. https://doi.org/10.3390/su152416630
  54. Pham, L. T. T., & Nguyen, Y. T. H. (2023). An integrated framework approach to understanding Vietnamese people’s intention to adopt smart home solutions. Human Behavior and Emerging Technologies, 2023(1), 8882543. https://doi.org/10.1155/2023/8882543
  55. Qalati, S. A., Qureshi, N. A., Ostic, D., & Sulaiman, M. A. B. A. (2022). An extension of the theory of planned behavior to understand factors influencing Pakistani households’ energy-saving intentions and behavior: A mediated–moderated model. Energy Efficiency, 15(6), 1–21. https://doi.org/10.1007/s12053-022-10050-z
  56. Ringle, C. M., Sarstedt, M., Sinkovics, N., & Sinkovics, R. R. (2023). A perspective on using partial least squares structural equation modelling in data articles. Data in Brief, 48, 109074. https://doi.org/10.1016/j.dib.2023.109074
  57. Rizzi, F., Annunziata, E., Contini, M., & Frey, M. (2020). On the effect of exposure to information and self-benefit appeals on consumer’s intention to perform pro-environmental behaviours: A focus on energy conservation behaviours. Journal of Cleaner Production, 270, 122039. https://doi.org/10.1016/j.jclepro.2020.122039
  58. Shah, R., Modi, A., Muduli, A., & Patel, J. D. (2023). Purchase intention for energy-efficient equipment appliances: Extending TPB with eco-labels, green trust, and environmental concern. Energy Efficiency, 16(4), 31. https://doi.org/10.1007/s12053-023-10111-x
  59. Shin, J., Park, Y., & Lee, D. (2018). Who will be smart home users? An analysis of adoption and diffusion of smart homes. Technological Forecasting and Social Change, 134(January), 246–253. https://doi.org/10.1016/j.techfore.2018.06.029
  60. Si-dai, G., Cheng-Peng, L., Hang, L., & Ning, Z. (2021). Influence mechanism of energy efficiency label on consumers’ purchasing behavior of energy-saving household appliances. Frontiers in Psychology, 12(October), 1–15. https://doi.org/10.3389/fpsyg.2021.711854
  61. Singh, V. K., Henriques, C. O., & Martins, A. G. (2019). Assessment of energy-efficient appliances: A review of the technologies and policies in India’s residential sector. Wiley Interdisciplinary Reviews: Energy and Environment, 8(3), 1–19. https://doi.org/10.1002/wene.330
  62. Tang, Z., & Chen, L. (2023). Measurement and analysis of direct and indirect household energy consumption: A case study of China. Frontiers in Energy Research, 11(July), 1–13. https://doi.org/10.3389/fenrg.2023.1220207
  63. Tang, Z., Warkentin, M., & Wu, L. (2019). Understanding employees’ energy saving behavior from the perspective of stimulus-organism-responses. Resources, Conservation and Recycling, 140(September 2018), 216–223. https://doi.org/10.1016/j.resconrec.2018.09.030
  64. Thanh, N. D. (2023). The impact of media publicity and online product reviews on consumers’ purchase intentions of energy-efficient appliances. VNU University of Economics and Business, 3(6), 77. https://doi.org/10.57110/vnujeb.v3i6.232
  65. Wang, Q., Niu, G., Gan, X., & Cai, Q. (2022). Green returns to education: Does education affect pro-environmental attitudes and behaviors in China? PLoS ONE, 17(2 February), 1–20. https://doi.org/10.1371/journal.pone.0263383
  66. Wang, Z., Sun, Q., Wang, B., & Zhang, B. (2019). Purchasing intentions of Chinese consumers on energy-efficient appliances: Is the energy efficiency label effective? Journal of Cleaner Production, 238, 117896. https://doi.org/10.1016/j.jclepro.2019.117896
  67. Wang, Z., Zhang, B., & Li, G. (2014). Determinants of energy-saving behavioral intention among residents in Beijing: Extending the theory of planned behavior. Journal of Renewable and Sustainable Energy, 6(5), 1–18. https://doi.org/10.1063/1.4898363
  68. Waris, I., Dad, M., & Hameed, I. (2021). Promoting environmental sustainability: The influence of knowledge of eco-labels and altruism in the purchase of energy-efficient appliances. Management of Environmental Quality: An International Journal, 32(5), 989–1006. https://doi.org/10.1108/MEQ-11-2020-0272
  69. Waris, I., & Hameed, I. (2021). An empirical study of consumers intention to purchase energy efficient appliances. Social Responsibility Journal, 17(4), 489–507. https://doi.org/10.1108/SRJ-11-2019-0378
  70. Wibowo, A. H. (2023). Persebaran Konsumsi Listrik di Berbagai Pulau Indonesia. Retrieved from https://data.goodstats.id/statistic/wibowoadnanhasyim/persebaran-konsumsi-listrik-di-berbagai-pulau-indonesia-qlAfd
  71. Xin, D., Zhi Sheng, Z., & Jiahui, S. (2022). How technological innovation influences environmental pollution: Evidence from China. Complexity, 2022, 2022(1), 5535310. https://doi.org/10.1155/2022/5535310
  72. Yang, X., Chen, L., Wei, L., & Su, Q. (2020). Personal and media factors related to citizens’ pro-environmental behavioral intention against haze in China: A moderating analysis of TPB. International Journal of Environmental Research and Public Health, 17(7), 2314. https://doi.org/10.3390/ijerph17072314
  73. Zaato, S. G., Zainol, N. R., Khan, S., Rehman, A. U., Faridi, M. R., & Khan, A. A. (2023). The mediating role of customer satisfaction between antecedent factors and brand loyalty for the Shopee application. Behavioral Sciences, 13(7), 1–22. https://doi.org/10.3390/bs13070563
  74. Zahra, F., & Astuti, Y. (2023). Government policy effect toward energy-efficient appliances purchase intention in West Java. Journal of Humanities and Social Studies (JHSS), 07(02), 343–347. https://doi.org/10.33751/jhss.v7i2.7940
  75. Zainudin, N., Lau, J. L., & Munusami, C. (2022). Modelling household behavioural changes as an opportunity for sustainable home energy. Environmental Economics and Policy Studies, 24(1), 73–97. https://doi.org/10.1007/s10018-021-00311-z
  76. Zhang, H., Gladisch, A., Pickavet, M., Tao, Z., & Mohr, W. (2010). Energy efficiency in communications. IEEE Communications Magazine, 48(11), 48–49. https://doi.org/10.1109/MCOM.2010.5621966
  77. Zhang, J., Ma, L., & Li, J. (2021). Why low-carbon publicity effect limits? The role of heterogeneous intention in reducing household energy consumption. Energies, 14(22), 7634. https://doi.org/10.3390/en14227634
  78. Zhang, W., & Liu, L. (2022). Unearthing consumers’ intention to adopt eco-friendly smart home services: An extended version of the theory of planned behavior model. Journal of Environmental Planning and Management, 65(2), 216–239. https://doi.org/10.1080/09640568.2021.1880379
  79. Zhang, W., & Luo, B. (2023). Predicting consumer intention toward eco-friendly smart home services: Extending the theory of planned behavior. Economic Change and Restructuring, 56(5), 3335–3352. https://doi.org/10.1007/s10644-022-09477-2
  80. Zhang, X., Cheng, X., & Huang, X. (2023). “Oh, my God, buy it!” Investigating impulse buying behavior in live streaming commerce. International Journal of Human-Computer Interaction, 39(12), 2436–2449. https://doi.org/10.1080/10447318.2022.2076773
  81. Zhang, Y., Xiao, C., & Zhou, G. (2020). Willingness to pay a price premium for energy-saving appliances: Role of perceived value and energy efficiency labeling. Journal of Cleaner Production, 242, 118555. https://doi.org/https://doi.org/10.1016/j.jclepro.2019.118555
  82. Zhao, C., Zhang, M., & Wang, W. (2019). Exploring the influence of severe haze pollution on residents’ intention to purchase energy-saving appliances. Journal of Cleaner Production, 212, 1536–1543. https://doi.org/10.1016/j.jclepro.2018.12.134
  83. Zheng, S. Y., Liu, H., Guan, W., Yang, Y., Li, J. Y., Fahad, S., & Li, B. (2022). Identifying intention-based factors influencing consumers’ willingness to pay for electric vehicles: A sustainable consumption paradigm. Sustainability (Switzerland), 14(24). https://doi.org/10.3390/su142416831.