1,671
Views
3
CrossRef citations to date
0
Altmetric
Research Articles

The Impact of Sustainable Technologies in the Perceived Well-being: The Role of Intrinsic Motivations

, &
Pages 3873-3884 | Received 14 Dec 2022, Accepted 10 Apr 2023, Published online: 24 Apr 2023

References

  • Abu Bakar, A. A., Osman, M. M., Bachok, S., Ibrahim, M., & Mohamed, M. Z. (2015). Modelling economic wellbeing and social wellbeing for sustainability: A theoretical concept. Procedia Environmental Sciences, 28(2014), 286–296. https://doi.org/10.1016/j.proenv.2015.07.037
  • Administration, I. T. (2021). Greece – Energy. Retrieved from https://www.trade.gov/country-commercial-guides/greece-energy
  • Adu-Gyamfi, G., Song, H., Nketiah, E., Obuobi, B., Adjei, M., & Cudjoe, D. (2022). Determinants of adoption intention of battery swap technology for electric vehicles. Energy, 251, 123862. https://doi.org/10.1016/j.energy.2022.123862
  • Awan, A., Sadiq, M., Hassan, S. T., Khan, I., & Khan, N. H. (2022). Combined nonlinear effects of urbanization and economic growth on CO2 emissions in Malaysia. An application of QARDL and KRLS. Urban Climate, 46, 101342. https://doi.org/10.1016/j.uclim.2022.101342
  • Azam, W., Khan, I., & Ali, S. A. (2023). Alternative energy and natural resources in determining environmental sustainability: A look at the role of government final consumption expenditures in France. Environmental Science and Pollution Research International, 30(1), 1949–1965. https://doi.org/10.1007/s11356-022-22334-z
  • Barreto, M. L., Szóstek, A., Karapanos, E., Nunes, N. J., Pereira, L., & Quintal, F. (2014). Understanding families’ motivations for sustainable behaviors. Computers in Human Behavior, 40, 6–15. https://doi.org/10.1016/j.chb.2014.07.042
  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351. https://doi.org/10.2307/3250921
  • Brod, M., Tesler, L. E., & Christensen, T. L. (2009). Qualitative research and content validity: Developing best practices based on science and experience. Quality of Life Research, 18(9), 1263–1278. https://doi.org/10.1007/s11136-009-9540-9
  • Butler, T. (2011). Compliance with institutional imperatives on environmental sustainability: Building theory on the role of Green IS. The Journal of Strategic Information Systems, 20(1), 6–26. https://doi.org/10.1016/j.jsis.2010.09.006
  • Capstick, S., Nash, N., Whitmarsh, L., Poortinga, W., Haggar, P., & Brügger, A. (2022). The connection between subjective wellbeing and pro-environmental behaviour: Individual and cross-national characteristics in a seven-country study. Environmental Science & Policy, 133(February), 63–73. https://doi.org/10.1016/j.envsci.2022.02.025
  • Cha, E. S., Kim, K. H., & Erlen, J. A. (2007). Translation of scales in cross-cultural research: Issues and techniques. Journal of Advanced Nursing, 58(4), 386–395. https://doi.org/10.1111/j.1365-2648.2007.04242.x
  • Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii–xvi.
  • Çop, S., Alola, U. V., & Alola, A. A. (2020). Perceived behavioral control as a mediator of hotels’ green training, environmental commitment, and organizational citizenship behavior: A sustainable environmental practice. Business Strategy and the Environment, 29(8), 3495–3508. https://doi.org/10.1002/bse.2592
  • Çop, S., Olorunsola, V. O., & Alola, U. V. (2021). Achieving environmental sustainability through green transformational leadership policy: Can green team resilience help? Business Strategy and the Environment, 30(1), 671–682. https://doi.org/10.1002/bse.2646
  • Crosno, J. L., & Cui, A. P. (2014). A multilevel analysis of the adoption of sustainable technology. Journal of Marketing Theory and Practice, 22(2), 209–224. https://doi.org/10.2753/MTP1069-6679220213
  • Dadzie, J., Runeson, G., Ding, G., & Bondinuba, F. K. (2018). Barriers to adoption of sustainable technologies for energy-efficient building upgrade-Semi-structured interviews. Buildings, 8(4), 57. https://doi.org/10.3390/buildings8040057
  • Davis, L. W. (2011). Evaluating the slow adoption of energy efficient investments: Are renters less likely to have energy efficient appliances? In D. Fullerton & C. Wolfram (Eds.), The design and implementation of US climate policThe design and implementation of US climate policy (pp. 301–316). University of Chicago Press.
  • Deci, E. L., & Ryan, R. M. (2002). Handbook of self-determination research. Retrieved from https://psycnet.apa.org/record/2002-01702-000
  • Dysvik, A., & Kuvaas, B. (2011). Intrinsic motivation as a moderator on the relationship between perceived job autonomy and work performance. European Journal of Work and Organizational Psychology, 20(3), 367–387. https://doi.org/10.1080/13594321003590630
  • El Hedhli, K., Chebat, J. C., & Sirgy, M. J. (2013). Shopping well-being at the mall: Construct, antecedents, and consequences. Journal of Business Research, 66(7), 856–863. https://doi.org/10.1016/j.jbusres.2011.06.011
  • Erell, E., Portnov, B. A., & Assif, M. (2018). Modifying behaviour to save energy at home is harder than we think…. Energy and Buildings, 179, 384–398. https://doi.org/10.1016/j.enbuild.2018.09.010
  • European Parliament (2019). 2019/944 of the European Parliament and of the Council of 5 June 2019 on common rules for the internal market for electricity and amending Directive 2012/27/EU. Official Journal of the European Union, 62, 125–199. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L:2019:158:TOC
  • Eurostat (2019). Household composition statistics. Eurostat-Statistics Explained. Retrieved from http://ec.europa.eu/eurostat/statistics-explained/index.php/Household_composition_statistics
  • Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440–452. https://doi.org/10.2307/3151718
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
  • Fusch, P. I., & Ness, L. R. (2015). Are we there yet? Data saturation in qualitative research. The Qualitative Report, 20(9), 1408–1416. http://www.nova.edu/ssss/QR/QR20/9/fusch1.pdf
  • Gimpel, H., Graf, V., & Graf-Drasch, V. (2020). A comprehensive model for individuals’ acceptance of smart energy technology – A meta-analysis. Energy Policy, 138, 111196. https://doi.org/10.1016/j.enpol.2019.111196
  • Girod, B., Mayer, S., & Nägele, F. (2017). Economic versus belief-based models: Shedding light on the adoption of novel green technologies. Energy Policy, 101(May 2016), 415–426. https://doi.org/10.1016/j.enpol.2016.09.065
  • Guillen-Royo, M. (2019). Sustainable consumption and wellbeing: Does on-line shopping matter? Journal of Cleaner Production, 229, 1112–1124. https://doi.org/10.1016/j.jclepro.2019.05.061
  • Hair, J., Hult, G. T., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM) (Joseph F. Hair, Jr., G. Tomas, M. Hult, Christian Ringle, & Marko Sarstedt, Eds.). Sage.
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE Publications.
  • 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
  • Jakučionytė-Skodienė, M., Krikštolaitis, R., & Liobikienė, G. (2022). The contribution of changes in climate-friendly behaviour, climate change concern and personal responsibility to household greenhouse gas emissions: Heating/cooling and transport activities in the European Union. Energy, 246, 123387. https://doi.org/10.1016/j.energy.2022.123387
  • Jie, H., Khan, I., Alharthi, M., Zafar, M. W., & Saeed, A. (2023). Sustainable energy policy, socio-economic development, and ecological footprint: The economic significance of natural resources, population growth, and industrial development. Utilities Policy, 81, 101490. https://doi.org/10.1016/j.jup.2023.101490
  • Joo, Y. J., So, H. J., & Kim, N. H. (2018). Examination of relationships among students’ self-determination, technology acceptance, satisfaction, and continuance intention to use K-MOOCs. Computers & Education, 122, 260–272. https://doi.org/10.1016/j.compedu.2018.01.003
  • Kamolsook, A., Badir, Y. F., & Frank, B. (2019). Consumers’ switching to disruptive technology products: The roles of comparative economic value and technology type. Technological Forecasting and Social Change, 140, 328–340. https://doi.org/10.1016/j.techfore.2018.12.023
  • Ke, X., Du, H. S., Wagner, C. (2019). Encouraging individuals to go green by gamification: An empirical Study. In Proceedings of the 23rd Pacific Asia Conference on Information Systems: Secure ICT Platform for the 4th Industrial Revolution, PACIS 2019.
  • Ke, W., Liu, H., Wei, K. K., Gu, J., & Chen, H. (2009). How do mediated and non-mediated power affect electronic supply chain management system adoption? The mediating effects of trust and institutional pressures. Decision Support Systems, 46(4), 839–851. https://doi.org/10.1016/j.dss.2008.11.008
  • Kumareswaran, K., Rajapaksha, I., & Jayasinghe, G. Y. (2021). Energy & Buildings Energy poverty, occupant comfort, and wellbeing in internally displaced people’s residences in Sri Lanka. Energy and Buildings, 236, 110760. https://doi.org/10.1016/j.enbuild.2021.110760
  • Lee, D.-J., Sirgy, M. J., Larsen, V., & Wright, N. D. (2002). Developing a subjective measure of consumer well-Being. Journal of Macromarketing, 22(2), 158–169. https://doi.org/10.1177/0276146702238219
  • Liu, H., Alharthi, M., Atil, A., Zafar, M. W., & Khan, I. (2022). A non-linear analysis of the impacts of natural resources and education on environmental quality: Green energy and its role in the future. Resources Policy, 79, 102940. https://doi.org/10.1016/j.resourpol.2022.102940
  • Liu, H., Khan, I., Zakari, A., & Alharthi, M. (2022). Roles of trilemma in the world energy sector and transition towards sustainable energy: A study of economic growth and the environment. Energy Policy, 170, 113238. https://doi.org/10.1016/j.enpol.2022.113238
  • Marikyan, D., Papagiannidis, S., & Alamanos, E. (2019). A systematic review of the smart home literature: A user perspective. Technological Forecasting and Social Change, 138, 139–154. https://doi.org/10.1016/j.techfore.2018.08.015
  • Mi, L., Zhao, J., Xu, T., Yang, H., Lv, T., Shang, K., Qiao, Y., & Zhang, Z. (2021). How does COVID-19 emergency cognition influence public pro-environmental behavioral intentions? An affective event perspective. Resources, Conservation, and Recycling, 168, 105467. https://doi.org/10.1016/J.RESCONREC.2021.105467
  • Mock, M., Omann, I., Polzin, C., Spekkink, W., Schuler, J., Pandur, V., Brizi, A., & Panno, A. (2019). “Something inside me has been set in motion”: Exploring the psychological wellbeing of people engaged in sustainability initiatives. Ecological Economics, 160(February), 1–11. https://doi.org/10.1016/j.ecolecon.2019.02.002
  • Nasseef, O. A., Baabdullah, A. M., Alalwan, A. A., Lal, B., & Dwivedi, Y. K. (2022). Artificial intelligence-based public healthcare systems: G2G knowledge-based exchange to enhance the decision-making process. Government Information Quarterly, 39(4), 101618. https://doi.org/10.1016/j.giq.2021.101618
  • Nie, P., Li, Q., & Sousa-Poza, A. (2021). Energy poverty and subjective well-being in China: New evidence from the China Family Panel Studies. Energy Economics, 103(August), 105548. https://doi.org/10.1016/j.eneco.2021.105548
  • Ozmen Garibay, O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., Falco, G., Fiore, S. M., Garibay, I., Grieman, K., Havens, J. C., Jirotka, M., Kacorri, H., Karwowski, W., Kider, J., Konstan, J., Koon, S., Lopez-Gonzalez, M., Maifeld-Carucci, I., … Xu, W. (2023). Six human-centered artificial intelligence grand challenges. International Journal of Human–Computer Interaction, 39(3), 391–437. https://doi.org/10.1080/10447318.2022.2153320
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
  • Rasmussen, J. (2017). The additional benefits of energy efficiency investments—A systematic literature review and a framework for categorisation. Energy Efficiency, 10(6), 1401–1418. https://doi.org/10.1007/s12053-017-9528-1
  • Ringle, C. M., Wende, S., Becker, J.-M. (2018). SmartPLS 3. 2015. Website. Retrieved from http://www.smartpls.com
  • Ritchie, H., Roser, M., Rosado, P. (2020). Energy. Our World in Data. Retrieved from https://ourworldindata.org/energy-production-consumption
  • Ryan, R. M., & Deci, E. L. (1985). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being self-determination theory. Ryan.
  • Sangroya, D., & Nayak, J. K. (2017). Factors influencing buying behaviour of green energy consumer. Journal of Cleaner Production, 151, 393–405. https://doi.org/10.1016/j.jclepro.2017.03.010
  • Sarker, S., Chatterjee, S., Xiao, X., & Elbanna, A. (2019). The sociotechnical axis of cohesion for the IS discipline: Its historical legacy and its continued relevance. MIS Quarterly, 43(3), 695–719. https://doi.org/10.25300/MISQ/2019/13747
  • Sequeiros, H., Oliveira, T., & Thomas, M. (2022). The impact of IoT smart home services on psychological well-being. Information Systems Frontiers, 24(3), 1009–1026. https://doi.org/10.1007/s10796-021-10118-8
  • Tauseef Hassan, S., Wang, P., Khan, I., & Zhu, B. (2023). The impact of economic complexity, technology advancements, and nuclear energy consumption on the ecological footprint of the USA: Towards circular economy initiatives. Gondwana Research, 113, 237–246. https://doi.org/10.1016/j.gr.2022.11.001
  • Venkatesh, V., Brown, S. A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS Quarterly, 37(1), 21–54. https://doi.org/10.25300/MISQ/2013/37.1.02
  • Venkatesh, V., Brown, S. A., & Sullivan, Y. W. (2016). Guidelines for conducting mixed-methods research: An extension and illustration. Journal of the Association for Information Systems, 17(7), 435–494. https://doi.org/10.17705/1jais.00433
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly: Management Information Systems, 27(3), 425–478. https://doi.org/10.2307/30036540
  • Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unidied theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
  • Wang, Z., Ali, S., Akbar, A., & Rasool, F. (2020). Determining the influencing factors of biogas technology adoption intention in Pakistan: The moderating role of social media. International Journal of Environmental Research and Public Health, 17(7), 2311. https://doi.org/10.3390/ijerph17072311
  • Wang, X., McGill, T. J., & Klobas, J. E. (2020). I want it anyway: Consumer perceptions of smart home devices. Journal of Computer Information Systems, 60(5), 437–447. https://doi.org/10.1080/08874417.2018.1528486
  • Warkentin, M., Goel, S., & Menard, P. (2017). Shared benefits and information privacy: What determines smart meter technology adoption? Journal of the Association for Information Systems, 18(11), 758–786. https://doi.org/10.17705/1jais.00474
  • Watson, R. T., Boudreau, M. C., & Chen, A. J. (2010). Information systems and environmentally sustainable development: Energy informatics and new directions for the is community. MIS Quarterly: Management Information Systems, 34(1), 23–38. https://doi.org/10.2307/20721413
  • Wunderlich, P. J., Kranz, J. J., Veit, D. J. (2013). Beyond carrot-and-stick: How values and endogenous motivations affect residential green is adoption. In International Conference on Information Systems (ICIS 2013): Reshaping Society through Information Systems Design (pp. Vol. 1, pp. 585–603). Retrieved from https://www.researchgate.net/publication/258909427
  • Wunderlich, P., Veit, D. J., & Sarker, S. (2019). Adoption of sustainable technologies: A mixed-methods study of German households. MIS Quarterly, 43(2), 673–691. https://doi.org/10.25300/MISQ/2019/12112
  • Yang, S., & Zhao, D. (2015). Do subsidies work better in low-income than in high-income families? Survey on domestic energy-efficient and renewable energy equipment purchase in China. Journal of Cleaner Production, 108, 841–851. https://doi.org/10.1016/j.jclepro.2015.07.022
  • Yoon, C. (2018). Extending the TAM for Green IT: A normative perspective. Computers in Human Behavior, 83, 129–139. https://doi.org/10.1016/j.chb.2018.01.032
  • Yoon, J. K., & Kim, C. (2022). Positive emodiversity in everyday human-technology interactions and users’ subjective well-being. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2022.2121564
  • Yoon, S. B., & Cho, E. (2016). Convergence adoption model (CAM) in the context of a smart car service. Computers in Human Behavior, 60, 500–507. https://doi.org/10.1016/j.chb.2016.02.082
  • Zhang, Q., Appau, S., & Lord, P. (2021). Energy poverty, children’s wellbeing and the mediating role of academic performance: Evidence from China. Energy Economics, 97, 105206. https://doi.org/10.1016/j.eneco.2021.105206