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Beyond technology acceptance: Development and evaluation of technology-environmental, economic, and social sustainability theory

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  • Al-Emran, Mostafa

Abstract

Cutting-edge technologies play a pivotal role in achieving the three pillars of sustainable development: environment, economy, and society. These technologies might have positive or negative impacts on sustainable development. While IS theories, such as TAM, UTAUT, and UTAUT2, have provided invaluable insights into the determinants of technology adoption and use, they overlooked the subsequent impacts of technology use. From the sustainability perspective, this necessitates a holistic theoretical framework that goes beyond existing IS theories/models by examining the direct effect of technology use on environmental, economic, and social sustainability. Therefore, we developed the Technology-Environmental, Economic, and Social Sustainability Theory (T-EESST) in this research. T-EESST extends beyond existing IS theories by linking technology use to the three dimensions of sustainability. Due to its inclusivity of all facets of sustainability, the Metaverse is selected as a case study to evaluate the T-EESST. The data collected from a survey of 311 Metaverse users provided empirical support for T-EESST. The results showed that technology use significantly impacts environmental, economic, and social sustainability. The T-EESST contributes significantly to the IS and sustainability literature by bridging the gap between technology acceptance models and sustainability. The study offers practical implications for policymakers, decision-makers, developers, designers, service providers, and practitioners. It also provides numerous research directions as a road map for future extensions to T-EESST.

Suggested Citation

  • Al-Emran, Mostafa, 2023. "Beyond technology acceptance: Development and evaluation of technology-environmental, economic, and social sustainability theory," Technology in Society, Elsevier, vol. 75(C).
    • Handle: RePEc:eee:teinso:v:75:y:2023:i:c:s0160791x23001884
    DOI: 10.1016/j.techsoc.2023.102383
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    References listed on IDEAS

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    Cited by:

    1. Undheim, Trond Arne, 2024. "In search of better methods for the longitudinal assessment of tech-derived X-risks: How five leading scenario planning efforts can help," Technology in Society, Elsevier, vol. 77(C).
    2. Jin, Keyan & Zhong, Ziqi & Zhao, Elena Yifei, 2024. "Sustainable digital marketing under big data: an AI random forest model approach," LSE Research Online Documents on Economics 121402, London School of Economics and Political Science, LSE Library.
    3. Islam, Md. Monirul & Shahbaz, Muhammad & Ahmed, Faroque, 2024. "Robot race in geopolitically risky environment: Exploring the Nexus between AI-powered tech industrial outputs and energy consumption in Singapore," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Al-Emran, Mostafa & Deveci, Muhammet, 2024. "Unlocking the potential of cybersecurity behavior in the metaverse: Overview, opportunities, challenges, and future research agendas," Technology in Society, Elsevier, vol. 77(C).
    5. Park, Eunil, 2024. "Examining metaverse game platform adoption: Insights from innovation, behavior, and coolness," Technology in Society, Elsevier, vol. 77(C).

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