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Understanding green IT adoption: TAM and dual-lens of innovation resistance
- Source :
- Cogent Business & Management, Vol 11, Iss 1 (2024)
- Publication Year :
- 2024
- Publisher :
- Taylor & Francis Group, 2024.
-
Abstract
- The escalating environmental impact of IT products in Gulf Cooperation Council (GCC) countries, particularly Saudi Arabia, has prompted the exploration of specific green IT adoption practices, such as the use of energy-efficient computers, renewable energy-powered devices, and electronics with sustainability certifications. However, existing theoretical models often overlook aspects of long-term usage and resistance to technology adoption. To bridge this gap, this study integrates the widely recognized Technology Acceptance Model (TAM) and Innovation Resistance Theory (IRT) to understand the drivers and barriers affecting consumers’ intention to adopt green IT products. Cross-sectional data were collected from 237 consumers using an online survey. Variance-based structural equation modeling (SEM), specifically partial least squares (PLS)-SEM analysis, was employed. The results underscore the importance of perceived ease of use and usefulness as key drivers of adoption intention. Simultaneously, active innovation resistance, encompassing usage, value, and risk factors, and passive innovation resistance, linked to image and traditions, emerged as significant barriers. Increased passive barriers underlined the necessity for particular approaches to overcome them. Using acceptance and resistance theories, this research has improved our knowledge of IT adoption dynamics. This study helps practitioners promote green IT adoption by emphasising user-friendly design and passive resistance. We discuss the study’s limitations and advise additional research.
Details
- Language :
- English
- ISSN :
- 23311975
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Cogent Business & Management
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.6171997fae8f4aaea776347d14f93374
- Document Type :
- article
- Full Text :
- https://doi.org/10.1080/23311975.2024.2403646