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Green Information Technology Adoption Antecedence: A Conceptual Framework

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Emerging Trends in Intelligent Computing and Informatics (IRICT 2019)

Abstract

Green Information Technology (Green IT) has been adopted in developed countries, as a strategic initiative consideration for developing sustainable business practices, through the balancing economic and environmental performance of an organization. However, there is still a low adoption in developing countries like Malaysia, and limited empirical research on the Green IT adoption, despite it being a necessity even though numerous government incentives were provided to adopt the green IT in Malaysia. The aims of this research are to develop a conceptual framework to determine the relationship between learning capability, innovation capability, emotional capability, and government incentives as drivers toward green IT Adoption. In order to develop the green IT adoption’s antecedents’ relationships in Malaysia, this research will rely on some technology adoption theories such as Technology-organization-environment (TOE), Resource-based theory (RBT), Institutional theory (IT). Based on previous literature, there is a relationship among green IT adoption with organization capabilities, and government incentives, but in a scattered manner. Furthermore, this study has provided integrated framework for researchers and business homes, it showed that internal and external factors play major role in green IT adoption within organizations, So, they can start their green initiatives to cope with requirements in a new industrial revolution 4.0. Also, economic and environment sustainability should be considered as consequences factors in future researches.

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Abu Al-Rejal, H.M.E., Udin, Z.M., Hassan, M.G., Sharif, K.I.M., Al-Rahmi, W.M., Al-kumaim, N.H. (2020). Green Information Technology Adoption Antecedence: A Conceptual Framework. In: Saeed, F., Mohammed, F., Gazem, N. (eds) Emerging Trends in Intelligent Computing and Informatics. IRICT 2019. Advances in Intelligent Systems and Computing, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-33582-3_103

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