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- Title
Behavioural Model for Decision-Makers’ towards the Intention to Adopt Green Information Technology: A Preliminary Study.
- Authors
Buba, Abba Kyari; Ibrahim, Othman
- Abstract
This preliminary survey investigates and validates the measurement model of factors influencing decision makers’ intentions to adopt Green information technology (Green-IT) in manufacturing sectors in Nigeria. The Norm Activation Model (NAM) and Theory of Planned Behaviour (TPB) were used to explore the factors that could influence decisionmakers’ intention in adopting Green-IT. Using constructs from the NAM and TPB, this survey proposes a model for identified behavioural factors. A quantitative research approach with a data collection and analysis plan using a cross-sectional survey design was adopted. A sample of 30 decision-makers in the top three manufacturing industries in Nigeria was selected using a purposive sampling procedure for participation in the study. The data collected was analysed using Partial Least Square Structural Equation Modelling (PLS-SEM) to test the proposed model. The model was validated in two phases: (i) Initial Measurement Model and (ii) Modified Measurement Model. Findings revealed that Green- IT Attitude, Subjective Norm, Ascription of Responsibility, Awareness of Consequences, Personal Norm, Environmental Concern, and Perceive Behavioural Control were the key elements of the behavioural intention model to adopt Green-IT, with 31 indicators having factor loadings of >0.5, adequate internal consistency reliability, CR > 0.7, and Cronbach’s Alpha, >0.7. The result revealed convergent validity, and acceptable discriminant validity was assessed using AVE > 0.5 and Fornell-lacker’s criterion. The results from the full-scale study would contribute to developing a context-specific model to examine Green-IT adoption in developing nations.
- Subjects
NIGERIA; NON-Aligned Movement (Organization); PLANNED behavior theory; GREEN technology; INFORMATION technology; STRUCTURAL equation modeling
- Publication
Pertanika Journal of Science & Technology, 2021, Vol 29, Issue 4, p2409
- ISSN
0128-7680
- Publication type
Article
- DOI
10.47836/pjst.29.4.09