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Proposition: Antecedents like performance expectancy, effort
expectancy, social
Proposition: Antecedents like performance expectancy, effort
expectancy, social influence, and facilitating conditions (as described
by UTAUT) influence the adoption of AI-driven green logistics, which in
turn affects the green advantage of logistics companies
Research Questions
1. Do UTAUT factors indeed affect the adoption of AI-driven green logistics
2. Does AI-driven green logistics affect the green advantage of logistic firms?
3. Does G-readiness moderate the influence of antecedents on adoption?
Conceptual Model:
Outcome variable: Green Advantage
Mediator: Adoption of AI-driven green logistic
Exogenous/Independent variable: Performance expectancy, effort expectancy, social influence, and facilitating conditions
Moderator: G-readiness
Survey with the help of a structured questionnaire
Data collection: From middle to top managers working in Saudi logistics firms through Google Forms-enabled virtual survey.
Data Analysis: PLS-based SEM
Survey with the help of a structured questionnaire has to be submitted to DR for approval within one day “google forum ”
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