User Acceptance Model for Smart Incentives in Sustainable Video Streaming towards 6G

Abstract

The rapid growth of 5G video streaming is intensifying energy consumption across access, core, and data-center networks, underscoring the critical need for energy and carbon-efficient solutions. While reducing streaming bitrates improves energy efficiency, its success hinges on user acceptance--particularly when lower bitrates may be perceived as reduced quality of experience (QoE). Therefore, there is a need to develop transparent, user-centric incentive models that balance sustainability with perceived value. We propose a user-acceptance model that combines diverse environmental awareness, personalized responsiveness to incentives, and varying levels of altruism into a unified probabilistic framework. The model incorporates dynamic, individualized incentives that adapt over time. We further enhance the framework by incorporating (i) social well-being as a motivator for altruistic choices, (ii) provider-driven education strategies that gradually adjust user acceptance thresholds, and (iii) data-driven learning of user traits from historical offer--response interactions. Extensive synthetic-data experiments reveal the trade-offs between provider cost and network flexibility, showing that personalized incentives and gradual behavioral adaptation can advance sustainability targets without compromising stakeholder requirements.