The service trade with AI and energy efficiency: Multiplier effect of the digital economy in a green city by using quantum computation based on QUBO modeling

Da Huo, Wenjia Gu, Dongmei Guo and Aidi Tang

Energy Economics, 2024, vol. 140, issue C

Abstract: This research examines the energy efficiency of city districts through the Malmquist–DEA model and investigates the spatial effects of the service trade and the digital economy on energy efficiency in urban green development. The study also delves into the specific context of the AI service trade to gain insights into and align with the emerging digital intelligence industry. The interplay of the service trade with the digital economy, alongside the AI service trade with innovation, significantly enhances urban energy efficiency and demonstrates positive externalities. Building on the empirical findings, this research employs cluster analysis to explore the green development of city districts and uses AI technology to program green communication and cooperation mechanisms across district clusters, employing quantum computation based on QUBO modeling. This study contributes to a deeper understanding of the cofunction of the service trade and the digital economy in terms of energy efficiency and aids in developing new quality productivities for green cities through quantum-based AI advancements. This research has clear implications for cutting-edge interdisciplinary applications of green AI technologies in social computing science.

Keywords: Service trade with AI; Energy efficiency; Digital economy; Green city; Quantum computation (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:140:y:2024:i:c:s0140988324006844

DOI: 10.1016/j.eneco.2024.107976

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