Leveraging green perceptions and transparency to improve green performance in furniture supply chains: an experimental design for ChatGPT and manual online customer service

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Authors: Jun Shi, Shan Xie, Fashen Huang, Kanchana Sethanan, Ming‐Lang Tseng, Kuo‐Jui Wu
Cited by: 0
References: 61

Abstract

Leveraging green perceptions and transparency requires positive messaging through online customer service, as shown by previous studies. Although green furniture firms are trying to incorporate ChatGPT into their existing online customer service, its impact on green performance has yet to be explored. Therefore, this research uses an experimental design based on signalling theory to identify the mechanisms involved in the generation, transmission, and perception of signals. This experiment will guide how ChatGPT should be implemented. The results reveal significant differences between ChatGPT and manual online customer service. Green transparency has a significant impact on green performance across the furniture supply chain when ChatGPT is utilised. Proper training is crucial before integrating ChatGPT into online customer service. Without sufficient training, ChatGPT may struggle to address customer needs effectively. Skilled manual staff are necessary to guide the successful incorporation of ChatGPT into the furniture industry's online services.

Fields of Study & Subjects

Sustainable Supply Chain Management Environmental Sustainability in Business AI in Service Interactions

Publication details

Journal / source
International Journal of Logistics Research and Applications
Pages
1–18
Publication date
15 January 2026
Language
EN