Trust Anchors in the Sharing Economy: A Study on Trust and Usage Intention in Shijiazhuang’s AI-Era Sharing Economy

Qiuxiang Tu; Changzhou Dong; Shiyu Guo; Sijing Liu; Ying Li

doi:10.54097/zh0bbe08

Authors

Qiuxiang Tu
Changzhou Dong
Shiyu Guo
Sijing Liu
Ying Li

DOI:

https://doi.org/10.54097/zh0bbe08

Keywords:

Sharing Economy, Trust Anchors, Dynamic Pricing, Regulatory Sandbox, Cluster Analysis

Abstract

This study investigates trust anchors in China's sharing economy, with a focus on Shijiazhuang as a representative second-tier city during the AI era. Utilizing mixed-methods research (PPS sampling of 985 participants, SEM, and LPA/K-means clustering), we quantify drivers of trust and usage intention. Key findings reveal that trust mediates 58% of usage intention (β=1.059***), with price transparency (β=0.81) and privacy protection (β=0.804) as dominant factors. Latent profile analysis identifies three user segments: high-trust adopters (32%, tech professionals motivated by ESG values), price-sensitive pragmatists (45%, county residents prioritizing cost-effectiveness), and risk-averse avoiders (23%, seniors with low digital literacy). To address trust deficits (mean=3.64/5), we propose a tripartite "Trust-Value-Behavior" framework integrating: 1. Blockchain-IoT solutions for real-time resource tracking and transparency enhancement; 2. Dynamic pricing strategies optimized through AI algorithms to segment users and boost engagement; 3. Cross-platform carbon credit incentives modeled on credit card points systems to reward high-trust behaviors. Policy implications advocate for regulatory sandboxes to test adaptive rules in fintech and mobility sectors, alongside government-platform co-guarantees for risk-averse groups. This research advances theoretical understanding of Confucian relational trust in digital platforms while offering scalable operational models for regional sharing economies.

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