Research on data transaction compliance: A collaborative and co-governance approach considering buyer erroneous feedback
Fanghao Xiao, Xinqing Sun, Junxin Shen, Wenxia Yi
TL;DR
This paper proposes a collaborative governance model to improve data transaction compliance by integrating platform audits, government oversight, and buyer feedback.
Contribution
The novel contribution is a collaborative governance model using evolutionary game theory to address compliance risks in data transactions.
Findings
Accurate buyer feedback promotes compliance and reduces regulatory burdens.
Reputation effects enhance seller behavior but have an inverted U-shaped relationship with government enthusiasm.
Balanced subsidies and punishments are needed to avoid free-riding behaviors.
Abstract
Data transactions are frequently hindered by compliance risks due to participants’ lack of self-regulation and the presence weak regulatory mechanism. To address seller’s non-compliant transaction issues, this study proposes a collaborative governance model that integrates platform audits, government oversight, and buyer supervision. This model considers the heterogeneity of buyer utility and applies evolutionary game theory in a noisy feedback environment. The results indicate that accurate buyer feedback can promote compliance and reduce the supervisory burdens on platforms and governments. The reputation effect can enhance the positive behavior of sellers and platforms but has an “inverted U-shaped” relationship with government regulatory enthusiasm. The government’s subsidy and accountability should avoid a “heavy subsidy and light accountability “and the platform’s reward and…
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Taxonomy
TopicsPrivacy, Security, and Data Protection · Digital Platforms and Economics · Blockchain Technology Applications and Security