Open Data in the Digital Economy: An Evolutionary Game Theory Perspective

2024-06-01

IEEE Transactions on Computational Social Systems

AI Summary

Existing research on open data–driven sustainable development overlooks the critical role of data intermediaries—particularly regulatory entities—in governing data ecosystems. Method: This study constructs a tripartite evolutionary game model integrating data providers, users, and regulators—the first systematic incorporation of regulators into open data literature—to characterize multi-stakeholder co-evolutionary dynamics. It employs replicator dynamics analysis, numerical simulation, and sensitivity testing to examine nonlinear interactions among regulatory incentives, user costs, and data value. Contribution/Results: The analysis identifies multiple evolutionarily stable strategies (ESS) and quantifies threshold effects: regulatory reward-penalty intensity and users’ data mining capability exhibit nonlinear, bifurcation-like impacts on cooperation rates. Findings provide empirically grounded theoretical foundations for designing incentive-compatible platform mechanisms and evidence-based data governance policies to advance sustainable development through open data.

Technology Category

• Game Theory and Economic Paradigms: Cooperative Game Theory
• Multiagent Systems: Mechanism Design
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Open data, as an essential element in the sustainable development of the digital economy, is highly valued by many relevant sectors in the implementation process. However, most studies suppose that there are only data providers and users in the open data process and ignore the existence of data regulators. In order to establish long-term green supply relationships between multistakeholders, we hereby introduce data regulators and propose an evolutionary game model to observe the cooperation tendency of multistakeholders (data providers, users, and regulators). The newly proposed game model enables us to intensively study the trading behavior which can be realized as strategies and payoff functions of the data providers, users, and regulators. Besides, a replicator dynamic system is built to study evolutionary stable strategies of multistakeholders. In simulations, we investigate the evolution of the cooperation ratio as time progresses under different parameters, which is proved to be in agreement with our theoretical analysis. Furthermore, we explore the influence of the cost of data users to acquire data, the value of open data, the reward (penalty) from the regulators, and the data mining capability of data users to group strategies and uncover some regular patterns. Some meaningful results are also obtained through simulations, which can guide stakeholders to make better decisions in the future.

Problem

• Develops evolutionary game model
• Analyzes multi-stakeholder cooperation
• Explores open data dynamics

Innovation

• Introduces evolutionary game theory
• Includes data regulators model
• Analyzes multi-stakeholder cooperation dynamics