English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
 
 
DownloadE-Mail
  Open Data in the Digital Economy: An Evolutionary Game Theory Perspective

Li, Q., Pi, B., Feng, M., Kurths, J. (2023 online): Open Data in the Digital Economy: An Evolutionary Game Theory Perspective. - IEEE Transactions on Computational Social Systems.
https://doi.org/10.1109/TCSS.2023.3324087

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Li, Quin1, Author
Pi, Bin1, Author
Feng, Minyu1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 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.

Details

show
hide
Language(s): eng - English
 Dates: 2023-10-20
 Publication Status: Published online
 Pages: 12
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1109/TCSS.2023.3324087
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Game Theory
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: IEEE Transactions on Computational Social Systems
Source Genre: Journal, SCI, Scopus
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/2329-924X
Publisher: Institute of Electrical and Electronics Engineers (IEEE)